Bioinformatics Analysis Reveals Crosstalk Among Platelets, Immune Cells, and the Glomerulus That May Play an Important Role in the Development of Diabetic Nephropathy

Frontiers in Medicine

Haojun Zhang¹  Fukai Cao²  Hong Shen³  Hailan He⁴  Boyu Li⁴  Zhiguo Li⁴  Xinduo Zhang⁴  Xinyue Yao⁴ 

[1] Beijing Key Lab for Immune-Mediated Inflammatory Diseases, Institute of Clinical Medical Sciences, China-Japan Friendship Hospital, Beijing, China;Department of Jitang College, North China University of Science and Technology, Tangshan, China;Department of Modern Technology and Education Center, North China University of Science and Technology, Tangshan, China;The Hebei Key Lab for Organ Fibrosis, The Hebei Key Lab for Chronic Disease, School of Public Health, International Science and Technology Cooperation Base of Geriatric Medicine, North China University of Science and Technology, Tangshan, China;

关键词: diabetic nephropathy;    pathogenesis;    bioinformatics;    platelet;    glomerulus;    immune cell;   

DOI  :  10.3389/fmed.2021.657918

来源: DOAJ

【 摘 要 】

Diabetic nephropathy (DN) is the main cause of end stage renal disease (ESRD). Glomerulus damage is one of the primary pathological changes in DN. To reveal the gene expression alteration in the glomerulus involved in DN development, we screened the Gene Expression Omnibus (GEO) database up to December 2020. Eleven gene expression datasets about gene expression of the human DN glomerulus and its control were downloaded for further bioinformatics analysis. By using R language, all expression data were extracted and were further cross-platform normalized by Shambhala. Differentially expressed genes (DEGs) were identified by Student's t-test coupled with false discovery rate (FDR) (P < 0.05) and fold change (FC) ≥1.5. DEGs were further analyzed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to enrich the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. We further constructed a protein-protein interaction (PPI) network of DEGs to identify the core genes. We used digital cytometry software CIBERSORTx to analyze the infiltration of immune cells in DN. A total of 578 genes were identified as DEGs in this study. Thirteen were identified as core genes, in which LYZ, LUM, and THBS2 were seldom linked with DN. Based on the result of GO, KEGG enrichment, and CIBERSORTx immune cells infiltration analysis, we hypothesize that positive feedback may form among the glomerulus, platelets, and immune cells. This vicious cycle may damage the glomerulus persistently even after the initial high glucose damage was removed. Studying the genes and pathway reported in this study may shed light on new knowledge of DN pathogenesis.

【 授权许可】

Unknown