Research Techniques Made SimpleArticles 73–84 (2018–2019)

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JOURNAL OF INVESTIGATIVE DERMATOLOGYThe official journal of The Society for Investigative Dermatology and European Society for Dermatological Research

Volume 139 RTMS 73e84 September 2019

EditorMark C. Udey, St. Louis, MO

Principal Deputy EditorThomas Krieg, Cologne, Germany

Deputy EditorsLeena Bruckner-Tuderman, Freiburg, GermanyKilian Eyerich, Munich, GermanyDavid E. Fisher, Boston, MAJoel M. Gelfand, Philadelphia, PAValerie Horsley, New Haven, CTSarah E. Millar, Philadelphia, PATony Oro, Stanford, CAVincent Piguet, Toronto, Canada

Section EditorsMartine Bagot, Paris, FranceIsaac Brownell, Bethesda, MDAn-Wen Chan, Toronto, CanadaKeith A. Choate, New Haven, CTAndrzej Dlugosz, Ann Arbor, MIJames T. Elder, Ann Arbor, MIJanet Fairley, Iowa City, IAJohn E. Harris, Worcester, MADaniel H. Kaplan, Pittsburgh, PAEthan A. Lerner, Boston, MACarien M. Niessen, Cologne, GermanyMartin Roecken, Tubingen, GermanyThomas Schwarz, Kiel, GermanyPhyllis I. Spuls, Amsterdam, The NetherlandsMarjana Tomic-Canic, Miami, FLMiriam Wittmann, Leeds, UK

Statistical EditorChao Xing, Dallas, TX

Reviews EditorsJohann E. Gudjonsson, Ann Arbor, MIDavid P. Kelsell, London, UK

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Editorial Process ManagerSarah Forgeng, Chapel Hill, NC

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Cells to Surgery Quiz ContributorsJeremy Etzkorn, Philadelphia, PAEva Hurst, St. Louis, MORajiv Nijhawan, Dallas, TXKeyvan Nouri, Miami, FL

Meet the Investigator EditorAyman Grada, Boston, MA

Meeting Reports Section EditorJouni Uitto, Philadelphia, PA

Podcast EditorRobert Dellavalle, Denver, CO

Research Techniques Made SimpleJodi Lynn Johnson, Chicago, IL, Coordinating EditorSara J. Brown, Dundee, UK, Contributing EditorLu Q. Le, Dallas, TX, Contributing Editor

SnapshotDx Quiz ContributorsMilan Anadkat, St. Louis, MOBen Chong, Dallas, TXEmily Chu, Philadelphia, PAMariya Miteva, Miami, FL

Editors EmeritiMarion B. Sulzberger, 1938-1949Naomi M. Kanof, 1949-1967Richard B. Stoughton, 1967-1972Irwin M. Freedberg, 1972-1977Ruth K. Freinkel, 1977-1982Howard P. Baden, 1982-1987David A. Norris, 1987-1992Edward J. O’Keefe, 1992-1997Conrad Hauser, 1997-2002Lowell A. Goldsmith, 2002-2007Paul R. Bergstresser, 2007-2012Barbara A. Gilchrest, 2012-2017

Editorial ConsultantsMasayuki Amagai, Tokyo, JapanMaryam Asgari, Boston, MAJurgen Becker, Graz, AustriaMark Berneburg, Tubingen, GermanyTilo Biedermann, Munich, GermanyWendy B. Bollag, Augusta, GAVladimir Botchkarev, Bradford, UKJoke Bouwstra, Leiden, The NetherlandsPaul E. Bowden, Cardiff, UKJulide Celebi, New York, NYAngela M. Christiano, New York, NYCheng-Ming Chuong, Los Angeles, CACristina de Guzman Strong, St. Louis, MOThomas N. Darling, Bethesda, MDJeffrey M. Davidson, Nashville, TNRobert Dellavalle, Denver, COMitchell F. Denning, Chicago, ILRichard L. Eckert, Baltimore, MDTatiana Efimova, Washington, DCAlexander H. Enk, Heidelberg, GermanyGary J. Fisher, Ann Arbor, MIMayumi Fujita, Aurora, CORichard Gallo, San Diego, CASpiro Getsios, Collegeville, PAMichel F. Gilliet, Lausanne, SwitzerlandMatthias Goebeler, Wurzburg, Germany

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athleen J. Green, Chicago, ILichael Hertl, Marburg, Germanylain Hovnanian, Paris, Franceam Hwang, Sacramento, CAivkah Isseroff, Davis, CAndrew Johnston, Ann Arbor, MIenji Kabashima, Kyoto, Japaneli-Matti Kahari, Turku, Finlandatsuyoshi Kawamura, Yamanashi, Japaneinhard Kirnbauer, Vienna, Austriaeidi H. Kong, Bethesda, MDLambert, Ghent, Belgiumlexander G. Marneros, Boston, MAaterina Missero, Napoli, Italyaria Morasso, Bethesda, MDkimichi Morita, Nagoya, Japaneisuke Nagao, Bethesda, MDaul Nghiem, Seattle, WAamar Nijsten, Rotterdam, The Netherlandsanabu Ohyama, Tokyo, Japanmy S. Paller, Chicago, ILndrey A. Panteleyev, Moscow, Russiaarlo Pincelli, Modena, Italyraca Raposo, Paris, Franceennis Roop, Denver, COarbjit S. Saini, Baltimore, MD

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ernanda Sakamoto, Boston, MAelmut Schaider, Brisbane, Australiahristoph Schlapbach, Berne, Switzerlandartin Schmelz, Berne, Switzerlandijayasaradhi Setaluri, Madison, WIhn Seykora, Philadelphia, PAn C. Simon, Leipzig, Germanyli Sprecher, Tel Aviv, Israelobert S. Stern, Boston, MAeorg Stingl, Vienna, Austriaakoto Sugaya, Tokyo, Japanobert Swerlick, Atlanta, GAergey M. Troyanovsky, Chicago, ILensin Tsao, Boston, MArwin Tschachler, Vienna, Austriauni Uitto, Philadelphia, PAaurice van Steensel, Dundee, UKaoxi Wang, Beijing, Chinaicole L. Ward, Cleveland, OHendy Weinberg, Bethesda, MDhomas Werfel, Hannover, Germanyraci Wilgus, Columbus, OHiovanna Zambruno, Rome, Italyuejun Zhang, Heifei, Chinain Zheng, Charlestown, MAetlef Zillikens, Lubeck, Germany

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JOURNAL OF INVESTIGATIVE DERMATOLOGY

Research Techniques Made Simple Articles 73e84 (2018e2019)

EDITORIALS

Putting “Research Techniques Made Simple” Articles to Work for You and for theFuture of Investigative Dermatology JL Johnson

Use of “Research Techniques Made Simple” Series in Translational Topics Training inDermatology at Oregon Health & Science University

S Ophaug and TR Medler

RTMS ARTICLES

Article 73 Research Techniques Made Simple: Animal Models of Wound Healing

A Grada, J Mervis and V Falanga

Article 74 Research Techniques Made Simple: Transepidermal Water Loss Measurement as aResearch Tool

H Alexander, S Brown, S Danby and C Flohr

Article 75 Research Techniques Made Simple: CAR T-Cell Therapy

HF Siddiqi, KW Staser and VE Nambudiri

Article 76 Research Techniques Made Simple: Network Meta-Analysis

J Watt, AC Tricco, S Straus, A Angeliki Veroniki, G Naglie and AM Drucker

Article 77 Research Techniques Made Simple: Itch Measurement in Clinical Trials

S Erickson and BS Kim

Article 78 Research Techniques Made Simple: Interpreting Measures of Association in ClinicalResearch

MR Roberts, S Ashrafzadeh and MM Asgari

Article 79 Research Techniques Made Simple: Profiling the Skin Microbiota

MD Grogan, C Bartow-McKenney, L Flowers, SAB Knight, A Uberoi and EA Grice

Article 80 Research Techniques Made Simple: Mouse Models of Atopic Dermatitis

D Kim, T Kobayashi and K Nagao

Article 81 Research Techniques Made Simple: Parabiosis to Elucidate Humoral Factors in SkinBiology

CA Spencer and TH Leung

Article 82 Research Techniques Made Simple: Using Genetic Variants for Randomization

A Budu-Aggrey and L Paternoster

Article 83 Research Techniques Made Simple: Teledermatology in Clinical Trials

CW Laggis, VL Williams, X Yang and CL Kovarik

Article 84 Research Techniques Made Simple: Forward Genetic Screening to Uncover GenesInvolved in Skin Biology

W McAlpine, J Russell, AR Murray, B Beutler and E Turer

i Answers

xiii Supplementary Information

ª 2019 The Author. Published

EDITORIAL

Putting “Research Techniques MadeSimple” Articles to Work for You and forthe Future of Investigative Dermatology

he Research Techniques Made Simple(RTMS) series of the Journal of Investiga-

T tive Dermatology (JID) was created to be

an educational tool for scientists and clinicianstraining for a lifelong career in Dermatology.Since its inception in the fall of 2012, 84 articleshave been written and published monthly online,in seven volumes of annual reprints, and in eachprint issue of the JID since 2018. RTMS articlescome as a packet that includes the article itself, asupplemental Powerpoint presentation to alloweasy adaptation for journal clubs and teaching,and at-a-glance summary points. For cliniciansneeding to keep up-to-date on the myriad oftechniques driving our field, professional credit forfurthering education can be obtained, becauseeach article comes with an online quiz worth 1Continuing Medical Education Personal Devel-opment Hour (CME PDH).The RTMS series has been designed in part to

help address a knowledge gap identified byUnited States residents surveyed over manyyears, who state that residency training related toresearch techniques is not heavily emphasized,although it is adequate preparation for boardexams. Those surveyed state that expert facultyeffectively lead discussions of primary researcharticles containing scientific principles, butresearch techniques are only sometimes or oc-casionally explained. Relevant RTMS articles areoften available, but they are infrequently used intraining programs or journal clubs in the UnitedStates, according to respondents to 2016 and2019 surveys at the Society for InvestigativeDermatology’s Resident and PhD Career Devel-opment Retreats. It is possible that utilization isimproving. In 2016 over half of survey re-spondents stated they had never read an RTMSarticle, while in 2019 that number had droppedto a third, with more than another third statingthat they use the articles to understand tech-niques used in primary literature or to designexperiments. It seems likely that RTMS articlesare more heavily used outside the Unites States.Individual RTMS articles were downloaded over20,000 times and some have been cited in over100 other articles. Interestingly, selected RTMS

Journal of Investigative Dermatology (2019) 139, 1841e1842.doi:10.1016/j.jid.2019.07.687

by Elsevier, Inc. on behalf of the Society for Investigative Derma

articles are among the most frequently down-loaded articles published in the JID.

The 2019 print edition of the RTMS series in-cludes an editorial (Ophaug and Medler) explain-inghowRTMSarticles have been incorporated intoa Translational Topics in Dermatology forum at theOregon Health and Science University, whichcould be mimicked at any university worldwide.An opportunity for implementation of RTMS arti-cles occurs each month when the latest JID isreleased. Three papers in each issue of the JID arehighlighted and appear online with commentaries.The RTMS editors select one RTMS article to serveas a companion to each highlighted JID article. Forexample, Research Techniques Made Simple: An-imalModels ofWoundHealing (Grada et al., 2018)was recently selected to accompany a commentaryand two articles published on diabetic woundhealing (Barros et al., 2019; Tomic-Canic andDiPietro, 2019; Wilkinson et al., 2019). These fourarticles could easily be used as a foundation for ajournal clubpresentation in any trainingprogram toinclude cutting edge research and make aconcerted effort to understand the research tech-niques underlying the study designs.RTMS articles are freely available to interested

individuals and do not require a subscription tothe JID, so they can be maximally leveraged inonline and didactic learning programs. At-a-glance summary points help distill the mostimportant information, and the CME certificationfor 1 PDH incentivizes clinicians to stay currenton developing research techniques.As you read RTMS articles, use them to help

design your own experiments, and ultimately goon to publish, please remember to cite the RTMSarticle that facilitated your research. If you notice atopic that has not yet been covered, forman authorteam and approach the RTMS editors with anoutline so that your idea can help the field moveforward. One goal of RTMS editors is to anticipatewhere skin-related research is going. We want tobe able to link you, via anRTMSarticle, to themostrelevant primary literature so that your trainingexperience can include a firm foundation ofresearch techniques—made simple. We aim forthe articles to be excellent teaching tools andfirmly believe that broader implementation willhave a positive impact on the rapidly expandingfield of investigative dermatology.

tology. www.jidonline.org 1841

Table 1. Research Techniques Made Simple: Articleson Animal Models in Dermatology

RTMS article title Reference

Transgenic Mouse Technology in Skin Biology:Generation of Complete or Tissue-SpecificKnockout Mice

Scharfenbergeret al. (2014)

Transgenic Mouse Technology in Skin Biology:Inducible Gene Knockout in Mice

Gunschmannet al. (2014)

Transgenic Mouse Technology in Skin Biology:Generation of Knockin Mice

Tellkampet al. (2014)

Lineage Tracing Mediated by Cre-RecombinaseActivity

Vorhagenet al. (2015)

Assessing the In Vivo Epidermal Barrier in Mice:Dye Penetration Assays

Schmitz et al.(2015)

Humanized Mice in Dermatology Research Griffin et al. (2015)

Drug Delivery Techniques, Part 1: Concepts inTransepidermal Penetration and Absorption

Schmiederet al. (2015)

Drug Delivery Techniques, Part 2: Commonly UsedTechniques to Assess Topical Drug Bioavailability

Patel et al.(2016)

Skin Carcinogenesis Models: XenotransplantationTechniques

Mollo et al.(2016)

Mouse Models of Autoimmune Blistering Diseases Pollmann andEming (2017)

Murine Models of Human Psoriasis Hawkes et al.(2018)

Animal Models of Wound Healing Grada et al. (2018)

Mouse Models of Atopic Dermatitis Kim et al. (2019)

Parabiosis to Elucidate Humoral Factors inSkin Biology

Spencer andLeung (2019)

Forward Genetic Screening to Uncover GenesInvolved in Skin Biology

McAlpineet al. (2019)

EDITORIAL

1842

I am currently a 4th year medical student (8th yearMedical Science Training Program student) andcompleted my PhD in Bioengineering in 2018. I utilizedstructural and computational techniques to studymechanisms underpinning innate immune hyper-activation by nucleic acid nanocrystals in psoriasis,lupus, and scleroderma. I plan to become a physician-scientist in immunodermatology, focusing on devel-oping new therapies for autoimmune skin diseases. Ifound the RTMS series to be extremely informative andhighly educational. I primarily used it as a learningresource to expandmy knowledge of current techniquesin skin biology. I found the articles on animal models ofskin diseases (Table 1) and on bioinformatics tech-niques applied to dermatology (Foulkes et al., 2017) tobe the most useful. I plan to utilize this series to educatemy future students and have also recommended it totrainees in my former thesis lab.

—Ernest Lee, PhD

Trainee at the University of California, Los Angeles

CONFLICT OF INTERESTThe author is the Coordinating Editor for the Research Techniques MadeSimple Series.

Journal of Investigative Dermatology (2019), Volume 139

Jodi L. Johnson1,2,*1Department of Pathology, Northwestern University, FeinbergSchool of Medicine, Chicago, Illinois, USA; and 2Department ofDermatology, Northwestern University, Feinberg School ofMedicine, Chicago, Illinois, USA*Correspondence: 303 East Chicago Avenue, Chicago, Illinois 60611, USA.E-mail: jodi-johnson@northwestern.edu

REFERENCES

Barros JF, Waclawiak I, Pecli C, Borges PA, Georgii JL, Ramos-Junior ES, et al.Role of chemokine receptor CCR4 and regulatory T cells in wound healingof diabetic mice. J Invest Dermatol 2019;139:1161e70.

Foulkes AC, Watson DS, Griffiths CEM, Warren RB, Huber W, Barnes MR.Research techniques made simple: bioinformatics for genome-scalebiology. J Invest Dermatol 2017;137:e163e8.

Grada A, Mervis J, Falanga V. Research techniques made simple: animalmodels of wound healing. J Invest Dermatol 2018;138:2095e105.e1.

Griffin RL, Kupper TS, Divito SJ. Humanized mice in dermatology research.J Invest Dermatol 2015;135:e39e43.

Günschmann C, Chiticariu E, Garg B, Hiz MM, Mostmans Y, Wehner M, et al.Transgenic mouse technology in skin biology: inducible gene knockout inmice. J Invest Dermatol 2014;134:1e4.

Hawkes JE, Adalsteinsson JA, Gudjonsson JE, Ward NL. Research techniquesmade simple: murine models of human psoriasis. J Invest Dermatol2018;138:e1e8.

Kim D, Kobayashi T, Nagao K. Research techniques made simple: mousemodels of atopic dermatitis. J Invest Dermatol 2019;139:984e90.e1.

McAlpine W, Russell J, Murray RA, Beutler B, Turer E. Research techniquesmade simple: forward genetic screening to uncover genes involved in skinbiology. J Invest Dermatol 2019;139:1848e53.e1.

Mollo MR, Antonini D, Cirillo L, Missero C. Research techniques made sim-ple: skin carcinogenesis models: xenotransplantation techniques. J InvestDermatol 2016;136:e13e7.

Patel P, Schmieder S, Krishnamurthy K. Research techniques made simple:drug delivery techniques, part 2: Commonly used techniques to assesstopical drug bioavailability. J Invest Dermatol 2016;136:e43e9.

Pollmann R, Eming R. Research techniques made simple: mouse models ofautoimmune blistering diseases. J Invest Dermatol 2017;137:e1e6.

Scharfenberger L, Hennerici T, Kiraly G, Kitzmuller S, Vernooij M, Zielinski JG.Transgenic mouse technology in skin biology: generation of complete ortissue-specific knockout mice. J Invest Dermatol 2014;134:1e5.

Schmieder S, Patel P, Krishnamurthy K. Research techniques made simple:drug delivery techniques, part 1: Concepts in transepidermal penetrationand absorption. J Invest Dermatol 2015;135:1e5.

Schmitz A, Lazi’c E, Koumaki D, Kuonen F, Verykiou S, Rubsam M. Assessingthe in vivo epidermal barrier in mice: dye penetration assays. J InvestDermatol 2015;135:1e4.

Spencer CA, Leung TH. Research techniques made simple: parabiosis toelucidate humoral factors in skin biology. J Invest Dermatol 2019;139:1208e13.e1.

Tellkamp F, Benhadou F, Bremer J, Gnarra M, Knüver J, Schaffenrath S, et al.Transgenic mouse technology in skin biology: generation of knockin mice.J Invest Dermatol 2014;134:1e3.

Tomic-Canic M, DiPietro LA. Cellular senescence in diabetic wounds: whentoo many retirees stress the system. J Invest Dermatol 2019;139:997e9.

Vorhagen S, Jackow J, Mohor SG, Tanghe G, Tanrikulu L, Skazik-Vogt C, et al.Lineage tracing mediated by cre-recombinase activity. J Invest Dermatol2015;135:1e4.

Wilkinson HN, Clowes C, Banyard KL, Matteuci P, Mace KA, Hardman MJ.Elevated local senescence in diabetic wound healing is linked topathological repair via CXCR2. J Invest Dermatol 2019;139:1171e81.e6.

This is a reprint of an article that originally appeared in the September 2019 issue of the Journal of Investigative Dermatology. It retains its original paginationhere. For citation purposes, please use these original publication details: Johnson JL. Putting “Research Techniques Made Simple” Articles toWork for You andfor the Future of Investigative Dermatology. J Invest Dermatol 2019;139(9):1841e1842; doi:10.1016/j.jid.2019.07.687

ª 2019 The Authors. Publishe

EDITORIAL

Use of “Research Techniques MadeSimple” Series in Translational TopicsTraining in Dermatology at OregonHealth & Science University

ermatology is an interdisciplinary spe-cialty that requires incorporation of

Dexpertise from multiple backgrounds,

including pathology, immunology, genetics, celland developmental biology, biomedical engi-neering, and cancer biology, to better understandthe mechanisms underlying conditions arising inour patients. It is critically important for derma-tology training programs to reflect this broad andever-expanding array of topics to prepare thenext generation of clinicians and basic scientistsfor a lifetime of encountering new challenges.The training program at Oregon Health & Sci-ence University (OHSU) has tackled this need inpart through a monthly seminar called “Trans-lational Topics in Dermatology.” In this format, adermatology resident and a basic science traineepresent a joint seminar exploring unansweredquestions in dermatology. In this seminar, eachresidentescientist team selects a general theme,intended to explore fundamental clinical andscientific concepts within the field of derma-tology. Presentation themes broadly draw uponthe Journal of Investigative Dermatology’s (JID)Skin Biology Lecture Series that includes topicssuch as the structure and function of skin, me-lanocyte biology, DNA damage and repair,cutaneous immunology, the basement mem-brane zone, and cutaneous appendages. Pre-senters have also chosen to explore subjectsbased upon research interests and career plans,including topics in pediatric dermatology; im-mune profiling in prognosis and therapy; clinicaltrials; and novel augmentations to proceduraldermatology, such as cell therapy. The residentpresents the clinical features of the associateddermatoses, pathogenesis, and therapeutic stra-tegies, whereas the basic scientist explores thelatest research, which may include their ownwork. Together, the rotating pair provide a forumthat engenders vigorous discussion betweenresidents, trainees, researchers, and faculty cli-nicians on the future directions in research

Journal of Investigative Dermatology (2019) 139, 1843e1844.doi:10.1016/j.jid.2019.07.684

d by Elsevier, Inc. on behalf of the Society for Investigative Derm

needed to resolve questions and improve treat-ment options for skin disease. As a dermatologyresident and basic scientist team, we have writ-ten this article to highlight how TranslationalTopics in Dermatology has positively impactedour career trajectories, how the Research Tech-niques Made Simple (RTMS) series of the JID canbe utilized to enhance the experience of such aforum, and how other universities may imple-ment similar programs to benefit their owntraining experiences.The Translational Topics in Dermatology se-

ries provides many professional growth oppor-tunities. The opportunity to deliver an in-depthhour-long seminar to a multidisciplinary audi-ence helps build confidence in public speakingand teamwork. From a resident’s perspective, theprospect of learning complex molecular mecha-nisms and laboratory techniques in addition tothe fundamental clinical, histopathologic, andtherapeutic concepts required by training pro-grams can be daunting. The breadth of contentcovered in residency training curricula makes itchallenging to invest the time and energyrequired to achieve a similar depth of knowledgeabout laboratory techniques. Residents preparingTranslational Topics talks utilize a variety of re-sources to better understand study design andbasic science research techniques, includingdiscussions with their scientist counterparts andthe JID’s RTMS articles. RTMS is a series of freeonline articles that help distill complex conceptsrelated to laboratory assays, statistical methods,and animal models, as well as clinical andpatient-oriented studies, into an easily digestibleformat. There are currently over 80 RTMS articlesavailable to help presenters better understandcomplex research techniques and prepare theirseminars. RTMS articles have been used recentlyin our Translational Topics forum to enhancediscussion of the exciting finding that chimericantigen receptor (CAR) T cells could be adaptedto target anti-desmoglein-3eproducing B cellsfor pemphigus vulgaris (PV) treatment (Ellebrechtet al., 2016). Siddiqi and colleagues wrote anRTMS article describing the technique of gener-ating CAR T cells, their Food and Drug

atology. www.jidonline.org 1843

EDITORIAL

1844

Administrationeapproved use for B-cell malignancies, andtheir potential uses in PV and melanoma (Siddiqi et al., 2018).The RTMS article by Siddiqi et al. provided additional detailsabout the techniques used in the Ellebrecht et al. manuscriptand ultimately aided our interpretation of the results. Addi-tionally, we have found several RTMS articles describingmouse models of disease, including atopic dermatitis, psori-asis, and autoimmune blistering conditions, helpful inweighing the benefits and disadvantages of each model instudying complex dermatologic conditions (Hawkes et al.,2018; Kim et al., 2019; Pollmann and Eming, 2017). Over-all, we find that the RTMS articles enhance the TranslationalTopics in Dermatology program by providing a deeper un-derstanding of the material presented and provide a struc-tured resource to explore unfamiliar topics in laboratoryresearch as they relate to the presentation and management ofskin disease.From a basic scientist’s perspective, particularly one

embarking on a new career in dermatologic research, thefield can be intimidating in part because of its breadth. Thetraining program at OHSU is comprehensive and rigorous,consisting of Dermatology Research Division Joint LabMeetings, Trainee Seminars, High Impact DermatologyResearch Journal Clubs, Translational Topics in Dermatology,Faculty Forums, and the Storrs and Lobitz guest lectureships.Trainees are also encouraged to shadow clinicians and takepart in morphology conferences to help scientists bridge theclinical language gap and offer a deeper understanding ofclinical practice. However, special emphasis is placed onTranslational Topics in Dermatology, and it quickly becamethe forum that I most looked forward to each month, as itallowed a more in-depth view of fundamental concepts crit-ical to the understanding of skin biology and provided clinicalinsights into the pathogenesis and treatment of disease. Thetraining program, and Translational Topics in Dermatology inparticular, has greatly impacted my research and career tra-jectory. While at OHSU, I investigated mechanisms by whichimmunoglobulins and complement regulate immune cellfunction in squamous cell carcinomas (Medler et al., 2018).After attending a faculty forum in which Lynne Morrison, MD,presented on autoimmune bullous disorders, I hypothesizedthat these same pathways may regulate PV pathogenesis andthat some of the targeted therapies I was using for squamouscell carcinoma might also be relevant for PV treatment. Webegan collaborating and I was able to obtain funding to testmy hypothesis in the laboratory. Throughout my in-vestigations, I incorporated my research into subsequentTranslational Topics in Dermatology for further discussionabout results and to inform research direction. These dialogswere instrumental in the development and implementation ofthis project; it was a perfect confluence of the training pro-gram, intellectual environment, and interdepartmental sup-port that allowed the project to flourish.Based on our collective experience with the Translational

Topics in Dermatology forum, we offer several suggestions to

Journal of Investigative Dermatology (2019), Volume 139

other departments considering the incorporation of a similarseries to their own training programs. We encourage pre-senters to frame their talks around a specific clinical question;posing a central clinical question empowers residents toperform a focused review of the current medical literature,rather than simply summarizing a relevant textbook chapter.Answering a central clinical question provides a unifiedobjective for presenters, helping to avoid the scenario ofpartners presenting two parallel talks rather than a fully inte-grated translational seminar. We also recommend expandingoutreach to include partnerships with diverse interdisciplinarytrainees, such as those within Biomedical Engineering, Phar-macology, or Bioinformatics programs. Lastly, we suggestseeking out experts to help expand your knowledge base.Overall, the Translational Topics in Dermatology program

at OHSU has been well-received and highly successful, withRTMS assisting trainees along the way. Through TranslationalTopics in Dermatology, trainees present fresh and innovativemedical and scientific knowledge that ultimately mayimprove one’s clinical practice or research direction—itcertainly has enriched ours!

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSThe authors acknowledge the OHSU Department of Dermatology Training inthe molecular basis of skin/mucosa pathobiology (T32 CA106195-15) and theOHSU Knight Cancer Institute (P30 CA069533).

Solveig Ophaug1,* and Terry R. Medler2,31Department of Dermatology, Oregon Health & Science University,Portland, Oregon, USA; 2Department of Cell, Developmental &Cancer Biology, Oregon Health & Science University, Portland,Oregon, USA; and 3Earle A. Chiles Research Institute, Robert W.Franz Cancer Center, Providence Portland Medical Center, Portland,Oregon, USA*Correspondence: SolveigOphaug, Department ofDermatology,OregonHealth& Science University, 3303 S.W. Bond Avenue, Portland, Oregon 97239.E-mail: ophaug@ohsu.edu

REFERENCES

Ellebrecht CT, Bhoj VG, Nace A, Choi EJ, Mao X, Cho MJ, et al. Reengineeringchimeric antigen receptor T cells for targeted therapy of autoimmune dis-ease. Science 2016;353:179e84.

Hawkes JE, Adalsteinsson JA, Gudjonsson JE, Ward NL. Research techniquesmade simple: murine models of human psoriasis. J Invest Dermatol2018;138:e1e8.

Kim D, Kobayashi T, Nagao K. Research techniques made simple: mousemodels of atopic dermatitis. J Invest Dermatol 2019;139:984e90.e1.

Medler TR, Murugan D, Horton W, Kumar S, Cotechini T, Forsyth AM, et al.Complement C5a fosters squamous carcinogenesis and limits T cellresponse to chemotherapy. Cancer Cell 2018;34:561e78.e6.

Pollmann R, Eming R. Research techniques made simple: mouse models ofautoimmune blistering diseases. J Invest Dermatol 2017;137:e1e6.

Siddiqi HF, Staser KW, Nambudiri VE. Research techniques made simple:CAR T-cell therapy. J Invest Dermatol 2018;138:2501e4.e1.

This is a reprint of an article that originally appeared in the September 2019 issue of the Journal of Investigative Dermatology. It retains its original paginationhere. For citation purposes, please use these original publication details: Ophaug S, Medler TR. Use of “Research Techniques Made Simple” Series in Trans-lational Topics Training in Dermatology at Oregon Health & Science University. J Invest Dermatol 2019;139(9):1843e1844; doi:10.1016/j.jid.2019.07.684

RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple: AnimalModels of Wound Healing

Ayman Grada1, Joshua Mervis2 and Vincent Falanga1

Animal models have been developed to study the complex cellular and biochemical processes of wound repairand to evaluate the efficacy and safety of potential therapeutic agents. Several factors can influence woundhealing. These include aging, infection, medications, nutrition, obesity, diabetes, venous insufficiency, andperipheral arterial disease. Lack of optimal preclinical models that are capable of properly recapitulating humanwounds remains a significant translational challenge. Animal models should strive for reproducibility, quan-titative interpretation, clinical relevance, and successful translation into clinical use. In this concise review, wediscuss animal models used in wound experiments including mouse, rat, rabbit, pig, and zebrafish, with aspecial emphasis on impaired wound healing models.

Journal of Investigative Dermatology (2018) 138, 2095e2105; doi:10.1016/j.jid.2018.08.005

1DepartmenMassachuse

CorrespondUSA. E-mail

ª 2018 The

CME Activity Dates: 20 September 2018Expiration Date: 19 September 2019Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: All authors,planning committee members, CME committee members andstaff involved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

t of Dermatology, Boston University School of Medicine, Boston, Mtts, USA

ence: Ayman Grada, Department of Dermatology, Boston University: Grada@bu.edu

Authors. Published by Elsevier, Inc. on behalf of the Society for Inv

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Investiga-tive Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduring ma-terial for a maximum of 1.0 AMA PRA Category 1 Credit(s)�.Physicians should claim only the credit commensurate with theextent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Oct18 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONThe critical processes underlying wound healing have beeninitially described using animal models (Eming et al., 2014;Martin, 1997). Although animals do not develop chronicwounds in a way that closely resembles those arising inhumans, animal models have provided valuable insightsinto the principles of wound management. For example, thenow accepted notion that wounds heal faster when keptmoist came from research experiments in the domestic pig(Helfman et al., 1994). However, because of anatomical

a

and physiological differences among and within animalspecies, including humans, no single model can suit allneeds. Data generated from preclinical studies on woundrepair may vary considerably depending on the animalmodel chosen and on other biological variables such asage, sex, microbiome, and wound location (Elliot et al.,2018). Preclinical models should be validated before pro-ceeding with testing.When looking at preclinical models of wound healing, the

majority of studies are performed in either rodents or pigs.

ssachusetts, USA; and 2Boston University School of Medicine, Boston,

School of Medicine, 609 Albany Street, J313, Boston, Massachusetts 02118,

estigative Dermatology. www.jidonline.org 2095

BENEFITS� Investigating mechanisms of wound repair andregeneration.

� Testing the efficacy and safety of potentialtherapeutics.

� Ethical regulations prohibit the use of humans,especially humans with impaired wound healing,in potentially harmful studies.

LIMITATIONS� Anatomical and physiological differences amongand within animal species, including humans. Noone model can recapitulate the heterogeneityand complexity of chronic wounds in humans.

� Reproducibility and translation of preclinical datainto clinical reality remains an ultimate challenge.

� Lack of standardization in designs andprocedures.

RESEARCH TECHNIQUES MADE SIMPLE

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Primates are rarely used, mainly because of the higher costand animal care committees’ concerns regarding these ani-mals. Moreover, primates heal with far less collagen deposi-tion than humans do. Other animals offer limited benefit forwound research because of their size, temperament, andmaintenance expense.

ACUTE AND IMPAIRED HEALINGThe natural (acute) wound healing process in adult mammals,including humans, progresses in four orderly phases thatoverlap in time: coagulation, inflammation, migration-proliferation (including matrix deposition), and remodeling(Falanga, 2005). Acute wounds, such as those created bysurgery or trauma, occur suddenly and heal in a relativelypredictable timeframe. Deregulation or interruption of one ormore phases of the normal healing process leads to chronicwounds (Eming, 2014). A chronic wound is a wound that failsto progress through the normal phases of healing in an orderlyand timely manner. Persistent inflammation is a hallmark ofthe chronic wound microenvironment. Some of the majorcauses of impaired wound healing include diabetes mellitus,vascular insufficiencies, and prolonged local pressure.

ANIMAL MODELS OF ACUTE HEALINGAcute wound models are useful for studying the naturalhealing processes and for drug discovery. Although we willfocus mainly on models of impaired healing, acute woundmodels that are commonly used include excisional, inci-sional, and burn models, which all have well-establishedprotocols (DiPietro and Burns, 2003).

ANIMAL MODELS OF IMPAIRED HEALINGChronic wounds in animals can be created from an acutewound by inducing diabetes, mechanical pressure, ischemia,or reperfusion injury. Chronic wounds are uncommon in

Journal of Investigative Dermatology (2018), Volume 138

animals, and thus all animal models have limitations (Mustoeet al., 2006).

Diabetic wound modelsNo single model can reproduce the entire diabetic patho-logical process and its variations. Each model mimics merelyone aspect of this complex disease. Hyperglycemia can bechemically induced in mice and rats by intraperitoneal orcaudal vein injection of streptozotocin or alloxan to causeselective destruction of insulin-producing beta cells of thepancreas. Animals are allowed to manifest hyperglycemia forseveral weeks before making a cutaneous wound throughcutting, burning, or radiation. A pig model of diabetic ulcerswas established (Velander et al., 2008). However, thesewounds healed after 18 days, which is not consistent withdiabetic wounds in humans. Diabetes and insulin resistancecan be induced by genetic manipulation as well. There aretwo types: type 1 diabetes models include the nonobesediabetic (i.e., NOD) mouse, streptozotocin-induced diabeticrat or mouse, bio-breeding (i.e., BB) rat, and Chinese hamster.Type 2 diabetes models include the obese ob/ob mouse(leptin receptor deficient), db/db mouse (a point mutation inthe leptin receptor gene), NONcNZO10 mouse, and Zuckerfa/fa rats. The most common type 2 diabetic model (db/dbmouse) has significant limitations in predicting humans out-comes because human type 2 diabetes does not involveleptin abnormalities and is polygenic. No animal modelmimics the chronic problems that result in type 2 diabeticulcers (Fang et al., 2010).

Pressure ulcer modelsThe primary cause of pressure ulcers is repeated ischemia-reperfusion injury caused by prolonged mechanical pres-sure, especially over a bony prominence. Pressure ulcers canbe modeled in loose-skinned animals such as rats and miceby surgically implanting a metal plate under the skin(Figure 1), followed by intermittent and periodic compres-sions of the skin using an external magnet (Reid et al., 2004;Wassermann et al., 2009). Loose-skinned animals with littlesubcutaneous fat, mainly rats, are suitable for modeling agedhuman skin (Nguyen et al., 2008). Greyhound dogs have alsobeen used because of their thin skin (Swaim et al., 1993). Pigsare better animals to model pressure ulcers of young humansbecause of their tight skin (Nguyen, 2008). A cast can beplaced over a bony prominence in pigs to cause a reperfusioninjury and friction on the skin surface (Swaim et al., 1997).

Ischemic wound modelsThe rabbit ear ulcer model has been extensively used tosimulate ischemic wounds. Cutaneous ischemia is created byear vessel ligation. Skin banding has been shown to create anischemic model in guinea pigs (Constantine and Bolton,1986). Bipedicle flap (surgically isolated area of skin withminimal continued blood supply) has been used to createischemia on the dorsal skin of pigs (Figure 1). Molecularmarkers are used to validate the hypoxic state of tissues.

Biofilm-infected wound modelOne characteristic of chronic human wounds is bacterialinfection and biofilm, which impairs healing by inducingprolonged proinflammatory cytokines (Edwards and Harding,

Figure 1. Animal models of woundhealing. (aeg) Examples of chronicskin wound animal models, theirclinical relevance, benefits anddrawbacks. (a) Rabbit ear ischemiamodel (profile view). (b) Chemicallyinduced type 2 diabetic mouse model(dorsal view). (c) Excision woundsplinting model in mouse (dorsalview). (d) Rat magnet ischemia-reperfusion model (profile view).(e) Pig wound infection model (dorsalview). This method is also applicableto rodents and rabbits. (f) Pig flapischemia model (dorsal view). Thismethod is also applicable to rodentsand rabbits. (g) Mouse tail full-thickness wound model (dorsal view).This method is also applicable to wild-type, transgenic, and knockout mice.This work is partially derived fromNunan et al. (2014) used under CC BY.

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RESEARCH TECHNIQUES MADE SIMPLE

Table 1. Features of different animal species used in modeling of wound healingAnimalSpecies Skin Type

Primary HealingMechanism Advantages Limitations

Mouse Loose skinned Contraction � Small

� Very common

� Cost efficient

� Easy to handle and maintain

� Numerous transgenic,

knockout, and gene-

inducible lines readily

available

� Species-specific reagents

widely available for many

techniques such as immuno-

histochemistry and flow

cytometry

� Broad knowledge base on

mouse wound healing from

years of extensive research

� Mouse tail model enables the

study of delayed healing in

wild-type mice, which can

then be used as controls in

studies of mutant strains

� Loose skin and very high hair

density do not reflect the ar-

chitecture of human skin

� In the absence of outside

intervention (i.e., splinting),

wounds heal primarily via

contraction, obviating the

need for a robust proliferative

phase of wound healing

� Use of splinting to avoid

contraction introduces

foreign material to the

wound site

� Partial-thickness wounds can

be difficult to make because

of thinness of skin

� Consistently poor trans-

lational efficacy of therapeu-

tics in humans

� Mouse genomic, immune,

and inflammatory responses

differ significantly from

humans’ after injury

Rat Loose skinned Contraction � Small

� Common

� Cost efficient

� Easy to handle and maintain

� Bigger than mice, which al-

lows for larger or more

numerous wounds per animal

� Broad knowledge base on rat

wound healing from years of

extensive research

� Loose skin and high hair

density do not reflect the ar-

chitecture of human skin

� Heal primarily via contrac-

tion, thus minimizing the

relevance of re-epithelization

and granulation unless

splinting technique is used

� Use of splinting to avoid

contraction introduces

foreign material to the

wound site

� Less genetically tractable

than mice

� Relative paucity of species-

specific reagents compared

with mice

(continued )

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2004; James et al., 2008). Wound-healing kinetics in thepresence of biofilm have been studied in several animalmodels (Gurjala et al., 2011). After wounding a rodent, rabbit,or pig, a bacterial suspension of Pseudomonas aeruginosa orStreptococcus aureus can be applied to the surface of thewound. Bacterial concentration is adjusted according topathogenicity, virulence, and the extent of the immuneresponse of the host (Robson, 1997). An occlusive dressingshould be used to prevent cross-contamination and provideoptimal conditions for bacterial growth. The rabbit ear can be

Journal of Investigative Dermatology (2018), Volume 138

used to combine a biofilm model with ischemia, increasing itsclinical relevance (Gurjala, 2011). The rabbit ear model hasbeen used to study the efficacy of traditional wound care inthe presence of a P. aeruginosa biofilm (Seth et al., 2012).

CHOICE OF ANIMAL SPECIESSeveral factors should be consideredwhen choosing an animalspecies for wound experiments (Table 1). These include cost,availability, ease of handling, investigator familiarity, andsimilarity to humans. The use of small animals has a cost

Table 1. ContinuedAnimalSpecies Skin Type

Primary HealingMechanism Advantages Limitations

Rabbit Loose skinned Contraction � Relatively inexpensive

� Rapid breeding with prodi-

gious offspring

� Rabbit ear model overcomes

wound contraction

� Maybe well-suited to testing

potential therapeutics,

because rabbit and human

skin respond similarly to

aging, delayed healing, and

various topical drugs

� Can create several wounds in

the same ear

� Contralateral ear can be used

as a control

� Larger-caliber vessels make

ischemic ligation easier

� Rabbit ear model can be

adapted for study of

hypertrophic scarring

� Limited genetic tractability

� Paucity of species-specific

reagents

Guinea pig Loose skinned Contraction � Relatively small and cheap

� Unable to produce endoge-

nous vitamin C, so dietary

deficiency allows study of the

role of collagen in wound

healing

� Not commonly used today

� Variable pregnancy rates,

small and variable litter size,

and relatively long gesta-

tional time (60e70 days)

� Lack of transgenic methods

and a limited number of

strains

Pig Tight skinned Partial-thickness wound healswith re-epithelialization andgranulation. Full-thickness

wound heals with contraction.

� Large size allows for larger

and more numerous wounds

� Skin architecture, hair den-

sity, and physiology of

wound healing most closely

resemble what is seen in

humans

� Very relevant for preclinical

studies looking at

interventions

� Expensive to maintain

� Administration of anesthesia

is more difficult and requires

a skilled veterinarian

� All surgical procedures

generally require greater skill

and expertise

� Long gestational times

� Poor genetic tractability and

few transgenic lines available

� Not practical for most

research facilities

� Dermis of larger, older ani-

mals is often significantly

thicker than that of humans

� Less vascular dermis and lack

of eccrine sweat glands over

almost all body surfaces are

notable differences from hu-

man skin

(continued )

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Table 1. ContinuedAnimalSpecies Skin Type

Primary HealingMechanism Advantages Limitations

Zebrafish Not applicable Re-epithelialization andgranulation

� Small

� Low cost

� Greater genetic tractability

� Healing phases are discrete

and uncoupled from each

other, allowing isolated study

of a particular process (i.e.,

epithelialization)

� Investigation of regenerative

healing

� Relatively underdeveloped

model

� Limited number of validated

zebrafish reagents such as

antibodies and cell lines are

available to the research

community

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advantage. There are, however, several limitations, includinglimits towound size, skin thinness relative to humans, follicularpattern, and hair growth cycle that differs from humans(Table 2). Wounds in areas with higher hair density heal fasterthan those in less hairy or nonhairy areas (Ansell et al., 2011).

MouseMice are cost effective and amenable to genetic manipula-tion, which allows for mechanistic studies. Full-thicknesssurgical incisions and excisions performed on mouse dorsalskin are the most popular wound models. Dorsal sites tend tobe quite useful in keeping the animal from reaching andmanipulating the wound. For preclinical studies of thera-peutics, each mouse can act as its own internal controlbecause each animal can be given two wounds, enabling theapplication of both the treatment and control on the samemouse. However, using mice to simulate human woundclosure has significant limitations. Wound healing in mice isfundamentally different from that in humans in that it isdominated by myofibroblast-mediated contraction. This dif-ference is in part due to an extensive subcutaneous striatedmuscle layer called the panniculus carnosus that is mostlyabsent in humans. In mice, this muscle layer allows the skinto move independently of the deeper tissues; hence, it iscalled “loose skin.” A splinting technique is used to minimizecontraction (Galiano et al., 2004; Wang et al., 2013) and toallow healing through granulation and re-epithelialization,similar to humans. Mouse skin in males is up to 40% stron-ger than in females because of a thicker dermal layer. Bycontrast, females have thicker epidermal and hypodermallayers (Wong et al., 2011).

Wound healing is significantly accelerated when micewere wounded in the late anagen compared with the catagenor telogen hair cycle stages (Ansell, 2011). To minimize theimpact of hair follicles on wound healing, wounding must becreated during telogen or early exogen, the resting phases ofthe hair cycle. One alternative is to use outbred hairless mice(Hr gene mutation).

Transgenic mice. Transgenic and knockout mouse modelshave been used to study the impact of a single gene in woundhealing. IL-6eknockout mice have shown significantlydelayed wound healing compared with wild-type mice

Journal of Investigative Dermatology (2018), Volume 138

(Gallucci et al., 2000). Although genetically modified micehave tremendous potential for revealing the molecular path-ways behind wound repair processes, overall, their utility iscomplicated by compensatory changes in gene expressionand unanticipated effects, so that many gene knockouts havenot given the predicted effects, and a great deal of effort goesinto defining the molecular pathways involved in thephenotype (Fang and Mustoe, 2008).

Mouse tail. Ideally, one would like to have the option tomodel a chronic wound in wild-type animals. Traditionally,geneticallymodified strains, such as the diabeticdb/dbmouse,have been used to model impaired healing (Beer et al., 1997).Thus, the mouse tail model was developed to recapitulatedelayed wound closure in the wild-type animal (Falanga et al.,2004). A rectangular (0.3 � 1.0 cm) full-thickness excision ismade on the dorsal aspect of the tail, 1 cm distal to the body ofthe mouse (Figure 2). The excised skin exposes the underlyingfascia, leaving a rectangular full-thickness defect. Comparedwith back dorsal wounds, which heal within a few days, thetail wounds require up to 21 days for full resurfacing, anexpanded timeframe to test hypotheses and therapies. Becausetail hair remains short, the wounds can be followed sequen-tially and measured clinically without killing the animals.Wild-type, transgenic, and knockout mice can be used.

RatSimilar to mice, rats have loose skin and therefore heal pre-dominantly by contraction. Healing by contraction is morerapid than re-epithelialization because new tissue is notformed. Unlike humans, mice and rats do not create hyper-trophic scars or keloids. The collagen produced in theirwounds comes from subcutaneous panniculus carnosusmuscles (Cohen et al., 1979). Several wound models haveused rats because of their size, wide availability, and tractablenature. Although mice may translate into lower maintenancebudgets, rats provide a larger area of skin for wound studies.Male Sprague Dawley rats in the 250e300-gram weightrange are the preferred strain. Male rats generally cost lessthan females of the same size (Dorsett-Martin, 2004).

