No Association Between SelectedCandidate Gene Polymorphismsand Severe Chronic PeriodontitisJohan C. Wohlfahrt,* Tianxia Wu,† James S. Hodges,‡ James E. Hinrichs,* and Bryan S. Michalowicz*

Background: Chronic periodontitis (CP) risk is influencedby environmental and genetic factors. Using a case-controldesign, we tested for associations between CP and selectedDNA sequence variations (single nucleotide polymorphisms[SNPs]) in or near genes coding for proteins that play a rolein the pathogenesis of this disease.

Methods: DNA was analyzed from 219 whites who were ex-amined clinically. Cases (N = 137) were ‡35 years of age witheight or more teeth having ‡5 mm of proximal clinical attach-ment loss. Controls (N = 82) were ‡45 years of age with minimalor no proximal attachment loss or pocketing. Nine diallelic poly-morphisms (gene and SNP descriptor) were studied in sub-jects: cytotoxic T-lymphocyte antigen-4 (CTLA-4, 49 A>G),human b-defensin-1 (DEFB1, 692 G>A), intercellular adhesionmolecule-1 (ICAM-1, 1548 A>G), Fas ligand (fasL, -844 C>T),inducible costimulator (ICOS, 3990 G>T), interleukin-6 (IL-6,-174 G>C), cysteine-cysteine chemokine receptor-5 (CCR5,59653 C>T), osteoprotegerin (OPG, 245 T>G), and osteopontin(OPN, 707 C>T). Genotypes were determined using an auto-mated fluorogenic 59-nuclease, polymerase chain reaction-based assay. Gender and smoking history (pack-years) wereincluded as covariates in logistic regression analyses.

Results: Heavy smoking (>10 pack-years) and male genderwere significantly associated with disease (P <0.001). For allSNPs tested, the allele frequencies and distributions of geno-types did not differ between cases and controls (P>0.05). Noun-adjusted or adjusted odds ratios (comparing genotypes in casesversus controls) were significantly different than 1.0 (P >0.05)under any additive, dominant, or recessive inheritance model.

Conclusions: None of the SNPs tested were strongly associ-ated with generalized severe chronic periodontitis in NorthAmerican whites. A potentially more fruitful approach in futurestudies will be to test for associations between periodontitisand haplotype blocks constructed from either multiple SNPs incandidate gene regions or from panels of markers that spanthe entire genome. J Periodontol 2006;77:426-436.

KEY WORDS

Case-control studies; cytokines; genetics; inflammation;periodontitis; polymorphism, single nucleotide.

It is widely accepted that specific mi-croorganisms are essential for the de-velopment of destructive periodontal

disease.1 Although this specific plaquetheory helps explain the poor correlationbetween clinical plaque scores and dis-ease levels, a substantial amount of thevariation in disease in the population can-not be attributed to measured environ-mental factors. Results from twin studiessuggest that about half of the variance indisease measures is attributed to geneticvariation.2,3 This heritable componentmay reflect, among other things, interin-dividual differences in immunologic re-sponsiveness to bacterial antigens, whichis controlled in part by multiple genes.4

Recent advances in molecular biologyhave made the search for genetic riskmarkers for complex diseases more fea-sible. The population-based case-controlstudy is one of the more common designsused for this purpose. With this design,the prevalence of a genetic marker (typ-ically some coding sequence variation orpolymorphism) is compared betweenaffected individuals and healthy controlsrandomly selected from the same popu-lation. One limitation with the case-control design is the difficulty in matchinggroups on genetic background.5 False-positive or -negative findings are pos-sible if cases and controls are recruitedfrom genetically diverse racial or ethnicgroups and the prevalence of the markerand disease differs between groups.Family-based association studies, whichuse cases and controls from the samebiologic families, greatly reduce the risk

* Department of Preventive Sciences, School of Dentistry, University of Minnesota,Minneapolis, MN.

† National Institute of Dental and Craniofacial Research, Bethesda, MD.‡ Division of Biostatistics, School of Public Health, University of Minnesota.

doi: 10.1902/jop.2006.050058

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of population stratification. Nonethe-less, the case-control design is generallythought to be easier to conduct and moreefficient in terms of genotyping thanfamily-based approaches.6

Although human leukocyte antigens(HLA), which are highly variable tissueantigens, were first studied in periodon-tology 30 years ago,7 more recent ef-forts8 have attempted to define risk forperiodontal disease as a function of var-iations at the genotypic level (i.e., codingor DNA sequence variations). Over thepast decade or so, nearly 200 such stud-ies have been reported in the literature.

The purpose of the present study wasto search for novel genetic risk markersfor chronic periodontitis. We focused onsingle nucleotide polymorphisms (SNPs),or base-pair substitutions, because theyare common in the human genome andcan be typed in a high-throughput andrelatively inexpensive manner. To date, over 3 millionSNPs have been identified and archived in public da-tabases. We selected SNPs for study based on the fol-lowing criteria: 1) the SNP resided in or near a genethat codes for a protein known to play a role in thepathogenesis of periodontitis; 2) the gene or flankingregions contain a polymorphism that had been asso-ciated with an inflammatory or infectious disease; and3) the frequency of the minor or variant allele wasgreater than 10% in whites. We searched public data-bases (e.g., National Center for Biotechnology Infor-mation [NCBI]) and the literature for candidate SNPs.

