High-resolution mass spectrometry for exploring metabolic signatures of sepsis-induced acute kidney injury

Sepsis is a commonly encountered scenario in an intensive care unit (ICU), and the kidney is one of the organs frequently affected. Sepsis-induced acute kidney injury (SIAKI) contributes to the high mortality and morbidity. A major reason for this is the lack of biomarkers for SIAKI in ICU patients. Metabolic phenotype signatures of SIAKI may enable metabolite biomarker discovery for diagnosis. With the progress of the Omics, currently, high-resolution mass spectrometry-based metabolomics is being used for biomarker discovery. Orthogonal partial least-squares discriminant analysis (OPLS-DA) afforded a good predictive tool to distinguish patients and detect the specific metabolic patterns. Variable importance for projection (VIP) was conducted to identify potential biomarkers for SIALI. Receiver operating characteristic analysis was performed for evaluating the diagnostic accuracy of potential metabolites. In this study, some potential biomarkers were successfully discovered by the commonly used variable selection method, VIP of OPLS-DA. Six metabolites were identified as the potential biomarkers for distinguishing SIAKI patients. Meanwhile, malonylcarnitine, D-glutamine and 3-methoxytyrosine were found to be the important variables to distinguish between SIAKI patients and healthy cases. According to the receiver operating characteristic analysis, we reported malonylcarnitine, with an area under concentration–time curve value of 0.995, maybe as a novel diagnostic biomarker associated with SIALI patients. Our results indicate that serum metabolic profiling by high-resolution mass spectrometry might be a helpful tool for determining the metabolic phenotype of SIAKI patients.

[1]  Q. Liang,et al.  High-throughput metabolic profiling for discovering metabolic biomarkers of sepsis-induced acute lung injury , 2016 .

[2]  A. Zhang,et al.  Discovery of serum metabolites for diagnosis of progression of mild cognitive impairment to Alzheimer's disease using an optimized metabolomics method , 2016 .

[3]  S. Bagshaw,et al.  Prevention and treatment of sepsis-induced acute kidney injury: an update , 2015, Annals of Intensive Care.

[4]  P. Honore,et al.  Presepsin and sepsis-induced acute kidney injury treated with continuous renal replacement therapy: will another promising biomarker bite the dust? , 2015, Critical Care.

[5]  A. Zhang,et al.  Potential urine biomarkers from a high throughput metabolomics study of severe sepsis in a large Asian cohort , 2015 .

[6]  R. Bellomo,et al.  Sepsis-Induced Acute Kidney Injury. , 2015, Critical care clinics.

[7]  A. Zhang,et al.  Metabolomics of alcoholic liver disease: a clinical discovery study , 2015 .

[8]  Peng Wang,et al.  Exogenous Carbon Monoxide Decreases Sepsis-Induced Acute Kidney Injury and Inhibits NLRP3 Inflammasome Activation in Rats , 2015, International journal of molecular sciences.

[9]  Xue-jian Zhao,et al.  Panaxadiol Saponin and Dexamethasone Improve Renal Function in Lipopolysaccharide-Induced Mouse Model of Acute Kidney Injury , 2015, PloS one.

[10]  A. Azim,et al.  Antimicrobial dosing in critically ill patients with sepsis-induced acute kidney injury , 2015, Indian Journal of Critical Care Medicine.

[11]  Shaoli Zhou,et al.  Dexmedetomidine protects against acute kidney injury through downregulating inflammatory reactions in endotoxemia rats. , 2015, Biomedical reports.

[12]  J. Locasale,et al.  High-Resolution Metabolomics with Acyl-CoA Profiling Reveals Widespread Remodeling in Response to Diet* , 2015, Molecular & Cellular Proteomics.

[13]  J. Kellum,et al.  Acute kidney injury in severe sepsis: pathophysiology, diagnosis, and treatment recommendations. , 2015, Journal of veterinary emergency and critical care.

[14]  G. Wagener,et al.  New insights into the mechanisms of acute kidney injury in the intensive care unit. , 2015, Journal of clinical anesthesia.

[15]  N. Singh,et al.  Antimicrobial dosing in critically ill patients with sepsis-induced acute kidney injury , 2015, Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine.

[16]  Q. Liang,et al.  Discovery of serum metabolites for diagnosis of mild cognitive impairment to Alzheimer's disease progression using an optimized metabolomics method , 2015 .

[17]  Wentao Bao Biomarkers, diagnosis and management of sepsis-induced acute kidney injury: a narrative review , 2015, Heart, lung and vessels.

[18]  N. Roewer,et al.  Sepsis-induced acute kidney injury by standardized colon ascendens stent peritonitis in rats - a simple, reproducible animal model , 2014, Intensive Care Medicine Experimental.

[19]  B. Allaouchiche,et al.  Metabolic phenotyping of traumatized patients reveals a susceptibility to sepsis. , 2013, Analytical chemistry.

[20]  Stephanie J. Reisinger,et al.  An Integrated Clinico-Metabolomic Model Improves Prediction of Death in Sepsis , 2013, Science Translational Medicine.

[21]  James B. Mitchell,et al.  Metabolomics Reveals That Tumor Xenografts Induce Liver Dysfunction* , 2013, Molecular & Cellular Proteomics.

[22]  Q. Zhan,et al.  Global and Targeted Metabolomics of Esophageal Squamous Cell Carcinoma Discovers Potential Diagnostic and Therapeutic Biomarkers* , 2013, Molecular & Cellular Proteomics.