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Neurology. 2002 Oct 22;59(8):1170-82.

Molecular profiles of inflammatory myopathies.

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  • 1Department of Neurology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA. sagreenberg@partners.org

Abstract

OBJECTIVE:

To describe the use of large-scale gene expression profiles to distinguish broad categories of myopathy and subtypes of inflammatory myopathies (IM) and to provide insight into the pathogenesis of inclusion body myositis (IBM), polymyositis, and dermatomyositis.

METHODS:

Using Affymetrix GeneChip microarrays, the authors measured the simultaneous expression of approximately 10,000 genes in muscle specimens from 45 patients in four major disease categories (dystrophy, congenital myopathy, inflammatory myopathy, and normal). The authors separately analyzed gene expression in 14 patients limited to the three major subtypes of IM. Bioinformatics techniques were used to classify specimens with similar expression profiles based on global patterns of gene expression and to identify genes with significant differential gene expression compared with normal.

RESULTS:

Ten of 11 patients with IM, all normals and nemaline myopathies, and 10 of 12 patients with Duchenne muscular dystrophy were correctly classified by this approach. The various subtypes of inflammatory myopathies have distinct gene expression signatures. Specific sets of immune-related genes allow for molecular classification of patients with IBM, polymyositis, and dermatomyositis. Analysis of differential gene expression identifies as relevant to disease pathogenesis previously reported cytokines, major histocompatibility complex class I and II molecules, granzymes, and adhesion molecules, as well as newly identified members of these categories. Increased expression of actin cytoskeleton genes is also identified.

CONCLUSIONS:

The molecular profiles of muscle tissue in patients with inflammatory myopathies are distinct and represent molecular signatures from which diagnostic insight may follow. Large numbers of differentially expressed genes are rapidly identified.

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PMID:
12391344
[PubMed - indexed for MEDLINE]
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