To investigate the underlying mechanisms of Parkinson’s Disease (PD) from the perspective of network biology, focusing on protein-protein interactions (PPIs).

We used Proteinarium, a novel multi-sample PPI analysis and visualization tool, to examine RNA-sequencing data for 613 PD patients and 196 healthy controls (HCs) from the Parkinson’s Progression Markers Initiative database. Subjects were clustered according to similarities in their PPI graphs. Mechanisms associated with clusters dominated by PD patients were investigated using Gene Set Enrichment Analysis (GSEA), examining PPI networks, and analyzing cluster phenotypes related to immune system function.

We examined three significant PD-dominated clusters: C1, C2, and C3. In C1, PPI network and GSEA implicate the innate immune system, with multiple known regulators of neutrophil migration acting as hub genes. C1 PD patients display significantly more exaggerated changes in neutrophil and lymphocyte concentrations when compared to HCs. For C2, our findings suggest involvement of RNA polymerase II (POLR2) and Fibroblast Growth Receptor II, with hub genes FGF1 and multiple subunits of POLR2. C2 displayed significantly reduced neutrophil and lymphocyte concentration differences relative to HCs. For C3, network analysis and GSEA implicate dysregulation of G-coupled protein receptors (GPCR), with several G-protein subunits and GPCR-dependent neuropeptides acting as hub genes. C3 immune phenotypes show significantly higher neutrophil concentrations than expected.

We present a novel approach for subtyping PD patients by highlighting three PD subtypes based on underlying protein networks and molecular mechanisms. In each PD subtype, we demonstrated phenotypic differences related to immune system function. These relevant molecular pathways can be further explored and targeted for drug development in future research.