Gene-Environment-Wide Association Studies: Emerging Approaches

By Duncan C. Thomas. Nature reviews genetics, 2010

707 citations recorded by the source corpus.

Despite the yield of recent genome-wide association (GWA) studies, the identified variants explain only a small proportion of the heritability of most complex diseases. This unexplained heritability could be partly due to gene–environment (G×E) interactions or more complex pathways involving multiple genes and exposures. This Review provides a tutorial on the available epidemiological designs and statistical analysis approaches for studying specific G×E interactions and choosing the most appropriate methods. I discuss the approaches that are being developed for studying entire pathways and available techniques for mining interactions in GWA data. I also explore methods for marrying hypothesis-driven pathway-based approaches with 'agnostic' GWA studies.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1a0a16f3a8943f13fae14f55b789e7a4f5d313f5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

In Molecular Biology

Citations in the corpus

A Tutorial on Interaction (2014, background): “Recently there has also been considerable interest in the challenges of assessing interaction in genome-wide-association studies when multiple comparison problems are present (Kraft, 2004; Gayan et al., 2008; Khoury and Wacholder, 2009; Murcray et al., 2009; Pierce and Ahsan, 2010; Thomas, 2010).”
Applications of next-generation sequencing to the study of biological invasions (2015, background): “Three popular approaches are genome-wide selection scans (GWSS) (Storz, 2005), genome-wide association scans (GWAS) (Hirschhorn and Daly, 2005) and genetic-environment association scans (GEAS) (Thomas, 2010).”
REVIEW: PART OF A HIGHLIGHT ON BREEDING STRATEGIES FOR FORAGE AND GRASS IMPROVEMENT Will genomic selection be a practical method for plant breeding? (2012, background): “Recently, Thomas (2010) reviewed potent approaches for gene–environment–wide association studies, i.e. mining GW association data for G × E interactions.”
Modulation of Genetic Associations with Serum Urate Levels by Body-Mass-Index in Humans (2015, background): “Gene by environment (GxE) detection requires a larger sample-size than that required for the detection of main effects of comparable magnitude [29] (a rule of thumb proposed for case control design is a four time larger study [30]).”
The advantages and limitations of trait analysis with GWAS: a review (2013, background): “The contribution of a gene to a trait may vary depending on the environmental conditions, and methods to identify such gene-by-environment (GxE) interactions have been suggested [66].”