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Gene expression signatures: biomarkers toward diagnosing multiple sclerosis
Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis include magnetic resonance imaging and detection of immunologic abnormalities in cerebrospinal fluid. We determine...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3291793/ https://www.ncbi.nlm.nih.gov/pubmed/21938015 http://dx.doi.org/10.1038/gene.2011.66 |
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author | Tossberg, John T. Crooke, Philip S. Henderson, Melodie A. Sriram, Subramaniam Mrelashvili, Davit Chitnis, Shilpa Polman, Chris Vosslamber, Saskia Verweij, Cor L. Olsen, Nancy J. Aune, Thomas M. |
author_facet | Tossberg, John T. Crooke, Philip S. Henderson, Melodie A. Sriram, Subramaniam Mrelashvili, Davit Chitnis, Shilpa Polman, Chris Vosslamber, Saskia Verweij, Cor L. Olsen, Nancy J. Aune, Thomas M. |
author_sort | Tossberg, John T. |
collection | PubMed |
description | Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis include magnetic resonance imaging and detection of immunologic abnormalities in cerebrospinal fluid. We determined if gene expression differences in blood discriminated MS subjects from comparator groups and identified panels of ratios that performed with varying degrees of accuracy depending upon complexity of comparator groups. High levels of overall accuracy were achieved by comparing MS to homogeneous comparator groups. Overall accuracy was compromised when MS was compared to a heterogeneous comparator group. Results, validated in independent cohorts, indicate that gene expression differences in blood accurately exclude or include a diagnosis of MS and suggest these approaches may provide clinically useful prediction of MS. |
format | Online Article Text |
id | pubmed-3291793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
record_format | MEDLINE/PubMed |
spelling | pubmed-32917932012-08-01 Gene expression signatures: biomarkers toward diagnosing multiple sclerosis Tossberg, John T. Crooke, Philip S. Henderson, Melodie A. Sriram, Subramaniam Mrelashvili, Davit Chitnis, Shilpa Polman, Chris Vosslamber, Saskia Verweij, Cor L. Olsen, Nancy J. Aune, Thomas M. Genes Immun Article Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis include magnetic resonance imaging and detection of immunologic abnormalities in cerebrospinal fluid. We determined if gene expression differences in blood discriminated MS subjects from comparator groups and identified panels of ratios that performed with varying degrees of accuracy depending upon complexity of comparator groups. High levels of overall accuracy were achieved by comparing MS to homogeneous comparator groups. Overall accuracy was compromised when MS was compared to a heterogeneous comparator group. Results, validated in independent cohorts, indicate that gene expression differences in blood accurately exclude or include a diagnosis of MS and suggest these approaches may provide clinically useful prediction of MS. 2011-09-22 2012-02 /pmc/articles/PMC3291793/ /pubmed/21938015 http://dx.doi.org/10.1038/gene.2011.66 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Tossberg, John T. Crooke, Philip S. Henderson, Melodie A. Sriram, Subramaniam Mrelashvili, Davit Chitnis, Shilpa Polman, Chris Vosslamber, Saskia Verweij, Cor L. Olsen, Nancy J. Aune, Thomas M. Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title | Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title_full | Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title_fullStr | Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title_full_unstemmed | Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title_short | Gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
title_sort | gene expression signatures: biomarkers toward diagnosing multiple sclerosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3291793/ https://www.ncbi.nlm.nih.gov/pubmed/21938015 http://dx.doi.org/10.1038/gene.2011.66 |
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