A 3′ UTR transition within DEFB1 is associated with chronic and aggressive periodontitis

Article metrics

Abstract

Periodontal diseases are complex inflammatory diseases and affect up to 20% of the worldwide population. An unbalanced reaction of the immune system toward microbial pathogens is considered as the key factor in the development of periodontitis. Defensins have a strong antimicrobial function and are important contributors of the immune system toward maintaining health. Here, we present the first systematic association study of DEFB1. Using a haplotype-tagging single nucleotide polymorphism (SNP) approach, including described promoter SNPs of DEFB1, we investigated the associations of the selected variants in a large population (N=1337 cases and 2887 ethnically matched controls). The 3′ untranslated region SNP, rs1047031, showed the most significant association signal for homozygous carriers of the rare A allele (P=0.002) with an increased genetic risk of 1.3 (95% confidence interval: 1.11–1.57). The association was consistent with the specific periodontitis forms: chronic periodontitis (odds ratio=2.2 (95% confidence interval: 1.16–4.35), P=0.02), and aggressive periodontitis (odds ratio=1.3 (95% confidence interval 1.04–1.68), P=0.02). Sequencing of regulatory and exonic regions of DEFB1 identified no other associated variant, pointing toward rs1047031 as likely being the causative variant. Prediction of microRNA targets identified a potential microRNA-binding site at the position of rs1047031.

Introduction

Parodontopathies are highly prevalent1 and, according to the WHO, affect human populations worldwide at prevalence rates of up to 20%.2 They are caused by an unbalanced immune reaction toward environmental and behavioral effects. A pathogenic microflora is the causative agent for the development of parodontopathies, but a poor oral hygiene and most importantly, smoking3 also contribute strongly to the disease risk. Periodontitis is a complex chronic inflammatory disease of the periodontium, which results in a loss of connective tissue and bone support of the teeth and has been shown in epidemiological studies to have a co-morbidity with coronary heart disease and diabetes.4 Chronic periodontitis (CP) is one of the most common forms of parodontopathies and the major cause of tooth loss in adults above 40 years. Advanced forms are characterized by inflammation that extends deep into the tissues of the periodontium, a process that eventually causes the loss of the supporting connective tissue and the alveolar bone. Aggressive periodontitis (AgP) is the most severe form of parodontopathies, characterized by a rapid progression with a particularly early age of onset (generally <35 years).

Defensins are proteins secreted by the immune system, which help to maintain the balance between healthy state and disease condition in the complex environment of the mouth,5 and have broad-spectrum antimicrobial activity against bacteria, fungi and some viruses.6 The human β-defensin genes (DEFB) are clustered on chromosome 8p23.1 and show considerable variations in copy number except for DEFB1, which has only two copies per diploid genome.7 This makes DEFB1 accessible to straightforward association analysis of potential genetic susceptibility variants. Consistent with all human epithelial tissues tested to date, including intestinal mucosa,8 the urogenital tract,9 and airway epithelia,10 DEFB1 is constitutively expressed in the gingival epithelial tissues.11 It is inducible only by commensal bacteria and not, unlike hBD-2 and DEFB103, by pathogenic bacteria.12 Therefore, DEFB1 has been suggested to be responsible for maintaining a healthy status in mucosal epithelials before infection with pathogenic bacteria, and can thus be considered to function as a guardian in the maintenance of mucosal and oral health.

Accordingly, associations of specific single nucleotide polymorphisms (SNPs) of DEFB1 with inflammatory and allergic diseases of host–environment interfaces, such as mucosal surfaces of intestines (Crohn’s disease),13 respiratory tracts (asthma)14 and the skin (atopic dermatitis)15 have been, sometimes ambiguously, described. It is well accepted that genetic factors also have a major function in the increased susceptibility to periodontitis,16, 17 although the inherited risk variants have largely remained unexplained,16, 17, 18 which seems to be largely due to the fact that most studies were under-powered for proper interpretation.

To analyze the role of antimicrobial peptides in periodontal diseases, we explore the potential associations of nine DEFB1 haplotype-tagging SNPs and its common promoter SNPs rs11362, rs1800972 and rs1799946 in a large clinical analysis population. We give evidence for the relevance of the variant rs1047031 in periodontal disease development in independent populations of specific parodontopathic disease forms CP and AgP. This finding supports the hypothesis that DEFB1 is a crucial gene in the pathophysiology of periodontitis, and may prompt the reconsideration of evidence related to DEFB1 in disease susceptibility observed in previous association studies of other complex inflammatory diseases of the interfaces.

