Parkinson's disease causality and heterogeneity: a proteogenomic view

Pathogenesis and clinical heterogeneity in Parkinson's disease (PD) have been evaluated from genetic, pathological, and clinical perspective. Technology allowing for high-throughput proteomic analyses in cerebrospinal fluid (CSF) has opened new opportunities to scrutinize this heterogeneity. This is to date the most comprehensive proteomics profiling in CSF of PD patients and controls, both in terms of subjects (n=1103) and proteins (n=4135). Combining CSF aptamer-based proteomics with genetics across all samples we determined the protein quantitative trait loci (pQTLs) linking genetic variants with protein abundance in CSF. Analyzing pQTLs together with summary statistics from the largest PD genome wide association study (GWAS) led us to identify 68 potential causal proteins by Mendelian randomization. The top PD causal protein, GPNMB, has colocalization support and has been reported to be upregulated in the substantia nigra of PD patients. We also examined three subcohorts of PD patients: LRRK2 variant carriers (LRRK2+), GBA variant carriers (GBA+) and idiopathic PD patients, each with their respective controls. The second goal was to identify proteomic differences between PD patients and controls within and between the three subcohorts. Statistical analyses revealed six proteins differentially expressed when comparing GBA+ PD patients with unaffected GBA+ controls, seven proteins when comparing LRRK2+ PD patients with unaffected LRRK2+ controls and 23 proteins when comparing idiopathic PD patients with healthy controls who did not carry any severe PD mutations. Furthermore a hypothesis-free stratification of idiopathic PD patients based on their proteomic profile revealed two protein modules based on the co-expression network structure. Based on these modules, cluster analysis revealed two patient endotypes for idiopathic PD. Differences in the CSF proteomic signature between subcohorts and between idiopathic endotypes, as well as causal targets identified using both proteomics and genetics may together influence the way we approach the identification of potential therapeutic targets in PD.

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