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Open AccessJournal ArticleDOI

Gene-environment interactions for complex traits: Definitions, methodological requirements and challenges

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 discussed

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Journal ArticleDOI

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.
Journal ArticleDOI

Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical consequences.

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
References
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Journal ArticleDOI

Gene–environment interactions in human diseases

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.
Journal ArticleDOI

Contrasting Genetic Influence of CCR2 and CCR5 Variants on HIV-1 Infection and Disease Progression

TL;DR: Genetic association analysis of five acquired immunodeficiency syndrome (AIDS) cohorts revealed that although CCR2-64I exerts no influence on the incidence of HIV- 1 infection, HIV-1-infected individuals carrying the C CR2- 64I allele progressed to AIDS 2 to 4 years later than individuals homozygous for the common allele.
Journal ArticleDOI

Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials.

TL;DR: Examining the architecture of the entire set of subgroups within a trial, analyzing similar subgroups across independent trials, and interpreting the evidence in the context of known biologic mechanisms and patient prognosis are recommended.
Journal ArticleDOI

One Degree of Freedom for Non-Additivity

John W. Tukey
- 01 Sep 1949 - 
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.
Journal ArticleDOI

Balancing life-style and genomics research for disease prevention

TL;DR: A balanced approach to genetic research for disease prevention should provide the best data to make informed choices about the most effective means to prevent disease.
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