| Title: | Genetic predictors of GLP1 receptor agonist weight loss and side effects |
| Journal: | Nature |
| Published: | 8 Apr 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41951734/ |
| DOI: | https://doi.org/10.1038/s41586-026-10330-z |
| URL: | https://www.nature.com/articles/s41586-026-10330-z.pdf |
Publication 18060
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Abstract
The development of glucagon-like peptide 1 (GLP1) receptor agonists, including semaglutide and tirzepatide, has transformed the clinical management of overweight and obesity. However, substantial inter-person variability exists in both weight loss efficacy and the incidence of side effects1. To investigate the genetic basis of this variability, here we conduct a genome-wide association study of self-reported weight loss and treatment-related side effects in 27,885 people following GLP1 receptor agonist therapy. We identify a missense variant in GLP1R that is associated significantly with increased efficacy of GLP1 medications (P = 2.9 × 10−10), with an additional −0.76 kg of weight loss expected per copy of the effect allele. Furthermore, we identify associations linking variation in both GLP1R and GIPR to GLP1 medication-related nausea or vomiting, with the GIPR association being restricted to people using tirzepatide. We incorporate these findings into a broader model of GLP1 medication response, and demonstrate the ability to stratify patients by efficacy and side effect risk. These findings provide direct genetic evidence that variation in the drug target genes contributes to inter-person variability in response and lay the foundation for precision medicine approaches in the treatment of obesity.</p>
13 Authors
- Qiaojuan Jane Su
- James R. Ashenhurst
- Wanwan Xu
- Vinh Tran
- R. Ryanne Wu
- Catherine H. Weldon
- Jingchunzi Shi
- Barry Hicks
- Noura S. Abul-Husn
- Stella Aslibekyan
- Michael V. Holmes
- Bertram L. Koelsch
- Adam Auton
1 Application
| Application ID | Title |
|---|---|
| 95801 | Exploring the relationship of genetics, proteins, metabolites and other biomarkers with clinical endpoints |
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