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

Viral Exanthems and Herpes Virus Branch, Division of Viral and Rickettsial Diseases, National Centre for Infectious Diseases, Centres for Disease Control and Prevention, 1600 Clifton Rd, Atlanta, Georgia.
Journal of Translational Medicine (Impact Factor: 3.93). 01/2004; 1(1):10. DOI: 10.1186/1479-5876-1-10
Source: PubMed

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.

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.

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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Available from: Toni Whistler, Sep 27, 2015
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    • "The heterogeneity of the patient population (Whistler et al., 2003) and the use of various methods and samples have contributed to conflicting results. Despite this various specific abnormalities have been observed repetitively in the ME/CFS patient population or substantial subgroup thereof (Table 2). "
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    ABSTRACT: Myalgic Encephalomyelitis (ME) was identified as a new clinical entity in 1959 and has been acknowledged as a disease of the central nervous system/neurological disease by the World Health Organisation since 1969. Cognitive impairment, (muscle) weakness, circulatory disturbances, marked variability of symptoms, and, above all, post-exertional malaise: a long-lasting increase of symptoms after minor exertion, are distinctive symptoms of ME.Chronic Fatigue Syndrome (CFS) was introduced in 1988 and was redefined into clinically evaluated, unexplained (persistent or relapsing) chronic fatigue, accompanied by at least four out of a list of eight symptoms, e.g. headaches and unrefreshing sleep, in 1994.Although the labels are used interchangeably, ME and CFS define distinct diagnostic entities. Post-exertional malaise and cognitive deficits e.g. are not mandatory for the diagnosis CFS, while obligatory for the diagnosis ME. “Fatigue” is not obligatory for the diagnosis ME.Since fatigue and other symptoms are subjective and ambiguous, research has been hampered. Despite this and other methodological issues, research has observed specific abnormalities in ME/CFS repetitively, e.g. immunological abnormalities, oxidative and nitrosative
    Frontiers in Physiology 03/2014; 5:109. DOI:10.3389/fphys.2014.00109 · 3.53 Impact Factor
    • "ive between indi - viduals and changes in expression profiles of PBMCs were characteristic in a wide range of diseases , including : juvenile arthritis ( Barnes et al . , 2004 ) , hypertension ( Bull et al . , 2004 ; Chon et al . , 2004 ; Okuda et al . , 2002 ) , cancer ( De Vos et al . , 2002 ; DePrimo et al . , 2003 ) , chronic fatigue disease ( Whistler et al . , 2003 ) , and neuronal injuries ( Tang et al . , 2001 , 2003 ) , lupus ( Bennett et al . , 2003 ; Rus et al . , 2002 ) , transplantation ( Zhang et al . , 2002 ) , and under various environmental pres - sures , such as exercise ( Zhang et al . , 2002 ) and smoking ( Ryder et al . , 2004 ) . It would have been ideal model to com - pare the cha"
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    ABSTRACT: Peripheral blood mononuclear cells (PBMCs) offer a significant promise for gene expression analyses as a substitute for tissues that are not easily accessible. The objective of this study was to validate the use of PBMCs for gene expression analysis as a marker of nutritional intervention as an alternative to skeletal muscle tissue (SMT) biopsies. We performed a transcriptome comparison of PBMCs versus SMT after an 8-week supplementation with n-3 polyunsaturated fatty acid (PUFA) in 16 obese and insulin-resistant subjects. Expression levels of 48,803 transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina, San Diego, CA). In SMT, 36,738 (75%) transcripts were detected, whereas 34,182 (70%) transcripts were detected in PBMCs. Further, 88% (32,341) of these transcripts were coexpressed in both tissues. Importantly, a strong correlation (r = 0.84, p < 0.0001) was observed between transcript expression levels of PBMCs and SMT after n-3 PUFA supplementation. In conclusion, PBMCs express the majority of transcripts expressed in SMT subsequent to n-3 PUFA supplementation and their expression levels are comparable. In the interest of practicalities and cost, these results support the use of PBMCs as a surrogate model for SMT gene expression in nutrigenomic studies. Further research on PBMC and SMT gene expression in response to other nutritional exposures is warranted.
    Omics: a journal of integrative biology 01/2011; 15(1-2):1-7. DOI:10.1089/omi.2010.0073 · 2.36 Impact Factor
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    • "The results indicate subtle changes in the immune system in CFS patients. Whistler et al (2003)* ‡ CFS 23/0 CDC By grouping the CFS patients according to the onset of illness (gradually/sudden), 117 genes differentially expressed in peripheral blood mononuclear cells were identified when using the Atlas Human 3.81 oligonucleotide glass microarrays containing 3800 genes. The majority of these genes were involved in oxidative phosphorylation, glucose metabolism, purine and pyrimidine metabolism, and glycolysis. "
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    ABSTRACT: Fatigue is a common symptom and includes both physical and mental components. It can be associated with a variety of different syndromes and diseases, but in many cases is not associated with other comorbid conditions. Most humans have experienced acute fatigue in relation to different stressors. Acute fatigue typically decreases as the effect of the triggering factor is reduced and a normal homeostatic balance is restored. Fatigue that persists for 6 months or more is termed chronic fatigue. Chronic fatigue (CF) in combination with a minimum of 4 of 8 symptoms and the absence of diseases that could explain these symptoms, constitute the case definition for chronic fatigue syndrome. In spite of its prevalence, the biology of fatigue is relatively poorly understood and biological markers have not yet been identified. This literature search was performed in PubMed to identify research on the genetics and epigenetics of fatigue. Publications were included if fatigue was a major topic and the topic was combined with genetic and/or epigenetic measurements in adult humans. A total of 40 publications were identified. Although altered functioning in the hypothalamic-pituitary-adrenal axis, the serotonergic system, and associations with infectious agents have been identified, the search for genetic or epigenetic markers of fatigue, either in the context of CF or chronic fatigue syndrome (CFS) has been relatively unproductive or, in the case of epigenetics, nonexistent. Although several studies, both hypothesis-testing and hypothesis-generating, have been performed to search for biomarkers, they have mostly been underpowered, restricted by the heterogeneity of the phenotype, or limited by an unsystematic study design. To be able to confirm the hypothesis that risk for, or levels of, fatigue are influenced by the genetic or epigenetic background of an individual, studies need to be based on larger sample sizes with a more clearly defined phenotype. Studies need to focus not only on the influence of a single aspect such as single nucleotide polymorphisms (SNPs) or differential gene expression on disease risk or state, but also on the systems biology behind the disease in combination with information on environmental influences and validation of findings in functional studies.
    PM&R 05/2010; 2(5):456-65. DOI:10.1016/j.pmrj.2010.04.003 · 1.53 Impact Factor
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