New genomic technique reveals obesity gene variants

Nov 29, 2010

Obesity is highly heritable, but so far genetic association studies have only explained a small fraction of this heritability. Now, in a study published in BioMed Central's open access journal Genome Biology, researchers have identified DNA variants in two nervous system genes that are associated with an excessively high BMI.

Kelly Frazer and colleagues from UC San Diego, Scripps Translational Science Institute and Sanofi-Aventis used a new approach that is likely to become popular in searching for hidden : the resequencing of a candidate area of the genome in a large number of individuals followed by screening for within this region that are associated with the disease or condition in question.

Frazer said, "We sequenced two intervals encoding the enzymes FAAH and MGLL which modulate the levels of endocannabinoids present in the brain and peripheral tissues that are involved in the regulation of and appetite. The level of these endocannabinoids is high in obese patients, and thus these two enzymes provide strong candidates to examine for a genetic association with ".

In these two genes, the researchers were able to identify four regions associated with BMI: the FAAH promoter, MGLL promoter, MGLL intron 2, and an enhancer in the MGLL intron 3. Further testing of one of these regions revealed rare variants that were associated with increased levels of endocannabinoids in the plasma, which is consistent with previous findings.

According to Frazer, "This is one of the first studies to use the new sequencing technologies to link rare and low frequency variants to a complex trait such as obesity and will be of particular interest to understand more comprehensively the role of inheritance in obesity, a rapidly rising serious health issue across the world".

Explore further: Changes in scores of genes contribute to autism risk

More information: Population sequencing of two endocannabinoid metabolic genes identifies rare and common regulatory variants associated with extreme obesity and metabolite level, Olivier Harismendy, Vikas Bansal, Gaurav Bhatia, Masakazu Nakano, Michael Scott, Xiaoyun C Wang, Colette Dib, Edouard Turlotte, Jack C Sipe, Sarah S Murray, Jean-Francois Deleuze, Vineet Bafna, Eric J Topol and Kelly A Frazer, Genome Biology (in press), genomebiology.com/

add to favorites email to friend print save as pdf

Related Stories

Large-scale analysis identifies 32 genetic loci for obesity

Oct 11, 2010

An international team of researchers has identified 18 new genetic loci associated with obesity assessed by BMI, and confirmed a link between obesity and 14 previously known loci. Almost 250,000 individuals were included ...

Brain background to body mass

Dec 14, 2008

A genetic study of more than 90,000 people has identified six new genetic variants that are associated with increased Body Mass Index (BMI), the most commonly used measure of obesity. Five of the genes are known to be active ...

Human Genome Project is 10: Where are we now?

Mar 02, 2010

"It's hard to think back and remember how we worked then. We were scrabbling around in the dark," says Professor Mark McCarthy of the Oxford Centre for Diabetes, Endocrinology and Metabolism [OCDEM], recalling ...

Recommended for you

Changes in scores of genes contribute to autism risk

Oct 29, 2014

Small differences in as many as a thousand genes contribute to risk for autism, according to a study led by Mount Sinai researchers and the Autism Sequencing Consortium (ASC), and published today in the journal Nature.

Dozens of genes associated with autism in new research

Oct 29, 2014

Two major genetic studies of autism, led in part by UC San Francisco scientists and involving more than 50 laboratories worldwide, have newly implicated dozens of genes in the disorder. The research shows ...

Genetic link to kidney stones identified

Oct 29, 2014

A new breakthrough could help kidney stone sufferers get an exact diagnosis and specific treatment after genetic links to the condition were identified.

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.