11 May 2008
Researchers from St George's Hospital, London, have announced that they have identified seven different subtypes of chronic fatigue syndrome (CFS), also known as Myalgic Encephalopathy (ME) and post-viral fatigue syndrome.
It has been estimated that some 250,000 people in the UK are affected by this illness (for more information, see the ME Association) but it is very difficult to diagnose, due to the wide spectrum of clinical symptoms and severity experienced by different patients in addition to extreme, chronic fatigue that is not alleviated by rest. Despite the availability of diagnostic criteria, definitive diagnosis of CFS/ME remains elusive, and is essentially reached by the exclusion of other potential underlying conditions. There is a lingering belief among some clinicians that the disease is a purely psychological phenomenon, but evidence of a biological basis is mounting steadily.
The new study was based on genetic analysis of 55 patients and 75 healthy blood donors; researchers reported to a conference in Cambridge last week that they have identified seven distinct subtypes of CFS/ME typified by specific genetic patterns, linked to specific symptoms. For example, the most common forms were linked to moderate levels of body pain and sleep problems (type four), and fatigue (type six), whilst other forms showed different symptoms such as stomach problems and muscular weakness (type five), and anxiety, depression and pain (type one).
Comment: Although the results from such a small study will require confirmation in a much larger cohort of subjects, researchers hope that the work may lead to a diagnostic test for the condition. Neil Abbot, of ME Research UK commented: "It's a hard illness to get a handle on, so a clinical test would be the single best way forward for everyone" (see BBC news). Previous research has shown that genetic analysis can identify specific sub-types of cancer, potentially allowing much more precise diagnosis, prognosis and clinical management; now it seems possible that genomic information could aid diagnosis in other complex conditions that involve significant genetic contributions to pathology.