Gene expression profiling affords a unique opportunity to characterize CFS at a systems biology level. Changes in gene expression underlie many biologic processes and may provide insight into disease-specific gene expression and the response of genes to environmental stimuli. In a proof-of-concept study, we found that CFS patients had different blood mononuclear cell gene expression patterns than non-fatigued controls  and that CFS is a heterogeneous illness as evidenced by different gene expression profiles for patients reporting gradual onset of their illness compared with those reporting sudden onset of illness . In addition, differential display polymerase chain reaction on a small number of CFS and control subjects identified candidate biomarkers in the peripheral blood [13, 14].
CFS is defined by a post-exertional fatigue that does not subside 24 hours following physical stress. In contrast, exercise in healthy, untrained people induces changes in cellular homeostasis in 1 to 4 hours and a return to basal levels within 24 hours, as measured in muscle . Analysis of peripheral blood gene expression in the healthy control subjects confirmed this observation since the majority of gene expression levels were the same before and 24 hours following exercise challenge. This implied that expression either returned to basal levels or was unchanged as a result of the exercise challenge. And indeed, many of the 21 exercise-induced, differentially expressed genes in control subjects were characterized by GOs that reflect a diverse set of molecular functions necessary for cell function and viability. (These ontologies overlapped with those identified in the GO comparison analysis given in Figure 2a). Figure 1 clearly illustrates the reciprocal pattern of gene expression in the 21 genes for most of the control subjects. In contrast, 11 of the genes were unchanged in CFS subjects before and after exercise; with 5 being classified in a transport-related ontology. Because this difference in gene expression is so dramatic, it implicates a fundamental perturbation in the biochemical activity of lymphocyte and monocyte peripheral blood fractions from CFS subjects compared with control subjects that does not affect classical immunologic markers (i.e, CD45) that have been shown to be unaffected in CFS patients [16, 17]. Rather, low expression of these genes may have subtle effects on immune function. Immune dysfunction has been inconsistently implicated in CFS pathogenesis .
Class comparison was used to identify these 21 differentially expressed genes, which indicated the possible disturbance of biologic pathways (Figure 1). To explore this possibility, we used the GO comparison that is based on the knowledge that gene expression levels are dependent variables in biological processes, cellular components, and molecular functions. In this way, multiple genes in the same category reinforce each other and enhance the power for identifying the significance of the category. The GO categories considered significantly different (p < 0.005) when comparing CFS subjects with controls after exercise challenge were those pertaining to ion transporter activity (a total of 87 genes applied to this category in the comparison of CFS and controls after exercise) and ATPase activity coupled to transmembrane movement (42 genes). When the CFS and control classes are compared prior to exercise, ion transport activity and voltage-gated, ion channel activity are identified (38 and 44 genes within the GO categories, respectively).
It is evident that ion transport and ion channel activity segregate cases from controls and that exercise seems to intensify these differences. Several other conditions have been reported in which fluctuating fatigue occurs that are known to be caused by abnormal ion channels. These conditions include genetically determined channelopathies and acquired conditions such as neuromyotonia, myasthenic syndromes, multiple sclerosis, and polyneuropathies [19, 20]. There are other transmembrane functions associated with differences between controls and CFS patients, including signal transducer activity through receptor binding/activity (Figure 3a). Signal transduction of transmembrane receptors occurs by a number of mechanisms, including structural changes, ion channels, and changes of transmembrane potentials. The G-protein-coupled receptors play an important role in the membrane trafficking machinery . The most obvious exercise-induced changes in CFS cases pertain to gene regulation at the point of chromatin structure; whether these changes reflect the differences seen in the mRNA transcripts relating to membrane trafficking differences between cases and controls has not yet been determined.
One interesting correlate of this study was the finding that the complement pathway showed significant differences between CFS and control subjects after exercise. This has been reported previously in the analysis of these same exercise challenge-derived specimens. Sorensen et al.  measured levels of complement split products in the sera of these subjects and found differences between CFS and control subjects in C4a after exercise challenge. Complement activation was identified as an ontology that was significantly different between CFS and control subjects after exercise. The correlates on the data are interesting as their study measured protein levels (i.e., gene product levels) and this study measured the transcript levels.
The class comparison analysis performed in this study accounted for multiple testing and the over fitting problems of microarray data analysis. The lack of statistical significance in the 3 other class comparison analyses performed (CFS cases compared before and after exercise, comparison of cases to controls at baseline, and the comparison of cases to controls 24 hours after exercise) reflects low experimental sensitivity, most likely due to a small number of subjects, rather than an absence of biological effect. This is accounted for in the gene ontology comparison tool where classes are compared by GO category rather than with regard to individual genes.
The next line of research will detail larger numbers of subjects in the expression arrays. The emphasis in such studies will be on developing a gene expression-based multivariate function, or predictor, that accurately predicts the class membership of a new sample on the basis of the expression levels of key genes. Class discovery tools will also be applied to CFS subjects' expression profiles in an attempt to further describe discrete subsets of this disease on the basis of gene expression as we have done for gradual and sudden onset of illness . However, the methods used in this study will be applied to these data sets too, as these analytical tools will prove to be very helpful in defining the pathophysiology of CFS. It is hoped that this broader, more fully encompassing approach to CFS research will open many doors to the understanding of this syndrome and perhaps of fatigue and un-wellness in general.