Gene-environment interactions in genome-wide association studies: A comparative study of tests applied to empirical studies of type 2 diabetes

Marilyn C. Cornelis, Eric J Tchetgen Tchetgen, Liming Liang, Lu Qi, Nilanjan Chatterjee, Frank B. Hu, Peter Kraft

Research output: Contribution to journalArticle

Abstract

The question of which statistical approach is the most effective for investigating gene-environment (G-E) interactions in the context of genome-wide association studies (GWAS) remains unresolved. By using 2 case-control GWAS (the Nurses' Health Study, 1976-2006, and the Health Professionals Follow-up Study, 1986-2006) of type 2 diabetes, the authors compared 5 tests for interactions: standard logistic regression-based case-control; case-only; semiparametric maximum-likelihood estimation of an empirical-Bayes shrinkage estimator; and 2-stage tests. The authors also compared 2 joint tests of genetic main effects and G-E interaction. Elevated body mass index was the exposure of interest and was modeled as a binary trait to avoid an inflated type I error rate that the authors observed when the main effect of continuous body mass index was misspecified. Although both the case-only and the semiparametric maximum-likelihood estimation approaches assume that the tested markers are independent of exposure in the general population, the authors did not observe any evidence of inflated type I error for these tests in their studies with 2,199 cases and 3,044 controls. Both joint tests detected markers with known marginal effects. Loci with the most significant G-E interactions using the standard, empirical-Bayes, and 2-stage tests were strongly correlated with the exposure among controls. Study findings suggest that methods exploiting G-E independence can be efficient and valid options for investigating G-E interactions in GWAS.

Original languageEnglish (US)
Pages (from-to)191-202
Number of pages12
JournalAmerican Journal of Epidemiology
Volume175
Issue number3
DOIs
StatePublished - Feb 1 2012
Externally publishedYes

Fingerprint

Gene-Environment Interaction
Genome-Wide Association Study
Type 2 Diabetes Mellitus
Body Mass Index
Joints
Health
Logistic Models
Nurses
Population
Genes

Keywords

  • case study
  • case-control studies
  • diabetes mellitus, type 2
  • epidemiologic methods
  • genome-wide association study
  • genotype-environment interaction

ASJC Scopus subject areas

  • Epidemiology

Cite this

Gene-environment interactions in genome-wide association studies : A comparative study of tests applied to empirical studies of type 2 diabetes. / Cornelis, Marilyn C.; Tchetgen, Eric J Tchetgen; Liang, Liming; Qi, Lu; Chatterjee, Nilanjan; Hu, Frank B.; Kraft, Peter.

In: American Journal of Epidemiology, Vol. 175, No. 3, 01.02.2012, p. 191-202.

Research output: Contribution to journalArticle

Cornelis, Marilyn C. ; Tchetgen, Eric J Tchetgen ; Liang, Liming ; Qi, Lu ; Chatterjee, Nilanjan ; Hu, Frank B. ; Kraft, Peter. / Gene-environment interactions in genome-wide association studies : A comparative study of tests applied to empirical studies of type 2 diabetes. In: American Journal of Epidemiology. 2012 ; Vol. 175, No. 3. pp. 191-202.
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