Genetic predictors of GLP1 receptor agonist weight loss and side effects | Nature

## Summary
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. Participants reported greater BMI loss using tirzepatide compared with semaglutide (median 4.75 versus 3.71 kg m −2 ; P = 9.7 × 10 −29 , median test), despite similar treatment times (8.1 versus 8.4 months), consistent with previous reports 9 . To investigate the relative contribution of non-genetic factors that predict GLP1 medication efficacy, we fit a linear model to assess the combined effect of age, sex, pre-treatment BMI, drug type, drug dose and time on drug on total BMI loss (Supplementary Table 3 ). These data indicate that survey participants generally accurately self-reported which drug type they were using, although EHR data reported a higher fraction of users relying on compounded versions of the medications (18.9% in EHR versus 13.5% in self-report for semaglutide, and 6.1% versus 4.8% for tirzepatide).

## Article Content
Download PDF
Subjects
Genome-wide association studies
Medical genetics
Pharmacology
Weight management
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 effects
1
. 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.
Main
Approximately 40% of adults in the USA are classified as living with obesity—a chronic condition that affects the risk of several health conditions including type 2 diabetes (T2D) and cardiovascular disease. Until recently, therapeutic strategies for people with obesity were of limited efficacy
2
, with the main strategies for weight loss focused on lifestyle interventions, including diet and exercise
3
.
GLP1 and gastric inhibitory polypeptide (GIP) are two primary gastrointestinal hormones (incretins) secreted from the gastrointestinal tract after food ingestion. Incretins stimulate pancreatic β-cell proliferation and insulin secretion, delay gastric emptying and act centrally to suppress appetite. Recently, potent incretin mimetics, including semaglutide (a GLP1 receptor agonist) and tirzepatide (a dual GLP1 and GIP receptor agonist), have become widely available for patients with obesity or who have overweight and have a cardiovascular risk factor. The clinical efficacy of semaglutide and tirzepatide has led to these drugs being among the most commonly prescribed in the USA, with an estimated one in eight people having used a GLP1 receptor agonist medication
4
.
For people using GLP1 receptor agonists, there is large variation in weight loss
1
. In a study of semaglutide efficacy, the average reduction in weight from baseline was 10.2%, but 4.9% of patients achieved over 25% reduction from baseline, and 32.2% achieved less than a 5% reduction from baseline or even weight gain
5
. Identifying factors that predict a person’s response to GLP1 medications may help guide treatment strategy, including choice of drug, dose and speed of dose escalation.
In other contexts, genetic variation is known to have an important role in treatment response, both for intended and adverse events
6
,
7
,
8
. We hypothesized that some of the variation in GLP1 medication efficacy could be attributed to genetics, and surveyed 23andMe research participants regarding their use of GLP1 medications. Using these data, we conducted a large genome-wide association study (GWAS), and identified robust evidence that variants in the
GLP1R
locus are associated with both differential weight loss and side effects. Further analysis revealed an additional nausea and vomiting association in the
GIPR
locus specifically within the tirzepatide-treated population. We incorporated our genetic findings into broader models that combine demographic, clinical and genetic features to predict efficacy and side effects, and demonstrated the ability of this model to stratify patients by weight loss in a held out electronic health record (EHR) dataset. Our results highlight the opportunity for pharmacogenetics and precision medicine approaches applied to GLP1 medication.
In August 2024, we surveyed 23andMe research participants about their GLP1 medication usage, focusing on those taking weight loss medication. As of August 2025, we had collected over 27,885 survey respondents who had reported using at least one of Ozempic, Wegovy, compounded semaglutide, Mounjaro, Zepbound or compounded tirzepatide (Extended Data Table
1
). Study participants were mostly female (82.4%) with a median age of 52 years. Most respondents were of European ancestry (78.3%), although the study also included substantial representation from Latino (12.9%) and African American (4.2%) ancestries.
Study participants reported a median body mass index (BMI) of 35.1 kg m
−2
before initiating GLP1 treatment, with 96.8% of participants having a BMI of at least 25 at baseline. T

---

## Expert Analysis

### Merits
- In other contexts, genetic variation is known to have an important role in treatment response, both for intended and adverse events 6 , 7 , 8 .
- Using these data, we conducted a large genome-wide association study (GWAS), and identified robust evidence that variants in the GLP1R locus are associated with both differential weight loss and side effects.
- As noted in other studies, medication seemed more effective in women 10 (ΔBMI % = −12.2% in women versus −10.0% in men; P = 5.0 × 10 −31 , Mood’s median test; Supplementary Table 1 ), and in people of European ancestry 11 (ΔBMI % = −12.1% in Europeans versus −10.6% in non-Europeans; P = 4.7 × 10 −16 , Mood’s median test; Supplementary Table 2 ) before correcting for other factors.
- T2D status was found to be a highly significant predictor of weight loss efficacy ( P = 2.0 × 10 −73 ; Supplementary Table 4 ), with an average predicted reduction of 2.87 percentage points in BMI loss for people with a T2D diagnosis.

### Areas for Consideration
- 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.
- Main Approximately 40% of adults in the USA are classified as living with obesity—a chronic condition that affects the risk of several health conditions including type 2 diabetes (T2D) and cardiovascular disease.
- Recently, potent incretin mimetics, including semaglutide (a GLP1 receptor agonist) and tirzepatide (a dual GLP1 and GIP receptor agonist), have become widely available for patients with obesity or who have overweight and have a cardiovascular risk factor.

### Implications
- Identifying factors that predict a person’s response to GLP1 medications may help guide treatment strategy, including choice of drug, dose and speed of dose escalation.
- We hypothesized that some of the variation in GLP1 medication efficacy could be attributed to genetics, and surveyed 23andMe research participants regarding their use of GLP1 medications.
- We incorporated our genetic findings into broader models that combine demographic, clinical and genetic features to predict efficacy and side effects, and demonstrated the ability of this model to stratify patients by weight loss in a held out electronic health record (EHR) dataset.
- Non-genetic predictors of BMI loss We examined non-genetic factors that were predictive of GLP1 medication efficacy, as measured by the percentage change in BMI from baseline (ΔBMI % ).

### Expert Commentary
This article covers data, loss, ehr topics. Notable strengths include discussion of data. Areas of concern are also raised. Readability: Flesch-Kincaid grade 0.0. Word count: 2355.