Identification of necroptosis-related genes in Parkinson's disease by integrated bioinformatics analysis and experimental validation

被引:7
|
作者
Cheng, Lei [1 ]
Zhou, Zhongyan [2 ]
Shi, Wenting [2 ]
Zhang, Jing [2 ]
Qin, Liyun [3 ]
Hu, Hongyi [2 ]
Yan, Juntao [4 ]
Ye, Qing [3 ]
机构
[1] Shanghai Univ Tradit Chinese Med, Longhua Hosp, Dept Tuina, Shanghai, Peoples R China
[2] Shanghai Univ Tradit Chinese Med, Longhua Hosp, Cardiovasc Res Lab, Shanghai, Peoples R China
[3] Shanghai Univ Tradit Chinese Med, Longhua Hosp, Dept Neurol, Shanghai, Peoples R China
[4] Shanghai Univ Tradit Chinese Med, Yueyang Hosp Integrated Tradit Chinese Med & Weste, Dept Tuina, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
parkinson's disease; programmed cell; death; necroptosis; inflammation; integrated bioinformatics analysis; immune infiltration; macrophage; DATABASE; CELLS;
D O I
10.3389/fnins.2023.1097293
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
BackgroundParkinson's disease (PD) is the second most common neurodegeneration disease worldwide. Necroptosis, which is a new form of programmed cell death with high relationship with inflammation, plays a vital role in the progression of PD. However, the key necroptosis related genes in PD are not fully elucidated. PurposeIdentification of key necroptosis-related genes in PD. MethodThe PD associated datasets and necroptosis related genes were downloaded from the GEO Database and GeneCards platform, respectively. The DEGs associated with necroptosis in PD were obtained by gap analysis, and followed by cluster analysis, enrichment analysis and WGCNA analysis. Moreover, the key necroptosis related genes were generated by PPI network analysis and their relationship by spearman correlation analysis. Immune infiltration analysis was used for explore the immune state of PD brain accompanied with the expression levels of these genes in various types of immune cells. Finally, the gene expression levels of these key necroptosis related genes were validated by an external dataset, blood samples from PD patients and toxin-induced PD cell model using real-time PCR analysis. ResultTwelve key necroptosis-related genes including ASGR2, CCNA1, FGF10, FGF19, HJURP, NTF3, OIP5, RRM2, SLC22A1, SLC28A3, WNT1 and WNT10B were identified by integrated bioinformatics analysis of PD related dataset GSE7621. According to the correlation analysis of these genes, RRM2 and WNT1 were positively and negatively correlated with SLC22A1 respectively, while WNT10B was positively correlated with both OIF5 and FGF19. As the results from immune infiltration analysis, M2 macrophage was the highest population of immune cell in analyzed PD brain samples. Moreover, we found that 3 genes (CCNA1, OIP5 and WNT10B) and 9 genes (ASGR2, FGF10, FGF19, HJURP, NTF3, RRM2, SLC22A1, SLC28A3 and WNT1) were down- and up- regulated in an external dataset GSE20141, respectively. All the mRNA expression levels of these 12 genes were obviously upregulated in 6-OHDA-induced SH-SY5Y cell PD model while CCNA1 and OIP5 were up- and down- regulated, respectively, in peripheral blood lymphocytes of PD patients. ConclusionNecroptosis and its associated inflammation play fundamental roles in the progression of PD and these identified 12 key genes might be served as new diagnostic markers and therapeutic targets for PD.
引用
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页数:14
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