Novel predictive biomarkers for acute injury superimposed on chronic kidney disease.

INTRODUCTION AND OBJECTIVES

Chronic kidney disease (CKD) is a risk factor for the development of acute kidney injury (AKI). Recent studies have revealed numerous biomarkers eligible for AKI prediction. However, the expression and performance of AKI biomarkers in acute injury superimposed on preexisting CKD (AonC) remain elusive. The aim of this study was to evaluate whether biomarkers which robustly expressed in acute kidney injury could predict acute injury based on CKD.

MATERIALS AND METHODS

Mice were classified into cohorts: AKI, CKD, AonC and sham. The AonC model mice were subjected to renal bilateral ischemia/reperfusion (I/R) injury fourteen days after intraperitoneally administrated with 20mg/kg aristolochic acid. Severity of acute ischemic injury was stratified by clamping the dissected bilateral renal arteries with non-traumatic microvascular clips for 20 or 35min. The AKI mice were induced with renal bilateral I/R injury and CKD mice were crafted with 20mg/kg aristolochic acid administrated intraperitoneally. Histology, genetic and protein expression of biomarkers were measured in three cohorts.

RESULTS

We found that serum creatinine dramatically increased in severe (sAonC) but not in moderate (mAonC) injury mice. Upregulation of Kidney injury molecule-1 (KIM-1) mRNA, tissue inhibitor of metalloproteinase-2 (TIMP-2), Syndecan-1 (SDC-1) mRNA and insulin-like growth factor binding protein-7 (IGFBP7) protein indicated the onset of mAonC. An increase in neutrophil gelatinase-associated lipocalin (NGAL), rhomboid-like protein 2 (RHBDL2), Syndecan-1 (SDC-1) mRNA and protein, and a decrease in IGFBP7 protein were associated with sAonC.

CONCLUSIONS

Our study revealed the variational expression of AKI biomarkers in AonC kidneys, and uncovered IGFBP7 protein can be used as a sensitive biomarker to predict and differentiate AonC severity. The performance of RHBDL2 and SDC-1 in predicting severe AonC was promising, providing new biomarkers for predicting AonC.