An ischemic, H-shaped, double flap model in rats’ dorsumwas developed for studying the influence of different factorson flap survival (Quirinia et al., 1992). However, this model

Table 2. Characteristics of human and animal skin: mean thickness of skin layers and hair density in animal species used in wound experiments

Species Site

SC VE D Hair Density,hairs/ cm2

Healing TimeCourse, days Sourcemm SD/SE* mm SD/SE* mm SD

Mouse Dorsum 9 — 29 — 662 — 658 (thick) Closes in <5 days becauseof contraction of skin

Monteiro-Riviere et al. (1990)Mouse Buttock, ear, shoulder,

back, abdomen (paraffin)3.38 �0.30* 11.50 �1.24* — —

Mouse Buttock, ear, shoulder, back,abdomen (frozen)

6.69 �0.96* 9.24 �0.96* — —

Mouse Back w5 — w21e22 — w275e280 Ma et al. (2002)Rat Dorsum 18 — 32 — 2,040 — 289 (thick) Closes in <5 days because

of contraction of skinMonteiro-Riviere et al. (1990)

Rat Buttock, ear, shoulder,back, abdomen (paraffin)

4.04 �0.47* 15.34 �1.21* — —

Rat Buttock, ear, shoulder, back,abdomen (frozen)

9.91 �1.14* 10.70 �1.73* — — Oznurlu et al. (2009)

Rabbit Lumbar dorsum 11.7 �3.6 20.6 �4.0 2,174.0 �486.7 13e16, or longer dependingon wound size

Oznurlu et al. (2009)Rabbit Lumbar dorsum 9.5 �1.6 19.4 �4.8 1,719.3 �258.5Rabbit Buttock, ear, shoulder,

back, abdomen (paraffin)6.89 �0.88* 13.83 �1.23* — — 80 (medium) Monteiro-Riviere et al. (1990)

Rabbit Buttock, ear, shoulder,back, abdomen (frozen)

10.91 �1.48* 9.39 �1.25* — —

Pig Buttock, ear, shoulder,back, abdomen (paraffin)

12.85 �1.19* 53.17 �3.19* — — 11 (sparse) 12e14, or longer dependingon wound size

Monteiro-Riviere et al. (1990)

Pig Buttock, ear, shoulder,back, abdomen (frozen)

41.33 �3.73* 15.37 �1.51* — —

Pig Ear 17e28 60e85 1,440e2,210 (including H) Jacobi et al. (2007)Human Abdomen 17 — 47 — 2,906 — 11 (sparse) 7e14, or longer depending

on wound sizeMonteiro-Riviere et al. (1990)

Human — 10 — 50e120 — 2.28 — Qvist et al. (2000)Human Various sites — — 31e637 (including SC) 521e1,977 (E þ D) Lee and Hwang (2002)

Abbreviations: D, dermis; E, epidermis; H, hypodermis or subcutaneous tissue; SC, stratum corneum; SD, standard deviation; SE, standard error; VE, viable epidermis.Modified from Wei et al. (2017), used under CC BY.*Denotes standard error (SE).

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Figure 2. Ischemic rabbit ear model.A circumferential incision is made atthe base of the ear. The rostral andcentral arteries are ligated, leavingthree main veins and the small caudalartery intact. Reprinted from SurgicalResearch, Saulis A, Mustoe TA; 2001.p. 857-873. Models of WoundHealing in Growth Factor Studies.With permission from Elsevier.

Figure 3. Mouse tail model. Gross appearance of a full-thickness wound on amouse tail, immediately after wounding. The fascia is glistening white.Reprinted from Falanga et al. (2004) with permission from Wiley.

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has limitations. The rapidity with which the tissue returns tonormal levels of perfusion prevents extended testing of po-tential therapeutic agents. Meanwhile, it is difficult to eval-uate healing in incisional wounds, because breaking strengthmeasurements reflect only one aspect of healing. An opti-mized ischemic flap model was established by creating full-thickness excisional wounds within a bipedicle dorsal skinflap in rats (Gould et al., 2005). In this model, modificationswere made to the bipedicle flap model described initially bySchwarz et al. (1995). The two main modifications are (i)making the skin flap sufficiently narrow so that the bloodsupply is random and the wounds located in the midpoint ofthe flap are ischemic and (ii) inserting a silicone sheet beneaththe skin flap, which prevents re-adherence and reperfusion ofthe flap from the underlying tissue. In this model, the pan-niculus carnosus muscle is removed from the wound bed bydissecting just above the muscle fascia. Wound contraction islimited (but not eliminated) by tacking the flap to the siliconesheet (Gould, 2005). The final product is a flap that does notdevelop necrosis yet remains ischemic for up to 2 weeks withmarkedly impaired healing.

Rabbit earRabbit ear has been widely used as an ischemic woundmodel to study the effects of hypoxia on healing, as firstdescribed by Ahn and Mustoe (1990). The rabbit ear isvascularized by three main arteries (Figure 3). An ischemiczone is created by ligating two (rostral and central arteries)of the three arteries at the base of the ear through acircumferential incision, thus disrupting dermal arterial cir-culation while maintaining the veins. A 6-mm punch biopsydown through the cartilage will create a full-thicknesswound that lacks a vascular base and has a very limitedlateral vascular supply. Because the dermis of the rabbit earis firmly attached to the cartilage, the avascular wound bedcannot close by contraction and, instead, heals via epithe-lization and granulation tissue formation. However, theischemia is reversible, and collateral circulation develops inabout 14 days. The main advantage of this model is thatrabbit ear provides a large surface area on which several

Journal of Investigative Dermatology (2018), Volume 138

similar ulcers can be created in the same ear, and thecontralateral ear can serve as a control. Furthermore,because of the splinting from ear cartilage, open wounds inthe rabbit ear allow easy quantification of epithelization asan independent variable from granulation tissue. Althoughtheoretically a similar model could be applied to rodents,the technical aspects (surgical skills and magnification) havemade this prohibitive.The rabbit ear model has also been used to study the

effects of various topical growth factors in promoting healingof chronic wounds (Xia et al., 1999). Although promisingresults were achieved with growth factor therapies in animalstudies, human clinical trials have been disappointing.Nonetheless, some notable observations have been made thatpoint to rabbit wounds behaving similarly to human wounds.These similarities include increased scarring with delayedepithelialization and less scarring with old age, topical ste-roids, and collagen synthesis inhibitors.

MULTIPLE CHOICE QUESTIONS1. Which of the following animal species heal

predominantly by contraction?

A. Humans

B. Pigs

C. Mice and rats

D. Zebrafish

2. The mouse tail model has the following featuresexcept which of the following?

A. Rapid healing capacity

B. Can be used to study scarring

C. Offers longer duration of wound closure

D. Contraction is minimal

3. Which of the following animal species is mostrelevant to partial-thickness wound modeling?

A. Pig

B. Greyhound

C. Rabbit

D. Guinea pig

4. To choose an optimal animal model, one musttake into consideration the following factors:

A. Size

B. Cost

C. Reproducibility

D. All of the above

5. Which of the following adult animals exhibitsscar-free skin regeneration?

A. Mouse

B. Rat

C. Pig

D. Zebrafish

See online version of this article for a detailed explanationof correct answers.

RESEARCH TECHNIQUES MADE SIMPLE

PigPigs are standard models for wound healing because of thesignificant similarities to human skin (Montagna and Yun,1964). Key similarities include epidermal and dermal thick-ness and related ratios (for weanling pigs), epidermal turnovertime (around 30 days), pattern and structure of hair follicles,content and structure of dermal collagen and elastin, dermalmetabolism, types of immune cells present, and biologicalresponse to growth factors. Perhaps most importantly, partial-thickness wounds in both pigs and humans heal mainlythrough re-epithelialization, not contraction. In contrast, cir-cular full-thickness wounds heal significantly by contractionin pig models. Both percutaneous permeability and trans-dermal absorption in human skin is closer to those in pig skinthan in other animal models (Bartek et al., 1972). Size of flaps,grafts, and dermal wounds have been standardized for com-parison of therapeutic agents.Pigs are substantially more expensive to purchase and

maintain. Although human and pig skin are quite comparablein a number of facets, dissimilarities certainly exist. Pig skinhas a higher pH, fatty subcutis, and predominantly apocrinesweat glands, with eccrine sweat glands confined only tospecialized regions. Moreover, although microvascularanatomy is consistent between humans and pigs, skinvasculature, particularly of the dermis, is richer in human skin(Montagna and Yun, 1964). Weanling pigs have a dermissimilar in thickness to humans, but larger animals have amuch thicker and stiffer skin than humans. These differencesare likely to have relevant implications for physiologicalstudies.The pig model is used to study a variety of cutaneous

wounds including partial- and full-thickness excisionalwounds, incisional wounds, laser-induced wounds,ischemic wounds, and second degree burns (Seaton et al.,2015). In pigs, limb denervation followed by casting hasalso been used to develop a model of pressure ulcers(Hyodo et al., 1995).

Guinea pigStudies of the effects of vitamin C deficiency on woundhealing are generally performed in the guinea pig because,like human beings, guinea pigs require vitamin C from dietarysources (Bartlett et al., 1942). The vitamin C-deficient(“scorbutic”) guinea pig was used throughout the early tomid-20th century to investigate the role of collagen in woundhealing (Abercrombie et al., 1956). Vitamin C is essential forcollagen synthesis. Most other animals, including the pig, cansynthesize their own vitamin C and thus do not make goodmodels to study the effects of dietary vitamin C deficiency onwound healing.

ZebrafishZebrafish can regenerate many tissues and organs. A full-thickness wound model can be quickly and reproduciblycreated on the flank of adult zebrafish (Richardson et al.,2013). Wounds show rapid re-epithelization (within hours),independent of coagulation and inflammation. Furthermore, agranulation-like tissue is formed and later cleared, resulting inminimal scar formation. Unlike the overlapping phases ofwound healing in mammals, healing processes occur

sequentially in zebrafish, allowing for better identification ofdirect and indirect effects caused by chemical or geneticmanipulation. Furthermore, it provides an opportunity toperform high-throughput small-molecule drug screens(Richardson et al., 2016). The zebrafish model has been usedto study the role of inflammation in wound healing (Hoodlesset al., 2016).

CONCLUSIONAnimal models provide invaluable information that can becorrelated with human wound healing. When it comes tointerpretation and implementation, one must not fail torecognize differences in each animal model. The investigatormust assess the merits and limitations of each model ac-cording to the experimental objectives. Creating an animalmodel that reflects the complexity and heterogeneity of

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chronic wounds in humans may be an unattainable goalbecause they are an outcome of multifactorial process that isinfluenced by both intrinsic and extrinsic factors such asimpaired circulation, infection, chronic inflammation, poornutrition, aging, limited physical activity, and chronic dis-ease, among others. Useful models are designed such thatthese impairments are comparable, thus permitting a higherdegree of validity. Given the ongoing advances in geneticmanipulation of mice and other animal species, new, moreuseful models of the wound repair will eventually emerge.

CONFLICT OF INTERESTThe authors state no conflict of interest.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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James GA, Swogger E, Wolcott R, Secor P, Sestrich J, Costerton JW, et al.Biofilms in chronic wounds. Wound Repair Regen 2008;16:37e44.

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Qvist MH, Hoeck U, Kreilgaard B, Madsen F, Frokjaer S. Evaluation of Göt-tingen minipig skin for transdermal in vitro permeation studies. Eur JPharm Sci 2000;11:59e68.

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Richardson R, Metzger M, Knyphausen P, Ramezani T, Slanchev K, Kraus C,et al. Re-epithelialization of cutaneous wounds in adult zebrafish com-bines mechanisms of wound closure in embryonic and adult mammals.Development 2016;143:2077e88.

Richardson R, Slanchev K, Kraus C, Knyphausen P, Eming S,Hammerschmidt M. Adult zebrafish as a model system for cutaneouswound-healing research. J Invest Dermatol 2013;133:1655e65.

Robson MC. Wound infection: a failure of wound healing caused by animbalance of bacteria. Surg Clin 1997;77:637e50.

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Schwarz DA, Lindblad WJ, Rees RS. Altered collagen metabolism and delayedhealing in a novel model of ischemic wounds. Wound Repair Regen1995;3:204e12.

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Xia YP, Zhao Y, Marcus J, Jimenez PA, Ruben SM, Moore PA, et al. Effects ofkeratinocyte growth factor-2 (KGF-2) on wound healing in an ischaemia-impaired rabbit ear model and on scar formation. J Pathol 1999;188:431e8.

This is a reprint of an article that originally appeared in the October 2018 issue of the Journal of Investigative Dermatology. It retains its original pagination here.For citation purposes, please use these original publication details: Grada A,Mervis J, Falanga V. Research TechniquesMade Simple: Animal Models ofWoundHealing. J Invest Dermatol 2018;138(10):2095e2105; doi:10.1016/j.jid.2018.08.005

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Research Techniques Made Simple: TransepidermalWater Loss Measurement as a Research Tool

Helen Alexander1, Sara Brown2, Simon Danby3 and Carsten Flohr1

Transepidermal water loss (TEWL) is the most widely used objective measurement for assessing the barrierfunction of skin in healthy individuals but also patients with skin diseases that are associated with skin barrierdysfunction, such as atopic dermatitis. TEWL is the quantity of condensed water that diffuses across a fixed areaof stratum corneum to the skin surface per unit time. The water evaporating from the skin is measured using aprobe that is placed in contact with the skin surface and contains sensors that detect changes in water vapordensity. TEWL can be measured using an open-chamber, unventilated-chamber, or condenser-chamber device.It is a sensitive measure that is affected by properties of the surrounding microclimate such as environmentalhumidity, temperature, and airflow and should be measured under controlled conditions. TEWL variessignificantly across different anatomical sites and also depends on sweat gland activity, skin temperature, andcorneocyte properties. Here we describe how to optimally use TEWL measurements as a skin research toolin vivo and in vitro.

Journal of Investigative Dermatology (2018) 138, 2295e2300; doi:10.1016/j.jid.2018.09.001

1Unit for PoLondon, UKResearch, D

CorrespondTrust and K

Abbreviatio

Journal of I

CME Activity Dates: 19 October 2018Expiration Date: 18 October 2019Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: All authors, plan-ning committee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

pulation-Based Dermatology Research, St John’s Institute of Dermato; 2Skin Research Group, School of Medicine, Ninewells Hospital & Mepartment of Infection, Immunity & Cardiovascular Disease, The Me

ence: Helen Alexander, Unit for Population-Based Dermatology Reseaing’s College London, London SE1 7EH, UK. E-mail: helen.2.alexand

ns: AD, atopic dermatitis; SC, stratum corneum; TEWL, transepiderm

nvestigative Dermatology (2018), Volume 138 ª 2018 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Nov18 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONThe outer layer of the epidermis, the stratum corneum (SC),contributes to skin barrier properties and has many protectivefunctions (Elias, 2008), including contribution to the controlof transcutaneous water loss. The movement of water acrossthe SC is primarily controlled by flattened corneocytes

le

e

surrounded by hydrophobic bilamellar lipids includingceramides, cholesterol, and free fatty acids. The permeabilitybarrier function of the skin is critical, and its impairment leadsto downstream signals that aim to restore barrier homeostasis.Transepidermal water loss (TEWL) measurement is the most

widely used objective measurement for assessing the barrier

ogy, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London,dical School, University of Dundee, Dundee, UK; and 3Sheffield Dermatologydical School, University of Sheffield, Sheffield, UK

rch, St John’s Institute of Dermatology, Guy’s and St Thomas’ NHS Foundationr@kcl.ac.uk

al water loss

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTS� TEWL measurement is used to objectively assessthe barrier function of the skin in vivo andin vitro.

� Skin diseases in which the skin barrier isdisturbed, such as atopic dermatitis (AD), contactdermatitis, and psoriasis, are associated withelevated TEWL.

� TEWL can be measured using an open-chamberdevice, an unventilated-chamber device, or acondenser-chamber device.

� TEWL is affected by properties of the surroundingmicroclimate such as environmental humidity,temperature, and airflow and should be measuredunder controlled conditions.

RESEARCH TECHNIQUES MADE SIMPLE

function of the skin (Fluhr et al., 2006). TEWL measures thequantity of water lost from inside the body by diffusion acrossthe SC. Skin barrier dysfunction results in increased TEWL.Skin diseases in which the skin barrier is disturbed, such asatopic dermatitis (AD), contact dermatitis, psoriasis, and ich-thyoses, are associated with elevated TEWL.TEWL as a measure of skin water barrier status has been

validated in both humans and mice by correlating TEWL withabsolute water loss determined gravimetrically (Fluhr et al.,2006). In addition to gauging water barrier function, in vivoTEWL measurements consistently correlate with the percuta-neous absorption of topically applied compounds (Levin andMaibach, 2005). As such, TEWL measurements can be seenas an indirect measure of skin permeability (both inside tooutside and outside to inside), which is a function of skinbarrier status. A stronger skin barrier, characterized by largersurface corneocytes, an increased number of corneocytelayers (increased path length across the SC), and/or improvedinter-corneocyte lamellar lipid matrices are linked to reducedTEWL (Damien and Boncheva, 2010). The molecular orga-nization of the SC extracellular lipid matrix into a highlyordered lamellar bilayer structure is an important determinantof TEWL (Elias, 2008). The proportion of SC composed ofalpha-phase lipid bilayers inversely correlates with TEWL.Changes in the lipid matrix structure induced by environ-mental factors such as temperature and humidity may there-fore be responsible for the differences in TEWL observedunder these conditions (Damien and Boncheva, 2010).

TEWL MEASUREMENTTEWL is not measured directly, but inferred from measuringthe change (or flux) in water vapor density at the skin surfacecompared with a point farther away from the skin (Nilsson,1977). If water loss across the SC were zero, then thehumidity in the air adjacent to the skin surface would be thesame as ambient humidity. As water loss across the SCincreases, the humidity next to the skin surface rises aboveambient humidity. This creates a humidity gradient above theskin surface that is proportional to the SC water loss (Imhofet al., 2009). Water vapor density measurements are taken

over a fixed area of SC in a fixed time period, and the units forTEWL are stated as grams of water per square meter per hour(g$me2$he1).

TEWL can be measured using an open-chamber device, anunventilated-chamber device, or a condenser-chamberdevice. Because of the sensitivity and variability in mea-surement of TEWL, usually three or more readings are takento calculate a mean value.

TEWL DEVICESOpen-chamber devices consist of a hollow cylinder that isplaced in contact with the skin (Nilsson, 1977). Water vaporfrom the skin surface diffuses through the chamber and outinto the ambient atmosphere. The humidity gradient iscalculated from temperature and relative humidity readingsfrom two sensors that are fixed at different distances from theskin surface (Figure 1a). An advantage of open-chamberdevices is that they do not occlude the skin and thereforeleave the cutaneous microclimate relatively undisturbed.One of their major limitations, however, is that they arevulnerable to environmental influences, such as disturbancefrom ambient air movements.Unventilated-chamber devices consist of a chamber with a

closed upper end, which protects from ambient air movementdisturbances. Water vapor from the skin surface collects inthe chamber, causing the humidity to rise with time. Sensorsin the chamber measure the rate of increase in relativehumidity (Figure 1b). This method requires the chamber to belifted from the skin after every reading to allow the accumu-lated water vapor to escape. These devices therefore cannotbe used for continuous TEWL measurement.The more recently developed condenser-chamber device

has become increasingly used, because it provides a dynamicreading of the transcutaneous water loss (Imhof et al., 2009).The upper end of the chamber is closed by a condenser that iscooled below the freezing point of water. The condenserremoves water vapor from the chamber, enabling continuousmeasurements to be made without the need to interruptthe measurement to allow the water vapor to escape. Thecondenser also controls the microclimate within the chamberby protecting from ambient air movement and controlling thehumidity. The water vapor density is measured in a similarway to open chamber devices by separately spaced sensors inthe chamber (Figure 1c).A number of studies have compared the performance of

different TEWL devices and found that results show goodcorrelation (Farahmand et al., 2009; Fluhr et al., 2006).However, a small comparative study of an open-chambersystem with an unventilated-chamber system and acondenser-chamber system found that the condenser-chamber system was the only device that could detect theeffect of tape-stripping on TEWL and the only device thatcould discriminate between the effects of moisturizer andpetrolatum on skin barrier integrity (Farahmand et al., 2009),suggesting that the condenser-chamber method gives greatersensitivity.

FACTORS AFFECTING TEWLTEWL has been shown to vary significantly at differentanatomical sites within an individual (Kottner et al., 2013).

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Figure 1. TEWL devices. (a) Open-chamber TEWLdevice. A hollow cylinder is placed in contact withthe skin, and water vapor diffuses through the openchamber. Spatially separated temperature andrelative humidity sensors detect the humiditygradient. (b) Unventilated-chamber TEWL device.The upper end of the chamber is closed, resulting inwater vapor collecting in the chamber. Thetemperature and relative humidity sensors detect therate of increase of relative humidity. (c) Condenser-chamber TEWL device. The upper end of thechamber is closed by a condenser that removeswater vapor from the chamber, enabling continuousTEWL measurements to be recorded. Water vapordensity is measured by sensors in the chamber andcondenser. TEWL, transepidermal water loss.

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TEWL is high at the palms, soles, axillae, and forehead andlow at the calf and forearm. The increased TEWL at sites suchas the palms and soles is linked to the low sebaceous lipidcontent at these sites (Brancaleon et al., 2001). Regional dif-ferences in TEWL may also be due to differences in sweatgland activity, occlusion, skin temperature, thickness, andmicrovasculature as well as corneocyte size, maturity, andshedding. In adults, some studies suggest that TEWLdecreases with age but others have found no associationbetween TEWL and age (Kottner et al., 2013; Zouboulis et al.,2018). Some studies have found TEWL differences in differentethnic groups. For instance, TEWL is higher in blackand Asian skin compared with Caucasian skin (Kompaoreet al., 1993). Skin care practices also affect TEWL.Detergents such as sodium lauryl sulfate can damage the skinbarrier and lead to increased TEWL, whereas emollientstransiently occlude the skin and reduce TEWL (Danby et al.,2016). Skin surface temperature and sweating additionallyalter TEWL (Pinnagoda et al., 1990). Studies have also shownseasonal variation in TEWL and that TEWL is affected bycircadian rhythm and sun exposure (Le Fur et al., 2001; Liuet al., 2010).

TEWL MEASUREMENT IN VIVOGuidelines have been developed to help control externalfactors affecting TEWL in research studies and achieve con-sistency and accuracy (Pinnagoda et al., 1990; Rogiers andEEMCO Group, 2001). The selection of the skin area to betested is important, and the volar forearm is the site used mostoften for dermatological studies. There should be an intervalof at least 12 hours between application of topical skinproducts and TEWL measurement and at least 2 hoursbetween skin washing and TEWL measurement. A room oftemperature 18e21 �C and relative humidity of 40%e60%should be used and direct light avoided. Subjects shouldacclimatize to the environment for 20e30 minutes beforeTEWL measurement. TEWL measurements should ideally betaken at the same time of day and during the same season,avoiding the summer months.Calibration of TEWL instruments is essential and depends

on the device and manufacturer (Imhof et al., 2009;Pinnagoda et al., 1990). Because of the differences in TEWLmeasurement devices and study designs, there is a lack ofconsensus regarding reference TEWL values. It is therefore

Journal of Investigative Dermatology (2018), Volume 138

recommended that baseline TEWL measurements be recor-ded and that results be interpreted as a relative change(Rogiers and EEMCO Group, 2001).

In addition to the use of basal TEWL to assess the undis-turbed permeability of the skin barrier, TEWL measurementsconducted in conjunction with controlled skin barrierperturbation by tape-stripping are used to measure skinbarrier integrity (Danby et al., 2011). Tape-stripping is aprocedure where the uppermost layers of corneocytes arepeeled away from the surface using standardized adhesivediscs, such as D-Squame discs (CuDerm, TX). Where the skindisplays reduced structural integrity, tape-stripping removesmore corneocytes, leading to a more rapid disruption of theskin barrier and, consequently, a sharper increase in TEWLwith each consecutive stripping. Initially, healthy skin is fairlyinsensitive to tape-stripping, showing the capacity of the skinto withstand mild perturbation. Disrupted skin and skin with alow structural integrity exhibit greater changes in TEWL,underpinning the increased sensitivity of the technique. Thearea under the curve for TEWL measurements made over adefined number of tape strippings can be used to reflect theoverall integrity of the SC (Figure 2). Quantifying the amountof protein removed by each tape-strip disc can similarly beused to reflect the cohesiveness of the SC (Danby et al.,2016). Combination of the TEWL and protein data can beused to estimate the thickness of the SC by using Fick’s firstlaw of diffusion (Bashir et al., 2001).

The measurement of skin barrier recovery rates after barrierimpairment can show skin barrier differences that are notseen with basal TEWL measurement alone. For instance,aging and stress lead to delayed skin barrier recovery,whereas darkly pigmented skin, independent of race,recovers more quickly after tape stripping than lightly pig-mented skin (Ghadially et al., 1995; Muizzuddin et al., 2003;Reed et al., 1995). Barrier recovery kinetics can also be usedto assess response to topical treatments and to identify themetabolic processes that maintain a functioning skin barrier(Feingold, 2009).

TEWL MEASUREMENT IN VITROTEWL has also been used as a quantitative parameterto assess skin barrier integrity and function in explantedskin (Döge et al., 2017; Sundaram et al., 2016; Zhang et al.,2018) and skin barrier formation in cultured skin models

Figure 2. TEWL measurement in conjunction with controlled skin barrier perturbation by tape-stripping is used to measure skin barrier integrity in atopicdermatitis research. The area under the curve for TEWL measurements made over a defined number of tape strippings can be used to reflect the overall integrityof the stratum corneum. AD, atopic dermatitis; AUC, area under the curve; TEWL, transepidermal water loss.

Figure 3. In vitro TEWL measurement from isolated human epidermis andrat epidermal keratinocyte organotypic cell culture epidermis (ROC). ThisTEWL measurement was used to determine the occlusive properties of lipidnanoparticle formulations (MCT, D116 [Dynasan 116, Huls and Sasol,Germany], CM/CN [CM; ICN, USA] [CN; Acros, Pittsburgh PA], GMO[Eastman, Miami, FLA]) (n ¼ 3e4) (reprinted from Kuntsche et al., 2008 withpermission). MCT, medium chain triglycerides; D116, tripalmitate; CM,cholesteryl myristate; CN, cholesteryl nonanoate; GMO, glycerol monooleate;TEWL, transepidermal water loss.

RESEARCH TECHNIQUES MADE SIMPLE

(Nolte et al., 1993) and epidermal models (Hatano et al.,2005; Kuntsche et al., 2008) in vitro.TEWL may be measured on cultured samples directly (Biox

Systems, London, UK; https://www.biox.biz/Products/ProductDetails.php), or after mounting in a Franz cell(Tewitro TW24; CourageþKhazaka Electronic, Cologne,Germany; http://www.courage-khazaka.de/index.php/en/products/scientific/382-tewitro-e), or with adaptation toallow multiple wells to be measured simultaneously (TewitroTW24). TEWL measurement has been shown to directlycorrelate with the measurement of tritiated water flux and tobe a safer and more user-friendly measurement (Elmahjoubiet al., 2009).

One advantage of TEWL measurement in vitro is that it isless sensitive to the variable of water loss by sweating thatoccurs in vivo, but repeated measurements show variation asthe sample equilibrates to ambient temperature and humidityoutside the tissue culture incubator, so equilibration timeshould be standardized across replicated experiments.The absolute TEWL measurement shows variability be-

tween replicate experiments, and the different models givedifferent TEWL measurements (Figure 3), reflecting in part thedifferent distances between water source (media and/ordermis) and the epidermal surface. Direct comparisonsbetween experimental measurements are therefore notappropriate, and it is important to include within-experimentcontrols for comparison.

CLINICAL APPLICATIONS OF TEWL MEASUREMENTSkin barrier dysfunction and increased TEWL are majorpathologic features of AD (Elias, 2008; Flohr et al., 2010).TEWL is used as a research tool to objectively assess skinbarrier function, and it can be robustly correlated with theseverity of AD and response to treatment, leading to theinclusion of the parameter in some AD severity scores(Chamlin et al., 2002; Pinnagoda et al., 1990; Rogiers andEEMCO Group, 2001; Sugarman et al., 2003). Filaggrin is akey component of the epidermal skin barrier, and up to 50%

of patients with moderate to severe AD are heterozygous forone of the filaggrin gene (FLG) loss-of-function mutations(Baurecht et al., 2007). Studies have shown that at birth, thereis no difference in TEWL between FLG mutation and FLGwild-type groups (Horimukai et al., 2016; Kelleher et al.,2015). However at 2 months, 3 months, and 6 months ofage, those carrying an FLG mutation have a significantlyhigher TEWL than those without (Flohr et al., 2010; Kelleheret al., 2015). TEWL was found to be elevated in infants withFLG-null mutations even without clinical AD, suggesting thatskin barrier impairment may precede the clinical manifesta-tion of AD. Kelleher et al. and Horimukai et al. have shown

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MULTIPLE CHOICE QUESTIONS1. How is TEWL measured?

A. By measuring the volume of water on thesurface of the skin

B. By measuring absolute water loss from theskin gravimetrically

C. By measuring relative humidity andtemperature at the skin surface to calculatethe change in water vapor density

D. By measuring evaporation of water from theskin to the atmosphere

2. What advantages do condenser-chamber TEWLdevices have over unventilated-chamber andopen-chamber devices?

A. Water can diffuse out of the chamber intothe atmosphere.

B. Continuous TEWL measurements can bemade, and disturbance from ambient airmovements is minimized.

C. The chamber is closed, allowing water vaporto accumulate in the chamber.

D. Individual TEWL measurements can be madefaster.

3. What are the suggested conditions for TEWLmeasurement?

A. Room temperature of 18e21 �C, relativehumidity of 40%e60%, and direct light;subjects should acclimatize to theenvironment for 20e30 minutes before TEWLmeasurement.

B. Room temperature of 18e21 �C, relativehumidity of 20%e30%, and avoid directlight; subjects should acclimatize to theenvironment for 20e30 minutes before TEWLmeasurement.

C. Room temperature of 18e21 �C, relativehumidity of 20%e30%, and avoid direct light;take measurement as soon as subject entersthe testing environment.

D. Room temperature of 18e21 �C, relativehumidity of 40%e60%, and avoid directlight; subjects should acclimatize to theenvironment for 20e30 minutes before TEWLmeasurement.

4. Which body regions have the highest TEWL?

A. Palms, soles, axillae, and forehead

B. Calves and forearms

C. Antecubital fossae

D. Abdomen, chest, and back

5. Which statement is true regarding TEWL in AD?

A. At 3 months of age, FLG mutation-carryinginfants do not have increased TEWL.

B. TEWL is increased at birth in FLG mutation-carrying neonates compared with FLGewild-type neonates.

C. TEWL is not a parameter in any AD severityscores.

D. TEWL measured during the first days of lifecan predict the development of AD ininfancy.

See online version of this article for a detailed explanationof correct answers.

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Journal of Investigative Dermatology (2018), Volume 138

that TEWL measured during the first days of life can predictthe development of AD in infancy, independent of FLG status.These findings suggest that TEWL could potentially be used toidentify neonates at increased risk of AD and help guideprevention strategies—for instance, with regular emollientapplication.

CONCLUSIONSTEWL is a research tool that enables objective and noninva-sive measurement of one aspect of skin barrier function indermatological research. TEWL elevation is a hallmark of ADand may precede clinical manifestation of the disease, sug-gesting that TEWL measurement may be useful in guiding ADprevention strategies.

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSSJB holds a Wellcome Trust Senior Research Fellowship in Clinical Science(106865/Z/15/Z). CF is funded through a UK National Institute for HealthResearch (NIHR) Career Development Fellowship (CDF-2014-07-037) andalso supported by the NIHR Biomedical Research Centre based at Guy’s andSt Thomas’ NHS Foundation Trust and King’s College London. He hasreceived investigator-led research funding from Sanofi. His department hasreceived clinical trial funding from Sanofi and AbbVie to test novel thera-peutics in paediatric atopic eczema patients. The views expressed are those ofthe authors and not necessarily those of the UK National Health Service, theUK Department of Health or the National Institute of Health Research.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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Danby SG, Chalmers J, Brown K, Williams HC, Cork MJ. A functionalmechanistic study of the effect of emollients on the structure and functionof the skin barrier. Br J Dermatol 2016;175:1011e9.

Döge N, Avetisyan A, Hadam S, Pfannes EKB, Rancan F, Blume-Peytavi U,et al. Assessment of skin barrier function and biochemical changes ofex vivo human skin in response to physical and chemical barrierdisruption. Eur J Pharm Biopharm 2017;116:138e48.

Elias PM. Skin barrier function. Curr Allergy Asthma Rep 2008;8:299e305.

Elmahjoubi E, Frum Y, Eccleston GM, Wilkinson SC, Meidan VM. Trans-epidermal water loss for probing full-thickness skin barrier function:correlation with tritiated water flux, sensitivity to punctures and diversesurfactant exposures. Toxicol In Vitro 2009;23:1429e35.

Farahmand S, Tien L, Hui X, Maibach HI. Measuring transepidermal waterloss: A comparative in vivo study of condenser-chamber, unventilated-chamber and open-chamber systems. Ski Res Technol 2009;15:392e8.

Feingold KR. The outer frontier: the importance of lipid metabolism in theskin. J Lipid Res 2009;50(Suppl):S417e22.

Flohr C, England K, Radulovic S, McLean WHI, Campbell LE, Barker J, et al.Filaggrin loss-of-function mutations are associated with early-onseteczema, eczema severity and transepidermal water loss at 3 months ofage. Br J Dermatol 2010;163:1333e6.

Fluhr JW, Feingold KR, Elias PM. Transepidermal water loss reflects perme-ability barrier status: validation in human and rodent in vivo and ex vivomodels. Exp Dermatol 2006;15:483e92.

Ghadially R, Brown BE, Sequeira-Martin SM, Feingold KR, Elias PM. The agedepidermal permeability barrier. Structural, functional, and lipidbiochemical abnormalities in humans and a senescent murine model.J Clin Invest 1995;95:2281e90.

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Horimukai K, Morita K, Narita M, Kondo M, Kabashima S, Inoue E, et al.Transepidermal water loss measurement during infancy can predict thesubsequent development of atopic dermatitis regardless of filaggrinmutations. Allergol Int 2016;65:103e8.

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Kelleher M, Dunn-Galvin A, Hourihane JOB, Murray D, Campbell LE,McLean WHI, et al. Skin barrier dysfunction measured by transepidermalwater loss at 2 days and 2 months predates and predicts atopic dermatitisat 1 year. J Allergy Clin Immunol 2015;135:930e35.e1.

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Kuntsche J, Bunjes H, Fahr A, Pappinen S, Ronkko S, Suhonen M, et al.Interaction of lipid nanoparticles with human epidermis and an orga-notypic cell culture model. Int J Pharm 2008;354(1e2):180e95.

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Levin J, Maibach H. The correlation between transepidermal water loss andpercutaneous absorption: an overview. J Control Release 2005;103:291e9.

Liu Z, Fluhr JW, Song SP, Sun Z, Wang H, Shi YJ, et al. Sun-induced changesin stratum corneum function are gender and dose dependent in aChinese population. Skin Pharmacol Physiol 2010;23:313e9.

Muizzuddin N, Matsui MS, Marenus KD, Maes DH. Impact of stress of maritaldissolution on skin barrier recovery: tape stripping and measurement oftrans-epidermal water loss (TEWL). Skin Res Technol 2003;9:34e8.

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Nolte CJ, Oleson MA, Bilbo PR, Parenteau NL. Development of a stratumcorneum and barrier function in an organotypic skin culture. ArchDermatol Res 1993;285:466e74.

Pinnagoda J, Tupker RA, Agner T, Serup AJ. Guidelines for transepidermalwater loss (TEWL) measurement. Contact Dermatitis 1990;22:164e78.

Reed JT, Ghadially R, Elias PM. Skin type, but neither race nor gender, influenceepidermal permeability barrier function. ArchDermatol 1995;131:1134e8.

Rogiers V, EEMCO Group. EEMCO guidance for the assessment of trans-epidermal water loss in cosmetic sciences. Skin Pharmacol Appl SkinPhysiol 2001;14:117e28.

Sugarman J, Fluhr J, Fowler A, Bruckner T, Diepgen TL, Williams ML. TheObjective Severity Assessment of Atopic Dermatitis Score. ArchDermatol 2003;139:1417e22.

SundaramH,MackiewiczN, Burton E, Peno-Mazzarino L, Lati E,Meunier S. Pilotcomparative study of the topical action of a novel, crosslinked resilienthyaluronic acid on skin hydration and barrier function in a dynamic, three-dimensional human explant model. J Drugs Dermatol 2016;15:434e41.

Zhang Q, Murawsky M, LaCount T, Kasting GB, Li SK. Transepidermal waterloss and skin conductance as barrier integrity tests. Toxicol In Vitro2018;51:129e35.

Zouboulis CC, Elewa R, Ottaviani M, Fluhr J, Picardo M, Bernois A, et al. Ageinfluences the skin reaction pattern to mechanical stress and its repairlevel through skin care products. Mech Ageing Dev 2018;170:98e105.

This is a reprint of an article that originally appeared in theNovember 2018 issue of the Journal of InvestigativeDermatology. It retains its original pagination here.For citation purposes, please use these original publication details: AlexanderH, BrownS,Danby S, Flohr C. Research TechniquesMade Simple: TransepidermalWater Loss Measurement as a Research Tool. J Invest Dermatol 2018;138(11):2295–2300; doi:10.1016/j.jid.2018.09.001

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Research Techniques Made Simple: CAR T-Cell Therapy

Haziq F. Siddiqi1, Karl W. Staser2 and Vinod E. Nambudiri1

Chimeric antigen receptor (CAR) and chimeric autoantibody receptor T-cell therapy hold great promise in thetreatment of cancer and autoimmune disease, respectively. This powerful technique involves genetically en-gineering T lymphocytes to enable selective destruction of disease-causing cells. In the current approach, apatient’s T cells are genetically engineered to express an antigen-specific antibody fragment fused to activatingcytoplasmic T-cell signaling domains. After ex vivo activation and genetic modification of a patient’s own T cells,the individually tailored CAR T cells are then infused into the patient for the selective destruction of cellsbearing the targeted antigen. CAR T cells directed against the CD19 antigen expressed on B lymphoma cellshave shown remarkable clinical efficacy in the treatment of refractory lymphoma, with two anti-CD19 CAR-Tproducts recently gaining approval from the US Food and Drug Administration. For dermatological disease,preliminary studies have shown efficacy of CAR T cells in targeting melanoma cells and the pathogenic B cells inpemphigus vulgaris. Despite its great promise, current clinical CAR T-cell (or CAR-T) therapy carries a high riskof cytokine release syndrome, a potentially fatal systemic inflammatory response that can be manifest incutaneous findings. For the dermatologist, the rapid clinical emergence of CAR-T therapy promises to treat andcure a variety of dermatological conditions, but it also requires an astute awareness of potential cutaneouscomplications in the increasing number of patients undergoing CAR-T therapy.

Journal of Investigative Dermatology (2018) 138, 2501e2504; doi:10.1016/j.jid.2018.09.002

1Brigham anWashington

Correspond

Abbreviatiopemphigus

Journal of I

CME Activity Dates: 19 November 2018Expiration Date: 18 November 2019Estimated Time to Complete: 1 hour.

Planning Committee/Speaker Disclosure: Karl Staser, MD,PhD is a consultant/advisor for RiverVest Venture Partnersand Kinetic River and has intellectual property rights/patentholder with WUSTL/WUGEN. All other authors, planningcommittee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodologieson which many diagnostic and therapeutic advances are built.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describehowthese techniquescanbeutilizedand their limitations.� Describe the potential impact of these techniques.

d Women’s Hospital, Department of Dermatology, Harvard MedicalUniversity in St. Louis School of Medicine, St. Louis, MO

ence: Vinod E. Nambudiri, 221 Longwood Ave., Boston, MA 02115

ns: BCR, B-cell receptor; CAAR, chimeric autoantibody receptor; CAvulgaris; TCR, T-cell receptor

nvestigative Dermatology (2018), Volume 138 ª 2018 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society forInvestigative Dermatology. Beaumont Health is accreditedby the ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1Credit(s)�. Physicians should claim only the creditcommensurate with the extent of their participation in theactivity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Dec18 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONChimeric antigen receptors (CARs) are fusion proteinsconsisting of an antigen-recognition domain and T-cellintracellular signaling domains. Typically, the CAR antigen-recognition domain is an antibody single-chain variable

,

fragment derived from a monoclonal antibody specific for atarget antigen such as CD19 (Levine et al., 2017). The CARintracellular portion contains T-cell signaling domains thatactivate and potentiate the T-cell response. When the CAR Tcell’s antigen-recognition domain interacts with an antigen-

School, Boston, MA; and 2Division of Dermatology, Department of Medicine,

USA. E-mail: vnambudiri@bwh.harvard.edu

R, chimeric antigen receptor; CAR-T, chimeric antigen receptor T cell; PV,

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTSWhat are the domains of a chimeric antigen receptor?CARs are made of three domains:

(1) The extracellular portion contains the antigen-recognition domain. The antigen-recognitiondomain is typically an single-chain variablefragment antibody fragment or another peptidethat recognizes autoantibodies, such as withDsg3 CAAR T cells recognizing the anti-Dsg3BCR on B cells.

(2) A transmembrane domain that anchors the CARto the cell membrane.

(3) The intracellular domain that contains a CD3zasignaling domain and costimulatory domainsthat enhance T-cell proliferation, cytokinerelease, and killing activity after antigenbinding.

What are the major potential advantages of CAR T-celltherapy in melanoma and pemphigus vulgaris?

Melanoma: In melanoma, CAR T-cell therapy in com-bination with TCRs through the use of T cells co-expressing TCR and CAR for different melanoma anti-gens may help reduce tumor evasion of the immuneresponse and reduce likelihood of recurrence.Pemphigus vulgaris: In PV, CAAR T-cell therapy may

provide a strategy to eliminate self-reactive B cellswithout systemic immunosuppression. Specifically,CAAR T cells expressing desmoglein 3 recognize andinteract with anti-desmoglein 3 on pathogenic B cellswithout inducing off-target effects. Preliminary data incell cultures and animal models have shown this strategyto successfully eliminate B cells carrying the B-cell re-ceptor against desmoglein 3.

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bearing cell, the CAR T cell’s internal signaling domainsactivate CAR T cells to proliferate, secrete cytokines, and killthe antigen-bearing target cell. Accordingly, CAR T cells canmediate efficient, antigen-specific cell killing in a major his-tocompatibility unrestricted fashion. Clinically, CAR T-celltherapy has shown high response rates in multiple hemato-logic malignancies and is undergoing investigation for thetreatment of a variety of liquid and solid tumors (Levine et al.,2017). In 2017, the US Food and Drug Administrationapproved the first anti-CD19 CAR T-cell therapies forrelapsed or refractory B-cell precursor acute lymphoblasticleukemia and diffuse large B-cell lymphoma. Moreover, arecent study showed CAR T-cell (sometimes abbreviatedCAR-T) efficacy in targeting pathogenic B cells in pemphigusvulgaris, opening exciting avenues for CAR-T therapy indermatology (Ellebrecht et al., 2016).

OVERVIEW OF CAR-T METHODOLOGYCAR designA CAR construct consists of an extracellular antigen-recognitiondomain and intracellular T-cell signaling domains (Levine et al.,2017). In the majority of current CAR designs, the antigen-

recognition domain consists of an antigen-specific single-chain var-iable fragment. However, recent studies have shown the feasibility ofalternate antigen-recognition domain strategies, as with desmoglein3 (Dsg3)-expressing CARs that direct engineered T cells to attackpemphigus vulgaris-causing B cells expressing the anti-Dsg3 B-cellreceptor (BCR) (Ellebrecht et al., 2016). A spacer or hinge links theantigen-recognition domain to a transmembrane domain, anchoringthe CAR to the T-cell membrane. The intracellular portion containsT-cell signaling domains necessary for T-cell activation. In first-generation CARs, the intracellular signaling domain consists solelyof a CD3z chain, a component of the endogenous T-cell receptor(TCR). These first-generation CARs showed minimal killing andpersistence in vivo, likely because of low-level T-cell activation andexpansion in response to tumor antigens (Jensen et al., 2010; Tillet al., 2008). Subsequent CAR designs have refined the intracel-lular signaling domain to contain co-stimulatory domains. Second-generation CARs typically contain both CD3z and 4-1BB or CD28T-cell signaling moieties, and third-generation CARs express threedomains, such as CD3z, 4-1BB, and CD28. These second- and third-generation CAR T cells have shown excellent tumor killing andpersistence in vivo, and these designs underpin the currently USFood and Drug Administrationeapproved CAR T cells (Figure 1).

CAR T-cell productionAfter designing the CAR construct, the CAR elements are cloned intoa lentiviral or retroviral backbone plasmid using standard molecularcloning techniques. The CAR and viral enzyme plasmids are trans-fected into a packaging cell line (e.g., 293T cells) that can generatelarge titers of CAR-bearing virus (Levine et al., 2017). Peripheralblood mononuclear cells derived from the patient by leukapheresisare then stimulated with anti-CD3/CD28 beads to activate andexpand T cells. During CD3/CD28 activation, the patient’s T cells aretransduced with the CAR-bearing retro or lentivirus to produce CART cells containing a stably integrated and expressed CAR. Experi-mentally, successfully transduced T cells may be further enrichedusing markers such as GFP or human CD34 fused to the CAR andintroduced during transduction. After continued expansion ex vivo,highly enriched CAR T cells undergo washing, concentration, andcryopreservation for future transfer into the patient (Levine et al.,2017) (Figure 2).

