Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis

Author:

Zhang Hongliang1,Chen Tingting12,Zhang Yunyan1,Lin Jiangbo1,Zhao Wenjun3,Shi Yangyang4,Lau Huichong5,Zhang Yang1,Yang Minjun1,Xu Cheng1,Tang Lijiang2,Xu Baohui6ORCID,Jiang Jianjun1ORCID,Chen Xiaofeng17ORCID

Affiliation:

1. Department of Cardiology, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, 317000 Zhejiang Province, China

2. Department of Cardiology, Zhejiang Hospital, Hangzhou, 310013 Zhejiang Province, China

3. Department of Vascular Surgery, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, 317000 Zhejiang Province, China

4. Department of Radiation Oncology, University of Arizona, Tucson, AZ 85721, USA

5. Department of Medicine, Crozer-Chester Medical Center, Upland, PA 19013, USA

6. Division of Vascular Surgery, Stanford University School of Medicine, Stanford 94305, USA

7. Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202, USA

Abstract

Background. Aortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis. Method. Nine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO). Results. DEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD. Conclusion. Our analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Immunology,General Medicine,Immunology and Allergy

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3