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

Xueping Wang¹ Youquan Gu¹ Xiaoyan Liu² Qiang Wang¹ Chen Xie¹ Jun Chen^1*

• ¹Department of Neurology, First Hospital of Lanzhou University, China
• ²First People's Hospital of Longquanyi District, China

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, limited research has been conducted on NETs in the context of PD. Differential analysis was implemented to acquire differentially expressed genes (DEGs) between PD and Control, as well as between high-and low-score groups determined by gene set variation analysis (GSVA). Then, the genes within the critical module, obtained through weighted gene co-expression network analysis (WGCNA), were intersected with the DEGs to identify the overlapping genes. Next, five kinds of algorithms in the protein-protein interaction (PPI) were performed to identify potential biomarkers. Subsequently, a nomogram for forecasting PD probability was created. Enrichment analysis and immune infiltration analysis were performed on the identified biomarkers. qRT-PCR was performed to validate the expression trends of three biomarkers. Results revealed 798 DEGs between PD and Control groups, as well as 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 of these gene sets, a total of 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 analysis demonstrated up-regulation of GPR78, CADM3, and CACNA1E in the PD group. Our study authenticated GPR78, CADM3, and CACNA1E as the biomarkers associated with PD. These findings provide an original reference for the diagnosis and treatment of PD.