Results

In an explorative study, we genotyped 1337 periodontitis cases and 2887 ethnically matched controls (Table 1). We selected nine haplotype-tagging SNPs of DEFB1 covering two exons and the intervening intron of the 463-bp long mRNA encoding gene, including potentially upstream and downstream regulatory sequences (Figure 1). In addition, we analyzed associations of the 5′ UTR SNP G–20A (rs11362), C–44G (rs1800972) and G–52A (rs1799946), two of which have been earlier subjected to candidate gene association studies in patients with severe CP and early onset periodontitis (see Table 2).19, 20 Before adjustment for covariates: smoking, diabetes and the potential confounder gender using logistic regression analysis, five haplotype-tagging SNPs (rs1047031, rs2293958, rs2980930, rs5743401 and rs5743402) and the promoter SNP rs1800972 gave evidence for association with periodontitis (Supplementary Table S1). We next adjusted for covariates: smoking, diabetes and gender using logistic regression analysis. Subsequently, we corrected for multiple testing using conservative Bonferroni thresholds that corresponded to an uncorrected significance level of α=0.05. After covariate adjustment and correction for multiple testing, the haplotype-tagging SNPs rs1047031, rs2293958, rs2980930 and rs5743401 remained significant. SNP rs1800972 marginally missed significance after correction for multiple testing (Table 2). The highest difference in allele frequencies between cases and controls was seen for SNP rs1047031 with an allele frequency of 17.1% in controls and 20.5% in cases (Table 3).

Table 1 Characteristics of the study population
Figure 1
figure1

Genetic region of DEFB1. The top diagram shows the nominal −log10(P) under the assumption of a recessive genetic model, plotted as a function of the genomic single-nucleotide polymorphism (SNP) position (NCBI build 36). The bottom panel shows pairwise linkage disequilibrium (LD) in controls using metric r2. The haplotype-tagging SNPs (htSNPs) of the initial association analysis are indicated by numbers (1–9), the promoter SNPs of the follow-up analysis are depicted by their classical identification (rs identifiers are given in the text and tables).

Table 2 Association statistics for the haplotype-tagging SNPs and the promoter SNPs in periodontitis cases and controls
Table 3 Genotype counts and frequencies for the haplotype-tagging SNPs and the promoter SNPs in periodontitis cases and controls

To test whether the observed associations were present in sub-forms CP and AgP independently, we investigated the allele frequencies for the associated variants in 805 CP cases and 1153 controls, and in 532 AgP cases and 1472 further controls, separately. The 3′ UTR variant rs1047031 and the intronic SNP rs2293958 gave evidence for an association in CP as well as in AgP before covariate adjustment (Supplementary Table S1). On adjustment for smoking, diabetes and gender, only one SNP, rs1047031, remained significantly associated in both populations (Table 4). For this variant, the effect of the rare A allele was highly similar to that seen in the unadjusted analysis, and it increased the genetic risk the homozygous carriers with an odds ratio (OR) of 2.2 (95% confidence interval (CI): 1.2–4.3, P=0.021) for the CP population and of 1.3 (95% CI: 1.0–1.7) for the AgP population (Table 4). The rare allele for rs1047031 had a frequency of 20.0% in CP cases and 16.7% in CP controls. In the second case–control panel of the more severely affected AgP patients, the minor allele frequency was 21.2% compared with 17.5% in controls (Table 5). For 84 AgP patients, the diabetes status was unknown (Table 1). To exclude a systematic bias in the pattern of missing values with a potentially confounding effect, we estimated minor allele frequencies for the significant SNPs in patients of unknown diabetes status (N=84), and compared them with the AgP case population known to be free of diabetes (N=442). There were only small differences between the two groups, with a minor allele frequency of 21.2% for SNP rs1047031 in diabetes-free AgP patients, and a minor allele frequency of 20.0 % in AgP patients with unknown diabetes status.

Table 4 Association statistics of the significant haplotype-tagging SNPs in sub-phenotypes: chronic and aggressive periodontitis
Table 5 Genotype counts and frequencies for the significant haplotype-tagging SNPs and the promoter SNPs in sub-phenotypes: chronic and aggressive periodontitis

To choose the genetic model that could best explain the underlying association, we used Akaike's Information Criterion for describing the model fit in the logistic regression analysis. Akaike's Information Criterion is an established statistical criterion, which is known to be robust in identifying a sparse statistical model that nevertheless fits the data well. In our analysis, autosomal recessive and multiplicative genetic risk models showed the best model fit and suggested a mode of inheritance that is likely to be in-between the two models (Supplementary Table S2).

