Impact of glucagon-like-peptide-1 receptor agonists on non-motor symptoms in Parkinson’s disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Glucagon-Like-Peptide-1 Receptor Agonists (GLP-1 RAs), initially designed for diabetes management, show potential for treating motor disability in Parkinson’s Disease (PD) due to promising pre-clinical and clinical trial results. Previous studies including PD and non-PD populations also suggest GLP-1 RAs may improve cognition and reduce depression and anxiety. Despite the significant impact of non-motor symptoms (NMS) on PD patients’ quality of life, these symptoms are often overlooked or briefly assessed in GLP-1 RA studies. Objective: To perform a systematic review and meta-analysis to examine the impact of GLP-1 RA administration on non-motor symptoms in Parkinson’s disease (PD). Methods: We systematically searched PubMed, Embase, and Cochrane databases for randomized controlled trials (RCTs) comparing GLP-1 RAs to no GLP-1 RAs use in PD. Using a random-effects model, we analyzed studies after critical appraisal. Primary outcomes were the mean difference from baseline in reported non-motor symptoms, assessed using the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) Part I, Non-Motor Symptoms Rating Scale (NMSS), Beck Depression Inventory (BDI), Montgomery-Asberg Depression Rating Scale (MADRS), Montreal Cognitive Assessment (MoCA), and Mattis Dementia Rating Scale (MDRS). Due to variations in the availability of depression and cognitive scales across studies, we used the standard mean difference (SMD) to compare effect sizes for these outcomes. To account for multiple comparisons and reduce the risk of Type I errors, we applied Bonferroni correction (adjusted p-value of 0.0125). Statistical analysis was conducted using Review Manager 5.4.1, and heterogeneity was assessed with I² statistics. Results: Analyzing data from five RCTs (569 patients, 59% on GLP-1 RA) with 9-15 month follow-ups, GLP-1 RA significantly improved cognitive functions in PD patients (SMD 1.11; 95% CI: 0.29 to 1.94; p=0.0082; I²: 94%), maintaining significance after adjusting for multiple comparisons. Depression scores showed a medium effect size change towards improvement (SMD -0.49; 95% CI: -0.95 to -0.02; p=0.04; I²: 69%), but lost significance after correction. NMSS and MDS-UPDRS Part I changes were non-significant (p=0.99 and 0.29, respectively). High heterogeneity was observed in cognitive (I²: 94%), depression (I²: 69%), NMSS (I²: 68%), and MDS-UPDRS Part I (I²: 96%) outcomes. Conclusion: GLP-1 RAs significantly improved cognitive functions in PD patients, suggesting a potential benefit in treating cognitive impairment. However, the trend towards improvement in depression with GLP-1 RA treatment was not statistically significant after adjusting for multiple comparisons. Substantial heterogeneity among studies may have influenced results, affecting the reliability of findings. Future studies should use comprehensive assessments and longer follow-up to better understand GLP-1 RAs’ impact on NMS in PD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.038 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".