Emerging biomarkers and metabolomics for assessing toxic nephropathy and acute kidney injury (AKI) in neonatology (original) (raw)
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Current Medicinal Chemistry, 2012
For a long time, nephrotoxicity has been definitively defined as renal injury or dysfunction that arises as a direct or indirect result of exposure to drugs and industrial or environmental chemicals. There are a number of inherent difficulties in diagnostic procedures for toxic nephropathy, which include the absence of standard diagnostic criteria and the inability to relate exposure to a given agent and the observed effect. Critically ill newborns represent a high risk population for developing toxic nephropathy because of incomplete maturation of the kidney; furthermore, they are often treated with a combination of various therapeutic agents, each of them potentially inducing renal tissue injury. Antibiotics, antifungals, and non-steroidal antiiflammatory drugs (NSAIDs) can induce nephrotoxic damage by several, concomitant mechanisms of action on different segments of the nephron. The most common clinical feature following a nephrotoxic effect is acute kidney injury (AKI) which, in turn, comprises a spectrum of severe tissue damages along the nephron, leading to an abrupt decline in renal function. Because early stages of toxic nephropathy are characterized by very few specific clinical signs and symptoms, there is the urgent need to investigate new biomarkers for predicting nephrotoxicity and localizing the injury to a specific nephron site, in order to reduce the risk of acute renal injury and/or acute tubular necrosis. The most promising biomarker for the early assessment of kidney injury and damage is neutrophil gelatinase-associated lipocalin (NGAL). NGAL can be easily measured in urine by an automated analytical method, allowing its clinical use in emergency likewise creatinine. Considerable expectations in terms of improvement of the management of newborns developing drug-induced nephropaties derive from the clinical application of metabolomics.
Urine metabolomic profiling in neonatal nephrology
Clinical Biochemistry, 2014
a b s t r a c t 7 after asphyxia. This is responsible of the different behaviors of piglets 66 after a strong hypoxic stimulus giving rise to asystolia and/or shock. 67 After resuscitation, performed following a rigorous protocol by (the 68 same anesthesiologist in the same way with the same drugs) some 69 piglets die, others reach pre-hypoxic conditions after several hours 70 and they suffer from multi-organ failure (MOF), including acute kid-71 ney injury; finally other piglets reach basal pre-hypoxic values after 1 V. Fanos et al. / Clinical Biochemistry xxx (2014) Please cite this article as: Fanos V, et al, Urine metabolomic profiling in neonatal nephrology, Clin Biochem (2014), http://dx.doi.org/10.1016/ j.clinbiochem.2014.05.020 resuscitation very early (within 15 min). This is an expression of an in-73 trinsic resilience of the subject. Interestingly and surprisingly urinary 74 metabolomics performed on samples before resuscitation are able to 75 predict and anticipate the destiny of the piglet (death, MOF, quick 76 recovery). Piglets die Q7 by 2 different mechanisms (either cardiac or 77 respiratory): while today we are treating all of them in the same way 78
Discovery of Metabolomics Biomarkers for Early Detection of Nephrotoxicity
Toxicologic Pathology, 2009
Drug-induced nephrotoxicity is a major concern, since many pharmacological compounds are filtered through the kidneys for excretion into urine. To discover biochemical biomarkers useful for early identification of nephrotoxicity, metabolomic experiments were performed on Sprague-Dawley Crl:CD (SD) rats treated with the nephrotoxins gentamicin, cisplatin, or tobramycin. Using a combination of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS), a global, nontargeted metabolomics analysis was performed on urine and kidney samples collected after one, five, and twenty-eight dosing days. Increases in polyamines and amino acids were observed in urine from drug-treated rats after a single dose, and prior to observable histological kidney damage and conventional clinical chemistry indications of nephrotoxicity. Thus, these metabolites are potential biomarkers for the early detection of drug-induced nephrotoxicity. Upon prolonged dosing, nephrotoxin-induced changes included a progressive loss of amino acids in urine, concomitant with a decrease in amino acids and nucleosides in kidney tissue. A nephrotoxicity prediction model, based on the levels of branched-chain amino acids in urine, distinguished nephrotoxin-treated samples from vehicle-control samples, with 100%, 93%, and 70% accuracy at day 28, day 5, and day 1, respectively. Thus, this panel of biomarkers may provide a noninvasive method to detect kidney injury long before the onset of histopathological kidney damage.
Metabolomics in pediatric nephrology: emerging concepts
Pediatric nephrology (Berlin, Germany), 2014
Metabolomics, the latest of the "omics" sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome, and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry, metabolomics has the potential to play a major role in monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights into novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biological therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opport...
