Literature DB >> 19879655

Serum anti-GAGA4 IgM antibodies differentiate relapsing remitting and secondary progressive multiple sclerosis from primary progressive multiple sclerosis and other neurological diseases.

Johannes Brettschneider1, Troy D Jaskowski, Hayrettin Tumani, Sana Abdul, Dee Husebye, Haniah Seraj, Harry R Hill, Ella Fire, Larissa Spector, Jennifer Yarden, Nir Dotan, John W Rose.   

Abstract

The serum level of IgM antibodies against Glc(alpha1,4)Glc(alpha) (GAGA4) is higher in relapsing remitting multiple sclerosis (RRMS) compared to other neurological disease (OND) patients and healthy controls (HC). Detecting the level of anti-GAGA4 antibody by enzyme immunoassay and total IgM, we confirmed that anti-GAGA4 IgM can differentiate RRMS from OND patients and HC. Moreover, secondary progressive MS (SPMS) and RRMS patients have similar levels of anti-GAGA4 demonstrating the biomarker's presence throughout the disease. Interestingly, the anti-GAGA4 assay may also differentiate between primary progressive MS (PPMS) and RRMS/SPMS patients, since nearly all PPMS patients were negative for the assay.

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Year:  2009        PMID: 19879655     DOI: 10.1016/j.jneuroim.2009.07.017

Source DB:  PubMed          Journal:  J Neuroimmunol        ISSN: 0165-5728            Impact factor:   3.478


  9 in total

Review 1.  Diagnostic Criteria, Classification and Treatment Goals in Multiple Sclerosis: The Chronicles of Time and Space.

Authors:  Achilles Ntranos; Fred Lublin
Journal:  Curr Neurol Neurosci Rep       Date:  2016-10       Impact factor: 5.081

2.  Alpha actinin is specifically recognized by Multiple Sclerosis autoantibodies isolated using an N-glucosylated peptide epitope.

Authors:  Shashank Pandey; Ilaria Dioni; Duccio Lambardi; Feliciana Real-Fernandez; Elisa Peroni; Giulia Pacini; Francesco Lolli; Roberta Seraglia; Anna Maria Papini; Paolo Rovero
Journal:  Mol Cell Proteomics       Date:  2012-11-08       Impact factor: 5.911

3.  Uncovering cryptic glycan markers in multiple sclerosis (MS) and experimental autoimmune encephalomyelitis (EAE).

Authors:  Denong Wang; Roopa Bhat; Raymond A Sobel; Wei Huang; Lai-Xi Wang; Tomas Olsson; Lawrence Steinman
Journal:  Drug Dev Res       Date:  2014-03-11       Impact factor: 4.360

4.  Predictive nature of IgM anti-α-glucose serum biomarker for relapse activity and EDSS progression in CIS patients: a BENEFIT study analysis.

Authors:  M S Freedman; C Metzig; L Kappos; C H Polman; G Edan; H-P Hartung; D H Miller; X Montalban; J Yarden; L Spector; E Fire; N Dotan; S Schwenke; V Lanius; R Sandbrink; C Pohl
Journal:  Mult Scler       Date:  2011-12-19       Impact factor: 6.312

5.  Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria.

Authors:  Chris H Polman; Stephen C Reingold; Brenda Banwell; Michel Clanet; Jeffrey A Cohen; Massimo Filippi; Kazuo Fujihara; Eva Havrdova; Michael Hutchinson; Ludwig Kappos; Fred D Lublin; Xavier Montalban; Paul O'Connor; Magnhild Sandberg-Wollheim; Alan J Thompson; Emmanuelle Waubant; Brian Weinshenker; Jerry S Wolinsky
Journal:  Ann Neurol       Date:  2011-02       Impact factor: 10.422

6.  Comparison of printed glycan array, suspension array and ELISA in the detection of human anti-glycan antibodies.

Authors:  Tatiana Pochechueva; Francis Jacob; Darlene R Goldstein; Margaret E Huflejt; Alexander Chinarev; Rosemarie Caduff; Daniel Fink; Neville Hacker; Nicolai V Bovin; Viola Heinzelmann-Schwarz
Journal:  Glycoconj J       Date:  2011-09-23       Impact factor: 2.916

Review 7.  Blood Biomarkers for Traumatic Brain Injury: A Quantitative Assessment of Diagnostic and Prognostic Accuracy.

Authors:  Zoe S Gan; Sherman C Stein; Randel Swanson; Shaobo Guan; Lizette Garcia; Devanshi Mehta; Douglas H Smith
Journal:  Front Neurol       Date:  2019-04-26       Impact factor: 4.003

8.  Evaluation of anti α-d-Glcp-(1→4)-α-d-Glcp (GAGA4) IgM antibodies as a biomarker for multiple sclerosis.

Authors:  Chriselle D Braganza; Kristiana T Santoso; Emma M Dangerfield; Anne C La Flamme; Mattie S M Timmer; Bridget L Stocker
Journal:  RSC Adv       Date:  2018-08-06       Impact factor: 4.036

9.  Serum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.

Authors:  Georgina Arrambide; Carmen Espejo; Jennifer Yarden; Ella Fire; Larissa Spector; Nir Dotan; Avinoam Dukler; Alex Rovira; Xavier Montalban; Mar Tintore
Journal:  PLoS One       Date:  2013-03-28       Impact factor: 3.240

  9 in total

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