GBA1 variants and mortality in Parkinson's disease: A systematic review and meta-analysis.

Authors

Nathan Chan, Anthony Raphael, Justin Kim, Amy Haryanto, Saman Heshmat, Tien K Khoo

Published in

Journal of Parkinson's disease. Pages 1877718X261470604. Aug 07, 2026. Epub Aug 07, 2026.

Abstract

BackgroundVariants in the GBA1 gene are a common genetic risk factor for Parkinson's disease (PD). While GBA1-PD is associated with more rapid motor and cognitive decline, evidence regarding impact on survival remains debatable.ObjectivesThis systematic review and meta-analysis synthesizes longitudinal evidence of GBA1 variants as a prognostic factor for all-cause mortality in PD.MethodsWe searched MEDLINE, Embase, Cochrane (CENTRAL), ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform for studies comparing mortality in GBA1-PD versus non-carriers from inception to September 2025. Risk of bias was assessed using the Quality in Prognosis Studies tool. Hazard Ratios were pooled using a random-effects meta-analysis. Subgroup analysis was stratified by variant severity.ResultsEight studies (N = 13,690) were included. The primary meta-analysis (n = 4947) revealed GBA1 variants were associated with significantly increased all-cause mortality risk versus non-carriers (HR 1.53, 95% CI 1.24-1.87; I² = 0.7%). A subgroup analysis suggested a possible severity-dependent effect, with severe variants showing higher point estimates (HR 1.87; 95% CI 1.24-2.82) than mild variants (HR 1.38; 95% CI 1.03-1.83), although the test for subgroup differences was not statistically significant.ConclusionsGBA1 variants are a significant prognostic marker for reduced survival in PD. This risk may increase with variant severity and persist after adjustment for dementia in the studies that examined this, although the available data is limited. Limitations include heterogeneous screening methods and predominance of European ancestry in study populations. GBA1 status should be considered a significant prognostic factor for stratification in clinical trials and management.

PMID:
42565774
Bibliographic data and abstract were imported from PubMed on 07 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.