Gene-expression signatures

Biomarkers toward diagnosing multiple sclerosis

J. T. Tossberg, P. S. Crooke, M. A. Henderson, S. Sriram, D. Mrelashvili, S. Chitnis, C. Polman, S. Vosslamber, C. L. Verweij, N. J. Olsen, T. M. Aune

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis (MS) include magnetic resonance imaging and detection of immunological abnormalities in cerebrospinal fluid. We determined whether 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 with homogeneous comparator groups. Overall accuracy was compromised when MS was compared with 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 that these approaches may provide clinically useful prediction of MS.

Original languageEnglish (US)
Pages (from-to)146-154
Number of pages9
JournalGenes and Immunity
Volume13
Issue number2
DOIs
StatePublished - Feb 2012

Fingerprint

Transcriptome
Multiple Sclerosis
Biomarkers
Gene Expression
Cerebrospinal Fluid
Magnetic Resonance Imaging

Keywords

  • diagnosis
  • genomics
  • multiple sclerosis

ASJC Scopus subject areas

  • Genetics(clinical)
  • Immunology
  • Genetics

Cite this

Tossberg, J. T., Crooke, P. S., Henderson, M. A., Sriram, S., Mrelashvili, D., Chitnis, S., ... Aune, T. M. (2012). Gene-expression signatures: Biomarkers toward diagnosing multiple sclerosis. Genes and Immunity, 13(2), 146-154. https://doi.org/10.1038/gene.2011.66

Gene-expression signatures : Biomarkers toward diagnosing multiple sclerosis. / Tossberg, J. T.; Crooke, P. S.; Henderson, M. A.; Sriram, S.; Mrelashvili, D.; Chitnis, S.; Polman, C.; Vosslamber, S.; Verweij, C. L.; Olsen, N. J.; Aune, T. M.

In: Genes and Immunity, Vol. 13, No. 2, 02.2012, p. 146-154.

Research output: Contribution to journalArticle

Tossberg, JT, Crooke, PS, Henderson, MA, Sriram, S, Mrelashvili, D, Chitnis, S, Polman, C, Vosslamber, S, Verweij, CL, Olsen, NJ & Aune, TM 2012, 'Gene-expression signatures: Biomarkers toward diagnosing multiple sclerosis', Genes and Immunity, vol. 13, no. 2, pp. 146-154. https://doi.org/10.1038/gene.2011.66
Tossberg JT, Crooke PS, Henderson MA, Sriram S, Mrelashvili D, Chitnis S et al. Gene-expression signatures: Biomarkers toward diagnosing multiple sclerosis. Genes and Immunity. 2012 Feb;13(2):146-154. https://doi.org/10.1038/gene.2011.66
Tossberg, J. T. ; Crooke, P. S. ; Henderson, M. A. ; Sriram, S. ; Mrelashvili, D. ; Chitnis, S. ; Polman, C. ; Vosslamber, S. ; Verweij, C. L. ; Olsen, N. J. ; Aune, T. M. / Gene-expression signatures : Biomarkers toward diagnosing multiple sclerosis. In: Genes and Immunity. 2012 ; Vol. 13, No. 2. pp. 146-154.
@article{54481c613aef45bea712882fddc5eb0f,
title = "Gene-expression signatures: Biomarkers toward diagnosing multiple sclerosis",
abstract = "Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis (MS) include magnetic resonance imaging and detection of immunological abnormalities in cerebrospinal fluid. We determined whether 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 with homogeneous comparator groups. Overall accuracy was compromised when MS was compared with 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 that these approaches may provide clinically useful prediction of MS.",
keywords = "diagnosis, genomics, multiple sclerosis",
author = "Tossberg, {J. T.} and Crooke, {P. S.} and Henderson, {M. A.} and S. Sriram and D. Mrelashvili and S. Chitnis and C. Polman and S. Vosslamber and Verweij, {C. L.} and Olsen, {N. J.} and Aune, {T. M.}",
year = "2012",
month = "2",
doi = "10.1038/gene.2011.66",
language = "English (US)",
volume = "13",
pages = "146--154",
journal = "Genes and Immunity",
issn = "1466-4879",
publisher = "Nature Publishing Group",
number = "2",

}

TY - JOUR

T1 - Gene-expression signatures

T2 - Biomarkers toward diagnosing multiple sclerosis

AU - Tossberg, J. T.

AU - Crooke, P. S.

AU - Henderson, M. A.

AU - Sriram, S.

AU - Mrelashvili, D.

AU - Chitnis, S.

AU - Polman, C.

AU - Vosslamber, S.

AU - Verweij, C. L.

AU - Olsen, N. J.

AU - Aune, T. M.

PY - 2012/2

Y1 - 2012/2

N2 - Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis (MS) include magnetic resonance imaging and detection of immunological abnormalities in cerebrospinal fluid. We determined whether 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 with homogeneous comparator groups. Overall accuracy was compromised when MS was compared with 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 that these approaches may provide clinically useful prediction of MS.

AB - Identification of biomarkers contributing to disease diagnosis, classification or prognosis could be of considerable utility. For example, primary methods to diagnose multiple sclerosis (MS) include magnetic resonance imaging and detection of immunological abnormalities in cerebrospinal fluid. We determined whether 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 with homogeneous comparator groups. Overall accuracy was compromised when MS was compared with 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 that these approaches may provide clinically useful prediction of MS.

KW - diagnosis

KW - genomics

KW - multiple sclerosis

UR - http://www.scopus.com/inward/record.url?scp=84857790320&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857790320&partnerID=8YFLogxK

U2 - 10.1038/gene.2011.66

DO - 10.1038/gene.2011.66

M3 - Article

VL - 13

SP - 146

EP - 154

JO - Genes and Immunity

JF - Genes and Immunity

SN - 1466-4879

IS - 2

ER -