National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention

Standardized Clinical Reporting of Sequencing Data for DR-TB Diagnosis

Angela M. Starks, PhD

Chief, Laboratory Branch

Webinar Series: Next-generation sequencing for drug-resistant TB

Tuesday, February 12, 2019

Division of Tuberculosis Elimination

Why Focus on Standardized Molecular Reporting?

▪ Increasing use of DNA sequencing for molecular drug susceptibility testing– Allows for rapid and comprehensive results

– Useful for clinical management and surveillance of drug resistance

▪ Molecular testing will likely reduce phenotypic testing needs in many countries– Sequencing data can provide additional information beyond a

categorical result of resistant or susceptible

Why Focus on Standardized Molecular Reporting? (2)

▪ Need clearly communicated laboratory results with guidance for interpretation– Consistent

– Comparable

– Aid clinical decision making

▪ Harmonized reporting approach essential for patients to receive similar benefits from sequencing results

Saying the Same Thing in Different Ways Molecular analysis of rpoB

• No mutation detected

• Wild-type

• No mutation; likely rifampin susceptible

• No mutation in RRDR

• Mutation detected

• S531L mutation; S450L mutation

• TCG TTG; Ser531Leu

• Mutation detected; rifampin resistant

Variability of reporting can make it difficult to combine and compare data

Considerations Regarding Laboratory Reporting

▪ Genetic loci and associated anti-TB drugs for inclusion

▪ Reporting of heteroresistance

▪ Analytic pipeline and database for interpretation– Classification scheme for grading mutations

– What information might be included for a new, previously uncharacterized or poorly characterized mutation?

▪ When available, correlation of molecular and phenotypic drug susceptibility test results– How will discordance between these methods be reported and

explained?

Finding the Right Balance Enough information should be provided to interpret the results

Too much information or increasing the complexity of the information could hinder understanding

Different audiences may have different needs (laboratory, clinician, and surveillance)

Nice to Know Need to Know

Molecular Detection of Drug Resistance (MDDR) Service▪ U.S. CDC service implemented in 2009

– Clinical testing service for MTB

• Rapid detection/confirmation of multidrug resistance

• Provides additional information quickly for second-line drugs

• Targeted sequencing using conventional methods

– Available nationally to all jurisdictions

– Clinical consultation provided on request to aid results interpretation

– https://www.cdc.gov/tb/topic/laboratory/mddrusersguide.pdf

▪ U.S. CDC also supports Centers of Excellence for expert medical consultation regarding treatment – https://www.cdc.gov/tb/education/tb_coe/default.htm

MDDR PanelIsolates, NAAT+ Sediments, NAAT+ extractions from fixed tissue)

• rpoB (81bp region)+ Val176 +Ile572

• inhA (-15, -8)

• katG (Ser315)

• fabG1 (mabA) Leu203

• ahpC (promoter)

• embB (Met306, Gly406)

• pncA

• gyrA +gyrB QRDR

• rrs (nt1401/1402,1484)

• eis (promoter region)

• tlyA (coding region)

• Rifampin

• Isoniazid

• Isoniazid

• Isoniazid

• Isoniazid

• Ethambutol

• Pyrazinamide

• Fluoroquinolones

• Amikacin, Kanamycin,

Capreomycin

• Kanamycin

• Capreomycin

PSQ

Sanger

RTMCC requested isolate to be sent to CDC for full panel MDDR (Sanger sequencing)

Example of MDDR Report

A Few Lessons We Learned Along the Way…

Clarity of reporting is key

As the science advances, the reporting language needs to change

Feedback is important▪ You may understand what you mean, but do others using the report?

Access to consultation is essential

Sharing our experience is important▪ Wanted to engage as part of a broader effort to aid clear laboratory reporting

Gathering Expert Opinion

“Standardizing Reporting Language for DNA Sequencing of Resistance-associated Mutations of Mycobacterium tuberculosis complex”

• February 3–4, 2016 and September 27–28, 2017

• Sponsored by Critical Path Institute, WHO, FIND, and U.S. National Institutes of Health Division of AIDS

Participants included laboratorians, epidemiologists, clinicians, bioinformaticians, government representatives, and public health partners with expertise in reporting and use of molecular results

▪ Representation from Europe, North and South America, Southeast Asia, Africa, and the Western Pacific

Workshop Goals

Develop a laboratory report template for next generation sequence results for MTB

Determine minimal relevant data elements and optimal terminology

Identify an optimal report format

Focus on a report that is flexible

▪ Can meet specific programmatic needs

▪ User friendly for different training levels

• Simple summary and additional details for expert users

▪ Can be expanded as resistance-predicting datasets grow

Predominant Themes from Discussions

Strong preference towards laboratory report that individuals with a range of expertise could use for drug resistance prediction

Primary intended use is to provide information for healthcare providers to determine optimal treatment regimens

Results should be presented as two parallel reports

▪ A one-page simple report for those with less expertise in NGS

▪ A longer comprehensive report with additional NGS variables

Predominant Themes from Discussions (2)

Include complete drug name, not an abbreviation

Include a categorical interpretation for each drug for which a gene target is evaluated

Provide the specific mutation and frequency of the reported mutation among the reads examined

