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Integration of gene expression, clinical, and epidemiologic data to characterize chronic fatigue syndromes.

Whistler T, Unger ER, Nisenbaum R, Vernon SD
Integration of gene expression, clinical, and epidemiologic data to characterize chronic fatigue syndromes
Journal of Translational Medicine 2003;1:10

Summary

This study was an extension of earlier work by the CDC CFS Research Group, which showed that peripheral blood cell gene expression profiles distinguished the majority of CFS cases from non-fatigued controls. This study measured gene expression patterns in 23 persons with CFS identified from the general Wichita population in order to determine if integration of gene expression results with clinical and epidemiologic data would identify CFS subgroups. We found that women with sudden onset CFS had distinct gene expression profiles from those with gradual onset illness. This implies that there are distinct subtypes of CFS with different etiologic or triggering events and shows that these differences are maintained well into the disease process.

Because of the importance and timeliness of these findings we chose to publish in the Journal of Translational Medicine. This is an online journal published by BioMed Central. If accepted following review by rigorously selected subject matter experts, articles are immediately published and indexed by the National Library of Medicine. In addition, all research articles are "open access" allowing immediate free re-use and re-distribution in any medium provided that the original source is cited and material is not used commercially. This article may be accessed at: http://www.translational-medicine.com/content/1/1/10

Abstract

Background: Chronic fatigue syndrome (CFS) has no diagnostic clinical signs or diagnostic laboratory abnormalities and it is unclear if it represents a single illness. The CFS research case definition recommends stratifying subjects by co-morbid conditions, fatigue level and duration, or functional impairment. But to date, this analysis approach has not yielded any further insight into CFS pathogenesis. This study used the integration of peripheral blood gene expression results with epidemiologic and clinical data to determine whether CFS is a single or heterogeneous illness.

Results: CFS subjects were grouped by several clinical and epidemiological variables thought to be important in defining the illness. Statistical tests and cluster analysis were used to distinguish CFS subjects and identify differentially expressed genes. These genes were identified only when CFS subjects were grouped according to illness onset and the majority of genes were involved in pathways of purine and pyrimidine metabolism, glycolysis, oxidative phosphorylation, and glucose metabolism.

Conclusion: These results provide a physiologic basis that suggests CFS is a heterogeneous illness. The differentially expressed genes imply fundamental metabolic perturbations that will be further investigated and illustrates the power of microarray technology for furthering our understanding CFS.

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