MATERIALS AND METHODS

We used the case-control study design to test for as-sociations between chronic periodontitis and selectedSNPs. The institutional review boards at the Universityof Minnesota, Minneapolis (UMN), MN and Universityof the Pacific (UOP), San Francisco, CA approved theprotocol and consent process. Demographic informa-tion and medical, dental, and smoking histories wereobtained using self-administered questionnaires.Race and ethnicity were self-reported.

Subjects were recruited from outpatient dentalclinics at the UMN and the UOP between June 7,1994andApril7,2003.Probingdepth(PD)andclinicalattachment loss (CAL) measurements were recordedonsixsurfacesofall teeth,excluding thirdmolars,usinga manual probe. All measurements were obtained orreviewed by trained and calibrated examiners.

Cases were individuals ‡35 years of age with eightor more teeth having ‡5 mm of proximal CAL. At leastthree affected teeth had to be other than first molars orincisors. Rarely, cases could have fewer affected teeth

Table 1.

Marker Characteristics

Gene Locus

NCBI Accession (nucleotide

position) or dbSNP Number Descriptor

CTLA-4 2q33 rs231775 49 A>G

DEFB1 8p23.1 rs11362 692 G>A

ICAM-1 19p13.3-p13.2 rs5030382 1548 A>G

FasL 1q23 AB013303.1 (1530) -844 C>T

ICOS 2q33 AF488347.1 (3990) 3990 G>T

IL-6 7p21 AF039224.1 (378) -174 G>C

CCR5 3p21 U95626.1 (59653) 59653 C>T

OPG 8q24 AB008821.1 (245) 245 T>G

OPN 4q21-25 rs1126616 707 C>T

Table 2.

Demographic and Clinical Characteristicsof Subjects

Cases

(N = 137)

Controls

(N = 82)

Female N (%) 61 (44.5) 55 (67.1)

Mean (SD) age (years) 53.3 (10.5) 56.0 (10.9)

Minimum, maximum 36, 86 45, 86

Smoking history

Current (%) 52 (38.0) 10 (12.2)

Former (%) 61 (44.5) 25 (30.5)

Never (%) 24 (17.5) 47 (57.3)

Mean pack-years (SD)for current andformer smokers

27.9 (24.2) 5.9 (12.1)

Mean (SD) probingdepth (mm)

3.64 (0.83) 2.12 (0.24)

Mean (SD) attachmentloss (mm)

4.09 (1.23) 0.90 (0.75)

Mean (SD) N siteswith PD ‡5 mm

41.3 (27.8) 0.6 (1.3)

Sites (%) 28.9 0.38

Mean (SD) N siteswith AL ‡5 mm

51.72 (30.95) 1.03 (2.90)

Sites (%) 38.79 0.80

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427

if they had clinical, radiographic, or unequivocal an-amnestic evidence of generalized severe periodontaldisease. Many cases had undergone periodontaltreatment or had affected teeth extracted prior to en-rollment. Subjects were excluded as cases if they hada history of diabetes, human immunodeficiency virus(HIV) infection, or other medical conditions associ-ated with periodontitis; a history of immunosuppres-sive therapy; took drugs known to cause gingivalhyperplasia; or knew they had bone loss or gum dis-ease as adolescents.

Controls were ‡45 years of age and had at least ‡20natural teeth and no history of periodontal treatment.Controls could have had localized pocketing >3 mmprovided these sites had no or only incipient CAL(£2 mm), or localized proximal CAL, provided therewas no pocketing or inflammation. Controls were re-quired to have clear clinical, radiographic, or anam-nestic evidence that missing teeth were not lostbecause of periodontitis.

DNA Isolation and QuantitationDNA was isolated from whole blood.§ A 260-nm wave-length spectrophotometryi was used to quantify the

DNA. Once isolated, DNA sam-ples were stored at -70�C to-80�C until analyzed.

Candidate SNPsTable 1 provides informationabout thecandidateSNPs tested.Brief descriptions of theseSNPs and their associationswith other diseases are pro-vided in the Appendix.

GenotypingDNA samples were genotypedusing oligonucleotide allele-specific probes and a 59 nu-clease allelic discriminationassay.¶ Theassaymethodshavebeen described in more detailelsewhere.9-11 The osteopontin(OPN) SNP was typed using aprobe;# all other SNPs were as-sayed using an assay-designsystem.** Approximately 25ng genomic DNA was used foreach assay following a protocolfor 35 polymerase chain re-action (PCR) cycles12 and themanufacturer’s recommenda-tions. Some samples were di-luted with sterile nuclease-freewater to achieve a final con-centration of 25 ng DNA/ml.

A commercial laboratory†† performed these assays.

Statistical AnalysesWe tested whether the distribution of genotypes foreach SNP was in Hardy-Weinberg equilibrium (HWE)proportion in controls using x2 tests. Chi-square orFisher exact tests were used to compare the distribu-tion of genotypes between cases and controls. The ztest based on the normal distribution was used to com-pare allele frequencies between cases and controls.13

Two pairs of siblings were included in the case groupand one pair in the control group. The analyses, how-ever, did not account for sibling status.

