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整合分析与缺血性脑卒中内质网应激相关的生物标志物。

Integrative Analyses of Biomarkers Associated with Endoplasmic Reticulum Stress in Ischemic Stroke.

机构信息

Center of Interventional Medicine, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, China.

Library, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong Province, 519000, China.

出版信息

Comput Math Methods Med. 2022 Aug 25;2022:4212180. doi: 10.1155/2022/4212180. eCollection 2022.

DOI:10.1155/2022/4212180
PMID:36060663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9436554/
Abstract

BACKGROUND

Neuronal apoptosis, which is the primary pathological transform of cerebral injury following ischemic stroke (IS), is considered to be induced by endoplasmic reticulum stress (ERS) by numerous reports. However, ERS biomarkers in IS have not been fully identified yet. Consequently, the present study is aimed at exploring potential blood biomarkers by investigating the molecular mechanisms of ERS promoting neuronal apoptosis following IS development.

METHODS

A comprehensive analysis was performed with two free-accessible whole-blood datasets (GSE16561 and GSE37587) from the Gene Expression Omnibus database. Genetic information from 107 IS and 24 healthy controls was employed to analyze the differentially expressed genes (DEGs). Genes related to ERS (ERS-DEGs) were identified from the analysis. Enrichment analyses were performed to explore the biofunction and correlated signal pathways of ERS-DEGs. Protein-protein interaction (PPI) network and immune correlation analyses were performed to identify the hub genes along with their correspondent expressions and functions, all of which contributed to incremental diagnostic values.

RESULTS

A total of 60 IS-related DEGs were identified, of which 27 genes were confirmed as ERS-DEGs. GO and KEGG enrichment analysis corroborated that upregulated ERS-DEGs were principally enriched in pathways related to immunity, including neutrophil activation and Th17 cell differentiation. Moreover, the GSEA and GSVA indicated that T cell-related signal pathways were the most considerably immune pathways for ERS-DEG enrichment. A total of 10 hub genes were filtered out via the PPI network analysis. Immune correlation analysis confirmed that the expression of hub genes is associated with immune cell infiltration.

CONCLUSIONS

By integrating and analyzing the two gene expression data profiles, it can be inferred that ERS may be involved in the development of neuronal apoptosis following IS via immune homeostasis. The identified hub genes, which are associated with immune cell infiltration, may serve as potential biomarkers for relative diagnosis and therapy.

摘要

背景

神经元凋亡是缺血性脑卒中(IS)后脑损伤的主要病理转化,大量研究认为其是由内质网应激(ERS)引起的。然而,IS 中的 ERS 生物标志物尚未完全确定。因此,本研究旨在通过研究 ERS 促进 IS 发展后神经元凋亡的分子机制,探索潜在的血液生物标志物。

方法

从基因表达综合数据库(GEO)中使用两个免费的全血数据集(GSE16561 和 GSE37587)进行综合分析。使用 107 例 IS 和 24 例健康对照的遗传信息分析差异表达基因(DEGs)。从分析中确定与 ERS 相关的基因(ERS-DEGs)。进行富集分析以探讨 ERS-DEGs 的生物功能和相关信号通路。进行蛋白质-蛋白质相互作用(PPI)网络和免疫相关分析,以确定关键基因及其对应表达和功能,所有这些都有助于增加诊断价值。

结果

共鉴定出 60 个与 IS 相关的 DEG,其中 27 个基因被确认为 ERS-DEG。GO 和 KEGG 富集分析证实,上调的 ERS-DEG 主要富集在与免疫相关的途径中,包括中性粒细胞激活和 Th17 细胞分化。此外,GSEA 和 GSVA 表明,T 细胞相关信号通路是 ERS-DEG 富集最显著的免疫途径。通过 PPI 网络分析筛选出 10 个关键基因。免疫相关分析证实,关键基因的表达与免疫细胞浸润有关。

结论

通过整合和分析这两个基因表达数据谱,可以推断 ERS 可能通过免疫稳态参与 IS 后神经元凋亡的发生。与免疫细胞浸润相关的鉴定出的关键基因可能作为潜在的生物标志物用于相关诊断和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/9ccb4e73448c/CMMM2022-4212180.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/30c6ad4a89d1/CMMM2022-4212180.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/b10d925139f8/CMMM2022-4212180.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/ea618a860883/CMMM2022-4212180.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/da2ff5a27e87/CMMM2022-4212180.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/1b0d967abcf5/CMMM2022-4212180.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/4f1596866f40/CMMM2022-4212180.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/c156896d7037/CMMM2022-4212180.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/9ccb4e73448c/CMMM2022-4212180.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/30c6ad4a89d1/CMMM2022-4212180.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/b10d925139f8/CMMM2022-4212180.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/ea618a860883/CMMM2022-4212180.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/da2ff5a27e87/CMMM2022-4212180.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/1b0d967abcf5/CMMM2022-4212180.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/4f1596866f40/CMMM2022-4212180.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/c156896d7037/CMMM2022-4212180.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8d9a/9436554/9ccb4e73448c/CMMM2022-4212180.008.jpg

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