Integrating plasma circulating protein-centered multi-omics to identify potential therapeutic targets for Parkinsonian cognitive disorders

Abstract Background Parkinson's disease (PD), the second most common neurodegenerative disease with notable clinical heterogeneity, has Parkinson disease dementia (PDD) that severely impacts patients' quality of life. As no effective treatment exists, this study aimed to find potential drug targets for PD cognitive disorders. Methods Two-sample Mendelian randomization (MR) and transcriptome analysis were used to identify PD biomarkers. Protein-protein interaction (PPI), gene ontology (GO), and KEGG pathway analyses explored biological effects. A nomogram model was developed. Results 76 Mendelian randomization genes (MRGs) from MR and 1771 differentially expressed genes (DEGs) from the transcriptome were obtained. Three significant shared DEGs (S-DEGs) were identified, with USP8 and STXBP6 having strong diagnostic value for PDD. The nomogram model with these two genes showed enhanced predictive ability. These genes had physical interactions, co-localization, and correlated with ODC and NEU immune cells. USP8 was linked to five diseases, and STXBP6 to one. Conclusion USP8, STXBP6, and immune cells (ODC and NEU) associated with PDD were identified, offering new insights into PD progression.