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Open Access Highly Accessed Research article

A gene signature for post-infectious chronic fatigue syndrome

John W Gow1, Suzanne Hagan1, Pawel Herzyk2, Celia Cannon3, Peter O Behan1 and Abhijit Chaudhuri4*

Author affiliations

1 Dept. of Biological and Biomedical Sciences, Glasgow Caledonian University, Glasgow, G4 0BA, UK

2 The Sir Henry Wellcome Functional Genomics Facility, Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK

3 Glasgow Veterinary School, University of Glasgow, Glasgow, UK

4 Essex Centre for Neurological Sciences, Oldchurch Hospital, Romford, RM7 0BE, UK

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Citation and License

BMC Medical Genomics 2009, 2:38  doi:10.1186/1755-8794-2-38

Published: 25 June 2009

Abstract

Background

At present, there are no clinically reliable disease markers for chronic fatigue syndrome. DNA chip microarray technology provides a method for examining the differential expression of mRNA from a large number of genes. Our hypothesis was that a gene expression signature, generated by microarray assays, could help identify genes which are dysregulated in patients with post-infectious CFS and so help identify biomarkers for the condition.

Methods

Human genome-wide Affymetrix GeneChip arrays (39,000 transcripts derived from 33,000 gene sequences) were used to compare the levels of gene expression in the peripheral blood mononuclear cells of male patients with post-infectious chronic fatigue (n = 8) and male healthy control subjects (n = 7).

Results

Patients and healthy subjects differed significantly in the level of expression of 366 genes. Analysis of the differentially expressed genes indicated functional implications in immune modulation, oxidative stress and apoptosis. Prototype biomarkers were identified on the basis of differential levels of gene expression and possible biological significance

Conclusion

Differential expression of key genes identified in this study offer an insight into the possible mechanism of chronic fatigue following infection. The representative biomarkers identified in this research appear promising as potential biomarkers for diagnosis and treatment.