The genetics of Crohn's disease in the Ashkenazi Jewish population

Yale University, New Haven CT

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): Inflammatory bowel disease, which affects 1.4 million Americans, is characterized by chronic intestinal inflammation and comprises two major subtypes, Crohn's disease and ulcerative colitis. Genetic factors are central to the heritability and pathogenesis of this disease. The Ashkenazi Jewish population exhibits a population prevalence of Crohn's disease that is 4.3 to 7.7-fold greater than in other European- ancestry populations. Findings from a recent Ashkenazi-specific genome-wide association study of Crohn's disease showed significant overlap with previously established association signals in a general European- ancestry cohort, suggesting a similar genetic structure for high-frequency disease-related variation. The combined effect of the associated loci, however, accounted for a proportion of heritability that was smaller in the Ashkenazim than in the non-Jewish cohort, leading us to hypothesize that the genetic etiology of the increased Crohn's disease prevalence in the Ashkenazi Jewish population is primarily driven by rare variants of moderate or large effect, which have to date been poorly assayed by genome-wide association scans. Specific aims: The research proposal comprises three specific aims. The first aim will combine data from our previous Ashkenazi-specific association study and new data from exome sequencing of Ashkenazi Crohn's disease patients in order to test novel variants for case-control association. We will also use bioinformatic and statistical analyses to select a subset of newly discovered variants for follow-up genotyping in a large Ashkenazi case-control cohort. The second aim will evaluate and modify methods for analyzing statistical association of rare functional variants and will apply these strategies to optimize the detection of novel association signals in the Ashkenazi Jewish genotype datasets from Aim 1. To estimate variants' functional impacts, this analysis will integrate multiple outside sources of data, including signatures of natural selection evolutionary conservation, biological networks, and modifications in transcription and amino acid coding. Our third aim will utilize whole-genome sequencing data to improve haplotyping and refine genetic evolutionary history. This will extend the disease-oriented analysis from Aim 2 to include compound heterozygosity and the molecular evolution of each variant. Since each aim employs a different dataset, progress on all three aims will be made concurrently.