Screening and identification of critical biomarkers in erectile dysfunction: evidence from bioinformatic analysis

Abstract

Purpose Erectile dysfunction (ED) is one of the most common male-disease globally. Despite efforts to explain its pathogenesis, the molecular mechanisms of ED are still not well understood. Methods The microarray dataset GSE10804 was downloaded from the Gene Expression Omnibus (GEO) to find candidate genes in ED progression. After differentially expressed genes (DEGs) were identified, functional enrichment analysis was performed. In addition, a protein-protein interaction network (PPI) was established and module analysis was performed through the STRING and Cytoscape. Results and Conclusions A total of 618 DEGs were identified in all, containing 430 downregulated genes and 188 upregulated genes. The enriched functions and pathways of the DEGs include transcription from RNA polymerase II promoter, cell adhesion, calcium ion binding, receptor binding, Akt signaling pathway, receptor interaction, protein digestion, and absorption. We picked out twenty-five hub genes, with biological process (BP) analyses revealing that the genes were principally associated with cellular responses to amino acid stimuli, extracellular matrix structural constituent, collagen trimer, protein digestion and absorption, ECM-receptor interaction and PI3K-Akt signaling pathway. To sum up, DEGs and hub genes distinguished in this study not only help us understand the molecular mechanisms behind the carcinogenesis and progression of ED, but also play a part in the diagnosis and treatment of ED by providing candidate targets.

Comparison of critical biomarkers in 2 erectile dysfunction models based on GEO and NOS-cGMP-PDE5 pathway

“…Still, there have been a few studies of human tissues. [ 65 ] GO and KEGG pathway enrichment analysis of hub DEGs in human's ED samples showed that extracellular exosome in CC and collagen fibril organization in BP had the same downward trend compared with our present data. [ 65 ]…”

Identification of key genes in type 2 diabetes‐induced erectile dysfunction rats with stem cell therapy through high‐throughput sequencing and bioinformatic analysis

“…CLDN11 encodes a member of the claudin family, and claudins are integral membrane proteins and components of tight junction strands (Gumbiner, 1996). In our study, Cldn17 mRNA expression in the DMED group was higher than that in the NC group, and KEGG enrichment analysis showed (Hui et al, 2020). However, they did not found the role of CLDN11 in junctional and barrier integrity.…”

“…In our study, Cldn17 mRNA expression in the DMED group was higher than that in the NC group, and KEGG enrichment analysis showed upregulation of genes related to ECM–receptor interaction. Hui et al reanalysed the chip data published by Wessells et al's study and identified 618 DEGs and the enriched pathways of DEGs included ECM–receptor interaction(Hui et al., 2020). However, they did not found the role of CLDN11 in junctional and barrier integrity.…”

Hub Genes and Key Pathways of Intervertebral Disc Degeneration: Bioinformatics Analysis and Validation

“…Recently, microarray technology and bioinformatics analysis have become popular methods of exploration of disease pathogenesis and identification of biomarkers for disease progression [ 22 ]. The purpose of this study is to identify potential molecular targets and signaling pathways associated with IDD based on Gene Expression Omnibus datasets.…”