Back

Neuro-Adverse Events Associated with GLP-1 Receptor Agonists: A Study Based on the FAERS Database and External Validation Using NHANES Database

Bai, L.; Liu, Y.; Tongye, H.

2026-08-06 health economics
10.64898/2026.08.04.26359670 medRxiv
Show abstract

Background Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely prescribed for type 2 diabetes and obesity, yet their neuropsychiatric safety profile remains incompletely characterized. We aimed to systematically evaluate neuro-adverse event (AE) signals for six GLP-1RAs and to validate key findings using population-based data. Methods We conducted disproportionality analysis of FAERS data for semaglutide, liraglutide, dulaglutide, tirzepatide, exenatide, and lixisenatide. RORs were calculated for 93 predefined neuro-AE MedDRA PTs across 11 neurological categories. External validation used NHANES 2013-2018 (n=17,057; 70 GLP-1RA users) with survey-weighted regression. Results We identified 41 significant neuro-AE signals. Semaglutide showed the strongest neuromuscular signal, muscle atrophy (ROR 3.94; 95%CI 3.42-4.54), corroborated by tirzepatide (ROR 2.35; 95%CI 2.04-2.71). Exenatide generated the highest psychiatric signal: nervousness (ROR 4.03; 95%CI 3.70-4.40). NHANES confirmed higher depression odds (OR 2.05; 95%CI 1.32-3.19; P=0.001) and reduced sleep hours (beta -0.35; P=0.033). Conclusions GLP-1RAs carry multiple neuropsychiatric safety signals, including muscle atrophy as a potential class effect and depression risk corroborated by population-level data. These findings support heightened clinical monitoring.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.