We used logistic regression to examine associa-tions (summarized as odds ratios) between genotypeand case/control status while adjusting for gender andsmoking history. Age was not included in any modelbecause the selection criteria for both groups includedage restrictions. Smoking history was summarized

Figure 1.Distribution of single nucleotide polymorphism genotypes in cases (N = 137) and controls (N = 82).

§ QIAmp, DNA blood maxi or mini kits, QIAGEN, Valencia, CA.i Unico, model 2000, United Products & Instruments, Dayton, NJ.¶ TaqMan, Roche Molecular Systems, Pleasanton, CA.# Assays-on-Demand, Applied Biosystems, Foster City, CA.** Assays-by-Design, Applied Biosystems.†† ACGT, Wheeling, IL.

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using pack-years, and subjects were grouped into oneof three categories: 1) 0 pack-years (i.e., never smokers);2) 1 to 10 pack-years; or 3) >10 pack-years.

We did three logistic regressions for each SNP. In allregressions, case/control was the dependent variable.The threemodels differed in the codingof the indepen-dentvariable (genotype) for thespecificSNP.Foreachmodel, wild-type homozygotes were included in thereference group. If the wild-type homozygote, hetero-zygote, and variant homozygote genotypes are labeledAA, AB, and BB, respectively, then in the first regres-sion model, AB and BB were compared separately toAA. In the second and third models, the heterozygote(AB) genotypewas groupedwith either AA or BB, andthe resulting two groups compared. These lattermodels were used to test for associations under bothdominant and recessive risk models. Under a domi-nant model, only one copy of the variant allele (con-tained in the AB or BB genotypes) would confer anincrease(ordecrease) in risk fordisease. Ina recessivemodel, twocopiesof thevariantallele (contained in theBB genotype only) are needed to affect risk.

RESULTS

Although we enrolled subjects from all races andethnic groups, there were too few non-whites in our

sample to make meaningfulcomparisons between casesand controls separately in eachsubgroup. The analyses, there-fore, were limited to the 219non-Hispanic whites. Table 2summarizes selected charac-teristics of the groups. Theaverage age of the cases andcontrols was similar. The per-centage of females was signifi-cantly higher in controlsversus cases (P <0.01; Fisherexact test). The smoking histo-ries of the two groups also dif-fered significantly (x2 = 39.7;P <0.001). Cases were morelikely than controls to be cur-rent or former smokers. Amongcurrent and former smokers,cases smoked more cigarettesfor longer periods than controls.As expected, cases displayedwidespread pocketing andattachment loss, whereas con-trols displayed localized attach-ment loss, mainly on facialtooth sites.

The distribution of genotypesin controls did not differ signifi-

cantly (P >0.05) from Hardy-Weinberg equilibriumproportions (data not shown). The P value for theOPN SNP was 0.05, which was not considered statis-tically significant given the number of tests run.

Figure 1 depicts the distributions of the nine SNPgenotypes by group. None of the distributions differedsignificantly between cases and controls (P >0.05).Figure 2 depicts the frequencies of the wild-typeand variant alleles for the same SNPs. Again, therewere no statistically significant differences in allelefrequencies between cases and controls (P >0.05).

In the logistic regression analyses, no unadjusted(data not shown) or adjusted (Tables 3 and 4) oddsratios were significantly different than 1.0 (P >0.05).The smallest uncorrected P value was 0.056 forOPN under the recessive model. All other P valueswere >0.1.

In the adjusted analyses, being male and having a>10 pack-year smoking history were strongly associ-atedwith disease (P <0.001).We found no statisticallysignificant smoking-by-genotype interactions, whichwere tested using a variety of categories based onpack-year histories. We also found no significant associ-ations between genotypes and disease status in subjectswith <10 pack-year smoking histories (N = 36 cases and64 controls).

Figure 2.Frequency of wild-type and variant alleles in cases (N = 137) and controls (N = 82).

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Of the nine SNPs tested, two pairs reside on thesame chromosome (CTLA-4 and ICOS on chromo-some 2 and OPG and DEFB1 on chromosome 8).We constructed two-locus haplotypes for these pairsof markers and found no evidence that any haplo-type was associated with disease. The magnitude oflinkage disequilibrium (LD) between alleles atthese markers was low, with D9 values14 ranging from0.18 to 0.32.

DISCUSSION

In any epidemiological study, it is important that thephenotype is stable and can be determined accuratelyand precisely.15 In a clinical setting, it can be difficultto distinguish aggressive from chronic periodontitis,and patients may experience periods of both aggres-

sive and chronic disease. We attempted to study onlychronic periodontitis by excluding those with bone orattachment loss localized to first molars and incisorsor who recalled periodontal problems as adolescents.However, because we evaluated subjects at a singletime point, it is possible some of our cases had expe-rienced periods of aggressive periodontitis. By relyingprimarily on clinical diagnostic criteria, we also mayhave inadvertently pooled a number of subclinical dis-ease phenotypes. Use of clinical measures alone todefine disease may not be appropriate for geneticstudies.16 Although we used rigorous a priori clinicalcriteria, we may have generated a different spectrumof disease entities had we included microbiologicaland immunological criteria as well.

Often, initial reports of positive genetic associa-tions for complex diseases are not confirmed in later,larger studies. Ioannidis et al.17 found that only 16% ofgenetic associations were subsequently replicated‘‘with formal statistical significance, without hetero-geneity or bias.’’ Although there may be genuinevariation between populations, such contradictoryevidence also may be attributed to gene locus hetero-geneity or publication bias, the latter of which tends tofavor positive rather than negative findings.18 Thus, itis important that both positive and negative findingsbe reported in the literature.

