Literature DB >> 19022826

Invited commentary: from genome-wide association studies to gene-environment-wide interaction studies--challenges and opportunities.

Muin J Khoury1, Sholom Wacholder.   

Abstract

The recent success of genome-wide association studies in finding susceptibility genes for many common diseases presents tremendous opportunities for epidemiologic studies of environmental risk factors. Analysis of gene-environment interactions, included in only a small fraction of epidemiologic studies until now, will begin to accelerate as investigators integrate analyses of genome-wide variation and environmental factors. Nevertheless, considerable methodological challenges are involved in the design and analysis of gene-environment interaction studies. The authors review these issues in the context of evolving methods for assessing interactions and discuss how the current agnostic approach to interrogating the human genome for genetic risk factors could be extended into a similar approach to gene-environment-wide interaction studies of disease occurrence in human populations.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 19022826      PMCID: PMC2727257          DOI: 10.1093/aje/kwn351

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  29 in total

Review 1.  The use of common genetic polymorphisms to enhance the epidemiologic study of environmental carcinogens.

Authors:  N Rothman; S Wacholder; N E Caporaso; M Garcia-Closas; K Buetow; J F Fraumeni
Journal:  Biochim Biophys Acta       Date:  2001

2.  'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

Authors:  George Davey Smith; Shah Ebrahim
Journal:  Int J Epidemiol       Date:  2003-02       Impact factor: 7.196

3.  A vision for the future of genomics research.

Authors:  Francis S Collins; Eric D Green; Alan E Guttmacher; Mark S Guyer
Journal:  Nature       Date:  2003-04-14       Impact factor: 49.962

4.  Assessing the probability that a positive report is false: an approach for molecular epidemiology studies.

Authors:  Sholom Wacholder; Stephen Chanock; Montserrat Garcia-Closas; Laure El Ghormli; Nathaniel Rothman
Journal:  J Natl Cancer Inst       Date:  2004-03-17       Impact factor: 13.506

5.  Systems biology and new technologies enable predictive and preventative medicine.

Authors:  Leroy Hood; James R Heath; Michael E Phelps; Biaoyang Lin
Journal:  Science       Date:  2004-10-22       Impact factor: 47.728

6.  Genome-wide strategies for detecting multiple loci that influence complex diseases.

Authors:  Jonathan Marchini; Peter Donnelly; Lon R Cardon
Journal:  Nat Genet       Date:  2005-03-27       Impact factor: 38.330

7.  Gene-environment interaction in genome-wide association studies.

Authors:  Cassandra E Murcray; Juan Pablo Lewinger; W James Gauderman
Journal:  Am J Epidemiol       Date:  2008-11-20       Impact factor: 4.897

8.  An epidemiologic approach to ecogenetics.

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

9.  Detection of genotype-environment interaction in case-control studies of birth defects: how big a sample size?

Authors:  M J Khoury; T H Beaty; S J Hwang
Journal:  Teratology       Date:  1995-05

Review 10.  Reporting, appraising, and integrating data on genotype prevalence and gene-disease associations.

Authors:  Julian Little; Linda Bradley; Molly S Bray; Mindy Clyne; Janice Dorman; Darrell L Ellsworth; James Hanson; Muin Khoury; Joseph Lau; Thomas R O'Brien; Nat Rothman; Donna Stroup; Emanuela Taioli; Duncan Thomas; Harri Vainio; Sholom Wacholder; Clarice Weinberg
Journal:  Am J Epidemiol       Date:  2002-08-15       Impact factor: 4.897

View more
  76 in total

1.  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

2.  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

3.  Commentary: the year in endocrine genetics for basic scientists.

Authors:  William F Crowley
Journal:  Mol Endocrinol       Date:  2011-11-22

4.  Public understanding of risks from gene-environment interaction in common diseases: implications for public communications.

Authors:  C M Condit; L Shen
Journal:  Public Health Genomics       Date:  2010-08-13       Impact factor: 2.000

5.  A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

Authors:  Brisa N Sánchez; Shan Kang; Bhramar Mukherjee
Journal:  Biometrics       Date:  2011-09-28       Impact factor: 2.571

6.  Tests for Gene-Environment Interactions and Joint Effects With Exposure Misclassification.

Authors:  Philip S Boonstra; Bhramar Mukherjee; Stephen B Gruber; Jaeil Ahn; Stephanie L Schmit; Nilanjan Chatterjee
Journal:  Am J Epidemiol       Date:  2016-01-10       Impact factor: 4.897

7.  Recommendations and proposed guidelines for assessing the cumulative evidence on joint effects of genes and environments on cancer occurrence in humans.

Authors:  Paolo Boffetta; Deborah M Winn; John P Ioannidis; Duncan C Thomas; Julian Little; George Davey Smith; Vincent J Cogliano; Stephen S Hecht; Daniela Seminara; Paolo Vineis; Muin J Khoury
Journal:  Int J Epidemiol       Date:  2012-05-16       Impact factor: 7.196

8.  Genetic epidemiology with a capital E: where will we be in another 10 years?

Authors:  Duncan C Thomas
Journal:  Genet Epidemiol       Date:  2012-02-06       Impact factor: 2.135

Review 9.  Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.

Authors:  Chirag J Patel; Jacqueline Kerr; Duncan C Thomas; Bhramar Mukherjee; Beate Ritz; Nilanjan Chatterjee; Marta Jankowska; Juliette Madan; Margaret R Karagas; Kimberly A McAllister; Leah E Mechanic; M Daniele Fallin; Christine Ladd-Acosta; Ian A Blair; Susan L Teitelbaum; Christopher I Amos
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-07-14       Impact factor: 4.254

10.  The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

Authors:  Shi Li; Bhramar Mukherjee; Jeremy M G Taylor; Kenneth M Rice; Xiaoquan Wen; John D Rice; Heather M Stringham; Michael Boehnke
Journal:  Genet Epidemiol       Date:  2014-05-06       Impact factor: 2.135

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.