Objective: To assess the consistency of GBA1 variant classification across large Parkinson’s disease (PD) and Gaucher disease (GD) cohorts and determine how variant-specific biochemical data enhance pathogenicity assessment and PD risk stratification.

Background: With increasing implementation of exome and genome sequencing, interpretation of GBA1 variants linked to PD (GBA1‑PD) risk has become essential. Case–control studies have identified recurrent risk alleles, including p.Glu365Lys, p.Thr408Met, and the African variant (c.1225‑34C>A). Most GBA1‑PD risk alleles correspond to pathogenic (P), or likely pathogenic (LP) variants known from GD. Classification of rare or private variants depends on clinical context, biochemical evidence, and the application of ACMG criteria.

Method: A large PD cohort (>20,000 individuals; ROPAD) was analyzed to detect enrichment of heterozygous GBA1 variants. Variant evidence was consolidated using a GD cohort of >3,000 patients (Centogene’s “biodatabank”). Classifications were compared with ClinVar and HGMD to assess concordance. Although HGMD does not follow ACMG criteria, “DM” and “DM?” variants were considered as potential indicators of PD risk.

Results: In total, 767 GBA1 variants appeared in at least one dataset: 667 classified variants in the Biodatabank, 315 in ClinVar, and 387 DM/DM? variants in HGMD. Applying ACMG criteria, 323 variants (48%) at CENTOGENE and 147 variants (47%) in ClinVar were classified as P/LP with an overlap of 122 of those clinically relevant variants. The higher number of P/LP classifications in the Biodatabank reflects the availability of functional evidence—glucocerebrosidase activity and glucosylsphingosine levels—in GD cases which provides strong functional support for variant classification.

Conclusion: Harmonized classification of GBA1 variants is crucial for accurate GD diagnosis and for counselling heterozygous carriers on their PD risk. Biochemical pathway data from GD patients substantially reinforce variant interpretation and improve GBA1‑PD risk prediction. Curated and globally accessible databases integrating genetic and functional evidence are needed to ensure reliable and consistent clinical decision‑making.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/analyzing-the-classification-of-767-gba1-variants-to-guide-gba1-pd-risk-prediction/