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      Metabolomics insights into activated redox signaling and lipid metabolism dysfunction in chronic kidney disease progression

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          Abstract

          Early detection is critical in prevention and treatment of kidney disease. However currently clinical laboratory and histopathological tests do not provide region-specific and accurate biomarkers for early detection of kidney disease. The present study was conducted to identify sensitive biomarkers for early detection and progression of tubulo-interstitial nephropathy in aristolochic acid I-induced rats at weeks 4, 8 and 12. Biomarkers were validated using aristolochic acid nephropathy (AAN) rats at week 24, adenine-induced chronic kidney disease (CKD) rats and CKD patients. Compared with control rats, AAN rats showed anemia, increased serum urea and creatinine, progressive renal interstitial fibrosis, activation of nuclear factor-kappa B, and up-regulation of pro-inflammatory, pro-oxidant, and pro-fibrotic proteins at weeks 8 and 12. However, no significant difference was found at week 4. Metabolomics identified 12-ketodeoxycholic acid, taurochenodesoxycholic acid, LPC(15:0) and docosahexaenoic acid as biomarkers for early detection of tubulo-interstitial nephropathy. With prolonging aristolochic acid I exposure, LPE(20:2), cholic acid, chenodeoxycholic acid and LPC(17:0) were identified as biomarkers for progression from early to advanced AAN and lysoPE(22:5), indoxyl sulfate, uric acid and creatinine as biomarkers of advanced AAN. These biomarkers were reversed by treatment of irbesartan and ergone in AAN rats at week 24 and adenine-induced CKD rats. In addition, these biomarkers were also reversed by irbesartan treatment in CKD patients.

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          Highlights

          • •

            Tubulo-interstitial nephropathy (TIN) is a common cause of chronic kidney disease.

          • •

            Plasma biomarker discovery and validation was performed by UPLC-based metabolomics.

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            CKD progression associated with activated redox signaling and lipid dysfunction.

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            TIN was associated with abnormal amino acids, purine and phospholipid metabolisms.

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          Expansion of Urease- and Uricase-Containing, Indole- and p-Cresol-Forming and Contraction of Short-Chain Fatty Acid-Producing Intestinal Microbiota in ESRD

          Jakk Wong, Yvette Piceno, Todd Z. DeSantis … (2014)
          Background: Intestinal microbiome constitutes a symbiotic ecosystem that is essential for health, and changes in its composition/function cause various illnesses. Biochemical milieu shapes the structure and function of the microbiome. Recently, we found marked differences in the abundance of numerous bacterial taxa between ESRD and healthy individuals. Influx of urea and uric acid and dietary restriction of fruits and vegetables to prevent hyperkalemia alter ESRD patients' intestinal milieu. We hypothesized that relative abundances of bacteria possessing urease, uricase, and p-cresol- and indole-producing enzymes is increased, while abundance of bacteria containing enzymes converting dietary fiber to short-chain fatty acids (SCFA) is reduced in ESRD. Methods: Reference sets of bacteria containing genes of interest were compiled to family, and sets of intestinal bacterial families showing differential abundances between 12 healthy and 24 ESRD individuals enrolled in our original study were compiled. Overlap between sets was assessed using hypergeometric distribution tests. Results: Among 19 microbial families that were dominant in ESRD patients, 12 possessed urease, 5 possessed uricase, and 4 possessed indole and p-cresol-forming enzymes. Among 4 microbial families that were diminished in ESRD patients, 2 possessed butyrate-forming enzymes. Probabilities of these overlapping distributions were <0.05. Conclusions: ESRD patients exhibited significant expansion of bacterial families possessing urease, uricase, and indole and p-cresol forming enzymes, and contraction of families possessing butyrate-forming enzymes. Given the deleterious effects of indoxyl sulfate, p-cresol sulfate, and urea-derived ammonia, and beneficial actions of SCFA, these changes in intestinal microbial metabolism contribute to uremic toxicity and inflammation.
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            Aristolochic acid nephropathy: a worldwide problem.

