Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy

IF 4.5 3区 医学 Q2 IMMUNOLOGY Clinical immunology Pub Date : 2024-06-27 DOI:10.1016/j.clim.2024.110301
Xuelian Li , Shijiu Jiang , Boyuan Wang , Shaolin He , Xiaopeng Guo , Jibin Lin , Yumiao Wei
{"title":"Integrated multi-omics analysis and machine learning developed diagnostic markers and prognostic model based on Efferocytosis-associated signatures for septic cardiomyopathy","authors":"Xuelian Li ,&nbsp;Shijiu Jiang ,&nbsp;Boyuan Wang ,&nbsp;Shaolin He ,&nbsp;Xiaopeng Guo ,&nbsp;Jibin Lin ,&nbsp;Yumiao Wei","doi":"10.1016/j.clim.2024.110301","DOIUrl":null,"url":null,"abstract":"<div><p>Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.</p></div>","PeriodicalId":10392,"journal":{"name":"Clinical immunology","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical immunology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1521661624004108","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Septic cardiomyopathy (SCM) is characterized by an abnormal inflammatory response and increased mortality. The role of efferocytosis in SCM is not well understood. We used integrated multi-omics analysis to explore the clinical and genetic roles of efferocytosis in SCM. We identified six module genes (ATP11C, CD36, CEBPB, MAPK3, MAPKAPK2, PECAM1) strongly associated with SCM, leading to an accurate predictive model. Subgroups defined by EFFscore exhibited distinct clinical features and immune infiltration levels. Survival analysis showed that the C1 subtype with a lower EFFscore had better survival outcomes. scRNA-seq analysis of peripheral blood mononuclear cells (PBMCs) from sepsis patients identified four genes (CEBPB, CD36, PECAM1, MAPKAPK2) associated with high EFFscores, highlighting their role in SCM. Molecular docking confirmed interactions between diagnostic genes and tamibarotene. Experimental validation supported our computational results. In conclusion, our study identifies a novel efferocytosis-related SCM subtype and diagnostic biomarkers, offering new insights for clinical diagnosis and therapy.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
综合多组学分析和机器学习,开发出基于埃弗细胞增多症相关特征的脓毒性心肌病诊断标记和预后模型。
化脓性心肌病(SCM)的特点是炎症反应异常和死亡率升高。流出细胞在 SCM 中的作用尚不十分清楚。我们利用综合多组学分析探索了流出细胞在 SCM 中的临床和遗传作用。我们发现了六个与 SCM 密切相关的模块基因(ATP11C、CD36、CEBPB、MAPK3、MAPKAPK2 和 PECAM1),从而建立了一个准确的预测模型。根据 EFFscore 定义的亚组表现出不同的临床特征和免疫浸润水平。脓毒症患者外周血单核细胞(PBMCs)的 scRNA-seq 分析发现了四个与高 EFFscores 相关的基因(CEBPB、CD36、PECAM1、MAPKAPK2),突显了它们在 SCM 中的作用。分子对接证实了诊断基因与他米巴罗汀之间的相互作用。实验验证支持了我们的计算结果。总之,我们的研究发现了一种新的与流出相关的 SCM 亚型和诊断生物标志物,为临床诊断和治疗提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Clinical immunology
Clinical immunology 医学-免疫学
CiteScore
12.30
自引率
1.20%
发文量
212
审稿时长
34 days
期刊介绍: Clinical Immunology publishes original research delving into the molecular and cellular foundations of immunological diseases. Additionally, the journal includes reviews covering timely subjects in basic immunology, along with case reports and letters to the editor.
期刊最新文献
Carrier frequency and incidence estimation of deficiency of adenosine deaminase 2 in the Chinese population based on massive exome sequencing data Editorial Board Corrigendum to "Immunomodulatory effect of Lactococcus lactis JCM5805 on human plasmacytoid dendritic cells" [Clinical Immunology 149/3PB (2013) 509-518]. Aberrant overexpression of the autoantigen protein vimentin promotes Th17 cell differentiation and autoimmune arthritis via activation of STAT3 signaling Characterization of primary Sjögren's syndrome in the Taiwan Han population through a genome-wide association study and polygenic risk score analysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1