高级检索
当前位置: 首页 > 详情页

Single-Cell Sequencing Analysis and Multiple Machine Learning Methods Identified G0S2 and HPSE as Novel Biomarkers for Abdominal Aortic Aneurysm

文献详情

资源类型:
WOS体系:

收录情况: ◇ SCIE

单位: [1]Department of Cardiovascular, Shaanxi Provincial People’s Hospital, Xi’an, China, [2]Department of Cardiovascular Surgery, Yan'an Affiliated Hospital of Kunming Medical University, Kunming, China, [3]Department of Cardiovascular Surgery, China- Japan Friendship Hospital, Beijing, China, [4]Department of Cardiothoracic Surgery, Affiliated Hospital of Nantong University, Nantong, China, [5]Department of Pathology, College of Basic Medical Sciences China Medical University, Shenyang, China, [6]School of Biological Science and Medical Engineering, Beihang University, Beijing, China
出处:
ISSN:

关键词: abdominal aortic aneurysm single-cell sequencing weighted co-expression network analysis differentially expressed genes multiple machine learning methods

摘要:
Identifying biomarkers for abdominal aortic aneurysms (AAA) is key to understanding their pathogenesis, developing novel targeted therapeutics, and possibly improving patients outcomes and risk of rupture. Here, we identified AAA biomarkers from public databases using single-cell RNA-sequencing, weighted co-expression network (WGCNA), and differential expression analyses. Additionally, we used the multiple machine learning methods to identify biomarkers that differentiated large AAA from small AAA. Biomarkers were validated using GEO datasets. CIBERSORT was used to assess immune cell infiltration into AAA tissues and investigate the relationship between biomarkers and infiltrating immune cells. Therefore, 288 differentially expressed genes (DEGs) were screened for AAA and normal samples. The identified DEGs were mostly related to inflammatory responses, lipids, and atherosclerosis. For the large and small AAA samples, 17 DEGs, mostly related to necroptosis, were screened. As biomarkers for AAA, G0/G1 switch 2 (G0S2) (Area under the curve [AUC] = 0.861, 0.875, and 0.911, in GSE57691, GSE47472, and GSE7284, respectively) and for large AAA, heparinase (HPSE) (AUC = 0.669 and 0.754, in GSE57691 and GSE98278, respectively) were identified and further verified by qRT-PCR. Immune cell infiltration analysis revealed that the AAA process may be mediated by T follicular helper (Tfh) cells and the large AAA process may also be mediated by Tfh cells, M1, and M2 macrophages. Additionally, G0S2 expression was associated with neutrophils, activated and resting mast cells, M0 and M1 macrophages, regulatory T cells (Tregs), resting dendritic cells, and resting CD4 memory T cells. Moreover, HPSE expression was associated with M0 and M1 macrophages, activated and resting mast cells, Tregs, and resting CD4 memory T cells. Additional, G0S2 may be an effective diagnostic biomarker for AAA, whereas HPSE may be used to confer risk of rupture in large AAAs. Immune cells play a role in the onset and progression of AAA, which may improve its diagnosis and treatment.

基金:
语种:
被引次数:
WOS:
中科院(CAS)分区:
出版当年[2021]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
JCR分区:
出版当年[2020]版:
Q1 IMMUNOLOGY
最新[2023]版:
Q1 IMMUNOLOGY

影响因子: 最新[2023版] 最新五年平均[2021-2025] 出版当年[2020版] 出版当年五年平均[2016-2020] 出版前一年[2019版] 出版后一年[2021版]

第一作者:
第一作者单位: [1]Department of Cardiovascular, Shaanxi Provincial People’s Hospital, Xi’an, China, [2]Department of Cardiovascular Surgery, Yan'an Affiliated Hospital of Kunming Medical University, Kunming, China,
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:1320 今日访问量:0 总访问量:816 更新日期:2025-04-01 建议使用谷歌、火狐浏览器 常见问题

版权所有:重庆聚合科技有限公司 渝ICP备12007440号-3 地址:重庆市两江新区泰山大道西段8号坤恩国际商务中心16层(401121)