Multi-omics approaches for therapeutic target and biomarker discoveries in Parkinson’s Disease

Parkinson’s disease (PD) is a complex neurodegenerative disorder characterized by motor and cognitive impairments. In this study, we performed a meta-analysis of publicly available PD datasets on the CDIAM platform, a multi-omics analytical software platform that offers custom tools to unveil meaningful cell-cell interactions and ligand-receptor pairs (CellphoneDB), identify important pathways (GSEA and hypergeometric analysis), predict therapeutic targets (Pathway2Targets) and prioritize biomarkers (Biomarker2Validate). Several differentially expressed genes/proteins and enriched pathways consistently appeared across different datasets and -omics data types. Particularly, our Pathway2Targets tool identified GAPDH and HRAS, which are implicated in the mechanism of current PD treatment, as the highest scoring potential therapeutic targets. Likewise, CD44 and VEGFA were scored as the top-ranking robust biomarkers for PD. We also report a significant upregulation of immune cell interactions with other cell types in PD patients, signifying the contribution of neuroinflammation in PD pathogenesis. Our findings were in accordance with previous PD results, confirming the reliability of our computational workflow and analysis pipelines in terms of identifying pathways and biomarkers with high clinical and pathological relevance.