Literature DB >> 19944761

Gene expression profiling in multiple sclerosis: a disease of the central nervous system, but with relapses triggered in the periphery?

Boel Brynedal1, Mohsen Khademi, Erik Wallström, Jan Hillert, Tomas Olsson, Kristina Duvefelt.   

Abstract

The aetiology of multiple sclerosis (MS), an autoimmune demyelinating disease of the central nervous system (CNS), includes both genetic and environmental factors, but the pathogenesis is still incompletely known. We performed gene expression profiling on paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from 26 MS patients without immunomodulatory treatment, sampled in relapse or remission, and 18 controls using Human Genome U133 plus 2.0 arrays (Affymetrix). In the CSF, 939 probe sets detected differential expression in MS patients compared to controls, but none in PBMCs, confirming that CSF cells might mirror the disease processes. The regulation of selected transcripts in CSF of MS patients was confirmed by quantitative PCR. Unexpectedly however, when comparing MS patients in relapse to those in remission, 266 probe sets detected differential expression in PBMCs, but not in CSF cells, indicating the importance of events outside of the CNS in the triggering of relapse. 2009 Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 19944761     DOI: 10.1016/j.nbd.2009.11.014

Source DB:  PubMed          Journal:  Neurobiol Dis        ISSN: 0969-9961            Impact factor:   5.996


  28 in total

1.  CCAAT/enhancer binding protein-δ expression by dendritic cells regulates CNS autoimmune inflammatory disease.

Authors:  Vicky W W Tsai; Mohammad G Mohammad; Ornella Tolhurst; Samuel N Breit; Paul E Sawchenko; David A Brown
Journal:  J Neurosci       Date:  2011-11-30       Impact factor: 6.167

2.  Assessment and Treatment Strategies for a Multiple Sclerosis Relapse.

Authors:  Cynthia Wang; America Ruiz; Yang Mao-Draayer
Journal:  J Immunol Clin Res       Date:  2016-12-07

Review 3.  Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future.

Authors:  Itay Raphael; Johanna Webb; Olaf Stuve; William Haskins; Thomas Forsthuber
Journal:  Expert Rev Clin Immunol       Date:  2014-12-18       Impact factor: 4.473

4.  Blood RNA profiling in a large cohort of multiple sclerosis patients and healthy controls.

Authors:  Dorothee Nickles; Hsuan P Chen; Michael M Li; Pouya Khankhanian; Lohith Madireddy; Stacy J Caillier; Adam Santaniello; Bruce A C Cree; Daniel Pelletier; Stephen L Hauser; Jorge R Oksenberg; Sergio E Baranzini
Journal:  Hum Mol Genet       Date:  2013-06-06       Impact factor: 6.150

5.  Gene expression changes in multiple sclerosis relapse suggest activation of T and non-T cells.

Authors:  J William Lindsey; Sandeep K Agarwal; Filemon K Tan
Journal:  Mol Med       Date:  2010-09-17       Impact factor: 6.354

6.  Inhibition of hyaluronan synthesis protects against central nervous system (CNS) autoimmunity and increases CXCL12 expression in the inflamed CNS.

Authors:  Andre Michael Mueller; Bo Hyung Yoon; Saud Ahmed Sadiq
Journal:  J Biol Chem       Date:  2014-06-27       Impact factor: 5.157

7.  Identification of common key genes and pathways between type 1 diabetes and multiple sclerosis using transcriptome and interactome analysis.

Authors:  Nahid Safari-Alighiarloo; Mohammad Taghizadeh; Seyyed Mohammad Tabatabaei; Saeed Namaki; Mostafa Rezaei-Tavirani
Journal:  Endocrine       Date:  2020-01-07       Impact factor: 3.633

8.  Systematic review of genome-wide expression studies in multiple sclerosis.

Authors:  A K Kemppinen; J Kaprio; A Palotie; J Saarela
Journal:  BMJ Open       Date:  2011-07-18       Impact factor: 2.692

9.  Suppressed RNA-polymerase 1 pathway is associated with benign multiple sclerosis.

Authors:  Anat Achiron; Anna Feldman; David Magalashvili; Mark Dolev; Michael Gurevich
Journal:  PLoS One       Date:  2012-10-12       Impact factor: 3.240

10.  Random generalized linear model: a highly accurate and interpretable ensemble predictor.

Authors:  Lin Song; Peter Langfelder; Steve Horvath
Journal:  BMC Bioinformatics       Date:  2013-01-16       Impact factor: 3.169

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