Despite their impact on human complex traits and diseases, gene–environment interactions (G × E) remain challenging to assess statistically. The authors review considerations for the conceptualization, methodology, interpretation and reporting of G × E studies, and provide recommendations on how to avoid common pitfalls.
STATGEN 2024 talk
Distinct explanations underlie gene-environment interactions in the UK Biobank.
Arun Durvasula
Genetic effects across the genome may exhibit context dependence
- European vs. East Asian genetic correlation is less than 1 across a wide range of traits.
- Hinting at polygenic GxE
GxE can arise through different scenarios
- Imperfect genetic correlation
- Varying genetic variance
- Proportional amplification
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STATGEN 2024 talk
A New Test for Trait Mean and Variance Detects Unreported Loci for Blood Pressure Variation
Todd L. Edwards
If there is a GxE, then variance of Y differs by genotype.
If we don't know E, we can model both the mean & variance as function of the main predictor.
Known a long time - e.g. Waddington (1942) Canalization of development and the inheritance of acquired characters.
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We investigated #GxE for caffeine in vascular endothelial cells with a #MPRA for >40,000 genetic variants, characterized the regulatory activity response, and linked them to cardiovascular health.
We characterized the TFs for response to caffeine, identified >7,000 GxE, validated fine-mapped eQTLs in artery and characterized mechanisms for the role of #caffeine in #cardiovascular disease.
Charrvein
Jason H. Moore, Ph.D.
Daniel E. Weeks
NIOO-KNAW
Roger Pique-Regi