Identification of Differentially Expressed Genes and Pathways in Human Atrial Fibrillation by Bioinformatics Analysis

被引:4
|
作者
Pan, Defeng [1 ]
Zhou, Yufei [2 ,3 ]
Xiao, Shengjue [1 ]
Hu, Yue [4 ]
Huan, Chunyan [1 ]
Wu, Qi [1 ]
Wang, Xiaotong [1 ]
Pan, Qinyuan [1 ]
Liu, Jie [1 ]
Zhu, Hong [1 ]
机构
[1] Xuzhou Med Univ, Dept Cardiol, Affiliated Hosp, 99 Huaihai West Rd, Xuzhou 221004, Jiangsu, Peoples R China
[2] Fudan Univ, Zhongshan Hosp, Shanghai Inst Cardiovasc Dis, Dept Cardiol, Shanghai 200032, Peoples R China
[3] Fudan Univ, Inst Biomed Sci, Shanghai 200032, Peoples R China
[4] Xuzhou Med Univ, Dept Gen Practice, Affiliated Hosp, Xuzhou 221004, Jiangsu, Peoples R China
来源
INTERNATIONAL JOURNAL OF GENERAL MEDICINE | 2022年 / 15卷
关键词
atrial fibrillation; bioinformatics analysis; differentially expressed genes; pathways; protein-protein interaction network; HIPPO PATHWAY; ID1; FIBROSIS; BETA;
D O I
10.2147/IJGM.S334122
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Introduction: Atrial fibrillation (AF) is the most prevalent sustained cardiac arrhythmia, but the molecular mechanisms underlying AF are not known. We aimed to identify the pivotal genes and pathways involved in AF pathogenesis because they could become potential biomarkers and therapeutic targets of AF. Methods: The microarray datasets of GSE31821 and GSE41177 were downloaded from the Gene Expression Omnibus database. After combining the two datasets, differentially expressed genes (DEGs) were screened by the Limma package. MicroRNAs (miRNAs) confirmed experimentally to have an interaction with AF were screened through the miRTarBase database. Target genes of miRNAs were predicted using the miRNet database, and the intersection between DEGs and target genes of miRNAs, which were defined as common genes (CGs), were analyzed. Functional and pathway-enrichment analyses of DEGs and CGs were performed using the databases DAVID and KOBAS. Protein-protein interaction (PPI) network, miRNA- messenger(m) RNA network, and drug-gene network was visualized. Finally, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was used to validate the expression of hub genes in the miRNA-mRNA network. Results: Thirty-three CGs were acquired from the intersection of 65 DEGs from the integrated dataset and 9777 target genes of miRNAs. Fifteen "hub" genes were selected from the PPI network, and the miRNA-mRNA network, including 82 miRNAs and 9 target mRNAs, was constructed. Furthermore, with the validation by RT-qPCR, macrophage migration inhibitory factor (MIF), MYC proto-oncogene, bHLH transcription factor (MYC), inhibitor of differentiation 1 (ID1), and C-X-C Motif Chemokine Receptor 4 (CXCR4) were upregulated and superoxide Dismutase 2 (SOD2) was downregulated in patients with AF compared with healthy controls. We also found MIF, MYC, and ID1 were enriched in the transforming growth factor (TGF)-beta and Hippo signaling pathway. Conclusion: We identified several pivotal genes and pathways involved in AF pathogenesis. MIF, MYC, and ID1 might participate in AF progression through the TGF-beta and Hippo signaling pathways. Our study provided new insights into the mechanisms of action of AF.
引用
收藏
页码:103 / 114
页数:12
相关论文
共 50 条
  • [31] Identification of differentially expressed genes between mucinous adenocarcinoma and other adenocarcinoma of colorectal cancer using bioinformatics analysis
    Zhang, Xue
    Zuo, Jing
    Wang, Long
    Han, Jing
    Feng, Li
    Wang, Yudong
    Fan, Zhisong
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2020, 48 (08)
  • [32] Study on potential differentially expressed genes in stroke by bioinformatics analysis
    Xitong Yang
    Pengyu Wang
    Shanquan Yan
    Guangming Wang
    Neurological Sciences, 2022, 43 : 1155 - 1166
  • [33] Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis
    Abdolahi, Fatemeh
    Shahraki, Ali
    Sheervalilou, Roghayeh
    Mortazavi, Sedigheh Sadat
    BMC MEDICAL GENOMICS, 2023, 16 (01)
  • [34] Identification of differentially expressed genes and biological pathways in bladder cancer
    Tang, Fucai
    He, Zhaohui
    Lei, Hanqi
    Chen, Yuehan
    Lu, Zechao
    Zeng, Guohua
    Wang, Hangtao
    MOLECULAR MEDICINE REPORTS, 2018, 17 (05) : 6425 - 6434
  • [35] Identification of the key differentially expressed genes and pathways involved in neutrophilia
    He, Chengcheng
    Zhang, Yingchun
    Luo, Hongwei
    Luo, Bo
    He, Yancheng
    Jiang, Nan
    Liang, Yu
    Zeng, Jingyuan
    Luo, Yujiao
    Xian, Yujun
    Liu, Jiajia
    Zheng, Xiaoli
    INNATE IMMUNITY, 2020, 26 (04) : 270 - 284
  • [36] COMMON DIFFERENTIALLY EXPRESSED GENES AND PATHWAYS CORRELATING BOTH CORONARY ARTERY DISEASE AND ATRIAL FIBRILLATION
    Zheng, Youjing
    He, Jia-Qiang
    EXCLI JOURNAL, 2021, 20 : 126 - 141
  • [37] Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma
    Liang Sang
    Xue-Mei Wang
    Dong-Yang Xu
    Wen-jing Zhao
    World Journal of Gastroenterology, 2018, (24) : 2605 - 2616
  • [38] Bioinformatics analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma
    Sang, Liang
    Wang, Xue-Mei
    Xu, Dong-Yang
    Zhao, Wen-Jing
    WORLD JOURNAL OF GASTROENTEROLOGY, 2018, 24 (24) : 2605 - 2616
  • [39] Identification of genes and pathways in esophageal adenocarcinoma using bioinformatics analysis
    He, Feng
    Ai, Bo
    Tian, Lei
    BIOMEDICAL REPORTS, 2018, 9 (04) : 305 - 312
  • [40] Identification of key genes and pathways in diabetic nephropathy by bioinformatics analysis
    Geng, Xiao-dong
    Wang, Wei-wei
    Feng, Zhe
    Liu, Ran
    Cheng, Xiao-long
    Shen, Wan-jun
    Dong, Zhe-yi
    Cai, Guang-yan
    Chen, Xiang-mei
    Hong, Quan
    Wu, Di
    JOURNAL OF DIABETES INVESTIGATION, 2019, 10 (04) : 972 - 984