Literature DB >> 23369377

Potential of urinary metabolites for diagnosing multiple sclerosis.

Teklab Gebregiworgis, Chandirasegaran Massilamany, Arunakumar Gangaplara, Sivasubramani Thulasingam, Venkata Kolli, Mark T Werth, Eric D Dodds, David Steffen, Jay Reddy, Robert Powers.   

Abstract

A definitive diagnostic test for multiple sclerosis (MS) does not exist; instead physicians use a combination of medical history, magnetic resonance imaging, and cerebrospinal fluid analysis (CSF). Significant effort has been employed to identify biomarkers from CSF to facilitate MS diagnosis; however, none of the proposed biomarkers have been successful to date. Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Nevertheless, urinary metabolites have not been extensively explored as a source of biomarkers for MS. We demonstrate that urinary metabolites have significant promise for monitoring disease-progression, and response to treatment in MS patients. NMR analysis of urine permitted the identification of metabolites that differentiate experimental autoimmune encephalomyelitis (EAE)-mice (prototypic disease model for MS) from healthy and MS drug-treated EAE mice.

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Year:  2013        PMID: 23369377      PMCID: PMC3631445          DOI: 10.1021/cb300673e

Source DB:  PubMed          Journal:  ACS Chem Biol        ISSN: 1554-8929            Impact factor:   5.100


  34 in total

1.  3-Ureidopropionate contributes to the neuropathology of 3-ureidopropionase deficiency and severe propionic aciduria: a hypothesis.

Authors:  S Kölker; J G Okun; F Hörster; B Assmann; B Ahlemeyer; D Kohlmüller; S Exner-Camps; E Mayatepek; J Krieglstein; G F Hoffmann
Journal:  J Neurosci Res       Date:  2001-11-15       Impact factor: 4.164

2.  Using NMRView to visualize and analyze the NMR spectra of macromolecules.

Authors:  Bruce A Johnson
Journal:  Methods Mol Biol       Date:  2004

Review 3.  Fingolimod (FTY720): discovery and development of an oral drug to treat multiple sclerosis.

Authors:  Volker Brinkmann; Andreas Billich; Thomas Baumruker; Peter Heining; Robert Schmouder; Gordon Francis; Shreeram Aradhye; Pascale Burtin
Journal:  Nat Rev Drug Discov       Date:  2010-10-29       Impact factor: 84.694

4.  SOGGY: solvent-optimized double gradient spectroscopy for water suppression. A comparison with some existing techniques.

Authors:  Bao D Nguyen; Xi Meng; Kevin J Donovan; A J Shaka
Journal:  J Magn Reson       Date:  2006-11-27       Impact factor: 2.229

5.  NMRPipe: a multidimensional spectral processing system based on UNIX pipes.

Authors:  F Delaglio; S Grzesiek; G W Vuister; G Zhu; J Pfeifer; A Bax
Journal:  J Biomol NMR       Date:  1995-11       Impact factor: 2.835

Review 6.  The differential diagnosis of multiple sclerosis.

Authors:  Loren A Rolak; John O Fleming
Journal:  Neurologist       Date:  2007-03       Impact factor: 1.398

Review 7.  Proteomics-based technologies in the discovery of biomarkers for multiple sclerosis in the cerebrospinal fluid.

Authors:  A S T Lourenço; I Baldeiras; M Grãos; C B Duarte
Journal:  Curr Mol Med       Date:  2011-06       Impact factor: 2.222

8.  Basal ganglia lesions in a patient with 3-hydroxyisobutyric aciduria.

Authors:  Masayuki Sasaki; Naoto Yamada; Michio Fukumizu; Kenji Sugai
Journal:  Brain Dev       Date:  2006-05-19       Impact factor: 1.961

9.  Utilities for quantifying separation in PCA/PLS-DA scores plots.

Authors:  Bradley Worley; Steven Halouska; Robert Powers
Journal:  Anal Biochem       Date:  2012-10-15       Impact factor: 3.365

