• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于加权基因共表达网络分析的冠心病关键基因鉴定及其与免疫浸润的相关性。

Identification of key genes in coronary artery disease: an integrative approach based on weighted gene co-expression network analysis and their correlation with immune infiltration.

机构信息

Fourth Affiliated Hospital of China Medical University, Huanggu, Shenyang 110032, Liaoning, China.

出版信息

Aging (Albany NY). 2021 Mar 3;13(6):8306-8319. doi: 10.18632/aging.202638.

DOI:10.18632/aging.202638
PMID:33686958
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8034924/
Abstract

This study aimed to identify key genes related to coronary artery disease (CAD) and its association with immune cells infiltration. GSE20680 and GSE20681 were downloaded from GEO. We identified red and pink modules in WGCNA analysis and found 104 genes in these two modules. Next, least absolute shrinkage and selection operator (LASSO) logistic regression was used to screen and verify the diagnostic markers of CAD. We identified ASCC2, LRRC18, and SLC25A37 as the key genes in CAD diagnosis. We further studied the immune cells infiltration in CAD patients with CIBERSORT, and the correlation between key genes and infiltrating immune cells was analyzed. We also found immune cells, including macrophages M0, mast cells resting and T cells CD8, were associated with ASCC2, LRRC18 and SLC25A37. Gene enrichment analysis indicated that these genes mainly enriched in apoptotic signaling pathway for biological pathway analysis, riboflavin metabolism for KEGG analysis. The diagnostic efficiency of these key genes measured by AUC in the training set, testing set and validation cohort was 0.92, 0.96 and 0.83, respectively. In conclusion, ASCC2, LRRC18 and SLC25A37 can be used as diagnostic markers of CAD, and immune cell infiltration plays an important role in the onset and development of CAD.

摘要

本研究旨在鉴定与冠状动脉疾病(CAD)相关的关键基因及其与免疫细胞浸润的关系。从 GEO 下载了 GSE20680 和 GSE20681。我们在 WGCNA 分析中鉴定了红色和粉色模块,并在这两个模块中找到了 104 个基因。接下来,使用最小绝对收缩和选择算子(LASSO)逻辑回归筛选和验证 CAD 的诊断标志物。我们鉴定出 ASCC2、LRRC18 和 SLC25A37 是 CAD 诊断的关键基因。我们进一步使用 CIBERSORT 研究了 CAD 患者的免疫细胞浸润,并分析了关键基因与浸润免疫细胞的相关性。我们还发现与 ASCC2、LRRC18 和 SLC25A37 相关的免疫细胞包括巨噬细胞 M0、静止肥大细胞和 T 细胞 CD8。基因富集分析表明,这些基因主要富集在凋亡信号通路的生物通路分析中,KEGG 分析中的核黄素代谢。这些关键基因在训练集、测试集和验证队列中的 AUC 测量的诊断效率分别为 0.92、0.96 和 0.83。总之,ASCC2、LRRC18 和 SLC25A37 可以作为 CAD 的诊断标志物,免疫细胞浸润在 CAD 的发生和发展中起着重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/6d30dd6bdd09/aging-13-202638-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/75b22d6db2b5/aging-13-202638-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/95adc316da35/aging-13-202638-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/803921223af8/aging-13-202638-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/b28e99a70931/aging-13-202638-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/c570bc3a51f5/aging-13-202638-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/f3568388bc4b/aging-13-202638-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/6d30dd6bdd09/aging-13-202638-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/75b22d6db2b5/aging-13-202638-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/95adc316da35/aging-13-202638-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/803921223af8/aging-13-202638-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/b28e99a70931/aging-13-202638-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/c570bc3a51f5/aging-13-202638-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/f3568388bc4b/aging-13-202638-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1533/8034924/6d30dd6bdd09/aging-13-202638-g007.jpg

