AKI is a common clinical condition associated with a number of adverse outcomes. More timely diagnosis would allow for earlier intervention and could improve patient outcomes. The goal of early identification of AKI has been the primary impetus for AKI biomarker research, and has led to the discovery of numerous novel biomarkers. However, in addition to facilitating more timely intervention, AKI biomarkers can provide valuable insight into the molecular mechanisms of this complex and heterogeneous disease. Furthermore, AKI biomarkers could also function as molecular phenotyping tools that could be used to direct clinical intervention. This review highlights the major studies that have characterized the diagnostic and prognostic predictive power of these biomarkers. The mechanistic relevance of neutrophil gelatinase-associated lipocalin, kidney injury molecule 1, IL-18, livertype fatty acid-binding protein, angiotensinogen, tissue inhibitor of metalloproteinase-2, and IGF-binding protein 7 to the pathogenesis and pathobiology of AKI is discussed, putting these biomarkers in the context of the progressive phases of AKI. A biomarker-integrated model of AKI is proposed, which summarizes the current state of knowledge regarding the roles of these biomarkers and the molecular and cellular biology of AKI.

Biomarkers for acute kidney injury (AKI) have been used to predict the progression of AKI but a systematic comparison of the prognostic ability of each biomarkers alone or in combination has not been performed. In order to assess this, we measured the concentration of 32 candidate biomarkers in the urine of 95 patients with AKIN stage 1 after cardiac surgery. Urine markers were divided into eight groups based on the putative pathophysiologic mechanism they reflect. We then compared the ability of the markers alone or in combination to predict the primary outcome of worsening AKI or death (23 patients) and the secondary outcome of AKIN stage 3 or death (13 patients). IL-18 was the best predictor of both outcomes (AUC of 0.74 and 0.89). L-FABP (AUC of 0.67 and 0.85), NGAL (AUC of 0.72 and 0.83) and KIM-1 (AUC of 0.73 and 0.81) were also good predictors. Correlation between most of the markers was generally related to their predictive ability but KIM-1 had a relatively weak correlation with other markers. The combination of IL-18 and KIM-1 had a very good predictive value with an AUC of 0.93 to predict AKIN 3 or death. Thus, combination of IL-18 and KIM-1 would result in improved identification of high risk patients for enrollment in clinical trials.

Recent studies show the importance of mitochondrial dysfunction in the initiation and progression of acute kidney injury (AKI). However, no biomarkers exist linking renal injury to mitochondrial function and integrity. To this end, we evaluated urinary mitochondrial DNA (UmtDNA) as a biomarker of renal injury and function in humans with AKI following cardiac surgery. mtDNA was isolated from the urine of patients following cardiac surgery and quantified by qPCR. Patients were stratified into no AKI, stable AKI and progressive AKI groups based on Acute Kidney Injury Network (AKIN) staging. UmtDNA was elevated in progressive AKI patients, and was associated with progression of patients with AKI at collection to higher AKIN stages. To evaluate the relationship of UmtDNA to measures of renal mitochondrial integrity in AKI, mice were subjected to sham surgery or varying degrees of ischemia followed by 24 hours of reperfusion. UmtDNA increased in mice after 10-15 minutes of ischemia and positively correlated with ischemia time. Furthermore, UmtDNA was predictive of AKI in the mouse model. Finally, UmtDNA levels were negatively correlated with renal cortical mtDNA and mitochondrial gene expression. These translational studies demonstrate that UmtDNA is associated with recovery from AKI following cardiac surgery by serving as an indicator of mitochondrial integrity. Thus, UmtDNA may serve as valuable biomarker for the development of mitochondrial targeted therapies in AKI.

SummaryBackground Biomarkers of AKI that can predict which patients will develop severe renal disease at the time of diagnosis will facilitate timely intervention in populations at risk of adverse outcomes.Design, setting, participants, & measurements Liquid chromatography/tandem mass spectrometry was used to identify 30 potential prognostic urinary biomarkers of severe AKI in a group of patients that developed AKI after cardiac surgery. Angiotensinogen had the best discriminative characteristics. Urinary angiotensinogen was subsequently measured by ELISA and its prognostic predictive power was verified in 97 patients who underwent cardiac surgery between August 1, 2008 and October 6, 2011.Results The urine angiotensinogen/creatinine ratio (uAnCR) predicted worsening of AKI, Acute Kidney Injury Network (AKIN) stage 3, need for renal replacement therapy, discharge .7 days from sample collection, and composite outcomes of AKIN stage 2 or 3, AKIN stage 3 or death, and renal replacement therapy or death. The prognostic predictive power of uAnCR was improved when only patients classified as AKIN stage 1 at the time of urine sample collection (n=79) were used in the analysis, among whom it predicted development of stage 3 AKI or death with an area under the curve of 0.81. Finally, category free net reclassification improvement showed that the addition of uAnCR to a clinical model to predict worsening of AKI improved the predictive power.Conclusions Elevated uAnCR is associated with adverse outcomes in patients with AKI. These data are the first to demonstrate the utility of angiotensinogen as a prognostic biomarker of AKI after cardiac surgery.

Diabetic nephropathy is the leading cause of end stage renal disease. The urinary albumin to creatinine ratio is used as a predictor for the development of nephropathy but it is neither sensitive nor specific. Here we used liquid chromatography/mass spectrometry on urine of eight normoalbuminuric patients with type 2 diabetes from the VA Diabetes Trial to identify candidate markers for loss of renal function. Initial verification of 7 markers (agrin, haptoglobin, mannan-binding lectin serine protease 2, LAMP-2, angiotensinogen, NGAL and uromodulin) in the urine of an additional 30 patients showed that haptoglobin was the best predictor of early renal functional decline. We then measured this in the urine of 204 patients with type 2 diabetes who did not yet have significant kidney disease (eGFR stage 2 or better and an albumin to creatinine ratio less than 300 mg/g). In comparing the highest to lowest tertile, the odds ratio for having early renal function decline was 2.70 (CI 1.15, 6.32) using the haptoglobin to creatinine ratio compared to 2.50 (CI 1.14, 5.48) using the albumin to creatinine ratio after adjusting for treatment group and use of ACE inhibitors. Addition of the haptoglobin to creatinine ratio to a model using the albumin to creatinine ratio to predict early renal function decline resulted in improved predictive performance. Thus, the haptoglobin to creatinine ratio may be useful to predict patients with type 2 diabetes at risk of nephropathy prior to the development of macroalbuminuria or reduced GFR.