Abstract 12938: Circulating Long Noncoding RNAs Predicts Adverse Cardiovascular Outcomes in Patients With End-Stage Renal Disease

Abstract

Introduction: Cardiovascular (CV) disease is the major cause of death in uremic patients. Conventional risk factors fail to predict adverse CV outcomes with uremia. This study aimed to test the hypothesis that circulating long non-coding RNAs (lncRNA) can be a useful biomarker to predict CV events and death in uremic patients. Methods: Cell free, circulating lncRNA profiling was conducted using plasma RNA from end-stage renal disease (ESRD, n=33), chronic kidney disease (CKD, n=8) and healthy (n=19) subjects by RNA sequencing. Participants were followed up for 3 years for major adverse CV events (MACE: acute coronary syndrome, heart failure, stroke and CV death). Results: A total of 512 million sequencing reads were obtained from 60 plasma RNA samples. Among the 1897 lncRNAs detected in human plasma, 486 (363 up,123 down) and 41 (34 up, 7 down) were significantly dysregulated with ESRD and CKD, respectively. Hierarchical clustering analysis revealed that plasma lncRNA expression pattern discriminates ESRD and CKD from control samples. Pathway analysis of the dysregulated lncRNAs in ESRD based on their nearby mRNAs (cis-mRNA) showed significant enrichment of genes involved in unfolded protein response and fatty acyl-CoA biosynthesis, both of which have been implicated in the pathogenesis of uremia. Analysis on an independent microarray dataset obtained from renal biopsy samples of 48 patients with advanced kidney disease and 8 healthy subjects (GSE66494) revealed that ~15% (72 out of 486) of the dysregulated plasma lncRNA with ESRD are similarly dysregulated in diseased kidney tissues, suggesting that circulating lncRNA expression profiles can mirror, at least in part, the changes of lncRNA expression in diseased kidneys. During the follow-up period, 10 ESRD patients experienced MACE; 129 lncRNAs were differentially expressed in ESRD patients with MACE, compared to those without one. Among them, lncRNA FAM66D was a significant predictor of MACE (Hazard ratio 1.2, 95% CI 1.05-1.36, P =0.003) and could discriminate between ESRD patients with and without high risks for MACE (ROC curve AUC 0.92, 95% CI 0.76-1.00). Conclusions: Circulating lncRNAs reflect the disease states of uremia and could serve as a useful biomarker to predict the CV outcomes in uremic patients.