Unraveling the Genetic Overlap Between Parkinson’s Disease and Schizophrenia Through Genome-wide Association and Cell-Type Specific Transcriptomic Analysis

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Authors: Wenhua Sun, Mohammad Dehestani, Alice Braun, Nasser Karmali, Isabel Wurster, Benjamin Röeben, Roswitha Kemmner, Kathrin Brockmann, Manu Sharma, Marina Mitjans, Fabian Streit, Thomas Gasser
+1 more Vikas Bansal
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References: 55

Abstract

Abstract Background Parkinson’s disease (PD) and schizophrenia (SZ), while clinically distinct, exhibit overlapping symptoms and neurobiological features. Emerging genetic evidence suggests a shared heritable component between the two disorders. In this study, we aim to identify novel genetic loci common to both PD and SZ and to further investigate the convergent molecular mechanisms that may underlie their shared pathophysiology. Methods We analyzed large-scale genome-wide association studies (GWAS) on SZ (55,193 cases and 74,132 controls) and PD (56,306 cases and 1,417,791 controls) using a proxy-phenotype method combined with a Bayesian statistical approach to evaluate overlap in common genetic variants and enhance statistical power for genetic discovery. To elucidate the biological mechanisms underlying newly identified shared genetic loci associated with PD and SZ, we leveraged single-cell RNA sequencing (scRNA-seq) data from induced pluripotent stem cell (iPSC)-derived dopaminergic neurons generated by the FOUNDIN-PD consortium (416,216 high-quality single-cells from PD patients). We performed differential gene expression analysis, and gene ontology (GO) enrichment analysis to systematically investigate the functional relevance of one shared loci in a disease-relevant cellular context. The polygenic risk score (PRS) model was constructed by stratifying overlapping SNPs based on effect directions to predict PD clinical outcomes in the Tuebingen Parkinson cohort (TUEPAC). MAGMA gene-set enrichment analysis was used to identify the cell types enriched for each SNP set. Results We identified five SNPs with concordant effect directions and nine SNPs with discordant effect directions shared between PD and SZ. Of these fourteen SNPs, eleven were in linkage disequilibrium with previously reported PD GWAS hits. In addition, we identified three novel shared SNPs (rs2240921, rs11649804, and rs9607782) associated with both PD and SZ. Notably, a missense variant in RAI1 (rs11649804) emerged as a shared genetic signal between the two disorders. Differential expression analysis and gene ontology (GO) enrichment analysis implicated RAI1 in mitochondrial dysfunction-related biological processes, highlighting its potential role in PD pathogenesis. In addition, PD_discordant PRS was associated with non-motor symptoms and uniquely associated with genes expressed in brain vascular cell types. Conclusion In summary, our study provides novel insights into the shared genetic architecture of PD and SZ, highlighting previously unrecognized loci with potential cross-disorder relevance. Functional characterization of RAI1 loci suggests that mitochondrial dysfunction may represent convergent biological mechanisms underlying both neurodegenerative and psychiatric pathologies. Moreover, variants with opposing cross-disorders effects may capture biological pathways specifically contributing to non-motor heterogeneity. These findings advance our understanding of the molecular interplay between PD and SZ and open new avenues for the identification of shared therapeutic targets.

Fields of Study & Subjects

Genetic Associations and Epidemiology Single-cell and spatial transcriptomics Nuclear Receptors and Signaling

Publication details

Journal / source
medRxiv
Publication date
8 January 2026
Document type
Preprint