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Meta-Analyses Uncover Variants Involved in Obesity and Fat Distribution

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – A pair of meta-analyses appearing in the early online version of Nature Genetics this week provide a peek at some of the genetic factors underlying fat distribution and obesity — and suggest the traits stem from different sets of common variants.

"From a health perspective, the distinctions drawn here between [body mass index] and [waist-to-hip ratio] are steps toward better understanding the role of these two traits as risk factors for a range of diseases," Decode Genetics CEO Kari Stefansson, who was co-corresponding author on both papers, said in a statement.

For the first of these studies, members of an international research team known as the Genetic Investigation of Anthropometric Traits, or GIANT, consortium used data from 32 genome-wide association studies involving more than 77,000 individuals of European descent to track down genetic loci linked to waist-to-hip ratio.

Through the meta-analysis and validation testing using data for 113,636 more individuals, the researchers found 14 genetic loci associated with waist-to-hip ratio, including one locus detected through past research and 13 new loci.

Together, all 14 loci seem to account for just over 1 percent of waist-to-hip ratio variation, though seven loci seem to have a stronger influence in women than in men.

"By finding genes that have an important role in influencing fat distribution and the ways in which that differs between men and women, we hope to home in on the crucial underlying biological processes," co-corresponding author Cecilia Lindgren, a researcher with the Wellcome Trust Center for Human Genetics and the University of Oxford, said in a statement.

While those involved in the study emphasized that additional genetic and clinical studies are needed to better understand the functional roles of the newly detected variants, they say such findings may eventually offer insights into treating health problems tied to certain fat accumulation patterns.

"Efforts to tackle overall obesity through therapeutic or lifestyle-base modulation of overall energy balance have proved extremely challenging to implement, and the manipulation of processes associated with more beneficial patterns of fat distribution offers an alternative perspective for future drug discovery," the researchers concluded.

Meanwhile, in a second Nature Genetics paper, GIANT consortium researchers used data for nearly a quarter of a million individuals to do a meta-analysis and validation studies aimed at finding common variants that increase susceptibility to obesity. In the process, they not only verified a role for 14 previously detected BMI-related loci, but also uncovered 18 more.

"One of the most exciting parts of this work is that most of the BMI-associated variants identified are in or near genes that have never before been connected to obesity," Massachusetts General Hospital and Broad Institute researcher Elizabeth Speliotes said in a statement. "We are discovering that the underlying biological underpinnings of obesity are many, varied, and largely uncharacterized."

Speliotes was co-lead author on the BMI paper and co-author on the accompanying fat distribution genetic study.

Each of the variants detected slightly increases an individual's overall risk of obesity, the researchers explained, although the variants' predictive value so far is fairly modest.

The team noted that there are likely hundreds of yet undetected common genetic loci influencing BMI. "These results suggest that much of the biology that underlies obesity remains to be uncovered and that GWAS may provide an important entry point for investigation," they wrote.