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GLP1R locus variants associated with higher BMI and Type 2 Diabetes risk in genetically inferred European ancestry participantsDo your genes make you heavier? New data suggests specific gene variants are linked to higher body weight

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Key Takeaway
Note that GLP1R variants associate with higher BMI and T2D risk, supporting future precision medicine research.

This genetic association study evaluated the relationship between GLP1R locus variants and metabolic outcomes in a large cohort of 431,107 participants with genetically inferred European ancestry from the Million Veteran Program. The study compared participants carrying specific risk alleles against those with zero risk alleles to assess associations with body mass index and Type 2 Diabetes.

analysis found that the rs12213929 variant was associated with a higher body mass index, with an effect size of beta = 0.11 (95% CI 0.09-0.14, p = 1.94E-17). Similarly, the rs13216992 variant was independently associated with higher BMI, showing an effect size of beta = 0.10 (95% CI 0.07-0.13, p = 7.88E-14). When examining allelic burden, participants carrying four risk alleles exhibited a BMI that was 0.47 kg/m² higher than those with zero risk alleles (95% CI 0.39-0.55, p < 2E-16).

Regarding Type 2 Diabetes, the rs12213929 variant was associated with higher risk, with an odds ratio of 1.02 (95% CI 1.01-1.03, p = 0.0004). This association persisted after adjustment for BMI. In contrast, the rs13216992 variant showed an odds ratio of 1.00 (95% CI 0.99-1.01, p = 0.68), indicating that the association with Type 2 Diabetes was fully attenuated after adjustment for BMI. No adverse events, serious adverse events, discontinuations, or tolerability data were reported. The study did not report causality or specific limitations beyond the scope of genetic association analysis.

These results suggest that GLP1R variation may influence metabolic traits, providing a foundation for functional and pharmacogenomic studies to determine whether GLP1R variation can inform precision prevention and treatment of obesity and Type 2 Diabetes. Clinicians should interpret these genetic associations as observational findings that require further validation before influencing clinical practice.

Have you ever wondered if your DNA plays a role in your weight? A massive study involving over 431,000 people with European ancestry found that specific gene variations are linked to higher body mass index. These genetic markers act like biological signals that influence how your body stores fat. The research team analyzed data from the Million Veteran Program to see if these natural differences in our genes could predict weight outcomes.

The study focused on two specific gene locations. One marker was strongly linked to higher weight and also showed a small increase in Type 2 Diabetes risk, even after accounting for body weight. Another marker was linked to higher weight, but its connection to diabetes disappeared once researchers adjusted for body size. This suggests that for some people, weight gain is the main driver of diabetes risk, while for others, the gene might affect both independently.

There were no safety concerns to report because this study looked at natural genetic differences, not new drugs or treatments. However, remember that this is an association study, meaning it shows a link but does not prove that changing these genes will cure obesity or diabetes. These results provide a foundation for scientists to study how these genetic variations might guide future personalized prevention and treatment strategies.

What this means for you:
Specific gene variants are linked to higher weight and slightly higher diabetes risk in this large study.

Study Details

Sample sizen = 431,107
EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
Background: The glucagon-like peptide-1 receptor (GLP1R) is a key regulator of glucose metabolism and appetite and a major therapeutic target for type 2 diabetes (T2D) and obesity. Genetic studies have implicated the GLP1R locus in both body mass index (BMI) and T2D, but it remains unclear whether their underlying genetic associations are the same. Methods: We analyzed 431,107 participants of genetically inferred European ancestry from the Million Veteran Program. Within 500 kb of GLP1R, we performed locus-wide linear regression models for BMI and logistic regression models for T2D, adjusted for age, sex, and 10 principal components. We identified primary and secondary BMI sentinel variants using conditional analyses and evaluated their associations with T2D. Bayesian fine-mapping was used to construct credible sets of GLP1R locus for BMI and T2D. Results: Conditioning on the primary sentinel variant rs12213929 (upstream of GLP1R, {beta} = 0.11; 95% CI 0.09-0.14; p = 1.94E-17), we identified a secondary variant (rs13216992, intron of GLP1R) independently associated with BMI ({beta} = 0.10; 95% CI 0.07-0.13; p = 7.88E-14). The two sentinel variants showed low linkage disequilibrium (r2 = 0.03). A two-variant allelic burden score (0-4; sum of the rs12213929 G-allele count and rs13216992 C-allele count) showed that participants with 4 risk alleles had 0.47 kg/m2 higher BMI than those with 0 risk alleles (95% CI 0.39-0.55; p < 2E-16). Both variants were associated with higher T2D risk, but with distinct patterns after BMI adjustment: the rs12213929-T2D association persisted after adjustment for BMI (OR = 1.02; 95% CI 1.01-1.03; p = 0.0004), whereas the rs13216992-T2D association was fully attenuated (OR = 1.00; 95% CI 0.99-1.01; p = 0.68). Fine-mapping identified a compact 95% BMI credible set of 17 variants and a broader 95% T2D credible set of 42 variants, with all BMI credible variants contained within the T2D set. Conclusions: The GLP1R locus harbors at least two independent BMI-associated variants that exhibit heterogeneous relationships with T2D: rs12213929 influences T2D risk partly through BMI-independent pathways, whereas rs13216992 appears to act predominantly via adiposity. These findings refine the genetic architecture at this key therapeutic target gene and provide a foundation for functional and pharmacogenomic studies to determine whether GLP1R variation can inform precision prevention and treatment of obesity and T2D.
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