10.  Detection of autoreactive CD4 T cells using major histocompatibility complex class II dextramers.

Authors:  Chandirasegaran Massilamany; Bijaya Upadhyaya; Arunakumar Gangaplara; Charles Kuszynski; Jay Reddy
Journal:  BMC Immunol       Date:  2011-07-18       Impact factor: 3.615

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  10 in total

1.  A Urinary Metabolic Signature for Multiple Sclerosis and Neuromyelitis Optica.

Authors:  Teklab Gebregiworgis; Helle H Nielsen; Chandirasegaran Massilamany; Arunakumar Gangaplara; Jay Reddy; Zsolt Illes; Robert Powers
Journal:  J Proteome Res       Date:  2016-01-27       Impact factor: 4.466

2.  Urinary Urea, Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients.

Authors:  Hanaa B Atya; Sahar A Ali; Mohamed I Hegazy; Fathia Z El Sharkawi
Journal:  Indian J Clin Biochem       Date:  2017-05-22

3.  Metabolomics-based discovery of a metabolite that enhances oligodendrocyte maturation.

Authors:  Brittney A Beyer; Mingliang Fang; Benjamin Sadrian; J Rafael Montenegro-Burke; Warren C Plaisted; Bernard P C Kok; Enrique Saez; Toru Kondo; Gary Siuzdak; Luke L Lairson
Journal:  Nat Chem Biol       Date:  2017-11-13       Impact factor: 15.040

4.  Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis.

Authors:  J Singh; M Cerghet; L M Poisson; I Datta; K Labuzek; H Suhail; R Rattan; Shailendra Giri
Journal:  J Neuroimmune Pharmacol       Date:  2018-10-12       Impact factor: 4.147

5.  NMR Metabolomics Analysis of Parkinson's Disease.

Authors:  Shulei Lei; Robert Powers
Journal:  Curr Metabolomics       Date:  2013

6.  Peptidomics analysis reveals changes in small urinary peptides in patients with interstitial cystitis/bladder pain syndrome.

Authors:  Md Shadman Ridwan Abid; Haowen Qiu; Bridget A Tripp; Aline de Lima Leite; Heidi E Roth; Jiri Adamec; Robert Powers; James W Checco
Journal:  Sci Rep       Date:  2022-05-18       Impact factor: 4.996

7.  Untargeted Plasma Metabolomics Identifies Endogenous Metabolite with Drug-like Properties in Chronic Animal Model of Multiple Sclerosis.

Authors:  Laila M Poisson; Hamid Suhail; Jaspreet Singh; Indrani Datta; Aleksandar Denic; Krzysztof Labuzek; Md Nasrul Hoda; Ashray Shankar; Ashok Kumar; Mirela Cerghet; Stanton Elias; Robert P Mohney; Moses Rodriguez; Ramandeep Rattan; Ashutosh K Mangalam; Shailendra Giri
Journal:  J Biol Chem       Date:  2015-11-06       Impact factor: 5.157

8.  Profile of Circulatory Metabolites in a Relapsing-remitting Animal Model of Multiple Sclerosis using Global Metabolomics.

Authors:  Ak Mangalam; Lm Poisson; E Nemutlu; I Datta; A Denic; P Dzeja; M Rodriguez; R Rattan; S Giri
Journal:  J Clin Cell Immunol       Date:  2013-06-30

9.  Host and Microbial Tryptophan Metabolic Profiling in Multiple Sclerosis.

Authors:  Lorenzo Gaetani; Francesca Boscaro; Giuseppe Pieraccini; Paolo Calabresi; Luigina Romani; Massimiliano Di Filippo; Teresa Zelante
Journal:  Front Immunol       Date:  2020-02-18       Impact factor: 7.561

Review 10.  An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview.

Authors:  Insha Zahoor; Bin Rui; Junaid Khan; Indrani Datta; Shailendra Giri
Journal:  Cell Mol Life Sci       Date:  2021-01-15       Impact factor: 9.261

  10 in total

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