Genome-wide methylation data improves dissection of the effect of smoking on body mass index

by Carmen Amador, Yanni Zeng, Michael Barber, Rosie M. Walker, Archie Campbell, Andrew M. McIntosh, Kathryn L. Evans, David J. Porteous, Caroline Hayward, James F. Wilson, Pau Navarro, Chris S. Haley Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariat es, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between ind ividuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.
Source: PLoS Genetics - Category: Genetics & Stem Cells Authors: Source Type: research