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A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury

KIT Bio, 665 3rd Street, San Francisco, CA 94107, USA
Department of Surgery, University of California San Francisco, San Francisco, CA 94143, USA
Masters in Translational Medicine Program, University of California Berkeley, Berkeley, CA 94720, USA
Author to whom correspondence should be addressed.
J. Clin. Med. 2019, 8(4), 499;
Received: 14 March 2019 / Revised: 1 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
The current standard of care measures for kidney function, proteinuria, and serum creatinine (SCr) are poor predictors of early-stage kidney disease. Measures that can detect chronic kidney disease in its earlier stages are needed to enable therapeutic intervention and reduce adverse outcomes of chronic kidney disease. We have developed the Kidney Injury Test (KIT) and a novel KIT Score based on the composite measurement and validation of multiple biomarkers across a unique set of 397 urine samples. The test is performed on urine samples that require no processing at the site of collection and without target sequencing or amplification. We sought to verify that the pre-defined KIT test, KIT Score, and clinical thresholds correlate with established chronic kidney disease (CKD) and may provide predictive information on early kidney injury status above and beyond proteinuria and renal function measurements alone. Statistical analyses across six DNA, protein, and metabolite markers were performed on a subset of residual spot urine samples with CKD that met assay performance quality controls from patients attending the clinical labs at the University of California, San Francisco (UCSF) as part of an ongoing IRB-approved prospective study. Inclusion criteria included selection of patients with confirmed CKD and normal healthy controls; exclusion criteria included incomplete or missing information for sample classification, logistical delays in transport/processing of urine samples or low sample volume, and acute kidney injury. Multivariate logistic regression of kidney injury status and likelihood ratio statistics were used to assess the contribution of the KIT Score for prediction of kidney injury status and stage of CKD as well as assess the potential contribution of the KIT Score for detection of early-stage CKD above and beyond traditional measures of renal function. Urine samples were processed by a proprietary immunoprobe for measuring cell-free DNA (cfDNA), methylated cfDNA, clusterin, CXCL10, total protein, and creatinine. The KIT Score and stratified KIT Score Risk Group (high versus low) had a sensitivity and specificity for detection of kidney injury status (healthy or CKD) of 97.3% (95% CI: 94.6–99.3%) and 94.1% (95% CI: 82.3–100%). In addition, in patients with normal renal function (estimated glomerular filtration rate (eGFR) ≥ 90), the KIT Score clearly identifies those with predisposing risk factors for CKD, which could not be detected by eGFR or proteinuria (p < 0.001). The KIT Score uncovers a burden of kidney injury that may yet be incompletely recognized, opening the door for earlier detection, intervention and preservation of renal function. View Full-Text
Keywords: KIT Assay; chronic kidney disease; biomarker; non-invasive; urine; eGFR; cfDNA KIT Assay; chronic kidney disease; biomarker; non-invasive; urine; eGFR; cfDNA
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MDPI and ACS Style

Watson, D.; Yang, J.Y.C.; Sarwal, R.D.; Sigdel, T.K.; Liberto, J.M.; Damm, I.; Louie, V.; Sigdel, S.; Livingstone, D.; Soh, K.; Chakraborty, A.; Liang, M.; Lin, P.-C.; Sarwal, M.M. A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury. J. Clin. Med. 2019, 8, 499.

AMA Style

Watson D, Yang JYC, Sarwal RD, Sigdel TK, Liberto JM, Damm I, Louie V, Sigdel S, Livingstone D, Soh K, Chakraborty A, Liang M, Lin P-C, Sarwal MM. A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury. Journal of Clinical Medicine. 2019; 8(4):499.

Chicago/Turabian Style

Watson, Drew, Joshua Y.C. Yang, Reuben D. Sarwal, Tara K. Sigdel, Juliane M. Liberto, Izabella Damm, Victoria Louie, Shristi Sigdel, Devon Livingstone, Katherine Soh, Arjun Chakraborty, Michael Liang, Pei-Chen Lin, and Minnie M. Sarwal 2019. "A Novel Multi-Biomarker Assay for Non-Invasive Quantitative Monitoring of Kidney Injury" Journal of Clinical Medicine 8, no. 4: 499.

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