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.