Mayo Clinic researchers have created a genetic test that forecasts how individuals respond to weight-loss medications, including GLP-1 drugs. The test measures a person’s calories to satiation (CTS)—the amount of food needed to feel full—and links this biological indicator to treatment effectiveness. Published in Cell Metabolism, the study marks a significant advance toward personalized obesity treatment.
Understanding Obesity Beyond Body Size
Obesity affects over 650 million adults worldwide and arises from a complex interplay of genetics, environment, and behavior. This diversity explains why weight-loss treatments vary in effectiveness but current approaches often rely on simple metrics like BMI instead of the underlying biology.
Research led by Dr. Andres Acosta, a Mayo Clinic gastroenterologist, focuses on satiation, the physiological cue signaling fullness. His earlier work categorized obesity types based on eating behaviors, such as “hungry brain”—large meals—and “hungry gut”—frequent snacking.
In this study, nearly 800 adults with obesity ate freely from a meal until they felt full. Calories consumed ranged widely—from as few as 140 to over 2,000—with men generally eating more than women. Factors like body weight, age, and appetite hormones explained little of this variation, prompting a genetic analysis.
Genetic Insights Inform Medication Choice
The team used machine learning to create the Calories to Satiation Genetic Risk Score (CTS-GRS), combining variants in 10 genes linked to food intake. This score, derived from blood or saliva, predicts an individual’s satiation threshold.
The researchers tested CTS-GRS against responses to two FDA-approved drugs: phentermine-topiramate (Qsymia) and liraglutide (Saxenda). Findings showed:
Individuals with a high satiation threshold lost more weight on phentermine-topiramate, which may help reduce overeating of large meals (“hungry brain”).
Those with a low satiation threshold responded better to liraglutide, which may decrease overall hunger and snacking (“hungry gut”).
Dr. Acosta highlights that this genetic test can guide physicians in prescribing the most effective medication upfront, improving outcomes and cost efficiency.
Future Directions
Ongoing studies aim to predict responses to semaglutide (Ozempic, Wegovy) using CTS-GRS. Researchers also plan to enhance the test by integrating microbiome and metabolome data and creating models to foresee side effects like nausea.
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