Statistical power is an important issue in anystudy reporting negative findings. Power to detectassociations varies as a function of the sample sizeand prevalence of a particular exposure. In this study,we define ‘‘exposure’’ in terms of a particular geno-type or allele. For relatively common polymorphisms(i.e., those with minor allele frequencies >20%) anddepending on the inheritance model tested, we couldreject hypotheses that most genotypes were asso-ciated with at least a two- to four-fold increase ordecrease in risk for disease because the 95% confi-dence intervals excluded them (Table 4). For lesscommon polymorphisms or genotypes (e.g., CCR5and OPG), there were too few observations for somemodels to calculate odds ratios. For the OPN (707C>T) SNP, the confidence interval for the odds ratioin the recessive model (0.08 to 1.03; Table 4) wasbroadand includedvalues largeenough tobeclinicallysignificant.

The robustness of population-based genetic-association studies may be diminished by populationstratification, which occurs when populations withinthe same sample are genetically heterogeneous(i.e., admixed). Although population stratificationcan lead to false-positive findings, the magnitude ofbias is not well understood.19 Data from unlinkedmarkers can be used to explore and correct for suchbiases.20 Because we included only non-Hispanicwhites anddid not find anassociation betweendisease

Table 3.

Gender and Smoking-Adjusted OddsRatios for the Association BetweenGenotypes* and Disease Status

Polymorphism Genotype Odds Ratio (95% CI)

CTLA-4 (49 A>G) A/G 0.99 (0.49-2.00)

G/G 0.69 (0.26-1.80)

DEFB1 (692 G>A) A/G 1.44 (0.70-2.93)

G/G 1.95 (0.76-4.99)

ICAM-1 (1548 A>G) A/G 1.05 (0.51-2.17)

G/G 1.11 (0.40-3.08)

FasL (-844 C>T) C/T 0.66 (0.32-1.35)

T/T 0.47 (0.17-1.27)

ICOS (3990 G>T) G/T 0.97 (0.47-1.99)

T/T 2.06 (0.75-5.69)

IL-6 (-174 G>C) G/C 1.10 (0.54-2.27)

C/C 1.06 (0.43-2.62)

CCR5 (59653 C>T) C/T 0.82 (0.38-1.79)

T/T †

OPG (245 T>G) T/G 2.18 (0.70-6.75)

G/G †

OPN (707 C>T) C/T 0.77 (0.39-1.52)

T/T 3.06 (0.82-11.48)

* For each SNP, wild-type homozygotes are the reference group.† Too few observations to calculate odds ratios.

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and any marker, we did not explore the substructure ofour sample population.

Recently, two groups have reported on the same in-terleukin-6 (IL-6) -174 G>C SNP. Trevilatto et al.21

found that the distribution of genotypes was signifi-cantly different between healthy controls and subjectswith moderate to severe disease. The increase in riskappeared to be attributable to the GG genotype, whichwas more prevalent in subjects with severe disease(70.8%) compared to moderately affected (50.0%)and healthy subjects (33.3%). In contrast, Hollaet al.22 found no differences between patients andcontrols in genotypes and allele frequencies for the-174 G>C SNP. However, they did find that the hetero-zygote (GC) state at a neighboring SNP (at posi-tion -572) was significantly more prevalent incases (19.6%) than controls (6.1%). The three studies(Trevilatto et al.,21 Holla et al.,22 and ours) used sub-stantially different diagnostic criteria, which may beone reason for the discrepant results. It is importantto note that controls in our study were, on average,about 10 years older than those in other studies. Weselected 45 years as the minimum age for controlsto minimize the chance of including individuals whocould develop significant periodontal disease as olderadults.

Another recent study failed to detect an associationbetween susceptibility to periodontal disease and a32-base-pairdeletion in theCCR5gene,23 which is con-sistent with our findings for the CCR5 (59653 C>T)SNP. In this study by Folwaczny et al., the frequency

of the 32-base-pair deletion was notsignificantly different between peri-odontitis patients (9.9%) and healthycontrols (10.7%).

With so many genetic variationsavailable for study, one might ques-tion our approach of selecting oneSNP per candidate gene. Genetic-association study designs are predi-cated on the assumption that allelesat nearby loci are in LD (or associ-ated) with one another. Thus, associ-ations between a target SNP anddisease may arise because the targetSNP contributes directly to risk fordisease or because it is in LD withanother nearby variation that trulyconfers susceptibility or resistance.The power of LD mapping (wherebymarker alleles are used to localizethe position of unobserved disease al-leles) is a function of the frequencyof the disease allele and the extentof LD between the marker and dis-ease alleles. Abecasis et al.24 showed

that more than half of paired markers <50 kb apart arein LD to an extent considered useful for associationstudies. However, selecting single candidate SNPswithout prior knowledge of the structure of LD withinthe regions of interest may not capture enough of thegenetic variation to detect disease associations withnearby polymorphisms. Nonetheless, strong associa-tions with nearby polymorphisms (i.e., those withinseveral thousand base pairs of our SNPs) should havebeen detectable with our selected markers, albeit to aweaker extent, although we cannot rule out the possi-bility that other SNPs in these same regions are asso-ciated with severe periodontitis.

