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人类主动脉夹层中与衰老相关基因特征的综合分析。

Comprehensive analysis of gene signatures associated with aging in human aortic dissection.

作者信息

Yan Jingyi, Tan Xuerui

机构信息

Department of Cardiology, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, China.

Clinical Research Center, First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, 515041, China.

出版信息

Heliyon. 2024 May 17;10(11):e31298. doi: 10.1016/j.heliyon.2024.e31298. eCollection 2024 Jun 15.

DOI:10.1016/j.heliyon.2024.e31298
PMID:38828294
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11140614/
Abstract

BACKGROUND

Aortic dissection (AD) is a lethal aortic disease with limited effective therapeutic strategies. Aging increases the risk of AD, yet the underlying mechanisms remain unclear. This study aims to analyze the association of aging-related genes (Args) and AD using bioinformatic analysis. This helps provide novel insights into AD pathogenesis and contributes to developing novel therapeutic strategies.

METHODS

mRNA (GSE52093, GSE153434), miRNA (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded from GEO database. Args were downloaded from Aging Atlas database. Differentially-expressed Args were determined by intersecting Args and differentially-expressed mRNAs of two mRNA datasets. Cytoscape was used to identify hub genes and construct hub gene regulatory networks related to miRNAs. Seurat and clusterProfiler R package were used for investigating expression patterns of hub genes at single-cell level, and functional analysis, respectively. To validate the cellular expression pattern of hub genes, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determined using the DGIdb database.

RESULTS

HGF, , , , , and were identified as aging-related hub genes in AD. miR-221-3p was predicted to interact with . A decreased expression in smooth muscle cell subpopulation 4 (SMC4) was observed in AD versus normal aortic tissues, which was validated by sequencing 197,605 aortic cells from 13 AD patients. Additionally, upregulated genes of SMC4 in AD tissues were enriched in the "cellular senescence" pathway. These data indicated that decreased might promote SMC4 aging during AD formation. Eleven existing drugs targeting hub genes were identified, including ruxolitinib and filgrastim, which are associated with AD.

CONCLUSIONS

By sequencing transcriptomic data, this study revealed aging-related hub genes and regulatory network involved in AD formation. Additionally, this study proposed a noteworthy hypothesis that downregulated may exacerbate AD by promoting SMC aging, which requires further investigation.

摘要

背景

主动脉夹层(AD)是一种致命的主动脉疾病,有效的治疗策略有限。衰老会增加AD的风险,但其潜在机制仍不清楚。本研究旨在通过生物信息学分析来分析衰老相关基因(Args)与AD的关联。这有助于为AD的发病机制提供新的见解,并有助于开发新的治疗策略。

方法

从GEO数据库下载AD的mRNA(GSE52093、GSE153434)、miRNA(GSE98770)和单细胞RNA测序(scRNA-seq,GSE213740)数据集。从衰老图谱数据库下载Args。通过将Args与两个mRNA数据集的差异表达mRNA相交来确定差异表达的Args。使用Cytoscape识别枢纽基因并构建与miRNA相关的枢纽基因调控网络。分别使用Seurat和clusterProfiler R包在单细胞水平研究枢纽基因的表达模式和功能分析。为了验证枢纽基因的细胞表达模式,对我们自己的scRNA-seq数据进行了相同的分析。使用DGIdb数据库确定靶向枢纽Args的药物。

结果

HGF、 、 、 、 、 和 被确定为AD中与衰老相关的枢纽基因。预测miR-221-3p与 相互作用。与正常主动脉组织相比,在AD中观察到平滑肌细胞亚群4(SMC4)中 表达降低,这通过对13例AD患者的197,605个主动脉细胞进行测序得到验证。此外,AD组织中SMC4的上调基因在“细胞衰老”途径中富集。这些数据表明, 在AD形成过程中表达降低可能促进SMC4衰老。确定了11种现有的靶向枢纽基因的药物,包括与AD相关的鲁索替尼和非格司亭。

结论

通过对转录组数据进行测序,本研究揭示了与衰老相关的枢纽基因和参与AD形成的调控网络。此外,本研究提出了一个值得注意的假设,即 下调可能通过促进SMC衰老而加重AD,这需要进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/84e765c643b9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/05a6a07c879b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/b3356b36cf55/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/2c95de8ca8fe/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/d1708be917f2/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/64ca3cd522ee/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/117c0de8dcdd/gr6a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/84e765c643b9/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/05a6a07c879b/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/b3356b36cf55/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/2c95de8ca8fe/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/d1708be917f2/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/64ca3cd522ee/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/117c0de8dcdd/gr6a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/032a/11140614/84e765c643b9/gr7.jpg

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