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Genetic studies have shown that obesity risk is heritable and that, of the many common variants now associated with body mass index, those in an intron of the fat mass and obesity associated (FTO) gene have the largest effect. The size of the UK Biobank, and its joint measurement of genetic, anthropometric and lifestyle variables, offers an unprecedented opportunity to assess gene-by-environment interactions in a way that accounts for the dependence between different factors. We jointly examine the evidence for interactions between FTO (rs1421085) and various lifestyle and environmental factors. We report interactions between the FTO variant and each of: frequency of alcohol consumption(P=3.0X10-4); deviations from mean sleep duration (P=8.0x10-4); overall diet (P=5.0x10-6), including added salt (P=1.2x10-3); and physical activity (P=3.1x10-4).
Young AI, Wauthier F and Donnelly P (2016) Multiple novel gene-by-environment interactions modify the effect of FTO variants on body mass index, Nature Communications 7:12724 DOI: 10.1038/ncomms12724
Statistical methods to study the interplay between genetic and lifestyle factors using large-scale genetic data and a wide variety of lifestyle factors.
This research project aims to develop statistical methods for large-scale genome-wide association studies that include a wide variety of lifestyle factors. We will combine genetic and non-genetic data using three main approaches: we will study whether genetics can predict important lifestyle factors (such as smoking behaviour, diet, exercise, and alcohol consumption); we will test for interactions between genetic and environmental factors; we will study the genetic architecture of quantitative traits (such as obesity-related traits, bone density measures, and red blood cell measures) with increased statistical power. A major goal of this research is to develop novel statistical methods for analysing large-scale genetic data combined with a large number of lifestyle variables. The methods we develop will allow us and other researchers to use the UK Biobank resource to examine how behavioral traits and gene-environment interactions contribute to medically relevant traits, which will provide insights into human biology and therefore human health. This research will examine genetic markers for their potential role in explaining a series of traits and lifestyle factors. Specifically, we will develop and apply statistical methods for examining associations between genetic factors and a wide variety of non-genetic factors, while taking into account the correlations between the non-genetic factors themselves. Full cohort