New paper on gene expression in ME/CFS by Jonathan Kerr et al: PLoSone, 30 March 2011

April 14, 2011

From PLoSone, 30 March 2011.

Assessment of a 44 Gene Classifier for the Evaluation of Chronic Fatigue Syndrome from Peripheral Blood Mononuclear Cell Gene Expression
Daniel Frampton1, Jonathan Kerr2, Tim J. Harrison3, Paul Kellam1,4*

1 Department of Infection, Division of Infection and Immunity, University College London, London, United Kingdom, 2 Division of Clinical Sciences, St George's University of London, London, United Kingdom, 3 Department of Internal Medicine, University College London Medical School, London, United Kingdom, 4 The Wellcome Trust Genome Campus, The Wellcome Trust Sanger Institute, Cambridge, United Kingdom


Chronic fatigue syndrome (CFS) is a clinically defined illness estimated to affect millions of people worldwide causing significant morbidity and an annual cost of billions of dollars. Currently there are no laboratory-based diagnostic methods for CFS. However, differences in gene expression profiles between CFS patients and healthy persons have been reported in the literature. Using mRNA relative quantities for 44 previously identified reporter genes taken from a large dataset comprising both CFS patients and healthy volunteers, we derived a gene profile scoring metric to accurately classify CFS and healthy samples. This metric out-performed any of the reporter genes used individually as a classifier of CFS.

To determine whether the reporter genes were robust across populations, we applied this metric to classify a separate blind dataset of mRNA relative quantities from a new population of CFS patients and healthy persons with limited success. Although the metric was able to successfully classify roughly two-thirds of both CFS and healthy samples correctly, the level of misclassification was high. We conclude many of the previously identified reporter genes are study-specific and thus cannot be used as a broad CFS diagnostic.

Citation: Frampton D, Kerr J, Harrison TJ, Kellam P (2011) Assessment of a 44 Gene Classifier for the Evaluation of Chronic Fatigue Syndrome from Peripheral Blood Mononuclear Cell Gene Expression. PLoS ONE 6(3): e16872. doi:10.1371/journal.pone.0016872

Editor: Raya Khanin, Memorial Sloan Kettering Cancer Center, United States of America

Received: July 28, 2010; Accepted: January 7, 2011; Published: March 30, 2011

Copyright: © 2011 Frampton et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was funded by a research grant from the Chronic Fatigue Syndrome Research Foundation ( The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

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2 thoughts on “New paper on gene expression in ME/CFS by Jonathan Kerr et al: PLoSone, 30 March 2011”

  1. So to summarise then:

    Genes do not carry sufficient markers to allow identification of CFS.

    But they carry some markers, just not enough markers to validate this as a diagnoctic test.

    I don’t understand. How can genes in a study show distinguishable differences between patients ‘with CFS’ and those without, and yet not be enough to be used diagnostically?

    They found something, but it wasn’t enough?! Sounds daft to me.

  2. What a waste of time and money. The cohort studied was one previously used for another Kerr study (1), selected by the CDC diagnostic criteria – Reeves 2005, I imagine, but even Fukuda misdiagnoses because of the lesser importance placed on PEM as opposed to the Canadian Criteria. When will people realize you cannot study oranges by looking at apples?

    (1)Kerr JR, Petty R, Burke B, Gough J, Fear D, et al. (2008) Gene expression subtypes in patients with chronic fatigue syndrome/myalgic encephalomyelitis. J Inf Dis 197: 1171–1184.

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