Urinary metabolomic markers of aminoglycoside nephrotoxicity in newborn rats
Pediatric Research, 2013
Basic Science Investigation nature publishing group Background: Aminoglycoside exposure is a common cause of acute kidney injury (AKI). Delay in the diagnosis of AKI using conventional biomarkers has been one of the important obstacles in applying early effective interventions. We tested the hypothesis that urinary metabolomics could identify novel early biomarkers for toxic renal injury. Methods: Three-day-old rats were divided into three groups; they received a single daily injection of vehicle (0.9% NaCl solution) or gentamicin at a dose of 10 or 20 mg/kg/d for 7 d. Urine and blood were collected after 3 and 7 d of injections. Urinary metabolites were evaluated using high-performance liquid chromatography and gas chromatography/ mass spectrometry. results: A distinct urinary metabolic profile characterized by glucosuria, phosphaturia, and aminoaciduria was identified preceding changes in serum creatinine. At both the gentamicin doses, urinary tryptophan was significantly (P < 0.05) increased (fold change: 1.91 and 2.31 after 3 d; 1.81 and 1.93 after 7 d). Similarly, kynurenic acid, a tryptophan metabolite, showed a significant (P < 0.05) decrease (fold change: 0.26 and 0.24 after 3 d; 0.21 and 0.52 after 7 d), suggesting an interruption of the normal tryptophan metabolism pathway. conclusion: We conclude that urinary metabolomic profiling provides a robust approach for identifying early and novel markers of gentamicin-induced AKI. a cute kidney injury (AKI) in the intensive care setting is
Journal of Maternal-Fetal and Neonatal Medicine, 2011
Background: Clinical metabolomics is a recent "omic" technology which is defined as a global holistic overview of the personal metabolic status (fingerprinting). This technique allows to prove metabolic differences in different groups of people with the opportunity to explore interactions such as genotypephenotype and genotype-environment type, whether normal or pathological. Aim: To study chronic kidney injury 1) using urine metabolomic profiles of young adults born extremely low-birth weight (ELBW) and 2) correlating a biomarker of kidney injury, urinary neutrophil gelatinase-associated lipocalin (NGAL), in order to confirm the metabolomic injury profile. Method: Urine samples were collected from a group of 18 people (mean: 24-year-old, std: 4.27) who were born with ELBW and a group of 13 who were born at term appropriate for gestational age (AGA) as control (mean 25-year-old, std: 5.15). Urine samples were analyzed by 1 H-nuclear magnetic resonance spectroscopy, and then submitted to unsupervised and supervised multivariate analysis. Urine NGAL (uNGAL) was measured using ARCHITECT (ABBOTT diagnostic NGAL kit). Results: With a multivariate approach and using a supervised analysis method, PLS-DA, (partial least squares discriminant analysis) we could correlate ELBW metabolic profiles with uNGAL concentration. Conversely, uNGAL could not be correlated to AGA. Conclusions: This study demonstrates the relevance of the metabolomic technique as a predictive tool of the metabolic status of exELBW. This was confirmed by the use of uNGAL as a biomarker which may predict a subclinical pathological process in the kidney such as chronic kidney disease.
Metabolomics - Fundamentals and Applications, 2016
Throughout recent decades, the incidence of preterm birth has risen worldwide, and although the majority of preterm neonates now survive infancy, many suffer from debilitating morbidities in the short term and/or increased disease risks in the long term. Traditional diagnostic biomarkers suffer from considerable confounders, limiting their use in the early identification of diseases. There is a need to develop novel biomarkers that can identify, in real time, the evolution of organ dysfunction in an early diagnostic, monitoring, and prognostic fashion. Use of "omics," particularly metabolomics, may provide valuable information regarding functional pathways underlying different pathologies and prediction of clinical outcomes. The emerging knowledge generated by the application of metabolomics in neonatology provides new insights that can help to identify markers of early diagnosis, disease progression, response to treatment, and new therapeutic targets. In this chapter, we review the current knowledge of different metabolomics technologies in neonatal-perinatal medicine, including biomarker discovery, defining as yet unrecognized biologic therapeutic targets, and linking of metabolomics to relevant standard indices and long-term outcomes.
PLoS ONE, 2012
Premature infants are frequently exposed to aminoglycoside antibiotics. Novel urinary biomarkers may provide a noninvasive means for the early identification of aminoglycoside-related proximal tubule renal toxicity, to enable adjustment of treatment and identification of infants at risk of long-term renal impairment. In this proof-of-concept study, urine samples were collected from 41 premature neonates (#32 weeks gestation) at least once per week, and daily during courses of gentamicin, and for 3 days afterwards. Significant increases were observed in the three urinary biomarkers measured (Kidney Injury Molecule-1 (KIM-1), Neutrophil Gelatinase-associated Lipocalin (NGAL), and N-acetyl-b-D-glucosaminidase (NAG)) during treatment with multiple courses of gentamicin. When adjusted for potential confounders, the treatment effect of gentamicin remained significant only for KIM-1 (mean difference from not treated, 1.35 ng/mg urinary creatinine; 95% CI 0.05-2.65). Our study shows that (a) it is possible to collect serial urine samples from premature neonates, and that (b) proximal tubule specific urinary biomarkers can act as indicators of aminoglycoside-associated nephrotoxicity in this age group. Further studies to investigate the clinical utility of novel urinary biomarkers in comparison to serum creatinine need to be undertaken. Citation: McWilliam SJ, Antoine DJ, Sabbisetti V, Turner MA, Farragher T, et al. (2012) Mechanism-Based Urinary Biomarkers to Identify the Potential for Aminoglycoside-Induced Nephrotoxicity in Premature Neonates: A Proof-of-Concept Study. PLoS ONE 7(8): e43809.