Detection of Shared Genetic Variants Between Complex Diseases While Preserving LD Structure

• Activity Number: 540
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Julie Kobie* and Sihai Zhao and Yun R. Li and Hakon Hakonarson and Hongzhe Li
• Companies: University of Pennsylvania Perelman School of Medicine and University of Illinois at Urbana-Champaign and Children's Hospital of Philadelphia and Children's Hospital of Philadelphia and University of Pennsylvania
• Keywords: Simultaneous signal detection ; Pleiotropy ; Genome-wide association studies ; Autoimmune diseases ; Complex diseases ; LD dependency structure

Abstract

Studying complex diseases, such as autoimmune diseases, can lead to the detection of pleiotropic loci with otherwise small effects. Through the detection of pleiotropic loci, the genetic architecture of these complex diseases can be better defined, allowing for subsequent improvements in treatment and prevention efforts. We investigate the genetic relatedness of complex diseases through (1) the detection of shared genetic variants at particular loci and (2) the detection of shared genetic variants within a LD-defined window. We revisit the global test, originally proposed by Zhao et al. (2014), for the detection of shared genetic variants between a pair of complex diseases. Often genetic variants are assumed to be independent, though many data points are arbitrarily ignored through LD pruning. Utilizing individual genotype data from GWAS we propose, and validate with simulations, a perturbation procedure for evaluating the statistical significance of the global test while preserving the inherent dependency structure among genetic variants. The autoimmune disease pair ulcerative colitis and Crohn's disease shares at least one genetic variant, evaluated by the perturbation procedure.