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This Article Full Text Full Text (PDF) All Versions of this Article: jcp.2007.053553v1 61/6/730    most recent Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this link to a friend Similar articles in this journal Similar articles in PubMed Add article to my folders Download to citation manager Request Permissions Google Scholar Articles by Kerr, J R Articles by Nutt, D J PubMed PubMed Citation Articles by Kerr, J R Articles by Nutt, D J Pubmed/NCBI databases Medline Plus Health Information Chronic Fatigue Syndrome

Seven genomic subtypes of chronic fatigue syndrome/myalgic encephalomyelitis: a detailed analysis of gene networks and clinical phenotypes

¹ Department of Cellular and Molecular Medicine, St George’s University of London, London, UK
² Sir Joseph Hotung Centre for Musculoskeletal Disorders, St George’s Healthcare Trust and St George’s University of London, London, UK
³ Department of Asthma, Allergy and Respiratory Sciences, King’s College London, London, UK
⁴ Staffordshire Rheumatology Centre, Stoke on Trent, UK
⁵ Psychopharmacology Unit, Department of Community Based Medicine, University of Bristol, Bristol, UK

Correspondence to:
Dr J Kerr, St George’s University of London, Cranmer Terrace, London SW17 0RE, UK; jkerr{at}sgul.ac.uk

Aim: Chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) is a multisystem disease, the pathogenesis of which remains undetermined. The authors have recently reported a study of gene expression that identified differential expression of 88 human genes in patients with CFS/ME. Clustering of quantitative PCR (qPCR) data from patients with CFS/ME revealed seven distinct subtypes with distinct differences in Medical Outcomes Survey Short Form-36 scores, clinical phenotypes and severity.

Methods: In this study, for each CFS/ME subtype, those genes whose expression differed significantly from that of normal blood donors were identified, and then gene interactions, disease associations and molecular and cellular functions of those gene sets were determined. Genomic analysis was then related to clinical data for each CFS/ME subtype.

Results: Genomic analysis revealed some common (neurological, haematological, cancer) and some distinct (metabolic, endocrine, cardiovascular, immunological, inflammatory) disease associations among the subtypes. Subtypes 1, 2 and 7 were the most severe, and subtype 3 was the mildest. Clinical features of each subtype were as follows: subtype 1 (cognitive, musculoskeletal, sleep, anxiety/depression); subtype 2 (musculoskeletal, pain, anxiety/depression); subtype 3 (mild); subtype 4 (cognitive); subtype 5 (musculoskeletal, gastrointestinal); subtype 6 (postexertional); subtype 7 (pain, infectious, musculoskeletal, sleep, neurological, gastrointestinal, neurocognitive, anxiety/depression).

Conclusion: It was particularly interesting that in the seven genomically derived subtypes there were distinct clinical syndromes, and that those which were most severe were also those with anxiety/depression, as would be expected in a disease with a biological basis.