The extent of LD throughout the human genome isnot well understood and is the focus of intensiveresearch. LD decays rapidly as a function of physi-cal distance and time (measured in generations ormeiotic events) and appears to vary both acrossgenomic regions and among populations.25 Withincertain genomic regions (which are cold spots formeiotic recombination), it is possible to define hap-lotype blocks (and thus capture genomic variationover stretches of hundreds of thousands of basepairs) using relatively few SNPs;26 that is, somelarge segments of DNA appear to be transmittedthrough generations intact or without recombination.Thus, a more efficient design in complex disease re-search is to type multiple polymorphisms (e.g.,SNPs) within a region and examine the associationbetween disease and the haplotypes constructedfrom these genotypes.27 Although the analysis of

Table 4.

95% Confidence Limits of Odds Ratios From LogisticRegressions Adjusting for Gender and Smoking

Polymorphism

Wild-Type

Allele

Dominant Inheritance

Model*

Recessive Inheritance

Model†

CTLA-4 (49 A>G) A 0.58, 2.13 0.59, 3.59

DEFB1 (692 G>A) G 0.33, 1.23 0.26, 1.48

ICAM-1 (1548 A>G) A 0.47, 1.89 0.37, 2.33

FasL (-844 C>T) C 0.83, 3.23 0.69, 4.24

ICOS (3990 G>T) G 0.44, 1.69 0.19, 1.20

IL-6 (-174 G>C) G 0.47, 1.79 0.44, 2.27

CCR5 (59653 C>T) C 0.53, 2.50 ‡

OPG (245 T>G) T 0.18, 1.59 ‡

OPN (707 C>T) C 0.55, 2.04 0.08, 1.03

* Wild-type homozygotes are the reference group.† Wild-type homozygotes and heterozygotes are the reference group.‡ Too few observations to calculate odds ratio.

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haplotype blocks is an exciting advance in geneticepidemiology, strategies for selecting SNPs withinhaplotype blocks and the methods to define suchblocks continue to evolve.27

Finally, large consortia or collaborative groups havebeen assembled to study the genetic basis of commonand complex diseases including breast cancer,28

cardiovascular disease,29 asthma,30 and diabetes.31

Given that periodontal diseases are likely to beequally complex in their etiologies, similar efforts willbe needed to conduct systematic and robust searchesfor susceptibility alleles for these diseases. Multicen-ter collaborations also may promote the use of com-mon disease definitions and provide the samplepopulations necessary to detect alleles that confer amild to moderate increase in risk for disease.

ACKNOWLEDGMENTS

This study was supported by the Ervin Schaffer Chairin Periodontal Research, University of Minnesota anda National Institutes of Health/National Institute ofDental and Craniofacial Research grant (DE09737).The authors thank Dr. Mauricio Ronderos, Universityof the Pacific School of Dentistry, for his help with sub-ject recruitment.

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37. Kouki T, Gardine CA, Yanagawa T, Degroot LJ. Rela-tion of three polymorphisms of the CTLA-4 gene inpatients with Graves’ disease. J Endocrinol Invest2002;25:208-213.

38. Maurer M, Ponath A, Kruse N, Rieckmann P. CTLA4exon 1 dimorphism is associated with primary pro-gressive multiple sclerosis. J Neuroimmunol 2002;131:213-215.

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44. Zhao C, Wang I, Lehrer RI. Widespread expression ofbeta-defensin hBD-1 in human secretory glands andepithelial cells. FEBS Lett 1996;396:319-322.

45. Kabashima H, Yoneda M, Nagata K, Hirofuji T, MaedaK. The presence of chemokine (MCP-1, MIP-1alpha,MIP-1beta, IP-10, RANTES)-positive cells and chemo-kine receptor (CCR5, CXCR3)-positive cells in inflamedhuman gingival tissues. Cytokine 2002;20:70-77.

46. Lu Q, Jin L, Darveau RP, Samaranayake LP. Expres-sion of human beta-defensins-1 and -2 peptides inunresolved chronic periodontitis. J Periodontal Res2004;39:221-227.

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48. The International HapMap Project. Available at:http://www.hapmap.org/. Accessed August 25, 2005.

49. Puppo F, Contini P, Ghio M, Indiveri F. Soluble HLAclass I molecules/CD8 ligation trigger apoptosis ofCD8+ cells by Fas/Fas-ligand interaction. Scientific-WorldJournal 2002;2:421-423.

50. Gamonal J, Bascones A, Acevedo A, Blanco E, SilvaA. Apoptosis in chronic adult periodontitis analyzed byin situ DNA breaks, electron microscopy, and immu-nohistochemistry. J Periodontol 2001;72:517-525.

51. Sawa T, Nishimura F, Ohyama H, Takahashi K,Takashiba S, Murayama Y. In vitro induction of acti-vation-induced cell death in lymphocytes from chronicperiodontal lesions by exogenous Fas ligand. InfectImmun 1999;67:1450-1454.

52. Wu J, Metz C, Xu X, et al. A novel polymorphic CAAT/enhancer-binding protein beta element in the FasLgene promoter alters Fas ligand expression: A candi-date background gene in African American systemiclupus erythematosus patients. J Immunol 2003;170:132-138.

