Screening potential prognostic biomarkers of long non-coding RNAs for predicting the risk of chronic kidney disease

ABSTRACT

Not much is known about the roles of long non-coding RNAs (lncRNAs) for chronic kidney disease (CKD). In this study, we included CKD patient cohorts and normal controls as a discovery cohort to identify putative lncRNA biomarkers associated with CKD. We first compared the lncRNA expression profiles of CKD patients with normal controls, and identified differentially expressed lncRNAs and mRNAs. Co-expression network based on the enriched differentially expressed mRNAs and lncRNAs was constructed using WGCNA to identify important modules related to CKD. A lncRNA-miRNA-mRNA pathway network based on the hub lncRNAs and mRNAs, related miRNAs, and overlapping pathways was further constructed to reveal putative biomarkers. A total of 821 significantly differentially expressed mRNAs and lncRNAs were screened between CKD and control samples, which were enriched in nine modules using weighted correlation network analysis (WGCNA), especially brown and yellow modules. Co-expression network based on the enriched differentially expressed mRNAs and lncRNAs in brown and yellow modules uncovered 7 hub lncRNAs and 53 hub mRNAs. A lncRNA-miRNA-mRNA pathway network further revealed that lncRNAs of HCP5 and NOP14-AS1 and genes of CCND2, COL3A1, COL4A1, and RAC2 were significantly correlated with CKD. The lncRNAs of NOP14-AS1 and HCP5 were potential prognostic biomarkers for predicting the risk of CKD.