DERMATOLOGIC APPLICATIONS OF CAR T CELLSMelanomaMelanomas often develop resistance to targeted therapythrough antigen down-regulation or activation of compensa-tory signaling pathways (Sullivan and Flaherty, 2013). Takingadvantage of the T cells’ ability to reliably recognize mela-nomas, Rosenberg et al. (2008, 2011) used adoptive celltherapy to treat melanoma patients. In adoptive cell therapy,patient T cells with antitumor activity are expanded ex vivoand reinfused into the patient, with significant clinical success(Lu et al., 2017). Although adoptive cell therapy uses a singleT-cell clone expressing a single TCR (Uslu et al., 2016),developed as a multi-hit therapy to use T cells expressing botha TCR and a CAR, known as TETARs (i.e., T cells ExpressingTwo Additional Receptors). They found that co-expressingCAR and TCR in a single T cell can have stronger cytotoxiccapability than providing a mixture of T cells expressing asingle receptor. In particular, CARs targeting gp100, an

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Figure 1. CAR protein structure. (a) The CAR protein consists of a monoclonal antibody-derived ScFv ectodomain and a signaling endodomain. Theendodomain consists of a co-stimulatory domain and a T-celleactivating domain. (b) The three generations of CARs are defined by the number of signalingdomains in the endodomain. Adapted from Brudno and Kochenderfer, 2018. CAR, chimeric antigen receptor. ScFv, single-chain variable fragment.

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immunogenic antigen present in over 90% of melanomas, arevery promising (Zhang et al., 2014).

Pemphigus vulgarisPemphigus vulgaris (PV) is a blistering autoimmune diseasecaused by the production of autoantibodies against desmo-glein 3 (Dsg3), a desmosome and critical component of cell-cell junctions. PV is typically managed with systemic immu-nosuppressants, including rituximab, a monoclonal antibodytargeting CD20þ B cells. However, such therapies may havelimited efficacy and severe adverse effects.In preclinical models of PV, Ellebrecht et al. (2016) showed

that engineered T-cell therapy may be used to specificallyeliminate pathogenic antibody-producing B cells withoutsuppressing healthy B cells. The authors generated T cellsexpressing a chimeric autoantibody receptor (CAAR) selectivefor antibody-producing B cells. This CAAR consists of a PVautoantigen (Dsg3) fused to a CD137/CD3z signaling domain.In vivo, Dsg3 CAAR T cells selectively eliminated B cellsexpressing the anti-Dsg3 BCR, offering the potential for atargeted treatment approach.To identify an antigen-recognition domain with therapeutic

potential, different truncated Dsg3 fragments were engineeredas the CAAR extracellular domain. Two Dsg3 fragment-expressing CAAR constructs selectively killed anti-Dsg3 BCR-expressing B cells in vitro. In vivo, Dsg3 CAAR cells eliminatedanti-Dsg3 BCR-expressing B cells in preclinical mouse modelsusing human PV-causing anti-Dsg3 B cells, prevented blis-tering, and produced no major off-target toxicity (Ellebrechtet al., 2016; Ellebrecht and Payne, 2017). The use of CAART-cell therapy in PV may thus be a potential future clinical

Figure 2. Overview of method of preparing CAR T cells. There are five stages of CAchimeric antigen has been designed (ex vivo), the patient T cells are transduced wthen amplified in culture and are ultimately infused back into the patient. Adapte

Journal of Investigative Dermatology (2018), Volume 138

option for selectively removing self-reactive B cells withoutsystemic immunosuppression. Broadly, Ellebrecht et al.’s studyshows the potential to reengineer the CAR-T concept to targetautoantibody-expressing cells pathogenic in autoimmune dis-ease (i.e., CAAR T cells).

CURRENT AND FUTURE DIRECTIONSCAR T-cell therapy represents a powerful therapeuticapproach to multiple diseases in oncology, dermatology, andother fields. Although clinical trials have shown durable tu-mor remission in refractory B-cell malignancies, CAR-T ther-apy for cutaneous cancers and autoimmune diseases remainin preclinical testing. The density of solid tumors and non-hematopoietic organs such as the skin may complicate CART-cell tissue penetration and efficacy (Jin et al., 2016). For thisreason, novel approaches to CAR T-cell engineering and/oradjunctive therapy to increase therapeutic efficacy againstsolid tumors need exploration.With increasing clinical use, the CAR-T therapy’s efficacy

and potential toxicities are becoming more apparent. CAR Tcells induce high levels of inflammatory cytokines, which canlead to cytokine release syndrome, a potentially fatal conditionassociated with severe hypotension/tachycardia, capillaryleak, and disseminated intravascular coagulation (Bonifantet al., 2016). CAR T cells have also been reported to cause aspectrum of skin changes including rashes associated with andindependent of cytokine release syndrome. One case seriesreported CAR T-cell therapyeassociated Merkel cell carci-noma, cutaneous bacterial infections, granulomatous erup-tions, and lymphocytic eruptions mimicking the rash oflymphocyte recovery seen in individuals after hematopoietic

R T cell preparation. First, patient T cells are collected by leukapheresis. Once aith an expression vector to express the CAR fusion protein. These T cells ared from Brudno and Kochenderfer, 2018. CAR, chimeric antigen receptor.

MULTIPLE CHOICE QUESTIONS1. There are three generations of CARs. The

generation of a CAR is defined by which of thefollowing?

A. Therapeutic potency

B. Number of extracellular domains

C. Number of signaling domains

D. Likelihood of resistance by the target

2. What is the main role of CD3z in a CAR?

A. To bind the antigen

B. It is a programmed death ligand.

C. Structural stability of the CAR

D. T-cell activation

3. What is the source of T cells used in US Foodand Drug Administrationeapproved CAR T-celltherapies?

A. Blood donors

B. Patient’s thymus

C. Patient’s peripheral blood

D. Induced pluripotent stem cells

4. Which of the following targets would make alogical choice for highly selective CAAR T-celltherapy in pemphigus vulgaris?

A. All B cells expressing CD-19

B. All B cells expressing anti-desmoglein-3B-cell receptors

C. All cells expressing CD-30

D. All cells expressing CD-52

5. Which of the following cutaneous toxicities hasbeen described after CAR T-cell therapy forhematologic malignancy?

A. Multiple cutaneous melanomas

B. An eruption mimicking the rashof lymphocyte recovery

C. Eruptive epidermal inclusion cysts

D. Zosteriform dermatitis

RESEARCH TECHNIQUES MADE SIMPLE

stem cell transplantation (Rubin et al., 2016). Dermatologistsshould maintain a high suspicion for unique cutaneous toxic-ities in patients undergoing CAR-T therapy, and these unex-pected cutaneous toxicities may further inform mechanisms ofT cell-directed cutaneous inflammation.

CONCLUSIONIn summary, CAR and CAAR technology promises to effi-ciently treat and potentially cure various hematologic malig-nancies, solid tumors, autoimmune diseases, andinflammatory skin conditions. Although CAR therapy is in its

clinical infancy, preclinical advances are occurring rapidly.With increasing translation to the clinic, dermatologists arelikely to see and treat cutaneous toxicities related to CARtherapy while providing unique insights into the relationshipbetween the skin and the immune system.

CONFLICT OF INTERESTKarl Staser is a co-inventor on a pending patent related to CART technology.The other authors state no conflict of interest.

ACKNOWLEDGMENTSKWS would like to acknowledge his funding sources: the DermatologistResearch Investigator Fellowship (Dermatology Foundation), the Loan Repay-ment Program (NIH), and the Gabrielle's Angel Cancer Research Award.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

REFERENCESBonifant CL, Jackson HJ, Brentjens RJ, Curran KJ. Toxicity and management in

CAR T-cell therapy. Mol Ther Oncolytics 2016;3:16011.

Brudno JN, Kochenderfer JN. Chimeric antigen receptor T-cell therapies forlymphoma. Nat Rev Clin Oncol 2018;15:31e46.

Ellebrecht CT, Bhoj V, Nace A, Choi EJ, Mao X, Cho MJ, et al. Reengineeringchimeric antigen receptor T cells for targeted therapy of autoimmunedisease. Science 2016;353:179e84.

Ellebrecht CT, Payne AS. Setting the target for pemphigus vulgaris therapy. JCIInsight 2017;2:e92021.

Jensen MC, Popplewell L, Cooper LJ, DiGiusto D, Kalos M, Ostberg JR, et al.Antitransgene rejection responses contribute to attenuated persistence ofadoptively transferred CD20/CD19-specific chimeric antigen receptor redir-ected T cells in humans. Biol Blood Marrow Transplant 2010;16:1245e56.

Jin C, Yu D, Essand M. Prospects to improve chimeric antigen receptor T-celltherapy for solid tumors. Immunotherapy 2016;8:1355e61.

Levine BL, Miskin J, Wonnacott K, Keir C. Global Manufacturing of CAR-T celltherapy. Mol Ther Methods Clin Dev 2017;4:92e101.

Lu YC, Parker LL, Lu T, Zheng Z, Toomey MA, White DE, et al. treatment ofpatients with metastatic cancer using a major histocompatibility complexclass II-restricted T-cell receptor targeting the cancer germline antigenMAGE-A3. J Clin Oncol 2017;35:3322e9.

Rosenberg SA, Restifo NP, Yang JC, Morgan RA, Dudley ME. Adoptive celltransfer: a clinical path to effective cancer immunotherapy. Nat RevCancer 2008;8:299e309.

Rosenberg SA, Yang JC, Sherry RM. Durable complete responses in heavilypretreated patients with metastatic melanoma using T cell transferimmunotherapy. Clin Cancer Res 2011;17:4550e7.

Rubin CB, Elenitsas R, Taylor L, Lacey SF, Kulikovskaya I, Gupta M, et al.Evaluating the skin in patients undergoing chimeric antigen receptormodified T-cell therapy. J Am Acad Dermatol 2016;75:1054e7.

Sullivan RJ, Flaherty KT. Resistance to BRAF-targeted therapy in melanoma.Eur J Cancer 2013;49:1297e304.

Till BG, Jensen MC, Wang J, Chen EY, Wood BL, Greisman HA, et al.Adoptive immunotherapy for indolent non-Hodgkin lymphoma andmantle cell lymphoma using genetically modified autologous CD20-specific T cells. Blood 2008;15:2261e71.

Uslu U, Gerer K, Dorrie J, Schaft N. Combining a chimeric antigen receptorand a conventional T-cell receptor to generate T cells expressing twoadditional receptors (TETARs) for a multi-hit immunotherapy of mela-noma. Exp Dermatol 2016;25:872e9.

Zhang G, Wang L, Cui H, Wang X, Zhang G, Ma J, et al. Anti-melanomaactivity of T cells redirected with a TCR-like chimeric antigen receptor.Sci Rep 2014;4:3571.

This is a reprint of an article that originally appeared in theDecember 2018 issue of the Journal of InvestigativeDermatology. It retains its original pagination here.For citation purposes, please use these original publication details: Siddiqi HF, Staser KW,Nambudiri VE. Research TechniquesMade Simple: CAR T-Cell Ther-apy. J Invest Dermatol 2018;138(12):2501e2504; doi:10.1016/j.jid.2018.09.002

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4

RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple:Network Meta-Analysis

Jennifer Watt1,2,3, Andrea C. Tricco3,4, Sharon Straus1,2,3, Areti Angeliki Veroniki3,5,6,Gary Naglie1,2,7 and Aaron M. Drucker2,8,9

When making treatment decisions, it is often necessary to consider the relative efficacy and safety ofmultiple potential interventions. Unlike traditional pairwise meta-analysis, which allows for a comparisonbetween two interventions by pooling head-to-head data, network meta-analysis (NMA) allows for thesimultaneous comparison of more than two interventions and for comparisons to be made betweeninterventions that have not been directly compared in a randomized controlled trial. Given these advan-tages, NMAs are being published in the medical literature with increasing frequency. However, there areimportant assumptions that researchers and knowledge users (e.g., patients, clinicians, and policy makers)must consider when conducting and evaluating an NMA: network connectivity, homogeneity, transitivity,and consistency. There are also multiple NMA outputs that researchers and knowledge users shouldfamiliarize themselves with in order to understand NMA results (e.g., network plots, mean ranks). Our goalsin this article are to: (i) demonstrate how NMAs differ from pairwise meta-analyses, (ii) describe types ofevidence in a NMA, (iii) explain NMA model assumptions, (iv) provide readers with an approach to inter-preting a NMA, (v) discuss areas of ongoing methodological research, and (vi) provide a brief overview ofhow to conduct a systematic review and NMA.

Journal of Investigative Dermatology (2019) 139, 4e12; doi:10.1016/j.jid.2018.10.028

1Division ofUniversity oUniversity oReproductivSciences, ToInstitute, Wo

Correspondwchospital.c

Abbreviatio

Journal of I

CME Activity Dates: 19 December 2018Expiration Date: 18 December 2019Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Aaron Ducker, MDis a consultant/advisor for Sanofi-Aventis. All other authors,planning committee members, CME committee members andstaff involved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, residents,fellows, and related healthcare providers, seeks to reduce thegrowing divide between dermatology clinical practice and thebasic science/current research methodologies on which manydiagnostic and therapeutic advances are built.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

Geriatric Medicine, Department of Medicine, University of Toronto,f Toronto, Toronto, Canada; 3Li Ka Shing Knowledge Institute, St. Mf Toronto, Toronto, Canada; 5Department of Primary Education, Sche and Developmental Biology, Department of Surgery and Cancer,ronto, Canada; 8Division of Dermatology, Department of Medicine, Wmen’s College Hospital, Toronto, Canada

ence: Aaron Drucker, Women’s College Hospital, 76 Grenville Streea

ns: NMA, network meta-analysis; RCT, randomized controlled trial

nvestigative Dermatology (2019), Volume 139 ª 2018 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Jan19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

Toronto, Canada; 2Institute for Health Policy, Management and Evaluation,ichael’s Hospital, Toronto, Canada; 4Dalla Lana Faculty of Public Health,ool of Education, University of Ioannina, Ioannina, Greece; 6Institute ofFaculty of Medicine, Imperial College, London, England; 7Baycrest Healthomen’s College Hospital, Toronto, Canada; and 9Women’s College Research

t, 6th Floor, Toronto, Ontario M5S1B2, Canada. E-mail: aaron.drucker@

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTSComparing pairwise meta-analysis and NMA� Pairwise meta-analyses allow evidencecomparing two interventions to be synthesized;NMAs are used to compare more than twointerventions—some of which have not beendirectly compared in previous RCTs.

� NMAs can be used to rank interventions in termsof their relative efficacy or safety.

Limitations� Assumptions underlying NMAs must be carefullyconsidered, such as transitivity and consistency,because if these assumptions are not met, it mayjeopardize the conclusions of NMA.

� RCTs included in a NMA are subject to the samebiases as those included in pairwise meta-analyses and critical appraisal remains animportant component of a well-conductedsystematic review and NMA.

RESEARCH TECHNIQUES MADE SIMPLE

INTRODUCTIONA growing number of network meta-analyses (NMAs) arebeing published in the medical literature (Zarin et al., 2017).NMAs offer a way to make comparisons between many in-terventions simultaneously, helping to synthesize largeamounts of data relating to clinical outcomes. NMAs can also

Table 1. Comparing Pairwise and Network Meta-AnalysisVariable Pairwise meta-analysis

Number of comparators 2Questions answered byanalysis method

What is the efficacy or risk of harm associated wone intervention compared to another?

Systematic reviewquestion format

PICO

Risk of bias appraisal Cochrane Risk of Bias Tool for RCTsAssumptions Homogeneity

Influential biases Publication bias and small-study effectsConfoundingSelection bias

Information biasModel outputs Summary effect estimates

(e.g., OR, MD, SMD) and forest plotFunnel plot

Limitations Effect modifiers create heterogeneityBiases can generate misleading results

Reporting guidelines PRISMA

Abbreviations: MD, mean difference; NMA, network meta-analysis; OR, odds rPreferred Reporting Guidelines for Systematic Reviews and Meta-Analyses; RCTsurface under the cumulative ranking curve.

make indirect comparisons between interventions that havenot been compared in randomized controlled trials (RCTs)and rank interventions in terms of their relative efficacy orsafety. While there are clear advantages to NMAs, theirconduct and interpretation is more complex than that ofpairwise meta-analyses. Therefore, it is important for thoseconducting and reading NMAs to learn how to understandand interpret the findings. In this article, we will: (i) delineatehow NMAs differ from pairwise meta-analyses, (ii) describetypes of evidence in a NMA, (iii) explain NMA model as-sumptions, (iv) provide readers with an approach to inter-preting an NMA, (v) discuss areas of ongoing methodologicalresearch, and (vi) provide a brief overview of how to conducta systematic review and NMA. Two NMAs on treatments forpsoriasis will be used to illustrate these concepts (Jabbar-Lopez et al., 2017; Reich et al., 2012).

COMPARING PAIRWISE META-ANALYSIS AND NMAPairwise meta-analysis and NMA are compared and con-trasted in Table 1. Pairwise meta-analyses are applied whenthe desired end point is to derive a summary effect estimateacross a number of studies that compare the same two in-terventions (Figure 1a) (Abuabara et al., 2012). However, formany comparative effectiveness questions, the goal is tounderstand the relative efficacy and safety of more than twointerventions. For example, therapeutic decision making fora patient with moderate to severe chronic plaque psoriasisrequires comparison of all possible interventions, includingadalimumab, etanercept, other biologics, traditional sys-temic medications, and small moleculeetargeted agents.

Network meta-analysis

>2ith Which interventions are efficacious and/or safe?

What intervention is the most efficacious and/or safe?What is the comparative efficacy and/or safety between two

interventions that hasn’t been compared directly?Modified PICO to accommodate additional treatment comparisons

Cochrane Risk of Bias Tool for RCTsNetwork connectivity

HomogeneityTransitivityConsistency

Publication bias and small-study effectsConfoundingSelection bias

Information biasNetwork plot

Transitivity plot or tableSummary effect estimates (e.g., OR, MD, SMD) and forest plot

Ranking statistic: mean rank, SUCRA value or P-scoreInconsistency plot

Comparison-adjusted funnel plotEffect modifiers create heterogeneity and/or inconsistency

Biases can generate misleading resultsPRISMA-NMA

atio; PICO, population, intervention(s), comparator(s), outcome(s); PRIMSA,, randomized controlled trial; SMD, standardized mean difference; SUCRA,

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Figure 1. Illustration of intervention comparisons in pairwise and networkmeta-analysis. (a) A pairwise comparison between interventions 1 and 2. (b)Two direct comparisons (intervention 1 vs. 2 and intervention 2 vs. 3) and oneindirect comparison (intervention 1 vs. 3) in a network meta-analysis. (c) Threedirect comparisons (intervention 1 vs. 2, intervention 2 vs. 3, and intervention1 vs. 3) that form a closed loop.

6

RESEARCH TECHNIQUES MADE SIMPLE

This can be accomplished with NMA, from which summaryeffect estimates can be derived across more than two in-terventions, some of which have never been compareddirectly. Like pairwise meta-analyses, NMAs can be con-ducted in a frequentist or Bayesian framework (Chaimaniet al., 2013; Dias et al., 2018; van Valkenhoef andKuiper, 2016).

DIRECT AND INDIRECT EVIDENCEEstimates of relative efficacy or safety from NMA models canbe derived by combining both direct and indirect evidencefrom intervention comparisons that form a connectednetwork (Figure 2) (see section Assumptions of NetworkMeta-Analysis). Direct evidence describes data taken from atleast one RCT. Indirect evidence is derived from NMAmodels to describe the relative efficacy or safety for inter-vention comparisons that have not been studied in an RCT(Figure 1b). When a comparison is informed by both directand indirect evidence, this is referred to as a mixed effectestimate (Dias et al., 2018). For example, in the NMA

Figure 2. Examples of network plots. Connected network plots (Jabbar-Lopez etlines indicate that these two interventions have previously been compared directlyevaluating this treatment and the lines are weighted by the number of studies evalreporting the outcome of interest: (a) clear/nearly clear (minimal residual activity/P(b) mean change in the Dermatology Life Quality Index, and (c) withdrawal dueixekizumab; MTX, methotrexate; PBO, placebo; SEC, secukinumab; UST, ustekin

Journal of Investigative Dermatology (2019), Volume 139

conducted by Jabbar-Lopez et al. (2017), on the evaluationof biologic therapies for psoriasis, there was no RCT evi-dence comparing adalimumab and etanercept directly forthe outcome of “clear/nearly clear”; however, there weredirect comparisons between (i) adalimumab and placeboand (ii) etanercept and placebo. Authors were able to derivean indirect effect estimate comparing adalimumab and eta-nercept because each intervention had been compared to acommon intervention (placebo) (Figure 2) (Jabbar-Lopezet al., 2017).

ASSUMPTIONS OF NMAThere are four key assumptions of NMAs: (i) network con-nectivity, (ii) homogeneity, (iii) transitivity, and (iv) consis-tency (Table 2). The requirement for network connectivity isunique to NMA. Interventions must be connected to thenetwork to draw any conclusions about their direct and in-direct relationships with other interventions. In Figure 2, eachintervention is connected to at least one other intervention ineach network. If a treatment comparison is not connected toany other treatments in the network, it cannot be a part of theNMA.Readers are likely familiar with the concept of homoge-

neity: the true intervention effect should be sufficiently similaracross all studies making a direct comparison between thesame two intervention groups. Similar to pairwise meta-analyses, different potential sources of heterogeneity mustbe considered in studies included in NMAs: clinical, meth-odological, and statistical. If heterogeneity is anticipated be-tween studies, then a random-effects as opposed to fixed-effects model should be implemented (Higgins and Green,2011).The assumptions of transitivity and consistency refer to our

assessment of potential clinical and methodological effectmodifiers across a network of interventions. In assessingtransitivity, a judgment must be made about the distribution ofeffect modifiers and how they might influence direct andindirect effect estimates. For example, if all patients in onepsoriasis intervention comparison have severe disease at

al., 2017). Nodes represent individual interventions and nodes connected byin a study. In these examples, the nodes are weighted by the number of studiesuating this treatment comparison. Each panel is a network plot of interventionssoriasis Area and Severity Index >90/0 or 1 on Physician’s Global Assessment),to adverse events. ADA, adalimumab; ETA, etanercept; INF, infliximab; IXE,umab.

Table 2. Questions to Consider When Assessing the Assumptions of a Network Meta-AnalysisAssumption Questions to consider

Homogeneity Is there any clinical, methodological, or statistical heterogeneity between studies that compare the same interventions?Are there effect modifiers (e.g., age, gender, illness severity) between studies making the same treatment comparison that

could influence the summary effect estimate?Network connectivity Do all of the interventions form a connected network (as in Figure 2)?Transitivity Is there an imbalance in effect modifiers among studies included in the network?

In theory, could any patient randomized in one study within a network have been randomized to any of theother studies in this same network?

Consistency Where possible to assess, are the direct and indirect effect estimates from closed loops in thenetwork in agreement?

RESEARCH TECHNIQUES MADE SIMPLE

baseline (Interventions 1 vs. 2), while all patients in the othertwo treatment comparisons in a loop have moderate diseaseat baseline (interventions 1 vs. 3 and 2 vs. 3), this violates thetransitivity assumption. When there are imbalances in effectmodifiers across the network, subgroup analyses or meta-regression could be used to explore their influence on NMAeffect estimates, or perhaps the NMA should not beconducted.Consistency is the statistical measure of transitivity.

There may be inconsistency in a closed network loop ifthere is an imbalance of effect modifiers across treatmentcomparisons. In essence, direct and indirect effect esti-mates can be compared within a network to assess theirlevel of disagreement. There are tests that assess for con-sistency in a network as a whole (global tests) or at certainpaths (e.g., closed loops) of a network (local tests) (Diaset al., 2018). For example, the results of a loop-specificapproach to the assessment of inconsistency (local test)are presented in Figure 3. There is inconsistency in the

Figure 3. Example of an inconsistency plot. This is an example of aninconsistency plot with closed triangular loops of treatment comparisonsevaluating the Psoriasis Area and Severity Index 75 at 12/16 weeks (Jabbar-Lopez et al., 2017). The x-axis represents the scale for the IFs. The PBO-INF-MTX loop shows evidence of inconsistency between direct and indirectevidence because the 95% CI for the IF does not include zero. There is nosignificant inconsistency identified in any of the other loops. ADA,adalimumab; CI, confidence interval; ETA, etanercept; IF, inconsistencyfactor; INF, infliximab; IXE, ixekizumab; MTX, methotrexate; PBO, placebo;SEC, secukinumab; UST, ustekinumab.

closed loop containing three comparisons: placebo-methotrexate, placebo-infliximab, and methotrexate-infliximab. This means that the direct and indirect effectestimates of one of the treatment comparisons within thisclosed loop are significantly different from one another(the inconsistency factor’s 95% confidence interval doesnot cross zero). There is no inconsistency identified in theother closed loops. It is possible that statistical tests ofconsistency may fail to identify inconsistency; therefore, itis important to consider whether the transitivity assump-tion has been met prior to undertaking an NMA.RCTs in an NMA are subject to the same biases as those

included in pairwise meta-analyses. Critical appraisal of RCTSin an NMA is important because studies at high risk of biascan lead to violations of the homogeneity, transitivity, andconsistency assumptions. For example, if indirect evidencefrom a closed network loop of studies at low risk of bias in allaspects of critical appraisal did not show a significant benefitto receiving treatment, but one study (direct evidence) at highrisk of bias from lack of participant and outcome assessorblinding found a benefit to receiving treatment, this willviolate the transitivity (and possibly the consistency)assumption. Similarly, between-study heterogeneity will becreated if one study at high risk of bias due to lack ofparticipant and outcome assessor blinding found a benefit toreceiving a treatment, while a second study that was at lowrisk of bias on these aspects of critical appraisal did not findsuch a benefit.

INTERPRETING NMAA number of different measures of intervention efficacyand safety can be derived from NMAs (Table 3) (Diaset al., 2018). Figures and explanations for network plots(Figure 2), surface under the cumulative ranking curves(Figure 4), an inconsistency plot (Figure 3), and acomparison-adjusted funnel plot (Figure 5) are provided(Jabbar-Lopez et al., 2017). By convention, a higher meanrank or greater surface under the cumulative rankingvalue indicates that an intervention is either more effica-cious or safer (Dias et al., 2018). While most people arefamiliar with the interpretation of a frequentist effect es-timate, people may be less familiar with the interpretationof a Bayesian effect estimate. Reich et al. (2012) reportedthe mean relative risk (and 95% credible interval) of 50%,75%, and 90% reductions in the Psoriasis Area andSeverity Index for patients with moderate to severe

www.jidonline.org 7

Table 3. Commonly Reported Network Meta-Analysis OutputsNetwork meta-analysis output Description Interpretation

Network plot A diagram depicting how interventions (nodes) areconnected to one another through direct comparisons

(lines) (see Figure 2)

Provides an overview of the available evidence; a networkestimate of an intervention’s relative efficacy or safety

compared to other interventions in the network can only becalculated if it is connected to the network

Transitivity plot or table A table or plot summarizing potential effect modifiersacross studies

Studies in each network should appear sufficiently similar sothat the observed treatment effects are the result of receivingeach treatment and not an imbalance in effect modifiers

Summary effect estimate Estimate of the relative efficacy of interventions in thenetwork (e.g., OR, MD, SMD, HR) compared to othernetwork interventions, reported with a measure ofuncertainty (e.g., confidence/credible intervals or

predictive intervals)

Same interpretation as a summary effect estimate in apairwise meta-analysis

Ranking statistics Frequently presented as a mean/median rank, SUCRAvalue (or P-score) or probability of being the best

treatment

An intervention with a higher treatment ranking, SUCRAvalue, or probability of being the best is more efficacious

or more likely to cause harmInconsistency plot A plot reporting the inconsistency factors (absolute difference

between direct and indirect effect estimates) for eachcomparison in a closed network loop (see Figure 3)

An inconsistency factor with a confidence interval thatdoes not include zero indicates that there is significant

inconsistency between direct and indirect effect estimatesComparison-adjustedfunnel plot

Similar to a funnel plot in pairwise meta-analyses;however, the x-axis is the difference between each study-specific effect estimate and pooled effect estimate for each

comparison and comparisons havebeenordered in ameaningfulway (e.g., chronological treatment order) (see Figure 5)

Asymmetry in the plot indicates publicationbias/small-study effects

Abbreviations: HR, hazard ratio; MD, mean difference; NMA, network meta-analysis; OR, odds ratio; SMD, standardized mean difference; SUCRA, surfaceunder the cumulative ranking curve.

Figure 4. Examples of SUCRA curves. SUCRA curves of treatments evaluating the Psoriasis Area and Severity Index 75 at 12/16 weeks (Jabbar-Lopez et al.,2017). The cumulative probability that each treatment is ranked among the top n (e.g., 1, 2, ., 8) treatments (y-axis) is plotted against each possible rank (x-axis)for treatments in the network. Predictive probabilities incorporate the uncertainty in our network estimates from heterogeneity. IXE has the highest SUCRA value(96.4%) and PBO has the lowest SUCRA value (0%). ADA, adalimumab; ETA, etanercept; INF, infliximab; IXE, ixekizumab; MTX, methotrexate; PBO, placebo;SEC, secukinumab; SUCRA, Surface Under the Cumulative Ranking; UST, ustekinumab.

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RESEARCH TECHNIQUES MADE SIMPLE

Figure 5. Example of a comparison-adjusted funnel plot. This is an exampleof a comparison-adjusted funnel plot of treatment comparisons evaluating thePsoriasis Area and Severity Index 75 at 12/16 weeks (Jabbar-Lopez et al.,2017). Comparisons are color-coded as per the legend at the bottom of thefigure. The y-axis represents the standard error of each study-specific effectestimate. The x-axis represents the difference between the ln(OR) for eachstudy-specific effect estimate and the pooled effect estimate for eachcomparison (e.g., all of the study-specific estimates reporting on the PBO vs.ADA comparison). The blue diagonal line represents a linear regression of thex-axis variable on the y-axis variable. The paucity of studies in the bottom leftof the plot indicates there may be small studies missing that would havefavored established treatments. ADA, adalimumab; ETA, etanercept; INF,infliximab; IXE, ixekizumab; MTX, methotrexate; OR, odds ratio; PBO,placebo; SEC, secukinumab; UST, ustekinumab.

Figure 6. Example of a rank-heat plot. This is an example of a rank-heat plot of oEach ring represents a different outcome. Outcomes are also specified in the legaccording to their surface under the cumulative ranking curve values. Higher suefficacious and safer treatments. Uncolored areas indicate that the treatment wasA1c; bid, twice daily, OD, once daily; qid, four times per day.

RESEARCH TECHNIQUES MADE SIMPLE

psoriasis receiving biologics. In this case, the relative riskvalue represents the mean of the relative risk posteriordistribution for each relative treatment effect, and the95% credible interval represents the range of valueswithin which there is a 95% probability that the truevalue of the relative risk is found, given the observeddata. In contrast, Jabbar-Lopez et al. (2017) used a fre-quentist NMA approach. In a frequentist framework, the95% confidence interval means that there is a 95%chance of the true relative risk value being found withinthe intervals, given repeated randomized sampling. Fre-quentist modeling treats data as random and parametersas fixed unknown constants, whereas, Bayesian modelingtreats data as fixed and parameters as random (Kadane,1995).Knowledge users can use the International Society for

Pharmacoeconomics and Outcomes Research tool forinterpreting NMAs in health care decision making or theJournal of the American Medical Association Users’ Guideto the Medical Literature on NMAs for interpreting andcritically appraising a systematic review and NMA (Jansenet al., 2014; Mills et al., 2012). The GRADE (Grades ofRecommendation, Assessment, Development and Evalua-tion) approach has also been extended to assess the cer-tainty of NMA results. It provides a framework fordetermining the quality of evidence in NMA-derived effectestimates for each outcome (Brignardello-Petersen et al.,2018; Salanti et al., 2014).

utcomes associated with insulin use in patients with type 1 diabetes mellitus.end. Each “slice” represents a different treatment. Treatments are rankedrface under the cumulative ranking curve values (in green) indicate morenot included in the network meta-analysis of that outcome. A1c, hemoglobin

www.jidonline.org 9

Table 4. Conducting a Systematic Review and Network Meta-AnalysisSteps to follow when conducting a systematic review and network meta-analysis

1. Follow a modified PICO format when developing clinical questions for systematic reviews and NMAs because you are considering multiple interventionand comparator groups.

2. Register your systematic review and NMA protocol with PROSPERO and consider publishing the protocol in a peer-reviewed journal.3. Develop a comprehensive literature search strategy that will encompass all of the interventions and outcomes of interest.4. Complete all steps relating to article screening, data abstraction, and risk of bias appraisal independently in duplicate.5. Inspect network plots to ensure all interventions form a connected network.6. Make judgments concerning the homogeneity and transitivity assumptions prior to conducting NMA. Be explicit about how you model heterogeneity in

your NMA if you implement a random-effects model.7. Describe any assessments of global and local inconsistency. If there is inconsistency in your NMA, state how this is addressed.8. Assess for small-study effects and publication bias by using a plot such as the comparison-adjusted funnel plot.9. Present summary effect estimates for interventions and an estimate of heterogeneity. You can also present ranking statistics such as a mean rank and a

SUCRA value for each intervention.10. Follow the recommendations of the PRISMA extension statement for the reporting of NMAs when submitting your systematic review and NMA for

publication (Hutton et al., 2015).

Abbreviations: NMA, network meta-analysis; PICO, population, interventions, comparators, outcome(s); PRISMA, Preferred Reporting Guidelines forSystematic Reviews and Meta-Analyses; PROSPERO, International Prospective Register of Systematic Reviews; SUCRA, surface under the cumulative rankingcurve.

10

RESEARCH TECHNIQUES MADE SIMPLE

AREAS OF ONGOING METHODOLOGICAL RESEARCH INNMAThere remain a number of questions about how to applyNMA methods in clinical and policy decision making. Forexample, what is the best way to present NMA results toknowledge users? In addition to reporting summary effectestimates, is it best to report all of the surface under the cu-mulative ranking curve values individually or should amethod like a rank-heat plot be utilized (Veroniki et al.,2016a)? A rank-heat plot is a collated graphical representa-tion of ranking statistics demonstrating the comparative effectof interventions on a number of outcomes (Figure 6). Howcan data from non-randomized studies be incorporated intoNMAs? For adverse event data, in particular, this is animportant topic because many RCTs are underpowered todetect the potential for harm. Several models have beenproposed to include non-randomized studies in NMAs: (i)naïve pooling, (ii) data from non-randomized studies as priorinformation, and (iii) a three-level hierarchical model with anadditional level of uncertainty to account for the inclusion ofdifferent study designs (Schmitz et al., 2013). Lastly, how canindividual patient-level data best be included in NMAs toaccount for potential effect modifiers? Meta-analysts are usingseveral methods to incorporate individual patient-level data,including one- and two-stage Bayesian hierarchical NMAmodels (Veroniki et al., 2016b).

CONDUCTING A SYSTEMATIC REVIEW AND NMAWe provide an overview of the steps necessary to conducta systematic review and NMA in Table 4. There arestatistical packages available to conduct frequentist andBayesian NMAs (Chaimani et al., 2013; van Valkenhoef andKuiper, 2016). In conducting a Bayesian NMA, specialconsideration needs to be given to the choice of prior infor-mation for stochastic model parameters (Dias et al., 2018).Reich et al. (2012) implemented vague prior distributions forstudy-specific baselines in their NMA of biologic treatmentsfor moderate to severe psoriasis, but minimally informative

Journal of Investigative Dermatology (2019), Volume 139

and informative priors are also used in Bayesian NMAs (Diaset al., 2018; Reich et al., 2012).

SUMMARYResearchers may wish to undertake a systematic review andNMA because they can make indirect comparisons betweeninterventions that have not been previously compared inRCTs, compare the relative efficacy or safety of more than twointerventions simultaneously, and rank interventions in termsof their relative efficacy or safety. Much work has been doneto improve the reporting and interpretability of NMA results;however, researchers and knowledge users must be cautiouswhen reading NMA results and carefully consider many of thesame limitations that face pairwise meta-analyses, includingpotential threats to the validity of meta-analytic findings fromsystematic biases.

CONFLICT OF INTERESTAaron M. Drucker served as an investigator and has received research fundingfrom Sanofi and Regeneron and has been a consultant for Sanofi, RTI HealthSolutions, Eczema Society of Canada and Canadian Agency for Drugs andTechnology in Health. He has received honoraria from Astellas Canada, PrimeInc, Spire Learning, CME Outfitters, and Eczema Society of Canada. JenniferWatt is funded by a doctoral research award from the Canadian Institutes ofHealth Research and the University of Toronto Department of Medicine EliotPhillipson Clinician Scientist Training Program. Andrea C. Tricco is funded bya Tier 2 Canada Research Chair in Knowledge Synthesis. Andrea C. Triccoreceives funding from the Government of Canada through a Canada ResearchChair in Knowledge Synthesis. Sharon Straus is funded by a Tier 1 CanadaResearch Chair in Knowledge Translation. The remaining authors state noconflict of interest.

AUTHOR CONTRIBUTIONSJennifer Watt drafted the manuscript. Jennifer Watt, Andrea C. Tricco, SharonStraus, Areti Angeliki Veroniki, Gary Naglie, and AaronM. Drucker contributed tothe conception, design, and critical revision of the manuscript, and approved thefinal manuscript.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

MULTIPLE CHOICE QUESTIONS1. Which of the following are advantages of

conducting a network meta-analysis ascompared to a pairwise meta-analysis?

A. Make indirect comparisons betweeninterventions that have not been previouslycompared in randomized controlled trials.

B. Rank interventions in terms of their relativeefficacy or safety.

C. Increase the precision of our summary effectestimates by including both direct andindirect evidence.

D. All of the above

2. You read an article reporting the results of asystematic review and network meta-analysis.The authors report there was no inconsistencydetected in their network meta-analysis models.You should:

A. Accept the network meta-.analysis results asrobust because there was no inconsistencyidentified

B. Read further in the study methods andresults section to see if the authors evaluatedthe transitivity assumption prior toconducting the network meta-analysis.

C. Consider the similarities and differencesbetween the studies included in the networkmeta-analysis to evaluate the transitivityassumption.

D. B and C

3. Which of the following model outputs arecommon to both pairwise and networkmeta-analysis?

A. Summary effect estimate (e.g., odds ratio,mean difference)

B. Mean rank

C. Surface under the cumulative rankingcurve value

D. Inconsistency plot

4. Which of the following scenarios best describesa homogeneous comparison?

A. The mean age of patients enrolled in studiesevaluating comparison AB is 65 years;whereas, the mean age of patients enrolled instudies evaluating comparison AC is 70 years.

B. Among three studies evaluating comparisonAB, the mean age of patients enrolled instudy #1 is 65 years, the mean age of patientsenrolled in study #2 is 66 years, and the meanage of patients enrolled in study #3 is 63years.

C. The mean age of patients enrolled in studiesevaluating comparison AB is 65 years;whereas, the mean age of patients enrolled instudies evaluating comparison AC is 66 years.

D. Among three studies evaluating comparisonAB, the mean age of patients enrolled instudy #1 is 65 years, the mean age of patientsenrolled in study #2 is 45 years, and the meanage of patients enrolled in study #3 is 80years.

5. You conduct a network meta-analysis on thecomparative risk of death from new drugs usedto treat atopic dermatitis. The mean ranks forfour of the new drugs are as follows:

Drug A 6.2

Drug B 3.4

Drug C 8.1

Drug D 1.5

Which of the following is true?

A. Drug A is associated with a greater risk ofdeath compared to Drug B.

B. Drug D is associated with a lower risk ofdeath compared to Drug C.

C. Drug A is associated with a lower risk ofdeath compared to Drug B.

D. Drug D is associated with a lower risk ofdeath compared to Drug A.

RESEARCH TECHNIQUES MADE SIMPLE

REFERENCESAbuabara K, Freeman EE, Dellavalle R. The role of systematic reviews and

meta-analysis in dermatology. J Invest Dermatol 2012;132(11):e2.

Brignardello-Petersen R, Bonner A, Alexander PE, Siemieniuk RA,Furukawa TA, Rochwerg B, et al. Advances in the GRADE approach torate the certainty in estimates from a network meta-analysis. J Clin Epi-demiol 2018;93:36e44.

Chaimani A, Higgins JP, Mavridis D, Spyridonos P, Salanti G. Graphical toolsfor network meta-analysis in STATA. PLoS One 2013;8(10):e76654.

Dias S, Ades AE, Welton NJ, Jansen JP, Sutton AJ. Network Meta-Analysis forDecision-Making. Hoboken, NJ: Wiley; 2018.

Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of In-terventions. Version 5.1.0. Updated March 2011.

Hutton B, Salanti G, Caldwell DM, Chaimani A, Schmid CH, Cameron C,et al. The PRISMA extension statement for reporting of systematic reviewsincorporating network meta-analyses of health care interventions:checklist and explanations. Ann Intern Med 2015;162:777e84.

Jabbar-Lopez ZK, Yiu ZZN, Exton LS, Firouz Mohd Mustapa M,Samarasekera E, David Burden A, et al. Quantative evaluation of biologictherapy options for psoriasis: a systematic review and network meta-analysis. J Invest Dermatol 2017;137:1646e54.

Jansen JP, Trikalinos T, Cappelleri JC, Daw J, Andes S, Eldessouki R, et al.Indirect treatment comparison/network meta-analysis study question-naire to assess relevance and credibility to inform health care decisionmaking: an ISPOR-AMCP-NPC Good Practice Task Force Report. ValueHealth 2014;17:157e73.

Kadane JB. Prime Time for Bayes. Control Clin Trials 1995;16:313e8.

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Mills EJ, Ioannidis JPA, Thorlund K, Schunemann HJ, Puhan MA, Guyatt GH.How to use an article reporting a multiple treatment comparison meta-analysis. JAMA 2012;308:1246e53.

Reich K, Burden AD, Eaton JN, Hawkins NS. Efficacy of biologics in thetreatment of moderate to severe psoriasis: a network meta-analysis ofrandomized controlled trials. Br J Dermatol 2012;166:179e88.

Salanti G, Del Giovane C, Chaimani A, Caldwell DM, Higgins JP. Evaluatingthe quality of evidence from a network meta-analysis. PLoS One2014;9(7):e99682.

Schmitz S, Adams R, Walsh C. Incorporating data from various trial designsinto a mixed treatment comparison model. Stat Med 2013;32:2935e49.

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Van Valkenhoef G, Kuiper J. Package ’gemtc’. December 23, 2016. https://cran.r-project.org/web/packages/gemtc/gemtc.pdf. Accessed: November19, 2018.

Veroniki AA, Straus SE, Fyraridis A, Tricco AC. The rank-heat plot is a novelway to present the results from a network meta-analysis including mul-tiple outcomes. J Clin Epidemiol 2016a;76:193e9.

Veroniki AA, Straus S, Soobiah C, Elliot MJ, Tricco AC. A scoping review ofindirect comparison methods and applications using individual patientdata. BMC Med Res Methodol 2016b;16(47).

Zarin W, Veroniki AA, Nincic V, Varaei A, Reynen E, Motiwala SS, et al.Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review. BMC Med 2017;15(3):61.

This is a reprint of an article that originally appeared in the January 2019 issue of the Journal of InvestigativeDermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Watt J, Tricco AC, Straus S, Veroniki AA, Naglie G, Drucker AM. Research Techniques MadeSimple: Network Meta-Analysis. J Invest Dermatol 2019;139(1):4e12; doi:10.1016/j.jid.2018.10.028

RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple:Itch Measurement in Clinical Trials

Stephen Erickson1,2 and Brian S. Kim1,3,4,5

Chronic itch, defined as itch lasting longer than 6 weeks, is a highly prevalent and debilitating symptom knownto profoundly and negatively affect quality of life. The development of effective targeted therapies for somechronic itch disorders such as atopic dermatitis has given widespread recognition to the importance ofmeasuring itch in clinical trials. Clinical trials now use itch measurement as a primary outcome measure, andsteps toward the standardization of itch assessment are being made to meet the growing need for reliablymeasuring itch and its impact on quality of life in the clinical research setting. Itch can be evaluated via sub-jective patient-reported assessments or by objective measurement of scratching activity and scratching-induced skin changes. Herein, methods for the subjective assessment of itch via both unidimensional andmultidimensional tools are discussed.

Journal of Investigative Dermatology (2019) 139, 264e269; doi:10.1016/j.jid.2018.12.004

1Division ofUSA; 3CenteSchool of MUSA

Correspond8123, St. Lo

Abbreviatioreported ou

ª 2018 The

CME Activity Dates: 18 January 2019Expiration Date: 17 January 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Brian Kim, MD,MTR receives research support from LEO Pharma andCelgene; is a consultant/advisor for Pfizer, Inc., AbbVie,Concert, Theravance, Regeneron, Menlo, Incyte, Kiniksa,and Sanofi; and has stock ownership with Mallinckrodt,Inc., Gilead and, Nuigen Pharma, Inc. All other authors,planning committee members, CME committee membersand staff involved with this activity as content validationreviewers have no financial relationships with commercialinterests to disclose relative to the content of this CMEactivity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.

Dermatology, Department of Medicine, Washington University Schor for the Study of Itch, Washington University School of Medicine, Stedicine, St. Louis, Missouri, USA; and 5Department of Pathology and

ence: Brian S. Kim, Division of Dermatology, Department of Medicinuis, Missouri 63110, USA. E-mail: briankim@wustl.edu

ns: AD, atopic dermatitis; DLQI, Dermatology Life Quality Index; NRtcome; QoL, quality of life; VAS, visual analogue scale; VRS, verbal

Authors. Published by Elsevier, Inc. on behalf of the Society for Inv

� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Feb19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONPruritus or itch was defined in the late 17th century by theGerman physician Samuel Hafenreffer as an “unpleasantsensation that elicits the desire or reflex to scratch” (Ikomaet al., 2006, pp. 535). Although scratching in response to

Sr

acute itch may be protective against insects, parasites, andnoxious environmental substances, in its chronic form, itch isalmost always pathologic. Defined as itch lasting longer than6 weeks, chronic itch affects approximately 15% of theoverall population and has a profoundly negative impact on

ol of Medicine, St. Louis, Missouri, USA; 2Mercy Hospital, St. Louis, Missouri,. Louis, Missouri, USA; 4Department of Anesthesiology, Washington UniversityImmunology, Washington University School of Medicine, St. Louis, Missouri,

e, Washington University School of Medicine, 660 South Euclid Campus Box

, numerical rating scale; PBI-P, Patient Benefit Index for Pruritis; PRO, patient-ating scale

estigative Dermatology. www.jidonline.org 264

SUMMARY POINTS� Dramatic advances in the treatment of chronicitch, or itch lasting longer than 6 weeks, haveincreased the need for itch evaluation in theclinical research setting.

