Parkinson’s disease (PD) is one of the most prevalent movement disorders and its diagnosis relies heavily on the typical clinical manifestations in the late stages. This study aims to screen and identify biomarkers of PD for earlier intervention. We performed a differential analysis of postmortem brain transcriptome studies. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify biomarkers related to Braak stage. We found 58 genes with significantly different expression in both PD brain tissue and blood samples. PD gene signature and risk score model consisting of nine genes were constructed using least absolute shrinkage and selection operator regression (LASSO) and logistic regression.PLOD3andLRRN3in gene signature were identified to serve as key genes as well as potential risk factors in PD. Gene function enrichment analysis and evaluation of immune cell infiltration revealed thatPLOD3was implicated in suppression of cellular metabolic function and inflammatory cell infiltration, whereasLRRN3exhibited an inverse trend. The cellular subpopulation expression of thePLOD3andLRRN3has significant distributional variability. The expression ofPLOD3was more enriched in inflammatory cell subpopulations, such as microglia, whereasLRRN3was more enriched in neurons and oligodendrocyte progenitor cells clusters (OPC). Additionally, the expression ofPLOD3andLRRN3in Qilu cohort was verified to be consistent with previous results. Collectively, we screened and identified the functions ofPLOD3andLRRN3based the integrated study. The combined detection ofPLOD3andLRRN3expression in blood samples can improve the early detection of PD.