New genetic test can help predict how people will respond to weight-loss medications

Mayo Clinic researchers have developed a genetic test that can help predict how people will respond to weight loss medications such as GLP-1s.

The test estimates an individual’s calories to satiation (CTS) – how much food it takes for a person to feel full – and links this biological trait to treatment success. The findings, published in Cell Metabolism, represent a promising step toward more personalized and effective treatments for people living with obesity.

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.”

Andres Acosta, M.D., Ph.D., gastroenterologist at Mayo Clinic and senior author of the study

Beyond body size

Obesity is a chronic, complex disease that affects more than 650 million adults worldwide. It stems from a mix of genetic, environmental and behavioral factors that vary from person to person. This complexity helps explain why people respond differently to weight-loss interventions. Yet treatment decisions often rely on simple measures such as body mass index (BMI) rather than the biological processes that drive weight gain and weight loss.

To uncover these processes, Dr. Acosta has focused on satiation, the physiological signal that tells the body it has eaten enough. In 2021, he and his colleagues defined a series of obesity phenotypes to describe eating patterns. For example, some people with obesity tend to eat very large meals (“hungry brain”), while others may eat average portions but snack frequently throughout the day (“hungry gut”).

In this study, the researchers studied satiation in nearly 800 adults with obesity by inviting them to partake in an all-you-can-eat meal of lasagna, pudding and milk until they felt “Thanksgiving full.” The results revealed striking variation: Some participants stopped after 140 calories whereas others consumed more than 2,000. On average, men consumed more calories than women.

The team investigated possible explanations for this variability. Several factors, including body weight, height, percentage of body fat, waist-to-hip ratio and age – as well as appetite-related hormones such as ghrelin and leptin – played a small role. But none accounted for the huge range in calorie intake. So the researchers turned to genetics.

Using machine learning, the researchers combined variants in 10 genes known to influence food intake into a single metric called the CTS-GRS (Calories to Satiation Genetic Risk Score). The score, calculated from a blood or saliva sample, provides a personalized estimate of a person’s expected satiation threshold.

Matching genes to medications

Mayo Clinic researchers then calculated this CTS-GRS metric in clinical trials of two FDA-approved medications: a first-generation weight loss drug, phentermine-topiramate (brand name Qsymia), and a newer GLP-1 drug, liraglutide (Saxenda). They found that:

People with a high satiation threshold lost more weight on phentermine-topiramate. This drug may help control portion size and reduce large-meal overeating (hungry brain).
People with a low satiation threshold responded better to liraglutide. This drug may reduce overall hunger and frequency of eating (hungry gut).

“With one genetic test, we can predict who is most likely to succeed on two different medications,” says Dr. Acosta. “That means more cost-effective care and better outcomes for patients.”

The team has conducted additional studies to predict response to semaglutide, another GLP-1 medication (sold under the brand names Ozempic and Wegovy), and results are expected soon. They are working to expand the test by incorporating data from the microbiome and metabolome, as well as developing models to predict common side effects such as nausea and vomiting.