Integration of mouse and human studies for mapping periodontitis susceptibility

Objectives: Periodontitis is one of the most common inflammatory human diseases with a strong genetic component. 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 identifying common susceptibility factors. To discover novel risk loci we integrated quantitative trait loci (QTL) mapping in mice with association studies in humans .
Methods: We assessed alveolar bone loss in response to experimental periodontal infection in 25 lines (286 mice) from the Collaborative Cross (CC) mouse population using micro-computerized tomography (µCT) analysis. The orthologous human chromosomal regions of the significant mouse QTL were analyzed for association using imputed genotype data (OmniExpress BeadChip arrays) derived from case-control samples of aggressive periodontitis (AgP; 896 cases, 7,104 controls) and chronic periodontitis (CP; 2,746 cases, 1,864 controls) of Northwest-European and European-American descent, respectively.
Results: . In the mouse genome, QTL-mapping revealed two significant loci (minus log P-value=5.3; FDR=0.06) on chromosomes 1 (Perl3) and 14 (Perl4). The mapping resolution ranged from ~1.5 Mb to 3 Mb. Perl3 overlaps with a previously-reported QTL associated with residual bone volume in F2 cross and includes the murine gene Ccdc121. Its human orthologue was previously reported to be associated with CP in humans. Use of variation data from the genomes of the CC founder strains further refined the QTLs and suggested seven candidate genes (CAPN8, DUSP23, PCDH17, SNORA17, PCDH9, LECT1, and LECT2). We found no evidence of association of these candidates with the human orthologues.
Conclusions: The CC populations enabled mapping of confined QTL that confer susceptibility to alveolar bone loss in mice and larger human phenotype-genotype samples and additional expression data from gingival tissues are likely required to identify true positive signals.