Genetic data explored to help tailor obesity treatment, personalize care
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SAN DIEGO — The future of obesity management may include using personal genetic profiles to develop individualized prevention strategies and personalized treatment plans, according to a speaker at ObesityWeek 2022.
During a presentation at the meeting’s presidential plenary, Lee M. Kaplan, MD, PhD, director of the Obesity, Metabolism and Nutrition Institute at Massachusetts General Hospital, said some research has revealed a link between a person’s genes and obesity outcomes, but much more study is needed to make using genetic information relevant in practice.
“The unmet needs for genetic guidance in obesity are phenotyping that distinguishes subtypes more clearly, a greater understanding of the phenotypic spectrum, comparative studies to make assessments with multiple bariatric and surgical procedures, and statistically significant and reproducible predictors of response to nonsurgical therapies,” Kaplan said.
Tailoring obesity drugs and bariatric surgery
Researchers have shown how at least one drug therapy tailored toward people with a specific genetic phenotype of obesity can lead to weight loss. In findings published in The New England Journal of Medicine, setmelanotide (Imcivree, Rhythm Pharmaceuticals), a melanocortin-4 receptor agonist, was associated with profound weight loss for two patients with proopiomelanocortin (POMC)-deficient obesity.
“This was the first drug that led to a 25% weight loss, because what you’re doing is replacing what is missing and not trying to recalibrate an entire regulatory system,” Kaplan said.
Setmelanotide could possibly address other single gene and polygenetic diseases, Kaplan said. However, he added that “garden-variety” obesity, as opposed to monogenic or syndromic obesity, is actually a heterogeneous group of disorders. This leads to a wide variety of responses to diet, drug therapy, devices and bariatric surgery.
A study published in The Journal of Clinical Endocrinology & Metabolism revealed bariatric surgery outcomes are more similar between people who share more genes. In the study, the difference in excess weight loss for adults undergoing Roux-en-Y gastric bypass surgery was greater among adults who were not genetically related and lowest among four pairs of identical twins who shared 100% of the same genes.
Genetics and predicting obesity risk
Genetic information could potentially help providers predict who is at highest risk for developing obesity. In a study published in Cell, researchers examined whether genome-wide polygenic scores can predict the development of obesity. The researchers found that people in the top 2.5-percentile for highest genome-wide polygenic scores had a higher prevalence of obesity than the remainder of the cohort, and one-third of adults with a BMI of 40 kg/m2 or higher were in the top decile for genome-wide polygenic score.
Additionally, data from 3,722 adolescents in the Framingham Offspring Study revealed those who were in the top decile for obesity genome-wide polygenic score were more likely to develop obesity over 25 years of follow-up than those in the lower deciles.
“At birth, there’s very little predictive value of this polygenic score,” Kaplan said. “As these individual groups of patients matured in this longitudinal study, you get more and more tendency for the polygenic score to predict obesity. By the time you get to age 8 years, it’s very predictive, and by the time you get to age 18 years, it’s very highly predictive.”
Kaplan noted that despite the findings, genome-wide polygenic scores do not yet have clinical relevance, and outside of studies on bariatric surgery, there are no strong predictive data linking genetics and individual outcomes with obesity drugs or lifestyle therapies. However, Kaplan said, there are several potential uses for genetic information in obesity care, including the ability to predict therapy efficacy, identification of rare disease subtypes, the development of personalized prevention strategies, and the identification of disease mechanisms and new therapeutic targets.
Several consortiums have been formed to identify genetic predictors of treatment outcomes, Kaplan said. Genetic biobanking is becoming standard in large, phase 3 trials for new anti-obesity medications, and deconvolution of genome-wide polygenic obesity scoring systems is being performed to identify genes that contribute most to the disease.
“The opportunity for true precision obesity medicine is likely just around the corner,” Kaplan said. “It’s far enough away that we don’t have anything to use, as much as we’d like to, today, but it’s close enough that we see the pathway to get there.”
References:
- Hatoum IJ, et al. J Clin Endocrinol Metab. 2011;doi:10.1210/jc.2011-1130.
- Khera AV, et al. Cell. 2019;doi:10.1016/j.cell.2019.03.028.
- Kühnen, P, et al. N Engl J Med. 2016;doi:10.1056/NEJMoa1512693.
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Kaplan L. Update on the use of genetic information to tailor obesity treatment. Presented at: ObesityWeek; Nov. 1-4, 2022; San Diego.
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