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Serum metabolomics study of end-stage renal disease with depression: potential biomarkers for diagnosis and promising targets for therapy

semanticscholar(2019)

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Abstract
Abstract Background End-stage renal disease (ESRD) is the most severe stage during the development of the renal failure. And depression is the most common psychological disorder in patients with ESRD, which in turn aggravates the progression of renal failure and seriously reduce the quality of life in ESRD patients with depression, but its underlying mechanism remains unclear. This study aimed to reveal the pathogenesis and discover novel peripheral biomarkers for ESRD with depression through metabolomics analysis.Methods Ultra-high-performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used to explore changes of serum metabolites among healthy controls (n = 12), ESRD patients (n = 17), and ESRD patients with depression (n = 17). Also, the differential metabolites between groups were subjected to clustering analysis, pathway analysis, receiver operating characteristic (ROC) curve analysis.Results A total of 57 significant serum differential metabolites were identified between the ESRD without depression group and the ESRD with depression group, which were involved in 19 metabolic pathways, such as energy metabolism, glycerolipid metabolism and glutamate-centered metabolism. Moreover, the area under the ROC curve of Gentisic acid, Uric acid, 5-HT, 2-Phosphoglyceric acid, Leucyl-phenylalanine, Propenoyl carnitine, Malaoxon, Pregnenolone, 6-Thioxanthine 5'-monophosphate, Hydroxyl ansoprazole, Zileuton O-glucuronide, Cabergoline, PA (16:0/18:2(9Z,12Z)), PG (18:0/18:1(11Z)), probucol, etc. and their combination was greater than 0.90.Conclusions Inflammation, oxidative stress and metabolic abnormalities in energy metabolism, glycerolipid metabolism and glutamate-centered metabolism may be associated with the pathogenesis of ESRD with depression, which may be promising targets for therapy. Furthermore, the identified differential metabolites may serve as biomarkers for the diagnosis of ESRD patients with depression.
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