            Frédéric Debelle, Jean-Louis Vanherweghem, Joëlle Nortier (2008)
            Aristolochic acid nephropathy (AAN), a progressive renal interstitial fibrosis frequently associated with urothelial malignancies, was initially reported in a Belgian cohort of more than 100 patients after the intake of slimming pills containing a Chinese herb, Aristolochia fangchi. Although botanicals known or suspected to contain aristolochic acid (AA) were no longer permitted in many countries, several AAN cases were regularly observed all around the world. The incidence of AAN is probably much higher than initially thought, especially in Asia and the Balkans. In Asian countries, where traditional medicines are very popular, the complexity of the pharmacopoeia represents a high risk for AAN because of the frequent substitution of the botanical products by AA-containing herbs. In the Balkan regions, the exposure to AA found in flour obtained from wheat contaminated with seeds of Aristolochia clematitis could be responsible for the so-called Balkan-endemic nephropathy. Finally, despite the Food and Drug Administration's warnings concerning the safety of botanical remedies containing AA, these herbs are still sold via the Internet.
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              Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data.

              Alla Karnovsky, Terry Weymouth, Tim Hull … (2012)
              Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype-phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and molecular interactions. We describe a new, substantially redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks. Metscape 2 uses an internal relational database that integrates data from KEGG and EHMN databases. The new version of the tool allows users to identify enriched pathways from expression profiling data, build and analyze the networks of genes and metabolites, and visualize changes in the gene/metabolite data. We demonstrate the applications of Metscape to annotate molecular pathways for human and mouse metabolites implicated in the pathogenesis of sepsis-induced acute lung injury, for the analysis of gene expression and metabolite data from pancreatic ductal adenocarcinoma, and for identification of the candidate metabolites involved in cancer and inflammation. Metscape is part of the National Institutes of Health-supported National Center for Integrative Biomedical Informatics (NCIBI) suite of tools, freely available at http://metscape.ncibi.org. It can be downloaded from http://cytoscape.org or installed via Cytoscape plugin manager. metscape-help@umich.edu; akarnovs@umich.edu Supplementary data are available at Bioinformatics online.
              Article 0 comments Cited 180 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Ying-Yong Zhao
                Journal
                Journal ID (nlm-ta): Redox Biol
                Journal ID (iso-abbrev): Redox Biol
                Title: Redox Biology
                Publisher: Elsevier
                ISSN (Electronic): 2213-2317
                Publication date PMC-release: 28 September 2016
                Publication date Collection: December 2016
                Publication date (Electronic): 28 September 2016
                Volume: 10
                Pages: 168-178
                Affiliations
                [a ]Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, The College of Life Sciences, Northwest University, No. 229 Taibai North Road, Xi’an, Shaanxi 710069, China
                [b ]Division of Nephrology and Hypertension, School of Medicine, University of California Irvine, MedSci 1, C352, UCI Campus, Irvine, CA 92897, USA
                [c ]Research Center of TCM Processing Technology, Zhejiang Chinese Medical University, No. 548 Binwen Road, Hangzhou, Zhejiang 310053, China
                [d ]National Center for Natural Products Research, Department of BioMolecular Sciences, School of Pharmacy, University of Mississippi, Oxford, MS 38677, USA
                [e ]Department of Nephrology, the Affiliated Hospital of Shaanxi Institute of Traditional Chinese Medicine, No. 2 Xihuamen, Xi’an, Shaanxi 710003, China
                [f ]Solution Centre, Waters Technologies (Shanghai) Ltd., No. 1000 Jinhai Road, Shanghai 201203, PR China
                Author notes
                [1]

                Hua Chen and Gang Cao are co-first authors.

                Article
                Publisher ID: S2213-2317(16)30071-4
                DOI: 10.1016/j.redox.2016.09.014
                PMC ID: 5066525
                PubMed ID: 27750081
                SO-VID: 3ebc8a61-4be6-40c5-903b-7a0aeec15e11
                Copyright © © 2016 The Authors
                License:

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Date received : 13 July 2016
                Date revision received : 21 September 2016
                Date accepted : 26 September 2016
                Categories
                Subject: Research Paper

                Keywords: chronic kidney disease,metabolomics,inflammation,renal fibrosis,lipid metabolism,biomarker
                Data availability:
                Keywords: chronic kidney disease, metabolomics, inflammation, renal fibrosis, lipid metabolism, biomarker

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