BACKGROUND: GLP-1 receptor agonists (GLP-1RAs) are increasingly prescribed for diabetes and obesity management. Recent pharmacovigilance reports have raised concerns about potential neuropsychiatric adverse events, yet comprehensive safety assessments focusing on depressive disorders remain limited. This study investigated associations between specific GLP-1RAs and depressive disorders using real-world post-marketing surveillance data.
METHODS: We analyzed individual case safety reports (ICSRs) for liraglutide, semaglutide, and tirzepatide from the FDA Adverse Event Reporting System (FAERS) and WHO VigiBase databases through December 2024. Disproportionality analysis using reporting odds ratio (ROR) and information component (IC) identified signals of disproportionate reporting (SDRs) for depressive disorders. Time-to-onset analysis, stratified analyses, active comparator assessments, and co-medication evaluations were conducted to characterize these associations.
FINDINGS: Only semaglutide demonstrated statistically significant SDRs for depressive disorders in both databases (FAERS: ROR 1.26, 95% confidence interval (CI) 1.15-1.37; IC 0.33, 95% CI 0.20-0.45; VigiBase: ROR 1.38, 95% CI 1.27-1.49; IC 0.46, 95% CI 0.34-0.57), while liraglutide and tirzepatide showed no SDRs. Stratified analyses revealed increased disproportionality in females and healthcare professional reports. WSP analysis showed semaglutide-associated depression followed an early failure pattern, with no significant drug interactions identified with psychotropic medications.
INTERPRETATION: This pharmacovigilance investigation identified a semaglutide-specific SDR for depressive disorders across both databases, while liraglutide and tirzepatide showed no SDRs. Although inconsistent with reported protective effects in existing studies of GLP-1RAs, these findings suggest drug-specific rather than class-wide safety monitoring is warranted.
FUNDING: This work was supported by grants from the Foshan "Fourteen Five" Key Medical Specialty Construction Project (grant number FSZD145035) and Natural Science Foundation of Hunan Province (grant number 2023JJ60520).