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Gene variant appears to predict weight loss after gastric bypass

Date:
May 2, 2013
Source:
Massachusetts General Hospital
Summary:
Researchers have identified a gene variant that helps predict how much weight an individual will lose after gastric bypass surgery, a finding with the potential both to guide treatment planning and to facilitate the development of new therapeutic approaches to treating obesity and related conditions like diabetes.

More than one-third of adults in the United States are obese, and some of these individuals undergo gastric bypass surgery to shed the extra pounds. A genome-wide association study published by Cell Press May 2nd in The American Journal of Human Genetics reveals that the amount of weight loss after this surgery can be predicted in part by a DNA sequence variation found on chromosome 15. The findings explain why the success of gastric bypass surgery varies so widely and could help clinicians identify those who would benefit the most from this type of surgery.
Credit: AJHG, Hatoum et al.

Massachusetts General Hospital researchers have identified a gene variant that helps predict how much weight an individual will lose after gastric bypass surgery, a finding with the potential both to guide treatment planning and to facilitate the development of new therapeutic approaches to treating obesity and related conditions like diabetes. The report, published online in The American Journal of Human Genetics, is the first to identify genetic predictors of weight loss after bariatric surgery.

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"We know now that bypass surgery works not by physically restricting food intake but primarily through physiological effects -- altering the regulation of appetite to decrease hunger and enhance satiety and increasing daily energy expenditure," said Lee Kaplan, HMS associate professor of medicine at Mass General and director of the hospital's Obesity, Metabolism and Nutrition Institute. He is a senior author of the report. "Genetic factors appear to determine a patient's response to gastric bypass, and the identification of markers that predict postoperative weight loss could provide important insight into those physiological mechanisms."

The research team conducted genome-wide association studies of more than 1,000 patients who had bypass surgery at Mass General from 2000 to 2011, analyzing almost 2 million gene sites for associations between specific variants and the percentage of weight lost after surgery. One specific variant at a site on chromosome 15 was most closely associated with weight loss. Individuals with two copies of the beneficial version of the gene lost an average of almost 40 percent of their presurgical weight, while those with only one copy lost around 33 percent. The single individual in the study group who had no copies of the beneficial variant lost less than 30 percent of presurgical weight.

Expression of one of the genes closest to the site of this variant was also able to predict the percentage of weight lost. In addition, experiments in a mouse model of gastric bypass indicated that expression of the corresponding version of that human gene, as well as another gene adjacent to the variant site, was altered by bypass surgery. Additional gene variants not as strongly associated with the response to bypass surgery are candidates for further study in larger groups of patients.

Two predictive models developed by Kaplan and his team have had promising initial results. One of these combines the chromosome 15 genetic variant with clinical factors such as age, gender, the presence of diabetes and exercise behaviors to predict surgical outcomes; the other includes 12 additional gene variants the investigators are studying to determine their usefulness in treatment planning.

Notably, none of the predictive gene sites identified in this study is involved in pathways previously known to influence the development of obesity, suggesting that different genes contribute to the benefits of bypass. Development of drugs that target the activity of those genes might produce some of the same benefits without the need for surgery, Kaplan said.

"The fact that genetics appears to play such an important role in how well bypass surgery works in an individual patient gives us even more evidence that obesity results from dysfunction of the biological mechanisms that regulate fat mass and body weight and not solely from aberrant behavior or limited willpower," he adds. "Identifying the involved genes opens up the potential for new classes of antiobesity therapies that mimic or exploit the molecular mechanisms so effectively used by gastric bypass."

The study was supported by National Institutes of Health grants DK093257, DK088661 and DK090956, along with grants from Merck Research Laboratories and Ethicon Endo-Surgery.


Story Source:

The above story is based on materials provided by Massachusetts General Hospital. The original article was written by Sue McGreevey. Note: Materials may be edited for content and length.


Journal Reference:

  1. Ida J. Hatoum, Danielle M. Greenawalt, Chris Cotsapas, Mark J. Daly, Marc L. Reitman, Lee M. Kaplan. Weight Loss after Gastric Bypass Is Associated with a Variant at 15q26.1. The American Journal of Human Genetics, 2013; 92 (5): 827 DOI: 10.1016/j.ajhg.2013.04.009

Cite This Page:

Massachusetts General Hospital. "Gene variant appears to predict weight loss after gastric bypass." ScienceDaily. ScienceDaily, 2 May 2013. <www.sciencedaily.com/releases/2013/05/130502131901.htm>.
Massachusetts General Hospital. (2013, May 2). Gene variant appears to predict weight loss after gastric bypass. ScienceDaily. Retrieved November 27, 2014 from www.sciencedaily.com/releases/2013/05/130502131901.htm
Massachusetts General Hospital. "Gene variant appears to predict weight loss after gastric bypass." ScienceDaily. www.sciencedaily.com/releases/2013/05/130502131901.htm (accessed November 27, 2014).

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May 2, 2013 — A genome-wide association study reveals that the amount of weight loss after gastric bypass surgery can be predicted in part by a DNA sequence variation found on chromosome 15. The findings explain ... read more

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