Literature DB >> 29100025

Application of nuclear magnetic resonance spectroscopy for the detection of metabolic disorders in patients with moderate kidney insufficiency.

Adriana Mika1, Wojciech Wojtowicz2, Adam Ząbek2, Piotr Młynarz2, Michal Chmielewski3, Tomasz Sledzinski4, Piotr Stepnowski5.   

Abstract

Chronic kidney disease (CKD) is one of the major problems of modern medicine and a huge socioeconomic burden. Thorough knowledge of metabolic alterations associated with this condition is vital to prevent its progression. However, still little is known about metabolic disorders associated with CKD. In this study, we used 1H NMR spectroscopy and multivariate analysis to identify alterations in serum metabolites of patients with various stages of CKD. 1H NMR spectroscopy followed by multivariate analysis showed that CKD patients differed from the controls in terms of 15 endogenous metabolites, and MetPA analysis demonstrated significant intergroup differences in 5 potential target pathways and 14 metabolites. Owing a good performance of discriminant models, these findings suggest that CKD patients and healthy controls differ in terms of their metabolic fingerprints. In turn, the results of MetPA analysis imply that CKD and its progression exert an effect on selected metabolic pathways. This study provided a better insight into metabolic alterations associated with CKD, and identified some target pathways that can be potentially modified to slow down the progression of this serious and debilitating disease.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Chronic kidney disease; Creatinine; Discriminant models; Metabolomics; Nuclear magnetic resonance spectroscopy; Serum

Mesh:

Year:  2017        PMID: 29100025     DOI: 10.1016/j.jpba.2017.10.037

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  3 in total

1.  Plasma metabolic profiling analysis of Strychnos nux-vomica Linn. and Tripterygium wilfordii Hook F-induced renal toxicity using metabolomics coupled with UPLC/Q-TOF-MS.

Authors:  Houmin Luo; Caiyun Gu; Chuanxin Liu; Yuming Wang; Hao Wang; Yubo Li
Journal:  Toxicol Res (Camb)       Date:  2018-07-25       Impact factor: 3.524

2.  1,5-Anhydroglucitol predicts CKD progression in macroalbuminuric diabetic kidney disease: results from non-targeted metabolomics.

Authors:  Gesiane Tavares; Gabriela Venturini; Kallyandra Padilha; Roberto Zatz; Alexandre C Pereira; Ravi I Thadhani; Eugene P Rhee; Silvia M O Titan
Journal:  Metabolomics       Date:  2018-02-27       Impact factor: 4.290

3.  Serum-Urine Matched Metabolomics for Predicting Progression of Henoch-Schonlein Purpura Nephritis.

Authors:  Qian Zhang; Ling-Yun Lai; Yuan-Yuan Cai; Ma-Jie Wang; Gaoxiang Ma; Lian-Wen Qi; Jun Xue; Feng-Qing Huang
Journal:  Front Med (Lausanne)       Date:  2021-05-12
  3 in total

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