In earlier studies, the promoter SNPs: G–20A (rs11362)20 and C–44G (rs1800972)19 were subjected to candidate gene association studies in patients with severe CP and early onset periodontitis. In these studies, no association with periodontitis was observed. In our analysis, we observed an association of rs1800972 marginally missing the significance threshold (P=0.051 after correction for multiple testing; Table 2). Thus, we analyzed associations of rs11362, rs1800972 and of the adjacent SNP G–52A (rs1799946) in CP and AgP separately, although they were not significantly associated in the combined population. This analysis showed that SNP rs1800972 had only a very marginally lower allele frequency (22.5%) in the less severely affected CP cases than in the two control panels (23.6% and 23.0%). Instead, this borderline association was driven by the low frequency of the rare G allele in AgP cases (19.3%; Table 5). Accordingly, in the AgP panel, SNPs rs1800972 and rs1799946 showed a statistically significant evidence for association with AgP before and after adjustment (for association statistics before adjustment for covariates, see Supplementary Table S3). For rs1800972, this was Pmultiplicative=0.0017 with an OR of 0.7 (95% CI: 0.6–0.9), and for rs1799946 this was Precessive=0.0121 and Pmultiplicative=0.0075 with an OR of 1.5 (95% CI: 1.1–2.2) and 1.3 (95% CI: 1.1–1.5), respectively (Table 6).

Table 6 Association statistics of promoter SNPs in sub-phenotypes: chronic and aggressive periodontitis

In search of additional disease-associated mutations in the DEFB1 gene, we resequenced the two exons, splice sites and the promoter region in the genomic DNA of 47 individuals with AgP. No other associated SNP was identified at the nominal 0.05 significance level.

Subsequently, we performed a haplotype analysis using the four SNPs that remained significant in the pooled periodontitis population after Bonferroni correction for multiple testing. Of these, five haplotypes could be inferred, four of which had a frequency 2%. For two haplotypes, the frequency distribution showed a significant difference between cases and controls after 100 000 permutations. In particular, the CATT haplotype composed of rs2980930-C, rs1047031-A, rs2293958-T and rs5743401-T alleles was 3.4% more frequent in cases (P=0.0012), and the reciprocal GGAC haplotype was 2.6% more frequent in controls (P=0.037). The best single SNP association of the rs1047031-A allele had a nominal P-value (P=0.0012), which was identical to the CATT haplotype, indicating that this SNP explained most of the association within this region.

To identify a possible causal effect of the G → A nucleotide transition of SNP rs1047031, we analyzed the secondary structure of the mRNA (Vienna RNA Package 1.7.2.; http://rna.tbi.univie.ac.at/). The exchange had no effect on the mRNA folding and only marginally lowered the minimum free energy of the optimal secondary structure from −139.92 to −140.82 kcal mol−1. A prediction for microRNA targets (microRNA resource; http://www.microrna.org) identified a potential binding site of hsa-miR-1237 at the position of SNP rs1047031 with 80% homology (Figure 2). The nucleotide exchange resides within a potential 3′ binding site of the microRNA hsa-miR-1237 (MI0006327) and introduces a mismatch at the 2nd position.

Figure 2
figure2

Alignment of miRNA hsa-miR-1237 with the genomic sequence of DEFB1. The G/A transition of rs1047031+5 bp of the STOP codon of DEFB1 is marked by an arrow.

Discussion

These data provide evidence for a significant association of the rare A allele of the DEFB1 3′ variant rs1047031 with an increased risk for periodontal diseases. This association was independent of the periodontitis-specific covariates: smoking, diabetes and gender. The robustness of these data was further supported by a separate analysis of the two parodontopathic distinct forms: CP and AgP. Both independent case populations differed only marginally in terms of allele frequencies and contributed in a similar manner to the observed overall significant association signal of rs1047031. The enrichment of the rare A allele in CP (20.0%) and AgP (21.2%) cases is also seen when compared with the HapMap CEU reference population (15.0%).

