A groundbreaking study by Mayo Clinic has revealed that genetic testing can predict which patients are most likely to experience nausea when taking GLP-1 agonist medications such as Wegovy and Zepbound. Led by obesity expert Dr. Andres Acosta, the research tackles one of the most significant barriers to successful treatment with these popular weight-loss drugs.
Nausea, affecting up to 70% of GLP-1 users, is the primary reason patients discontinue these medications. The study analyzed genetic data from 110 participants to determine if a machine learning-assisted genetic risk score (CTSGRS) could identify patients at higher risk of experiencing side effects.
The results were striking. Patients with a high-CTSGRS who received liraglutide were significantly more likely to develop nausea (68%) compared to those with a low-CTSGRS (30%)—representing an odds ratio of 5.0. This pattern was not observed in patients receiving placebo.
"These findings have immediate and potentially transformative implications for how these blockbuster drugs are prescribed and for the development of new, more effective treatments with better tolerability," noted Mayo Clinic researchers in the paper titled "A GENETIC RISK SCORE ASSOCIATED WITH NAUSEA RESULTING FROM GLP-1 AGONIST TREATMENT."
Additional findings from the study revealed:
High-CTSGRS patients were also significantly more likely to report headaches (odds ratio of 5.4)
A trend indicating individuals with high-CTSGRS were more prone to experiencing GI-related side effects in general (73% vs. 53%)
The development of nausea was not associated with changes in total body weight loss at either 5 or 16 weeks
The CTSGRS score provides dual benefits for clinicians. Previous research indicated that a low CTSGRS score is associated with a two-fold greater weight loss with liraglutide treatment, suggesting the genetic risk score could predict both potential side effects and likelihood of successful weight loss.
This advancement opens the door to personalized medication approaches. By identifying genetic predispositions before treatment begins, clinicians could potentially match patients to the most suitable medications or implement proactive management strategies, significantly reducing treatment abandonment due to adverse effects.
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