Last updated:
Author(s):
Arshiya Mariam-Smith, Joseph H. Breeyear, Noah J. Daniels, Kevin M. Pantalone, Marcio L. Griebeler, Alison A. Motsinger-Reif, Daniel M. Rotroff
Publish date:
18 July 2025
Journal:
Diabetes Obesity and Metabolism
PubMed ID:
40677145

Abstract

AIMS: Nearly 42% of adults in the United States have obesity, a significant risk factor for many cardiometabolic diseases and cancers. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are promising interventions for weight loss, but their efficacy varies significantly across individuals. This study investigates the role of neurobeachin (NBEA), a gene that encodes a protein kinase A anchor protein, on weight loss response in two large, real-world cohorts.

MATERIALS AND METHODS: We utilised data from individuals prescribed a GLP-1RA in the NIH All of Us (N = 6556) and validated in the UK Biobank (N = 241). The NBEA genetic score for weight loss (12-18 months) was developed using the NIH All of Us cohort and independently validated in the UK Biobank. Logistic regression modelled associations between the score and outcomes, including high responsiveness (top 20th percentile for weight loss) and non-responsiveness (weight change ≥0%).

RESULTS: Individuals meeting the responsive NBEA score threshold were 82% more likely to be highly responsive (FDR p = 1·8 × 10-6) on liraglutide and were validated in the UK Biobank (odds ratio (OR) = 2·37; p = ·008). Individuals on semaglutide meeting this threshold for highly responsive had OR = 1·63 and OR = 2·21 in discovery and validation sets respectively (p < ·05). Individuals on liraglutide with a non-responsive NBEA score were 50% more likely to not lose weight (FDR p = 2.9 × 10-4) and were validated in the UK Biobank (OR = 1·81; p = ·041), but the non-response score did not validate for semaglutide.

CONCLUSION: These findings indicate that NBEA genetic variation is predictive of GLP-1RA weight loss and may support future efforts to identify individuals likely to experience significant weight loss with GLP-1RAs, enabling personalised obesity treatment strategies.

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