Exploring sphingolipid metabolism-related biomarkers for Parkinson's disease: a transcriptomic analysis

探索与鞘脂代谢相关的帕金森病生物标志物:转录组学分析

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Abstract

BACKGROUND: Related studies have pointed out that sphingolipids and their metabolites are involved in the growth of neurons, and were associated with the occurrence and development of central nervous system diseases. However, the role of sphingolipid metabolism-related genes (SMRGs) in Parkinson's Disease (PD) have not been fully elucidated. METHODS: In this study, PD-related transcriptome data were extracted from the Gene Expression Omnibus (GEO) database. The DE-SMRGs were obtained by intersecting the differentially expressed genes (DEGs) screened by "limma" and the SMRGs, and the functional enrichment analysis of these DE-SMRGs was conducted by "clusterProfiler." Then, the biomarkers of PD were screened by protein-protein interaction (PPI) analysis. Based on this, three methods, including functional similarity analysis, co-expression analysis, and gene set enrichment analysis (GSEA) were conducted to study the functions of biomarkers. Moreover, the immune cell infiltration analysis was used to further study the immune-related mechanisms of biomarkers in PD. Furthermore, the mRNA-miRNA regulatory network was constructed to reveal the potential regulation of biomarkers. Finally, the targeted drugs of biomarkers were predicted for the clinical treatment of PD. RESULTS: A totals of 14 DE-SMRGs were obtained by intersecting 1,139 DEGs and 97 SMRGs, and these genes were involved in the ceramide metabolic process. Five biomarkers, including Arylsulfatase B (ARSB), N-Acylsphingosine Amidohydrolase 1 (ASAH1), Galactosidase Beta 1 (GLB1), Hexosaminidase Subunit Beta (HEXB), and Prosaposin (PSAP) were screened, and they played an important role in the immune process and are associated with immune cells such as macrophages. The expression of biomarkers was validated in clinical human samples by quantitative reverse transcription polymerase chain reaction (qRT-PCR). The expression levels of GLB1, ASAH1 and PSAP were increased in human samples, which were consistent with the bioinformatics analysis results. Moreover, the mRNA-miRNA regulatory network was constructed, and it was worth noting that hsa-miR-134-5p could regulate ARSB and ASAH1, hsa-miR-27a-3p and hsa-miR-27b-3p could regulate ASAH1 and PSAP at the same time. In addition, Chondroitin sulfate could target ARSB and HEXB simultaneously. CONCLUSION: This study identified five sphingolipid metabolism-related biomarkers (ARSB, ASAH1, GLB1, HEXB, and PSAP) of PD. This finding provided the possibility of SMRGs as biomarkers for PD.

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