53. Sun T, Miao X, Zhang X, Tan W, Xiong P, Lin D.Polymorphisms of death pathway genes FAS andFASL in esophageal squamous-cell carcinoma. J NatlCancer Inst 2004;96:1030-1036.

54. Bella J, Kolatkar PR, Marlor CW, Greve JM, RossmannMG. The structure of the two amino-terminal domainsof human ICAM-1 suggests how it functions as arhinovirus receptor and as an LFA-1 integrin ligand.Proc Natl Acad Sci USA 1998;95:4140-4145.

55. Mojcik CF, Shevach EM. Adhesion molecules: Arheumatologic perspective. Arthritis Rheum 1997;40:991-1004.

56. Yamada M, Nakae H, Yumoto H, Shinohara C, Ebisu S,Matsuo T. N-acetyl-D-galactosamine specific lectin ofEikenella corrodens induces intercellular adhesionmolecule-1 (ICAM-1) production by human oral epi-thelial cells. J Med Microbiol 2002;51:1080-1089.

57. Lappin DF, McGregor AM, Kinane DF. The systemicimmune response is more prominent than the mucosalimmune response in the pathogenesis of periodontaldisease. J Clin Periodontol 2003;30:778-786.

58. Rezavandi K, Palmer RM, Odell EW, Scott DA, WilsonRF. Expression of ICAM-1 and E-selectin in gingivaltissues of smokers and non-smokers with periodonti-tis. J Oral Pathol Med 2002;31:59-64.

59. Mole N, Kennel-de March A, Martin G, Miller N, BeneMC, Faure GC. High levels of soluble intercellularadhesion molecule-1 (ICAM-1) in crevicular fluid ofperiodontitis patients with plaque. J Clin Periodontol1998;25:754-758.

60. Vora DK, Rosenbloom CL, Beaudet AL, CottinghamRW. Polymorphisms and linkage analysis for ICAM-1 and the selectin gene cluster. Genomics 1994;21:473-477.

61. Iwao M, Morisaki H, Morisaki T. Single-nucleotidepolymorphism g.1548G > A (E469K) in humanICAM-1 gene affects mRNA splicing pattern andTPA-induced apoptosis. Biochem Biophys Res Com-mun 2004;317:729-735.

62. Verity DH, Vaughan RW, Kondeatis E, et al. Intercel-lular adhesion molecule-1 gene polymorphisms inBehcet’s disease. Eur J Immunogenet 2000;27:73-76.

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63. Nieters A, Brems S, Becker N. Cross-sectional studyon cytokine polymorphisms, cytokine production afterT-cell stimulation and clinical parameters in a randomsample of a German population. Hum Genet 2001;108:241-248.

64. Low JH, Williams FA, Yang X, et al. Inflammatorybowel disease is linked to 19p13 and associated withICAM-1. Inflamm Bowel Dis 2004;10:173-181.

65. Coyle AJ, Lehar S, Lloyd C, et al. The CD28-relatedmolecule ICOS is required for effective T cell-depen-dent immune responses. Immunity 2000;13:95-105.

66. Haaning Andersen AD, Lange M, Lillevang ST. Allelicvariation of the inducible costimulator (ICOS) gene:Detection of polymorphisms, analysis of the promoterregion, and extended haplotype estimation. TissueAntigens 2003;61:276-285.

67. Papanicolaou DA, Wilder RL, Manolagas SC, ChrousosGP. The pathophysiologic roles of interleukin-6 inhuman disease. Ann Intern Med 1998;128:127-137.

68. Okada H, Murakami S. Cytokine expression in peri-odontal health and disease. Crit Rev Oral Biol Med 1998;9:248-266.

69. Fishman D, Faulds G, Jeffery R, et al. The effect ofnovel polymorphisms in the interleukin-6 (IL-6) geneon IL-6 transcription and plasma IL-6 levels, and anassociation with systemic-onset juvenile chronic ar-thritis. J Clin Invest 1998;102:1369-1376.

70. D’Aiuto F, Parkar M, Brett PM, Ready D, Tonetti MS.Gene polymorphisms in pro-inflammatory cytokinesare associated with systemic inflammation in patientswith severe periodontal infections. Cytokine 2004;28:29-34.

71. Veres A, Prohaszka Z, Kilpinen S, Singh M, Fust G,Hurme M. The promoter polymorphism of the IL-6 geneis associated with levels of antibodies to 60-kDa heat-shock proteins. Immunogenetics 2002;53:851-856.

72. Oppermann M. Chemokine receptor CCR5: Insightsinto structure, function, and regulation. Cell Signal2004;16:1201-1210.

73. Gamonal J, Acevedo A, Bascones A, Jorge O, Silva A.Characterization of cellular infiltrate, detection ofchemokine receptor CCR5 and interleukin-8 andRANTES chemokines in adult periodontitis. J Peri-odontal Res 2001;36:194-203.

74. Wang CR, Liu MF. Regulation of CCR5 expression andMIP-1alpha production in CD4+ T cells from patientswith rheumatoid arthritis. Clin Exp Immunol 2003;132:371-378.

75. Lewandowska M, Trzeciak WH, Jagodzinski PP. De-termination of the CCR2-64I/CCR5-59653T haplotypelinkage disequilibrium in a sample of Polish popula-tion. Genetika 2003;39:831-833.

