Shared Genetic Features of Psoriasis and Myocardial Infarction: Insights From a Weighted Gene Coexpression Network Analysis

被引:0
|
作者
Zhou, Qiaoyu [2 ]
Shi, Ruizheng [1 ,3 ]
机构
[1] Cent South Univ, Xiangya Hosp, Dept Cardiovasc Med, 87 Xiangya Rd, Changsha 410008, Hunan, Peoples R China
[2] Cent South Univ, Dept Cardiovasc Med, Xiangya Hosp 3, Changsha, Hunan, Peoples R China
[3] Cent South Univ, Xiangya Hosp, Dept Cardiovasc Med, Changsha, Hunan, Peoples R China
来源
基金
芬兰科学院; 中国国家自然科学基金;
关键词
ceRNA; differential gene analysis; myocardial infarction; psoriasis; WGCNA; TYROSINE KINASE 2; INHIBITION; RISK; ASSOCIATION; MORTALITY; TRANSPORT; STROKE; FAMILY; COHORT; FLVCR2;
D O I
10.1161/JAHA.123.033893
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Increasing evidence suggests a higher propensity for acute myocardial infarction (MI) in patients with psoriasis. However, the shared mechanisms underlying this comorbidity in these patients remain unclear. This study aimed to explore the shared genetic features of psoriasis and MI and to identify potential biomarkers indicating their coexistence.Methods and Results Data sets obtained from the gene expression omnibus were examined using a weighted gene coexpression network analysis approach. Hub genes were identified using coexpression modules and validated in other data sets and through in vitro cellular experiments. Bioinformatics tools, including the Human microRNA Disease Database, StarBase, and miRNet databases, were used to construct a ceRNA network and predict potential regulatory mechanisms. By applying weighted gene coexpression network analysis, we identified 2 distinct modules that were significant for both MI and psoriasis. Inflammatory and immune pathways were highlighted by gene ontology enrichment analysis of the overlapping genes. Three pivotal genes-Src homology and collagen 1, disruptor of telomeric silencing 1-like, and feline leukemia virus subgroup C cellular receptor family member 2-were identified as potential biomarkers. We constructed a ceRNA network that suggested the upstream regulatory roles of these genes in the coexistence of psoriasis and MI.Conclusions As potential therapeutic targets, Src homology and collagen 1, feline leukemia virus subgroup C cellular receptor family member 2, and disruptor of telomeric silencing 1-like provide novel insights into the shared genetic features between psoriasis and MI. This study paves the way for future studies focusing on the prevention of MI in patients with psoriasis.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Identification of crucial genes in intracranial aneurysm based on weighted gene coexpression network analysis
    X Zheng
    C Xue
    G Luo
    Y Hu
    W Luo
    X Sun
    Cancer Gene Therapy, 2015, 22 : 238 - 245
  • [32] Identification of potential proteases for abdominal aortic aneurysm by weighted gene coexpression network analysis
    Zhang, Hui
    Yang, Dan
    Chen, Siliang
    Li, Fangda
    Cui, Liqiang
    Liu, Zhili
    Shao, Jiang
    Chen, Yuexin
    Liu, Bao
    Zheng, Yuehong
    GENOME, 2020, 63 (11) : 561 - 575
  • [33] Enhancing cowpea wilt resistance: insights from gene coexpression network analysis with exogenous melatonin treatment
    Gan, Yudi
    Tu, Zhiwei
    Yang, Youxin
    Cheng, Liuyang
    Wang, Nan
    Fan, Shuying
    Wu, Caijun
    BMC PLANT BIOLOGY, 2024, 24 (01):
  • [34] Weighted Gene Coexpression Network Analysis Identified MicroRNA Coexpression Modules and Related Pathways in Type 2 Diabetes Mellitus
    Feng, Tianyu
    Li, Kexin
    Zheng, Pingping
    Wang, Yanjun
    Lv, Yaogai
    Shen, Li
    Chen, Yang
    Xue, Zhiqiang
    Li, Bo
    Jin, Lina
    Yao, Yan
    OXIDATIVE MEDICINE AND CELLULAR LONGEVITY, 2019, 2019
  • [35] Construction of a Prognosis-Related Gene Signature by Weighted Gene Coexpression Network Analysis in Ewing Sarcoma
    Zhao, Runhan
    Xiong, Chuang
    Zhang, Chao
    Wang, Lin
    Liang, Hao
    Luo, Xiaoji
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2022, 2022
  • [36] Use Of Weighted Gene Coexpression Network Analysis To Identify Connectivity Between Gut And Brain Gene Expression
    Khan, Tasnin
    Hatami, Asa
    Zhu, Chunni
    Kawaguchi, Riki
    Joshi, Swapna
    Chen, Han
    Hoffman, Jill
    Law, Ivy K. M.
    Rankin, Carl R.
    John, Varghese
    Geschwind, Daniel
    FASEB JOURNAL, 2022, 36
  • [37] Biomarkers identification for acute myocardial infarction detection via weighted gene co-expression network analysis
    Zhang, Shu
    Liu, Weixia
    Liu, Xiaoyan
    Qi, Jiaxin
    Deng, Chunmei
    MEDICINE, 2017, 96 (47)
  • [38] Early Stage Biomarkers Screening of Prostate Cancer Based on Weighted Gene Coexpression Network Analysis
    Meng, Lingyin
    Li, Yang
    Ren, Jing
    Shi, Tao
    Men, Jianlong
    Chang, Chawnshang
    DNA AND CELL BIOLOGY, 2019, 38 (05) : 468 - 475
  • [39] Identification of lncRNA and weighted gene coexpression network analysis of germinating Rhizopus delemar causing mucormycosis
    Kalita, Barsha
    Roy, Abhijeet
    Jayaprakash, Aiswarya
    Arunachalam, Annamalai
    Lakshmi, P. T., V
    MYCOLOGY-AN INTERNATIONAL JOURNAL ON FUNGAL BIOLOGY, 2023, 14 (04) : 344 - 357
  • [40] Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
    Liu, Hanhan
    Chen, Lu
    Lei, Xiang
    Ren, Hong
    Li, Gaoyang
    Deng, Zhihong
    DISEASE MARKERS, 2022, 2022