Objective: To characterize clinical and biomarker features of GBA1-NMC and evaluate whether CSF-αSynSAA status is associated with longitudinal clinical progression and phenoconversion.

Background: Pathogenic variants in GBA1 are among the most common genetic risk factors for Parkinson’s disease (PD), yet penetrance is low and predictors of phenoconversion remain poorly defined. Alpha-synuclein can be detected on CSF alpha-synuclein seed amplification assay (SAA) in a subset of GBA1 non-manifesting carriers (NMC).

Method: We included n=196 GBA1-NMC participants from the Parkinson’s Progression Markers Initiative (PPMI). GBA1-NMC with positive CSF-αSynSAA (SAA+, n=17) were compared with SAA− carriers (n=179). Baseline clinical characteristics, fluid biomarkers, and dopamine transporter imaging (DAT) were analyzed. Longitudinal changes in clinical measures were assessed using generalized estimating equation models adjusting for age, sex, and baseline score. Phenoconversion was defined as investigator diagnosis of parkinsonism or dementia during follow-up that remained stable at their last completed visit.

Results: There were no significant demographic differences between SAA+ and SAA- groups. At baseline, SAA+ carriers demonstrated a higher prevalence of hyposmia compared with SAA− carriers (65% vs 9%, p<0.0001) and had DAT values below the age- and sex-expected 75th percentile (35% vs 8%, p=0.0028). Other motor and non-motor clinical features were similar between groups. Over follow-up, no significant group differences were observed in longitudinal trajectories of MDS-UPDRS parts I–III or MoCA scores. Phenoconversion occurred more frequently in SAA+ carriers compared with SAA− carriers (n=5 [29%] versus n=4 [2%] within seven years; p<0.0001).

Conclusion: Minority of unenriched GBA1-NMCs are SAA+.  SAA+ was associated with hyposmia and DAT deficit. Majority of phenoconverters were SAA+. All SAA+ phenoconverters had baseline hyposmia and DAT deficit, suggesting that a multimodal biomarker approach combining olfactory dysfunction, DAT deficit, and α-synuclein detection may help identify individuals at highest risk of progression to clinically manifest synucleinopathy. However, the heterogeneity in disease timing, together with the small proportion of carriers meeting these combined biomarker criteria, poses important challenges for clinical trial design for preventative therapies.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/clinical-and-biomarker-trajectories-in-gba1-non-manifesting-carriers-with-and-without-%ce%b1-synuclein-seed-amplification-positivity/