Bioinformatic gene analysis for potential biomarkers and therapeutic targets of Parkinson's disease based on neutrophil extracellular traps

Abstract

Abstract Neutrophil extracellular traps (NETs) provide key innate immune mechanisms, and studies have shown innate immunity and adaptive immunity are directly linked in Parkinson’s disease (PD) pathology. However, there are few studies on NETs in PD. Differential analysis was implemented to acquire differentially expressed genes (DEGs) between PD and Control, and between high- and low-score groups obtained by GSVA. Then, the DEGs between PD and Control groups, DEGs between the two score groups, and the genes in the critical module were overlapped to achieve the overlapping genes. Next, five kinds of algorithms in the PPI were performed to achieve biomarkers. Subsequently, a nomogram for forecasting PD probability was created. Enrichment analysis and immune infiltration analysis was conducted of biomarkers. qRT-PCR was performed to verify the expression trends of three biomarkers. Results shown there were 798 DEGs between PD and Control groups and 168 DEGs between high- and low-score groups obtained by differential analyses. The pink module containing 926 genes was identified as the critical module. According to the intersection, 43 overlapping genes were screened out. Furthermore, GPR78, CADM3, and CACNA1E were confirmed as biomarkers. Moreover, we found that biomarkers mainly participated in pathways, such as ‘hydrogen peroxide catabolic process’ and ‘cell cycle’. Five kinds of differential immune cells between PD and Control groups were identified. Finally, the qRT-PCR result showed that GPR78, CADM3, and CACNA1E all up-regulated in the PD group. Our study authenticated GPR78, CADM3, and CACNA1E as the biomarkers were associated with PD. It provides an original reference for the diagnosis and treatment of PD.