Evidence map›Paper›PMID 38867262›Full record

ArticleEuropean journal of medical research2024

Comprehensive transcriptomic analysis unveils macrophage-associated genes for establishing an abdominal aortic aneurysm diagnostic model and molecular therapeutic framework.

Zhen Wu, Weiming Yu, Jie Luo, Guanghui Shen, Zhongqi Cui, Wenxuan Ni, Haiyang Wang

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In one paragraph

Article in European journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
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5citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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  3. Recent advances on the role of G0S2.Discover oncology · 2025
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhen Wu *Department of Vascular and Interventional Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China.
Weiming Yu *Department of Vascular and Interventional Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China.
Jie Luo *Department of Vascular and Interventional Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China.
Guanghui ShenDepartment of Vascular and Interventional Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China.
Zhongqi CuiDepartment of Clinical Laboratory, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, China.
Wenxuan NiDepartment of Clinical Laboratory, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, China. nnwwxx7@126.com.
Haiyang WangDepartment of Vascular and Interventional Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, Heilongjiang, China. wanghaiyanghmu@163.com.

Funding

National Natural Science Foundation of China 82170501
6 · The paper itself

Abstract

backgroundAbdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease. The aim of this research is to identify new biomarkers and therapeutic targets for the treatment of such deadly diseases.

methodsSingle-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms were used to identify distinct immune cell infiltration types between AAA and normal abdominal aortas. Single-cell RNA sequencing data were used to analyse the hallmark genes of AAA-associated macrophage cell subsets. Six macrophage-related hub genes were identified through weighted gene co-expression network analysis (WGCNA) and validated for expression in clinical samples and AAA mouse models. We screened potential therapeutic drugs for AAA through online Connectivity Map databases (CMap). A network-based approach was used to explore the relationships between the candidate genes and transcription factors (TFs), lncRNAs, and miRNAs. Additionally, we also identified hub genes that can effectively identify AAA and atherosclerosis (AS) through a variety of machine learning algorithms.

resultsWe obtained six macrophage hub genes (IL-1B, CXCL1, SOCS3, SLC2A3, G0S2, and CCL3) that can effectively diagnose abdominal aortic aneurysm. The ROC curves and decision curve analysis (DCA) were combined to further confirm the good diagnostic efficacy of the hub genes. Further analysis revealed that the expression of the six hub genes mentioned above was significantly increased in AAA patients and mice. We also constructed TF regulatory networks and competing endogenous RNA networks (ceRNA) to reveal potential mechanisms of disease occurrence. We also obtained two key genes (ZNF652 and UBR5) through a variety of machine learning algorithms, which can effectively distinguish abdominal aortic aneurysm and atherosclerosis.

conclusionOur findings depict the molecular pharmaceutical network in AAA, providing new ideas for effective diagnosis and treatment of diseases.

Indexed as

Aortic Aneurysm, AbdominalGene Expression ProfilingMacrophagesAnimalsBiomarkersDisease Models, AnimalGene Regulatory NetworksHumansMiceTranscriptomeBiomarkersAbdominal aortic aneurysmAtherosclerosisMachine learningMacrophage marker genesSingle-cell sequencing

Identifiers

PMID38867262
PMCPMC11167832

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.