Identification of cuproptosis-realated key genes and pathways in Parkinson’s disease via bioinformatics analysis

• Published in: PloS one Vol. 19; no. 4; p. e0299898
• Main Authors: Song, Jia, Li, Jia, Pei, Xiaochen, Chen, Jiajun, Wang, Lin
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 16.04.2024; Public Library of Science (PLoS)
• Subjects: Biology and life sciences; Cell Death; Cellular signal transduction; Computational Biology; Computer and Information Sciences; Control Groups; Diseases; Genes; Genetic aspects; Genomics; Health aspects; Humans; Identification and classification; Medical research; Medicine and Health Sciences; Medicine, Experimental; MicroRNA; MicroRNAs - genetics; Parkinson Disease - genetics; Parkinson's disease; Physiological aspects; Protein-protein interactions; Research and Analysis Methods; Taiwan; China; Taiwan
• DOI: 10.1371/journal.pone.0299898
• ISSN: 1932-6203

Parkinson's disease (PD) is the second most common worldwide age-related neurodegenerative disorder without effective treatments. Cuproptosis is a newly proposed conception of cell death extensively studied in oncological diseases. Currently, whether cuproptosis contributes to PD remains largely unclear. The dataset GSE22491 was studied as the training dataset, and GSE100054 was the validation dataset. According to the expression levels of cuproptosis-related genes (CRGs) and differentially expressed genes (DEGs) between PD patients and normal samples, we obtained the differentially expressed CRGs. The protein-protein interaction (PPI) network was achieved through the Search Tool for the Retrieval of Interacting Genes. Meanwhile, the disease-associated module genes were screened from the weighted gene co-expression network analysis (WGCNA). Afterward, the intersection genes of WGCNA and PPI were obtained and enriched using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the key genes were identified from the datasets. The receiver operating characteristic curves were plotted and a PPI network was constructed, and the PD-related miRNAs and key genes-related miRNAs were intersected and enriched. Finally, the 2 hub genes were verified via qRT-PCR in the cell model of the PD and the control group. 525 DEGs in the dataset GSE22491 were identified, including 128 upregulated genes and 397 downregulated genes. Based on the PPI network, 41 genes were obtained. Additionally, the dataset was integrated into 34 modules by WGCNA. 36 intersection genes found from WGCNA and PPI were significantly abundant in 7 pathways. The expression levels of the genes were validated, and 2 key genes were obtained, namely peptidase inhibitor 3 (PI3) and neuroserpin family I member 1 (SERPINI1). PD-related miRNAs and key genes-related miRNAs were intersected into 29 miRNAs including hsa-miR-30c-2-3p. At last, the qRT-PCR results of 2 hub genes showed that the expressions of mRNA were up-regulated in PD. Taken together, this study demonstrates the coordination of cuproptosis in PD. The key genes and miRNAs offer novel perspectives in the pathogenesis and molecular targeting treatment for PD.