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Rare variants in 44 dystonia genes show no major contribution to Parkinson's disease risk overall.

Rare variants in 44 dystonia genes show no major contribution to Parkinson's disease risk overall.
Photo by HI! ESTUDIO / Unsplash
Key Takeaway
Note that rare variants in dystonia genes do not appear to make a major contribution to overall Parkinson's disease risk.

This meta-analysis utilized whole-genome sequencing data from the Accelerating Medicines Partnership-PD and UK Biobank cohorts to assess the association of rare variants (minor allele frequency <1%) in 44 dystonia-related genes with Parkinson's disease. The study included 5,315 patients with Parkinson's disease, including 300 with early-onset disease, and 36,902 controls. The primary outcome evaluated the association of these rare variants with all Parkinson's disease cases and specifically with early-onset Parkinson's disease.

Regarding overall Parkinson's disease, several genes demonstrated nominal associations. Specifically, SQSTM1 (Ploss-of-function = 5.52 x 10-3), AOPEP (Pexonic = 6.96 x 10-3; Pnonsynonymous = 0.017), KCNA4 (Pexonic = 0.017), SPR (Pexonic = 0.029), SLC30A10 (PCADD≥20 = 0.046), and ACTB (Pexonic = 0.047) showed nominal significance. However, none of these associations remained statistically significant after correction for multiple testing.

For early-onset Parkinson's disease, five genes reached significance after multiple-test correction. The signal for GCH1 was nominally significant (Pnonsynonymous = 4.36 x 10-3, PFDR = 0.062). These signals were driven by small numbers of variant carriers and were not robust to leave-one-variant-out analyses. No safety data or adverse events were reported as this was a genetic association study rather than a clinical trial.

Key limitations include that signals in the early-onset subset were based on small numbers of variant carriers and require replication in larger cohorts. The study design was observational, assessing association rather than causation. Consequently, the genetic contribution of dystonia genes to overall Parkinson's disease risk does not appear major, and the robustness of early-onset findings remains uncertain pending further validation.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedApr 2026
View Original Abstract ↓
Background: Dystonia frequently co-exists with Parkinson's disease (PD), yet the extent of genetic overlap remains insufficiently explored. Objective: To examine whether rare variants in dystonia-related genes are associated with PD or early-onset PD (EOPD). Methods: We curated 44 dystonia-related genes using OMIM and the updated Movement Disorder Society report on hereditary dystonia. Whole-genome sequencing data from 5,315 PD patients, including 300 with EOPD, and 36,902 controls across the Accelerating Medicines Partnership-PD and UK Biobank cohorts were analyzed. For each gene, we evaluated rare variants (minor allele frequency <1%) in four pre-specified variant classes: exonic, nonsynonymous, CADD score [&ge;]20 and loss-of-function. For the rare variant burden analysis, SKAT-O was performed, followed by meta-analysis with MetaSKAT. Results: In analyses of all PD cases, several genes showed nominal associations in meta-analysis: SQSTM1 (Ploss-of-function = 5.52 x 10-3), AOPEP (Pexonic = 6.96 x 10-3; Pnonsynonymous = 0.017), KCNA4 (Pexonic = 0.017), SPR (Pexonic = 0.029), SLC30A10 (PCADD[&ge;]20 = 0.046), and ACTB (Pexonic = 0.047). However, none remained significant after multiple-testing correction. In exploratory EOPD analyses, five genes reached significance after multiple test correction (ATP5MC3, DNAJC12, KMT2B, TBC1D24, TMEM151A). These signals were driven by small numbers of variants and were not robust to leave-one-variant-out analyses. GCH1 was nominally significant in the meta-analysis of EOPD (Pnonsynonymous = 4.36 x 10-3, PFDR = 0.062). Conclusions: Rare variants in dystonia-related genes do not appear to make a major contribution to PD risk overall. Signals observed in the EOPD subset were based on small numbers of variant carriers and require replication in larger cohorts.
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