The mode of inheritance that best explains the underlying association is likely to be in-between the autosomal recessive and multiplicative model. This, and the observed magnitude of effects (OR: 1.3; 95% CI: 1.1–1.6) fall within the range of other common variant effects which influence complex diseases that were observed in much larger populations, for example like those with coronary artery disease (6.2%, OR: 1.3; meta-analysis with six studies for the strongest coronary artery disease-associated SNP rs1333049, based on 9400 individuals);21 diabetes (2.6%, OR: 1.1; rs864745 that gave the strongest statistically significant evidence for an association with type 2 diabetes in a meta-analysis based on 68 000 individuals);22, 23 and inflammatory bowel disease (4%, OR: 1.3; mean values of allele frequencies and OR values of 13 previously reported SNP associations that were verified in a recent replication study on Crohn's disease based on 3800 individuals).23

Earlier studies on periodontitis investigated associations of SNP G–20A (rs11362)20 and C–44G (rs1800972)19 with patients with severe CP and those with early onset periodontitis (currently most likely classified as AgP), respectively. These studies were of much smaller sample size than this study and observed no disease association. In our analysis of the pooled population, we observed an association marginally missing the significance threshold for rs1800972. A separate analysis of the two distinct sub-phenotypes, CP and AgP, showed that this borderline association was primarily driven by the low frequency of the rare G allele in AgP cases (19.3%) in contrast to CP cases (22.5%) when compared with the two control panels (23.6 and 23.0%). Interestingly, another study proposed a protective effect of the rare rs1800972 allele on the carriage of Candida species.24 Considering that individuals who experienced early development of periodontitis are likely to have inherited a major genetic disease variant, it is conceivable that larger CP populations may also show a positive association with this promoter variant. To clarify this, further replication experiments in larger populations of AgP and CP would be desirable.

The three promoter variants have further been subject to several other association studies on different diseases. In the past, these promoter SNPs were analyzed in association studies on Crohn's disease (positive association with rs11362 and rs180097213), airway colonization in cystic fibrosis (positive association of rs11362 and rs1799946),25 HIV infection (associations of rs1799946,26 rs1136227 and rs180097228) and chronic obstructive pulmonary disease (no association).29 However, these studies were characterized by small sample sizes and studies did not replicate the observed associations, except for associations with HIV, which were identified in different, albeit small populations of mixed ethnicity. The promoter sequence is a region of low linkage disequilibrium because of high recombination rates (r2<0.41), which could explain the varying allele frequencies and genetic effects for the same SNPs described in the cited studies.

The question arises as to how would the rs1047031 variant impair the normal function of DEFB1 in the maintenance of the epithelial barrier. SNP rs1047031 is located 5 bp inside the 3′ UTR. Sequencing of the complete translated sequence including the 5′ and 3′ UTRs has identified no further significantly associated polymorphisms. Thus, it could be speculated that SNP rs1047031 itself may have a potential functional effect on the increased susceptibility to periodontal diseases. The 3′ UTRs of human protein-coding genes are rich in microRNA (miRNA) target sites. It has been proposed that the miRNA regulation may be affected by polymorphisms in 3′ UTRs.30 miRNA target prediction of 3′ UTR variants of DEFB1 indicated that the G → A nucleotide transition could influence the putative 3′ binding site of the miRNA hsa-miR-1237. Although there is still a debate on the actual role of DEFB1 and the potential inducibility of DEFB1 by microbial pathogens, it is likely that some DEFB1 regulatory mechanisms exist to aid the maintenance of healthy status in the mucosal epithelials. In this regard, although speculative, the disease-associated variant could interfere with a potentially specific miRNA-mediated posttranscriptional regulatory mechanism, and might affect the binding efficiency of this or another yet unknown miRNA. It is also possible that we missed the true or an additional causal variant located within the large intron or within intergenic sequences distal or proximal to DEFB1, which was neither sequenced nor covered by a tagging SNP. Here, in addition to the replication of our finding in another large independent analysis of AgP and CP populations, further comprehensive studies are required. Furthermore, functional studies to verify a potential genotype-specific effect on miRNA binding are necessary to demonstrate a potential causal effect of this variant.

In conclusion, to the best of our knowledge, this study reports for the first time an association of a 3′ UTR variant of DEFB1 in large independent populations of the two specific sub-forms CP and AgP.

Patients and methods

Subjects

Patient and control samples for the CP and AgP association studies were recruited across Germany and the Netherlands (Table 1). All radiographs were analyzed by one calibrated dental examiner, who had been extensively trained by an experienced periodontist. Only individuals of German and Dutch ethnicity were included, judged on the basis of the location of both parental birthplaces. The genetic sub-structure of the German population has been assessed in a previous study,31 indicating only negligible sub-structures and therefore allowing a joint analysis of all German individuals. Written informed consents were obtained from all subjects recruited into this study. The study was approved by the ethical review board of each participating institute (Medical Ethical Committee, Universities of Bonn, Dresden, Kiel and Munich, Germany, and Medical Ethical Committee, Academic Medical Center, University of Amsterdam, The Netherlands). The diagnosis of CP or AgP was made according to the criteria established at the 1999 international classification workshop.32 In addition, the following inclusion criteria were used: Northern German CP patients were required to be older than 40 years at the time of diagnosis. Probing pocket depth, attachment level and furcation involvement were measured and bleeding upon probing was registered. The dimension of bone loss was assessed by means of dental radiographs and/or orthopantomographs. The percentage of bone loss was measured for each tooth based on the length of the roots. Patients presenting probing depths 5 mm with more than 30% bone loss for, at least, three teeth were included in the study.

