Search

Elevated urinary albumin excretion in patients with type 1 diabetes reverts to normoalbuminuria in a majority of patients but advances toward proteinuria in some. In order to gain valuable insights into the early pathophysiology of diabetic nephropathy we evaluated the association of kidney tubular injury biomarkers with changes in albuminuria in patients with type 1 diabetes mellitus. Urine levels of kidney injury molecule-1 (KIM-1), N-acetyl-β-D-glucosaminidase (NAG), and some inflammatory markers were determined in 38 healthy individuals and 659 patients with type 1 diabetes mellitus having varying degrees of albuminuria. Urinary interleukin-6, CXCL10/IP-10, NAG, and KIM-1 levels were very low in healthy individuals, increased in type 1 patients with normoalbuminuria, and were highest in diabetic patients that had microalbuminuria. Low baseline concentrations of urinary KIM-1 and NAG both individually and collectively were significantly associated with the regression of microalbuminuria over the subsequent 2 years; an effect independent of clinical characteristics. Progression and regression of microalbuminuria were unrelated to urinary levels of interleukins 6 and 8, CXCL10/IP-10, and monocyte chemoattractant protein-1. Thus our results show that lower urinary KIM-1 and NAG levels were associated with the regression of microalbuminuria in type 1 diabetes mellitus. Hence, tubular dysfunction is a critical component of the early course of diabetic nephropathy. [ABSTRACT FROM AUTHOR]

Kidney toxicity accounts both for the failure of many drug candidates as well as considerable patient morbidity. Whereas histopathology remains the gold standard for nephrotoxicity in animal systems, serum creatinine (SCr) and blood urea nitrogen (BUN) are the primary options for monitoring kidney dysfunction in humans. The transmembrane tubular protein kidney injury molecule-1 (Kim-1) was previously reported to be markedly induced in response to renal injury. Owing to the poor sensitivity and specificity of SCr and BUN, we used rat toxicology studies to compare the diagnostic performance of urinary Kim-1 to BUN, SCr and urinary N-acetyl-beta-D-glucosaminidase (NAG) as predictors of kidney tubular damage scored by histopathology. Kim-1 outperforms SCr, BUN and urinary NAG in multiple rat models of kidney injury. Urinary Kim-1 measurements may facilitate sensitive, specific and accurate prediction of human nephrotoxicity in preclinical drug screens. This should enable early identification and elimination of compounds that are potentially nephrotoxic.

Acute kidney injury (AKI) is a common condition with significant associated morbidity and mortality. The insensitivity and non-specificity of traditional markers of renal dysfunction prevent timely diagnosis, estimation of the severity of renal injury, and the administration of possible therapeutic agents. Here, we determine the prognostic ability of urinary liver-type fatty acid-binding protein (L-FABP), and further characterize its sensitivity and specificity as a biomarker of AKI. Initial western blot studies found increased urinary L-FABP in patients with confirmed AKI. A more extensive cross-sectional study found significant increases in urinary L-FABP, normalized to urinary creatinine, in 92 patients with established AKI compared with 62 patients without clinical evidence of AKI. In hospitalized patients, the diagnostic performance of urinary L-FABP for AKI, assessed by the area under the receiver operating characteristic curve, was 0.93. This compares favorably with other established biomarkers of AKI such as kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, N-acetyl-beta-glucosaminidase, and interleukin-18. Our study shows that age-adjusted urinary L-FABP levels were significantly higher in patients with poor outcome, defined as the requirement for renal replacement therapy or the composite end point of death or renal replacement therapy.

Acute kidney injury (AKI) is associated with high morbidity and mortality. The lack of sensitive and specific injury biomarkers has greatly impeded the development of therapeutic strategies to improve outcomes of AKI.The unique objective of this study was to evaluate the diagnostic performance of nine urinary biomarkers of AKI-kidney injury molecule-1 (KIM-1), neutrophil gelatinase associated lipocalin (NGAL), interleukin-18 (IL-18), hepatocyte growth factor (HGF), cystatin C (Cys), N-acetyl-beta-D-glucosaminidase (NAG), vascular endothelial growth factor (VEGF), chemokine interferon-inducible protein 10 (IP-10; CXCL10), and total protein-in a cross-sectional comparison of 204 patients with or without AKI.Median urinary concentrations of each biomarker were significantly higher in patients with AKI than in those without AKI (p < 0.001). The area under the receiver operating characteristics curve (AUC-ROC) for the combination of biomarkers using a logic regression model [risk score of 2.93*(NGAL > 5.72 and HGF > 0.17) + 2.93*(PROTEIN > 0.22) -2*(KIM < 0.58)] was greater (0.94) than individual biomarker AUC-ROCs. Age-adjusted levels of urinary KIM-1, NAG, HGF, VEGF, and total protein were significantly higher in patients who died or required renal replacement therapy (RRT) when compared to those who survived and did not require RRT.Our results demonstrate the comparative value of multiple biomarkers in the diagnosis and prognosis of AKI.

Reliable biomarkers of toxicity are necessary both for the safe conduct of pre-clinical and clinical trials, and are increasingly needed for accurate clinical evaluation of treatment regimens with the potential to cause tissue injury. Recent advances in technology have added several new tools to the biomarker screening toolkit and improved the throughput of existing quantitative assays. Genomics, proteomics, and metabolomics have provided a wealth of data in the search for predictive, specific biomarkers. Multiplexed ELISA-based assay systems, silicon nanowire arrays, and patterned paper present unique abilities for fast, efficient sample analysis over a broad dynamic range. Powerful integrative systems biology software and growing open-source data repositories offer new ways to share, reduce, and analyze data from multiple sources. Novel technologies reviewed here have the potential to significantly reduce assay time and cost and improve the sensitivity of screening methods for candidate biomarkers of toxicity.