Abstract
Periodontitis is a common dysbiotic inflammatory disease with an estimated heritability of 50%. Due to the limited sample size of available periodontitis cohorts and the underlying trait heterogeneity, genome-wide association studies (GWAS) of chronic periodontitis (CP) have been unsuccessful in discovering susceptibility factors. A strategy that combines agnostic GWAS with a well-powered candidate-gene approach has the potential to discover novel loci. We combined RNA-seq data from gingival tissues with quantitative trait loci (QTLs) that were identified in a F(2)-cross of mice resistant and susceptible to infection with oral bacterial pathogens. Four genes, which were located within the mapped QTLs, showed differential expression. The chromosomal regions across the human orthologous were interrogated for putative periodontitis-associated variants using existing GWAS data from a German case-control sample of aggressive periodontitis (AgP; 651 cases, 4,001 controls), the most severe and early onset form of periodontitis. Two haplotype blocks, one upstream to the coding region of UGT2A1 (rs146712414, P = 9.1 × 10(-5); odds ratio [OR], 1.34; 95% confidence interval [CI], 1.16-1.56) and one downstream of the genes PF4/PPBP/CXCL5 (rs1595009, P = 1.3 × 10(-4); OR, 1.32; 95% CI, 1.15-1.52), were associated with AgP. The association of rs1595009 was validated in an independent cohort of CP of European Americans (1,961 cases and 1,864 controls; P = 0.03; OR, 1.45; 95% CI, 1.01-1.29). This association was further replicated in another sample of 399 German CP cases (disease onset <60 y of age) and 1,633 controls ( P = 0.03; OR, 1.75; 95% CI, 1.06-2.90). The combined estimates of association from all samples were P = 2.9 × 10(-5) (OR, 1.2; 95% CI, 1.1-1.3). This study shows the strength of combining QTL mapping and RNA-Seq data from a mouse model with association studies in human case-control samples to identify genetic risk variants of periodontitis.