Online Program Home
My Program

Abstract Details

Activity Number: 551 - Risk Prediction Methods and Applications in Risk Stratified Prevention
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract #300172 Presentation
Title: Case-Only Analysis of Gene-Environment Interactions Using Polygenic Risk Scores
Author(s): Allison Meisner* and Nilanjan Chatterjee
Companies: Johns Hopkins Bloomberg School of Public Health and Johns Hopkins University
Keywords: case-control studies; case-only analysis; gene-environment interaction; polygenic risk score

Identification of gene (G)-environment (E) interactions is critical for understanding disease etiology, developing risk prediction models, and evaluating the impact of lifestyle interventions. Investigations of G-E interactions have led to limited findings to date, possibly due to low power for individual variants. Consequently, polygenic risk scores (PRS) are increasingly being used to detect global patterns of interaction. Motivated by the case-only method for evaluating interactions between a single variant and E, we propose a case-only method for the analysis of PRS-E interactions in case-control studies. We show that if the PRS and E are independent, a linear regression of the PRS on E in a sample of cases can be used to estimate the interaction parameter. Simulation studies indicate the efficiency of this approach is similar to that of a cohort study and about twice that of standard logistic regression analysis. Furthermore, if genotype data are available on a representative sample, the proposed method can estimate the main effect of the PRS. Extensions are considered to account for G-E dependence. We apply the proposed method to data from the UK Biobank study.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program