Identification of platelet-derived biomarker in a cohort of Parkinson's disease

Evidence has suggested that platelets (PLTs) share biochemical properties with neurons. However, whether PLTs might serve as biomarkers of Parkinson's disease (PD) remains uncertain. In this study, we first analyzed RNA data from a publicly available microarray of the substantia nigra (SN) and RNA-seq data from the PLTs of newly recruited PD patients using weighted gene coexpression network analysis (WGCNA). We found that in the SN, the majority of network modules were associated with chromatin organization, energy metabolism, and synaptic signaling, whereas those in the PLTs were related to chromatin organization and DNA metabolism. Potential PLT biomarkers were then screened by comparing the differentially expressed genes (DEGs) in the significant module pathways with those identified in the SN data by microarray. Additionally, significant genes were identified using genome-wide association study (GWAS) and transcriptome-wide association study (TWAS). The resulting 20 candidate genes were further tested for consistency in single-cell RNA-seq data, followed by assessment using receiver operating characteristic curve (ROC) analysis and qPCR validation. The combination of the CRLF3 and LRRC37A2 genes exhibited the best diagnostic performance. Collectively, both PLTs and the SN were common in the chromatin organization pathway, and the diagnostic value of PLT-derived CRLF3 and LRRC37A2 genes deserves further large-scale studies.