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Omics versus Questionnaires: Using methylation data to assess the environmental impact of smoking on obesity-related traits

By Carmen Amador, Yanni Zeng, Rosie M Walker, Archie Campbell, Andrew M McIntosh, Kathryn Evans, David J Porteous, Caroline Hayward, James F Wilson, Pau Navarro, Chris Haley

Posted 09 Oct 2020
bioRxiv DOI: 10.1101/2020.10.08.329672

Variation in complex traits related to obesity, such as body weight and body mass index, has a genetic basis with heritabilities between 40 and 70%. Nonetheless, the so-called global obesity pandemic is usually associated with environmental changes related to diet, lifestyle, and sociocultural and socioeconomic changes. However, most genetic studies do not include all relevant environmental covariates so their contribution, alongside genetics, to variation in obesity-related traits can not be assessed. Similarly, some studies have described interactions between a few individual genes linked to obesity and different environmental variables but the total contribution to differences between individuals is unknown. In this study we explored the effect of smoking and gene-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain by modelling them using self-reported data and a proxy created using methylation data. Our results indicate that exploiting omic measures as proxies for environmental variation can improve our models for complex traits such as obesity and can be used as a substitute of environmental measures when they are not available or jointly to improve their accuracy. ### Competing Interest Statement The authors have declared no competing interest.

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