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Human Molecular Genetics 2006 15(Review Issue 2):R124-R130; doi:10.1093/hmg/ddl215
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Genetics of obesity and the prediction of risk for health

Andrew J. Walley1,*, Alexandra I.F. Blakemore1 and Philippe Froguel1,2

1 Section of Genomic Medicine, Division of Medicine, Imperial College London, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK and 2 CNRS UMR8090-Institute of Biology, Pasteur Institute, Lille, France

* To whom correspondence should be addressed. Tel: +44 (0) 2083838311; Fax: +44 (0) 2083838577; Email: a.walley{at}imperial.ac.uk

Received July 26, 2006; Accepted August 1, 2006

Obesity has always existed in human populations, but until very recently was comparatively rare. The availability of abundant, energy-rich processed foods in the last few decades has, however, resulted in a sharp rise in the prevalence of obesity in westernized countries. Although it is the obesogenic environment that has resulted in this major healthcare problem, it is acting by revealing a sub-population with a pre-existing genetic predisposition to excess adiposity. There is substantial evidence for the heritability of obesity, and research in both rare and common forms of obesity has identified genes with significant roles in its aetiology. Application of this understanding to patient care has been slower. Until very recently, the health risks of obesity were thought to be well understood, with a straightforward correlation between increasing obesity and increasing risk of health problems such as type 2 diabetes, coronary heart disease, hypertension, arthritis and cancer. It is becoming clear, however, that the location of fat deposition, variation in the secretion of adipokines and other factors govern whether a particular obese person develops such complications. Prediction of the health risks of obesity for individual patients is not straightforward, but continuing advances in understanding of genetic factors influencing obesity risk and improved diagnostic technologies mean that the future for such prediction is looking increasingly bright.


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