Mayo Clinic develops a genetic test to personalize the response to weight loss medication

UAE—Researchers at Mayo Clinic have developed a new genetic test that predicts how individuals may respond to popular weight loss medications, including GLP-1 drugs.

The innovative test measures a biological feature known as “calories to satiation” (CTS), which refers to the amount of food a person needs to feel full.

By assessing this unique trait, the test aims to guide the selection of the most effective treatment for each patient.

According to the study published in Cell Metabolism, this technology represents a major step toward more personalized obesity care.

Dr. Andres Acosta, M.D., Ph.D., a gastroenterologist and senior author of the study, emphasized that patients deserve therapies tailored to their biology, not just their body size.

He noted that the test allows doctors to identify the right medication for each person from the start, making treatment both more effective and cost-efficient.

Obesity remains a complex and chronic condition affecting more than 650 million adults globally.

It results from a combination of genetic, environmental, and behavioral factors, which help explain why people respond differently to various weight loss interventions.

Despite this complexity, most current treatment strategies still rely on body mass index (BMI)—a simplistic measure that does not account for deeper biological factors influencing hunger and metabolism.

To better understand these underlying processes, Dr. Acosta’s team focused on satiation, the body’s physiological cue signaling fullness.

In earlier research conducted in 2021, they classified obesity into several phenotypes based on eating patterns.

For instance, individuals with the “hungry brain” phenotype tend to eat large meals, while those with the “hungry gut” phenotype consume typical meal sizes but snack frequently during the day.

In their latest study, the researchers invited nearly 800 adults with obesity to an all-you-can-eat experiment featuring lasagna, pudding, and milk until they felt “Thanksgiving full.”

 The range of calorie intake was striking: participants consumed anywhere between 140 and 2,000 calories, with men generally eating more than women.

Although factors like body weight, fat percentage, waist-to-hip ratio, age, and appetite hormones such as ghrelin and leptin played minor roles, none could fully explain the wide variation in satiation.

This led the team to investigate genetic factors.

Using machine learning, they identified 10 genes linked to food intake and combined them into a single measure called the Calories to Satiation Genetic Risk Score (CTS-GRS).

Derived from a simple blood or saliva sample, the CTS-GRS offers a personalized estimate of a person’s satiation threshold.

The team then tested this metric in clinical trials involving two FDA-approved medications: phentermine-topiramate (Qsymia), a first-generation drug, and liraglutide (Saxenda), a GLP-1 medication.

Results showed that individuals with a high satiation threshold—those who typically eat larger portions—responded better to phentermine-topiramate, which helps reduce meal size.

Conversely, people with a low satiation threshold—those who tend to eat more frequently—responded more effectively to liraglutide, which suppresses hunger and curbs frequent eating.

“With one genetic test, we can predict who is most likely to succeed with two different medications,” explained Dr. Acosta.

He added that such precision allows for more personalized care and improved patient outcomes.

Mayo Clinic researchers are now extending their work to include semaglutide, another GLP-1 medication marketed as Ozempic and Wegovy, with results expected soon.

The team is also expanding the CTS-GRS model to include microbiome and metabolome data while developing predictive tools for common side effects like nausea and vomiting.

The CTS-GRS technology has been licensed to Phenomix Sciences, Mayo Clinic’s innovation partner, and is already being used in more than 300 clinics across the United States.