Novel diagnostic biomarkers related to immune infiltration in Parkinson’s disease by bioinformatics analysis

Abstract

BackgroundParkinson’s disease (PD) is Pengfei Zhang Liwen Zhao Pengfei Zhang Liwen Zhao a common neurological disorder involving a complex relationship with immune infiltration. Therefore, we aimed to explore PD immune infiltration patterns and identify novel immune-related diagnostic biomarkers.Materials and methodsThree substantia nigra expression microarray datasets were integrated with elimination of batch effects. Differentially expressed genes (DEGs) were screened using the “limma” package, and functional enrichment was analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to explore the key module most significantly associated with PD; the intersection of DEGs and the key module in WGCNA were considered common genes (CGs). The CG protein–protein interaction (PPI) network was constructed to identify candidate hub genes by cytoscape. Candidate hub genes were verified by another two datasets. Receiver operating characteristic curve analysis was used to evaluate the hub gene diagnostic ability, with further gene set enrichment analysis (GSEA). The immune infiltration level was evaluated by ssGSEA and CIBERSORT methods. Spearman correlation analysis was used to evaluate the hub genes association with immune cells. Finally, a nomogram model and microRNA-TF-mRNA network were constructed based on immune-related biomarkers.ResultsA total of 263 CGs were identified by the intersection of 319 DEGs and 1539 genes in the key turquoise module. Eleven candidate hub genes were screened by the R package “UpSet.” We verified the candidate hub genes based on two validation sets and identified six (SYT1, NEFM, NEFL, SNAP25, GAP43, and GRIA1) that distinguish the PD group from healthy controls. Both CIBERSORT and ssGSEA revealed a significantly increased proportion of neutrophils in the PD group. Correlation between immune cells and hub genes showed SYT1, NEFM, GAP43, and GRIA1 to be significantly related to immune cells. Moreover, the microRNA-TFs-mRNA network revealed that the microRNA-92a family targets all four immune-related genes in PD pathogenesis. Finally, a nomogram exhibited a reliable capability of predicting PD based on the four immune-related genes (AUC = 0.905).ConclusionBy affecting immune infiltration, SYT1, NEFM, GAP43, and GRIA1, which are regulated by the microRNA-92a family, were identified as diagnostic biomarkers of PD. The correlation of these four genes with neutrophils and the microRNA-92a family in PD needs further investigation.

A Pilot Study to Investigate Peripheral Low-Level Chronic LPS Injection as a Model of Neutrophil Activation in the Periphery and Brain in Mice

“…Neutrophils are of therapeutic interest because they are the most abundant circulating leukocyte in humans and have been shown in both human and mouse models to be associated with a worse prognosis in neurodegenerative diseases [7][8][9]. Genes involved in neutrophil activation and adhesion have been identified in areas with blood-brain barrier (BBB) disruption and associated with disease progression [10][11][12][13]. Furthermore, humanized AD mouse model studies have shown an increase in short-term spatial memory and a decrease in capillary blood flow stalling when targeting neutrophil adhesion or accumulation [9,14,15].…”

Peripheral Low Level Chronic LPS Injection as a Model of Neutrophil Activation in the Periphery and Brain in Mice

“…Multiple studies have correlated the onset and progression of neurodegenerative diseases with proin ammatory factors and immune cell activation and accumulation [7][8][9] . Transcriptomics studies have demonstrated an increase in pro-in ammatory differentially expressed genes (DEGs) in neurodegeneration, and genes involved in neutrophil activation and adhesion have been identi ed in areas with blood brain barrier (BBB) disruption and associated with disease progression 7,[9][10][11] . Neutrophils are of therapeutic interest because they are the most abundant circulating leukocyte and have been shown in both human and mouse models to be associated with a worse prognosis in neurodegenerative diseases [12][13][14] .…”