Literature DB >> 16080585

Method for indirectly estimating gene-environment effect modification and power given only genotype frequency and odds ratio of environmental exposure.

Jimmy Thomas Efird1.   

Abstract

Both genes and environment are important determinants of disease. In this paper we model gene-environment effect modification on the odds ratio scale OR(GEID) and show how to indirectly estimate the effect and 95% confidence intervals (CI) for the simple case of no main genetic and environmental effects [i.e., OR(GE/D) = OR(GE/D) = 1]. A statistic is presented to test the null hypothesis OR(GE/D) = 1 and to calculate corresponding power, given the odds ratio for environmental exposure OR(E/D) and population genotype frequency (g). Direct extension of the above model provides a mathematical framework for estimating confidence bounds in more complex cases involving partial genetic and/or environmental effects.

Mesh:

Year:  2005        PMID: 16080585     DOI: 10.1007/s10654-005-2018-3

Source DB:  PubMed          Journal:  Eur J Epidemiol        ISSN: 0393-2990            Impact factor:   8.082


  7 in total

1.  A method of estimating comparative rates from clinical data; applications to cancer of the lung, breast, and cervix.

Authors:  J CORNFIELD
Journal:  J Natl Cancer Inst       Date:  1951-06       Impact factor: 13.506

Review 2.  Epidemiologic and genetic approaches in the study of gene-environment interaction: an overview of available methods.

Authors:  N Andrieu; A M Goldstein
Journal:  Epidemiol Rev       Date:  1998       Impact factor: 6.222

3.  Power and sample size calculations for case-control studies of gene-environment interactions with a polytomous exposure variable.

Authors:  I Foppa; D Spiegelman
Journal:  Am J Epidemiol       Date:  1997-10-01       Impact factor: 4.897

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Authors:  M J Khoury; M J Adams; W D Flanders
Journal:  Am J Hum Genet       Date:  1988-01       Impact factor: 11.025

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Authors:  R Ottman
Journal:  Genet Epidemiol       Date:  1990       Impact factor: 2.135

6.  The effect of genetic susceptibility on causal inference in epidemiologic studies.

Authors:  M J Khoury; W Stewart; T H Beaty
Journal:  Am J Epidemiol       Date:  1987-10       Impact factor: 4.897

7.  Minimum sample size estimation to detect gene-environment interaction in case-control designs.

Authors:  S J Hwang; T H Beaty; K Y Liang; J Coresh; M J Khoury
Journal:  Am J Epidemiol       Date:  1994-12-01       Impact factor: 4.897

  7 in total
  2 in total

Review 1.  Challenges and opportunities in genome-wide environmental interaction (GWEI) studies.

Authors:  Hugues Aschard; Sharon Lutz; Bärbel Maus; Eric J Duell; Tasha E Fingerlin; Nilanjan Chatterjee; Peter Kraft; Kristel Van Steen
Journal:  Hum Genet       Date:  2012-07-04       Impact factor: 4.132

2.  An Efficient Gatekeeper Algorithm for Detecting GxE.

Authors:  Jimmy T Efird
Journal:  Cancer Inform       Date:  2010-05-12
  2 in total

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