Southern German CP patients were diagnosed based on a standardized clinical examination protocol, including the evaluation of (1) the probing pocket depth measured at six locations on each tooth (mesio-buccal, mid-buccal, disto-buccal, mesio-lingual, mid-lingual and disto-lingual) using a Michigan type ‘O’ probe, (2) the involvement of furcation using a Naber-type probe, (3) bleeding on probing; registered as present or absent, and (4) bone loss as assessed by orthopantomographs. The probing pocket depth was determined from the free gingival margin to the base of the periodontal pocket keeping the probe in line with the long axis of the tooth. The furcation defects were examined by horizontal probing from the furcation entrance to the base of the defect. The furcation involvement was classified according to the protocol of Hamp et al.33 All patients included in this periodontitis group met the following clinical criteria: (1) a total of at least 15 teeth in situ, (2) 8 teeth with a probing pocket depth of 5 mm, at least, at one location and/or a furcation involvement class II and (3) radiographic evidence of bone loss. The Dutch CP patient cohort is a collection of three study groups as previously described.34, 35, 36

Inclusion criteria for the German and Dutch AgP patients were age at diagnosis 35 years and 2 teeth with 50% periodontal bone loss. A set of full-mouth dental radiographs or panorex was available for confirmative periodontal bone scoring. A total of 368 German (133 males, 224 females and 11 of unknown gender) and 164 Dutch AgP patients (44 males and 120 females) were included in the study. All aspects of the medical history, health status and smoking habits (current or former smoker, non-smoker or smoking status unknown) were recorded through a questionnaire.

For the CP association study, ethnically matched controls were obtained from either the Blood Service of the University Hospital Schleswig-Holstein, the Blood Service of the Bavarian Red Cross (Munich) and the Bloodbank (Sanquin, Amsterdam, The Netherlands). Absence of periodontal disease was proven in German CP control subjects using the following criteria: (1) a minimum of 22 teeth in situ, (2) 1 site with probing pocket depth 3 mm and (3) lack of any kind of furcation involvement at any tooth. Dutch CP control subjects were allowed to have one missing tooth per quadrant (third molar excluded), and showed, in 1-year-old dental bitewing radiographs, a distance between the cemento-enamel junction and alveolar bone crest of 3 mm for all teeth. Additional ethnically matched control panels were used for the AgP association study. German AgP controls (1104) were randomly selected from the population registry of Schleswig-Holstein, Germany (N=736) or recruited by the Blood Service of the University Hospital Schleswig-Holstein (N=368). All German AgP controls underwent an additional physical examination at the popgen37 facilities to obtain information regarding the general health status. Information regarding the oral health status and physical risk factors (for example, smoking, diabetes) was obtained from a questionnaire that was answered during medical consultation. In addition, a clinical check-up was also carried out. Dutch AgP controls were recruited by ACTA via the Bloodbank (Sanquin, Amsterdam, The Netherlands (N=368)). These healthy blood donors self-reported as being free of any periodontal diseases and gave information regarding their smoking habits. No further clinical check-up was carried out.

Genotyping and sequencing

Genomic DNA was extracted from blood (Invisorb Blood Universal Kit, Invitek, Berlin, Germany) and mouthwash samples,38 and amplified by whole genome amplification (GenomiPhi, Amersham, Uppsala, Sweden). Genotyping was carried out using the SNPlex and TaqMan Genotyping System (Applied Biosystems, Foster City, CA, USA) on an automated platform, using TECAN Freedom EVO and 96-well and 384-well TEMO liquid handling robots (TECAN, Männedorf, Switzerland). Genotypes were generated by automatic calling using the Genemapper 4.0 software (Applied Biosystems) with following settings: sigma separation >6, angle separation for two cluster SNPs <1.2 rad, median cluster intensity >2.2 logs. Genotypes were further reviewed manually and call rates >95% in each sample set were required.

