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Identification of novel metabolomic biomarkers in an experimental model of septic acute kidney injury.

José Luis Izquierdo-GarcíaNicolás NinPablo Cardinal-FernandezYenny RojasMarta de PaulaRosario GranadosLeticia Martínez-CaroJesús Ruíz-CabelloJosé A Lorente
Published in: American journal of physiology. Renal physiology (2018)
The aim of this study is the identification of metabolomic biomarkers of sepsis and sepsis-induced acute kidney injury (AKI) in an experimental model. Pigs were anesthetized and monitored to measure mean arterial pressure (MAP), systemic blood flow (QT), mean pulmonary arterial pressure, renal artery blood flow (QRA), renal cortical blood flow (QRC), and urine output (UO). Sepsis was induced at t = 0 min by the administration of live Escherichia coli ( n = 6) or saline ( n = 8). At t = 300 min, animals were killed. Renal tissue, urine, and serum samples were analyzed by nuclear magnetic resonance (NMR) spectroscopy. Principal component analyses were performed on the processed NMR spectra to highlight kidney injury biomarkers. Sepsis was associated with decreased QT and MAP and decreased QRA, QRC, and UO. Creatinine serum concentration and neutrophil gelatinase-associated lipocalin (NGAL) serum and urine concentrations increased. NMR-based metabolomics analysis found metabolic differences between control and septic animals: 1) in kidney tissue, increased lactate and nicotinuric acid and decreased valine, aspartate, glucose, and threonine; 2) in urine, increased isovaleroglycine, aminoadipic acid, N-acetylglutamine, N-acetylaspartate, and ascorbic acid and decreased myoinositol and phenylacetylglycine; and 3) in serum, increased lactate, alanine, pyruvate, and glutamine and decreased valine, glucose, and betaine concentrations. The concentration of several metabolites altered in renal tissue and urine samples from septic animals showed a significant correlation with markers of AKI (i.e., creatinine and NGAL serum concentrations). NMR-based metabolomics is a potentially useful tool for biomarker identification of sepsis-induced AKI.
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