Literature DB >> 33733358

Gene-Environment Interaction: A Variable Selection Perspective.

Fei Zhou1, Jie Ren2, Xi Lu1, Shuangge Ma3, Cen Wu4.   

Abstract

Gene-environment interactions have important implications for elucidating the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G × E interactions have been mainly conducted within the framework of genetic association studies. The high dimensionality of G × E interactions, due to the complicated form of environmental effects and the presence of a large number of genetic factors including gene expressions and SNPs, has motivated the recent development of penalized variable selection methods for dissecting G × E interactions, which has been ignored in the majority of published reviews on genetic interaction studies. In this article, we first survey existing studies on both gene-environment and gene-gene interactions. Then, after a brief introduction to the variable selection methods, we review penalization and relevant variable selection methods in marginal and joint paradigms, respectively, under a variety of conceptual models. Discussions on strengths and limitations, as well as computational aspects of the variable selection methods tailored for G × E studies, have also been provided.

Keywords:  Bayesian variable selection; Gene–environment interaction; Linear and nonlinear interaction; Marginal and joint analysis; Penalization

Mesh:

Year:  2021        PMID: 33733358     DOI: 10.1007/978-1-0716-0947-7_13

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  78 in total

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

Authors:  Marilyn C Cornelis; Eric J Tchetgen Tchetgen; Liming Liang; Lu Qi; Nilanjan Chatterjee; Frank B Hu; Peter Kraft
Journal:  Am J Epidemiol       Date:  2011-12-22       Impact factor: 4.897

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Journal:  Eur J Hum Genet       Date:  2008-06-04       Impact factor: 4.246

Review 4.  Genetic association studies.

Authors:  Kathryn L Lunetta
Journal:  Circulation       Date:  2008-07-01       Impact factor: 29.690

5.  Gene-environment interaction: definitions and study designs.

Authors:  R Ottman
Journal:  Prev Med       Date:  1996 Nov-Dec       Impact factor: 4.018

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Authors:  Marilyn C Cornelis; Frank B Hu
Journal:  Annu Rev Nutr       Date:  2012-04-23       Impact factor: 11.848

Review 7.  Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

Authors:  Naoko I Simonds; Armen A Ghazarian; Camilla B Pimentel; Sheri D Schully; Gary L Ellison; Elizabeth M Gillanders; Leah E Mechanic
Journal:  Genet Epidemiol       Date:  2016-04-07       Impact factor: 2.135

Review 8.  Gene-environment interactions in cardiovascular disease.

Authors:  Elena Flowers; Erika Sivarajan Froelicher; Bradley E Aouizerat
Journal:  Eur J Cardiovasc Nurs       Date:  2012-03-06       Impact factor: 3.908

Review 9.  A comprehensive review of genetic association studies.

Authors:  Joel N Hirschhorn; Kirk Lohmueller; Edward Byrne; Kurt Hirschhorn
Journal:  Genet Med       Date:  2002 Mar-Apr       Impact factor: 8.822

10.  Genetic association studies: an information content perspective.

Authors:  Cen Wu; Shaoyu Li; Yuehua Cui
Journal:  Curr Genomics       Date:  2012-11       Impact factor: 2.236

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  7 in total

1.  Sparse group variable selection for gene-environment interactions in the longitudinal study.

Authors:  Fei Zhou; Xi Lu; Jie Ren; Kun Fan; Shuangge Ma; Cen Wu
Journal:  Genet Epidemiol       Date:  2022-06-29       Impact factor: 2.344

2.  Pharmacogenetics of Addiction Therapy.

Authors:  David P Graham; Mark J Harding; David A Nielsen
Journal:  Methods Mol Biol       Date:  2022

3.  Overlapping group screening for detection of gene-environment interactions with application to TCGA high-dimensional survival genomic data.

Authors:  Jie-Huei Wang; Kang-Hsin Wang; Yi-Hau Chen
Journal:  BMC Bioinformatics       Date:  2022-05-30       Impact factor: 3.307

4.  Integrating Multi-Omics Data for Gene-Environment Interactions.

Authors:  Yinhao Du; Kun Fan; Xi Lu; Cen Wu
Journal:  BioTech (Basel)       Date:  2021-01-29

5.  Polygenic Risk of Hypertriglyceridemia Is Modified by BMI.

Authors:  Virginia Esteve-Luque; Marta Fanlo-Maresma; Ariadna Padró-Miquel; Emili Corbella; Maite Rivas-Regaira; Xavier Pintó; Beatriz Candás-Estébanez
Journal:  Int J Mol Sci       Date:  2022-08-30       Impact factor: 6.208

6.  Interep: An R Package for High-Dimensional Interaction Analysis of the Repeated Measurement Data.

Authors:  Fei Zhou; Jie Ren; Yuwen Liu; Xiaoxi Li; Weiqun Wang; Cen Wu
Journal:  Genes (Basel)       Date:  2022-03-19       Impact factor: 4.096

7.  Identifying Gene-Environment Interactions With Robust Marginal Bayesian Variable Selection.

Authors:  Xi Lu; Kun Fan; Jie Ren; Cen Wu
Journal:  Front Genet       Date:  2021-12-08       Impact factor: 4.599

  7 in total

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