Identification and construction of lncRNA-associated ceRNA network in diabetic kidney disease

Abstract

Abstract Diabetic kidney disease (DKD) has become the major contributor to end-stage renal disease with high incidence and mortality. The functional roles and exact mechanisms of long noncoding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) network in DKD are still largely unknown. This study sought to discover novel potential biomarkers and ceRNA network for DKD. The candidate differentially expressed genes (DEGs), lncRNAs and microRNAs (miRNAs) in human glomerular and tubular tissues derived from Gene Expression Omnibus database were systematically selected and analyzed. Functional enrichment analysis and protein-protein interaction network analysis were conducted to identify hub genes and reveal their regulatory mechanisms involved in DKD. Following this, the integrated ceRNA network was constructed by bioinformatics methods. A total of 164 DEGs, 6 lncRNAs and 18 miRNAs correlated with DKD were finally filtered and identified. It is noteworthy that the global lncRNA-associated ceRNA network related to DKD was constructed, among which lnc-HIST2H2AA4-1, VCAN-AS1 and MAGI2-AS1 were identified as the 3 key lncRNAs, and VCAN, FN1, CCL2, and KNG1 were identified as the predominant genes. Consistent with that observed in the training set, 3 of the key genes also showed significant differences in the 2 validation datasets. Integrating with functional enrichment analysis results, these key genes in the ceRNA network were mainly enriched in the immune and inflammation-related pathways. This study first identified key lncRNAs, miRNAs and their targets, and further revealed a global view of lncRNA-associated ceRNA network involved in DKD by using whole gene transcripts analysis.