Gene-environment interactions for complex traits: Definitions, methodological requirements and challenges
Astrid Dempfle,André Scherag,André Scherag,Rebecca Hein,Lars Beckmann,Jenny Chang-Claude,Helmut Schäfer +6 more
TLDR
This review discusses methodological issues involved in investigating gene–environment (G × E) interactions in genetic–epidemiological studies of complex diseases and their potential relevance for clinical application and attempts to clarify conceptual differences of the term ‘interaction’ in the statistical and biological sciences.Abstract:
Genetic and environmental risk factors and their interactions contribute to the development of complex diseases In this review, we discuss methodological issues involved in investigating gene-environment (G x E) interactions in genetic-epidemiological studies of complex diseases and their potential relevance for clinical application Although there are some important examples of interactions and applications, the widespread use of the knowledge about G x E interaction for targeted intervention or personalized treatment (pharmacogenetics) is still beyond current means This is due to the fact that convincing evidence and high predictive or discriminative power are necessary conditions for usefulness in clinical practice We attempt to clarify conceptual differences of the term 'interaction' in the statistical and biological sciences, since precise definitions are important for the interpretation of results We argue that the investigation of G x E interactions is more rewarding for the detailed characterization of identified disease genes (ie at advanced stages of genetic research) and the stratified analysis of environmental effects by genotype or vice versa Advantages and disadvantages of different epidemiological study designs are given and sample size requirements are exemplified These issues as well as a critical appraisal of common methodological concerns are finally discussedread more
Citations
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Prediction and Interaction in Complex Disease Genetics: Experience in Type 1 Diabetes
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The gene, environment association studies consortium (GENEVA): maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions
Marilyn C. Cornelis,Arpana Agrawal,John W. Cole,Nadia N. Hansel,Kathleen C. Barnes,Terri H. Beaty,Siiri N. Bennett,Laura J. Bierut,Eric Boerwinkle,Kimberly F. Doheny,Bjarke Feenstra,Eleanor Feingold,Myriam Fornage,Christopher A. Haiman,Emily L. Harris,M. Geoffrey Hayes,John A. Heit,Frank B. Hu,Jae H. Kang,Cathy C. Laurie,Hua Ling,Teri A. Manolio,Mary L. Marazita,Rasika A. Mathias,Daniel B. Mirel,Justin Paschall,Louis R. Pasquale,Elizabeth W. Pugh,John P. Rice,Jenna Udren,Rob M. van Dam,Xiaojing Wang,Janey L. Wiggs,Kayleen Williams,Kai Yu +34 more
TL;DR: The Gene, Environment Association Studies (GENEVA) consortium was initiated to identify genetic variants related to complex diseases; identify variations in gene‐trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes.
References
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Gene–environment interactions in human diseases
David J. Hunter,David J. Hunter +1 more
TL;DR: Suggestions are made for improvements in the study of study design, sample size and genotyping technology, which influence the analysis and interpretation of observed gene–environment interactions.
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Contrasting Genetic Influence of CCR2 and CCR5 Variants on HIV-1 Infection and Disease Progression
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One Degree of Freedom for Non-Additivity
TL;DR: The present writer is usually much more concerned with and worried about non-additivity, and until recently has suffered from the lack of a systematic way to seek it out, and then to measure it.
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