� Itch can be evaluated via subjective patient-reported assessment of itch intensity (e.g.,numerical rating scale, visual analogue scale) orby objective measurement of scratching activityand scratching-induced skin changes (e.g.,actigraphy, physician assessment).

� Itch is a complex, multifactorial entity withprofound effects on quality of life. Therefore,multidimensional assessments of patient well-being (e.g., ItchyQoL) provide valuableinformation.

� Current limitations of subjective measures of itchinclude the need for optimization and furtherdelineation of a clinically meaningful level ofimprovement. Objective measurement of itch ispromising but currently requires cautiousinterpretation.

RESEARCH TECHNIQUES MADE SIMPLE

265

quality of life (QoL) (Kini et al., 2011; Stander et al., 2010).The elderly population has an estimated chronic itch preva-lence of up to 25% (Stander et al., 2010; Valdes-Rodriguezet al., 2015). Dermatologic disorders such as allergic con-tact dermatitis, atopic dermatitis (AD), cutaneous T-cell lym-phoma, prurigo nodularis, and psoriasis are commonlyassociated with chronic itch. Chronic itch can also arise in thecontext of kidney, liver, and neurologic disorders, as well as avariety of hematologic and lymphoproliferative disorderssuch as polycythemia vera, leukemias, lymphomas, and othermalignancies. Many patients present with chronic idiopathicpruritus or pruritus of unknown origin (Millington et al.,2018). Given its high prevalence, association with multiplemedical disorders, and highly debilitating nature, there is agreat need for medications specifically for chronic itch. Tobetter understand and quantify chronic itch in clinical trials,effective and validated tools are needed, and steps toward thestandardization of itch measurement in clinical trials arebeing taken by groups such as the European Network onAssessment of Severity and Burden of Pruritus (PruNet)(Schoch et al., 2017; Stander et al., 2016).

Recent therapeutic advances that have been tested inrandomized clinical trials and in the community have led todramatic improvements in disease severity in classical chronicitch disorders like moderate-to-severe AD (Beck et al., 2014;Ruzicka et al., 2017; Simpson et al., 2016). These advanceshave improved the QoL of individuals with AD and placedpriority on addressing chronic itch as a central morbidity in ADand other disorders. Although historically used as a secondaryendpoint, recent clinical trials have begun to address chronicitch as a primary endpoint (Ruzicka et al., 2017; Yosipovitchet al., 2018b). Thus, in the near future, chronic itch mayformally emerge as a primary indication and morbidity, rather

Journal of Investigative Dermatology (2019), Volume 139

than a secondarymedical problem. The focus of this articlewillbe on highlighting new and existing tools that measure itch inpatients. This article is not meant to be comprehensive,because the number of metrics for evaluating itch is rapidlyincreasing, but will highlight some of the most commonly usedtools and their various strengths and weaknesses in advancingclinical itch research.

UNIDIMENSIONAL ITCH INTENSITY SCALESUnidimensional scalesmeasure a single variable such as pain oritch intensity alone and have recently been adapted to measureitch intensity for clinical trials (Phan et al., 2012). Subjectiveunidimensional scales have been well validated, are effective,and are widely used in pain research (Hjermstad et al., 2011).These include the numerical rating scale (NRS), verbal ratingscale (VRS), and visual analogue scale (VAS) (Table 1). On theNRS, patients score itch intensity on a scale from0 (no itch) to 10(worst imaginable itch) over a period of time, typically 24 hours(Figure 1a). On the VRS, patients score itch intensity using fivecategories from no itch (0) to very severe itch (4) (Figure 1b). TheVAS is a continuous visual scale that allows patients tomark itchintensity on a spectrum depicted as a 10-cm rulereshaped linelabeled at each end with 0 for no itch and 10 for worst imagin-able itch (Phan et al., 2012) (Figure 1c). Additional itch severityassessments have been developed and validated, such as theseverity of pruritus scale (Yosipovitch et al., 2018a). Collec-tively, these unidimensional scales are simple and efficient toolsfor measuring subjective itch intensity.Two studies with 471 and 310 patients with chronic itch of

different etiologies showed the NRS, VRS, and VAS to bereliable with high concordance (Phan et al., 2012; Reich et al.,2012). The NRS was a key secondary endpoint to measure itchin patients with moderate-to-severe AD in pivotal phase 3clinical trials leading to the approval of dupilumab, an anti-IL-4 receptor a monoclonal antibody, in 2017 (Simpson et al.,2016). Similarly, the VRS was used as a secondary endpoint,whereas the VAS was used as a primary endpoint, to measureitch in patients with moderate-to-severe AD in phase 2 clinicaltrials for nemolizumab, an anti-IL-31 receptor A monoclonalantibody (Ruzicka et al., 2017). Nemolizumab showed dose-dependent, anti-itch efficacy in these studies. Taken together,recent clinical trials in AD have shed light on how metrics foritch can be successfully used to monitor the efficacy and utilityof new and emerging treatments.In addition to quantifying itch, defining clinically meaningful

improvements in itch intensity, or any patient-reported outcome(PRO), allows for both investigators and clinicians to understandhow much of an impact a given medication may actually haveon the patient’s itch severity as described in the SPIRIT-PROExtension (Calvert et al., 2018). In other words, a statisticallysignificant improvement in itch may not equate to a clinicallymeaningful improvement in itch. Based on investigator-reportedand PRO data from four clinical trials in plaque psoriasis, a 4-point change in the NRS was recommended as a clinicallymeaningful improvement via anchor- and distribution-basedmethods (Kimball et al., 2016). Alternatively, a 2e3-pointdecrease in both VAS and NRS was suggested as the minimalclinically important difference after an observational study thatincluded patients with chronic itch of multiple causes (Reichet al., 2016). The clinical trials for dupilumab used an

Table 1. Summary of Measurement Tools for Itch Intensity, Associated Symptoms, and Quality of LifeScale Description Strengths Limitations Validation

Unidimensional Itch Intensity ScalesNRS Intensity rated 0e10 Simple to use

Validated and reliableWidely applicable

Easily assessed over time

No context at the time of measurement(e.g., environmental confounders)

Recall biasMissing data

Phan et al. (2012)Reich et al. (2012)VRS Intensity rated from none (0)

to very severe (4)VAS Intensity marked on 10-cm

line labeled 0e10Multidimensional Itch and Quality of Life Assessments

DLQI 10-item questionnaire ratingnonspecific symptom severity

and disease impact ondaily functioning

Items scored as 0 ¼ not at all,1 ¼ a little, 2 ¼ a lot,

3 ¼ very much

Simple to useValidated and reliable

Available in many languagesand a children’s version

Can be directly compared withother dermatologic conditions

Mildly time consumingNot itch specific

Less applicable to itch withoutskin manifestations

Psychological burden notdirectly assessed

Lewis and Finlay (2004)

ItchyQoL 22-item questionnaire addressingthree domains of itch impact:

symptoms, function, and emotions.Items scored as 1 ¼ never, 2 ¼ rarely,

3 ¼ sometimes, 4 ¼ often,5 ¼ all of the time

Simple to useValidated and reliableHighly itch specific

Psychological burden assessed

Moderately time consumingDifficult to get multiple time points

Desai et al. (2008)

5-D Recall over past 2 weeks:Duration (total hours)Degree (5 point NRS)

Direction (better or worse)Disability (QoL)Distribution

Simple to useValidated and reliable

Evaluates symptom changeover time

Itch specific

Moderately time consumingRecall bias

Elman et al. (2010)

PBI-P 27 potential treatment benefitsweighted by patient preference

Patient treatment goals andexpectations accounted for

Itch specific

Significantly time consuming Blome et al. (2009)

Electronic DiariesItchApp Smartphone application currently

available for Android phonesSimple to use

Validated and reliableHigh patient complianceMinimizes recall bias

Requires patients to own andoperate smartphones

Gernart et al. (2017)

Abbreviations: 5-D, 5-D Itch Scale; DLQI, Dermatological Life Quality Index; NRS, numerical rating scale; PBI-P, Patient Benefit Index for Pruritus; QoL,quality of life; VAS, visual analogue scale; VRS, verbal rating scale.

RESEARCH TECHNIQUES MADE SIMPLE

improvement of at least 4 points in peak NRS score at weeks 2,4, and 16 or of at least 3 points at week 16 in the weeklyaverage of daily peak NRS scores (Simpson et al., 2016).Emerging studies using various unidimensional itch intensityscales are allowing refinement of which endpoints and mile-stones translate to clinically meaningful patient outcomes.Althoughunidimensional itch intensity scales havebeenused

successfully in many clinical trials, potential limitations exist.First, given that these tools require patients to recall itch intensityover a given period, typically 24 hours, there is vulnerability toenvironmental and psychosocial confounders present at thetime of recording. Second, what recall period is ideal for effec-tively measuring itch has not been clearly defined. Third, someinvestigators and/or patients may use average versus peak itchintensity, which can have different levels of sensitivity andspecificity in measuring itch. To this point, in a recent clinicaltrial using the neurokinin 1 receptor antagonist tradipitant inchronic itch secondary to AD, VAS measurement of peak/worstitch intensity achieved significance, but mean itch intensity didnot. Fourth, the time of day at which itch is measured may alsoaffect itch severity. In the same clinical trial with tradipitant forAD, worst NRS itch during the day did not reach significance,but NRS itch at night did (Heitman et al., 2018). Fifth, missingdata are another concern. In a large validation study of 471patients, 12.5% of patients failed to record itch intensity on the

VAS at the first time point compared with 4.2% and 7.2% withNRS and VRS, respectively. Notably, patients older than 60years showednearly double thenumberofmissing valueson theVAS and NRS (16.1% and 9.1%, respectively) compared withyounger participants. TheVRShad the lowest number ofmissingvalues inelderly patientswith a rateof 3.7%at thefirst timepoint(Phan et al., 2012). Difficulty with the VAS andNRSmay be dueto the more abstract nature of converting a subjective sensationto a specificmark or number on a spectrum. However, methodssuch as daily diaries can be used tomaximize data points and tominimize variability, issueswith recall, andmissingdata. Patienteducation before use is important to ensure proper documen-tation and usage (Phan et al., 2012). A cartoon-illustratedversion of the 11-point NRS, called the ItchyQuant, showedconcurrent validity, was preferred by patients andmay be easierto use than the traditional NRS (Haydek et al., 2017) (Figure 2).

MULTIDIMENSIONAL ITCH ASSESSMENTSMultidimensional scales have been designed to obtain a moreholistic picture of the burden of itch on patients, taking intoaccount measures of QoL, itch frequency, course, and/orpatient expectations. These include the Dermatology LifeQuality Index (DLQI), ItchyQoL, 5-D Itch Scale, and PatientBenefit Index for Pruritus (PBI-P) (Blome et al., 2009; Desaiet al., 2008; Elman et al., 2010; Finlay and Khan, 1994;

www.jidonline.org 266

Figure 1. Numerical rating scale, verbal rating scale, and visual analoguescale.

267

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Pereira and Stander, 2017) (Table 1). Patient QoL (e.g., sleep,social functioning) is profoundly affected by chronic itch andis increasingly measured in clinical trials (Kini et al., 2011).Although validated scales such as the DLQI use itch as acomponent in its overall scoring, it is not designed to spe-cifically capture the relationship of itch to QoL. The DLQI istherefore often used as a QoL measurement in conjunctionwith unidimensional itch scales. The DLQI is a brief 10-itemquestionnaire in which patients rate nonspecific skin symp-tom (itchy, sore, painful, stinging) severity and disease impacton various aspects of daily life and social functioning scoredfrom 0 to 3 (0 ¼ not at all, 1 ¼ a little, 2 ¼ a lot, 3 ¼ verymuch). It is available in many languages and in a children’sversion. The DLQI predominantly emphasizes skin appear-ance and its impact on daily functioning, making it lessapplicable to itch without skin manifestations, and does notdirectly assess psychological burden (Lewis and Finlay,2004). To address these concerns, ItchyQoL, an itch-

Figure 2. ItchyQuant, an illustratednumeric rating scale for itch severity.Reprinted from Haydek et al. (2017).

Journal of Investigative Dermatology (2019), Volume 139

specific, 22-item questionnaire, was developed. Althoughmore time consuming than the DLQI, ItchyQoL is highlytailored to patients experiencing itch and better evaluatespsychological burden (e.g., frustration, irritability) (Desaiet al., 2008; Pereira and Stander, 2017; Stumpf et al.,2018). ItchyQoL addresses three domains of itch impact,symptoms, function, and emotions, with each item scoredfrom 1 to 5 (1 ¼ never; 2 ¼ rarely; 3 ¼ sometimes; 4 ¼ often;5 ¼ all of the time) (Desai et al., 2008). Thus, by coupling itchintensity directly to various aspects of QoL, the ItchyQoLprovides a more comprehensive assessment of patientssuffering from chronic itch. Indeed, validation in patients withchronic itch disorders of multiple different causes showedconstruct validity and reproducibility (Desai et al., 2008).

An additional important component in understanding theimpact of itch on an individual is time. Although the intensityor quality of one’s itch can be captured at one point in time,understanding the natural time course and rapidity ofresponse to treatment can also yield insight into the impact ofitch on patients. The 5-D itch scale assesses itch course over a2-week period with consideration of patients’ perspective ontheir symptoms. The five dimensions are degree (5-pointNRS), duration (total hours), direction (better or worse),disability (impairment of sleep, leisure, and function at home/work), and distribution on skin (16 potential locations of itch)(Elman et al., 2010). A study of 234 patients with itch ofmultiple causes found the 5-D itch scale to be reliable andvalid with high correlation to the unidimensional VAS (Elmanet al., 2010). The 5-D itch scale provides valuable informa-tion on itch course and QoL impact while remaining brief,easy to use, and widely applicable.The PBI-P is a tool that uniquely evaluates treatment

response in the context of patient-specified goals of therapy.Before treatment, patients complete a questionnaire todetermine the value placed on 27 potential benefits fromtreatment (e.g., reduced itch, improved sleep), ensuring thatthe morbidities associated with itch that are most important toeach patient are measured. After treatment, patients completea questionnaire on the outcome of the 27 potential benefits. Aweighted score is then calculated based on pre- and post-treatment responses (Blome et al., 2009). PBI-P validation in100 patients with chronic itch showed good correlation with

MULTIPLE CHOICE QUESTIONS1. Which unidimensional itch intensity scale allows

patients to mark itch intensity on a spectrumdepicted as a 10-cm rulereshaped line labeled ateach end with 0 for no itch and 10 for worstimaginable itch?

A. Verbal rating scale (VRS)

B. Visual analogue scale (VAS)

C. Numerical rating scale (NRS)

D. Dermatology Life Quality Index (DLQI)

2. Patient ease of use and compliance with theunidimensional itch intensity scales can beimproved by which of the following?

A. Electronic diaries (eDiaries)

B. Patient education before use

C. Cartoon-illustrated versions

D. All of the above

3. The impact of itch on patient quality of life (QoL)can be assessed by which of the following tools?

A. Visual analogue scale (VAS)

B. ItchyQoL

C. Eczema Area and Severity Index (EASI)

D. Scoring Atopic Dermatitis (SCORAD)

4. In addition to itch intensity alone,multidimensional itch assessments may alsoevaluate which of the following?

A. Patient QoL

B. Itch frequency and course

C. Patient expectations and treatment goals

D. All of the above

5. Which of the following are superior tools for themeasurement of itch?

A. Unidimensional itch intensity scales

B. Multidimensional itch assessments

C. Objective tools that measure scratchingactivity and associated skin changes

D. None of the above

RESEARCH TECHNIQUES MADE SIMPLE

the VAS and DLQI (Blome et al., 2009). Although timeconsuming, the PBI-P provides valuable insight into howpatients’ expectations play into their perceptions of treatment.These multidimensional assessments each provide uniqueinsights into chronic itch symptomatology and impact, andthey differ in terms of the kinds of data that they will generate.

ELECTRONIC DIARIESMonitoring itch intensity and/or QoL over time, particularlywith respect to therapeutic interventions, is a critically importantaspect of clinical trials. Suchmeasurements canbe performed asinfrequently as predefined study visits scheduled weeks tomonths apart or as frequently as multiple times per day. If dataare obtained inconsistently, measured at the wrong times, orsimply missing, then the outcomes can be greatly affected.Electronic diaries (eDiaries) are increasingly used in clinicaltrials to record patient responses to various itch measurementtools. In addition to simplifying data entry and increasing patientcompliance through reminders, eDiaries track the exact timewhen patients enter information, a notable benefit over paper-based diaries in which patients may retroactively respond toquestions from missed time points. The eDiary modules can beaccessed on tablets given to patients or, increasingly, viasmartphone applications such as ItchApp (Arone, Saint-Maurdes Fosses, France), which can be used on smartphones and hasbeen validated (Gernart et al., 2017; Schnitzler et al., 2018)(Table 1). eDiaries can improve accuracy by minimizing recallbias and missing data and increasing the number of data points.Monitoring has also been successfully facilitated through theintegration of itch assessments into electronic medical records(Mollanazar et al., 2016).

ASSESSMENT OF SCRATCHING ACTIVITYAlthough itch is, by definition, a subjective sensation,scratching is an objective event. Given that scratching is avirtually unavoidable reflex in response to itch, it can bemeasured in an objective fashion, such as actigraphy orphysician assessment, to further assess chronic itch symptomsin patients. Indeed, investigator-based measurements for ADdisease severity including the Eczema Area and Severity In-dex (i.e., EASI) and Scoring Atopic Dermatitis (i.e., SCORAD)tools measure scratching-induced changes in the skin as apart of the overall assessment. Furthermore, scratchingseverity assessment tools show potential in validation studiesand may be particularly helpful in pediatric populations inwhich PROs are harder to obtain than in adults (Udkoff andSilverberg, 2018). However, although objective measuresadd additional information, how scratching activity, and thuslesion development, relates to QoL remains to be moreclearly defined. For example, patients with AD typicallyexhibit excoriations, whereas individuals with idiopathicforms of itch often do not exhibit secondary lesions despiteeven higher mean itch severity (Oetjen et al., 2017). Addi-tionally, patients with severe itch may practice avoidancetechniques, and others may scratch out of habit, even in theabsence of itch sensation or burden as in primary excoriationdisorders (Stander et al., 2013). How objective measurementsof scratching activity add to current subjective metrics is anexciting area of research with current data requiring cautiousinterpretation.

CONCLUSIONSDramatic advances in the treatment of chronic itch disordershave increased the need for itch evaluation in the clinicalresearch setting. The unidimensional itch intensity scales(e.g., NRS, VRS, and VAS) provide simple, reliable, and validmeasures of itch intensity that have successfully been used inlarge-scale clinical trials. However, itch is a complex andmultifactorial entity that profoundly and negatively affectsQoL. Thus, increasingly, QoL assessments, such as the DLQI,or multidimensional tools that incorporate QoL, such as theItchyQoL, 5-D, and PBI-P, show great potential for moreholistically capturing the impact of itch. New apps and tools

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269

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may greatly improve compliance and provide more objectivemeasurements of itch in the future. Ultimately, clinical itchresearch has emerged as a well-recognized and importantarea of dermatology. The development of new tools willundoubtedly better inform clinical trials but also directlyimprove our basic understanding of chronic itch.

CONFLICT OF INTERESTBSK has worked as a consultant for AbbVie, Concert Pharmaceuticals, Incyte,Menlo Therapeutics, and Pfizer and served on advisory boards for Celgene,Kiniksa Pharmaceuticals, Menlo Therapeutics, Regeneron Pharmaceuticals,Sanofi, and Theravance Biopharma. BSK is also a stockholder of Gilead Sci-ences and Mallinckrodt Pharmaceuticals and is founder and chief scientificofficer of Nuogen Pharma. SE states no conflict of interest.

ACKNOWLEDGMENTSWe acknowledge support from the Doris Duke Charitable Foundation,Celgene Corporation, LEO Pharma, and the National Institute of ArthritisMusculoskeletal and Skin Diseases of the National Institutes of Health(K08AR065577 and R01AR070116).

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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Blome C, Augustin M, Siepmann D, Phan NQ, Rustenbach SJ, Stander S.Measuring patient-relevant benefits in pruritus treatment: development andvalidation of a specific outcomes tool. Br J Dermatol 2009;161:1143e8.

Calvert M, Kyte D, Mercieca-Bebber R, Slade A, Chan AW, King MT, et al.Guidelines for inclusion of patient-reported outcomes in clinical trialprotocols: The SPIRIT-PRO extension. JAMA 2018;319:483e94.

Desai NS, Poindexter GB, Monthrope YM, Bendeck SE, Swerlick RA, Chen SC.A pilot quality-of-life instrument for pruritus. J Am Acad Dermatol 2008;59:234e44.

Elman S, Hynan LS, Gabriel V, Mayo MJ. The 5-D itch scale: a new measure ofpruritus. Br J Dermatol 2010;162:587e93.

Finlay AY, Khan GK. Dermatology Life Quality Index (DLQI)—a simple practicalmeasure for routine clinical use. Clin Exp Dermatol 1994;19:210e6.

Gernart M, Tsianakas A, Zeidler C, Riebe C, Osada N, Pihan D, et al. ItchAppª:an app-based eDiary for assessment of chronic pruritus in clinical trials.Acta Derm Venereol 2017;97:601e6.

Haydek CG, Love E, Mollanazar NK, Valdes Rodriguez R, Lee H, Yosipovitch G,et al. Validation and banding of the ItchyQuant: a self-report itch severityscale. J Invest Dermatol 2017;137:57e61.

Heitman A, Xiao C, Polymeropoulos C, Welsh S, Bikker A, Birznieks G, et al.Tradipitant improves worst itch and disease severity in patients withchronic pruritus related to atopic dermatitis. Poster session presented at:10th Georg Rajka International Symposium of Atopic Dermatitis. 12 April2018; Utrecht, The Netherlands.

Hjermstad MJ, Fayers PM, Haugen DF, Caraceni A, Hanks GW, Loge JH, et al.Studies comparing numerical rating scales, verbal rating scales, and visualanalogue scales for assessment of pain intensity in adults: a systematicliterature review. J Pain Symptom Manage 2011;41:1073e93.

Ikoma A, Steinhoff M, Stander S, Yosipovitch G, Schmelz M. The neurobiologyof itch. Nat Rev Neurosci 2006;7:535e47.

Kimball AB, Naegeli AN, Edson-Heredia E, Lin CY, Gaich C, Nikai E, et al.Psychometric properties of the Itch Numeric Rating Scale in patients withmoderate-to-severe plaque psoriasis. Br J Dermatol 2016;175:157e62.

Kini SP, DeLong LK, Veledar E, McKenzie-Brown AM, Schaufele M, Chen SC.The impact of pruritus on quality of life: the skin equivalent of pain. ArchDermatol 2011;47:1153e6.

Lewis V, Finlay AY. 10 years experience of the Dermatology Life Quality Index(DLQI). J Investig Dermatol Symp Proc 2004;9:169e80.

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Millington GWM, Collins A, Lovell CR, Leslie TA, Yong ASW, Morgan JD, et al.British Association of Dermatologists’ guidelines for the investigation andmanagement of generalized pruritus in adults without an underlyingdermatosis, 2018. Br J Dermatol 2018;178:34e60.

Mollanazar NK, Sethi M, Rodriguez RV, Nattkemper LA, Ramsey FV, Zhao H,et al. Retrospective analysis of data from an itch center: Integrating vali-dated tools in the electronic health record. J Am Acad Dermatol 2016;75:842e4.

Oetjen LK, Mack MR, Feng J, Whelan TM, Niu H, Guo CJ, et al. Sensory neuronsco-opt classical immune signaling pathways to mediate chronic itch. Cell2017;171:217e228.e13.

Pereira MP, Stander S. Assessment of severity and burden of pruritus. Allergol Int2017;66:3e7.

Phan NQ, Blome C, Fritz F, Gerss J, Reich A, Ebata T, et al. Assessment ofpruritus intensity: Prospective study on validity and reliability of the visualanalogue scale, numerical rating scale and verbal rating scale in 471 pa-tients with chronic pruritus. Acta Derm Venereol 2012;92:502e7.

Reich A, Heisig M, Phan NQ, Taneda K, Takamori K, Takeuchi S, et al. Visualanalogue scale: Evaluation of the instrument for the assessment of pruritus.Acta Derm Venereol 2012;92:497e501.

Reich A, Riepe C, Anastasiadou Z, Medrek K, Augustin M, Szepietowsk JC, et al.Itch assessment with visual analogue scale and numerical rating scale:Determination of minimal clinically important difference in chronic itch.Acta Derm Venereol 2016;96:978e80.

Ruzicka T, Hanifin JM, Furue M, Pulka G, Mlynarczyk I, Wollenberg A, et al.Antieinterleukin-31 receptor A antibody for atopic dermatitis. N Engl JMed 2017;376:826e35.

Schnitzler C, Rosen J, Szepietowski JC, Reich A, Yosipovitch G, Reszke R, et al.Validation of “ItchAppª” in Poland and in the USA. Multicenter validationstudy of an electronical diary for the Assessment of pruritus [e-pub ahead ofprint]. J Eur Acad Dermatol Venereol 2018. https://doi.org/10.1111/jdv.15300 (accessed 15 November 2018).

Schoch D, Sommer R, Augustin M, Stander S, Blome C. Patient-reportedoutcome measures in pruritus: A systematic review of measurement.J Invest Dermatol 2017;137:2069e77.

Simpson EL, Bieber T, Guttman-Yassky E, Beck LA, Blauvelt A, Cork MJ, et al.Two phase 3 trials of dupilumab versus placebo in atopic dermatitis. N EnglJ Med 2016;375:2335e48.

Stander S, Augustin M, Reich A, Blome C, Ebata T, Phan NQ, et al.Pruritus assessment in clinical trials: consensus recommendations from theInternational Forum for the Study of Itch (IFSI) special interest group scoringitch in clinical trials. Acta Derm Venereol 2013;93:509e14.

Stander S, Schafer I, Phan NQ, Blome C, Herberger K, Heigel H, et al.Prevalence of chronic pruritus in Germany: results of a cross-sectionalstudy in a sample working population of 11,730. Dermatology2010;221:229e35.

Stander S, Zeidler C, Riepe C, Steinke S, Fritz F, Bruland P, et al. European EADVnetwork on assessment of severity and burden of Pruritus (PruNet): firstmeeting on outcome tools. J Eur Acad Dermatol Venereol 2016;30:1144e7.

Stumpf A, Pfleiderer B, Fritz F, Osada N, Chen SC, Stander S. Assessment ofquality of life in chronic pruritus: relationship between ItchyQoL andDermatological Life Quality Index in 1,150 Patients. Acta Derm Venereol2018;98:142e3.

Udkoff J, Silverberg JI. Validation of scratching severity as an objective assess-ment for itch. J Invest Dermatol 2018;138:1062e8.

Valdes-Rodriguez R, Mollanazar NK, González-Muro J, Nattkemper L, Torres-Alvarez B, López-Esqueda FJ, et al. Itch prevalence and characteristics in aHispanic geriatric population: a comprehensive study using a standardizeditch questionnaire. Acta Derm Venereol 2015;95:417e21.

Yosipovitch G, Simpson EL, Bushmakin AG, Cappelleri JC, Luger T, Stander S,et al. Assessment of pruritus in atopic dermatitis: validation of the Severityof Pruritus Scale (SPS). Itch 2018a;3(2):e13.

Yosipovitch G, Stander S, Kerby MB, Larrick JW, Perlman AJ, Schnipper EF, et al.Serlopitant for the treatment of chronic pruritus: results of a randomized,multicenter, placebo-controlled phase 2 clinical trial. J Am Acad Dermatol2018b;78:882e91.e10.

This is a reprint of an article that originally appeared in the February 2019 issue of the Journal of Investigative Dermatology. It retains its original pagination here.For citation purposes, please use these original publication details: Erickson S, KimBS. Research TechniquesMade Simple: ItchMeasurement in Clinical Trials. JInvest Dermatol 2019;139(2):264e269; doi:10.1016/j.jid.2018.12.004

RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple: InterpretingMeasures of Association in Clinical Research

Michelle R. Roberts1,2, Sepideh Ashrafzadeh1,2 and Maryam M. Asgari1,2

To bring evidence-based improvements in medicine and health care delivery to clinical practice, health careproviders must know how to interpret clinical research findings and critically evaluate the strength of evidence.This requires an understanding of differences in clinical study designs and the various statistical methods usedto identify associations. We aim to provide a foundation for understanding the common measures of associ-ation used in epidemiologic studies to quantify relationships between exposures and outcomes, includingrelative risks, odds ratios, and hazard ratios. We also provide a framework for critically assessing clinicalresearch findings and highlight specific methodologic concerns.

Journal of Investigative Dermatology (2019) 139, 502e511; doi:10.1016/j.jid.2018.12.023

1DepartmenMedicine, H

Correspond02114, USA

Abbreviatio

ª 2019 The

CME Activity Dates: 20 February 2019Expiration Date: 19 February 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Maryam Asgari,MD receives research support from Valeant Pharmaceuticalsand Pfizer, Inc. All other authors, planning committee mem-bers, CME committee members and staff involved with thisactivity as content validation reviewers have no financial re-lationships with commercial interests to disclose relative tothe content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodologieson which many diagnostic and therapeutic advances are built.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

t of Dermatology, Massachusetts General Hospital, Harvard Medicaarvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA

ence: Maryam M. Asgari, Department of Dermatology, Massachuset. E-mail: PORES@mgh.harvard.edu

ns: CI, confidence interval; HR, hazard ratio; I, incidence; O, odds;

Authors. Published by Elsevier, Inc. on behalf of the Society for Inv

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Mar19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONEpidemiology is the study of the distribution and de-terminants of disease and other health-related outcomeswithin populations. As the basic science of public health,epidemiologic studies can describe patterns of diseasewithin specific populations (descriptive epidemiology) orinvestigate etiology and risk factors for health outcomes(analytic epidemiology). A core feature of analytic epide-miology is the presence of an appropriate comparisongroup. Using analytic epidemiologic methods, we can

t

investigate hypotheses about exposure-outcome relation-ships by comparing exposure status between groups ofpeople. A sound understanding of epidemiologic principlesenables health care providers to consider if the effects of anexposure could warrant changes in clinical practice, treat-ment protocols, or community program management. In thisarticle, we describe several measures of associationfrequently encountered in analytic epidemiology anddiscuss factors to consider when interpreting clinicalresearch.

l School, Boston, Massachusetts, USA; and 2Department of Population

s General Hospital, 50 Staniford Street, Suite 230A, Boston, Massachusetts

OR, odds ratio; RR, relative risk

estigative Dermatology. www.jidonline.org 502

SUMMARY POINTS� Measures of association refers to a wide variety ofstatistics that quantify the strength and directionof the relationship between exposure andoutcome variables, enabling comparisonbetween different groups.

� The measure calculated depends on the studydesign used to collect data. Odds ratios shouldbe used for case-control and cross-sectionalstudies, whereas relative risk should be used incohort studies.

� When interpreting measures of association inclinical practice, consider whether the resultsmay have been affected by sources of bias andconfounding, as well as how generalizable thestudy sample is to the target population.

� Confounding may be addressed throughrandomization, matching, stratification, orstatistical adjustment, although unmeasuredconfounders or residual confounding may stillaffect the observed association.

� Effect sizes and measures of variability, such asconfidence intervals, may be more informativethan P-values for interpreting epidemiologicdata.

RESEARCH TECHNIQUES MADE SIMPLE

503

MEASURES OF ASSOCIATIONEpidemiologic study designs are differentiated by the pres-ence or absence of an intervention, randomization of partic-ipants, and the temporal relationships among comparisongroups. Common observational designs, including cohort,case-control, and cross-sectional studies, are shown inTable 1 (Besen and Gan, 2014; Silverberg, 2015).Relationships between exposures and outcomes are

quantified using various measures of association, which arestatistics that estimate the direction and magnitude of as-sociations among variables. Commonly used measures aredescribed in Table 2 and Figure 1. The reported measure ofassociation depends on the study design used to collect thedata and the statistical method used to analyze it (Pearce,1993). A useful way to visualize the calculation of severalmeasures of association is by constructing a basic 2 � 2contingency table (Figure 2), which shows the cross-tabulation of exposed and unexposed participants (rows)by those with and without an outcome of interest(columns).

Relative riskRelative risk (RR) is often calculated in cohort studies, whereparticipants with and without exposure(s) are followed forparticular outcome(s). This design allows for the calculationof incidence (I), found by dividing the number of new cases ofan outcome by the number of people at risk for the outcomeduring a specified period (Figure 2): Iexposed ¼ A/(A þ B) andIunexposed ¼ C/(C þ D). The RR is the ratio of the incidenceamong exposed participants to the incidence among

Journal of Investigative Dermatology (2019), Volume 139

unexposed participants: RR ¼ Iexposed/Iunexposed. Bycomparing incidence rates between the exposed and unex-posed groups, it is possible to determine if an exposure in-creases or decreases risk of an outcome.When RR is equal to 1, the incidence is the same among

those exposed and unexposed. An RR less than 1 suggests thatthe exposure is protective (Iexposed < Iunexposed), and an RRgreater than 1 suggests that the exposure is a risk factor for theoutcome (Iexposed > Iunexposed). For example, the relationshipbetween dietary vitamin D intake and risk of melanoma wasinvestigated in a cohort study, and a RR of 1.31 (95% confi-dence interval [CI]¼ 0.94e1.82) was observed for the highestquartile of vitamin D compared with the lowest quartile(Asgari et al., 2009b). The point estimate indicates a 31%increased risk of melanoma (or 1.31 times the risk) amongparticipants with the highest level of vitamin D intake, butbecause the CI includes the null value of 1, we would notconsider the finding statistically significant.

Odds ratioIn case-control or cross-sectional studies, where we cannotcalculate incidence rates, the odds ratio (OR) is typicallycalculated. The OR is the ratio of the exposure odds (O)among the case group to the exposure odds among thecontrol group (Figure 2): Ocase ¼ A/C, Ocontrol ¼ B/D, OR ¼Ocase/Ocontrol), and it is interpreted similarly to the RR. An ORequal to 1 indicates no association, an OR less than 1 sug-gests that the exposure is protective (exposure is less likelyamong the case group), and OR greater than1 suggests thatthe exposure is a risk factor (exposure is less likely among thecontrol group). For example, in a case-control study exam-ining the association between infection with human papillo-mavirus b and risk of squamous cell carcinoma, an OR of 4.0(95% CI ¼ 1.3e12.0) was observed (Asgari et al., 2008). ThisOR indicates that the odds of being exposed (i.e., having thishuman papillomavirus subtype) were 4 times greater amongthe case group than the control group or, put another way,that cases were 4 times more likely to have this humanpapillomavirus subtype than controls.When the outcome is rare, the OR approximates the RR.

This assumption, known as the rare disease assumption, canbe visualized in Figure 2. When the proportions in cells A andC are small, A þ B z B and C þ D z D. Therefore, RR ¼ [A/(A þ B)]/[C/(C þD)]z (A/B)/(C/D) ¼ (A/C)/(B/D) ¼OR. Whenthe outcome is more common (>10%), however, the ORprovides more extreme estimates than the RR. In Figure 2,where 44% of the study population has the outcome, the ORis much smaller than the RR.

Hazard ratioThe hazard ratio (HR) is the ratio of the rate at which theexposed group experiences an outcome to the rate at whichthe unexposed group experiences an outcome, and it pro-vides the instantaneous risk at a given time rather than thecumulative risk over the length of a study. It is calculated insurvival or time-to-event analyses, in which the outcomevariable is the time (days, months, years, etc.) until theoccurrence of the event of interest, such as development of adisease, disease complication (e.g., cancer recurrence),death, or other outcome. Participants who do not experience

Table 1. Study designs in clinical research1

Study Design Description Strengths/Utility Weaknesses

Meta-analysis Analysis in which multiple RCTs and/or

observational studies are combined

Larger sample size and higherstatistical power than individual studies

Limited by the quality and potentialheterogeneity of the individual studies they

combineExperimentalstudiesRandomized

controlled trialProspective design in which

participants are randomly allocatedto intervention and control groups

Control group may be placebo or acomparison intervention

Random assignment balances confoundingvariables between groups (even

unmeasured variables)Identification of causality between anexposure/intervention and outcome

ExpensiveMay not capture etiologically relevant time

periodPotential lack of generalizability

Differential loss to follow-up may introducebias

Potential ethical issuesQuasi-

experimentalNonrandomized intervention study Can assess the effects of an intervention

Useful when randomization is not possible forpractical or ethical reasons

Lack of random assignmentPotential loss of internal validity

ObservationalstudiesCohort Longitudinal design in which

participantsare followed up over time

May be prospective or retrospective

Possible to evaluate multiple exposuresand outcomes in the same study population

Temporal sequence of events is moreclearly indicated

Permits the calculation of disease incidenceFacilitates examination of rare exposuresReduces the potential for selection bias

at enrollment

Expensive and time consumingMay be inefficient for rare outcomes or

diseases with long latent periodsDifferential loss to follow-up may

introduce biasFor retrospective designs:

May be difficult to identify appropriateexposed cohort and comparison group

Data on important confounding variablesmay be absent

Potential for reduction in data quality ifrecords not designed for the study are used

Case-control Design in which participants with anoutcome (case group) and

participants without the outcome(control group) are sampled from adefined source population andcompared with respect to the

frequency of one or more exposuresMay be prospective or retrospectiveMay be nested within a cohort study

Facilitates the study of rare diseases/outcomesor those with long latency periods

Less expensive and time consumingthan cohort designs

More efficient when exposure dataare expensive or difficult to obtain

Advantageous for dynamic populations inwhich long-term follow-up may be difficult

Inefficient for rare exposuresDo not permit the calculation of disease

incidenceMay be subject to selection bias, particularly

due to nonrepresentative sampling ofcontrol individuals

More susceptible to information biases,including recall and observer biases

May be more difficult to establish temporalityCross-sectional Descriptive design in which data are

collected from a population at aspecific point in time

Provides a “snapshot” of exposuresand outcomes

Inexpensive and less time-consumingthan other designs

Can estimate prevalence of exposuresand outcomes simultaneously

Useful for monitoring health status and needsof a particular population

Temporality is difficult to ascertainTends to identify prevalent cases of longdisease duration (e.g., more serious casesmay not be captured because of death)

Potential for nonresponse bias

Ecologic Design in which data are collectedat the population, rather than

individual, levelPopulations may be definedgeographically or temporally

Useful for examining rare diseasesInexpensive and easy to conduct using routinely

collected dataUseful for monitoring population health, making

comparisons between populations, or whenindividual-level data are unavailable

Prone to bias and confounding, both withinand between groups

The ecologic fallacy, in which effectsobserved at the population level donot accurately reflect effects at the

individual levelMethodologic weaknesses limit

causal inferenceCase study or

seriesA descriptive analysis of an

individual case or series of cases,with no comparison group

Can describe new trends or rarecharacteristics of diseases

May detect previously unreported adverse effectsor potential new uses of medications

Useful in teaching clinical lessons learnedfrom patient care

May lack generalizabilityPotential confounding may not be

addressedDifficult to establish causality

Abbreviation: RCT, randomized controlled trial.1This table lists advantages and disadvantages common to clinical study designs but is not exhaustive. Readers are referred to the many excellent publishedreviews of epidemiologic study design principles, including Besen and Gan (2014) and Silverberg (2015).

RESEARCH TECHNIQUES MADE SIMPLE

an event during the follow-up period are censored. This oc-curs if the participant is lost to follow-up, the follow-up periodends and the participant is event-free, or the participant ex-periences another outcome. At the time of censoring, theparticipant stops contributing follow-up time to the analysis.

This type of censoring is known as right-censoring, becausethe true unobserved event lies to the right of the censoringtime. For example, in a survival analysis of acral lentiginousmelanoma, both melanoma-specific survival and overallsurvival, or all-cause mortality, were examined. In the

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Table 2. Examples of measures of association in clinical researchMeasure ofAssociation Definition Exposure Outcome

EffectEstimate Interpretation

Relative risk(RR)1

The ratio of the incidence in the exposedgroup to the incidence in the unexposed

group

Vitamin Dintake

Melanoma RR ¼ 1.31(95% CI ¼ 0.94

e1.82)

When compared with the lowest quartile ofdietary vitamin D intake, participants withthe highest quartile of intake had 1.31 timesthe risk of melanoma. This may also bephrased as having a 31% increase in

melanoma risk.Because the 95% CI includes 1 (the nullvalue, indicating no association betweenexposure and outcome), the results are notstatistically significant (Asgari et al., 2009b).

Odds ratio(OR)

The ratio of the exposure odds among thecase group to the exposure odds among

the control group

Presence orabsence of

HPV

Squamous cellcarcinoma

Any HPVspecies:

OR ¼ 0.9 (95%CI ¼ 0.4e1.8)

HPV b-papillomavirus:OR ¼ 4.0 (95%CI ¼ 1.3e12.0)

This study compared tissue from patientswith squamous cell carcinoma to tissue fromcontrol individuals with no history of skin

cancer. No statistically significantassociation between patients (cases) andcontrol individuals was observed when all

HPV species were considered as theexposure. In the subgroup analysis,

however, tissue from patients was 4 timesmore likely to contain the b-papillomavirusspecies compared with tissue from control

individuals(Asgari et al., 2008).

Hazardratio (HR)

The ratio of the rate at which patients witha risk factor experience an event to the rateat which patients without the risk factor

experience an event

Systemicimmune

suppression

Merkel cell carcinoma-specific survival

HR ¼ 3.8 (95%CI ¼ 2.2e6.4)

The rate of death from Merkel cellcarcinoma for people with systemic immunesuppression was 3.8 times higher than for

nonimmunosuppressed individuals(Paulson et al., 2013).

Pearsoncorrelationcoefficient(r)

Measures the strength and direction of thelinear association between two continuous

variables

GOLPH3Lgene

expression

HORMAD1 geneexpression

r ¼ 0.991 There is a strong, positive linear relationshipbetween GOLPH3L and HORMAD1 geneexpression, indicating that when one gene isexpressed, the other is often expressed as

well (Ioannidis et al., 2018).Spearmancorrelationcoefficient(rho)

Measures the monotonic relationshipbetween two variables

Individualtypologyangle

Melanin index r ¼ e0.98 There is a strong, negative monotonicrelationship between individual typologyangle and melanin index, indicating thatwhen one is low, the other is high (Wilkes

et al., 2015).Betacoefficient(linearregression)

Measures the association between acontinuous outcome variable and

continuous and/or categorical predictorvariable(s)

Pain (self-rated from0e10)

Sleep quality score(range ¼ 8e40, with

higher scores indicatingmore disturbed sleep)

b ¼ 0.21P < .001

There is a positive relationship between self-rated pain and sleep disturbance. For each1-unit increase in self-rated pain, sleep

quality score increases by 0.21. The P-valueindicates that this association is statistically

significant (Milette et al., 2013).Chi-squaredtest

Measures the association between twocategorical variables by assessing whetherthere is a significant difference between

observed and expected data

Traininglevel ofclinician

Treatment type P < 0.0001 Patients treated with Mohs surgery werealmost exclusively treated by attending

physicians (98.8% vs. 1.2% resident/nursepractitioner). Patients receiving excisionwere treated slightly more frequently byresident physicians (51% vs. 46.8%

attending and 2.1% nurse practitioner).Patients treated with destruction by

electrodissection and curettage were morecommonly treated by attending physicians(57.1% vs. 33.8% resident and 9.1% nursepractitioner). The P-value from the chi-

squared test indicates that these differencesare statistically significant(Asgari et al., 2009a).

Riskdifference(RD)

Measures the difference in risk betweenexposed and unexposed groups

UV lighttherapy

Psoriasis RD ¼ e0.06 After receiving UV light therapy, 2% ofpatients continued to experience psoriasis,compared with 8% of patients not receivingthis treatment. The RD indicates that patientswho received light therapy had 6 fewer

cases of persistent psoriasis per 100 peoplecompared with patients notreceiving light therapy.2

(continued )

Journal of Investigative Dermatology (2019), Volume 139505

RESEARCH TECHNIQUES MADE SIMPLE

Table 2. ContinuedMeasure ofAssociation Definition Exposure Outcome

EffectEstimate Interpretation

Relative riskreduction(RRR)

The proportion of risk reductionattributable to the exposure/intervention

UV lighttherapy

Psoriasis RRR ¼ 0.75 Using the data from the UV light/psoriasisexample, the relative risk may be calculatedas 0.02/0.08 ¼ 0.25 (the incidence in theexposed group divided by the incidence inthe unexposed group). The RRR is therefore0.75(1 e RR), which can be interpreted as

UV light therapy resulting in a 75%reduction in psoriasis incidence, relative topatients who did not receive light therapy.2

Numberneeded totreat (NNT)

The number of patients who must betreated for one patient to benefit

UV lighttherapy

Psoriasis NNT ¼ 16.7 Using the data from the UV light/psoriasisexample, the NNT may be calculated as 1/

(incidence among the unexposed eincidence among the exposed), or1/(0.08 e 0.02). Therefore, the NNT

equals 16.7, indicating that 17 patients needto be treated with UV light therapy for

one patient to benefit.2

Abbreviations: CI, confidence interval; HPV, human papillomavirus.1Relative risk may also be referred to as the risk ratio, rate ratio, or relative rate.2Mock data are used for these examples.

