Abstract
Emerging urinary kidney safety biomarkers have been evaluated in recent years and have been shown to be superior to the serum parameters blood urea nitrogen (BUN) and creatinine (sCr) for monitoring kidney injury in the proximal tubule. However, their potential application in differentiating the location of the initial kidney injury (eg, glomerulus vs tubule) has not been fully explored. Here, we assessed the performance of two algorithms that were constructed using either an empirical or a mathematical model to predict the site of kidney injury using a data set consisting of 22 rat kidney toxicity studies with known urine biomarker and histopathologic outcomes. Two kidney safety biomarkers used in both models, kidney injury molecule 1 (KIM-1) and albumin (ALB), were the best performers to differentiate glomerular injury from tubular injury. The performance of algorithms using these two biomarkers against the gold standard of kidney histopathologic examination showed high sensitivity in differentiating the location of the kidney damage to either the glomerulus or the proximal tubules. These data support the exploration of such an approach for use in clinical settings, leveraging urinary biomarker data to aid in the diagnosis of either glomerular or tubular injury where histopathologic assessments are not conducted.