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      Optimized Metabolomic Approach to Identify Uremic Solutes in Plasma of Stage 3–4 Chronic Kidney Disease Patients

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          Abstract

          Background

          Chronic kidney disease (CKD) is characterized by the progressive accumulation of various potential toxic solutes. Furthermore, uremic plasma is a complex mixture hampering accurate determination of uremic toxin levels and the identification of novel uremic solutes.

          Methods

          In this study, we applied 1H-nuclear magnetic resonance (NMR) spectroscopy, following three distinct deproteinization strategies, to determine differences in the plasma metabolic status of stage 3–4 CKD patients and healthy controls. Moreover, the human renal proximal tubule cell line (ciPTEC) was used to study the influence of newly indentified uremic solutes on renal phenotype and functionality.

          Results

          Protein removal via ultrafiltration and acetonitrile precipitation are complementary techniques and both are required to obtain a clear metabolome profile. This new approach, revealed that a total of 14 metabolites were elevated in uremic plasma. In addition to confirming the retention of several previously identified uremic toxins, including p-cresyl sulphate, two novel uremic retentions solutes were detected, namely dimethyl sulphone (DMSO 2) and 2-hydroxyisobutyric acid (2-HIBA). Our results show that these metabolites accumulate in non-dialysis CKD patients from 9±7 µM (control) to 51±29 µM and from 7 (0–9) µM (control) to 32±15 µM, respectively. Furthermore, exposure of ciPTEC to clinically relevant concentrations of both solutes resulted in an increased protein expression of the mesenchymal marker vimentin with more than 10% (p<0.05). Moreover, the loss of epithelial characteristics significantly correlated with a loss of glucuronidation activity (Pearson r = −0.63; p<0.05). In addition, both solutes did not affect cell viability nor mitochondrial activity.

          Conclusions

          This study demonstrates the importance of sample preparation techniques in the identification of uremic retention solutes using 1H-NMR spectroscopy, and provide insight into the negative impact of DMSO 2 and 2-HIBA on ciPTEC, which could aid in understanding the progressive nature of renal disease.

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          Most cited references32

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          HMDB: a knowledgebase for the human metabolome

          The Human Metabolome Database (HMDB, http://www.hmdb.ca) is a richly annotated resource that is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community. Since its first release in 2007, the HMDB has been used to facilitate the research for nearly 100 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 2.0) has been significantly expanded and enhanced over the previous release (version 1.0). In particular, the number of fully annotated metabolite entries has grown from 2180 to more than 6800 (a 300% increase), while the number of metabolites with biofluid or tissue concentration data has grown by a factor of five (from 883 to 4413). Similarly, the number of purified compounds with reference to NMR, LC-MS and GC-MS spectra has more than doubled (from 380 to more than 790 compounds). In addition to this significant expansion in database size, many new database searching tools and new data content has been added or enhanced. These include better algorithms for spectral searching and matching, more powerful chemical substructure searches, faster text searching software, as well as dedicated pathway searching tools and customized, clickable metabolic maps. Changes to the user-interface have also been implemented to accommodate future expansion and to make database navigation much easier. These improvements should make the HMDB much more useful to a much wider community of users.
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            A genome-wide association study of metabolic traits in human urine.

            We present a genome-wide association study of metabolic traits in human urine, designed to investigate the detoxification capacity of the human body. Using NMR spectroscopy, we tested for associations between 59 metabolites in urine from 862 male participants in the population-based SHIP study. We replicated the results using 1,039 additional samples of the same study, including a 5-year follow-up, and 992 samples from the independent KORA study. We report five loci with joint P values of association from 3.2 × 10(-19) to 2.1 × 10(-182). Variants at three of these loci have previously been linked with important clinical outcomes: SLC7A9 is a risk locus for chronic kidney disease, NAT2 for coronary artery disease and genotype-dependent response to drug toxicity, and SLC6A20 for iminoglycinuria. Moreover, we identify rs37369 in AGXT2 as the genetic basis of hyper-β-aminoisobutyric aciduria.
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              Metabolomics in the study of kidney diseases.

              Metabolomics--the nontargeted measurement of all metabolites produced by the body--is beginning to show promise in both biomarker discovery and, in the form of pharmacometabolomics, in aiding the choice of therapy for patients with specific diseases. In its two basic forms (pattern recognition and metabolite identification), this developing field has been used to discover potential biomarkers in several renal diseases, including acute kidney injury (attributable to a variety of causes), autosomal dominant polycystic kidney disease and kidney cancer. NMR and gas chromatography or liquid chromatography, together with mass spectrometry, are generally used to separate and identify metabolites. Many hurdles need to be overcome in this field, such as achieving consistency in collection of biofluid samples, controlling for batch effects during the analysis and applying the most appropriate statistical analysis to extract the maximum amount of biological information from the data obtained. Pathway and network analyses have both been applied to metabolomic analysis, which vastly extends its clinical relevance and effects. In addition, pharmacometabolomics analyses, in which a metabolomic signature can be associated with a given therapeutic effect, are beginning to appear in the literature, which will lead to personalized therapies. Thus, metabolomics holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in kidney disease.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                2 August 2013
                : 8
                : 8
                : e71199
                Affiliations
                [1 ]Department of Pharmacology and Toxicology, Radboud University Nijmegen Medical Centre, Nijmegen Centre for Molecular Life Sciences, Nijmegen, The Netherlands
                [2 ]Department of Physiology, Radboud University Nijmegen Medical Centre, Nijmegen Centre for Molecular Life Sciences, Nijmegen, The Netherlands
                [3 ]Department of Laboratory Medicine, Laboratory of Genetic, Endocrine and Metabolic Diseases, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
                [4 ]Department of Nephrology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
                [5 ]Department of Pediatrics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
                [6 ]Department of Pediatrics, Catholic University Leuven, Leuven, Belgium
                University of Tokushima, Japan
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HAMM UFHE LPvdH JGH RM. Performed the experiments: HAMM UFHE. Analyzed the data: HAMM UFHE. Contributed reagents/materials/analysis tools: MJGW JFMW RAW. Wrote the paper: HAMM UFHE MJGW LPvdH JGH RM.

                Article
                PONE-D-13-06833
                10.1371/journal.pone.0071199
                3732267
                23936492
                e88bd1dd-9e57-4eef-af98-bfb6ba6bd712
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 11 February 2013
                : 28 June 2013
                Page count
                Pages: 9
                Funding
                This work was supported by the Dutch Kidney Foundation (grant number IK08.03; www.nierstichting.nl). M.J.G. Wilmer was supported by a grant from the Dutch government to the Netherlands Institute for Regenerative Medicine (NIRM, grant No. FES0908; www.nirm.nl) and J.G. Hoenderop was supported by an EURYI award from the European Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Blood Chemistry
                Metabolism
                Molecular Cell Biology
                Chemistry
                Analytical Chemistry
                Applied Chemistry
                Chemical Properties
                Nuclear Magnetic Resonance
                Medicine
                Diagnostic Medicine
                Clinical Laboratory Sciences
                Clinical Chemistry
                Pathology
                Clinical Pathology
                Clinical Chemistry
                General Pathology
                Biomarkers
                Nephrology
                Chronic Kidney Disease
                Dialysis

                Uncategorized
                Uncategorized

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