RESEARCH TECHNIQUES MADE SIMPLE

melanoma-specific survival analysis, only melanoma-relateddeaths were considered events, and participants who diedof causes not related to melanoma were right-censored at thetime of death. In the overall survival analysis, however,deaths from any cause were considered events (Asgari et al.,2017). In contrast to right-censoring, left-censoring occurswhen the event has already taken place before the observa-tion period begins, and the true unobserved event lies to theleft of the censoring time. Estimation of the HR, as with Coxproportional hazards regression, accounts for only right-censored data (Clark et al., 2003).

Study Designs

Experimental

RandomizedControlled Trial

Rela ve riskHazard ra oCorrela oncoefficientsChi squared

testsRisk differenceRela ve riskreduc on

Number neededto treat

Quasiexperimental

Rela ve riskHazard ra oCorrela oncoefficientsChi squared

testsRisk differenceRela ve riskreduc onNumber

needed to treat

Cohort

Rela ve riskHazard ra oCorrela oncoefficientsChi squared

testsRisk differenceRela ve riskreduc onNumber

needed to treat

Case con

Odds raCorrelacoefficieChi squa

tests

Figure 1. Measures of association used in common clinical research study designare depicted.

When the HR is equal to 1, instantaneous event rates at aparticular time are the same in the exposed and unexposedgroups. When the HR is equal to 0.5, half as many people inthe exposed group have experienced an event compared withthe unexposed group, and when HR is equal to 2, twice asmany people have experienced an event. For example, in astudy examining the association between systemic immunesuppression and Merkel cell carcinoma-specific survival, anHR of 3.8 was observed (95% CI ¼ 2.2e6.4) (Paulson et al.,2013). This estimate indicates that the rate of death fromMerkel cell carcinoma was 3.8 times higher in people with

Observa onal

trol

oonntsred

Cross sec onal

Odds ra oPrevalence ra o(analogous torela ve risk)Correla oncoefficientsChi squared

tests

Ecologic

RatecomparisonsCorrela oncoefficients

Case study/ casereport

Not applicable

s.Measures of association commonly encountered in each type of study design

www.jidonline.org 506

Figure 2. Calculation of commonmeasures of association. A 2�2contingency table displays the numberof individuals with and without theexposure by the number of individualswith and without the outcome. Thisinformation can be used to calculateseveral several commonlyencountered measures of association.

507

RESEARCH TECHNIQUES MADE SIMPLE

systemic immune suppression. Because the 95% CI excludesthe null value of 1, we can conclude that this HR is statisti-cally significant.

Other measures of associationOther frequently encountered statistics include correlationcoefficients, beta coefficients (linear regression), chi-squared/Fisher exact tests, risk difference, relative risk reduction, andnumber needed to treat (NNT) (Table 2).

Correlation coefficients, including the Pearson r andSpearman rho statistics, measure the strength and directionbetween two variables and range from e1 (perfect negativecorrelation) to þ1 (perfect positive correlation). A positivecorrelation coefficient indicates that both variables increaseor decrease together, whereas a negative coefficient impliesthat as one variable increases, the other decreases (see ex-amples in Table 2). The Pearson r statistic is generally usedwhen data are continuous rather than categorical, and itassumes that the data are normally distributed and that thevariables are linearly related. When these assumptions arenot met, or when categorical data are involved, Spearmanrho may be more appropriate. Spearman rho assumes amonotonic relationship between ranked variables and canbe used for ordinal-level data. It is essentially a Pearsoncorrelation using variable ranks rather than variable values.Spearman rho is the nonparametric version of Pearson r, andtherefore it may be appropriate for nonnormally distributeddata or when variables are not linearly related (McDonald,2014a). For example, in a study examining cutaneoussarcoidosis, Rosenbach et al. (2013) calculated the corre-lations between disease severity and quality of life usingseveral different instruments. The Physician’s GlobalAssessment of disease severity was found to be moderatelypositively correlated with Skindex-29 assessments of symp-toms (Pearson r ¼ 0.41) but weakly negatively correlatedwith the Sarcoidosis Health Questionnaire assessment ofquality of life (Pearson r ¼ e0.18). The Physician’s GlobalAssessment, Skindex-29, and Sarcoidosis Health

Journal of Investigative Dermatology (2019), Volume 139

Questionnaire data were normally distributed. Because thedata from another assessment, the Dermatology Life QualityIndex, were not normally distributed and the sample sizewas small, the authors used the Spearman rho correlationcoefficient to identify a weak positive correlation with thePhysician’s Global Assessment (r ¼ 0.24).Linear regression is used to assess the relationship between

a continuous outcome variable and one or more categoricalor continuous predictor variables. For continuous predictors,a positive b coefficient represents the increase in the outcomevariable for every 1-unit increase in the predictor variable.Conversely, a negative b coefficient represents the decreasein the outcome variable for every 1-unit increase in the pre-dictor variable. Beta coefficients for categorical predictorshave a similar interpretation, except that the coefficient rep-resents the change in the outcome variable when switchingfrom one category of the predictor variable to another. Forinstance, a study of patients with systemic sclerosis sought toinvestigate associations between demographic and medicalvariables and sleep disturbance, measured using a sleepquality scale. The number of gastrointestinal symptoms(continuous predictor) and sleep disturbance (continuousoutcome) were positively associated (b ¼ 0.19, P ¼ 0.001).The beta coefficient indicates that for each 1-unit increase inthe number of gastrointestinal symptoms, sleep quality scoreincreases by 0.19 units. Female sex was also positivelyassociated with sleep disturbance, although the associationwas not statistically significant (b ¼ 0.07, P ¼ 0.164). Becausesex is a categorical variable, this beta coefficient indicatesthat being female, as opposed to being male, is associatedwith a 0.07-unit increase in sleep quality score (Milette et al.,2013).The chi-squared and Fisher exact statistics are often used

for testing relationships between categorical variables. Thesetests evaluate whether the proportions of one categoricalvariable differ by levels of another categorical variable (seeexample in Table 2). The null hypothesis for the chi-squared/Fisher exact test is that the variables are independent; that is,

Table 3. Points to consider when interpreting epidemiologic studiesBias, confounding, and statistical significance

1. Can the presence of biases or confounding explain the results?

� Biases and unaccounted for or unmeasured confounders may affect the validity of the point estimate

o Information bias: systematic errors in measurement that result in participants being misclassified with respect to exposure or outcome- Differential: classification errors are more likely in one group over another- Nondifferential: frequency of errors is roughly the same in the groups being compared

o Selection bias: results from the study population being nonrepresentative of the target population, and stems from- Control groups that are not representative of the population that produced the cases- Nonresponse or self-selection, whereby participation is related to exposure status- Differential loss to follow-up, in which the likelihood of being lost to follow-up is associated with exposure and/or outcome status

o Confounding: distortion of the true exposure-outcome relationship by independent variables that are associated with both exposure and

outcome- Can include variables such as age, sex, socioeconomic status, etc.

2. What is the variability?

� Wider confidence intervals indicate reduced precision of the point estimate

� Sample size can affect the estimate of effect size and statistical significance—small studies should be interpreted cautiously

Replication and generalizability

1. Have the results been replicated?

� Can methodologic weaknesses explain discrepancies in results between studies?

2. Is the exposure or intervention likely to have caused the outcome(s) reported?

� Evaluating the body of evidence and methodologic concerns in individual studies can aid in assessment of potential causality

� Although randomized controlled trials are often considered the standard for determining causality, they may be implausible for many

exposures

3. Do the results of a study apply only to particular groups of people?

� Differences between clinical and study populations may result from age, race, cultural factors, presence of comorbidities, etc.

4. Are there differences in the time course of the exposure or intervention under study compared with a clinical population?

RESEARCH TECHNIQUES MADE SIMPLE

the level of variable A does not predict the level of variable B.For each level of one variable, the expected frequencies ateach level of the second variable are calculated. The chi-squared test statistic is based on the difference between thefrequencies that are actually observed and those that wouldbe expected if there were no relationship between the twovariables. The more computationally intensive Fisher exacttest is typically used only when sample sizes are small. Thesetests do not evaluate the magnitude of the association butindicate whether the association is statistically significant. Forexample, in a study examining patient satisfaction aftertreatment for nonmelanoma skin cancer with either destruc-tion, excision, or Mohs surgery, categorical patientcharacteristics were compared among treatment groups usingchi-squared or Fisher exact tests. The training level of thetreating clinician (attending, resident, or nurse practitioner)differed significantly by treatment group (P < 0.001) (Asgariet al., 2009a).The risk difference is the absolute difference in risk be-

tween exposed and unexposed groups, and it is useful forevaluating the excess risk of disease associated with anexposure. The relative risk reduction is the proportion of riskthat is reduced in the exposed group relative to the unex-posed group. The number needed to treat is the number ofpatients who must be treated for one patient to benefit.Calculations for risk difference, relative risk reduction, and

number needed to treat are shown in Figure 2, and examplesare provided in Table 2.

METHODOLOGIC CONSIDERATIONSResources such as the US Preventive Services Task Force,Cochrane Library, International Agency for Research onCancer monographs, UpToDate, and DynaMed Plus provideevidence-based guidelines for clinical practice. However,for many diseases, expert summaries may be unavailable,making the interpretation of clinical research critical forproviders. Accurate interpretation requires a familiarity withmethodologic considerations in epidemiology, outlinedbriefly in this section (Table 3).

Bias and confoundingExamining potential sources of biases or confounding iscrucial for evaluating the validity of study findings (Figure 3)(Delgado-Rodríguez and Llorca, 2004; Sackett, 1979;Silverberg, 2015). Biases are systemic errors that result inincorrect estimation of the exposure-outcome association.Information biases are systematic errors in measurement,which result in participants being misclassified with respect toexposure or outcome. Selection biases stem from the studypopulation being nonrepresentative of the target population.The presence of bias may result in an overestimation or un-derestimation of the true association.

www.jidonline.org 508

Strategy

Stage

Bias

••

•

•

•

• Sele• Mea• Lead

Random samplinAppropriate conunexposed groupWell-defined exposure/outcomEnsure correct exposure/outcomclassification Correction for lelength bias

Study plan

ction bias surement error time bias

g/allocation trol group/ selection

e

e

ead time or

nning

• Imn

• N• A• B

• Blinding/pltrials)

• Confirm se• Minimize l• Assess for

participant

Study

Information bias (emisclassification–nondifferential)

Recall biaIntervieweProceduraquality of

onresponse bias ttrition bias (uneqerkson’s bias

acebo group (for r

lf-reports with meoss to follow-up systematic differens/nonparticipants

y implementation

xposure/outcome may be differentia

s r/observer bias l bias (differences information)

ual loss to follow-

randomized

dical records

nces between

l or

in

up)

• C• M• C• R

• Matching bvariable

• Stratified anregression a

• Sensitivity • Address mi

imputation)• Comparison

Data a

onfounding issing data itation/publicationesults distortion

y the confounding

d/or multivariate nalyses

analyses issing data (e.g.,

with similar stud

analysis

n bias

g

dies

Publishedstudy

d

Figure 3. Strategies to minimize biases common to observational research. Methods for addressing various biases in epidemiologic research are shown,although this list in not exhaustive. Readers are referred to several excellent reviews, including Choi and Pak (2005), Delgado-Rodríguez and Llorca (2004), andSackett (1979).

509

RESEARCH TECHNIQUES MADE SIMPLE

Confounding is a distortion of the exposure-outcome rela-tionship by independent variables that are associated withboth exposure and outcome. Confounding may be minimizedthrough statistical adjustment, stratification, matching, orrandomization. Methods to address confounding have beenreviewed in detail elsewhere (Greenland and Morgenstern,2001; Kim et al., 2017; McNamee, 2005; Wakkee et al.,2014). Suppose that, when examining the association be-tween serum vitamin D levels and skin cancer risk, weobserve an OR of 1.85, indicating an 85% increased risk ofskin cancer among participants with high serum vitamin Dlevels compared with those who have low levels. If partici-pants with high vitamin D levels are also more likely to haveincreased sun exposure, it could erroneously appear thatvitamin D increases the risk of skin cancer. In this hypothet-ical example, when sun exposure is addressed through sta-tistical adjustment, we observe an OR of 1.15. The attenuatedadjusted OR indicates that our unadjusted association wasspurious and due to confounding caused by strong sunexposure-vitamin D and sun exposure-skin cancer associa-tions. The likelihood of observing spurious associations maytherefore be reduced by implementing methods to reduceconfounding. Even when confounding is addressed, however,unmeasured confounders or residual confounding may distortthe observed association.

Statistical significanceAlthough a P-value less than 0.05 is widely considered sta-tistically significant, this cutoff is arbitrary and does not

Journal of Investigative Dermatology (2019), Volume 139

necessarily equate to clinical significance. Effect sizes, whichindicate the magnitude of the difference between groups, andmeasures of variability, such as confidence intervals, aremore informative when interpreting epidemiologic data(Greenland et al., 2016; Sullivan and Feinn, 2012). Wideconfidence intervals indicate large variability and reducedprecision of a point estimate. Other measures of variability ordispersion include range, interquartile range, variance, andstandard deviation. These measures indicate the extent towhich the mean of a given variable represents the studypopulation as a whole.Statistical power is the probability of correctly rejecting the

null hypothesis when it is false, or, alternatively, the likeli-hood of finding a statistically significant difference when onetruly exists (Sullivan and Feinn, 2012). Power is dependentupon effect size and sample size. Overpowered studies withvery large sample sizes may detect very small effect sizes thatare not clinically meaningful (Bhardwaj et al., 2004). Resultsfrom underpowered studies should also be interpreted withcaution, because true associations may be masked by smallsample size, or conversely, spurious, inflated risk estimatesmay be detected (Button et al., 2013).

Finally, when a large number of statistical tests are per-formed, some will be significant at P < 0.05 by chance alone,even when the null hypothesis is true. Statistical correctionsfor multiple comparisons aim to reduce the number of falsepositive findings; they include the Bonferroni correction,which reduces the P-value threshold for significance; resam-pling methods; and adjusting the false discovery rate. More

MULTIPLE CHOICE QUESTIONS1. A study follows adults with psoriasis treated with

either retinoids alone or retinoids withcorticosteroids. The relative risk of 6-monthpsoriasis recurrence is 0.8. What is the correctinterpretation of this finding?

A. The incidence of psoriasis recurrence inadults who are dual-treated with retinoidsand corticosteroids is 0.8 (80%).

B. Adults with psoriasis who are dual-treatedwith topical retinoids and corticosteroidshave 0.8 times the risk of having 6-monthpsoriasis recurrence compared with thosewho receive only retinoid treatment.

C. The difference in risk of 6-month psoriasisrecurrence between adults treated with onlyretinoids and those dual-treated with topicalretinoids and corticosteroids is 0.8 (80%).

D. The difference in risk of 6-month psoriasisrecurrence between adults treated with onlyretinoids and those dual-treated with topicalretinoids and corticosteroids is 0.2 (20%).

2. In a case-control study, what measure ofassociation should be used to calculateassociations between the exposure and outcome?

A. Hazard ratio

B. Pearson correlation coefficient

C. Odds ratio

D. Relative risk

3. Cananoddsratioeverapproximate therelative risk?

A. Yes, when the outcome (i.e., disease) beingstudied is rare.

B. Yes, when the exposure being studied is rare.

C. No, because the odds ratio is calculatedusing odds, and the relative risk iscalculated using incidence rates.

D. No, because these measures are calculatedusing data from different study designs.

4. What are confounders?

A. Variables that are associated only with theexposure

B. Independent variables that are associatedwith both the exposure and the outcome

C. Variables that are associated only with anoutcome

D. Variables that are the consequence of anexposure

5. A chi-squared test is used for what type of data?

A. Discrete quantitative

B. Ratio

C. Continuous quantitative

D. Categorical

RESEARCH TECHNIQUES MADE SIMPLE

detailed information about multiple comparisons may befound in Bender and Lange (2001), Cao and Zhang (2014),and McDonald (2014b).

Replication, causality, and generalizabilityReplication is key in clinical research, and methodologicconcerns that may explain discrepancies between studiesshould be considered. In observational studies, causality be-tween an exposure and outcome is difficult to ascertainconcretely. For many exposures, randomized controlled trialsare implausible, and well-designed observational studies arethe best alternative (Rothman and Greenland, 2005). Clini-cians should also judge the degree to which a study simulatesclinical practice and whether the results are generalizable tohis/her own patient population (Wu et al., 2014). Forexample, mutations in NCSTN, PSENEN, and PSEN1, whichaffect the function of g-secretase, have been strongly associ-ated with familial hidradenitis suppurativa in Chinese in-dividuals. In other populations, however, g-secretasemutations affect only a minority of hidradenitis suppurativapatients (Ingram, 2016). In some instances, lack of general-izability may render study findings noninformative for pop-ulations with different characteristics.

SUMMARYMeasures of association quantify the relationship between anexposure and an outcome, enabling comparison betweendifferent groups, and their validity is highly dependent on themethodologic context in which they were calculated. Interpret-ing epidemiologic findings, therefore, requires an assessment ofstudy methodology, including sources of bias and confounding,generalizability, and replication of results. Evaluating these fac-tors enables clinicians to critically evaluate the strength of evi-dence and make informed decisions for patient care.

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSThis work was supported by the National Institute of Arthritis and Musculo-skeletal and Skin Diseases (K24 AR069760, principal investigator: MMA).

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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after treatment of nonmelanoma skin cancer. Dermatol Surg 2009a;35:1041e9.

Asgari MM, Kiviat NB, Critchlow CW, Stern JE, Argenyi ZB, Raugi GJ, et al.Detection of human papillomavirus DNA in cutaneous squamous cellcarcinoma among immunocompetent individuals. J Invest Dermatol2008;128:1409e17.

Asgari MM, Maruti SS, Kushi LH, White E. A cohort study of vitamin D intakeand melanoma risk. J Invest Dermatol 2009b;129:1675e80.

Asgari MM, Shen L, Sokil MM, Yeh I, Jorgenson E. Prognostic factors andsurvival in acral lentiginous melanoma. Br J Dermatol 2017;177:428e35.

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Bhardwaj SS, Camacho F, Derrow A, Fleischer AB, Feldman SR. Statisticalsignificance and clinical relevance. Arch Dermatol 2004;140:1520e3.

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Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, et al.Power failure: why small sample size undermines the reliability ofneuroscience. Nat Rev Neurosci 2013;14:365e76.

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Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, et al.Statistical tests, P values, confidence intervals, and power: a guide tomisinterpretations. Eur J Epidemiol 2016;31:337e50.

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This is a reprint of an article that originally appeared in theMarch 2019 issue of the Journal of InvestigativeDermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Roberts MR, Ashrafzadeh S, Asgari MM. Research Techniques Made Simple: Interpreting Mea-sures of Association in Clinical Research. J Invest Dermatol 2019;139(3):502e511; doi:10.1016/j.jid.2018.12.023

RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple:Profiling the Skin Microbiota

Max D. Grogan1, Casey Bartow-McKenney1, Laurice Flowers1, Simon A.B. Knight1, Aayushi Uberoi1

and Elizabeth A. Grice1,2

Skin is colonized by microbial communities (microbiota) that participate in immune homeostasis, developmentand maintenance of barrier function, and protection from pathogens. The past decade has been marked by anincreased interest in the skin microbiota and its role in cutaneous health and disease, in part due to advances innext-generation sequencing platforms that enable high-throughput, culture-independent detection of bacteria,fungi, and viruses. Various approaches, including bacterial 16S ribosomal RNA gene sequencing and meta-genomic shotgun sequencing, have been applied to profile microbial communities colonizing healthy skin anddiseased skin including atopic dermatitis, psoriasis, and acne, among others. Here, we provide an overview ofculture-dependent and -independent approaches to profiling the skin microbiota and the types of questionsthat may be answered by each approach. We additionally highlight important study design considerations,selection of controls, interpretation of results, and limitations and challenges.

Journal of Investigative Dermatology (2019) 139, 747e752; doi:10.1016/j.jid.2019.01.024

1DepartmenUniversity o

Correspond

Abbreviatio

ª 2019 The

CME Activity Dates: 20 March 2019Expiration Date: 19 March 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: All authors, plan-ning committee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

t of Dermatology, University of Pennsylvania, Perelman School of Mf Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsyl

ence: Elizabeth A. Grice, 421 Curie Boulevard, BRB 1015, Philadelp

ns: OTU, operational taxonomic unit; rRNA, ribosomal RNA

Authors. Published by Elsevier, Inc. on behalf of the Society for Inv

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Apr19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONThe skin is an ecosystem that supports the growth of aplethora of indigenous microbiota consisting of bacteria,fungi, mites, and viruses. Skin commensal microbes coexistwith the host and contribute to tissue integrity and immunehomeostasis. Perturbation of skin commensal microbialcommunities can influence normal skin health, predisposeskin to pathogenic colonization, and contribute to inflam-matory dermatological disorders. The goal of most skin

v

microbiota surveys is to identify individual taxa (e.g., genera,species, strains) or community features (e.g., diversity, rich-ness) that are associated with a phenotype or a perturbation.Profiling the skin microbiota is often a jumping-off point forstudies that seek to establish causation and/or to dissect themolecular and biochemical mechanisms of host-microbecrosstalk through reductionist approaches. Furthermore,because microbes are exquisitely sensitive to their environ-ment, they are a reservoir of potential biomarkers that could

edicine, Philadelphia, Pennsylvania, USA; and 2Department of Microbiology,ania, USA

hia, Pennsylvania 19104. E-mail: egrice@pennmedicine.upenn.edu

estigative Dermatology. www.jidonline.org 747

SUMMARY POINTSBenefits� Sequencing-based approaches do not requiregrowth and isolation of microorganisms inculture and therefore select for microorganismsthat do not readily grow in isolation underartificial conditions.

� Skin microbiota surveys are a powerfulhypothesis-generating tool that producequantitative, community-wide data sets.

� Several user-friendly bioinformatic tools havebeen developed for the analysis and visualizationof microbiome sequencing data.

� Metagenomic shotgun sequencing isincreasingly being applied to skin microbiota,and it provides strain-level taxonomic resolutionand insight into the genetic repertoire of themicrobiota.

Limitations� Skin specimens are typically low in bioburdenand extremely susceptible to reagent andenvironmental contamination, which producesfalse positive results.

� Culture-independent approaches cannotdistinguish live versus dead microorganisms.

� The sequencing data obtained are associative,and additional experiments are required toshow causality.

� Many analytical approaches require referencedata sets, which are limited for skin microbes,especially fungi.

Box 1. Definitions and misnomers

The authors recommend the adoption of definitionsproposed by Marchesi and Ravel (2015).� Microbiota: The assemblage of microorganismsexisting in a defined environment

� Microbiome: Microorganisms, their geneticmaterial, and the surrounding environmentalconditions

� Metagenomics: The application of shotgunsequencing of DNA to reveal the genomes andgenes of the microbiota

Common misnomers to avoid (Marchesi and Ravel,2015):� 16S/16S analysis/16S survey: The proper term toapply here is 16S rRNA genes or 16S rRNA genesequencing/analysis because the methods thatthese misnomers refer to rely on sequencingDNA and the gene that encodes a structuralsubunit of the ribosomal RNA. RNA is notsequenced, and 16S is a metric that refers toparticle size.

� Microflora: Although widely used in theliterature, the original definition of flora refers toplants and not microbes. The correct term to useis microbiota.

RESEARCH TECHNIQUES MADE SIMPLE

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inform the status of skin health, distinguish between variationsof disease, or suggest optimal treatment approaches. There-fore, exhaustive analyses of skin microbiota can not onlyprovide better understanding of cutaneous processes anddiseases but can also suggest targets for developing therapies.With a growing appreciation for the importance of the

human microbiome has come a surge in the development ofnext-generation sequencing technology and analytical toolsthat serve as the workhorses for characterizing microbialcommunities. Historically, detection and characterization ofskin microbiota has depended on culture-based methods.Next-generation sequencingebased methods eliminate thebiases associated with isolating and culturing microbes in thelaboratory to more precisely profile the composition of mi-crobial communities.Amplicon-based sequencing is the most common strategy

used to construct community profiles of skin microbiota. Thismethod has been extensively used to characterize bacterialcommunities by targeting the highly conserved 16S ribosomalRNA (rRNA) gene, which contains hypervariable regions thatare widely divergent among different bacterial taxa (Laneet al., 1985). More recently, metagenomic shotgun

Journal of Investigative Dermatology (2019), Volume 139

sequencing has been used for both taxonomic and functionalannotation of skin microbial communities. This approachcaptures multikingdom communities (including fungi, viruses,and archaea) at the strain-level resolution and enablesreconstruction of the community-level microbial geneticrepertoire. Here, we provide an overview of the current ap-proaches used to profile skin microbiota, the metrics associ-ated with each, and the bioinformatic tools that arecommonly used to analyze and visualize data. Please refer toBox 1 for definitions of terms used commonly throughout, aswell as misnomers to avoid.

APPROACHES AND METHODSCollection and processing of skin microbiotaspecimens and controlsThe first step in any study to profile the skin microbiota requirescollection of a microbial specimen (Figure 1), and the collectiontechnique can profoundly influence study results. Although a stan-dardized protocol for skin microbiome studies remains to be estab-lished, many investigators use a noninvasive, easy-to-performswabbing technique. Collection techniques, including preparation ofthe skin, were recently comprehensively reviewed by Kong et al.(2017). Whatever technique is chosen, its application should beconsistent across all specimens that are collected and compared inthe study. A well-designed study also controls for factors that mightaffect the existing skin microbial community or expose skin to foreigncommunities (Goodrich et al., 2014). For example, many studiesexclude participants whose skin was exposed to systemic or topical

Extract bulk genomic DNA

bacterial 16S rRNA gene or fungal ITSRandom fragmentation

and sequencing

Amplicon- Based Sequencing

Shotgun Metagenomic Sequencing

Assemble into contigsAssign taxonomy

Predict gene content

Enrichment analysis of metabolic and genetic pathways

Group similar sequences intooperational taxonomic units (OTUs)

Statistical analysis and graphical representation

Specimen collection

Culture microbial isolates

1 3 4 5 62 7 8Cofactor and vitamin biosynthesisCentral carbohydrate metabolismAminoacyl tRNAPyrimidine metabolismSerine and threonine metabolismAromatic amino acid metabolism

Mineral/organic ion transport systemHistidine metabolism

Terpenoid backbone biosynthesisReplication systemATP synthesisCysteine and methionine metabolismLysine metabolism

Samples

Rela

tive

Abu

ndan

ce

1.0

0

GenusEnterobacterFinegoldiaHelcococcusKlebsiellaPeptostreptococcusCorynebacteriumStreptococcusAnaerococcusBrevibacteriumPseudomonasAlcaligenesStaphylococcus

0.5

Samples

Figure 1. Approaches to profiling theskin microbiota. A specimen iscollected and then subjected toculture-dependent and/or culture-independent techniques. Typicalworkflows for amplicon-basedsequencing and shotgun metagenomicsequencing are compared. Examplesof output for each are shown as astacked bar plot depicting relativeabundances of bacteria and a heatmapillustrating enrichment of differentgenetic and metabolic pathwaysamong samples. OTU, operationaltaxonomic unit; rRNA, ribosomalRNA.

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antimicrobials. DNA extraction techniques also should be consistentacross studies and ideally performed using purposely designed kitsthat use a combination of chemical and physical lysis methods (e.g.,detergents and bead beatings), followed by an isolation protocol thatminimizes DNA loss and contamination (Goodrich et al., 2014).

Negative controls are a critical component of any well-designedskin microbiome study because they allow empirical assessment ofbackground contamination from reagents and the environment. Thisis of particular concern for skin samples that are relatively low inbioburden (Salter et al., 2014), and proper steps need to be taken tominimize and/or remove contaminants (de Goffau et al., 2018; Kimet al., 2017). A negative control, null-exposure specimen shouldbe collected and processed through DNA extraction, library prepa-ration, and sequencing exactly as the experimental specimens. It isalso critical to include positive controls. Sequencing of a mockcommunity, containing microbial DNA from known organisms inknown quantities, allows one to benchmark experimental ap-proaches and pipelines. These positive controls can be generatedand validated in house or purchased from a repository.

Amplicon-based sequencing approachesThe 16S rRNA gene provides a highly suitable target for bacterialclassification by DNA sequencing. A description of this method, as itapplies to the skin microbiome, has recently been described in the

“Research Techniques Made Simple” series (Jo et al., 2016). In brief,this region of the bacterial genome consists of conserved and hy-pervariable regions and, in particular for the skin microbiome, theV1eV3 region was found to yield accurate results for taxonomicclassification (Meisel et al., 2016). The V4 primers that arecommonly used in studying microbiota from the gastrointestinal tract(Caporaso et al., 2012) require some minor modifications to capturethe highly prevalent and abundant skin microbe Cutibacterium acnes(Zeeuwen et al., 2017). For the analysis of fungal communities, re-gions of DNA between the 18S, 5.8S, and 28S rRNA genes, termedinternal transcribed spacers, contain both hypervariable regions andconserved regions for taxonomic identification and primer anneal-ing, respectively. The internal transcribed spacer sequence resides ina much broader phylogenetic population and is thought of as a more“universal barcode” for fungi, but the variation also comes with lessaccuracy and specificity in taxonomic identification (Schoch et al.,2012). Additionally, fungi are less studied, and thus, their phyloge-netic placement through computational methods and expert-basedcuration of phylogenetic relationships are lacking, which can be alimiting factor.

Most investigators rely on institutional cores or commercial op-erations to perform the sequencing. Here, we will focus more on thecomputational pipeline of analysis, which starts with the input of rawsequence data and ends with statistical analysis and graphical

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representation of the microbial communities (Figure 1). The currentrecommended pipeline tools are QIIME2, mothur, and HmmUFOtu(Caporaso et al., 2010; Kuczynski et al., 2011; Schloss et al., 2009;Zheng et al., 2018). The first step in the pipeline is preprocessing,in which sequencing errors are eliminated. The next step is groupingof DNA sequences into operational taxonomic units (OTUs). Thisgrouping is based on similarity or sequences that are close based ona defined sequence distance metric (Rossello-Mora and Amann,2001). Because it is highly likely that all microbes in an environ-ment are not known, OTUs have become the standard for catalogingthe microbiome (Rossello-Mora and Amann, 2001; Schloss andHandelsman, 2005).

This process of OTU picking can be achieved in two ways: bymatching sample sequences to a database of reference sequences(such as Greengenes [DeSantis et al., 2006]), or alternatively, the se-quences can be clustered into de novo OTUs with no references.Once clustered, these OTUs are mapped to known sequences todetermine the taxonomic composition of the sample (Caporaso et al.,2010; Zheng et al., 2018). At this stage in the pipeline, the output is anOTU table (formatted as a delimited text file or BIOM file). This tableincludes all OTUs identified; their abundance, or number of reads,found in each sample; and, usually, the taxonomy assigned to eachOTU. The level of taxonomic classification varies in accuracy and isdependent on the region of the 16S rRNA gene sequenced and theidentity of microbes in the sample. Results given at the species levelshould be interpreted cautiously unless customized (e.g., skin-specific)databases are being used (Conlan et al., 2012; Meisel et al., 2016).

Once taxonomic assignment is complete, the typical next step inthe pipeline is to examine the diversity of the microbiome bothwithin and between different samples, termed alpha and betadiversity, respectively. Most of the tools for this analysis weredeveloped by the field of ecology and have been adapted tomicrobial community ecology. The pipeline tools QIIME2 or mothurhave built-in plugins or programs to perform these analyses directly,but many alternative tools exist, particularly for users with statisticaland bioinformatics backgrounds. A large collection of these down-stream tools, such as those in the vegan package (Oksanen et al.,2018), can be installed into an R environment. R is an open-sourcecomputer language/environment designed for statistical analysesand graphical presentation of data (R Core Team, Vienna, Austria). Awidely used R tool is phyloseq, which offers an intuitive suite offunctions to aggregate data, perform statistical analysis, and graphthe results (McMurdie and Holmes, 2013).

Statistical analysis and graphical presentationTypically, microbiome data are nonparametric; the distribution ofdata (OTUs) is unknown, and thus, assumptions about the distribu-tion should not be made when selecting statistical tests. Conse-quently, nonparametric statistics need to be used. For example, inplace of t tests, an appropriate choice is the Mann-Whitney/Wilcoxon rank-sum test. Instead of applying an analysis of vari-ance (i.e., ANOVA) test across more than 2 groups, the Kruskal-Wallis one-way analysis of variance test can be used, and theSpearman rank correlation coefficient should be used rather than thePearson when examining co-occurrence of OTUs and/or taxa.Additionally, microbiome data are inherently multidimensional andthus require specialized tools. One of these is UniFrac (Lozuponeand Knight, 2005), which uses a distance matrix that incorporatesphylogenetic distances in comparing dissimilarity of microbialcommunities between two or more samples (beta diversity).

Journal of Investigative Dermatology (2019), Volume 139

Multidimensional data can be challenging to display visually;three-dimensional graphs can be difficult to interpret, and fourdimensions and greater cannot be drawn. To overcome this, a pro-cedure termed principal component analysis (i.e., PCA) can be used.This is a statistical technique that transforms large sets of observationsinto a set of uncorrelated variables termed principal components,which emphasize the major differences in the data. The first principalcomponent has the largest variation in the data, the second principalcomponent has the next largest variation and is unrelated to the first.The first and second principal components are then plotted as a two-dimensional graph. Other methods that perform this task arenonmetric multidimensional scaling (i.e., nMDS), of which principalcoordinates analysis (i.e., PCoA) is a subtype. The details of thesemethods are beyond the scope of this review, but they permit statisticalanalysis to be performed on the data in the form of a permutationalmultivariate ANOVA, or PERMANOVA. These statistical and graphicaltools are available in the vegan R package. Many other statisticalmethods have been adopted for more specific analyses and graphingof microbiome data, including defining community types throughDirichlet multinomial clustering and identifying biomarkers by testingmultiple decision tree models, in a process known as random forests,both of which can be performed in the R environment.

Shotgun metagenomic sequencingShotgun metagenomic sequencing, or the untargeted sequencing ofall microbial genomes present in a specimen, is considerably richerin providing information than amplicon-based profiling approaches.Unlike amplicon-based sequencing, where specific primers aretargeted to regions of rRNA genes, DNA is prepared for shotgunmetagenomics by random fragmentation, addition of barcodedsequencing tags, and limited cycle amplification (Figure 1). Becauseshotgun metagenomics captures a greater variety of gene content in asample, multikingdom compositions at strain-level resolution (anexample can be found in Oh et al. [2014]), as well as functionalprofiles for communities, are captured. Shotgun metagenomics haveprovided key insights into the skin microbiome in atopic dermatitis,including the role of strain-level variation of Staphylococcus aureus(Byrd et al., 2017) and mechanistic understanding of how microbialmetabolic pathways are altered to enhance ammonia production andincrease skin pH (Chng et al., 2016).

Two different analytical approaches are used for shotgun meta-genomic data sets: assembly-based and read-based profiling (for acomprehensive discussion, the authors recommend Quince et al.[2017]). Although read-based, assembly-free profiling is faster andmitigates issues with assembly, it relies on reference genomes at theexpense of uncharacterized microbes that have no referencesavailable. A popular tool to generate taxonomic profiles withoutassembly is MetaPhlan, which maps shotgun reads to referencemarker genes (Segata et al., 2012). These data may then be used toderive the alpha and beta diversity metrics previously described.Functional profiles can be produced using the HUMAnN tool(Abubucker et al., 2012) or similar, which takes the DNA reads andmaps them against universal gene-protein databases. This allowsidentification of the proteins encoded by the DNA and functionalpathway linkage of the proteins.

A case for integrating culture-dependent and -independentapproachesSequencing technologies have illuminated the diversity of microbialspecies on the skin. However, when evaluating microbial data

MULTIPLE CHOICE QUESTIONS1. Which of the following is an advantage of

culture-independent, sequencing-basedapproaches to analyzing skin microbiota?

A. It distinguishes microbes that are living fromthose that are dead.

B. It establishes causative links.

C. It does not require culturing microbes inartificial conditions.

D. It is difficult to contaminate reagents andsamples.

2. What is the advantage of shotgun metagenomicsequencing compared with 16S rRNA genesequencing?

A. Increased taxonomic resolution

B. Enhanced growth of microbes

C. Recovery of bacterial, fungal, and viralsequences

D. A and C

3. Which of the following is not a recommendedpractice when designing a study for culture-independent profiling of microbiota?

A. Including negative controls to assessbackground contamination

B. Using a variety of DNA extraction kits

C. Controlling for antibiotic exposures

D. Including a mock community as a positivecontrol

4. Which of the following is a common andrecommended practice when analyzing 16SrRNA gene sequencing data?

A. Testing associations/correlations with everysingle variable until something is significant

B. Using parametric statistical tests becausemicrobiome data are always normallydistributed

C. Assigning sequences to operationaltaxonomic units, or OTUs

D. Ignoring sequences in negative controlsamples

5. Which of the following is a bioinformatic tool/pipeline that is commonly used for the analysisof microbiome data sets?

A. QIIME2

B. R

C. mothur

D. All of the above

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observed from sequencing-based techniques, it is important torecognize the limitations. The approaches described measure onlythe presence of DNA in a sample. They are unable to show if thespecies was recently acquired or is a stable community member, atransient member, or deceased. The standard practice to identifymicrobial species in clinical settings relies on culture-based tech-niques. This traditional approach should not be disregarded in thedesign of research studies that take advantage of sequencing tech-nologies, because culture-based techniques are able to identifyviable organisms.

Ideally, samples for culturing should be processed immediatelyafter collection. Depending on the study objective, various mediaand growth conditions can be used to quantify specific organisms. Tosuccessfully culture organisms that are traditionally difficult to grow,such as strict anaerobic bacteria, swabs should immediately behandled in anaerobic conditions. Therefore, if the study objective is togain a comprehensive quantification of the most abundant microbialspecies, then separate specimens should be collected for aerobic andanaerobic growth. Once isolated, colonies can be identified either by16S rRNA gene sequencing, matrix-assisted laser desorption/ionizationetime-of-flight mass spectrometry (i.e., MALDI-TOF), orwhole-genomesequencing, andcomparisonscanbemadewith culture-independent profiles obtained by sequencing-based approaches.

As described previously, reagent contamination is a major prob-lem for low-bioburden microbial samples, including skin samples;examination of culture-based data and literature allows one to assessthe plausibility of observing a given species in the ecosystem of theskin (de Goffau et al., 2018). For example, it is highly unlikely thatextreme halophiles or thermophiles would be present on the skin,because the conditions and nutrients are not consistent with thebiology of these microorganisms; nonetheless, results such as thesecontinue to be reported in the literature in the absence of meaningfulcontrol data. Therefore, we urge readers to critically examine theirdata in the context of the biology of the microorganisms observed,which can be inferred from culture-based techniques.

CONCLUSIONS AND FUTURE DIRECTIONSCulture-independent approaches for examining the skinmicrobiota have their own limitations that warrant consider-ation. These include but are not limited to (i) the inability todistinguish live versus dead organisms; (ii) reliance on refer-ence databases that exclude uncharacterized microbes; (iv)reagent and environmental contamination, that when notproperly controlled for, result in conclusions that are notconsistent with cutaneous biology; and (iv) associative datasets that are unable to distinguish cause and effect. Addi-tionally, the low bioburden of the skin has limited theapplication of techniques such as metatranscriptomics, whichwould allow the assessment of transcriptionally activemicrobiota. Because many of the analytical approachesrequire reference genomes, future efforts should focus onbuilding comprehensive reference databases of skin-specificmicrobes, including yeasts, bacteria, viruses, and othermicroeukaryotes such as Demodex species. Even though agoal of the National Institutes of Health Human MicrobiomeProject was to create 3,000 microbial reference genomes forthis purpose, at present count, only 124 of the 1,556 total

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genomes sequenced were derived from skin (Joint GenomeInstitute, 2019). Finally, increased attention to robust studydesigns and inclusion of essential controls will enable theinterpretation and translation of skin microbiome studies andtheir biological and/or clinical relevance.

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSThis work was supported by awards from the National Institutes of Health(R01-NR-015639, R01-AR-006663 and R00-AR-060873 to EAG), BurroughsWellcome Fund PATH Award (to EAG), and the Linda Pechenik MontagueInvestigator Award (to EAG). This research was also supported by the PennSkin Biology and Disease Resource-Based Center (P30-AR-069589). CB-Mand LF were supported by a Dermatology Research Training Grant (T32-AR-007465).

AUTHOR CONTRIBUTIONSAll authors participated in drafting and finalizing the manuscript andfigures.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

REFERENCESAbubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, et al.

Metabolic reconstruction for metagenomic data and its application to thehuman microbiome. PLoS Comput Biol 2012;8(6):e1002358.

Byrd AL, Deming C, Cassidy SKB, Harrison OJ, Ng WI, Conlan S, et al.Staphylococcus aureus and Staphylococcus epidermidis strain diversityunderlying pediatric atopic dermatitis. Science Transl Med 2017;9(397).

Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK,et al. QIIME allows analysis of high-throughput community sequencingdata. Nat Methods 2010;7:335e6.

Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al.Ultra-high-throughput microbial community analysis on the IlluminaHiSeq and MiSeq platforms. ISME J 2012;6:1621e4.

Chng KR, Tay AS, Li C, Ng AH, Wang J, Suri BK, et al. Whole metagenomeprofiling reveals skin microbiome-dependent susceptibility to atopicdermatitis flare. Nat Microbiol 2016;1(9):16106.

Conlan S, Kong HH, Segre JA. Species-level analysis of DNA sequence datafrom the NIH Human Microbiome Project. PLoS One 2012;7(10):e47075.

de Goffau MC, Lager S, Salter SJ, Wagner J, Kronbichler A, Charnock-Jones DS, et al. Recognizing the reagent microbiome. Nat Microbiol2018;3:851e3.

DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al.Greengenes, a chimera-checked 16S rRNA gene database andworkbench compatible with ARB. Appl Environ Microbiol 2006;72:5069e72.

Goodrich JK, Di Rienzi SC, Poole AC, Koren O, Walters WA, Caporaso JG,et al. Conducting a microbiome study. Cell 2014;158:250e62.

Jo J, Kennedy EA, Kong HH. Research Techniques Made Simple: Bacterial 16Sribosomal RNA gene sequencing in cutaneous research. J Invest Der-matol 2016;136:e23e7.

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Joint Genome Institute. Integrated microbial genomes. https://img.jgi.doe.gov/cgi-bin/imgm_hmp/main.cgi; 2019 (accessed February 18, 2019).

Kim D, Hofstaedter CE, Zhao C, Mattei L, Tanes C, Clarke E, et al. Optimizingmethods and dodging pitfalls in microbiome research. Microbiome2017;5:52.

Kong HH, Andersson B, Clavel T, Common JE, Jackson SA, Olson ND, et al.Performing skin microbiome research: a method to the madness. J InvestDermatol 2017;137:561e8.

Kuczynski J, Stombaugh J, Walters WA, Gonzalez A, Caporaso JG, Knight R.Using QIIME to analyze 16s rRNA gene sequences from microbialcommunities. Curr Protoc Bioinformatics 2011;36:10.7.1e10.7.20.

Lane DJ, Pace B, Olsen GJ, Stahl DA, Sogin ML, Pace NR. Rapid determi-nation of 16S ribosomal RNA sequences for phylogenetic analyses. ProcNatl Acad Sci USA 1985;82:6955e9.

Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparingmicrobial communities. Appl Environ Microbiol 2005;71:8228e35.

Marchesi JR, Ravel J. The vocabulary of microbiome research: a proposal.Microbiome 2015;3:31.

McMurdie PJ, Holmes S. Phyloseq: an R package for reproducible interactiveanalysis and graphics of microbiome census data. PLoS One 2013;8(4):e61217.

Meisel JS, Hannigan GD, Tyldsley AS, San Miguel AJ, Hodkinson BP,Zheng Q, et al. skin microbiome surveys are strongly influenced byexperimental design. J Invest Dermatol 2016;136:947e56.

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Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’Hara RB, et al.Vegan: community ecology package. R package version 2.4-6. http://CRAN.R-project.org/package¼vegan; 2018 (accessed February 18,2019).

Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. Shotgun meta-genomics, from sampling to analysis. Nat Biotechnol 2017;35:833e44.

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Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Re-agent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 2014;12:87.

Schloss PD, Handelsman J. Introducing DOTUR, a computer program fordefining operational taxonomic units and estimating species richness.Appl Environ Microbiol 2005;71:1501e6.

Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al.Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial commu-nities. Appl Environ Microbiol 2009;75:7537e41.

Schoch CL, Seifert KA, Huhndorf S, Robert V, Spouge JL, Levesque CA, et al.Nuclear ribosomal internal transcribed spacer (ITS) region as a universalDNA barcode marker for Fungi. Proc Natl Acad Sci USA 2012;109(16):6241e6.

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This is a reprint of an article that originally appeared in the April 2019 issue of the Journal of Investigative Dermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Grogan MD, Bartow-McKenney C, Flowers L, Knight SAB, Uberoi A, Grice EA. Research Tech-niques Made Simple: Profiling the Skin Microbiota. J Invest Dermatol 2019;139(4):747e752; doi:10.1016/j.jid.2019.01.024

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Research Techniques Made Simple:Mouse Models of Atopic Dermatitis

Doyoung Kim, Tetsuro Kobayashi and Keisuke Nagao

Atopic dermatitis (AD) is a common, chronic inflammatory skin disease characterized by impaired barrierfunction, eczematous dermatitis, and chronic pruritus. Mouse models have been heavily used to deepen ourunderstanding of complicated disease mechanisms in AD and to provide a preclinical platform before per-forming clinical interventional research on novel therapeutic agents in humans. However, what aspects ofhuman AD these mouse AD models faithfully recapitulate is insufficiently understood. We categorized mouseAD models into three groups: (i) inbred models, (ii) genetically engineered mice in which genes of interest areoverexpressed or deleted in a specific cell type, and (iii) models induced by topical application of exogenousagents. To maximize benefits from current murine AD models, understanding the strengths and limitations ofeach model is essential when selecting a system suitable for a specific research question. We describe knownand emerging AD mouse models and discuss the usefulness and pitfalls of each system.

