Bioinformatics-based analysis of core genes and pathway enrichment in early diabetic nephropathy

被引:1
|
作者
Han, Yangwenxuan [1 ]
Liu, Xiaoyan [1 ]
Shang, Jing [1 ]
Li, Na [1 ]
Zhang, Chunjian [1 ]
Li, Ying [1 ]
Zheng, Jiaxin [1 ,2 ]
机构
[1] Heilongjiang Acad Tradit Chinese Med, Dept Nephrol 1, Harbin 150036, Heilongjiang, Peoples R China
[2] Heilongjiang Univ Tradit Chinese Med, Affiliated Hosp 2, Dept Nephrol 2, Harbin 150001, Heilongjiang, Peoples R China
关键词
Bioinformatics; Core gene; DN; GLYCATION END-PRODUCTS; CHRONIC KIDNEY-DISEASE; CELLS; RISK;
D O I
10.14715/cmb/2023.69.7.9
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Diabetic nephropathy (DN) is the main cause of end-stage renal disease (ESRD). Bioinformatics technology was adopted to screen and analyze the core genes of early DN to explore its pathogenesis. GSE30528, GSE96804, and GSE30122 chip data were obtained from Gene Expression Omnibus (GEO) database to screen DN and healthy controls for differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional annotation and signaling pathway enrichment; String and Cytoscape were used for protein-protein interaction (PPI) network construction and core gene screening, NCBI-Genes to search the expression profile of core genes. 17 common genes were screened, with 6 genes up -regulated and 11 genes down-regulated. The major functional annotations of differential genes were the generation of precursor metabolites and energy, Immune response, and Phosphorylation. They were concentrated on Focal adhesion, PI3K/Akt signaling pathway, and Human papillomavirus infection pathway. The expressions of VEGFA and THBS1 were down-regulated, while the expressions of ITGB1, MMP7, and SOX9 were up-regulated. The core genes VEGFA and THBS1 were highly expressed in Thyroid and Appendix, but lowly expressed in Testis. MMP7 was highly expressed in the Gall bladder and low in the Adrenal. SOX9 was highly expressed in Thyroid and lowly expressed in the bone marrow. ITGB1 was highly expressed in Fat and low in Pancreas. Bioinformatics technology can mine chip data and present new targets for diagnosing and treating DN, but further verification is needed.
引用
收藏
页码:51 / 56
页数:6
相关论文
共 50 条
  • [41] Bioinformatics-Based Identification of MicroRNA-Regulated and Rheumatoid Arthritis-Associated Genes
    Song, Yi-Jiang
    Li, Guiling
    He, Jian-Hua
    Guo, Yao
    Yang, Li
    PLOS ONE, 2015, 10 (09):
  • [42] Identification of metabolic reprogramming-related genes as potential diagnostic biomarkers for diabetic nephropathy based on bioinformatics
    Chen, Hong
    Su, Xiaoxia
    Li, Yan
    Dang, Cui
    Luo, Zuojie
    DIABETOLOGY & METABOLIC SYNDROME, 2024, 16 (01):
  • [43] Identification of Ferroptosis-related Genes for Diabetic Nephropathy by Bioinformatics and Experimental Validation
    Song, Siyuan
    Yu, Jiangyi
    CURRENT PHARMACEUTICAL DESIGN, 2025,
  • [44] New insights into the ferroptosis and immune infiltration in endometriosis: a bioinformatics-based analysis
    Liu, Lusha
    Han, Feifei
    Du, Naiyi
    Liu, Yakun
    Duan, Aihong
    Kang, Shan
    Li, Bin
    FRONTIERS IN IMMUNOLOGY, 2025, 15
  • [46] Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer
    Chen, Shaojie
    Huang, Feifei
    Chen, Shangxiang
    Chen, Yinting
    Li, Jiajia
    Li, Yaqing
    Lian, Guoda
    Huang, Kaihong
    FRONTIERS IN GENETICS, 2021, 12
  • [47] Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Pediatric Sepsis
    Xie, Kexin
    Kong, Shan
    Li, Fuxing
    Zhang, Yulin
    Wang, Jing
    Zhao, Weidong
    MEDICAL SCIENCE MONITOR, 2020, 26
  • [48] Bioinformatics analysis on enrichment analysis of potential hub genes in breast cancer
    Wei, Limin
    Wang, Yukun
    Zhou, Dan
    Li, Xinyang
    Wang, Ziming
    Yao, Ge
    Wang, Xinshuai
    TRANSLATIONAL CANCER RESEARCH, 2021, 10 (05) : 2399 - 2408
  • [49] Screening and Analysis of Core Genes for Osteoporosis Based on Bioinformatics Analysis and Machine Learning Algorithms
    Lu, Yongxia
    Wang, Wei
    Yang, Baiyuan
    Cao, Gui
    Du, Yue
    Liu, Jingyu
    INDIAN JOURNAL OF ORTHOPAEDICS, 2024, 58 (07) : 944 - 954
  • [50] Bioinformatics-based analysis of the roles of sex hormone receptors in endometriosis development
    Zhao, Xiaoling
    Kong, Weimin
    Zhou, Chunxiao
    Deng, Boer
    Zhang, He
    Guo, Huimin
    Chen, Shuning
    Pan, Zhendong
    INTERNATIONAL JOURNAL OF MEDICAL SCIENCES, 2023, 20 (03): : 415 - 428