Sequencing of genomic DNA was carried out using Applied Biosystems BigDye chemistry according to the supplier's recommendations (for primer sequences see Supplementary Table S4). Traces were inspected for the presence of SNPs and InDels using novoSNP.39

Haplotype analysis

Haplotype estimation was carried out using an EM algorithm.40 Haplotype significance was assessed through 100 000 permutations as implemented in Haploview 4.0.41

RNA secondary structure analysis

RNA secondary structure prediction was carried out using the Vienna RNA Package 1.7.2. on the web interface for online RNA folding on the Vienna RNA WebServers.42 The target mRNA prediction was carried out using ‘The microRNA.org’ resource.43

Statistical analysis

Markers were tested for deviations from Hardy–Weinberg equilibrium in controls before inclusion in the analyses (http://ihg2.helmholtz-muenchen.de/cgi-bin/hw/hwa2.pl, α=0.05). Single-marker, case–control analysis was carried out using PLINK v2.049.44 Linkage disequilibrium measures were plotted using the GOLD (graphical overview of linkage disequilibrium) program.45 We assessed the significance of associations with or between single-locus genotypes using χ2 and Fisher's exact tests for 2 × 2 and 2 × 3 contingency tables, where applicable. Logistic regression analysis was carried out in the R statistical environment, version 2.7.2 (http://www.r-project.org). Significance was assessed using Wald and likelihood-ratio tests. P-values <0.05 were considered nominally significant.

Conflict of interest

The authors declare no conflict of interest.

References

  1. 1

    Pihlstrom BL, Michalowicz BS, Johnson NW . Periodontal diseases. Lancet 2005; 366: 1809–1820.

  2. 2

    Petersen PE . The World Oral Health Report 2003: continuous improvement of oral health in the 21st century—the approach of the WHO Global Oral Health Programme. Community Dent Oral Epidemiol 2003; 31 (Suppl 1): 3–23.

  3. 3

    Bergstrom J . Influence of tobacco smoking on periodontal bone height. Long-term observations and a hypothesis. J Clin Periodontol 2004; 31: 260–266.

  4. 4

    Emrich LJ, Shlossman M, Genco RJ . Periodontal disease in non-insulin-dependent diabetes mellitus. J Periodontol 1991; 62: 123–131.

  5. 5

    Dale BA, Fredericks LP . Antimicrobial peptides in the oral environment: expression and function in health and disease. Curr Issues Mol Biol 2005; 7: 119–133.

  6. 6

    Huttner KM, Bevins CL . Antimicrobial peptides as mediators of epithelial host defense. Pediatr Res 1999; 45: 785–794.

  7. 7

    Groth M, Szafranski K, Taudien S, Huse K, Mueller O, Rosenstiel P et al. High-resolution mapping of the 8p23.1 beta-defensin cluster reveals strictly concordant copy number variation of all genes. Hum Mutat 2008; 29: 1247–1254.

  8. 8

    O’Neil DA, Porter EM, Elewaut D, Anderson GM, Eckmann L, Ganz T et al. Expression and regulation of the human beta-defensins hBD-1 and hBD-2 in intestinal epithelium. J Immunol 1999; 163: 6718–6724.

  9. 9

    Valore EV, Park CH, Quayle AJ, Wiles KR, McCray Jr PB, Ganz T . Human beta-defensin-1: an antimicrobial peptide of urogenital tissues. J Clin Invest 1998; 101: 1633–1642.

  10. 10

    Singh PK, Jia HP, Wiles K, Hesselberth J, Liu L, Conway BA et al. Production of beta-defensins by human airway epithelia. Proc Natl Acad Sci USA 1998; 95: 14961–14966.

  11. 11

    Dommisch H, Acil Y, Dunsche A, Winter J, Jepsen S . Differential gene expression of human beta-defensins (hBD-1, -2, -3) in inflammatory gingival diseases. Oral Microbiol Immunol 2005; 20: 186–190.

  12. 12

    Vankeerberghen A, Nuytten H, Dierickx K, Quirynen M, Cassiman JJ, Cuppens H . Differential induction of human beta-defensin expression by periodontal commensals and pathogens in periodontal pocket epithelial cells. J Periodontol 2005; 76: 1293–1303.

  13. 13

    Kocsis AK, Lakatos PL, Somogyvari F, Fuszek P, Papp J, Fischer S et al. Association of beta-defensin 1 single nucleotide polymorphisms with Crohn's disease. Scand J Gastroenterol 2008; 43: 299–307.

  14. 14

    Levy H, Raby BA, Lake S, Tantisira KG, Kwiatkowski D, Lazarus R et al. Association of defensin beta-1 gene polymorphisms with asthma. J Allergy Clin Immunol 2005; 115: 252–258.

