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颈动脉粥样硬化与帕金森病潜在共同致病机制的生物信息学分析

Bioinformatics analysis of potential common pathogenic mechanism for carotid atherosclerosis and Parkinson's disease.

作者信息

Wang Quan, Xue Qun

机构信息

Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China.

出版信息

Front Aging Neurosci. 2023 Aug 15;15:1202952. doi: 10.3389/fnagi.2023.1202952. eCollection 2023.

Abstract

BACKGROUND

Cerebrovascular disease (CVD) related to atherosclerosis and Parkinson's disease (PD) are two prevalent neurological disorders. They share common risk factors and frequently occur together. The aim of this study is to investigate the association between atherosclerosis and PD using genetic databases to gain a comprehensive understanding of underlying biological mechanisms.

METHODS

The gene expression profiles of atherosclerosis (GSE28829 and GSE100927) and PD (GSE7621 and GSE49036) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for these two disorders, we constructed protein-protein interaction (PPI) networks and functional modules, and further identified hub genes using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The diagnostic effectiveness of these hub genes was evaluated using Receiver Operator Characteristic Curve (ROC) analysis. Furthermore, we used single sample gene set enrichment analysis (ssGSEA) to analyze immune cell infiltration and explored the association of the identified hub genes with infiltrating immune cells through Spearman's rank correlation analysis in R software.

RESULTS

A total of 50 shared DEGs, with 36 up-regulated and 14 down-regulated genes, were identified through the intersection of DEGs of atherosclerosis and PD. Using LASSO regression, we identified six hub genes, namely C1QB, CD53, LY96, P2RX7, C3, and TNFSF13B, in the lambda.min model, and CD14, C1QB, CD53, P2RX7, C3, and TNFSF13B in the lambda.1se model. ROC analysis confirmed that both models had good diagnostic efficiency for atherosclerosis datasets GSE28829 (lambda.min AUC = 0.99, lambda.1se AUC = 0.986) and GSE100927 (lambda.min AUC = 0.922, lambda.1se AUC = 0.933), as well as for PD datasets GSE7621 (lambda.min AUC = 0.924, lambda.1se AUC = 0.944) and GSE49036 (lambda.min AUC = 0.894, lambda.1se AUC = 0.881). Furthermore, we found that activated B cells, effector memory CD8 + T cells, and macrophages were the shared correlated types of immune cells in both atherosclerosis and PD.

CONCLUSION

This study provided new sights into shared molecular mechanisms between these two disorders. These common hub genes and infiltrating immune cells offer promising clues for further experimental studies to explore the common pathogenesis of these disorders.

摘要

背景

与动脉粥样硬化相关的脑血管疾病(CVD)和帕金森病(PD)是两种常见的神经系统疾病。它们有共同的危险因素且常同时发生。本研究旨在利用基因数据库调查动脉粥样硬化与PD之间的关联,以全面了解潜在的生物学机制。

方法

从基因表达综合数据库(GEO)下载动脉粥样硬化(GSE28829和GSE100927)和PD(GSE7621和GSE49036)的基因表达谱。在确定这两种疾病的共同差异表达基因(DEGs)后,我们构建了蛋白质-蛋白质相互作用(PPI)网络和功能模块,并使用最小绝对收缩和选择算子(LASSO)回归进一步鉴定枢纽基因。使用受试者工作特征曲线(ROC)分析评估这些枢纽基因的诊断效能。此外,我们使用单样本基因集富集分析(ssGSEA)分析免疫细胞浸润,并通过R软件中的Spearman等级相关分析探索鉴定出的枢纽基因与浸润免疫细胞的关联。

结果

通过动脉粥样硬化和PD的DEGs交集,共鉴定出50个共享的DEGs,其中36个基因上调,14个基因下调。使用LASSO回归,我们在lambda.min模型中鉴定出6个枢纽基因,即C1QB、CD53、LY96、P2RX7、C3和TNFSF13B,在lambda.1se模型中鉴定出CD14、C1QB、CD53、P2RX7、C3和TNFSF13B。ROC分析证实,这两个模型对动脉粥样硬化数据集GSE28829(lambda.min AUC = 0.99,lambda.1se AUC = 0.986)和GSE100927(lambda.min AUC = 0.922,lambda.1se AUC = 0.933)以及PD数据集GSE7621(lambda.min AUC = 0.924,lambda.1se AUC = 0.944)和GSE49036(lambda.min AUC = 0.894,lambda.1se AUC = 0.881)均具有良好的诊断效率。此外,我们发现活化B细胞、效应记忆CD8 + T细胞和巨噬细胞是动脉粥样硬化和PD中共同的相关免疫细胞类型。

结论

本研究为这两种疾病之间的共同分子机制提供了新的见解。这些共同的枢纽基因和浸润免疫细胞为进一步的实验研究探索这些疾病的共同发病机制提供了有希望的线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6ac4/10464527/6f265f60c713/fnagi-15-1202952-g001.jpg

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