Development of a multiple urinary biomarker model to predict the tubulointerstitial fibrosis area in patients with primary IgA Nephropathy

Abstract

Background

Previous studies highlighted the utility of individual urinary biomarkers in the prediction of interstitial fibrosis in IgA Nephropathy patients. However, it´s uncertain which biomarker or combination of biomarkers provides a more accurate estimation of renal interstitial fibrosis Surface. Herein, we measured the urinary excretion of a set of seven tubular injury biomarkers in a group of patients with primary IgA Nephropathy and analyzed their utility as non-invasive estimators of interstitial fibrosis area found on kidney biopsy.

Methods

Two hundred forty-seven adults with primary IgA Nephropathy diagnosed by kidney biopsy and a control group of 50 healthy control were included. The urinary excretion of EGF, MCP-1, NGAL, KIM-1, L-FABP, β2-microglobulin and DKK-3 was measured in urine samples collected at the day of the renal biopsy. Estimated glomerular filtration rate was measured by the CKD-EPI formula. Interstitial fibrosis area was quantified using a quantitative morphometric procedure and graded according to Oxford Classification. Predictive multivariate models were developed to predict the interstitial fibrosis surface.

Results

Patients with primary IgA Nephropathy showed significantly higher urinary levels of DKK-3, L-FABP and β2-microglobulin, and lower EGF levels than healthy controls. Interstitial fibrosis was negatively correlated with urinary EGF levels and positively with age, proteinuria, eGFR and urinary DKK-3, L-FABP and β2-microglobulin. The best model to predict interstitial fibrosis area accounted for > 60% of its variability and included age, eGFR, proteinuria, DKK-3, EGF, L-FABP and β2-microglobulin.

Conclusions

Our study provides a model to estimate the IFS in IgA Nephropathy which could be useful to monitor the progression of chronic kidney injury.