Acute kidney injury (AKI) represents a common and devastating problem in clinical medicine. The incidence of AKI varies from 5 % of hospitalized patients to 30–50 % of patients in intensive care units. Despite significant improvements in therapeutics, evidence suggests that the incidence of AKI is increasing at an alarming rate, and the associated mortality and morbidity have remained high despite improvements in clinical care [46, 49, 51]. A major reason for this high mortality and morbidity is the lack of early biomarkers for AKI, resulting in an unacceptable delay in the initiation of therapy. In addition, convenient biomarkers are urgently needed to distinguish between the various etiologies of AKI and to predict its clinical outcomes. Fortunately, the application of proteomics research to human and animal models of AKI has uncovered several novel biomarkers.

Significant efforts have been made to develop an early diagnostic biomarker for AKI in the hope that the early identification of renal injury will enable more effective therapeutic interventions. Ho et al. [16] used SELDI-TOF/MA to determine urinary proteomic profiles at different time points following coronary artery bypass grafting (CABG) operations. The active 25-amino acid form of hepcidin (hepcidin-25) was found to be dominantly elevated in postoperative non-AKI urine samples compared with AKI samples. This biomarker was further validated in an independent cohort of 338 patients [17]. The log10 hepcidin-25/Cr ratio reached a sensitivity of 68 % and a specificity of 68 %, with an AUC of 0.80 for the avoidance of AKI and a negative predictive value 0.96. Areeger et al. [3] collected urine samples from 36 patients after cardiopulmonary bypass surgery. They compared the urinary proteomes of patients with and without AKI on the first postoperative day. After the operation, inflammation-associated (zinc-α-2-glycoprotein, leucine-rich α-2-glycoprotein, mannan-binding lectin serine protease 2, basement membrane-specific heparan sulfate proteoglycan, and immunoglobulin kappa) or tubular dysfunction-associated (retinol-binding protein, adrenomedullin-binding protein, and uromodulin) proteins were found to be differentially regulated. Zinc-α-2-glycoprotein and a fragment of adrenomedullin-binding protein were decreased in patients with AKI. The decreased excretion of zinc-α-2-glycoprotein in patients with AKI was confirmed by Western blot and ELISA in an independent cohort of 22 patients with and 46 patients without AKI. Zinc-α-2-glycoprotein is thus a potentially useful predictive marker for AKI after cardiopulmonary bypass surgery.

In the last 10 years, urine neutrophil gelatinase-associated lipocalin (NGAL, also known as lcn2) has become one of the most important predictive biomarkers of AKI. NGAL is one of the earliest and most robustly induced proteins in the kidney after ischemic or nephrotoxic AKI in animal models. Indeed, the NGAL protein is easily detected in urine soon after AKI [24, 25, 45]. However, NGAL measurements may be influenced by a number of coexisting variables, such as preexisting renal disease and systemic or urinary tract infections [12]. Research to explore more accurate AKI predictive biomarkers is ongoing. Areeger et al. [4] collected urine on the first day of AKI in critically ill patients; 12 patients with an early recovery and 12 matching patients with late/non-recovery were selected, and their proteomes were analyzed by gel electrophoresis and mass spectrometry. A total of 8 prognostic candidates were identified. Subsequent ELISA quantification demonstrated that IGFBP-7 was the most potent predictor of renal recovery. IGFBP-7 and NGAL, a traditional AKI biomarker, were chosen for further analyses in an independent verification group of 28 patients with AKI and 12 control patients without AKI. The comparative analysis indicated that IGFBP-7 and NGAL were significantly upregulated in the urine of AKI patients, which in turn predicted the mortality (IGFBP-7: AUC 0.68; NGAL: AUC 0.81), recovery (IGFBP-7: AUC 0.74; NGAL: AUC 0.70), and severity (IGFBP-7: AUC 0.77; NGAL: AUC 0.69) of AKI. The levels of these proteins were also associated with AKI duration. IGFBP-7 was a more accurate predictor of renal outcome than NGAL. Thus, IGFBP-7 is a novel prognostic urinary marker that warrants further investigation.

Urinary proteomics provide a novel method for identifying early diagnostic and prognostic biomarkers of AKI. This technique can be integrated with and is complementary to traditional hypothesis-driven approaches. Moreover, this technique provides an additional armamentarium for discovery-based biomarker studies and can provide novel insights into the underlying pathophysiology of AKI, which may ultimately lead to the identification of novel therapeutic targets.

Kidney disease has been the subject of a number of urinary proteomics studies. This research has greatly improved our understanding of the mechanisms of various kidney diseases and has provided alternative biomarkers for classification, diagnosis, and response prediction. However, several limitations have hampered the development of this approach and the translation of results to clinical applications.

First, there are challenges in the standardization of urine collection, preparation, and storage in urinary proteomics. The quality and quantity of urine proteins are affected by diet and exercise, and thus, sample collection under stable conditions is critical for the reliability and comparability of urinary proteomics results. Moreover, the storage, preparation, and analysis of urine samples may also affect the profiling. Standardization of these techniques is required to obtain more reliable proteomics data. Although an international normal urine collection protocol has been developed by the European Kidney and Urine Proteomics (EuroKUP) group and the Human Kidney and Urine Proteome Project (HKUPP) (http://​www.​hkupp.​org), there are still no globally acceptable guidelines for urine sampling with mass proteinuria [23].