76. Theoleyre S, Wittrant Y, Tat SK, Fortun Y, Redini F,Heymann D. The molecular triad OPG/RANK/RANKL:Involvement in the orchestration of pathophysiologicalbone remodeling. Cytokine Growth Factor Rev 2004;15:457-475.

77. Kong YY, Yoshida H, Sarosi I, et al. OPGL is a keyregulator of osteoclastogenesis, lymphocyte develop-ment and lymph-node organogenesis. Nature 1999;397:315-323.

78. Hasegawa T, Yoshimura Y, Kikuiri T, et al. Expressionof receptor activator of NF-kappa B ligand and osteo-protegerin in culture of human periodontal ligamentcells. J Periodontal Res 2002;37:405-411.

79. Crotti T, Smith MD, Hirsch R, et al. Receptor activatorNF kappaB ligand (RANKL) and osteoprotegerin

(OPG) protein expression in periodontitis. J Periodon-tal Res 2003;38:380-387.

80. Mogi M, Otogoto J, Ota N, Togari A. Differentialexpression of RANKL and osteoprotegerin in gingivalcrevicular fluid of patients with periodontitis. J DentRes 2004;83:166-169.

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Correspondence: Dr. Bryan Michalowicz, School ofDentistry, University of Minnesota, 17-116 Moos Tower,515 Delaware St. SE, Minneapolis, MN 55455. E-mail:micha002@umn.edu.

Accepted for publication August 30, 2005.

APPENDIX

CTLA-4 (CD152)CTLA-4 is a member of the immunoglobulin super-family and functions as a negative regulator of T-cellactivity. CD28 stimulates and CTLA-4 inhibits T-cellactivation,32 and the interaction between these twomolecules may regulate peripheral self-tolerance.33

CTLA-4 expression is upregulated on T cells fromperiodontitis patients following stimulation with Por-phyromonas gingivalis.34 CTLA-4 has also beenshown to inhibit T-cell – mediated bone resorption inrodents.35 Following stimulation with Actinobacillusactinomycetemcomitans, CTLA-4 inhibited the B7costimulatory signal in T-helper (Th) cells, whichotherwise triggers inflammatory osteoclastic boneresorption.

A substitution at position +49 (A>G) results in athreonine to alanine amino acid substitution. Whenstimulated with immature dendritic cells, T cells fromG/G homozygotes proliferate more than cells fromwild-type homozygotes.36 This SNP has been associ-ated with Graves’ disease,37 multiple sclerosis,38

rheumatoid arthritis,39 and type I diabetes.40

DEFB1Defensins are 3.5 to 5-kDa cysteine- and arginine-rich, positively charged antimicrobial peptides found

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in macrophages, neutrophils, and epithelia.41

b-defensins kill bacteria by disrupting the cell mem-brane. Twenty-eight human b-defensins have beenidentified.42

Human b-defensins (hBD-1, -2, -3, and -4) are ex-pressed in oral tissues and are involved in epithelialand mucosal defense.43,44 hBD-1 is found in humangingival epithelial cells but not fibroblasts.45 hBD-1 expression is upregulated in periodontitis diseasesites compared to healthy sites in the same sub-jects.46

The variant (G) allele of a SNP at position 668 inDEFB1 appears to confer protection against Candidaalbicans in humans.42 We chose to study a nearbyG>A SNP at position 692 in the 59 untranslated region(rs11362), which forms an important nuclear factor-kappa B (NF-kB) transcription-binding site.47 We didnot determine the functional significance of rs11362nor estimate the extent of LD between it and the func-tional SNP. Nonetheless, seven SNPs within 5,500base pairs upstream and 4,600 base pairs down-stream of rs11362 are in complete LD (= 1) withit,48 suggesting that recombinations within this nar-row stretch of DNA are rare. Thus, it is highly likelythat the functional SNP and rs11362, which are sep-arated only by 24 base pairs, are in complete LD withone another.

FasL (CD95)Tissue turnover is achieved through a process calledprogrammed cell death, or apoptosis. FasL appears tobe involved in the induction of T-cell apoptosis, andfas/fasL interactions may play an important role inmaintaining immune tolerance and preventing auto-immune diseases.49 Fas, fasL, and p53 are foundin inflammatory infiltrates in periodontitis but nothealthy tissues.50 FasL can trigger apoptotic celldeath of lymphocytes isolated from periodontitislesions.51

Wu et al.52 identified a C>T SNP at position -844 inthe promoter region of fasL. Basal expression of fasLon peripheral blood cells was significantly higher in-844C than in -844T homozygotes. The authors the-orized that the -844C homozygous genotype maylead to the increased expression of fasL and to alteredfasL-mediated signaling in lymphocytes. The CCgenotype has been associated with systemic lupuserythematosus in African Americans52 and esophagealsquamous cell carcinoma in Chinese individuals.53

ICAM-1 (CD54)ICAM-1 is a member of the superfamily of im-munoglobulin adhesion molecules and functions asa ligand for lymphocyte function-associated antigens(LFA).54 LFA-1 (an integrin also known as CD11a)and ICAM-1 interact as accessory molecules betweenthe T-cell receptor (TCR) and the major histocompat-

ibility complex (MHC). The LFA-1/ICAM-1 com-plex amplifies the bond between TCR and MHC andthus improves antigen presentation and processing.ICAM-1 also plays a role in both recruitment andactivation of leukocytes.55