Journal of Investigative Dermatology (2019) 139, 984e990; doi:10.1016/j.jid.2019.02.014

Cutaneous LBethesda, M

CorrespondCenter Driv

Abbreviatio

ª 2019 The

CME Activity Dates: 19 April 2019Expiration Date: 18 April 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: All authors, plan-ning committee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

eukocyte Biology Section, Dermatology Branch, National Institute oaryland, USA

ence: Keisuke Nagao, Dermatology Branch, National Institute of Arthe, Bethesda, Maryland, 20892-1908, USA. E-mail: keisuke.nagao@ni

n: AD, atopic dermatitis

Authors. Published by Elsevier, Inc. on behalf of the Society for Inv

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INTRODUCTIONAtopic dermatitis (AD) is a common, chronic inflammatoryskin disease with underlying barrier impairment and isaccompanied by severe pruritus and associated with type 2/22-mediated inflammation. Recent studies have begun tounveil and dissect the complex pathophysiology in AD,including the genetic basis for barrier impairment, diverseaspects of the dysregulated immune system, and theinvolvement of commensal microbiota, particularly,

f

Staphylococcus aureus. Numerous AD mouse models havebeen generated over the years, each recapitulating one ormore aspects of human AD (Figure 1a). However, a consid-erable gap remains between what has been learned in mousemodels and what information can be translated into humans.Better understanding of each AD mouse model may enableresearchers to perform studies directly relevant to human ADpathogenesis and to identify or validate novel therapeutictargets. To reflect the spectrum of inflammation involved in

Arthritis and Musculoskeletal and Skin Disease, National Institutes of Health,

ritis and Musculoskeletal and Skin Diseases, Building 10, Room 12N240B, 10h.gov

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BENEFITS� Mouse AD models are valuable tools used todeepen mechanistic insight into diseasepathogenesis and to develop novel therapeuticagents in AD.

� Recent advances in genetic engineering haveaccelerated our understanding of the biologicalsignificance of targeted genes in vivo.

LIMITATIONS� Each animal model reflects limited aspects ofhuman AD.

� There remains a considerable translational gapbetween AD mouse models and human AD.

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classic and monogenic AD, as well as in AD mouse models,skin inflammation discussed herein is referred to as eczema-tous dermatitis.

MOUSE MODELS OF ADMouse AD models can be categorized into three groups: (i)inbred strains of mice that develop AD-like phenotypes; (ii)genetically engineered models with either ablation or over-expression of a single gene, either ubiquitously or in a certaincell lineage; and (iii) AD-like phenotypes induced by exog-enous agents. Understanding the strengths and limitations ofeach model would allow researchers to select a system that issuitable for a particular research question and to be aware ofthe caveats that need be considered.

Figure 1. Examples of AD mousemodels. (a) Features of AD mousemodels that may be considered forphenotype analyses. (b) Grossphenotype and histology of an8-week-old Adam17fl/fl Sox9-Cremouse and a littermate control. (c)Phenotype and histology of MC903-induced AD-like inflammation;45 mmol/L of MC903 in ethanol wasapplied onto back skin of a C57BL/6mouse every other day for 14 days.Scale bars ¼ 50 mm. AD, atopicdermatitis.

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Inbred modelsImpaired skin barrier is a fundamental component of ADpathogenesis. Genetic studies have linked several chromo-somal loci or genes involved in epidermal differentiation torisk of AD. FLG mutations (a genetic cause for ichthyosisvulgaris) contribute to barrier defect and represent a majorpredisposing factor for AD development in humans (Brownet al., 2012; Kezic et al., 2011). The flaky tail mice (ma/ma,Flgft/ft) harbor mutations in genes involved solely in kerati-nocyte homeostasis. These mice develop spontaneouseczematous dermatitis under specific pathogen-free condi-tions, with enhanced immune responses against percuta-neous antigens (Fallon et al., 2009). Mutations in Flg andTmem79 have been identified, the latter causing a defect in acomponent of lamellar granule assembly machineries,conferring both matted hair and spontaneous AD-like phe-notypes (Sasaki et al., 2013; Saunders et al., 2013). Segrega-tion of the two mutated genes determined Tmem79, but notFlg, as the causative gene mutation that drove eczematousdermatitis. Consistently, genomic ablation of Flg is not suffi-cient for spontaneous onset of the AD-like phenotype, eitherunder specific pathogen-free conditions or upon S. aureusinoculation (Kobayashi et al., 2015), further indicating that atleast one additional defect is required for the development ofeczematous dermatitis (Kawasaki et al., 2012; Sasaki et al.,2013).Another inbred strain is the NC/Nga mouse, in which

pruritic skin lesions develop when mice are maintained underconventional housing conditions (Matsuda et al., 1997). NC/Nga mice, like the flaky tail mice, exhibit pronounced type 2immune responses. The genetic determinant in these miceappears to be localized in chromosome 9, which includesgenes involved in immunity, such as Thy1, Cd3d, Cd3e,

Table 1. Summary of the representative preclinical mouse models of human atopic dermatitisCategory Advantages/Limitations Examples Characteristics References

Inbred modelsPros: resembles natural course of human AD;enhanced percutaneous sensitization tohaptens and allergensCons: lack of genetic information in somestrains; variable induction protocols whencombined with hapten or allergen challenges;some models do not spontaneouslydevelop dermatitis under specificpathogen-free conditions

Flaky tail(ma/ma, Flgft/ft)

� Recapitulates barrier defect in asubset of human AD

� Combined genetic alteration ofFlg and Tmem79

Fallon et al., 2009Sasaki et al., 2013

Saunders et al., 2013

NC/Nga � Spontaneous onset in conventionalhousing condition

� Genetic determinant linked toimmune-related genes

Kohara et al., 2001Matsuda et al., 1997

Genetically engineered modelsPros: useful in elucidating gene-specificfunctions in vivo; powerful when crossedwith other strainsCons: time consuming and expensiveto generate; undesirable effects fromunexpected gene expression or alteration(i.e. variable penetrance,inefficiency of Cre)

OverexpressionIL-4 (K14-IL4 Tg)

IL-13 (K5-tTA-IL13 Tg)� Keratinocyte-specific overexpressionof type 2 cytokines, recapitulatinghuman AD, including chronicparenchymal changes

Chan et al., 2006Zheng et al., 2009

IL-31 (EF1a-IL31or Em-Lck-IL31 Tg)

� Pruritus and disruption of theskin barrier

Dillon et al., 2004

TSLP (K5-rtTA-TSLPTg)

IL-18 (K14-IL18 Tg)IL-33 (K14-IL33 Tg)

� Keratinocyte expression of type 2cytokines that activate innatelymphoid cells

Imai et al., 2013Konishi et al., 2002Yoo et al., 2005

JAK1(Jak1spade/spade)

� JAK1 hyperactivation leadingto barrier dysfunction

Yasuda et al., 2016

AblationADAM17

(Adam17fl/fl Sox9Cre)� Spontaneous dysbiosis andeczematous skin inflammation

Kobayashi et al., 2015

CARMA-1(unmodulated)

� N-ethyl-N-nitrosoureaeinduced,genome-wide mutagenesis model

� Mutation in mouse ortholog ofCARMA-1/CARD11

Jun et al., 2003

Models induced by exogenous agentsPros: time-controlled induction;applicable to various mouse strainsCons: nonstandardized products for someallergens; variable protocols (doses anddurations); labor-intensive(daily applications)

Hapten-induced(e.g., oxazolone,

trinitrochlorobenzene(TNCB))

Allergen-induced(e.g., ovalbumin,house dust mite)

� AD-like inflammation inducedby repeated challenge

� Ambiguous distinction betweenAD and allergic contactdermatitis

Kitagaki et al., 1995, 1997Matsuoka et al., 2003Spergel et al., 1998Wang et al., 2007

MC903(calcipotriol)-induced

� High reproducibility of AD-likeresponses in various strains

Kim et al., 2013Li et al., 2006

Myles et al., 2016Naidoo et al., 2018Oetjen et al., 2017

Abbreviation: AD, atopic dermatitis.

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Cd3g, Il10ra, Il18, and Csk (Kohara et al., 2001). Thus, thesemice, in contrast to the flaky tail mice, might reflect thealtered immune component of AD. Although the spontaneousnature of inbred mice may reflect the natural course in humanAD, it is not trivial to pinpoint the underlying genetic defect. Itshould also be noted that genetic background-unique modi-fiers may either attenuate or aggravate phenotypes in anymouse model. Therefore, it is important that researchers becognoscenti regarding the genetic backgrounds of the miceand choose appropriate controls.

Genetically engineered modelsThe overall complexity of AD pathogenesis and the vastnumbers of secondary gene changes downstream of chronicinflammation hampers the narrowing down of genes that play

central roles in AD pathogenesis. In this regard, transgenicand knockout or conditional knockout mice are valuable inelucidating the biological significance of the targeted mole-cules. Genetically engineered mice with altered expression ofAD-related genes would provide an approach to investigatingthe biological function of each molecule. The generation ofgenetically engineered mice is time consuming and costly,requiring strategic planning. A list of selected mouse strainswith genetic modification is shown in Table 1.Transgenic mice overexpressing type 2 cytokines, IL-4 or

IL-13 in epidermis, develop spontaneous pruritus and chronicdermatitis. In both strains, skin lesions are characterized byprominent infiltration of T cells, mast cells, eosinophils, andmacrophages, and total IgE and IgG1 are elevated in serum(Chan et al., 2001; Zheng et al., 2009). These models also

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recapitulate chronic epithelial and stromal changes observedin human AD, such as acanthosis or dermal remodeling withfibrosis and increased vasculature. The efficacy of dupilumab,a monoclonal antibody that blocks the binding of these cy-tokines to their cognate receptor, emphasizes that thesetransgenic mice are effective AD models. However, lymphoidcells, rather than keratinocytes, produce IL-4 and IL-13 inboth mice and humans under physiological conditions.IL-31, the predominant source of which are T helper type 2

cells, is associated with pruritus and disruption of the physicalskin barrier, and it has recently gained attention as a noveltherapeutic target in AD (Dillon et al., 2004; Feld et al., 2016;Ruzicka et al., 2017). Transgenic mice overexpressing IL-31,driven by the ubiquitous promoter for EF1a, develop hairloss by 2 months of age and display dermatitis with prominentscratch behavior (Dillon et al., 2004).Keratinocyte-derived cytokines may also play crucial roles

during atopic inflammation. TSLP is a keratinocyte-derivedtype 2 cytokine. A doxycycline-inducible, keratinocyte-specific transgenic expression of TSLP (K5-TSLP) in miceleads to the onset of AD-like skin lesions after 2e3 weeks ofdoxycycline treatment, with concomitant increase in serumtotal IgE and the type 2 immunity-associated chemokineCCL17 (Yoo et al., 2005). Keratinocyte-specific expression ofthe IL-1 family of cytokines, IL-18 and IL-33, each also exhibitAD-like phenotypes (Imai et al., 2013; Konishi et al., 2002).Given the fact that TSLP transgenic mice lacking conventionalT cells (K5-TSLP, TCRb�/�) still develop skin inflammationand that the three keratinocyte-derived cytokines, TSLP, IL-18, and IL33, are important tissue-derived cytokines thatactivate group 2 innate lymphoid cells (i.e., ILC2), thesemodels might be useful in studying the crosstalk betweenkeratinocytes and innate immunity. An anti-IL-33 antibody iscurrently under clinical trial (NCT03738423, NCT03736967).Although IL18 has not been associated with human AD ingenome-wide association studies, loci including IL18R1 andIL18RAP have been reported, implicating the involvement ofthis cytokine (Tamari and Hirota, 2014).The imbalance of skin commensal microbiota, termed dys-

biosis, is now a recognized feature of human AD. AlthoughS. aureus colonization in AD skin has been known for morethan half a century, whether it contributed to pathogenesis, orwas merely a result of chronic inflammation, had beendebated. A mouse model that recapitulated this condition hadbeen lacking. We recently reported that Adam17fl/fl Sox9-Cremice, which lack ADAM17 in keratinocytes, spontaneouslydeveloped dysbiosis that was dominated by Corynebacteriumspecies and S. aureus (Kobayashi et al., 2015). These micedisplay dry skin at approximately 3e4 weeks after birth, thendevelop overt eczematous dermatitis at approximately 6 weeks(Figure 1b). Eczematous dermatitis is preceded by the emer-gence of S. aureus, and targeting of the dysbiotic organismswith antibiotics extinguishes skin inflammation (Kobayashiet al., 2015). Although eczematous dermatitis is less promi-nent in the absence of S. aureus in mice housed in facilitieswith stringent health status (unpublished observation), this canbe taken advantage of by inoculating S. aureus to induceeczematous dermatitis in a time-controlled manner.AD mouse models have also been established through

screening libraries following chemically induced, genome-

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wide mutagenesis. Heterozygous mutations in CARD11,encoding a scaffolding protein involved in lymphocyte re-ceptor signaling, are linked with monogenic AD in humans(Ma et al., 2017). Growing evidence suggests a benefit oftargeting Janus kinase in AD (Guttman-Yassky et al., 2019). Inthese contexts, two N-ethyl-N-nitrosoureaederived models,CARMA-1/Card11-mutant mice (Jun et al., 2003) andJAK1spade/spade mice (Yasuda et al., 2016) might be interestingmodels for understanding atopic inflammation from the im-mune signaling perspective.

Models induced by epicutaneous application of exogenousagentsInduced mouse models are perhaps the most frequently usedsystems in the fields of dermatologic research such asimmunology and carcinogenesis. Although topical applica-tion can be labor intensive, it enables time- and dose-controlled induction of a phenotype and can be used in avariety of mouse models, including genetically modifiedmice.Haptens are small molecules that penetrate intact mouse

epidermis and provoke adaptive immune responses uponsubsequent exposures, resulting in contact hypersensitivityresponses that model allergic contact dermatitis in humans.Repeated hapten challenge is reported to induce AD-likedermatitis by shifting type 1 to type 2 responses (Kaplanet al., 2012; Kitagaki et al., 1995, 1997). Allergic contactdermatitis and AD are distinct entities, and whether dermatitisinduced by chronic hapten application recapitulates eczem-atous dermatitis remains to be determined.Sensitization to protein antigens is thought to occur in pa-

tients with AD and may contribute to the onset of food allergyand asthma, known as the atopic march. Multiple epicuta-neous exposure to ovalbumin can induce AD-like symptoms(Spergel et al., 1998) with ovalbumin-specific IgG1, IgG2a, andIgE humoral responses (Wang et al., 2007). Human AD-likesymptoms can also be induced by applications of house dustmite extract onto mouse skin (Matsuoka et al., 2003). Skinchanges in both models are enhanced when the barrierdisruption is induced mechanically or by using mice thatexhibit spontaneous skin barrier perturbation, such as NC/Ngaor flaky tail mice. The relevance of skin inflammation inducedin the house dust mite model has yet to be determined,because humans presumably are not exposed to high doses ofhouse dust mite antigens percutaneously. Commerciallyavailable house dust mite and ovalbumin allergen productscan vary in their allergen composition and concentration,depending on how they are prepared (Casset et al., 2012).

Although rash observed during topical application of cal-cemic vitamin D3 analogs in psoriasis patients is clinicallydistinct from AD, topical application of MC903 (calcipotriol)to mouse skin recapitulates features of AD (Figure 1c), such asinflammation, itch, and barrier dysfunction (Li et al., 2006;Naidoo et al., 2018). Mice treated with MC903 also haveincreased serum IgE. Conveniently, these AD-like responsescan be induced regardless of genetic backgrounds, enablingthe use of this model in mice that carry multiple transgeneswithout the necessity for backcrossing, which may facilitatetheir use in preclinical studies. Emerging concepts of ADpathogenesis such as innate lymphoid cells, sensory neuron,

MULTIPLE CHOICE QUESTIONS1. The MC903 model used to study human atopic

dermatitis represents which category of mousemodel?

A. Inbred model

B. Genetically engineered transgenic model

C. Genetically engineered knockout model

D. Model induced by an exogenous agent

2. Which of the following mutations is the mostresponsible for atopic dermatitis-likeinflammation in flaky tail mice?

A. Flg

B. Tmem79

C. Tslp

D. Adam17

3. Which of the following cytokines fromkeratinocytes is responsible for the activationof group 2 innate lymphoid cells 2 (ILC2)?

A. TSLP

B. IL-18

C. IL-33

D. All of the above

4. Which of the following microbes is responsiblefor the development of skin inflammation inAdam17fl/fl Sox9Cre mice?

A. Cutibacterium acnes

B. Malassezia furfur

C. Pseudomonas aeruginosa

D. Staphylococcus aureus

5. Which of the following sentences highlights alesson from a recent study that comparedtranscriptomic profiles between human atopicdermatitis (AD) and mouse models?

A. The oxazolone-induced mouse modelexhibited the highest degree of overlapwith human AD.

B. More than 50% of core signatures of thehuman AD transcriptome overlapped withthe differential expression genes analyzedin all tested mouse models.

C. Based on available databases, less than 5% ofprotein coding genes are not shared inmouse and human AD.

D. Each animal model reflects limited aspects ofhuman AD.

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or microbiota have also been explored by using this model(Kim et al., 2013; Myles et al., 2016; Oetjen et al., 2017).

Comparison of murine AD models to human ADTo date, the gross phenotypes of mouse models have beencorrelated with human AD by comparing clinical

manifestations, histology, and expression of a limited numberof markers. However, emerging cutting-edge technologieswith transcriptomic analysis now deepen our understandingof each model and should allow us to compare complexmolecular networks between species. Comparison of geneexpression data from mouse models to a differentiallyexpressed list (meta-analysis derived AD: “MADAD”) of 595genes from human AD skin defined by meta-analysis showedthat the IL-23einjection model, a cytokine that is usuallyassociated with psoriasis, exhibited the highest degree ofoverlap (Chan et al., 2006; Ewald et al., 2017). Our analysisof Adam17fl/fl Sox9-Cre mice showed overlap with the humanAD transcriptome to a degree that was comparable to the IL-23einjected model (Woodring et al., 2018). However, themaximum overlap of genes remains under 40% in any model,suggesting that animal models each reflect limited aspects ofhuman AD. These observations warrant further evaluations ofthe predictive power of each as preclinical models. Oneapproach to identifying a model that reflects human AD mightbe to test whether therapeutics with known clinical efficacy inhumans are also effective in AD mouse models. It is possiblethat mouse models reflect certain subsets of classic humanAD and that further clinical subcategorization of AD isneeded. More than 20% of protein coding genes are notshared between mice and humans, suggesting that the twospecies may have developed unique immune systems afterdivergence from common ancestors. Future analysis mayrequire the establishment of bioinformatics analytical frame-works with an evolutionary systems biology approach.

CONCLUSIONS AND FUTURE PERSPECTIVESWe have highlighted the diversity of current murine ADmodels and their advantages and limitations that should beconsidered when selecting a model that is appropriate foreach research question or interpreting published studies. Toincrease the translatability of AD mouse models, it may bebeneficial to establish phenotype criteria and accumulatetranscriptome data, which should facilitate distinction ofeczematous dermatitis from other forms of skin inflammation(Figure 1a), such as psoriasis and contact hypersensitivity.Practical and reproducible approaches for evaluating thedegree of inflammation are also essential, because earthickness, transepidermal water loss, and other laboratoryassays are variably used. A standardized clinical scoringsystem should be useful in reducing variability betweenstudies (Kobayashi et al., 2015; Plant et al., 2012). Finally,beyond mouse models, nonmurine animal models for ADsuch as canine AD may better recapitulate human AD andthus be powerful models for preclinical studies (Cosgroveet al., 2013; Michels et al., 2016).

ORCIDsDoyoung Kim: http://orcid.org/0000-0002-0194-9854Tetsuro Kobayashi: https://orcid.org/0000-0003-2316-4748Keisuke Nagao: http://orcid.org/0000-0002-7005-3138

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSWe apologize to those in the field whose work could not be included becauseof space constraints.

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This research was supported by the Intramural Research Program of theNational Institute of Arthritis and Musculoskeletal and Skin Diseases of theNational Institutes of Health.

AUTHOR CONTRIBUTIONSWritingeoriginal draft preparation by DK, with assistance from TK;writingereview and editing by KN.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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Yoo J, Omori M, Gyarmati D, Zhou B, Aye T, Brewer A, et al. Spontaneousatopic dermatitis in mice expressing an inducible thymic stromal lym-phopoietin transgene specifically in the skin. J Exp Med 2005;202:541e9.

Zheng T, Oh MH, Oh SY, Schroeder JT, Glick AB, Zhu Z. Transgenicexpression of interleukin-13 in the skin induces a pruritic dermatitis andskin remodeling. J Invest Dermatol 2009;129:742e51.

This is a reprint of an article that originally appeared in theMay 2019 issue of the Journal of Investigative Dermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Kim D, Kobayashi T, Nagao K. Research Techniques Made Simple: Mouse Models of AtopicDermatitis. J Invest Dermatol 2019;139(5):984e990; doi:10.1016/j.jid.2019.02.014

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RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple: Parabiosis toElucidate Humoral Factors in Skin Biology

Casey A. Spencer1 and Thomas H. Leung1,2,3

Circulating factors in the blood and lymph support critical functions of living tissues. Parabiosis refers to thecondition in which two entire living animals are conjoined and share a single circulatory system. This surgicallycreated animal model was inspired by naturally occurring pairs of conjoined twins. Parabiosis experimentstesting whether humoral factors from one animal affect the other have been performed for more than 150 yearsand have led to advances in endocrinology, neurology, musculoskeletal biology, and dermatology. Thedevelopment of high-throughput genomics and proteomics approaches permitted the identification of po-tential circulating factors and rekindled scientific interest in parabiosis studies. For example, this technique maybe used to assess how circulating factors may affect skin homeostasis, skin differentiation, skin aging, woundhealing, and, potentially, skin cancer.

Journal of Investigative Dermatology (2019) 139, 1208e1213; doi:10.1016/j.jid.2019.03.1134

1DepartmenMedical Cen

Correspond

Journal of I

CME Activity Dates: 21 May 2019Expiration Date: 20 May 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: All authors, plan-ning committee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

t of Dermatology, University of Pennsylvania School of Medicine, Pter, Philadelphia, Pennsylvania, USA; and 3Institute for Regenerativ

ence: Thomas Leung, 421 Curie Boulevard, 1006 BRB II/III, Philadel

nvestigative Dermatology (2019), Volume 139 ª 2019 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Jun19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONThe techniques resulting in parabiosis began in the 1860swhen French biologist Bert tested the viability of skin allo-grafts by joining two rats together and attaching flaps of skinfrom one animal to another (Bert, 1864). He showed that aviable cross-circulation was established by injecting fluid intothe tail vein of one animal and observing its appearance inthe partner animal. In 1908, Sauerbruch and Heyde coinedthe term parabiosis and modified the technique by extendingthe length of the incision and adding an intestinal

he

p

anastomosis (Sauerbruch and Heyde, 1908). In 1933, Bunsterand Meyer improved on the technique by joining the skin,muscle layers, and abdominal wall together (Bunster andMayer, 1933). The union became more stable, and this pro-tocol remains the basis of most modern approaches. Interestin parabiosis peaked in the 1960s and 1970s as scientistsused it to study a variety of topics, including cancer, lifespan,blood pressure, and energy balance.In 1959, Hervey used parabiosis to show that a circulating

factor was involved in energy balance (Hervey, 1959). He

iladelphia, Pennsylvania, USA; 2Corporal Michael Crescenz Veterans AffairsMedicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

hia, Pennsylvania 19104, USA. E-mail: thl@pennmedicine.upenn.edu

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTS� Parabiosis experiments connect two livinganimals together, so that they share a singlecirculatory system.

� Parabiosis experiments assess whether acirculating factor in blood or lymph from oneanimal may affect the other animal.

� Heterochronic parabiosis (connecting young andaged animals together) asks whether physiologicskin processes are affected by young bloodmilieu.

LIMITATIONS� Animals should be background-matched to havethe best chance of survival.

� Circulatory system anastomosis requires 2 weeksto mature before a steady state is reached.

RESEARCH TECHNIQUES MADE SIMPLE

parabiosed young rats together and damaged the ventrome-dial hypothalamus of one parabiont to induce hyperphagiaand obesity. Despite unlimited access to food, the non-lesioned partner stopped eating, lost weight, and appeared tobe responding to a circulating satiety factor released by theother rat. These studies were later confirmed with obese/obese and diabetic/diabetic mice, which showed that obesemice lacked a circulating signal that regulated energy balanceand that diabetic mice appeared insensitive to the signal (seereview in Harris, 2013). The signal was identified to be leptin,and subsequent parabiosis experiments confirmed leptin’sability to circulate between parabionts.In recent years, investigators resurrected parabiosis to study

questions of aging in somatic stem cells. Because musclefunction declines with age, they asked if the change was dueto stem cell intrinsic change or whether stem cell functionalitymay be influenced by their surroundings (Conboy et al.,2005). The results of these studies unequivocally showedthat the aged environment impairs the regenerative potentialof older individuals. When exposed to young blood, agedstem cells adopted a more youthful potential. When youngstem cells are exposed to aged blood, they lost regenerativepotential (Brack et al., 2007). Similar studies havenow been extended for neurons and brain function (Villedaet al., 2011, 2014).Our group used parabiosis in studies of scar formation and

skin regeneration. Physicians have observed that surgicalwounds in the elderly heal with thinner scars than wounds inyoung patients. We showed that full-thickness skin wounds inaged, but not young, mice fully regenerate (Nishiguchi et al.,2018). We connected aged and young mice together, termedheterochronic parabiosis, to elucidate whether the observedphenotypes—scar formation and skin regeneration—arecaused by circulating factors or local signaling (Figure 1). Ourresults showed that exposure of aged animals to blood fromyoung mice counteracts their regenerative capacity (Figure 2).

We identified the factor by performing global transcriptomicanalysis of wound-edge tissue from regenerating and non-regenerating mice. We distilled a list of 80 potential genes to13 genes by looking for circulating proteins. We showed thatSDF1 is expressed at higher levels in the wounded skin ofyoung mice and that genetic deletion of SDF1 in young skinenhanced tissue regeneration.

BASIC PRINCIPLES OF PARABIOSIS: EXPERIMENTAL DESIGN,METHODOLOGY, AND INTERPRETATIONSThe technique of establishing the parabiotic state was recentlyreviewed, and an excellent video describes the surgical procedure(Kamran et al., 2013). Before parabiosis surgery, pairs should be co-housed for 1 week for proper acclimation. We remove fur 24 hoursbefore surgery to shorten anesthesia time during the formal proced-ure. Standard aseptic surgical procedures are used, and the animalsare kept warm with a heating pad. Briefly, mirror-image incisions atthe left and right flanks are made through the skin, and skin is gentlyfreed from superficial fascia. At this point, investigators may chooseto join the peritoneal walls of the mice (Villeda et al., 2011, 2014).We and others omit the peritoneal joining to minimize invasivenessof the procedure, and we still establish an effective blood exchange.Elbow and knee joints from each parabiont are sutured together.After joints are stabilized, the skin flaps of the mice are suturedtogether—first dorsally, then ventrally. Kamran et al. (2013) recom-mend a continuous suture, but in our experience, the use of singleinterrupted sutures minimizes wound dehiscence if the suture fails oris removed by the animal. Other techniques call for stapling the skinof each mouse together (Villeda et al., 2011, 2014). The time tocomplete the surgery ranges between 30 and 60 minutes, dependingon the experience of the surgeon. In particular, the decisions ofwhether to join the peritoneums and how extensively to join thelimbs will influence the duration of the surgery and the stability of thepairings.

The postprocedure care is more critical than the procedure itself.For postoperative pain, each mouse is treated with antibiotics, sub-cutaneous normal saline, meloxicam, and buprenorphine hydro-chloride. We have found that placing Steri-Strips (3M, St. Paul, MN)vertically over the skin sutures 2 to 3 days after the procedure pro-vides a physical barrier against the parabionts removing the suture.Several recovery characteristics are analyzed daily after surgery,including weight, grooming responses, urination, and defecation.Animals are excluded if they fail overall health inspections. If suturesare removed by the mice, they are replaced on a daily basis. Theincisions are healed 2 weeks after surgery, and sutures may beremoved. For our skin-wounding studies, we waited 4 weeks aftersurgical connection to perform additional skin injury to maximize therecovery from the procedure. This time period may be adjustedbased on the specific experiment. We and others have kept para-biotic pairs connected for 8 months without significant problems(Kamran et al., 2013). Taken together, female, background-matchedmice of similar size and weight offer the greatest chance of successfor parabiosis experiments.

Technical challengesPerioperative mortality remains one of the major challenges inparabiotic experiments. However, the survival of parabiotic pairs hasimproved significantly with better anesthesia and postoperativemonitoring. In our experience, more than 90% of our pairs recover

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WoundParabiont A adopts

phenotype B

Both parabionts maintainindividual phenotypes

Systemiccirculating factor

Localcell signaling

Both parabiontsmaintain phenotype B

Parabiont B adopts phenotype A

Both parabiontsmaintain phenotype A

Pairings

CONTROLIsochronic parabiosis BB

EXPERIMENTALHeterochronic parabiosis AB

Isochronic parabiosis AA

CONTROL

ConclusionObservationIntervention

Figure 1. Example of parabiosis experiment to test age-defined phenotypes. Comparing heterochronic parabiosis pairs to isochronic parabiosis control pairsallows for assessment of age-mediated changes. An optional intervention, such as skin wounding or UV exposure, may be added. Isochronic control pairs shouldmaintain their baseline individual phenotype. If so, we conclude that the parabiosis procedure itself does not alter the phenotype. If both mice in a heterochronicparabiosis pair maintain their original individual phenotypes, we conclude that no circulating factor is involved in this phenotype. If either parabiont adopts anew phenotype, we conclude that a systemic circulating factor may be responsible for the phenotypic change.

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RESEARCH TECHNIQUES MADE SIMPLE

from the procedure, similar to results reported by others (Conboyet al., 2013).

Parabiosis involves the continuous exchange of fluids and cellsbetween partners, and a second period of high mortality, calledparabiotic disease (also known as parabiotic disharmony or para-biotic intoxication), occurs 1e2 weeks after surgery when thevascular anastomoses are maturing. The condition is independent ofthe procedure. The incidence can still be as high as 20%e30% ofpairs in highly inbred strains of mice and rats and 60%e70% inoutbred strains of mice (Conboy et al., 2013; Finerty and Panos,1951). One parabiont becomes pale, anemic, stops eating, anddies within a few days. The other member develops hyperemia, bestnoted by reddening and dilation of blood vessels of the feet, ear, andtail (Harris, 2013). If the parabiosis pair is separated when thesesymptoms are first noted, it is possible that both of the individualanimals will survive (Hall and Hall, 1957). Parabiotic disease likelyrepresents underlying graft-versus-host disease, where the rejected“organ” may be the vascular anastomoses. Lethal irradiation of oneof the parabionts abrogates parabiotic disease, suggesting that theimmune system is responsible. How the immune system of onemouse becomes dominant over that of the other mouse remains anopen question. Finally, we noticed that the incidence of parabioticdisease is much less frequent when members of a pair were litter-mates, which has been observed in other studies (Binhammer et al.,1963; Eichwald et al., 1959).

Kinetic considerationsThe on-rate for any parabiotic effect is 1e2 weeks after surgery topermit sufficient vascular connections to develop and mature. This

Journal of Investigative Dermatology (2019), Volume 139

rate seems to be similar in animals of all ages. For our studies of skinwound healing, we waited for 1 month before further skin injury. Anobjective way to determine whether the parabiosis procedureestablished sufficient blood exchange is to connect a mouse carryinga reporter gene (e.g., mTmG mouse) and a nonreporter mouse. Threeweeks after parabiosis, we drew venous blood from the mice androutinely obtained mixing rates between 35% and 40%, which isconsistent with those reported by others (Conboy et al., 2005;Nishiguchi et al., 2018). Other groups have reported similar find-ings, where mixing equilibrium is reached within 14 days but not 7days after surgery (Gibney et al., 2012).

A second kinetic consideration is the rate of clearance of factorsfrom the circulation. The rate of blood exchange in parabiosismodels is relatively slow. Some proteins may be cleared from thecirculation faster than they can exchange. Thus, some factors maynot reach the partner in a parabiotic pair, and this result may lead toa false negative conclusion that a circulating factor is not involved.Harris et al. (2013) provide a more in-depth discussion on bloodexchange and clearance rates in parabiosis. Acute cross-circulationstudies achieved by directly connecting large blood vessels be-tween two animals results in complete mixing of blood in less than10 minutes, and it is more likely that rapidly cleared factors will bepresent at high enough concentrations to be active in the other an-imal (Epstein et al., 1966; Laplace, 1980; Stewart et al., 1963).

APPLICATIONS OF PARABIOSISThere are three common applications for which parabiosisexperiments may be helpful in skin research.

Isochronic

Aged:Aged

Young:Young

Heterochronic

Young Parabiont

Aged Parabiont

Weeks

Young:Youngor

Aged:Aged

Young:Aged

HeterochronicParabiosis

IsochronicParabiosis

Young:Younga b

Aged:Aged

Young Parabiont

Aged Parabiont

00

1

2

Wou

nd S

urfa

ce A

rea

(mm

2 )

3

4

1 2 3 4

***

Figure 2. A circulating factorpromotes scar formation in agedmice. (a) Isochronic aged:agedparabiosis led to significant woundclosure, while isochronicyoung:young parabiosis did not, asphotographed. Within theheterochronic parabiosis pairs, theaged parabiont did not close its earhole and adopted the young parabiontphenotype. (b) Ear hole measurementsof individual parabionts within eachpair. n ¼ 5. ***P < 0.001, comparingaged:aged with young:young or eitherparabiont of young:aged. Aged:agedparabionts had significant woundclosure compared with young:youngor young:aged parabionts.

Parabiont A Parabiont B

Potential physiological conditions

Aged

Mutant

Wounded

Irradiated

Infected

Obese

Young

Wildtype

Unwounded

Non-irradiated

Non-infected

Lean

Figure 3. Potential physiological conditions to be studied with parabiosis.Parabiosis may be used to study a variety of phenotypes. Potentialphysiological conditions are not limited to the provided list.

RESEARCH TECHNIQUES MADE SIMPLE

1. The most common use of parabiosis in dermatologystudies is to test whether a circulating factor may beinvolved in a specific skin physiologic process, that is,differentiation, neoplastic formation, or wound healing.The circulating factor is induced in one animal, and thepaired animal is assessed for a change in phenotype. Miceused for parabiosis can vary in physiological condition,making parabiosis an ideal technique for understanding avariety of biological processes (Figure 3). Parabiosis sur-gery is also reversible, which allows confirmation that acirculating factor is responsible for a phenotypic change.

2. Parabiosis has been instrumental in answering questionsabout systemic regulation of cell and tissue aging in mul-tiple organs. Heterochronic parabiosis allows researchersto test whether constant exposure to young or old bloodchanges physiologic skin processes (Figure 1). Here, weused heterochronic parabiosis to assess changes in scarformation and wound healing with age. A similar approachmay be used to study skin aging and response to UVdamage. Isolation of aged cells exposed, in vivo, to youngblood has shown clear molecular changes that may persistfor some period of time (Goodell and Rando, 2015). Agedskin and young skin have well-characterized phenotypicdifferences (thickness, rate of cell proliferation) (Adleret al., 2007; Leung et al., 2013). Parabiosis experimentswill lead to a better understanding of cellular plasticity orthe epigenetic regulation of the cellular state that defines acell as being young or old. This reprogramming is clearly

different than induced pluripotent stem cell reprogram-ming, because these cells do not lose their differentiatedstate. The cells continue to be of the same lineages; theonly change is that their regenerative tendencies becomerejuvenated by the young blood milieu. These experimentswould separate the differences between dedifferentiation

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MULTIPLE CHOICE QUESTIONS1. For best results, mice should be which of the

following for parabiosis?

A. Female

B. Background-matched

C. Of similar size

D. All of the above

2. What protein variable can give a false negativeresult in parabiosis experiments?

A. Size

B. Molecular weight

C. Synthetic rate

D. Clearance rate

3. Parabiotic disease is the most common cause ofdeath for parabiosis pairs 1e2 weeks aftersurgery. What is the incidence in outbredstrains?

A. 20%

B. 40%

C. 60%

D. 100%

4. Parabiosis experiments were instrumental inidentifying the first circulating factor in satiety.What is this factor?

A. Insulin

B. Resistin

C. Leptin

D. Limastatin

5. What is the perioperative mortality in parabiosisexperiments?

A. 10%

B. 20%

C. 30%

D. 40%

E. 50%

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RESEARCH TECHNIQUES MADE SIMPLE

and rejuvenation and allow for a more precise moleculardefinition of skin aging.

3. The application of parabiosis using genetically alteredmouse strains allows for direct testing of signaling path-ways/networks involved in regulating an identified pro-cess. To definitely show that circulating SDF1 from youngblood was responsible for promoting scar formation inaged mice, we performed parabiosis between young skin-deficient SDF1 mice and aged wild-type mice (Figure 2)(Nishiguchi et al., 2018). In this instance, young blooddeficient in SDF1 was not sufficient to promote scar for-mation in aged mice.

As a powerful experimental system to identify molecularand cellular mechanisms, parabiosis has a distinguished

Journal of Investigative Dermatology (2019), Volume 139

history in dissecting fundamental biological processes acrossmultiple fields. The combination of parabiosis with high-throughput genomics and proteomics approaches willcontinue to answer important unanswered questions in skinbiology, particularly related to the epigenetics of skin agingand skin rejuvenation.

CONFLICT OF INTERESETThe authors state no conflict of interest.

ACKNOWLEDGMENTSTHL receives support from the National Institutes of Health (K08-AR066661and P30-AR069589), Veterans Affairs (I01RX002701), the Moseley Founda-tion, and the H.T. Leung Foundation. We thank C. Natale for careful readingof the manuscript.

AUTHOR CONTRIBUTIONSConceptualization and Writing: CAS and THL.

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

REFERENCESAdler AS, Sinha S, Kawahara TLA, Zhang JY, Segal E, Chang HY. Motif module

map reveals enforcement of aging by continual NF-kB activity. GenesDev 2007;21:3244e57.

Bert P. Experiences et considerations sur la greffe animale. J Anatomie Phys-iologie 1864;1:69e87.

Binhammer RT, Epstein S, Whitehouse A. Development of parabiosis intoxi-cation in rat parabionts. Anat Rec 1963;145:503e11.

Brack AS, Conboy MJ, Roy S, Lee M, Kuo CJ, Keller C, et al. Increased Wntsignaling during aging alters muscle stem cell fate and increases fibrosis.Science 2007;317(5839):807e10.

Bunster E, Mayer RK. An improved method of parabiosis. Anat Rec 1933;57:339e43.

Conboy IM, Conboy MJ, Wagers AJ, Girma ER, Weissman IL, Rando TA.Rejuvenation of aged progenitor cells by exposure to a young systemicenvironment. Nature 2005;433(7027):760e4.

Conboy MJ, Conboy IM, Rando TA. Heterochronic parabiosis: historicalperspective and methodological considerations for studies of aging andlongevity. Aging Cell 2013;12:525e30.

Eichwald EJ, Lustgraaf EC, Strainer M. Genetic factors in parabiosis. J NatlCancer Inst 1959;23:1193e213.

Epstein RB, Graham TC, Buckner CD, Bryant J, Thomas ED. Allogeneicmarrow engraftment by cross circulation in lethally irradiated dogs.Blood 1966;28:692e707.

Finerty JC, Panos TC. Parabiosis intoxication. Proc Soc Exp Biol Med 1951;76:833e5.

Gibney BC, Chamoto K, Lee GS, Simpson DC, Miele LF, Tsuda A, et al. Cross-circulation and cell distribution kinetics in parabiotic mice. J Cell Physiol2012;227:821e8.

Goodell MA, Rando TA. Stem cells and healthy aging. Science2015;350(6265):1199e204.

Hall CE, Hall O. Postseparation recovery from parabiosis intoxication in therat. Am J Physiol 1957;189:495e7.

Harris RBS. Contribution made by parabiosis to the understanding of energybalance regulation. Biochim Biophys Acta 2013;1832:1449e55.

Hervey GR. The effects of lesions in the hypothalamus in parabiotic rats.J Physiol 1959;145:336e52.

Kamran P, Sereti K-I, Zhao P, Ali SR, Weissman IL, Ardehali R. Parabiosis inmice: a detailed protocol. J Vis Exp 2013;80:50556.

Laplace JP. Compensatory hypertrophy of the residual small intestine afterpartial enterectomy. A neurohumoral feedback? Ann Rech Vet 1980;11:165e77.

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Leung TH, Zhang LF, Wang J, Ning S, Knox SJ, Kim SK. Topical hypochloriteameliorates NF-kBemediated skin diseases in mice. J Clin Invest2013;123:5361e70.

Nishiguchi MA, Spencer CA, Leung DH, Leung TH. Aging suppresses skin-derived circulating SDF1 to promote full-thickness tissue regeneration.Cell Rep 2018;24:3383e5.

Sauerbruch R, Heyde M. Ueber Parabiose kunstlich vereinigter Warmbliiter.Munch Med Wochenschr 1908;55:153e6.

Stewart JD, Williams JS, Kluge DN, Drapanas T. Effect of cross circulation onmetabolism following hepatectomy. Ann Surg 1963;158:812e9.

Villeda SA, Luo J, Mosher KI, Zou B, Britschgi M, Bieri G, et al. The ageingsystemic milieu negatively regulates neurogenesis and cognitive func-tion. Nature 2011;477(7362):90e4.

Villeda SA, Plambeck KE, Middeldorp J, Castellano JM, Mosher KI, Luo J, et al.Young blood reverses age-related impairments in cognitive function andsynaptic plasticity in mice. Nat Med 2014;20:659e63.

This is a reprint of an article that originally appeared in the June 2019 issue of the Journal of Investigative Dermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Spencer CA, Leung TH. Research Techniques Made Simple: Parabiosis to Elucidate HumoralFactors in Skin Biology. J Invest Dermatol 2019;139(6):1208e1213; doi:10.1016/j.jid.2019.03.1134

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RESEARCH TECHNIQUES MADE SIMPLE

Research Techniques Made Simple: Using GeneticVariants for Randomization

Ashley Budu-Aggrey and Lavinia Paternoster

Observational epidemiological studies have identified associations between a number of modifiable exposuresand outcomes, including in dermatology, such as between smoking and psoriasis. However, it is challenging todetermine if such relationships are causal because of the potential of confounding and reverse causation.Mendelian randomization (MR) is a statistical method that can be used to investigate the causal relationshipsbetween an exposure and outcome by using a genetic instrument that proxies the exposure. The resultingestimate (under certain assumptions) can be interpreted as the causal estimate, free of confounding andreverse causation. In this review, we provide an overview of how to undertake an MR analysis, with examplesfrom the dermatology literature. We also discuss the challenges and future directions of this method.

Journal of Investigative Dermatology (2019) 139, 1416e1421; doi:10.1016/j.jid.2019.03.1138

Medical Res

CorrespondBristol, Brist

Abbreviatio

Journal of I

CME Activity Dates: 20 June 2019Expiration Date: 19 June 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Lavinia Paternosteris a consultant/advisor for Merck. All other authors, planningcommittee members, CME committee members and staffinvolved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodologieson which many diagnostic and therapeutic advances are built.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

earch Council Integrative Epidemiology Unit, Population Health Scie

ence: Lavinia Paternoster, Medical Research Council Integrative Epideol, UK. E-mail: L.Paternoster@bristol.ac.uk

ns: BMI, body mass index; GWAS, genome-wide association study;

nvestigative Dermatology (2019), Volume 139 ª 2019 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Jul19 e click ‘CME on De-mand’ and locate the article to complete the test. Fax or othercopies will not be accepted. To receive credits, learners mustreview the CME accreditation information; view the entirearticle, complete the post-test with a minimum performancelevel of 60%; and complete the online evaluation form inorder to claim CME credit. The CME credit code for this ac-tivity is: 21310. For questions about CME credit email cme@beaumont.edu.

INTRODUCTIONObservational epidemiological studies have uncovered re-lationships between disease and various explanatory factorsknown as exposures (Table 1). Notable examples indermatology include the association of psoriasis withsmoking (Armstrong et al., 2014) and, more recently, theassociation of atopic dermatitis with cardiovascular traits(Standl et al., 2017). However, traditional observationalstudies are prone to biases such as confounding, where theobserved association may be due to the exposure being

m

related to other lifestyle or socioeconomic factors that havea casual influence on disease. Furthermore, the observedassociations may be due to reverse causation, where dis-ease is actually influencing the assumed exposure (Lawloret al., 2008); for example, having psoriasis could influ-ence an individual’s propensity to smoke. Mendelianrandomization (MR) presents a method for evaluating cau-sality in an observational study setting. We aim to providean overview of the principle of MR and the statisticalmethods used.

nces, Bristol Medical School, University of Bristol, Bristol, UK

iology Unit, Population Health Sciences, Bristol Medical School, University of

MR, Mendelian randomization

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTS� Mendelian randomization (MR) is a statisticalmethod for investigating causality betweenexposure and outcome variables in observationalepidemiology.

� Unlike traditional observational studies, MR usesgenetic variants as instruments (or proxies) forthe exposure, hence avoiding confounding andreverse causation.

� Application of such methods in the field ofdermatology is a promising area of research.

� Future directions and developments will allowMR to be a valuable tool for investigating causalpathways for disease, as well as providing insightinto therapeutic interventions.

Figure 1. Illustrative diagram of standard Mendelian randomization (MR)analysis. A valid genetic instrument (Z) must be truly associated with theexposure (X), must not be associated with confounders (C), and should havean effect only on the outcome (Y) via the exposure. Dashed arrows representviolations of these MR assumptions.

Table 1. GlossaryTerm Description

Confounder A variable that is a common cause of both theexposure and the outcome.

Exposure An explanatory variable used to explain or predict anoutcome variable, such as a trait or disease.

