Efficacy and Safety of Glucagon‐Like Peptide‐1 Agonists for Psychiatric Symptoms: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have emerged as potential therapeutic options for psychiatric symptoms due to their effects on mood and behavior. However, their use has been primarily for metabolic diseases, and limited research has evaluated their psychiatric efficacy. This systematic review examined the impact of GLP-1 RAs on psychiatric symptoms, categorizing studies based on whether psychiatric outcomes were primary or secondary. METHODS: A comprehensive search through OVID databases from inception to November 2024 identified 26 studies (n = 3020), with 5 studies evaluating psychiatric symptoms as primary outcomes (e.g., substance use disorders) and 21 studies assessing secondary outcomes across various conditions. Additionally, 10 registered clinical trials were identified. RESULTS: Among the five studies targeting primary outcomes, exenatide and dulaglutide were investigated in cocaine use disorder, alcohol use disorder, and nicotine dependence. Exenatide 2 mg once-weekly demonstrated reductions in cocaine craving in two cases over 6 weeks in a case series study. However, mixed results were reported across studies, including no significant changes in a separate case series (n = 12, p = 0.46). Dulaglutide 1.5 mg weekly did not significantly affect smoking abstinence (RR = 0.87, p = 0.25) but reduced alcohol consumption by 29% in a secondary analysis. For studies assessing secondary outcomes, GLP-1 RAs showed variable effects. In mood disorders, liraglutide 1.8 mg/day significantly improved depression and anhedonia. In Type 2 diabetes, semaglutide improved diabetes-related quality of life (Cohen' and anxiety (Cohen's d = 0.48) compared to dulaglutide. Exenatide studies reported mixed results, with one randomized controlled trial (RCT) showing significant reductions in Beck's Depression Inventory (BDI) scores (Δ = -5.2). A total of nine RCTs were included in this review and the risk of bias was assessed using the JBI Critical Appraisal Checklist for RCTs. All included RCTs met the majority of criteria, indicating moderate-to-high methodological quality. Of the included RCTs, three reported a statistically significant effect on the primary psychiatric outcome, whereas six reported no significant effect. CONCLUSION: GLP-1 RAs showed mixed and inconclusive effects on psychiatric symptoms. Although some studies suggested potential benefits, others reported null findings. Given the variability across trials, further research is needed to clarify their therapeutic potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".