An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group - Institut Pasteur Access content directly
Journal Articles Genetic Epidemiology Year : 2016

An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group

Thomas Winkler
  • Function : Author
Alisa Manning
  • Function : Author
Hugues Aschard
Michael Brown
  • Function : Author
Alanna Morrison
  • Function : Author
Myriam Fornage
  • Function : Author
Li-An Lin
  • Function : Author
Melissa Richard
  • Function : Author
Traci Bartz
  • Function : Author
Bruce Psaty
  • Function : Author
Caroline Hayward
  • Function : Author
Ozren Polasek
  • Function : Author
Jonathan Marten
  • Function : Author
Igor Rudan
  • Function : Author
Mary Feitosa
  • Function : Author
Aldi Kraja
  • Function : Author
Michael Province
  • Function : Author
Xuan Deng
  • Function : Author
Virginia Fisher
  • Function : Author
Yanhua Zhou
  • Function : Author
Lawrence Bielak
  • Function : Author
Jennifer Smith
  • Function : Author
Jennifer Huffman
  • Function : Author
Sandosh Padmanabhan
  • Function : Author
Blair Smith
  • Function : Author
Jingzhong Ding
  • Function : Author
Yongmei Liu
  • Function : Author
Kurt Lohman
  • Function : Author
Claude Bouchard
  • Function : Author
Tuomo Rankinen
  • Function : Author
Treva Rice
  • Function : Author
Donna Arnett
  • Function : Author
Karen Schwander
  • Function : Author
Xiuqing Guo
  • Function : Author
Walter Palmas
  • Function : Author
Jerome Rotter
  • Function : Author
Tamuno Alfred
  • Function : Author
Erwin Bottinger
  • Function : Author
Ruth Loos
  • Function : Author
Najaf Amin
  • Function : Author
Oscar Franco
  • Function : Author
Cornelia van Duijn
  • Function : Author
Dina Vojinovic
  • Function : Author
Daniel Chasman
  • Function : Author
Paul Ridker
  • Function : Author
Lynda Rose
  • Function : Author
Sharon Kardia
  • Function : Author
Xiaofeng Zhu
  • Function : Author
Kenneth Rice
  • Function : Author
Ingrid Borecki
  • Function : Author
Dabeeru Rao
  • Function : Author
W James Gauderman
  • Function : Author
L Adrienne Cupples
  • Function : Author
W. James Gauderman
  • Function : Author
L. Adrienne Cupples
  • Function : Author

Abstract

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.

Dates and versions

pasteur-03278740 , version 1 (05-07-2021)

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Cite

Yun Ju Sung, Thomas Winkler, Alisa Manning, Hugues Aschard, Vilmundur Gudnason, et al.. An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group. Genetic Epidemiology, 2016, 40 (5), pp.404-415. ⟨10.1002/gepi.21978⟩. ⟨pasteur-03278740⟩

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