Evaluation of microRNAs miR-196a, miR-30a-5P, and miR-490 as biomarkers of disease activity among patients with FSGS

Abstract

Background and objectives: This study aimed to identify urinary microRNAs (miRNAs) as biomarkers for FSGS disease activity.

Design, setting, participants, & measurements: Candidate urinary miRNAs were identified in pooled urine samples from patients with active FSGS (FSGS-A) and FSGS in remission (FSGS-CR), and were then validated using individual samples. Their levels were compared both under different treatment responses in a prospective study of FSGS and in patients with different membranous nephropathy (MN) and diabetic nephropathy (DN) disease activity. The prediction of these miRNAs for treatment responses was further analyzed in both retrospective and prospective cohorts of patients with FSGS.

Results: All 54 miRNAs were included as candidate biomarkers, including those with high levels in patients with FSGS-A (n=9) under the TaqMan Low Density Array as well as those with conserved expression in kidneys and involved in immune response. TaqMan probe-based quantitative RT-PCR confirmed the higher levels of four miRNAs in patients with FSGS-A in two independent cohorts (n=18 and n=80). Urinary miR-196a, miR-30a-5p, and miR-490 discriminated FSGS-A from FSGS-CR, with an area under the curve of ≥ 0.80. After steroid treatment, their levels were lower in steroid-responsive patients with FSGS (all P<0.001), but were unchanged in steroid-resistant patients. The levels of miRNAs were similar between active MN and MN in remission as well as active DN and incipient DN (all P>0.05). Urinary miR-30a-5p marginally predicted the response to steroid treatment in patients with FSGS-A, with an area under the curve of 0.63 (P=0.03).

Conclusions: The levels of urinary miR-196a, miR-30a-5p, and miR-490 are associated with FSGS disease activity.

Keywords: FSGS; biomarkers; miRNAs; urine.

Figure 1.

A flow diagram of the research design for identifying biomarkers of FSGS activity and predicting patient responses to steroid treatment. (A) The study of identifying biomarkers of FSGS activity. (B) The study of predicting patient responses to steroid treatment. *MicroRNAs with conserved expression in kidneys and involved in immune response were also included as candidates. CR, complete remission; DN-A, active diabetic nephropathy; FSGS-A, active FSGS; FSGS-CR, FSGS in remission; IDN, incipient diabetic nephropathy; miR, microRNA; miRNA, microRNA; MN-A, active membranous nephropathy; MN-CR, membranous nephropathy in complete remission; NC, normal control.

Figure 2.

Receiver operating characteristic curve analysis of the ability of urinary miRNAs to serve as biomarkers in the validation set for discriminating FSGS-A from controls and from FSGS-CR. (A) ROC curve of discriminating FSGS-A from controls. (B) ROC curve of discriminating FSGS-A from FSGS-CR. 95% CI, 95% confidence interval; AUC, area under the curve.

Figure 3.

Urinary levels of miR-196a, miR-30a-5p, and miR-490 after treatment in the prospective study. (A) The urinary levels of the three miRNAs in steroid-responsive patients. (B) The urinary levels of the three miRNAs in steroid-resistant patients.

Figure 4.

Prediction value of urinary miR-30a-5p in steroid-responsive patients. (A) Receiver operating characteristic curve analysis of the urinary miR-30a-5p in predicting steroid-responsive patients in a retrospective study (n=139). (B) The percentage reduction in the level of proteinuria and the miR-30a-5p in a prospective study (n=22).