F-statistic Obtained from the regression of a response variable ona predictor variable, for example, the regression of theexposure of interest on an instrumental variable (IV).This can be used as a measure of the strength of

association between an IV and the exposure, therebygiving an indication of the strength of the instrument.The further away the F-statistic is from 1, the strongerthe instrument. The F-statistic also depends on the size

of the sample.GWAS Genome-wide association study. Involves analyzing

genetic variants across the genome, such as single-nucleotide polymorphisms for association with a

disease or trait of interest.Instrumentalvariable (IV)

A variable that is associated with an exposure ofinterest but not the outcome. In MR studies, geneticvariants are used as IVs. A valid IV must also be

independent of confounders of the exposure-outcomeassociation and must affect only the outcome via the

exposure.Mendelianrandomization

A method for assessing the causal effect of an exposureon an outcome by using genetic variants as instruments

or proxies for the exposure variable.MR-base A centralized database of summary GWAS data and an

analytical platform to perform Mendelianrandomization and sensitivity analyses.

PheWAS Phenome-wide association study. Involves analyzingthe association between genetic variants and multiplephenotypic variables (on a phenome-wide scale) rather

than a single phenotype.Pleiotropy Occurs when a genetic instrument is independently

associated with multiple risk factors for the outcome, inaddition to the exposure of interest. This results in thethird IV assumption being violated, which assumes thatthe genetic instrument affects only the outcome via the

exposure.Reverse causality Where an association is due to the assumed outcome

variable influencing the exposure variable rather thanthe exposure influencing the outcome.

Sensitivityanalysis

Performed to assess the robustness of the main analysisor the validity of the main results.

RESEARCH TECHNIQUES MADE SIMPLE

THE PRINCIPLE OF MRMR is a form of instrumental variable analysis whereby ge-netic variants are used as instruments (or proxies) for anexposure of interest (Table 1). Because genetic variants arerandomly segregated at conception and cannot be influencedby confounding factors or the outcome itself, they can beused to estimate the causal effect of the exposure upon anoutcome (Lawlor et al., 2008) (Figure 1).

Performing MR requires two pieces of information: (i) theeffect of the genetic instrument on the exposure (bXZ) and (ii)the effect of the genetic instrument on the outcome (bYZ).These can then be used to estimate the causal effect of theexposure on the outcome (causal bYX ) with the following ratio(Wald, 1940): causal bYX ¼ bYZ

bXZ.

For a genetic variant to qualify as an instrumental variable,three core assumptions must be satisfied: the variants (i) mustbe truly associated with the exposure of interest, (ii) must notbe associated with confounders of the exposure-outcomerelationship, and (iii) must affect only the outcome via theexposure and not through an alternative pathway (Zhenget al., 2017). The use of genetic variants in an MR frame-work can be compared with a randomized controlled trial,where genotypes are used to randomize individuals todifferent subgroups (Lawlor et al., 2008). The effect of thegenetic instrument on the outcome (bYZ) is analogous to anintention-to-treat effect from an association betweenrandomization and an outcome in a randomized controlledtrial (Burgess and Thompson, 2015).

Because MR requires estimates of the associations betweengenetic variants and the exposure and genetic variants andthe outcome, the rise of genome-wide association studies(GWASs) (Tsoi et al., 2018) provides a wealthy resource ofgenetic instruments for MR. Published summary GWAS datacan be obtained from various sources such as the GWAScatalogue (www.ebi.ac.uk/gwas/) and MR-base (www.mrbase.org) or directly from the authors of the GWAS(Figure 2). Commonly, independent single-nucleotide poly-morphisms (SNPs) that have been reported to be associatedwith an exposure on a genome-wide significance level(P-value < 5 � 10e8) are used as genetic instruments for the

exposure (Zheng et al., 2017), but MR analyses can be con-ducted by using just a single genetic variant or even using allvariants in the genome (appropriately weighted by their effect

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Figure 2. Workflow for performing two-sample MR analysis. SummaryGWAS data provide a wealthy resource of genetic instruments to perform MR.Various MR methods and sensitivity analyses can be performed withanalytical platforms such as MR-base. Adapted from Hemani et al. (2018).MR, Mendelian randomization; SNP, single-nucleotide polymorphism.

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on the exposure). Published MR studies in dermatologyinclude those investigating causal relationships between fattyacids and melanoma (Liyanage et al., 2018), vitamin D levelsand AD risk (Manousaki et al., 2017) as well as skin aging(Noordam et al., 2017), and, most recently, body mass index(BMI) and psoriasis risk (Budu-Aggrey et al., 2019), which willbe referred to throughout this review.

MR APPROACHES AND STATISTICAL METHODSMR study designsA basic MR study design involves obtaining all information requiredfrom the same set of individuals, meaning that the genetic, exposure,and outcome data are all available from the same study. This isknown as one-sample MR (Table 2). Large population-based studies

Journal of Investigative Dermatology (2019), Volume 139

such as the UK Biobank provide ideal data sets for such analyses tobe carried out. However, it may not always be possible to gatherexposure and outcome measures from the same data set. Two-sam-ple MR is therefore more commonly adopted, whereby the effect ofgenetic variants on the exposure is obtained from one sample, andthe effect of genetic variants on the outcome is obtained fromanother (Table 2). This approach has been greatly facilitated by theincreasing availability of summary GWAS data, as well as analyticalplatforms to perform two-sample MR, such as MR-base. The steps fora two-sample MR are shown in Figure 2 (Hemani et al., 2018).

We recently investigated causality between BMI and psoriasisusing both one-sample MR with individual-level data from the UKBiobank and Nord-Trøndelag Health Study (i.e., HUNT) and two-sample MR with published summary GWAS data. Consistentresults were obtained from both analyses. The combined causal es-timate suggested a 9% increase in the risk of psoriasis per 1 unitincrease in BMI (Budu-Aggrey et al., 2019) (Figure 3). This findingsupports previous reports of weight loss improving the prognosis ofpsoriasis (Maglio et al., 2017) and could suggest weight control as anintervention to prevent or treat psoriasis.

A bidirectional MR approach can also be adopted that investigatescausal effects in both directions (Table 2). This requires suitable ge-netic instruments to be available for both traits. Such analysis canhelp uncover the direction of causality that explains the observa-tional association. For example, when considering the relationshipbetween BMI and psoriasis, we performed bidirectional MR andfound evidence that the observational relationship is largely due tothe causal effect of higher BMI on psoriasis risk rather than a causaleffect of psoriasis influencing BMI (Budu-Aggrey et al., 2019).

MR statistical methodsThe simplest method to perform MR involves dividing the effect ofthe genetic instrument on the outcome by the effect of the geneticinstrument on the exposure. This is commonly termed the ratio ofcoefficients method or the Wald ratio method (as described earlier)and can be performed with either summarized or individual-leveldata (Burgess et al., 2017). Two-stage methods can also beapplied, such as two-stage least squares, as used in the BMI andpsoriasis article by Budu-Aggrey et al. (2019) (Table 2). This methodinvolves regressing the exposure on the genetic instruments and thenregressing the outcome on the genetically predicted values from thefirst regression, which allows for the true standard error to be esti-mated. Additional MR methods have been previously discussedelsewhere (Burgess et al., 2017).

Combining multiple variantsWhere multiple genetic instruments are available for an exposure,these can be combined into a genetic risk score and used as a singleinstrument to perform MR (Zheng et al., 2017). Alternatively, an in-verse-varianceeweighted approach can be applied, whereby theratio estimate from each independent genetic variant is combined byusing a fixed-effect meta-analysis model, where each variant isassumed to provide independent information, and the contribution ofeach variant is the inverse of the variance of its effect on the outcome(Burgess et al., 2013) (Table 2).

Sensitivity methodsOne major potential problem with MR occurs when the genetic in-strument affects the outcome through an alternative pathway that isdistinct from the exposure of interest (termed pleiotropy) (Table 1),which violates the third assumption (as outlined earlier). Various

Table 2. Methods and approaches for MR analysisCategory Description

MR study designOne-sample MR Performed with genetic instruments, exposure

and outcome data that have been measured inthe same sample population.

Two-sample MR The effect of the genetic instruments on theexposure and the effect of the genetic

instruments on the outcome are obtained froma non-overlapping sample populations.

Bidirectional MR The causal relationship between two traits isinvestigated in both directions. This approachcan be applied to one-sample or two-sample

MR.Statistical methodsWald ratio method Performed with a single genetic instrument (or

genetic risk score) by dividing the coefficient ofthe outcome-instrument association by the

coefficient of the exposure-instrumentassociation.

Two-stage least squares(2SLS) regression

Involves two regression stages where theexposure is regressed on the genetic

instruments. The outcome is then regressed onthe genetically predicted exposure values from

the first-stage regression.Combining multiplevariantsInverse-varianceweighted (IVW) estimator

Combination of ratio estimates from individualvariants in a fixed-effect meta-analysis. Thecontribution of each instrument is the inverseof the variance of its effect on the outcome.

Genetic risk score (GRS) Multiple genetic instruments for an exposureare combined into a genetic risk score. Thiscan then be used as a single instrument to

perform MR.Sensitivity analysisMR-Egger regression Sensitivity analysis to perform MR with

multiple instruments. This can be used todetect pleiotropy and provide a causal estimate

that is robust to pleiotropy.Weighted-medianestimator

Sensitivity analysis to perform MR withmultiple instruments. Will provide consistentcausal estimates when at least 50% of the

information in the analysis comes from validgenetic instruments.

Mode-based estimator An MR sensitivity analysis that will provide arobust causal estimate in the presence ofpleiotropy, if the most common pleiotropyvalue is zero across the genetic instruments.

Latent causal variableanalysis

Distinguishes between genetic correlation andcausation by mediating the genetic correlationbetween two traits with a latent causal variablethat itself has a causal effect on each trait.

Abbreviation: Mendelian randomization.

RESEARCH TECHNIQUES MADE SIMPLE

sensitivity methods have been developed to detect and addresspleiotropy, including MR-Egger regression, weighted-median anal-ysis, the mode-based estimate, and the latent causal variable method(Table 2). These methods have different assumptions, but they aim toestimate the true causal effect in the presence of modest levels ofpleiotropy (O’Connor and Price, 2018; Zheng et al., 2017).

Challenges and limitations of MR studiesAlthough MR has proven to be a useful tool for estimating causality,there are instances where MR may be limited or the instrumentalvariable assumptions may be violated. In some cases, there may beonly weak genetic instruments available for the exposure of inter-est. Genetic instruments that explain very little of the variance inexposure can result in weak instrument bias, where the causal es-timates can be biased toward the null in a two-sample MR settingand toward the observational estimate in a one-sample MR setting(Zheng et al., 2017). This highlights the need for GWASs to uncoverassociated variants and strong, reliable instruments to perform MR.The F-statistic from the regression of the exposure on the geneticinstrument indicates the strength of the instrument (Table 1). It isrecommended that genetic variants with an F-statistic greater than10 be used (Burgess et al., 2013; Lawlor et al., 2008). Because theF-statistic is dependent on sample size, weak instrument bias canalso be addressed by using larger sample sizes (Burgess andThompson, 2015). Additionally, combining individual variantsinto a genetic risk score increases the instrument strength. The in-strument for BMI in our psoriasis analysis had an F-statistic of7,091, indicating a strong instrument for BMI (Budu-Aggrey et al.,2019).

Although it is assumed that a genetic instrument is independent ofconfounders, this cannot be tested for all potential confounders.However, it is sensible to test for association between the geneticinstrument and any available measured potential confounders.

Applications and future directions for MRMR is commonly performed to investigate the causality of establishedobservational associations. However, a “hypothesis-free” approachcan also be adopted to uncover novel causal relationships. This in-volves performing MR on a phenome-wide scale, known as MR-pheWAS, where the effect of a single exposure on multiple outcomesis evaluated. This has been shown by Haycock et al. (2017), whofound that telomere length increased the risk of several cancers andreduced the risk of nonneoplastic diseases.

MR can also be applied to investigate the causal role of moleculartraits, such as gene expression, methylation, and protein biomarkers,on disease. In doing so, genetic variants associated with expression(expression quantitative trait loci), methylation (methylation

Figure 3. One-sample and two-sample MR estimates give evidence ofincreased psoriasis risk with 1 unitincrease in BMI (kg/m2). One sampleMR has been performed withindividual- level data. Two-sampleMR has been performed with summaryGWAS data. Adapted from Budu-Aggrey et al. (2019). BMI, body mass;CI, confidence interval; HUNT, Nord-Trøndelag Health Study; GWAS,genome-wide association study; MR,Mendelian randomization.

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MULTIPLE CHOICE QUESTIONS1. Which of the following is a limitation of

observational studies that can be addressed withMR?

A. Publication bias

B. Selection bias

C. Confounding

D. Inadequate sample size

2. Which of the following is NOT an assumptionfor a valid MR instrument?

A. The instrument must be truly associated withthe exposure and the outcome.

B. The instrument must be truly associated withthe exposure.

C. The instrument must not be associated withconfounders of the exposure-outcomerelationship.

D. The instrument must affect only the outcomevia the exposure.

3. Which of the following can be used to uncoverthe direction of a causal relationship?

A. Two-sample MR

B. Observational analysis

C. One-sample MR

D. Bidirectional MR

4. Which of the following can be used to addresspleiotropy in MR?

A. Wald ratio method

B. MR-Egger regression

C. Inverse-variance weighted estimator

D. Two-stage least squares

5. Which of the following statements is FALSE?

A. MR can be performed in a hypothesis-freemanner.

B. MR estimates represent the effect oflong-term exposures.

C. Pleiotropic genetic instruments cannot beincluded in MR analyses.

D. MR can be used to investigate the causal roleof molecular phenotypes.

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quantitative trait loci), or plasma protein levels (protein quantitativetrait loci) are used as genetic instruments for the exposure and canprovide insight into the causal pathways that underlie disease. Thishas been shown for AD, where MR analysis with protein quantitativetrait loci gave evidence that IL1RL2 and IL18R1 are causal proteinsfor AD risk (Sun et al., 2018).

Many MR studies are performed in cohorts with limited ethnicvariation. As shown by Ogawa et al. (2018), transethnic MR studiescan make the causal estimate more robust to confounding by

Journal of Investigative Dermatology (2019), Volume 139

population stratification and more generalizable to broader ethnicbackgrounds (Ogawa et al., 2018).

We also expect that MR methods will begin to be applied tooutcomes of disease progression (as opposed to onset), to enablethem to be more informative for the treatment of patients (Paternosteret al., 2017). Such studies have begun to emerge in other diseaseareas, such as Parkinson disease (Simon et al., 2014), and couldpotentially uncover novel therapeutic targets or drug repurposingopportunities in dermatology.

CONCLUSIONMR has proven to be a robust statistical method to infer causalrelationships in observational studies. In this review, we havepresented strategies for performing MR, as well as the limi-tations and promising extensions of this method. As largeGWAS summary statistics and open-access data sets becomeincreasingly available and additional methods continue to bedeveloped, the potential for MR analysis to produce furtherevidence of causality for dermatological traits will increase.This, in turn, will aid in the understanding of underlyingmechanisms of disease and inform disease prevention andtreatment.

CONFLICT OF INTERESTLP has received personal fees from Merck for Scientific Input Engagementrelated to MR methodology.

ACKNOWLEDGMENTSAB-A is funded by a grant awarded by the British Skin Foundation (8010Innovative Project), awarded to LP. AB-A and LP work in a research unitfunded by the UK Medical Research Council (MC_UU_00011/1).

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

REFERENCESArmstrong AW, Harskamp CT, Dhillon JS, Armstrong EJ, Armstrong AW.

Psoriasis and smoking: a systematic review and meta-analysis fundingsources. Br J Dermatol 2014;170:304e14.

Budu-Aggrey A, Brumpton B, Tyrrell J, Watkins S, Modalsli EH, Celis-Morales C, et al. Evidence of a causal relationship between body massindex and psoriasis: a Mendelian randomization study. PLoS Med2019;16(1):e1002739.

Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysiswith multiple genetic variants using summarized data. Genet Epidemiol2013;37:658e65.

Burgess S, Small DS, Thompson SG. A review of instrumental variable esti-mators for Mendelian randomization. Stat Methods Med Res 2017;26:2333e55.

Burgess S, Thompson SG. Mendelian randomization: methods for using ge-netic variants in causal estimation, https://books.google.co.uk/books?id¼WYSbBgAAQBAJ&printsec¼frontcover&dq¼MendelianþRandomizationþMethodsþforþusingþGeneticþvariantsþinþCasualþEstimationþCRCþPress&hl¼en&sa¼X&ved¼0ahUKEwjbwuT9k5reAhUqBMAKHYvmBlMQ6AEIMjAB#v¼onepage&q&f¼false; 2015 (accessed 22 Oct 2018).

Haycock PC, Burgess S, Nounu A, Zheng J, Okoli GN, Bowden J, et al. As-sociation between telomere length and risk of cancer and non-neoplasticdiseases. JAMA Oncol 2017;3:636.

Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. TheMR-base platform supports systematic causal inference across the humanphenome. eLife 2018;7:e34408.

Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelianrandomization: using genes as instruments for making causal inferencesin epidemiology. Stat Med 2008;27:1133e63.

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Liyanage UE, Law MH, Ong JS, Cust AE, Mann GJ, Ward SV, et al. Poly-unsaturated fatty acids and risk of melanoma: a Mendelian random-isation analysis. Int J Cancer 2018;143:508e14.

Maglio C, Peltonen M, Rudin A, Carlsson LMS. Bariatric surgery and theincidence of psoriasis and psoriatic arthritis in the Swedish obese sub-jects study. Obesity (Silver Spring) 2017;25:2068e73.

Manousaki D, Paternoster L, Standl M, Moffatt MF, Farrall M, Bouzigon E,et al. Vitamin D levels and susceptibility to asthma, elevated immuno-globulin E levels, and atopic dermatitis: a Mendelian randomizationstudy. PLoS Med 2017;14(5):e1002294.

Noordam R, Hamer MA, Pardo LM, van der Nat T, Kiefte-de Jong JC,Kayser M, et al. No causal association between 25-hydroxyvitamin Dand features of skin aging: evidence from a bidirectional Mendelianrandomization study. J Invest Dermatol 2017;137:2291e7.

O’Connor LJ, Price AL. Distinguishing genetic correlation from causationacross 52 diseases and complex traits. Nat Genet 2018;50:1728e34.

Ogawa K, Stuart PE, Tsoi LC, Suzuki K, Nair RP, Mochizuki H, et al. A trans-ethnic Mendelian randomization study identifies causality of obesity onrisk of psoriasis [e-pub ahead print]. J Invest Dermatol 2019;139:1397e400.

Paternoster L, Tilling K, Davey Smith G. Genetic epidemiology and Mendelianrandomization for informing disease therapeutics: conceptual andmethodological challenges. PLoS Genet 2017;13(10):e1006944.

Simon KC, Eberly S, Gao X, Oakes D, Tanner CM, Shoulson I, et al. Mendelianrandomization of serum urate and Parkinson disease progression. AnnNeurol 2014;76:862e8.

Standl M, Tesch F, Baurecht H, Rodríguez E, Müller-Nurasyid M, Gieger C,et al. Association of atopic dermatitis with cardiovascular risk factors anddiseases. J Invest Dermatol 2017;137:1074e81.

Sun BB, Maranville JC, Peters JE, Stacey D, Staley JR, Blackshaw J, et al.Genomic atlas of the human plasma proteome. Nature 2018;558:73e9.

Tsoi LC, Patrick MT, Elder JT. Research techniques made simple: usinggenome-wide association studies to understand complex cutaneousdisorders. J Invest Dermatol 2018;138(3):e23e9.

Wald A. The fitting of straight lines if both variables are subject to error. AnnMath Stat 1940;11:284e300.

Zheng J, Baird D, Borges M-C, Bowden J, Hemani G, Haycock P, et al. Recentdevelopments in mendelian randomization studies. Curr Epidemiol Rep2017;4:330e45.

This is a reprint of an article that originally appeared in the July 2019 issue of the Journal of Investigative Dermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Budu-Aggrey A, Paternoster L. Research Techniques Made Simple: Using Genetic Variants forRandomization. J Invest Dermatol 2019;139(7):1416e1421; doi:10.1016/j.jid.2019.03.1138

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Research Techniques Made Simple:Teledermatology in Clinical Trials

Caroline W. Laggis1, Victoria L. Williams2, Xiaoshi Yang3 and Carrie L. Kovarik4

Telemedicine is well established as a means of providing high-quality healthcare at a distance, particularly topatients in underserved populations. Technologies in teledermatology can be used to complement traditionalmethodologies of clinical trials, expanding accessibility of trials to people typically unable to participate inresearch. Tools of communication technology may enhance many aspects of clinical trials in dermatology, fromrecruitment and retention of participants to collection of real-time data. Clinical trials can be made completelyvirtual or incorporate aspects of virtual technologies at any stage of research. Virtual clinical trials are consideredhighly patient-centered, as the ability of participants to engage with research staff from their own home oftensupplants theneed formanyor all on-site clinic visits. As technological advances influenceevery aspectofmodernlife, clinical trials will also evolve to incorporate these tools, meeting participant expectations and overcomingtraditional challengesof conducting research. Virtual clinical trials comewith specific issuespertaining to analysisof data, technology, and oversight. As more virtual trials are conducted, advantages and limitations of using suchtechnology in research will become clearer and regulatory guidelines will be more firmly established.

Journal of Investigative Dermatology (2019) 139, 1626e1633; doi:10.1016/j.jid.2019.04.004

1DepartmenPennsylvaniProvince, C

CorrespondStreet, Phila

Journal of I

CME Activity Dates: 19 July 2019Expiration Date: 18 July 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Victoria L Williams,MD is a Consultant/Advisor for Patient Discovery. All otherauthors, planning committee members, CME committee mem-bers and staff involved with this activity as content validationreviewers have no financial relationships with commercial in-terests to disclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodolo-gies on which many diagnostic and therapeutic advances arebuilt.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

t of Dermatology, University of Utah, Salt Lake City, Utah, USA; 2Da, Philadelphia, Pennsylvania, USA; 3Department of Social Medicinehina; and 4Department of Dermatology and Medicine, Perelman Sch

ence: Carrie L. Kovarik, MD, Department of Dermatology and Medicdelphia, Pennsylvania 19104. E-mail: carrie.kovarik@pennmedicine.u

nvestigative Dermatology (2019), Volume 139 ª 2019 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Aug19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONTelemedicine has been in existence for decades as a way toprovide healthcare at a distance using communication tech-nologies, and dermatology is well-suited for the delivery ofdiagnoses using visually based video and photography. Usingteledermatology, clinical services can be provided to under-served populations in a reliable and cost-effective manner

when compared to more traditional face-to-face modalities(Yang et al., 2018). Systematic reviews (Mounessa et al.,2018; Warshaw et al., 2011) and numerous studies(Armstrong et al., 2018; Balakrishnan et al., 2018) haveshown acceptable concordance rates between diagnosesrendered through teledermatology and traditional face-to-face

epartment of Dermatology, Perelman School of Medicine, University of, School of Public Health, China Medical University, Shenyang, Liaoningool of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

ine, Perelman School of Medicine, University of Pennsylvania, 3600 Sprucepenn.edu

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTS� Technological advances in telemedicine, mobiledevices, and cloud computing have providednumerous tools that can be used to enhancetraditional methodologies of clinical researchand have paved the way for conducting clinicaltrials virtually.

� Virtual clinical trials offer many advantages overtraditionalmodalities for certain research scenarios,including diversifying research populations,reaching underserved areas, improving recruitmentand retention of participants, gathering patient-driven data, and potentially improving efficiencywhile decreasing cost.

� When using aspects of virtual clinical trials, it isimportant to recognize current limitations, suchas the lack of regulatory guidelines and the needfor standardization of data collection methods,for example, photographs taken by participantsfor dermatology-based research.

RESEARCH TECHNIQUES MADE SIMPLE

consultations as well as comparable management concor-dance and patient satisfaction. Although not as well estab-lished as the healthcare-based clinical applications,teledermatology is emerging as a useful methodology forconducting clinical trials.In dermatology, clinical trials are typically conducted in

a medical facility and require regular visits by the researchparticipant. Now, with the use of technology, all or part ofa clinical trial can be conducted virtually. The generalconcept of a virtual clinical trial is that most, if not all, stepstake place in participants’ homes with the assistance of acoordination center (Hirsch et al., 2017). A single, or a few,facilities are appointed to manage administrative informa-tion, real-time data, and safety concerns provided virtuallyby participants and research staff. Some study designscombine more traditional clinical trial methodologies withnew technologies to create a hybrid or augmented siteapproach. In this paper, we aim to provide an overview ofappropriate uses for teledermatology in clinical trials anddiscuss potential ways that technology can be leveraged asa tool to accelerate scientific discovery, decrease partici-pant burden, and augment traditional clinical research.Advantages, as well as unique issues and limitations withthe use of teledermatology in clinical trials, are alsooutlined.

BRIEF OVERVIEW OF VIRTUAL CLINICAL TRIALSVirtual technologies have historically been utilized to com-plement conventional methodologies of drug development.Pfizer was the first to conduct a fully virtual clinical trial in2011, establishing a framework for workflow and pitfalls.Other notable trials, including those in dermatology, arehighlighted in Table 1. The PEMPHIX trial (Hoffman-La, 2018)was the first to recruit and monitor patients virtually in a

randomized control trial to compare oral with infused medi-cations. This trial investigated the safety and efficacy of rit-uximab versus mycophenolate mofetil in the treatment ofpemphigus vulgaris, a rare autoimmune blistering disease.Approximately 10% of the participants enrolled virtually.Communications and data input were done almost entirelythrough mobile applications and telemedicine visits. Thisstudy noted an enrollment speed for participants using virtualmethods approximately 20 times faster on average than moreconventional enrollment techniques at a traditional site(Neuer, 2016), which is significant given the relative rarity ofthe disease under investigation. Table 1 also lists severalongoing and recently completed telemedicine-based virtualtrials.

WHAT IS THE ROLE OF TELEDERMATOLOGY IN CLINICALTRIALS?Teledermatology and different modes of communicationtechnology can be used to enhance clinical trials. Cliniciansshould be aware of the range of tools that can simplify orstreamline portions of clinical research, most notably therecruitment of participants, collecting feedback and data fromparticipants and staff, and retention of participants. Thesetools can be integrated into parts of a trial without the trialbecoming entirely virtual. Figure 1 illustrates the patient’sjourney through a clinic trial and where aspects of tele-dermatology can be incorporated along the way.

Recruitment and screening of participantsThe recruitment of participants into clinical trials is frequentlya major obstacle to the success of a study. With conventionalmethods, reports show that 10% of studies fail to enroll asingle patient, and 25% under-enroll (Lamberti and Getz,2015). The Clinical Trials Transformation Initiative outlinedthe actionable recommendations needed to improve patientrecruitment (Huang et al., 2018), many of which could beaddressed with the use of telemedicine as part of the meth-odology. Social media outlets are a prime example of widelyaccessible avenues for advertisement regarding new clinicaltrials and engagement among participants. One studycurrently underway (Studer, 2016) focuses on the use of awireless blood glucose meter in a completely virtual clinicaltrial setting in which all participants were recruited throughFacebook and then self-registered with an application at aseparate site. A research coordinator then screened the studymaterials, and the required materials and equipment weremailed to the selected participants. Additionally, with globaluse of social media, there is a greater potential to involvemore diverse and underrepresented patient populations whencompared to traditional methods of recruitment.

Collecting participant feedback and real-world trial dataCompleted virtual clinical trials have shown that quality datacan be reliably provided directly to coordinators using a webportal or an application downloaded on a smartphone(Table 1). This technology can be utilized to allow patients toenter data on their own time. Customized online surveysprovide an easy mechanism to collect data on patients’ ex-periences, perspectives, and self-reported disease metrics(Maymone et al., 2018). These surveys can be rapidlydeveloped and administered, as well as collected and

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Table 1. Overview of Previous and Ongoing Virtual Clinical TrialsDisease/Study (Dates ofStudy) Purpose Telemedicine Use in Trial Outcome

Overactive bladder,REMOTE trial (2011e12)

New drug study1 Telemedicine was used via a patient-facing web portal in order to manage

participants from their homes.

Trial ended early, primarily because ofcomplicated online processes

at key stepsParkinson’s disease(2011e12)

Evaluate the feasibility of providingspecialty care to individuals with

Parkinsonism via web-basedtelemedicine in their homes2

Video conferencing with participants Remote clinical assessments wereconducted nationally and rapidly from a

single site, confirming self-reporteddiagnosis

Alzheimer’s disease(2014e15)

Monitor real-world function in homeenvironments of participants3

Data gathered from strategically placedsensors were used to assess global

cognitive and motor impairment in realtime.

Patterns of intra-individual variationdetected in each of these areas were usedto predict outcomes, such as low mood,

loneliness, and cognitive functionAcne,AOBiome Study (2017)

Determine the efficacy of a newtopical ammonia oxidizing bacteria

for treatment4

Trial was conducted entirely usingvirtual technologies and utilized

photographs patients took of themselves,which were uploaded to an app on

iPhones provided by the trial.

The Phase 2b of the study achieved theprimary endpoint at week 12 of a

statistically significant 2-point reductionin an Investigator’s Global Assessmentof acne severity compared to vehicle

control (P ¼ 0.03)Pemphigus vulgaris,PEMPHIX trial(2014eongoing)

Compare efficacy of rituximab tomycophenolate mofetil in the treatment

of pemphigus vulgaris5

Communications with research teamtook place almost entirely in patients’homes using a smartphone app, mobilenurses, and study coordinators. This

study was a hybrid, with infrequent visitsto the clinic over years.

Study is active, but no longer recruiting

Severe acne (2016e18) New drug study of a subcutaneous drug(ClinicalTrials.gov: NCT02998671)

Virtual enrollment, self-photography, andnurse-assisted photography at home, and

home lab draws

Phase 2a placebo controlled RCTenrollment completed

Cluster headache(2016e18)

New drug study of subcutaneous drug(ClinicalTrials.gov NCT02619617)

Virtual enrollment and monitoring,home-based injections, and lab draws

at home

Phase 2a placebo controlled RCT,enrollment completed; 80% of

patients enrolled virtuallyNonalcoholic fatty liverdisease (2016eongoing)

New drug study of oral drug(ClinicalTrials.gov NCT02913105)

Virtual enrollment and monitoring,home-based assessments, and

intermittent imaging at study site

Phase 2a placebo controlled RCT,enrollment completed

Type II diabetes(2018e19)

Study of recently-approved diabetes drugin underrepresented minority populations

(ClinicalTrials.gov NCT03434119)

Virtual enrollment and monitoring,home-based assessments, andhome-based or local labs

Phase 4 study of marketed drug innew population, recently closed

All trials listed, except REMOTE and Alzheimer’s studies, reported using a patient portal with capacity to perform both store-and-forward, as well as videotelemedicine.Abbreviation: RCT, randomized control trial.1Hirsch et al., 2017; Jadhav, 2016; Orri et al., 20142Dorsey et al., 2015a; Dorsey et al., 2015b3Lyons et al., 20154Jackson, 2017; Singer et al., 20185Hoffman-La, 2018

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RESEARCH TECHNIQUES MADE SIMPLE

analyzed, with a lower cost and fewer errors than traditionaltelephone or mail questionnaires.Trial data can also be collected virtually using wearable

sensors to track compliance with the trial’s design and allowdaily “e-journal” entries. Photographs and videos, whethertaken by the participant or trial staff, can be used to monitordisease severity, response to treatment, or potential adverseevents and side effects of trial interventions.

Retention of participantsTraditional clinical trials have a high drop-out rate, with only50% average participant retention (Lamberti and Getz, 2015).Poor retention causes significant delays and costs, as well asimplications to scientific, financial, ethical, and policy de-velopments (Hirsch et al., 2017). With more convenient andpatient-centered models for data collection and monitoring,virtual clinical trials aim to decrease patient burden, enhance

Journal of Investigative Dermatology (2019), Volume 139

compliance with protocols, and improve retention ofparticipants.

WHAT TECHNOLOGIES ARE AVAILABLE WITHIN THE REALMOF TELEDERMATOLOGY?Table 2 provides examples of the “virtual toolbox” availableto investigators. The most applicable to dermatology clinicaltrials are social media outlets for recruitment, online surveytools for data collection, synchronous and asynchronousstudy visits using photography or video conferencing, andpatient portals for communication with study coordinatorsand providers.Investigators in other fields have pioneered real-time

sensors, such as blood glucose monitors for patients withdiabetes and motion-detector sensors for patients withneurologic conditions. A dermatology trial recently utilizedwrist-worn actigraphy sensors to measure nocturnalscratching in patients with atopic dermatitis (Moreau et al.,

Figure 1. The patient journey in avirtual clinical trial. The patientjourney through a clinical trial, withgreen dialogue boxes indicating pointsin which tools of telemedicine may beused to improve participantexperience, streamline protocol, andprovide a more patient-centeredapproach. SAF, store-and-forward.

RESEARCH TECHNIQUES MADE SIMPLE

2018). Wearable sensors allow objective outcome mea-sures to be more easily and accurately monitored in thehome than a monthly diary of events or reliance on patientreporting.Certified Clinical Trial Research Pharmacists are specially

trained, licensed pharmacists who operate through site-lessclinical research organizations to virtually access partici-pant data and interact with participants as needed in theirhomes (Hirsch et al., 2017). Incorporation of CertifiedClinical Trial Research Pharmacists has the potential toimprove the safety and satisfaction of clinical trial partici-pants in drug studies.

WHAT ARE THE ADVANTAGES OF USINGTELEDERMATOLOGY IN CLINICAL TRIALS?The primary advantages of using clinically-based telemedi-cine for healthcare delivery are the decrease of the burden ofpatients in need of medical care and the improvement ofhealthcare access for underserved populations, a concept thatalso applies readily to virtual clinical research. Opening upclinical trials to patients in geographically remote areas ordisparate living conditions provides an opportunity to studydiverse and previously uninvolved sectors of the populationand may lead to study populations that are more represen-tative of the actual population with the disease. Somedermatological diseases are more prevalent in elderly or low-income populations. However, because of significantcomorbidities or social issues, these groups may have diffi-culty committing to frequent on-site appointments requiredby traditional trial models and may benefit from technologicalmethodologies. Rare diseases in dermatology require wider

recruitment areas and multiple facilities, which can be madepossible with virtual clinical trials.In developing countries, the burden of skin disease is high

but often inadequately studied because of the lack ofhealthcare infrastructure and limited research funding. Mo-bile data collection tools have been used with success inthese settings for health surveillance research, epidemiologicdata collection, and studies to monitor disease severity andtreatment response (Baloyi et al., 2018; Devi et al., 2015;Forsell et al., 2011; Ha et al., 2016; Laytin et al., 2018;Quercia et al., 2018). Communication technology can pro-vide an opportunity for these underserved patient pop-ulations to benefit from access to new and potentially moreefficacious diagnostic and therapeutic interventions in clin-ical trials.Overall, virtual trials are considered more patient-

centered by “engaging patients directly in research func-tions, overcoming geographic obstacles to connect stake-holders, and incorporating patient input into the researchprocess” (Covington and Veley, 2015). The advantages alsoextend to the study coordinator role, as one study reported66% less time spent on study coordination activities whencompared to traditional methods (Studer, 2016). Easingrecruitment and retention of participants enhances the effi-ciency of conducting clinical trials. New drug trials average12 years in investment time and billions of dollars to com-plete (Sertkaya et al., 2014). Transitioning to virtual meth-odologies may significantly decrease cost and acceleratecompletion of trials by centralizing collection of data anddecreasing the number of sites to maintain. Figure 2 illus-trates the advantages and disadvantages of using tele-dermatology in clinical trials.

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Table 2. Toolbox for Incorporating Aspects of Telemedicine into Clinical TrialsAspect of Clinical Trials Telemedicine Tools

Recruitment and screening ofparticipants

- Social media outlets provide highly visible avenues for recruitment of participants- Online questionnaires and web-based portals for streamlined registration and simplified screening ofparticipants into trials

- Partnerships and engagement with patient advocacy groups or patient communitiesGaining informed consent - Participants can read over study information on their own time, interact with investigators and

staff virtually, save documents, and sign informed consents onlineParticipant education - Numerous modalities for patient education can be streamlined on web-based portals, including

tutorial videos, informed consent videos, and documents on key points of trial informationParticipant feedback and datacollection

- Web-based portals allow for participant feedback during their own time, including perspectives, experiences,and questions related to the ongoing trial through online communication systems and message boards

- Data collection through web-based or app-based portals via online surveys, participant “e-journals,” digitaldata points from wearable sensors, and weights of medications to ensure proper usage

- Photographs and video conferencing (taken by participants and/or trial staff) can be used to monitor diseaseseverity, response to intervention, and adverse side effects

Adherence and data quality - Text messages or other push reminders about upcoming visits or for medication adherencecan be sent within study apps or directly to participants’ mobile devices

Retention of participants - Improved compliance and understanding of trial protocols by shifting the convenience towards the participant- Flexible data entry times based on participants schedule and in their own home- Decrease or elimination of on-site visits

Monitoring for adverse eventsand safety

- High accessibility to coordinators via web-based portals for discussion of adverse events at any intervalrather than waiting for on-site visit appointments

- Safety monitoring via patient or staff entered outcomes on a regular basis- Incorporation of Clinical Trial Research Pharmacists for drug related questions and monitoring

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WHAT UNIQUE ISSUES ARE INVOLVED WITH THE USE OFTELEDERMATOLOGY IN CLINICAL TRIALS?Sampling issuesIn general, patient participation in medical trials has not re-flected the shifting demographics of the population of theUnited States, especially among minority ethnic populations(Charrow et al., 2017). In comparison, participant populationsthat are self-recruited via social media often more appropri-ately reflect population demographics. However, this popu-lation may not represent a true random selection and may beviewed as a “convenience sample.” Self-selected participantsmay also represent a biased population, as they may be more

Figure 2. Advantages anddisadvantages of virtual clinical trials.Major advantages and disadvantagesof using technology in clinical trialsor conducting an entirely virtualclinical trial.

Journal of Investigative Dermatology (2019), Volume 139

prone to use the Internet or computers. Recruitment tech-niques are ideally designed to enroll the most representativeselection of the population that will ultimately receive thedrug, thus they should be multipronged in their approach(Covington and Veley, 2015).

Technology and coordination issuesGiven the heavy reliance of virtual clinical trials on smart-phones and videoconferencing, technological access andfunctionality become key concerns. A high-speed signal andaccess to a smartphone or computer is essential for partici-pants. In 2017, approximately 64% of people around the

MULTIPLE CHOICE QUESTIONS1. Which statement is true regarding previous and

ongoing virtual clinical trials?

A. There has never been a successful virtualclinical trial in the field of dermatology

B. The first virtual clinical trial had no issueswith implementation of online registrationfor their participants

C. Use of technology has improved recruitmentand retention in a clinical trial concerningpemphigus vulgaris

D. Dermatology has pioneered the use ofwearable sensors for data collection in virtualclinical trials

2. Which study might be inappropriate to considerconducting completely virtually?

A. Comparing use of two systemic medicationsfor a rare autoimmune disease acrossseveral states

B. Multistage study with various subpopulationsrequiring frequent coordination of socialwork, pharmacy, physical therapy, oncology,and dermatology

C. An interventional clinical trial with a newtopical drug for rosacea requiring weeklyevaluation of clinical progression of diseaseand patient-reported experiences using themedication

D. A trial designed to study the effect of an oralmedication for acne on liver enzymes on amonthly basis

3. Which of the following is false regarding the useof social media in recruitment of participants forclinical trials?

A. Study population can be viewed as a randomsample of the general population

B. Social media represents a tool to recruitparticipants over a wider and more diversepopulation than traditional methods

C. Facebook has been used in previous trials forthe recruitment of participants to clinicaltrials

D. A study that recruits participants with socialmedia alone may exclude some populations

4. Which of the following is not an advantage ofincorporating technology into a clinical trial?

A. Patient-centered data collection allowsparticipants to enter data on their own timerather than attend frequent on-site clinic visits

B. Potential for increased communicationbetween study coordinators and researchparticipants

C. Streamlined online informed consent andstudy registration

D. No need for training to ensure quality ofphotos taken by participants for datacollection purposes

5. Which of the following is an important limitationregarding the use of technology in clinical trials?

A. Storage of online data must comply withrigorous privacy standards

B. The current guidelines for conducting virtualclinical trials are too restrictive

C. The general population is uncomfortablewith communication technologies like socialmedia and applications on their phones

D. Most potential participants do not haveaccess to reliable Internet

Note: See online version of this article for a detailed explanation ofcorrect answers.

RESEARCH TECHNIQUES MADE SIMPLE

world had access to the Internet, and 72% owned a smart-phone, and these numbers are substantially higher in theUnited States (Poushter et al., 2018). Conducting trials usingsmartphones provided by the researchers is one way toexpand eligible populations. However, this may excludecertain sectors, such as elderly patients who have limitedexperience using similar technology or populations indeveloping countries where unreliable connectivity may posea problem.Coordinating multiple parties involved in clinical trials onto

a single virtual conference call can be more difficult thansimply requiring all parties to be present at the time of aparticipant visit. Thus, studies that require multiple disciplinesand significant coordination of trial resources may not workwell with completely virtual methodology. Other potentialcomplications of virtually conducted trials include difficultyin administering trial medications via mail, coordinatinginfused medications, and ensuring participants are compliantwith obtaining necessary lab testing outside of an office visitsetting.When participants are required to use video conferencing

or store-and-forward photographs for data collection, theremust be clear instructions and quality cameras provided toassure standardized, high-quality images. This is particularlyessential in dermatological clinical trials where photographsor video monitoring may be a primary tool for assessment ofdisease progression and success of interventions. A recentlypublished article about acne (Singer et al., 2018) demon-strates the reliability of assessing standard clinical outcomesfrom smartphone-based digital photographs compared to inperson visits. Because smartphone cameras and the use ofthem are nearly ubiquitous in the population, reliable andmethodical training is the primary limitation to widespreadclinical trial usage of these photographic modalities fromhome.

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RESEARCH TECHNIQUES MADE SIMPLE

Regulatory and legal issuesThere is not yet a standardized set of guidelines that clinicalinvestigators can follow regarding the implementation ofvirtual technology into studies. Currently, virtual trials arebeing conducted on a case-by-case basis and regulatoryguidelines vary by region and country. Lack of standardguidelines and regulatory uncertainty may be a reason moregroups are not conducting virtual trials.Other legal considerations include ensuring appropriate

licensure is held or acquired among health practitioners in allstates where participants in the study reside. Finally, a majorbenefit of virtual trials is that a single site can recruit patientsfrom multiple states.

CONCLUSIONDevelopment of and access to technology within healthcare has progressed at a faster rate than the methodologiesused to conduct clinical trials. Participants appreciate theconvenience offered by clinical trials that provide accessto online registration, monitoring, and virtual data collec-tion. Direct access to study coordinators is often expectedby clinical research participants, and virtual platformsmake this access more feasible. Integrating virtual toolsinto clinical trials is critical to advancing research meth-odologies. Standardized regulatory guidelines wouldenhance the industry’s ability to conduct these trials withconfidence.

ORCIDsCaroline W. Laggis: https://orcid.org/0000-0003-3819-9345Victoria L. Williams: https://orcid.org/0000-0002-3842-2693Xiaoshi Yang: https://orcid.org/0000-0003-1426-128XCarrie L. Kovarik: https://orcid.org/0000-0002-3258-3605

CONFLICT OF INTERESTVW serves as a consultant for Patient Discovery Inc, which has created a web-based educational program for patients on biologic medications and thatcould be utilized for clinical research. The other authors state no conflict ofinterest.

ACKNOWLEDGMENTSWe thank Vera David and Jonathan Cotliar at Science 37 for their expert input.

AUTHOR CONTRIBUTIONSConceptualization: CWL, CLK; Data Curation: CWL, VLW, XY, CLK; FormalAnalysis: CWL, XY, CLK; Investigation: CWL, VLW, CLK; Methodology: CWL,CLK; Project Administration: CWL, CLK; Supervision: CLK; Writing e OriginalDraft Preparation: CWL; Writing e Review and Editing: CWL, VLW, XY, CLK

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teaching slides are availableas supplementary material.

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Charrow A, Xia FD, Joyce C, Mostaghimi A. Diversity in dermatology clinicaltrials: A systematic review. JAMA Dermatol 2017;153:193e8.

Covington D, Veley K. The Remote Patient-Centered Approach in ClinicalResearch. Appl Clin Trials 2015;24.

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Dorsey ER, Darwin KC, Mohammed S, Donohue S, Tethal A, Achey MA, et al.Virtual research visits and direct-to-consumer genetic testing in Parkin-son’s disease. Digit Health 2015a;1:2055207615592998.

Dorsey ER, Wagner JD, Bull MT, Rizzieri A, Grischkan J, Achey MA, et al.Feasibility of virtual research visits in fox trial finder. J Parkinsons Dis2015b;5:505e15.

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This is a reprint of an article that originally appeared in theAugust 2019 issue of the Journal of InvestigativeDermatology. It retains its original pagination here. Forcitation purposes, please use these original publication details: Laggis CW, Williams VL, Yang X, Kovarik CL. Research Techniques Made Simple: Telederma-tology in Clinical Trials. J Invest Dermatol 2019;139(8):1626e1633; doi:10.1016/j.jid.2019.04.004

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Research Techniques Made Simple: Forward GeneticScreening to Uncover Genes Involved in Skin Biology

William McAlpine1, Jamie Russell1, Anne R. Murray1, Bruce Beutler1 and Emre Turer1,2

The primary goals of modern genetics are to identify disease-causing mutations and to define the functions ofgenes in biological processes. Two complementary approaches, reverse and forward genetics, can be used toachieve this goal. Reverse genetics is a gene-driven approach that comprises specific gene targeting followedby phenotypic assessment. Conversely, forward genetics is a phenotype-driven approach that involves thephenotypic screening of organisms with randomly induced mutations followed by subsequent identification ofthe causative mutations (i.e., those responsible for phenotype). In this article, we focus on how forward ge-netics in mice can be used to explore dermatologic disease. We outline mouse mutagenesis with the chemicalN-ethyl-N-nitrosourea and the strategy used to instantaneously identify mutations that are causative of specificphenotypes. Furthermore, we summarize the types of phenotypic screens that can be performed to explorevarious aspects of dermatologic disease.