▪ Nucleotide change and position(s)

OR

▪ Amino acid change(s) using the three-letter abbreviation with its associated codon

Use MTB numbering system

One-page Simple Report

Includes laboratory and patient demographics as well as assay details

Describes results for first and second-line anti-TB drugs

Provides basic summary of results including identification of high-confidence resistance-associated mutations

Mutations with less clear interpretations refer users to seek expert consultation

▪ In example, interpretations based on likelihood ratios using data from ReSeqTBdatabase (https://platform.reseqtb.org/)

Longer Comprehensive Report

Includes high-confidence mutations from simple one-page report with additional data

▪ Mutations with less definitive interpretations

▪ Technical details

Relevant for expert consultation to advise on all identified mutations

Would specify resistance prediction to different DST concentrations (e.g., moxifloxacin)

Could include section for resistance prediction of new or repurposed anti-TB drugs

Long Report NGS Statistics

Proposed Next Steps for Template

Translation into multiple languages, beta-testing, and piloting in different settings

Development of education and training criteria relevant for different levels of expertise and role

Alignment of reporting with treatment guidelines and processes for expert consultation

Piloting of the reporting framework in electronic systems

For more information, contact CDC1-800-CDC-INFO (232-4636)TTY: 1-888-232-6348 www.cdc.gov

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

AcknowledgementsFeb 3-4 2016 workshop

Name Affiliation

Andrea Cabibbe World Health Organization

Anita Suresh Beckton Dickenson

Astrid Ferlinz Thermofisher

Beverly Metchock Centers for Disease Control and Prevention

Camilla Rodrigues P.D. Hinduja National Hospital and Medical Research Centre

Catherine Arnold Public Health England

Daniela Maria Cirillo San Raffaele Scientific Institute

Derrick Crook Oxford

Frank Cobelens Amsterdam Institute for Global Health and Development

Gunta Dravniece KNCV Tuberculosis Foundation

Ibrahim Abubakar University College London

Katja Einer Qiagen

Lakshmi Jayashankar National Institute of Health, Division of AIDS

Lori Armstrong Centers for Disease Control and Prevention

Maha Reda Farhat Harvard

Marco Schito Critical Path Institute

Martina Casenghi Medecins Sans Frontieres

Matteo Zignol World Health Organization

Nazir Ismail National Institute for Communicable Diseases

Pennan Barry California Department of Public Health

Peter Cegielski Centers for Disease Control and Prevention

Stefan Neimann Research Center Borstel

Tim Rodwell Foundation for Innovative New Diagnostics

Yan Ling Zhao China Centers for Disease Control

For more information, contact CDC1-800-CDC-INFO (232-4636)TTY: 1-888-232-6348 www.cdc.gov

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Acknowledgements (2)Sept 27-28 2017 Workshop

Name Affiliation

Lucilaine Ferrazoli Adolfo Lutz Institute

Jennifer Gardy BC Centre for Disease Control

James Posey Centers for Disease Control and Prevention

Alicia Chou Critical Path Institute

Marco Schito Critical Path Institute

Matthew Ezewudo Critical Path Institute

Rick Liwski Critical Path Institute

Anita Suresh Foundation for Innovative New Diagnostics

Timothy Rodwell Foundation for Innovative New Diagnostics

Irina Kontsevaya Imperial College London

Leen Rigouts Institute of Tropical Medicine Antwerp

Jeffrey Tornheim Johns Hopkins School of Medicine

Sven Hoffner Karolinska Institutet

Jody Phelan London School of Hygiene and Tropical Medicine

K.R. Uma Devi National Institute for Research in Tuberculosis

Nguyen Van Hung National Lung Hospital, Hanoi

Thuong Nguyen Thuy Thuong Oxford University Clinical Research Unit Hospital for Tropical Diseases

Camilla Rodrigues P.D. Hinduja National Hospital and Medical Research Centre

Valeriu Crudu Phthisiopneumology Institute

Vlad Nikolayevskyy Public Health England

Alena Skrahina Republican Research and Practical Centre for Pulmonology and Tuberculosis

Christoph Lange Research Center Borstel

Stefan Niemann Research Center Borstel

Daniela Cirillo San Raffaele Scientific Institute

Paolo Miotto San Raffaele Scientific Institute

Leonid Chindelevitch Simon Fraser University

Jason Hinds St. George's University of London

Rob Warren Stellenbosch University

Tom Shinnick TB Diagnostics Advisor, former GLI Chair

Soyoun Shin The Korean Institute of Tuberculosis

David Engelthaler Translational Genomics Research Institute

Rebecca Colman University of California San Diego

Claudio Koser University of Cambridge

Ana Gibertoni Cruz University of Oxford

Derrick Crook University of Oxford

Joseph Shea Wadsworth Center, New York State Department of Health

Kimberlee Musser Wadsworth Center, New York State Department of Health

Matteo Zignol World Health Organization

For more information, contact CDC1-800-CDC-INFO (232-4636)TTY: 1-888-232-6348 www.cdc.gov

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Acknowledgements (3)

Critical Path Institute/ CPTR

WHO

NIH/DAIDS

FIND

NDWG