相似文献

1
Identification of key genes in coronary artery disease: an integrative approach based on weighted gene co-expression network analysis and their correlation with immune infiltration.基于加权基因共表达网络分析的冠心病关键基因鉴定及其与免疫浸润的相关性。
Aging (Albany NY). 2021 Mar 3;13(6):8306-8319. doi: 10.18632/aging.202638.
2
Identification of potential M2 macrophage-associated diagnostic biomarkers in coronary artery disease.冠心病中潜在 M2 巨噬细胞相关诊断生物标志物的鉴定。
Biosci Rep. 2022 Dec 22;42(12). doi: 10.1042/BSR20221394.
3
Identification of immune-related key genes in the peripheral blood of ischaemic stroke patients using a weighted gene coexpression network analysis and machine learning.基于加权基因共表达网络分析和机器学习的缺血性脑卒中患者外周血免疫相关关键基因的鉴定。
J Transl Med. 2022 Aug 12;20(1):361. doi: 10.1186/s12967-022-03562-w.
4
Immune-related potential biomarkers and therapeutic targets in coronary artery disease.冠状动脉疾病中与免疫相关的潜在生物标志物和治疗靶点。
Front Cardiovasc Med. 2023 Jan 6;9:1055422. doi: 10.3389/fcvm.2022.1055422. eCollection 2022.
5
Identification of potential biomarkers for atrial fibrillation and stable coronary artery disease based on WGCNA and machine algorithms.基于 WGCNA 和机器学习算法鉴定心房颤动和稳定型冠状动脉疾病的潜在生物标志物。
BMC Cardiovasc Disord. 2024 Aug 2;24(1):401. doi: 10.1186/s12872-024-04062-z.
6
Identification of hub genes and their correlation with immune infiltration in coronary artery disease through bioinformatics and machine learning methods.通过生物信息学和机器学习方法鉴定冠心病中的枢纽基因及其与免疫浸润的相关性。
J Thorac Dis. 2022 Jul;14(7):2621-2634. doi: 10.21037/jtd-22-632.
7
In Silico Identification of Key Genes and Immune Infiltration Characteristics in Epicardial Adipose Tissue from Patients with Coronary Artery Disease.基于生物信息学的方法鉴定冠心病患者心外膜脂肪组织中的关键基因和免疫浸润特征。
Biomed Res Int. 2022 Oct 29;2022:5610317. doi: 10.1155/2022/5610317. eCollection 2022.
8
Identification of diagnostic biomarkers and immune cell infiltration in coronary artery disease by machine learning, nomogram, and molecular docking.基于机器学习、列线图和分子对接技术鉴定冠心病的诊断生物标志物和免疫细胞浸润。
Front Immunol. 2024 Apr 2;15:1368904. doi: 10.3389/fimmu.2024.1368904. eCollection 2024.
9
Immune Cell Infiltration Analysis Based on Bioinformatics Reveals Novel Biomarkers of Coronary Artery Disease.基于生物信息学的免疫细胞浸润分析揭示冠状动脉疾病的新型生物标志物
J Inflamm Res. 2023 Jul 26;16:3169-3184. doi: 10.2147/JIR.S416329. eCollection 2023.
10
CD8 T and NK cells characterized by upregulation of NPEPPS and ABHD17A are associated with the co-occurrence of type 2 diabetes and coronary artery disease.以NPEPPS和ABHD17A上调为特征的CD8 T细胞和自然杀伤细胞与2型糖尿病和冠状动脉疾病的共病有关。
Front Immunol. 2024 Feb 23;15:1267963. doi: 10.3389/fimmu.2024.1267963. eCollection 2024.

引用本文的文献

1
Immunophenotyping identifies key immune biomarkers for coronary artery disease through machine learning.免疫表型分析通过机器学习识别冠状动脉疾病的关键免疫生物标志物。
PLoS One. 2025 Aug 26;20(8):e0328811. doi: 10.1371/journal.pone.0328811. eCollection 2025.
2
Identifying pyroptosis- and inflammation-related genes in spinal cord injury based on bioinformatics analysis.基于生物信息学分析鉴定脊髓损伤中与焦亡和炎症相关的基因。
Sci Rep. 2025 Jul 14;15(1):25424. doi: 10.1038/s41598-025-10541-w.
3
Genetic alterations in coronary cell lines exposed to sirolimus and paclitaxel.

