Literature DB >> 35834115

Screening of Diabetic Nephropathy Progression-Related Genes Based on Weighted Gene Co-expression Network Analysis.

Ling'an Yu1, Haiying Tao2.   

Abstract

The purpose of this study is to explore the progression-related genes of diabetic nephropathy (DN) through weighted gene co-expression network analysis (WGCNA). The gene expression dataset GSE14202 was downloaded from the GEO database for differential expression analysis. WGCNA v1.69 was used to perform co-expression analysis on differentially expressed genes. 25 modular genes were selected through WGCNA. The motif enrichment analysis was performed on 25 genes, and 34 motifs were obtained, of which 8 transcription factors (TFs) were differentially expressed. GENIE3 was applied to analyze the expression correlation of 8 differentially expressed TFs and 25 genes. Combined with the predicted TF-target gene relationship, 69 interactions between 8 TFs and 18 genes were obtained. The functional enrichment analysis of 18 genes showed that 7 key genes were obviously enriched in adaptive immune response and were clearly up-regulated in advanced DN patients. The expression of C1S, LAIR1, CD84, SIT1, SASH3, and CD180 in glomerular samples from DN patients was significantly up-regulated in compared with normal samples, and the expression of these genes was negatively correlated with GFR. We observed that in the in vitro cell model of DN, the relative expression levels of 5 key genes (except SASH3) were obviously elevated in the high-glucose group. Five key genes were identified to be related to the progression of DN. The findings of this study may provide new ideas and therapeutic targets for exploring the pathogenesis of DN.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Bioinformatics analysis; Diabetic nephropathy; Differentially expressed genes; Human glomerular endothelial cells; Weighted gene co-expression network analysis

Year:  2022        PMID: 35834115     DOI: 10.1007/s10528-022-10250-3

Source DB:  PubMed          Journal:  Biochem Genet        ISSN: 0006-2928            Impact factor:   2.220


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