  15. 15

    Prado-Montes de Oca E, Garcia-Vargas A, Lozano-Inocencio R, Gallegos-Arreola MP, Sandoval-Ramírez L, Dávalos-Rodríguez NO et al. Association of beta-defensin 1 single nucleotide polymorphisms with atopic dermatitis. Int Arch Allergy Immunol 2007; 142: 211–218.

  16. 16

    Michalowicz BS, Diehl SR, Gunsolley JC, Sparks BS, Brooks CN, Koertge TE et al. Evidence of a substantial genetic basis for risk of adult periodontitis. J Periodontol 2000; 71: 1699–1707.

  17. 17

    Corey LA, Nance WE, Hofstede P, Schenkein HA . Self-reported periodontal disease in a Virginia twin population. J Periodontol 1993; 64: 1205–1208.

  18. 18

    Loos BG, John RP, Laine ML . Identification of genetic risk factors for periodontitis and possible mechanisms of action. J Clin Periodontol 2005; 32 (Suppl 6): 159–179.

  19. 19

    Boniotto M, Hazbon MH, Jordan WJ, Lennon GP, Eskdale J, Alland D et al. Novel hairpin-shaped primer assay to study the association of the -44 single-nucleotide polymorphism of the DEFB1 gene with early-onset periodontal disease. Clin Diagn Lab Immunol 2004; 11: 766–769.

  20. 20

    Wohlfahrt JC, Wu T, Hodges JS, Hinrichs JE, Michalowicz BS . No association between selected candidate gene polymorphisms and severe chronic periodontitis. J Periodontol 2006; 77: 426–436.

  21. 21

    Schunkert H, Gotz A, Braund P, McGinnis R, Tregouet DA, Mangino M et al. Repeated replication and a prospective meta-analysis of the association between chromosome 9p21.3 and coronary artery disease. Circulation 2008; 117: 1675–1684.

  22. 22

    Zeggini E, Scott LJ, Saxena R, Voight BF, Marchini JL, Hu T et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet 2008; 40: 638–645.

  23. 23

    Franke A, Balschun T, Karlsen TH, Hedderich J, May S, Lu T et al. Replication of signals from recent studies of Crohn's disease identifies previously unknown disease loci for ulcerative colitis. Nat Genet 2008; 40: 713–715.

  24. 24

    Jurevic RJ, Bai M, Chadwick RB, White TC, Dale BA . Single-nucleotide polymorphisms (SNPs) in human beta-defensin 1: high-throughput SNP assays and association with Candida carriage in type I diabetics and nondiabetic controls. J Clin Microbiol 2003; 41: 90–96.

  25. 25

    Tesse R, Cardinale F, Santostasi T, Polizzi A, Manca A, Mappa L et al. Association of beta-defensin-1 gene polymorphisms with Pseudomonas aeruginosa airway colonization in cystic fibrosis. Genes Immun 2008; 9: 57–60.

  26. 26

    Baroncelli S, Ricci E, Andreotti M, Guidotti G, Germano P, Marazzi MC et al. Single-nucleotide polymorphisms in human beta-defensin-1 gene in Mozambican HIV-1-infected women and correlation with virologic parameters. AIDS 2008; 22: 1515–1517.

  27. 27

    Milanese M, Segat L, Pontillo A, Arraes LC, de Lima Filho JL, Crovella S . DEFB1 gene polymorphisms and increased risk of HIV-1 infection in Brazilian children. AIDS 2006; 20: 1673–1675.

  28. 28

    Braida L, Boniotto M, Pontillo A, Tovo PA, Amoroso A, Crovella S . A single-nucleotide polymorphism in the human beta-defensin 1 gene is associated with HIV-1 infection in Italian children. AIDS 2004; 18: 1598–1600.

  29. 29

    Matsushita I, Hasegawa K, Nakata K, Yasuda K, Tokunaga K, Keicho N . Genetic variants of human beta-defensin-1 and chronic obstructive pulmonary disease. Biochem Biophys Res Commun 2002; 291: 17–22.

  30. 30

    Landi D, Gemignani F, Naccarati A, Vodicka P, Vodickova L, Novotny J et al. Polymorphisms within micro-RNA-binding sites and risk of sporadic colorectal cancer. Carcinogenesis 2008; 29: 579–584.

  31. 31

    Steffens M, Lamina C, Illig T, Bettecken T, Vogler R, Entz P et al. SNP-based analysis of genetic substructure in the German population. Hum Hered 2006; 62: 20–29.

  32. 32

    Armitage GC . Development of a classification system for periodontal diseases and conditions. Ann Periodontol 1999; 4: 1–6.

