Prediction of marker genes associated with hypertension by bioinformatics analyses

被引:7
|
作者
Gao, Yuan [1 ]
Qi, Guo-Xian [1 ]
Jia, Zhi-Mei [1 ]
Sun, Ying-Xian [1 ]
机构
[1] China Med Univ, Dept Cardiol, Hosp 1, 155 Nanjing St, Shenyang 110001, Liaoning, Peoples R China
关键词
hypertension; differentially expressed genes; protein- protein interaction network; transcription factor; LYSYL OXIDASE; EXPRESSION; RAT; DYSFUNCTION; CYTOSCAPE; DISEASE; ALPHA; ARRAY;
D O I
10.3892/ijmm.2017.3000
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
This study aimed to explore the underlying marker genes associated with hypertension by bioinformatics analyses. A gene expression profile (GSE54015) was downloaded. The differentially expressed genes (DEGs) between the normotensive female (NF) and hypertensive female (HF), and between the normotensive male (NM) and hypertensive male (HM) groups were analyzed. Gene Ontology (GO) and pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. The transcription factors (TFs), and the common DEGs between the HF and HM groups were then analyzed. In total, 411 DEGs were identified between the HF and NF groups, and 418 DEGs were identified between the HM and NM groups. The upregulated DEGs in the HF and HM groups were enriched in 9 GO terms, including oxidation reduction, such as cytochrome P450, family 4, subfamily b, polypeptide 1 (Cyp4b1) and cytochrome P450, family 4, subfamily a, polypeptide 31 Cyp4a31). The downregulated DEGs were mainly enriched in GO terms related to hormone metabolic processes. In the PPI network, cytochrome P450, family 2, subfamily e, polypeptide 1 (Cyp2e1) had the highest degree in all 3 analysis methods in the HF group. Additionally, 4 TFs were indentified from the 2 groups of data, including sterol regulatory element binding transcription factor 1 (Srebf1), estrogen receptor 1 (Esr1), retinoid X receptor gamma (Rxrg) and peroxisome proliferator-activated receptor gamma (Pparg). The intersection genes were mainly enriched in GO terms related to the extracellular region. On the whole, our data indicate that the DEGs, Cyp4b1, Cyp4a31 and Loxl2, and the TFs, Esr1, Pparg and Rxrg, are associated with the progression of hypertension, and may thus serve as potential therapeutic targets in this disease.
引用
收藏
页码:137 / 145
页数:9
相关论文
共 50 条
  • [31] Identification of key differentially expressed genes associated with non-small cell lung cancer by bioinformatics analyses
    Xiao, Yubo
    Feng, Min
    Ran, Haiying
    Han, Xiao
    Li, Xuegang
    MOLECULAR MEDICINE REPORTS, 2018, 17 (05) : 6379 - 6386
  • [32] Identification of genes associated with apoptosis-sensitive acute lymphoblastic leukemia responsive to ionising radiation by bioinformatics analyses
    Sun, Ying
    Huo, Meng
    Zhang, Chunyan
    Wang, Rengui
    Wen, Tingguo
    INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2016, 9 (11): : 22194 - 22199
  • [33] Identification of Hub Genes in Atypical Teratoid/Rhabdoid Tumor by Bioinformatics Analyses
    Pan, Xin
    Liu, Wei
    Chai, Yi
    Hu, Libo
    Wang, Junhua
    Zhang, Yuqi
    JOURNAL OF MOLECULAR NEUROSCIENCE, 2020, 70 (11) : 1906 - 1913
  • [34] Integrated bioinformatics analyses of key genes involved in hepatocellular carcinoma immunosuppression
    Huang, Hongyan
    Hu, Youwen
    Guo, Li
    Wen, Zhili
    ONCOLOGY LETTERS, 2021, 22 (06)
  • [35] Identification of key pathways and genes in endometrial cancer using bioinformatics analyses
    Liu, Yan
    Hua, Teng
    Chi, Shuqi
    Wang, Hongbo
    ONCOLOGY LETTERS, 2019, 17 (01) : 897 - 906
  • [36] Identification of Hub Genes in Atypical Teratoid/Rhabdoid Tumor by Bioinformatics Analyses
    Xin Pan
    Wei Liu
    Yi Chai
    Libo Hu
    Junhua Wang
    Yuqi Zhang
    Journal of Molecular Neuroscience, 2020, 70 : 1906 - 1913
  • [37] Identification of hub genes associated with spermatogenesis by bioinformatics analysis
    Liu, Shuang
    Bian, Yan-chao
    Wang, Wan-lun
    Liu, Tong-Jia
    Zhang, Ting
    Chang, Yue
    Xiao, Rui
    Zhang, Chuan-ling
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [38] Identification of hub genes associated with spermatogenesis by bioinformatics analysis
    Shuang Liu
    Yan-chao Bian
    Wan-lun Wang
    Tong-Jia Liu
    Ting Zhang
    Yue Chang
    Rui Xiao
    Chuan-ling Zhang
    Scientific Reports, 13
  • [39] Identification of genes associated with disc degeneration using bioinformatics
    Ji, S-C
    Han, N.
    Liu, Y.
    Li, G.
    Sun, Z.
    Li, Z.
    BIOTECHNIC & HISTOCHEMISTRY, 2015, 90 (05) : 353 - 360
  • [40] Identification of genes associated with lung cancer by bioinformatics analysis
    Li, J.
    Yu, H.
    Ma, Y. -F.
    Zhao, M.
    Tang, J.
    EUROPEAN REVIEW FOR MEDICAL AND PHARMACOLOGICAL SCIENCES, 2017, 21 (10) : 2397 - 2404