Literature DB >> 20212493

Gene--environment-wide association studies: emerging approaches.

Duncan Thomas1.   

Abstract

Despite the yield of recent genome-wide association (GWA) studies, the identified variants explain only a small proportion of the heritability of most complex diseases. This unexplained heritability could be partly due to gene--environment (G×E) interactions or more complex pathways involving multiple genes and exposures. This Review provides a tutorial on the available epidemiological designs and statistical analysis approaches for studying specific G×E interactions and choosing the most appropriate methods. I discuss the approaches that are being developed for studying entire pathways and available techniques for mining interactions in GWA data. I also explore methods for marrying hypothesis-driven pathway-based approaches with 'agnostic' GWA studies.

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Year:  2010        PMID: 20212493      PMCID: PMC2891422          DOI: 10.1038/nrg2764

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  161 in total

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3.  Using hierarchical modeling in genetic association studies with multiple markers: application to a case-control study of bladder cancer.

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4.  Estimating interaction between genetic and environmental risk factors: efficiency of sampling designs within a cohort.

Authors:  Alexandre Bureau; Mamadou S Diallo; Jose M Ordovas; L Adrienne Cupples
Journal:  Epidemiology       Date:  2008-01       Impact factor: 4.822

5.  Optimal designs for two-stage genome-wide association studies.

Authors:  Andrew D Skol; Laura J Scott; Gonçalo R Abecasis; Michael Boehnke
Journal:  Genet Epidemiol       Date:  2007-11       Impact factor: 2.135

Review 6.  Molecular epidemiology: on the path to prevention?

Authors:  F P Perera
Journal:  J Natl Cancer Inst       Date:  2000-04-19       Impact factor: 13.506

7.  Annotation: the analysis of variance and the analysis of causes.

Authors:  R C Lewontin
Journal:  Am J Hum Genet       Date:  1974-05       Impact factor: 11.025

8.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

9.  Imputing gene-treatment interactions when the genotype distribution is unknown using case-only and putative placebo analyses--a new method for the Genetics of Hypertension Associated Treatment (GenHAT) study.

Authors:  Barry R Davis; Charles E Ford; Eric Boerwinkle; Donna Arnett; John Eckfeldt; Henry Black
Journal:  Stat Med       Date:  2004-08-15       Impact factor: 2.373

Review 10.  Epistasis and its implications for personal genetics.

Authors:  Jason H Moore; Scott M Williams
Journal:  Am J Hum Genet       Date:  2009-09       Impact factor: 11.025

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  312 in total

1.  Subgroups at high risk for ischaemic heart disease:identification and validation in 67 000 individuals from the general population.

Authors:  Ruth Frikke-Schmidt; Anne Tybjærg-Hansen; Greg Dyson; Christiane L Haase; Marianne Benn; Børge G Nordestgaard; Charles F Sing
Journal:  Int J Epidemiol       Date:  2014-10-30       Impact factor: 7.196

2.  Next generation analytic tools for large scale genetic epidemiology studies of complex diseases.

Authors:  Leah E Mechanic; Huann-Sheng Chen; Christopher I Amos; Nilanjan Chatterjee; Nancy J Cox; Rao L Divi; Ruzong Fan; Emily L Harris; Kevin Jacobs; Peter Kraft; Suzanne M Leal; Kimberly McAllister; Jason H Moore; Dina N Paltoo; Michael A Province; Erin M Ramos; Marylyn D Ritchie; Kathryn Roeder; Daniel J Schaid; Matthew Stephens; Duncan C Thomas; Clarice R Weinberg; John S Witte; Shunpu Zhang; Sebastian Zöllner; Eric J Feuer; Elizabeth M Gillanders
Journal:  Genet Epidemiol       Date:  2011-12-06       Impact factor: 2.135

3.  Testing gene-environment interaction in large-scale case-control association studies: possible choices and comparisons.

Authors:  Bhramar Mukherjee; Jaeil Ahn; Stephen B Gruber; Nilanjan Chatterjee
Journal:  Am J Epidemiol       Date:  2011-12-22       Impact factor: 4.897

4.  Invited commentary: GE-Whiz! Ratcheting gene-environment studies up to the whole genome and the whole exposome.

Authors:  Duncan C Thomas; Juan Pablo Lewinger; Cassandra E Murcray; W James Gauderman
Journal:  Am J Epidemiol       Date:  2011-12-22       Impact factor: 4.897

Review 5.  Unraveling the genetic component of systemic sclerosis.

Authors:  José Ezequiel Martín; Lara Bossini-Castillo; Javier Martín
Journal:  Hum Genet       Date:  2012-01-05       Impact factor: 4.132

6.  Gene-by-environment experiments: a new approach to finding the missing heritability.

Authors:  Marinus H van Ijzendoorn; Marian J Bakermans-Kranenburg; Jay Belsky; Steven Beach; Gene Brody; Kenneth A Dodge; Mark Greenberg; Michael Posner; Stephen Scott
Journal:  Nat Rev Genet       Date:  2011-11-18       Impact factor: 53.242

7.  Environmental change exposes beneficial epistatic interactions in a catalytic RNA.

Authors:  Eric J Hayden; Andreas Wagner
Journal:  Proc Biol Sci       Date:  2012-06-20       Impact factor: 5.349

8.  Efficient genome-wide association testing of gene-environment interaction in case-parent trios.

Authors:  W James Gauderman; Duncan C Thomas; Cassandra E Murcray; David Conti; Dalin Li; Juan Pablo Lewinger
Journal:  Am J Epidemiol       Date:  2010-06-11       Impact factor: 4.897

9.  The environment and schizophrenia.

Authors:  Jim van Os; Gunter Kenis; Bart P F Rutten
Journal:  Nature       Date:  2010-11-11       Impact factor: 49.962

10.  BAYESIAN SEMIPARAMETRIC ANALYSIS FOR TWO-PHASE STUDIES OF GENE-ENVIRONMENT INTERACTION.

Authors:  Jaeil Ahn; Bhramar Mukherjee; Stephen B Gruber; Malay Ghosh
Journal:  Ann Appl Stat       Date:  2013-03       Impact factor: 2.083

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