New Test Predicts Optimal Responders to Weight-Loss Medications

Despite the popularity of the new generation of weight-loss medications such as Wegovy and Zepbound, individual responses to these drugs vary.

At the recent Digestive Disease Week conference in Washington, Mayo Clinic’s associate professor of medicine, Dr. Andres Acosta, unveiled a genetic test he developed that can predict which individuals are most likely to experience positive outcomes from semaglutide (Wegovy).

Named , the test, developed by a company co-founded by Acosta, Phenomix, categorizes individuals into distinct types of weight gain based on a combination of genetic and other factors. Acosta has identified approximately two dozen genes linked to obesity and over 6,000 variants of these genes, enabling him to classify people struggling with weight gain into four distinct categories:

  • Hungry Brain: This group experiences a constant feeling of hunger regardless of their food intake.
  • Hungry Gut: Individuals in this category feel full after eating, but their hunger returns within an hour.
  • Emotional Hungry: These individuals use food as a coping mechanism or reward, ignoring their physiological hunger cues.
  • Slow Burn: This group has a decreased ability to burn calories.

In his latest presentation, Acosta reported that the MyPhenome Hungry Gut test can predict semaglutide responsiveness with 75% accuracy (results not yet published in a journal).

“This has significant implications—firstly for the patient, as it eliminates trial and error, and secondly, as a physician, I want to know which patients will respond because I am asking them to spend $1,000 a month or pay a substantial copay if their insurance covers the drugs,” he said. Identifying individuals who will benefit from medications like Wegovy could also address accessibility issues by directing only the most suitable candidates to these treatments. “It has the potential to revolutionize obesity management,” he added.

The study was conducted on a small scale, involving 84 overweight or obese individuals, some with diabetes, who provided saliva samples for genetic analysis via the MyPhenome test and completed a questionnaire about their eating habits. All participants received semaglutide for a year, with most reaching the maximum dosage. Since the Hungry Gut profile relates to appetite and semaglutide suppresses appetite, Acosta found that individuals in this category tended to lose the most weight on semaglutide. Of the 84 participants, 51 (approximately 60%) were classified as Hungry Gut.

“After a year, patients with Hungry Gut lost 19.5% of their body mass compared to 10% for those who were not Hungry Gut,” Acosta explained. “That’s almost double the weight loss. For the first time, we can identify the optimal responders.”

Acosta and his team emphasize the need for larger studies to replicate these initial findings before the test can be widely adopted. Currently, doctors can order the MyPhenome test for patients through Phenomix’s website, and it can be used as an additional tool in conjunction with other information to assist patients and doctors in determining the suitability of the medication.

“My aspiration is to approach chronic diseases like obesity with the same precision and personalization that we use in cancer treatment,” Acosta said about the future of the test. It’s also conceivable that as newer weight loss medications are approved, pharmaceutical companies will develop companion screening tests to identify individuals who will most likely benefit from their products. Insurance providers may also rely on such tests to make reimbursement decisions, ensuring that patients receive the most appropriate treatments.

Acosta believes that the test’s potential extends beyond semaglutide. He suggests that some older weight-loss medications may be equally effective for certain individuals, but until now, doctors have relied on a trial-and-error approach when prescribing them. With more precise methods of matching patients to the medications that work best for them, the efficacy of existing weight-loss drugs could be optimized for each patient.