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
TL;DR: These two topics concern the use and interpretation of statistical models for risk of diseases with several, perhaps many, etiological risk factors, and were both the subject of lively debate some 30 to 40 years ago when such models first came into widespread use in epidemiology.
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Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical consequences.
J. Carlos Pastor,Jimena Rojas,Jimena Rojas,Salvador Pastor-Idoate,Salvador Pastor-Idoate,Salvatore Di Lauro,Lucia Gonzalez-Buendia,Santiago Delgado-Tirado +7 more
TL;DR: Inflammation is one of the major components of PVR, and new genetic biomarkers that have the potential to predict its development are described, including one directed towards neuroprotection, which can also be useful for preventing visual loss after any RD.
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The evidence for a role of B cells in multiple sclerosis
TL;DR: There is no longer doubt that B cells are relevant to the etiology and pathogenesis of MS and elucidating the role of B cells in MS will be a fruitful strategy for disease prevention and treatment.
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Genetic screening for the risk of type 2 diabetes: worthless or valuable?
TL;DR: It is demonstrated that first-degree family history is associated with twofold increased risk of future type 2 diabetes, and advances in genotyping technology during the last 5 years have facilitated rapid progress in large-scale genetic studies.
Journal ArticleDOI
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.
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