Journal of Investigative Dermatology (2019) 139, 1848e1853; doi:10.1016/j.jid.2019.04.013

1Center for tof Gastroen

CorrespondTexas, 7539Medical Cen

Abbreviatio

Journal of I

CME Activity Dates: 21 August 2019Expiration Date: 20 August 2020Estimated Time to Complete: 1 hour

Planning Committee/Speaker Disclosure: Bruce Beutler, MDreceives research support from Pfizer, Inc. All other authors,planning committee members, CME committee members andstaff involved with this activity as content validation reviewershave no financial relationships with commercial interests todisclose relative to the content of this CME activity.

Commercial Support Acknowledgment: This CME activity issupported by an educational grant from Lilly USA, LLC.

Description: This article, designed for dermatologists, resi-dents, fellows, and related healthcare providers, seeks toreduce the growing divide between dermatology clinicalpractice and the basic science/current research methodologieson which many diagnostic and therapeutic advances are built.

Objectives: At the conclusion of this activity, learners shouldbe better able to:� Recognize the newest techniques in biomedical research.� Describe how these techniques can be utilized and theirlimitations.

� Describe the potential impact of these techniques.

he Genetics of Host Defense, University of Texas Southwestern Medicterology, University of Texas Southwestern Medical Center, Dallas, T

ence: Bruce Beutler, Center for the Genetics of Host Defense, Univers0-8505, USA. E-mail: Bruce.Beutler@UTSouthwestern.edu or Emre Tuter, 5323 Harry Hines Boulevard, Dallas, Texas, 75390-8505, USA.

ns: CRISPR, clustered regularly interspaced short palindromic repeat

nvestigative Dermatology (2019), Volume 139 ª 2019 The A

CME Accreditation and Credit Designation: This activity hasbeen planned and implemented in accordance with theaccreditation requirements and policies of the AccreditationCouncil for Continuing Medical Education through the jointprovidership of Beaumont Health and the Society for Inves-tigative Dermatology. Beaumont Health is accredited bythe ACCME to provide continuing medical educationfor physicians. Beaumont Health designates this enduringmaterial for a maximum of 1.0 AMA PRA Category 1 Cred-it(s)�. Physicians should claim only the credit commensuratewith the extent of their participation in the activity.

Method of Physician Participation in Learning Process: Thecontent can be read from the Journal of InvestigativeDermatology website: http://www.jidonline.org/current. Testsfor CME credits may only be submitted online at https://beaumont.cloud-cme.com/RTMS-Sept19 e click ‘CME onDemand’ and locate the article to complete the test. Fax orother copies will not be accepted. To receive credits, learnersmust review the CME accreditation information; view theentire article, complete the post-test with a minimum perfor-mance level of 60%; and complete the online evaluation formin order to claim CME credit. The CME credit code for thisactivity is: 21310. For questions about CME credit emailcme@beaumont.edu.

INTRODUCTIONGenetic studies in mice are critical to the mechanistic un-derstanding of human disease. In classical genetics, twocommon approaches are implemented to elucidate genefunction: reverse and forward genetics. Reverse genetics is agene-to-phenotype approach in which a specific gene is

i

targeted, and the phenotypic effects of this disruption areexamined. In contrast, forward genetics is a phenotype-to-gene approach that begins with a mutant phenotype of in-terest and proceeds to the identification of the disrupted gene.Both methods have been used to elucidate genes required forprotection against dermatologic disease (DeStefano and

al Center, Dallas, Texas, USA; and 2Department of Internal Medicine, Divisionexas, USA

ty of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas,rer, Center for the Genetics of Host Defense, University of Texas SouthwesternEmail: Emre.Turer@UTSouthwestern.edu

s; ENU, N-ethyl-N-nitrosourea

uthors. Published by Elsevier, Inc. on behalf of the Society for Investigative Dermatology.

SUMMARY POINTSAdvantages� Forward genetics is unbiased and can lead tounexpected breakthroughs.

� With increased genomic damage saturation,multiple mutations affect the same pathway. Thecomplete set of genes involved in a biologicpathway can thus be deduced by forwardgenetics provided that enough mice areassessed.

� Hypomorphic mutations introduced by ENU canbe viable, whereas early lethality may be causedby a complete loss of function.

� New drug targets can be ascertained frommutations that modify disease.

Limitations� Forward genetics in mice is resource intensiveand can be both expensive and laborious.

� The mechanism by which mutations in somegenes give rise to a phenotype can be difficult tosolve. p

rint&web4C=FPO

Figure 1. Breeding scheme for the generation of G3 mice. G0 mice are bredto C57BL/6J females. G1 males are crossed to C57BL/6J females to produceG2 mice. The G3 generation results from backcrossing of G2 females to theG1 founder mouse. Asterisks represent mutations derived from the G0 male.ENU, N-ethyl-N-nitrosourea.

RESEARCH TECHNIQUES MADE SIMPLE

Christiano, 2014). Reverse genetics generally involves priorknowledge or speculation as to how a gene may function,which can limit the finding of novel and unexpected path-ways leading to a disease phenotype. Forward genetics makesno such assumptions. Because forward genetics does not startwith any preconceived ideas as to how phenotypes arise, itcan lead to the discovery of new molecules or pathwaysinvolved in a biological process that were previously unde-tected by researchers. Moreover, if enough mutations arescreened for a specific phenotype, the full set of genes withnonredundant function in a biological process can bedefined.

ENU MUTAGENESIS AND BREEDING STRATEGYThe mutagen used for forward genetics in mice is N-ethyl-N-nitrosourea (ENU). While other mutation systems exist (e.g.,radiation induced and transposons), ENU mutagenesis ispreferred because of the high mutation rate and the ability togenerate deleterious missense alleles. ENU generates thehighest mutational load in the germline of any known agent,introducing approximately 3,000 mutations into each malegamete after three intraperitoneal injections of 100 mg/kgbody weight, administered at weekly intervals (Arnold et al.,2012). ENU is a DNA alkylating agent that modifies nucleo-tide residues by the transfer of an ethyl group. ENU causespoint mutations that result in A-T to T-A transversions or A-Tto G-C transitions; G-C to C-G transversions are rarelyobserved (Arnold et al., 2012). At the protein level, 70% ofENU mutations result in nonsynonymous changes, with 65%of these being missense and the remainder resulting fromnonsense or splice mutations (Arnold et al., 2012).

Point mutations leading to missense alleles are ideal forseveral reasons. First, monogenic diseases, including thoseinvolving skin, are most commonly caused by coding regionpoint mutations rather than by mutations in intronic or regu-latory regions (DeStefano and Christiano, 2014; Oliver andDavies, 2012). Moreover, in addition to null alleles, ENU-induced nucleotide substitutions can generate hypomorphs,hypermorphs, and neomorphs that more closely resembledisease-causing alleles in humans (Oliver and Davies, 2012).The terms hypomorphic and hypermorphic describe muta-tions that result in a partial loss or gain of function, respec-tively, whereas neomorphic describes a mutation that confersa new function. Hypomorphic mutations can be compatiblewith viability even if they occur in essential genes, whichcomprise an estimated one-third of the genome. Indeed,viable hypomorphic mutations in essential genes are morelikely to cause phenotypes as compared with hypomorphicmutations in nonessential genes (Wang et al., 2018).ENU mutagenesis is usually carried out on a highly inbred

genetic background such as C57BL/6J, in which there is ho-mozygosity at almost all loci, and mutations induced by ENUare readily detected in the heterozygous state by high-throughput DNA sequencing (e.g., with an Illuminasequencing platform). Because ENU-induced phenotypes aretypically ascribable to changes in coding sense, it is sufficientto cover the coding region (whole-exome sequencing) todetect the great majority of causative mutations. ENU-induced genetic variation is rather limited within a singlepedigree (compared with human genetic variation within alarge population of unrelated individuals); therefore, when

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RESEARCH TECHNIQUES MADE SIMPLE

a phenotype is detected, it will most likely be ascribable to asingle nucleotide change.Assessment of mutations in the homozygous state is

preferred over the heterozygous state because for manygenes, mutations causing dominant phenotypes either do notoccur or occur very rarely. The generation of mice with ho-mozygous ENU mutations is achieved by the followingbreeding scheme (Figure 1). ENU-mutated male mice (G0) arebred to a wild-type female mouse, and mutations are trans-mitted in the heterozygous state to the G1 generation. G1males are bred to wild-type females, and the mutations areagain transmitted in the heterozygous state to the G2 gener-ation. G2 daughters are backcrossed to the G1 males,yielding G3 mice with mutations in the heterozygous and thehomozygous states, which allows for the detection of phe-notypes that are caused by both dominant and recessivemodels of inheritance. On average, a phenotypically neutralmutation will be transmitted to homozygosity in 12.5% of theG3 mice, but if a mutation impairs survival in the homozy-gous state, or is linked to another mutation that does so, fewerhomozygotes may be observed. This breeding scheme doesnot mutagenize the X chromosome because only G1 males,bearing mutagenized Y chromosomes, are used to producepedigrees. Alternative breeding schemes that involve thebreeding of G0 males with G1 females carrying germlinemutations derived from other mutagenized males can be usedto screen for X-linked phenotypes. Moreover, mutations onthe Y chromosome rarely yield phenotypes because of thehighly repetitive Y chromosome sequence.The size of pedigrees produced for forward genetic studies

strikes a balance. On the one hand, there is a desire to detecteven those mutations that do compromise survival, in addi-tion to the desire to dissociate linked mutations by meioticrecombination and thereby resolve which mutation is caus-ative of a particular phenotype. On the other hand, increasingthe number of G3 mice analyzed increases the cost of theprocess per mutation screened. Typically, an average numberof 50e60 G3 mice are produced per pedigree, and pedigreeswith fewer than 20 G3 mice are not screened.

REAL-TIME MAPPING OF A QUALITATIVE TRAITIn the past, identification of the causative mutation for aphenotype involved positional cloning, a process that oftenrequired several years of breeding, outcrossing, and

aFigure 2. Mapping of a hair lossphenotype to a Dsg4 mutation. (a)Representative image of hair lossexhibited by four mice in a pedigree.(b) Manhattan plot showing theP-value of association between thephenotype and the mutationsidentified in the pedigree, calculatedusing a recessive model of inheritance.The �log10 P-values were plottedversus the chromosomal positions ofmutations. Horizontal red and purplelines represent thresholds of P ¼ 0.05with or without Bonferroni correction,respectively.

Journal of Investigative Dermatology (2019), Volume 139

backcrossing to establish a critical region, followed byphysical mapping in which the gene content of the criticalregion was determined and the subsequent mutationidentification by Sanger sequencing of all the coding re-gions and splice junctions. This process has been greatlyaccelerated not only by the advent of massively parallelsequencing techniques but also by genotyping all the G3mice at all the mutation sites and the use of high-speedstatistical computation to test the null hypothesis thateach mutation has nothing to do with any phenotypicvariance that might be observed in the screening (Wanget al., 2015). The real-time identification of mutations isbased on the premise that causation can be ascribed if allinduced and/or background stock mutations are known,and if the zygosity of those mutations is known in all G3mice (Wang et al., 2015). An average of 60 mutations incoding residues are transmitted from every ENU-mutagenized G0 progenitor to the G1 founder of eachpedigree, and these mutations are identified by whole-exome sequencing. The G1 male serves as the grandsireof the pedigree. All the mutations in a G1 mouse aretransmitted to the G3 mice, and the G3 mice are genotypedacross the mutated loci before phenotypic screening. Assoon as phenotypic data are collected from the G3 mice,they can be combined with the genotypic information todetermine the likelihood that an observed association be-tween phenotype and genotype would occur by chance(given dominant, additive, or recessive models ofinheritance).Both qualitative and quantitative phenotypes can be

subjected to real-time mapping. As an example of theformer, real-time mapping was used to identify a mutationin Dsg4 causative of a hair loss phenotype. Whole-exomesequencing of the pedigree revealed 72 coding regionmutations. Thirty-six G3 mice were produced and assessedfor a hair loss phenotype. These mice were sequenced at all72 loci identified in the G1 founder and then assessed forvarious phenotypes. Upon visual inspection, four mice inthis pedigree exhibited early hair loss (Figure 2a). Thirty-two appeared normal and were designated as unaffected.Automated mapping by recessive, additive, and dominantmodels of inheritance implicated a missense mutation inDsg4 that results in a valine to glutamic acid change atamino acid 211 of the protein. Mapping was the strongest

b

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RESEARCH TECHNIQUES MADE SIMPLE

with a recessive model of inheritance (P ¼ 1.2 � 10e5,Figure 2b); the 4 affected mice were homozygous for themissense mutation in Dsg4, whereas the 32 mice that wereunaffected were either wild-type or heterozygous at thislocus. Moreover, the affected mice exhibited varying zy-gosities at the other 71 loci that were found to be mutatedwith ENU, increasing the likelihood that the Dsg4 mutationis causative for the phenotype. Generally, phenotypicmappings are confirmed via the generation of mice thatknock-in for the ENU mutation using the clustered regu-larly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 technology; however, in thiscase, mutations in Dsg4 have been reported to cause var-iable hair loss in lanceolate hair (lah) mouse models(Sundberg et al., 2000), making verification unnecessary.An overview of the forward genetic approach in its entiretyis provided in Figure 3.

PHENOTYPIC SCREENINGAn incisive screen is a critical element in forward genetics. Ascreen should address a well-defined and realistic question. Itshould also be robust to the extent that few false positives areregistered (i.e., minimal type 1 error), meaning that a mini-mum amount of resources will be dedicated to the explora-tion of mutations that ultimately prove to be noncausative.The less one understands about a biological phenomenon,the more one stands to gain by screening, and the less can beaccomplished by other approaches. Yet it is usually a mistaketo conclude at the outset that “too much is known” about aparticular topic to warrant screening. Biological phenomenamediated by a small number of genes with nonredundantfunction will yield few causative mutations, yet these may becompellingly important. Those that depend upon largenumbers of genes, perhaps operating independently in mul-tiple cell types, will yield many causative mutations, which,however, may be more difficult to understand mechanisti-cally. In such a situation, the mutations with the greatest effectsize and the greatest novelty may be the ones to pursue.While some quantitative phenotypes may show a small effectsize, it is important to remember that most human pheno-variance results from additive or synergistic genetic differ-ences at multiple loci. From this standpoint, ENU-inducedmutations may point the way to a detailed understanding of

a

b

c

Figure 3. Overview of the forward genetics approach conducted at the Center fobackcrossing of 8e10 G2 mice to their G1 father. (b) Whole-exome sequencing imutated loci identified in the whole-exome sequencing of the G1 mouse. (d) G3 mphenotype data are used for mapping by Linkage Analyzer (Wang et al., 2015). Cmutant allele are displayed by the Linkage Explorer. (f) Causative mutations are coallele, which may be generated by CRISPR/Cas9 targeting. ENU, N-ethyl-N-nitrosoCRISPR-associated protein 9.

complex phenotypes. ENU mutagenesis can and should beused to suppress disease phenotypes, as well as to createthem.Mouse phenotypes can present spontaneously or only in

the presence of an environmental challenge. In our labora-tory, G3 mice undergo a series of phenotypic assays, begin-ning with those that are least invasive and ending with thosethat are highly invasive. The pipeline provides a compre-hensive assessment of visible, innate and adaptive immune,metabolic, and neurobehavioral phenotypes. The phenotypesdetected during screening are cataloged and made publiclyavailable at mutagenetix.utsouthwestern.edu. At the begin-ning of the phenotypic pipeline, the mice are inspected forvisible phenotypes, including differences in size, limb num-ber, behavior, and skin. In total, 96,569 G3 mice thatharbored over 155,957 ENU alleles have been assessed inthis manner, and 32 mutations that lead to alterations in grossmorphology of skin, hair, or nails have been detected. Someof these mutations were found in genes that were known to beimportant for cutaneous biology including Dsg4, Lyst, andTmem79 (Barbosa et al., 1996; Perou et al., 1996; Sasakiet al., 2013; Sundberg et al., 2000), whereas others (e.g.,Gk5, Tmprss6, Mbtps1, Dock7, Krt33a, and Krt25 [Blasiuset al., 2009; Brandl et al., 2009; Crozat et al., 2009; Duet al., 2008a, 2008b; Rutschmann et al., 2012; Zhang et al.,2017]) had not been implicated previously. Because allcoding ENU mutations are ascertained through whole-exomesequencing, the genome saturation achieved by a phenotypicassay can be determined provided that the probability that amutation is damaging is known. In addition, 39% of geneshave been severely damaged or destroyed and assessed forvisible phenotypes with at least three mice homozygous foreach damaging mutation.In some cases, phenotypes may only become apparent

after environmental manipulation. This includes chal-lenging mice with exogenous agents such as microbes orchemicals. Examples of dermatologic challenge assays thatcould be conducted include wound healing (Grada et al.,2018) and chemically induced psoriasis (Hawkes et al.,2018), which were recently featured in this ResearchTechniques Made Simple series. These two models sharefeatures with the intestinal dextran sulfate sodium injurymodel, which is one of the more fruitful assays in our

d

e f

r Genetics of Host Defense. (a) A minimum of 20 G3 mice are produced froms performed on the G1 founder. (c) G2 and G3 mice are genotyped across theice undergo a series of phenotypic assays. (e) Genotype data and quantitative

alculated P-values for nonlinkage and scatterplots of phenotypic data for everynfirmed by observation of the mutant phenotype in mice with a second mutanturea; CRISPR, clustered regularly interspaced short palindromic repeats; Cas9,

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MULTIPLE CHOICE QUESTIONS1. ENU mutagenesis primarily results in what type

of mutations?

A. Insertions

B. Deletions

C. Nucleotide substitutions

D. Duplications

2. Which of the following statements is correct?

A. Mutations in the G2 generation can be foundin the heterozygous form.

B. Mutations in the G3 generation can be foundin the heterozygous form.

C. Mutations in the G3 generation can be foundin the homozygous form.

D. All of the above.

3. On average, what fraction of the G3 mice arehomozygous for a functionally neutralmutation?

A. 1/16

B. 1/8

C. 1/4

D. 1/2

4. What is the probability that a G3 mouse ishomozygous for two unlinked neutralmutations?

A. 1/64

B. 1/32

C. 1/16

D. 1/8

5. Injection of germline mutant mice with mousecytomegalovirus to determine genes requiredfor resistance to infection is an example ofwhich of the following?

A. Spontaneous screen

B. Challenge screen

C. Modifier screen

See online version of this article for a detailed expla-nation of correct answers.

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RESEARCH TECHNIQUES MADE SIMPLE

laboratory (Turer et al., 2017). Moreover, phenotypesobserved in these assays can be scored quantitatively,which offers the advantage of objectively mapping traits ofeven weak effect.Almost all the phenotypes detected in our pipeline are

monogenic in nature, but occasionally complex phenovar-iance caused by mutations in the same pedigree can occur.For example, mice with white-spotted cream-colored coatswere produced in the presence of a Sox10 mutation, whichcaused the white spots, and a Tyr mutation, which resulted inthe cream color. Large numbers of G3 mice are required to

Journal of Investigative Dermatology (2019), Volume 139

detect complex traits caused by homozygosity for two un-linked recessive alleles because of the low probability (1/64)that a mouse will be homozygous at each locus. While mu-tations that have additive effects are rarely detected, multiplephenotypes within the same pedigree frequently occur.

CONCLUDING REMARKSForward genetics is an unbiased tool for elucidating the geneswith nonredundant function in selected biological processes.Real-time mapping technology has made it possible for us todeclare thousands of mutations responsible for phenotypes ina relatively short time. Moreover, the degree of saturation(percentage of genes damaged or destroyed and tested forphenotypic effect N times or more in the homozygous state)may be tracked as mutagenesis and screening progress (Wanget al., 2018). In the era of precision medicine, the ENUmutagenesis program detailed here can be envisioned forrapidly determining the significance of variants found in pa-tients and families carrying hereditary dermatologic disease.There is a substantial opportunity to use germline mutagen-esis to create or mitigate dermatologic diseases.

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSWe thank Diantha Lavine for expert assistance in figure generation. This workwas supported by the Immunology T32 Training Grant AI005184 at the UTSouthwestern Medical Center (to WM); NIH Grants K08 DK107886 (to ET),R37 GM066759 (to BB), R01 AI125581 (to BB), and U19 AI100627 (to BB);and by the Lyda Hill Foundation.

AUTHOR CONTRIBUTIONSCoordinated and Oversaw Research: BB, ET; Researcher: JR, WM; Trainee:WM; Writing: ARM, ET, WM, BB

SUPPLEMENTARY MATERIALSupplementary material is linked to this paper. Teachingslides are available as supplementary material.

REFERENCESArnold CN, Barnes MJ, Berger M, Blasius AL, Brandl K, Croker B, et al. ENU-

induced phenovariance in mice: inferences from 587 mutations. BMCRes Notes 2012;5:577.

Barbosa MD, Nguyen QA, Tchernev VT, Ashley JA, Detter JC, Blaydes SM,et al. Identification of the homologous beige and Chediak-Higashi syn-drome genes. Nature 1996;382:262e5.

Blasius AL, Brandl K, Crozat K, Xia Y, Khovananth K, Krebs P, et al. Mice withmutations of Dock7 have generalized hypopigmentation and white-spotting but show normal neurological function. Proc Natl Acad SciUSA 2009;106:2706e11.

Brandl K, Rutschmann S, Li X, Du X, Xiao N, Schnabl B, et al. Enhancedsensitivity to DSS colitis caused by a hypomorphic Mbtps1 mutationdisrupting the ATF6-driven unfolded protein response. Proc Natl AcadSci USA 2009;106:3300e5.

Crozat K, Li X-H, Smart N, Beutler B. Record for Spikey, updated May13, 2016. MUTAGENETIX, B. Beutler and colleagues, Center for theGenetics of Host Defense, UT Southwestern, Dallas, TX. 2009.https://mutagenetix.utsouthwestern.edu/phenotypic/phenotypic_rec.cfm?pk=125. Accessed 2018 January 13.

DeStefano GM, Christiano AM. The genetics of human skin disease. ColdSpring Harb Perspect Med 2014;4:a015172.

Du X, Li X-h, Smart NG, Beutler B. Record for Plush, updated December 12,2013. MUTAGENETIX, B. Beutler and colleagues, Center for the Ge-netics of Host Defense, UT Southwestern, Dallas, TX. 2008a. https://

RESEARCH TECHNIQUES MADE SIMPLE

mutagenetix.utsouthwestern.edu/phenotypic/phenotypic_rec.cfm?pk=96.Accessed 2018 January 13.

Du X, She E, Gelbart T, Truksa J, Lee P, Xia Y, et al. The serine proteaseTMPRSS6 is required to sense iron deficiency. Science 2008b;320:1088e92.

Grada A, Mervis J, Falanga V. Research techniques made simple:animal models of wound healing. J Investig Dermatol 2018;138:2095e105.e1.

Hawkes JE, Adalsteinsson JA, Gudjonsson JE, Ward NL. Research techniquesmade simple: murine models of human psoriasis. J Invest Dermatol2018;138:e1e8.

Oliver PL, Davies KE. New insights into behaviour using mouse ENU muta-genesis. Hum Mol Genet 2012;21:R72e81.

Perou CM, Moore KJ, Nagle DL, Misumi DJ, Woolf EA, McGrail SH, et al.Identification of the murine beige gene by YAC complementation andpositional cloning. Nat Genet 1996;13:303e8.

Rutschmann S, Crozat K, Li X, Du X, Hanselman JC, Shigeoka AA, et al.Hypopigmentation and maternal-zygotic embryonic lethality causedby a hypomorphic mbtps1 mutation in mice. G3 (Bethesda) 2012;2:499e504.

This is a reprint of an article that originally appeared in the September 2019 issue oFor citation purposes, please use these original publication details: McAlpine WForward Genetic Screening to Uncover Genes Involved in Skin Biology. J Invest

Sasaki T, Shiohama A, Kubo A, Kawasaki H, Ishida-Yamamoto A, Yamada T,et al. A homozygous nonsense mutation in the gene for Tmem79, acomponent for the lamellar granule secretory system, producesspontaneous eczema in an experimental model of atopic dermatitis.J Allergy Clin Immunol 2013;132:1111e20.e4.

Sundberg JP, Boggess D, Bascom C, Limberg BJ, Shultz LD, Sundberg BA,et al. Lanceolate hair-J (lahJ): a mouse model for human hair disorders.Exp Dermatol 2000;9:206e18.

Turer E, McAlpine W, Wang KW, Lu T, Li X, Tang M, et al. Creatine maintainsintestinal homeostasis and protects against colitis. Proc Natl Acad SciUSA 2017;114:E1273e81.

Wang T, Bu CH, Hildebrand S, Jia G, Siggs OM, Lyon S, et al. Probability ofphenotypically detectable protein damage by ENU-induced mutations inthe Mutagenetix database. Nat Commun 2018;9:441.

Wang T, Zhan X, Bu CH, Lyon S, Pratt D, Hildebrand S, et al. Real-timeresolution of point mutations that cause phenovariance in mice. ProcNatl Acad Sci USA 2015;112:E440e9.

Zhang D, Tomisato W, Su L, Sun L, Choi JH, Zhang Z, et al. Skin-specificregulation of SREBP processing and lipid biosynthesis by glycerol kinase5. Proc Natl Acad Sci USA 2017;114:E5197e206.

f the Journal of InvestigativeDermatology. It retains its original pagination here., Russel J, Murray AR, Beutler B, Turer E. Research Techniques Made Simple:Dermatol 2019;139(9):1848e1853; doi:10.1016/j.jid.2019.04.013

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RTMS Article 73, October 2018 Research TechniquesMade Simple: Animal Models of Wound Healing

QUESTIONS

1. Which of the following animal species healpredominantly by contraction?A. HumansB. PigsC. Mice and ratsD. Zebrafish

2. The mouse tail model has the following features exceptwhich of the following?A. Rapid healing capacityB. Can be used to study scarringC. Offers longer duration of wound closureD. Contraction is minimal

3. Which of the following animal species is most relevant topartial-thickness wound modeling?A. PigB. GreyhoundC. RabbitD. Guinea pig

4. To choose an optimal animal model, one must take intoconsideration the following factors:A. SizeB. CostC. ReproducibilityD. All of the above

5. Which of the following adult animals exhibits scar-freeskin regeneration?A. MouseB. RatC. PigD. Zebrafish

ª 2018 Society for Investigative Dermatology

ANSWERS

1. C

2. A

3. A

4. D

5. D

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RTMS Article 74, November 2018 Research TechniquesMade Simple: Transepidermal Water Loss Measurementas a Research Tool

QUESTIONS

1. How is TEWL measured?A. By measuring the volume of water on the surface of the

skinB. By measuring absolute water loss from the skin

gravimetricallyC. By measuring relative humidity and temperature at the

skin surface to calculate the change in water vapordensity

D. By measuring evaporation of water from the skin to theatmosphere

2. What advantages do condenser-chamber TEWL deviceshave over unventilated-chamber and open-chamberdevices?A. Water can diffuse out of the chamber into the

atmosphere.B. Continuous TEWL measurements can be made, and

disturbance from ambient air movements is minimized.C. The chamber is closed, allowing water vapor to

accumulate in the chamber.D. Individual TEWL measurements can be made faster.

3. What are the suggested conditions for TEWLmeasurement?A. Room temperature of 18e21 �C, relative humidity

of 40%e60%, and direct light; subjects shouldacclimatize to the environment for 20e30 minutesbefore TEWL measurement.

B. Room temperature of 18e21 �C, relative humidityof 20%e30%, and avoid direct light; subjects shouldacclimatize to the environment for 20e30 minutesbefore TEWL measurement.

C. Room temperature of 18e21 �C, relative humidityof 20%e30%, and avoid direct light; takemeasurement as soon as subject enters the testingenvironment.

D. Room temperature of 18e21 �C, relative humidityof 40%e60%, and avoid direct light; subjects shouldacclimatize to the environment for 20e30 minutesbefore TEWL measurement.

Journal of Investigative Dermatology (2018), Volume 138

4. Which body regions have the highest TEWL?A. Palms, soles, axillae, and foreheadB. Calves and forearmsC. Antecubital fossaeD. Abdomen, chest, and back

5. Which statement is true regarding TEWL in AD?A. At 3 months of age, FLG mutation-carrying infants do

not have increased TEWL.B. TEWL is increased at birth in FLG mutation-carrying

neonates compared with FLGewild-type neonates.C. TEWL is not a parameter in any AD severity scores.D. TEWL measured during the first days of life can predict

the development of AD in infancy.

ANSWERS

1. C

2. B

3. D

4. A

5. D

ª 2018 Society for Investigative Dermatology

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RTMS Article 75, December 2018 Research TechniquesMade Simple: CAR T-Cell Therapy

QUESTIONS

1. There are three generations of CARs. The generation of aCAR is defined by which of the following?A. Therapeutic potencyB. Number of extracellular domainsC. Number of signaling domainsD. Likelihood of resistance by the target

2. What is the main role of CD3z in a CAR?A. To bind the antigenB. It is a programmed death ligand.C. Structural stability of the CARD. T-cell activation

3. What is the source of T cells used in US Food and DrugAdministrationeapproved CAR T-cell therapies?A. Blood donorsB. Patient’s thymusC. Patient’s peripheral bloodD. Induced pluripotent stem cells

4. Which of the following targets would make a logicalchoice for highly selective CAAR T-cell therapy inpemphigus vulgaris?A. All B cells expressing CD-19B. All B cells expressing anti-desmoglein-3 B-cell

receptorsC. All cells expressing CD-30D. All cells expressing CD-52

5. Which of the following cutaneous toxicities has beendescribed after CAR T-cell therapy for hematologicmalignancy?A. Multiple cutaneous melanomasB. An eruption mimicking the rash of lymphocyte

recoveryC. Eruptive epidermal inclusion cystsD. Zosteriform dermatitis

ª 2018 Society for Investigative Dermatology

ANSWERS

1. C

2. D

3. C

4. B

5. B

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RTMS Article 76, January 2019 Research Techniques MadeSimple: Network Meta-Analysis

DrDrDr

QUESTIONS

1. Which of the following are advantages of conductinga network meta-analysis as compared to a pairwisemeta-analysis?A. Make indirect comparisons between interventions that

have not been previously compared in randomizedcontrolled trials.

B. Rank interventions in terms of their relative efficacy orsafety.

C. Increase the precision of our summary effect estimatesby including both direct and indirect evidence.

D. All of the above

2. You read an article reporting the results of a systematicreview and network meta-analysis. The authors reportthere was no inconsistency detected in their networkmeta-analysis models. You should:A. Accept the network meta-.analysis results as robust

because there was no inconsistency identifiedB. Read further in the study methods and results section to

see if the authors evaluated the transitivity assumptionprior to conducting the network meta-analysis.

C. Consider the similarities and differences between thestudies included in the network meta-analysis toevaluate the transitivity assumption.

D. B and C

3. Which of the following model outputs are common toboth pairwise and network meta-analysis?A. Summary effect estimate (e.g., odds ratio, mean

difference)B. Mean rankC. Surface under the cumulative ranking curve valueD. Inconsistency plot

4. Which of the following scenarios best describes ahomogeneous comparison?A. The mean age of patients enrolled in studies evaluating

comparison AB is 65 years; whereas, the mean age ofpatients enrolled in studies evaluating comparison ACis 70 years.

B. Among three studies evaluating comparison AB, themean age of patients enrolled in study #1 is 65 years,the mean age of patients enrolled in study #2 is 66

Journal of Investigative Dermatology (2019), Volume 139

years, and the mean age of patients enrolled in study#3 is 63 years.

C. The mean age of patients enrolled in studies evaluatingcomparison AB is 65 years; whereas, the mean age ofpatients enrolled in studies evaluating comparison ACis 66 years.

D. Among three studies evaluating comparison AB, themean age of patients enrolled in study #1 is 65 years,the mean age of patients enrolled in study #2 is 45years, and the mean age of patients enrolled in study#3 is 80 years.

5. You conduct a network meta-analysis on the comparativerisk of death from new drugs used to treat atopicdermatitis. The mean ranks for four of the new drugs areas follows:

ug A 6.2ug B 3.4ug C 8.1ug D 1.5

Dr

Which of the following is true?A. Drug A is associated with a greater risk of death

compared to Drug B.B. Drug D is associated with a lower risk of death

compared to Drug C.C. Drug A is associated with a lower risk of death

compared to Drug B.D. Drug D is associated with a lower risk of death

compared to Drug A.

ANSWERS

1. D

2. D

3. A

4. B

5. A

ª 2018 Society for Investigative Dermatology

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RTMS Article 77, February 2019 Research TechniquesMade Simple: Itch Measurement in Clinical Trials

QUESTIONS

1. Which unidimensional itch intensity scale allows patientsto mark itch intensity on a spectrum depicted as a 10-cmrulereshaped line labeled at each end with 0 for no itchand 10 for worst imaginable itch?A. Verbal rating scale (VRS)B. Visual analogue scale (VAS)C. Numerical rating scale (NRS)D. Dermatology Life Quality Index (DLQI)

2. Patient ease of use and compliance with theunidimensional itch intensity scales can be improvedby which of the following?A. Electronic diaries (eDiaries)B. Patient education before useC. Cartoon-illustrated versionsD. All of the above

3. The impact of itch on patient quality of life (QoL) can beassessed by which of the following tools?A. Visual analogue scale (VAS)B. ItchyQoLC. Eczema Area and Severity Index (EASI)D. Scoring Atopic Dermatitis (SCORAD)

4. In addition to itch intensity alone, multidimensional itchassessments may also evaluate which of the following?A. Patient QoLB. Itch frequency and courseC. Patient expectations and treatment goalsD. All of the above

5. Which of the following are superior tools for themeasurement of itch?A. Unidimensional itch intensity scalesB. Multidimensional itch assessmentsC. Objective tools that measure scratching activity and

associated skin changesD. None of the above

ª 2018 Society for Investigative Dermatology

ANSWERS

1. B

2. D

3. B

4. D

5. D

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RTMS Article 78, March 2019 Research Techniques MadeSimple: Interpreting Measures of Association in ClinicalResearch

QUESTIONS

1. A study follows adults with psoriasis treated with eitherretinoids alone or retinoids with corticosteroids. Therelative risk of 6-month psoriasis recurrence is 0.8. Whatis the correct interpretation of this finding?A. The incidence of psoriasis recurrence in adults who are

dual-treated with retinoids and corticosteroids is 0.8(80%).

B. Adults with psoriasis who are dual-treated with topicalretinoids and corticosteroids have 0.8 times the risk ofhaving 6-month psoriasis recurrence compared withthose who receive only retinoid treatment.

C. The difference in risk of 6-month psoriasis recurrencebetween adults treated with only retinoids and thosedual-treated with topical retinoids and corticosteroidsis 0.8 (80%).

D. The difference in risk of 6-month psoriasis recurrencebetween adults treated with only retinoids and thosedual-treated with topical retinoids and corticosteroidsis 0.2 (20%).

2. In a case-control study, what measure of associationshould be used to calculate associations between theexposure and outcome?A. Hazard ratioB. Pearson correlation coefficientC. Odds ratioD. Relative risk

3. Can an odds ratio ever approximate the relative risk?A. Yes, when the outcome (i.e., disease) being studied is

rare.B. Yes, when the exposure being studied is rare.C. No, because the odds ratio is calculated using odds,

and the relative risk is calculated using incidence rates.D. No, because these measures are calculated using data

from different study designs.

Journal of Investigative Dermatology (2019), Volume 139

4. What are confounders?A. Variables that are associated only with the exposureB. Independent variables that are associated with both the

exposure and the outcomeC. Variables that are associated only with an outcomeD. Variables that are the consequence of an exposure

5. A chi-squared test is used for what type of data?A. Discrete quantitativeB. RatioC. Continuous quantitativeD. Categorical

ANSWERS

1. B

2. C

3. A

4. B

5. D

ª 2019 Society for Investigative Dermatology

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RTMS Article 79, April 2019 Research Techniques MadeSimple: Profiling the Skin Microbiota

QUESTIONS

1. Which of the following is an advantage of culture-independent, sequencing-based approaches toanalyzing skin microbiota?A. It distinguishes microbes that are living from those that

are dead.B. It establishes causative links.C. It does not require culturing microbes in artificial

conditions.D. It is difficult to contaminate reagents and samples.

2. What is the advantage of shotgun metagenomicsequencing compared with 16S rRNA gene sequencing?A. Increased taxonomic resolutionB. Enhanced growth of microbesC. Recovery of bacterial, fungal, and viral sequencesD. A and C

3. Which of the following is not a recommended practicewhen designing a study for culture-independentprofiling of microbiota?A. Including negative controls to assess background

contaminationB. Using a variety of DNA extraction kitsC. Controlling for antibiotic exposuresD. Including a mock community as a positive control

4. Which of the following is a common and recommendedpractice when analyzing 16S rRNA gene sequencingdata?A. Testing associations/correlations with every single

variable until something is significantB. Using parametric statistical tests because microbiome

data are always normally distributedC. Assigning sequences to operational taxonomic units, or

OTUsD. Ignoring sequences in negative control samples

ª 2019 Society for Investigative Dermatology

5. Which of the following is a bioinformatic tool/pipelinethat is commonly used for the analysis of microbiomedata sets?A. QIIME2B. RC. mothurD. All of the above

ANSWERS

1. C

2. D

3. B

4. C

5. D

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RTMS ANSWERS �

RTMS Article 80, May 2019 Research Techniques MadeSimple: Mouse Models of Atopic Dermatitis

QUESTIONS

1. The MC903 model used to study human atopic dermatitisrepresents which category of mouse model?A. Inbred modelB. Genetically engineered transgenic modelC. Genetically engineered knockout modelD. Model induced by an exogenous agent

2. Which of the following mutations is the most responsiblefor atopic dermatitis-like inflammation in flaky tail mice?A. FlgB. Tmem79

C. TslpD. Adam17

3. Which of the following cytokines from keratinocytes isresponsible for the activation of group 2 innate lymphoidcells 2 (ILC2)?A. TSLPB. IL-18C. IL-33D. All of the above

4. Which of the following microbes is responsible for thedevelopment of skin inflammation in Adam17fl/flSox9Cre mice?A. Cutibacterium acnes

B. Malassezia furfur

C. Pseudomonas aeruginosa

D. Staphylococcus aureus

Journal of Investigative Dermatology (2019), Volume 139

5. Which of the following sentences highlights a lesson froma recent study that compared transcriptomic profilesbetween human atopic dermatitis (AD) and mousemodels?A. The oxazolone-induced mouse model exhibited the

highest degree of overlap with human AD.B. More than 50% of core signatures of the human AD

transcriptome overlapped with the differentialexpression genes analyzed in all tested mouse models.

C. Based on available databases, less than 5% of proteincoding genes are not shared in mouse and human AD.

D. Each animal model reflects limited aspects of humanAD.

ANSWERS

1. D

2. B

3. D

4. D

5. D

ª 2019 Society for Investigative Dermatology

� RTMS ANSWERS

RTMS Article 81, June 2019 Research Techniques MadeSimple: Parabiosis to Elucidate Humoral Factors in SkinBiology

QUESTIONS

1. For best results, mice should be which of the following forparabiosis?A. FemaleB. Background-matchedC. Of similar sizeD. All of the above

2. What protein variable can give a false negative result inparabiosis experiments?A. SizeB. Molecular weightC. Synthetic rateD. Clearance rate

3. Parabiotic disease is the most common cause of death forparabiosis pairs 1e2 weeks after surgery. What is theincidence in outbred strains?A. 20%B. 40%C. 60%D. 100%

4. Parabiosis experiments were instrumental in identifyingthe first circulating factor in satiety. What is this factor?A. InsulinB. ResistinC. LeptinD. Limastatin

5. What is the perioperative mortality in parabiosisexperiments?A. 10%B. 20%C. 30%D. 40%E. 50%

ª 2019 Society for Investigative Dermatology

ANSWERS

1. D

2. D

3. C

4. C

5. A

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RTMS Article 82, July 2019 Research Techniques MadeSimple: Using Genetic Variants for Randomization

QUESTIONS

1. Which of the following is a limitation of observationalstudies that can be addressed with MR?A. Publication biasB. Selection biasC. ConfoundingD. Inadequate sample size

2. Which of the following is NOT an assumption for a validMR instrument?A. The instrument must be truly associated with the

exposure and the outcome.B. The instrument must be truly associated with the

exposure.C. The instrument must not be associated with

confounders of the exposure-outcome relationship.D. The instrument must affect only the outcome via the

exposure.

3. Which of the following can be used to uncover thedirection of a causal relationship?A. Two-sample MRB. Observational analysisC. One-sample MRD. Bidirectional MR

4. Which of the following can be used to address pleiotropyin MR?A. Wald ratio methodB. MR-Egger regressionC. Inverse-variance weighted estimatorD. Two-stage least squares

5. Which of the following statements is FALSE?A. MR can be performed in a hypothesis-free manner.B. MR estimates represent the effect of long-term

exposures.C. Pleiotropic genetic instruments cannot be included in

MR analyses.D. MR can be used to investigate the causal role of

molecular phenotypes.

Journal of Investigative Dermatology (2019), Volume 139

ANSWERS

1. C

2. A

3. D

4. B

5. C

ª 2019 Society for Investigative Dermatology

� RTMS ANSWERS

RTMS Article 83, August 2019 Research Techniques MadeSimple: Teledermatology in Clinical Trials

QUESTIONS

1. Which statement is true regarding previous and ongoingvirtual clinical trials?A. There has never been a successful virtual clinical trial

in the field of dermatologyB. The first virtual clinical trial had no issues with

implementation of online registration for theirparticipants

C. Use of technology has improved recruitment andretention in a clinical trial concerning pemphigusvulgaris

D. Dermatology has pioneered the use of wearablesensors for data collection in virtual clinical trials

2. Which study might be inappropriate to considerconducting completely virtually?A. Comparing use of two systemic medications for a rare

autoimmune disease across several statesB. Multistage study with various subpopulations requiring

frequent coordination of social work, pharmacy,physical therapy, oncology, and dermatology

C. An interventional clinical trial with a new topical drugfor rosacea requiring weekly evaluation of clinicalprogression of disease and patient-reportedexperiences using the medication

D. A trial designed to study the effect of an oralmedication for acne on liver enzymes on a monthlybasis

3. Which of the following is false regarding the use of socialmedia in recruitment of participants for clinical trials?A. Study population can be viewed as a random sample of

the general populationB. Social media represents a tool to recruit participants

over a wider and more diverse population thantraditional methods

C. Facebook has been used in previous trials for therecruitment of participants to clinical trials

D. A study that recruits participants with social mediaalone may exclude some populations

ª 2019 Society for Investigative Dermatology

4. Which of the following is not an advantage ofincorporating technology into a clinical trial?A. Patient-centered data collection allows participants to

enter data on their own time rather than attendfrequent on-site clinic visits

B. Potential for increased communication between studycoordinators and research participants

C. Streamlined online informed consent and studyregistration

D. No need for training to ensure quality of photos takenby participants for data collection purposes

5. Which of the following is an important limitationregarding the use of technology in clinical trials?A. Storage of online data must comply with rigorous

privacy standardsB. The current guidelines for conducting virtual clinical

trials are too restrictiveC. The general population is uncomfortable with

communication technologies like social media andapplications on their phones

D. Most potential participants do not have access toreliable Internet

ANSWERS

1. C

2. B

3. A

4. D

5. A

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RTMS Article 84, September 2019 Research TechniquesMade Simple: Forward Genetic Screening to UncoverGenes Involved in Skin Biology

QUESTIONS

1. ENU mutagenesis primarily results in what type ofmutations?A. InsertionsB. DeletionsC. Nucleotide substitutionsD. Duplications

2. Which of the following statements is correct?A. Mutations in the G2 generation can be found in the

heterozygous form.B. Mutations in the G3 generation can be found in the

heterozygous form.C. Mutations in the G3 generation can be found in the

homozygous form.D. All of the above.

3. On average, what fraction of the G3 mice arehomozygous for a functionally neutral mutation?A. 1/16B. 1/8C. 1/4D. 1/2

4. What is the probability that a G3 mouse is homozygousfor two unlinked neutral mutations?A. 1/64B. 1/32C. 1/16D. 1/8

5. Injection of germline mutant mice with mousecytomegalovirus to determine genes required forresistance to infection is an example of which of thefollowing?A. Spontaneous screenB. Challenge screenC. Modifier screen

Journal of Investigative Dermatology (2019), Volume 139

ANSWERS

1. C

2. D

3. B

4. A

5. B

ª 2019 Society for Investigative Dermatology

RTMS SUPPLEMENTARY INFORMATION

RTMS Articles 73e84 (2018e2019) Teaching Slides

Teaching slides are available for every RTMS article. Please visit the URLs below:

Article 73, October 2018 http://dx.doi.org/10.1016/j.jid.2018.08.005

Article 74, November 2018 http://dx.doi.org/10.1016/j.jid.2018.09.001

Article 75, December 2018 http://dx.doi.org/10.1016/j.jid.2018.09.002

Article 76, January 2019 http://dx.doi.org/10.1016/j.jid.2018.10.028

Article 77, February 2019 http://dx.doi.org/10.1016/j.jid.2018.12.004

Article 78, March 2019 http://dx.doi.org/10.1016/j.jid.2018.12.023

Article 79, April 2019 http://dx.doi.org/10.1016/j.jid.2019.01.024

Article 80, May 2019 http://dx.doi.org/10.1016/j.jid.2019.02.014

Article 81, June 2019 http://dx.doi.org/10.1016/j.jid.2019.03.1134

Article 82, July 2019 http://dx.doi.org/10.1016/j.jid.2019.03.1138

Article 83, August 2019 http://dx.doi.org/10.1016/j.jid.2019.04.004

Article 84, September 2019 http://dx.doi.org/10.1016/j.jid.2019.04.013

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