Evidence map›Paper›PMID 41204291›Full record

ArticleEuropean journal of medical research2025

Identification and validation of key genes related to apoptosis in multiple organ dysfunction syndrome.

Jian Zhang, Zhi-Ying Wen, Yan-Xiao Li, Hui-Ping Sun, Ying-Ying Zheng

Abstract read
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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jian Zhang *Cardiac Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Zhi-Ying Wen *Department of Cardiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Yan-Xiao LiDepartment of Cardiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Hui-Ping SunCardiac Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Ying-Ying ZhengDepartment of Cardiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China. zhengying527@163.com.

Funding

the Natural Science Foundation of Xinjiang Uygur Autonomous Region 2022D01C237
6 · The paper itself

Abstract

backgroundApoptosis occupies a core position in the pathogenesis of multiple organ dysfunction syndrome (MODS). Therefore, exploring key mechanisms of action of apoptosis-related genes (ARGs) in MODS will play a positive and promoting role in the diagnosis and treatment of MODS.

methodsWe obtained MODS-related data from public databases, and analyzed the disparately expressed genes between MODS and controls, as well as the weighted gene co-expression network analysis (WGCNA) genes most related to MODS. The intersection with ARGs was then used to obtain candidate genes. After that, by combining Cytoscape software, machine learning algorithms with expression verification, key genes were obtained, and a nomogram model was constructed and evaluated. Next, centering on key genes, gene set enrichment analysis, immune infiltration analysis, small ubiquitin-like modifier (SUMO) analysis, regulatory network construction, and drug prediction were carried out. At last, the expression of key genes in clinical samples was validated.

resultsAfter screening, S100A9, S100A8, and BCL2A1 were identified as the key genes of MODS. They were all significantly highly expressed in MODS and jointly participated in "oxidative phosphorylation" signaling pathway. The nomogram constructed based on the key genes had excellent predictive ability. There were 15 types of differentially infiltrated immune cells between MODS and controls, and they were correlated with the key genes. In addition, each of the key genes had two or more SUMOylation sites, and multiple miRNAs (hsa-let-7d-5p) and lncRNAs (XIST) were predicted. Subsequently, the key genes also jointly predicted potential drugs (curcumin). Finally, in clinical samples of MODS, the key genes also showed high expression.

conclusionS100A9, S100A8, and BCL2A1 were the key genes of MODS in terms of apoptosis. The constructed nomogram had an excellent predictive value. It offers a novel approach and potential targeted therapy for the clinical diagnosis and treatment of MODS.

Indexed as

ApoptosisMultiple Organ FailureGene Expression ProfilingGene Regulatory NetworksHumansNomogramsApoptosisKey genesMultiple organ dysfunction syndromeNomogramPredictive

Identifiers

PMID41204291
PMCPMC12595649

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