Identification of biomarkers in Parkinson’s disease by comparative transcriptome analysis and WGCNA highlights the role of oligodendrocyte precursor cells

Abstract

BackgroundParkinson’s disease (PD) is an age-related neurodegenerative disease characterized by the death of dopamine neurons in the substantia nigra. A large number of studies have focused on dopamine neurons themselves, but so far, the pathogenesis of PD has not been fully elucidated.ResultsHere, we explored the significance of oligodendrocyte precursor cells (OPCs)/oligodendrocytes in the pathogenesis of PD using a bioinformatic approach. WGCNA analysis suggested that abnormal development of oligodendrocytes may play a key role in early PD. To verify the transcriptional dynamics of OPCs/oligodendrocytes, we performed differential analysis, cell trajectory construction, cell communication analysis and hdWGCNA analysis using single-cell data from PD patients. Interestingly, the results indicated that there was overlap between hub genes and differentially expressed genes (DEGs) in OPCs not in oligodendrocytes, suggesting that OPCs may be more sensitive to PD drivers. Then, we used ROC binary analysis model to identify five potential biomarkers, including AGPAT4, DNM3, PPP1R12B, PPP2R2B, and LINC00486.ConclusionIn conclusion, our work highlights the potential role of OPCs in driving PD.