Genetic Test Predicts Response to Weight Loss Medications

Obesity is a chronic and complex disease affecting more than 650 million adults worldwide, driven by a mix of genetic, environmental, and behavioral factors. This complexity explains why people respond so differently to weight-loss interventions, yet treatment decisions often rely on simple measures such as body mass index. Researchers have now demonstrated that biological signals of satiation can be used to predict which medications will be most effective, offering a pathway to more personalized care.

Researchers at the Mayo Clinic (Rochester, MN, USA) have developed a genetic test that estimates an individual’s calories to satiation (CTS), or the amount of food it takes for someone to feel full. The test uses a metric called the Calories to Satiation Genetic Risk Score (CTS-GRS), created by combining variants in 10 genes linked to food intake. Calculated from a blood or saliva sample, this score provides a personalized estimate of satiation thresholds that can be used to guide treatment.

In a study of nearly 800 adults with obesity, participants ate an all-you-can-eat meal until they felt “uncomfortably full,” revealing wide variation in intake, ranging from 140 to more than 2,000 calories. Traditional factors such as body size, fat percentage, hormones, and age only explained a small part of this variation. Applying the CTS-GRS in clinical trials, researchers found that people with a high satiation threshold lost more weight on phentermine-topiramate, while those with a low threshold responded better to liraglutide.

The findings, published in Cell Metabolism, show that one genetic test can predict which patients are most likely to succeed on two different medications, enabling more cost-effective care and better health outcomes. The research team is expanding the test to include responses to semaglutide and incorporating microbiome and metabolome data. They are also working on predictive models for common side effects such as nausea, aiming to further refine and personalize obesity treatments.

“Patients deserve treatments that reflect their biology, not just their body size. This test helps us deliver the right medication to the right person from the start,” said Dr. Andres Acosta, gastroenterologist at Mayo Clinic and senior author of the study. "With one genetic test, we can predict who is most likely to succeed on two different medications. That means more cost-effective care and better outcomes for patients."

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