Integration of gene expression, clinical, and epidemiologic data to characterize Chronic Fatigue Syndrome

被引:41
作者
Toni Whistler
Elizabeth R Unger
Rosane Nisenbaum
Suzanne D Vernon
机构
[1] Viral Exanthems/Herpes Virus Branch, Div. of Viral/Rickettsial Diseases, Natl. Center for Infectious Diseases, Atlanta, GA
关键词
Chronic Fatigue Syndrome; Chronic Fatigue Syndrome Patient; Pyrimidine Metabolism; Chronic Fatigue Syndrome Subject; Chronic Fatigue Syndrome Case;
D O I
10.1186/1479-5876-1-10
中图分类号
学科分类号
摘要
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. © 2003 Whistler et al; licensee BioMed Central Ltd.
引用
收藏
页数:8
相关论文
共 22 条
  • [1] Fukuda K., Straus S.E., Hickie I., Sharpe M.C., Dobbins J.G., Komaroff A., The chronic fatigue syndrome: A comprehensive approach to its definition and study, Ann. Intern. Med., 121, pp. 953-959, (1994)
  • [2] Reyes M., Dobbins J.G., Mawle A.C., Steele L., Gary H.E., Malani H., Schmid S., Fukuda K., Stewart J., Nisenbaum R., Reeves W.C., Risk factors for CFS: A case control study, Journal of Chronic Fatigue Syndrome, 2, pp. 17-33, (1996)
  • [3] Reyes M., Dobbins J.G., Nisenbaum R., Subedar N., Randall B., Reeves W.C., Chronic fatigue syndrome progression and self-defined recovery: Evidence from the CDC surveillance system, Journal of Chronic Fatigue Syndrome, 5, pp. 17-27, (1999)
  • [4] Nisenbaum R., Reyes M., Unger E.R., Reeves W.C., Factor analysis of symptoms among subjects with unexplained chronic fatigue: What can we learn about chronic fatigue syndrome?, J. Psychosom. Res., (2003)
  • [5] Nutt C.L., Mani D.R., Betensky R.A., Tamayo P., Cairncross J.G., Ladd C., Pohl U., Hartmann C., McLaughlin M.E., Batchelor T.T., Black P.M., von Deimling A., Pomeroy S.L., Golub T.R., Louis D.N., Gene expression-based classification of malignant gliomas correlates better with survival than histological classification, Cancer Res., 63, pp. 1602-1607, (2003)
  • [6] Hoffmann K.F., McCarty T.C., Segal D.H., Chiaramonte M., Hesse M., Davis E.M., Cheever A.W., Meltzer P.S., Morse III H.C., Wynn T.A., Disease fingerprinting with cDNA microarrays reveals distinct gene expression profiles in lethal type 1 and type 2 cytokine-mediated inflammatory reactions, FASEB J., 15, pp. 2545-2547, (2001)
  • [7] Benson M., Carlsson B., Carlsson L.M., Mostad P., Svensson P.A., Cardell L.O., DNA microarray analysis of transforming growth factor-beta and related transcripts in nasal biopsies from patients with allergic rhinitis, Cytokine, 18, pp. 20-25, (2002)
  • [8] Van Der Pouw Kraan T.C., Van Gaalen F.A., Huizinga T.W., Pieterman E., Breedveld F.C., Verweij C.L., Discovery of distinctive gene expression profiles in rheumatoid synovium using cDNA microarray technology: Evidence for the existence of multiple pathways of tissue destruction and repair, Genes Immun., 4, pp. 187-196, (2003)
  • [9] Mycko M.P., Papoian R., Boschert U., Raine C.S., Selmaj K.W., cDNA microarray analysis in multiple sclerosis lesions: Detection of genes associated with disease activity, Brain, 126, pp. 1048-1057, (2003)
  • [10] Vernon S.D., Unger E.R., Dimulescu I.M., Rajeevan M., Reeves W.C., Utility of the blood for gene expression profiling and biomarker discovery in chronic fatigue syndrome, Dis. Markers, 18, pp. 193-199, (2002)