Literature DB >> 14625084

Quantitative and qualitative changes in gene expression patterns characterize the activity of plaques in multiple sclerosis.

Lotti Tajouri1, Albert S Mellick, Kevin J Ashton, Anthony E G Tannenberg, Rashed M Nagra, Wallace W Tourtellotte, Lyn R Griffiths.   

Abstract

Multiple sclerosis (MS) is a complex autoimmune disorder of the CNS with both genetic and environmental contributing factors. Clinical symptoms are broadly characterized by initial onset, and progressive debilitating neurological impairment. In this study, RNA from MS chronic active and MS acute lesions was extracted, and compared with patient matched normal white matter by fluorescent cDNA microarray hybridization analysis. This resulted in the identification of 139 genes that were differentially regulated in MS plaque tissue compared to normal tissue. Of these, 69 genes showed a common pattern of expression in the chronic active and acute plaque tissues investigated (Pvalue<0.0001, rho=0.73, by Spearman's rho analysis); while 70 transcripts were uniquely differentially expressed (> or = 1.5-fold) in either acute or chronic active tissues. These results included known markers of MS such as the myelin basic protein (MBP) and glutathione S-transferase (GST) M1, nerve growth factors, such as nerve injury-induced protein 1 (NINJ1), X-ray and excision DNA repair factors (XRCC9 and ERCC5) and X-linked genes such as the ribosomal protein, RPS4X. Primers were then designed for seven array-selected genes, including transferrin (TF), superoxide dismutase 1 (SOD1), glutathione peroxidase 1 (GPX1), GSTP1, crystallin, alpha-B (CRYAB), phosphomannomutase 1 (PMM1) and tubulin beta-5 (TBB5), and real time quantitative (Q)-PCR analysis was performed. The results of comparative Q-PCR analysis correlated significantly with those obtained by array analysis (r=0.75, Pvalue<0.01, by Pearson's bivariate correlation). Both chronic active and acute plaques shared the majority of factors identified suggesting that quantitative, rather than gross qualitative differences in gene expression pattern may define the progression from acute to chronic active plaques in MS.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 14625084     DOI: 10.1016/j.molbrainres.2003.09.008

Source DB:  PubMed          Journal:  Brain Res Mol Brain Res        ISSN: 0169-328X


  33 in total

Review 1.  Genomics and proteomics: role in the management of multiple sclerosis.

Authors:  Ludwig Kappos; Lutz Achtnichts; Frank Dahlke; Jens Kuhle; Y Naegelin; Rupert Sandbrink; Raija L P Lindberg
Journal:  J Neurol       Date:  2005-09       Impact factor: 4.849

2.  An inexpensive gel electrophoresis-based polymerase chain reaction method for quantifying mRNA levels.

Authors:  William D Bradford; Laty Cahoon; Sara R Freel; Laura L Mays Hoopes; Todd T Eckdahl
Journal:  Cell Biol Educ       Date:  2005

3.  Identification of differentially expressed proteins in experimental autoimmune encephalomyelitis (EAE) by proteomic analysis of the spinal cord.

Authors:  Tong Liu; K Christian Donahue; Jun Hu; Michael P Kurnellas; Jennifer E Grant; Hong Li; Stella Elkabes
Journal:  J Proteome Res       Date:  2007-06-16       Impact factor: 4.466

4.  Crystallins and neuroinflammation: The glial side of the story.

Authors:  Jennifer E Dulle; Patrice E Fort
Journal:  Biochim Biophys Acta       Date:  2015-06-03

5.  The GSTP1 gene variant rs1695 is not associated with an increased risk of multiple sclerosis.

Authors:  José A G Agúndez; Elena García-Martín; Carmen Martínez; Julián Benito-León; Jorge Millán-Pascual; María Díaz-Sánchez; Patricia Calleja; Diana Pisa; Laura Turpín-Fenoll; Hortensia Alonso-Navarro; Lucía Ayuso-Peralta; Dolores Torrecillas; Esteban García-Albea; José Francisco Plaza-Nieto; Félix Javier Jiménez-Jiménez
Journal:  Cell Mol Immunol       Date:  2014-12-22       Impact factor: 11.530

6.  Cerebrospinal fluid and plasma oxidative stress biomarkers in different clinical phenotypes of neuroinflammatory acute attacks. Conceptual accession: from fundamental to clinic.

Authors:  Srdjan Ljubisavljevic; Ivana Stojanovic; Slobodan Vojinovic; Dragan Stojanov; Svetlana Stojanovic; Gordana Kocic; Dejan Savic; Tatjana Cvetkovic; Dusica Pavlovic
Journal:  Cell Mol Neurobiol       Date:  2013-05-16       Impact factor: 5.046

7.  Variation within DNA repair pathway genes and risk of multiple sclerosis.

Authors:  Farren B S Briggs; Benjamin A Goldstein; Jacob L McCauley; Rebecca L Zuvich; Philip L De Jager; John D Rioux; Adrian J Ivinson; Alastair Compston; David A Hafler; Stephen L Hauser; Jorge R Oksenberg; Stephen J Sawcer; Margaret A Pericak-Vance; Jonathan L Haines; Lisa F Barcellos
Journal:  Am J Epidemiol       Date:  2010-06-03       Impact factor: 4.897

8.  A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis.

Authors:  Carlos Riveros; Drew Mellor; Kaushal S Gandhi; Fiona C McKay; Mathew B Cox; Regina Berretta; S Yahya Vaezpour; Mario Inostroza-Ponta; Simon A Broadley; Robert N Heard; Stephen Vucic; Graeme J Stewart; David W Williams; Rodney J Scott; Jeanette Lechner-Scott; David R Booth; Pablo Moscato
Journal:  PLoS One       Date:  2010-12-01       Impact factor: 3.240

9.  Discovery of novel disease-specific and membrane-associated candidate markers in a mouse model of multiple sclerosis.

Authors:  Laura F Dagley; Nathan P Croft; Ruth Isserlin; Jonathan B Olsen; Vincent Fong; Andrew Emili; Anthony W Purcell
Journal:  Mol Cell Proteomics       Date:  2013-12-20       Impact factor: 5.911

10.  Differential effects of Th1, monocyte/macrophage and Th2 cytokine mixtures on early gene expression for molecules associated with metabolism, signaling and regulation in central nervous system mixed glial cell cultures.

Authors:  Robert P Lisak; Joyce A Benjamins; Beverly Bealmear; Liljana Nedelkoska; Diane Studzinski; Ernest Retland; Bin Yao; Susan Land
Journal:  J Neuroinflammation       Date:  2009-01-21       Impact factor: 8.322

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.