IDENTIFYING LONG NON-CODING RNA BIOMARKERS FROM URINARY EXOSOMES FOR DIABETIC NEPHROPATHY

Abstract BACKGROUND AND AIMS Diabetic nephropathy (DN) is the common cause of end-stage renal disease. However, the early and specific diagnostic biomarkers are still lacking. Urinary exosomes are a potential source of biomarkers for kidney disease due to their renal cell origination, stability, and noninvasive collection. Long non-coding RNAs (lncRNAs) are increasingly recognized to be involved in diverse pathophysiological processes including kidney disease. Here we set to characterize the lncRNAs profiles in urinary exosomes of DN with aims to identify novel non-invasive biomarkers of DN. METHOD First-morning urine was collected from 11 healthy people, 9 patients with diabetes mellitus (DM), and 8 patients with biopsy-proven DN. Urinary exosomes were pelleted by ultracentrifugation and total RNA was extracted for next generation sequencing (NGS). The lncRNA profile of urinary exosomes was first characterized in terms of the detectable RNA numbers, expression levels in different groups. Then differential gene expression analysis was performed to facilitate the discovery of potential biomarkers. RESULTS Similar tremendous number of lncRNAs was detected with a total number of 6439 transcripts present in urinary exosomes in each group. In terms of the expression levels, the percentage of transcripts with TPM above 1 was 31.4%, 32.8%, 33.2% in the healthy group, DM and DN patients respectively, suggesting that no significant alteration of lncRNAs numbers and distribution in DN and diabetes conditions. Next, the differential expression analysis was performed to identify the distinct differential lncRNAs. Compared with healthy people, 18 lncRNAs were upregulated and 67 lncRNAs were downregulated in DM group, while 37 unregulated and 80 downregulated lncRNAs were identified in DN group. Moreover, the profile of lncRNAs in urinary exosomes was significantly different in DN patients compared to DM group with 59 lncRNAs upregulated and 36 lncRNAs downregulated. To explore the candidate biomarkers, 12 upregulated lncRNAs and 4 downregulated lncRNAs from the two comparison sets (DN versus Healthy, DN versus Healthy) were identified, among which FLJ16779 was present with the most remarkable difference. Further analysis showed that the sensitivity and specificity of FLJ16779 for distinguishing DN from healthy people are both 87.5%, and the area under the curve (AUC) was 0.9531. Additionally, the sensitivity and specificity of FLJ16779 for distinguishing DN from DM were 75% and 87.5% respectively, and AUC was 0.9063. CONCLUSION Urinary exosomes contain rich lncRNAs information with differential expression profiles in DN patients compared to DM and healthy controls, suggesting the possible involvement of lncRNAs in the pathogenesis of DN. lncRNA FLJ16779 might be a promising non-invasive biomarker of DN which requires further validation.