Population Based Genetic Association Study for Two Correlated Complex Diseases with Binary Disease Status and an Underlying Pleiotropic Gene

• Activity Number: 584 - Statistical Methods for Genetic Association Analysis
• Type: Contributed
• Date/Time: Wednesday, August 2, 2017 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Vishal Midya*
• Companies: Penn State College of Medicine
• Keywords: Correlated Complex Diseases ; Binary Disease Status ; Joint Bivariate Model ; Pleiotropic Gene ; Linkage Disequilibrium

Abstract

In this work we have developed a novel joint bivariate Bernoulli type model for two correlated complex diseases with binary disease status for both genotypic and allelic level data assuming there is a pleiotropic gene responsible for this. We have used Likelihood Ratio Test (LRT) based on this newly developed model for testing of hypotheses. It is shown that the LRT based on the new Genotypic Bivariate Bernoulli Model (or Allelic Bivariate Bernoulli Model) performs much better in terms of power with respect to the usual Chi-Square Test for Homogeneity. This model also has uniformly higher power with respect to chi Square test for individual diseases. Even for very small values of linkage disequilibrium between the marker and disease alleles, this model based LRT has quite high power than the corresponding Chi-Square Test for Homogeneity.