本文引用的文献

1
Role of mechanical stress and neutrophils in the pathogenesis of plaque erosion.机械应力和中性粒细胞在斑块侵蚀发病机制中的作用。
Atherosclerosis. 2021 Feb;318:60-69. doi: 10.1016/j.atherosclerosis.2020.11.002. Epub 2020 Nov 6.
2
Mitochondrion-mediated iron accumulation promotes carcinogenesis and Warburg effect through reactive oxygen species in osteosarcoma.线粒体介导的铁积累通过活性氧促进骨肉瘤的致癌作用和瓦伯格效应。
Cancer Cell Int. 2020 Aug 18;20:399. doi: 10.1186/s12935-020-01494-3. eCollection 2020.
3
Cardiac Mast Cells: Underappreciated Immune Cells in Cardiovascular Homeostasis and Disease.
暴露于西罗莫司和紫杉醇的冠状动脉细胞系中的基因改变。
Arch Toxicol. 2025 Jun 6. doi: 10.1007/s00204-025-04101-4.
4
Integrating bulk and single-cell RNA sequencing data reveals epithelial-mesenchymal transition molecular subtype and signature to predict prognosis, immunotherapy efficacy, and drug candidates in low-grade gliomas.整合批量和单细胞RNA测序数据揭示上皮-间质转化分子亚型及特征,以预测低级别胶质瘤的预后、免疫治疗疗效和候选药物。
Front Pharmacol. 2023 Nov 20;14:1276466. doi: 10.3389/fphar.2023.1276466. eCollection 2023.
5
Gene modules and genes associated with postoperative atrial fibrillation: weighted gene co-expression network analysis and circRNA-miRNA-mRNA regulatory network analysis.与术后房颤相关的基因模块和基因:加权基因共表达网络分析及环状RNA-微小RNA-信使RNA调控网络分析
J Thorac Dis. 2023 Sep 28;15(9):4949-4960. doi: 10.21037/jtd-23-1179. Epub 2023 Sep 26.
6
Identifying pyroptosis- and inflammation-related genes in intracranial aneurysms based on bioinformatics analysis.基于生物信息学分析鉴定颅内动脉瘤中的细胞焦亡和炎症相关基因。
Biol Res. 2023 Sep 27;56(1):50. doi: 10.1186/s40659-023-00464-z.
7
Identification and validation of potential hypoxia-related genes associated with coronary artery disease.与冠状动脉疾病相关的潜在缺氧相关基因的鉴定与验证
Front Physiol. 2023 Aug 10;14:1181510. doi: 10.3389/fphys.2023.1181510. eCollection 2023.
8
m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy.m6A 调节子介导的 RNA 甲基化修饰模式参与调节缺血性心肌病中的免疫微环境。
Sci Rep. 2023 Apr 11;13(1):5904. doi: 10.1038/s41598-023-32919-4.
9
Identification through machine learning of potential immune- related gene biomarkers associated with immune cell infiltration in myocardial infarction.通过机器学习鉴定与心肌梗死免疫细胞浸润相关的潜在免疫相关基因生物标志物。
BMC Cardiovasc Disord. 2023 Mar 28;23(1):163. doi: 10.1186/s12872-023-03196-w.
10
An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles.体外方法研究肾脏细胞对人尿细胞外囊泡的贡献。
J Extracell Vesicles. 2023 Feb;12(2):e12304. doi: 10.1002/jev2.12304.
心肌肥大细胞:心血管稳态和疾病中被低估的免疫细胞。
Trends Immunol. 2020 Aug;41(8):734-746. doi: 10.1016/j.it.2020.06.006. Epub 2020 Jun 28.
4
The Innate Immune System and Cardiovascular Disease in ESKD: Monocytes and Natural Killer Cells.固有免疫系统与终末期肾病心血管疾病:单核细胞和自然杀伤细胞。
Curr Vasc Pharmacol. 2021;19(1):63-76. doi: 10.2174/1570161118666200628024027.
5
Identification of a competing endogenous RNA network associated with prognosis of pancreatic adenocarcinoma.与胰腺腺癌预后相关的竞争性内源性RNA网络的鉴定
Cancer Cell Int. 2020 Jun 11;20:231. doi: 10.1186/s12935-020-01243-6. eCollection 2020.
6
Monocyte CD36 expression associates with atherosclerotic burden in diabetes mellitus.单核细胞 CD36 表达与糖尿病患者的动脉粥样硬化负担相关。
Diabetes Res Clin Pract. 2020 May;163:108156. doi: 10.1016/j.diabres.2020.108156. Epub 2020 Apr 22.
7
Integration of molecular features with clinical information for predicting outcomes for neuroblastoma patients.将分子特征与临床信息相结合,以预测神经母细胞瘤患者的预后。
Biol Direct. 2019 Aug 23;14(1):16. doi: 10.1186/s13062-019-0244-y.
8
Pathologic T-cell response in ischaemic failing hearts elucidated by T-cell receptor sequencing and phenotypic characterization.通过 T 细胞受体测序和表型特征分析揭示缺血性衰竭心脏中的病理性 T 细胞反应。
Eur Heart J. 2019 Dec 21;40(48):3924-3933. doi: 10.1093/eurheartj/ehz516.
9
Intersections between transcription-coupled repair and alkylation damage reversal.转录偶联修复与烷化损伤逆转之间的交集。
DNA Repair (Amst). 2019 Sep;81:102663. doi: 10.1016/j.dnarep.2019.102663. Epub 2019 Jul 8.
10
eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models.eNetXplorer:用于广义线性模型中弹性网络家族的定量探索的 R 包。
BMC Bioinformatics. 2019 Apr 16;20(1):189. doi: 10.1186/s12859-019-2778-5.