Whole Exome Sequencing of Patients with Early-Onset Severe Periodontitis

• Applicants: Dr. Sandra Freitag-Wolf; Dr. Gesa Richter
• Subject Area: Dentistry, Oral Surgery
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 495133518

Periodontitis (PD) is a very common inflammatory disease of the oral cavity with prevalence rates of 11% for the severe forms. Genetic variability results in a variety of diverse manifestations of PD with a small proportion of very severe and early onset (EO) forms that often have familial aggregation. In general, it is considered that genetic factors strongly contribute to these EO phenotypes, which in particular are characterized by the absence of environmental risk factors. However, also for common forms of PD, the heritability is estimated at 0.4-0.5 but it increases with younger age of disease onset and severity. Genome-wide association studies have identified a few susceptibility single nucleotide polymorphisms (SNPs) but the comprehensive identification of common risk variants for PD requires much larger samples that worldwide currently do not exist. Whole-exome-sequencing (WES) of severe very early onset EO-PD cases performed in our preliminary works showed that risk genes detected by GWAS also harbor rare high-effect susceptibility variants. These mutations are not in linkage disequilibrium to the associations with common forms of PD. This is in line with the broad literature that shows similar observations for a variety of other common complex diseases. Here, we propose to perform WES sequencing of 440 severe EO-PD patients PD (age of first diagnosis ≤ 30 years) to identify rare variants with large effect sizes. In addition, the genes that harbor these mutations will subsequently be used as candidates for association tests in available imputed GWAS genotype data sets of common forms of PD. Furthermore, these genes represent legitimate candidates for gene network-based association tests and to establish the extent to which the biology of PD predisposition converges onto a restricted set of pathways. Precisely defined phenotype information allows the extension of current associations analyses to more complex statistical models to detect underlying gene-environment interactions followed by subgroup analyses (i.e. disease severity or onset). We anticipate that this project, which will use the largest case sample of severe EO-PD available worldwide, to have the potential to strongly advance our understanding of the genetic etiology of EO-PD and common forms of PD, and to locate intrinsic disease causing factors that have largely remained unknown to date. These data are required to subdivide different patient groups for improved diagnosis and therapy.

• DFG Programme: Research Grants