ICAM-1 expression increases in human gingivalepithelial cells following in vitro stimulation with oralpathogens.56 ICAM-1 expression is upregulated inperiodontitis sites compared to gingivitis sites57 andhealthy sites.58 Levels in gingival crevicular fluid(GCF) have been positively correlated with clinicalmeasures of gingival inflammation.59

Vora et al.60 identified a common A>G poly-morphism in codon 469 of exon 6. The site substitu-tion may modify inflammatory immune responses bychanging cell-cell interactions and then regulating ap-optosis.61 This 1548 G>A SNP has been associatedwith Behcet’s disease in subjects of Middle-Easterndescent,62 resistance to common colds,63 and inflam-matory bowel disease.64

ICOSICOS is a member of the CD28 family of costimulatoryT-cell surface receptors,65 which are necessary for in-ducing T-cell responses. ICOS is the counterpart ofCTLA-4, which through binding to the CD28 ligands(B7-1/B7-2) terminates the T-cell response. Througha complex chain of reactions, ICOS enhances secre-tion of IL-4, IL-5, IL-10, and interferon (IFN)-g fromTh2 cells. The B7 costimulatory pathway is essentialfor Th1-mediated alveolar bone resorption in rats.35

There are at least 16 polymorphisms within theICOS gene.66 The 3990 G>T SNP is in linkage disequi-librium with a 3396 G>T SNP, the latter of which islocated within a putative site for transcriptional regu-lation.66 ICOS, CD28, and CTLA-4, all of which areencoded at 2q33, have been linked to a number ofautoimmune diseases such as type 1 diabetes, sys-temic lupus erythematosus, celiac disease, and mul-tiple sclerosis.66

IL-6IL-6 is a pleiotropic molecule that affects both hu-moral and cellular immune pathways involved in hostdefense and tissue injury.67 Secreted by monocytes,macrophages, T-helper cells, and bone-marrow stro-mal cells, its major biologic functions are to promoteterminal differentiation of B cells into plasma cells,stimulate antibody secretion, and promote the syn-thesis of acute-phase proteins in the liver. The roleof IL-6 in the pathogenesis of periodontal diseasehas been well studied.68

Fishman et al.69 identified a C>G polymorphism atposition -174, which has been associated with IL-6levels in tissue69 and serum,70 levels of antibodies to60-kDa heat-shock proteins,71 and systemic juvenilerheumatoid arthritis and resistance tocommon colds.63

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CCR5CCR5 is a G protein-coupled receptor (GPCR) thatregulates trafficking and effector functions of mem-ory/effector T lymphocytes, macrophages, and im-mature dendritic cells.72 CCR5 recognizes macrophageinflammatory protein (MIP)-1a, regulated on activa-tion, normal T-cell expressed and secreted (RANTES),and MIP-1b as antagonists. CCR5 is expressed in in-flamed tissue from patients with periodontitis, butnot healthy controls.45 Among subjects with peri-odontitis, Gamonal et al.73 detected CCR5 in gingivaltissues prior to but not following periodontal therapy.

Wang and Liu74 found an association between rheu-matoid arthritis and the TT genotype of the 59653 C>TSNP in Chinese subjects. The 59653 SNP is in strong,but not absolute, LD with the CCR2-64I allele.75

OPGOsteoclastogenesis and osteoclast activation are reg-ulated by a cytokine system consisting of the receptoractivator of NF-kB ligand (RANKL), its cellular recep-tor (RANK), and the decoy receptor OPG. OPG servesas a decoy receptor for RANKL and thus inhibitsosteoclastogenesis.76 RANKL gene knockout micesuffer from severe osteopetrosis, defective tooth erup-tion, and defects in T- and B-cell differentiation.77

Thus, the RANK/RANKL/OPG pathway seems to af-fect T- and B-immune cell differentiation as well.

Hasegawa et al.78 demonstrated that human peri-odontal ligament (PDL) cells can synthesize OPG.Crotti et al.79 found that OPG mRNA expression wassignificantly lower in diseased versus healthy peri-odontal tissues. Mogi et al. found the same relation-ship for OPG levels in GCF.80

Landahl et al.81 identified 12 polymorphisms in theOPG gene region. The G allele of the 245 T>G poly-morphism was associated with decreased bone massdensity and increased fracture risk in osteoporotic pa-tients. The 245 T>G SNP is in linkage disequilibriumwith a number of neighboring polymorphisms (163A>G, 950 T>C, 1181 G>C, and 6890 A>C).

OPNOPN is a bone matrix phosphorylated glycoprotein.Secreted by a variety of cells including macrophages,osteoblasts, and osteoclasts, it binds to hydroxyapa-tite and helps anchor osteoclasts to the bone matrixmineral.82 OPN may function as a migratory mediatorfor macrophages83 and stimulate pro-Th1 cells.84

OPN levels are significantly elevated in the GCF ofperiodontitis versus healthy tooth sites.85

Fortonetal.86 foundanassociationbetweenthe707C>T polymorphism and systemic lupus erythemato-sus (SLE) in whites. The variant (T) allele also wasassociated with opportunistic infections, renal insuffi-ciency,andapossible resistance toavascularnecrosisin SLE patients.

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