  33. 33

    Hamp SE, Nyman S, Lindhe J . Periodontal treatment of multirooted teeth. Results after 5 years. J Clin Periodontol 1975; 2: 126–135.

  34. 34

    Loos BG, Leppers-Van de Straat FG, Van de Winkel JG, Van der Velden U . Fcgamma receptor polymorphisms in relation to periodontitis. J Clin Periodontol 2003; 30: 595–602.

  35. 35

    Laine ML, Morre SA, Murillo LS, van Winkelhoff AJ, Pena AS . CD14 and TLR4 gene polymorphisms in adult periodontitis. J Dent Res 2005; 84: 1042–1046.

  36. 36

    Bizzarro S, van der Velden U, ten Heggeler JM, Leivadaros E, Hoek FJ, Gerdes VE et al. Periodontitis is characterized by elevated PAI-1 activity. J Clin Periodontol 2007; 34: 574–580.

  37. 37

    Krawczak M, Nikolaus S, von Eberstein H, Croucher PJ, El Mokhtari NE, Schreiber S . PopGen: population-based recruitment of patients and controls for the analysis of complex genotype–phenotype relationships. Community Genet 2006; 9: 55–61.

  38. 38

    Laine ML, Farre MA, Crusius JB, van Winkelhoff AJ, Pena AS . The mouthwash: a non-invasive sampling method to study cytokine gene polymorphisms. J Periodontol 2000; 71: 1315–1318.

  39. 39

    Weckx S, Del-Favero J, Rademakers R, Claes L, Cruts M, De Jonghe P et al. novoSNP, a novel computational tool for sequence variation discovery. Genome Res 2005; 15: 436–442.

  40. 40

    Qin ZS, Niu T, Liu JS . Partition–ligation–expectation–maximization algorithm for haplotype inference with single-nucleotide polymorphisms. Am J Hum Genet 2002; 71: 1242–1247.

  41. 41

    Barrett JC, Fry B, Maller J, Daly MJ . Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005; 21: 263–265.

  42. 42

    Hofacker IL . Vienna RNA secondary structure server. Nucleic Acids Res 2003; 31: 3429–3431.

  43. 43

    Betel D, Wilson M, Gabow A, Marks DS, Sander C . The microRNA.org resource: targets and expression. Nucleic Acids Res 2008; 36: D149–D153.

  44. 44

    Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.

  45. 45

    Abecasis GR, Cookson WO . GOLD—graphical overview of linkage disequilibrium. Bioinformatics 2000; 16: 182–183.

Download references

Acknowledgements

The following dentists are gratefully acknowledged. They have helped with the recruitment of patients and are listed alphabetically: PGGL van der Avoort, G Althoff, DS Barendregt, MS Bertels, A Biggel, R Bodens, F Bröseler, C Christan, NHC Corba, F Cleve, BM Deblauwe, LJ van Dijk, RA Driessen, T Eger, A Engelmann, U Engelsmann, A Friedmann, P Eickholz, PA Eigenhuis, J Graswinckel, LJMM Gründemann, H Hamming, L Hanfland, W Heindl, B Heinz, JW Hutter, J Jansen, H Jentsch, G Knöfler, A Krug, WH van Leeuwen, Ch. Lienhard, A Manschot, F Meier, E Meijer, O Oberbeckmann, MDA Petit, AM van Puijenbroek, V Reichert, B Sigusch, B Simon, A Spahr, JA Speelman, NB Spits, J Stein, J Steinfort, RWR Steures, C Theben, C Tietmann, H Topoll, JAH Tromp, ATE Vangsted, Varoufaki, GA Voerman, K Wagner, GA van der Weijden and E van der Zee. This study was supported by a research grant of the ‘Research Center Inflammation Medicine’ of the Medical Faculty, Christian-Albrechts-University, University Medical Center Schleswig-Holstein, Campus Kiel (ASS and GMR); by the German Ministry of Education and Research (BMBF) through a National Genome Research Network (NGFN 01GS0809) grant (MN); by a grant from the Deutsche Forschungsgemeinschaft (KFO208) (ASS, GMR, HD and SJ); by the German Ministry of Education and Research through the popgen biobank project (01GR0468); by a grant from BONFOR of the Medical Faculty, University of Bonn (SJ) and a grant from the ARPA Research Foundation (BG-S and SJ), Regensburg, Germany.

Author information

Correspondence to A S Schaefer.

Additional information

Supplementary Information accompanies the paper on Genes and Immunity website (http://www.nature.com/gene)

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Keywords

  • periodontitis
  • DEFB1
  • 3′ UTR
  • miRNA
  • association
  • genetic susceptibility

Further reading