Identification of marker genes for differential diagnosis of chronic fatigue syndrome

Abstract

Chronic fatigue syndrome (CFS) is a clinically defined condition characterized by long-lasting disabling fatigue. Because of the unknown mechanism underlying this syndrome, there still is no specific biomarker for objective assessment of the pathological fatigue. We have compared gene expression profiles in peripheral blood between 11 drug-free patients with CFS and age- and sex-matched healthy subjects using a custom microarray carrying complementary DNA probes for 1,467 stress-responsive genes. We identified 12 genes whose mRNA levels were changed significantly in CFS patients. Of these 12 genes, quantitative real-time PCR validated the changes in 9 genes encoding granzyme in activated T or natural killer cells (GZMA), energy regulators (ATP5J2, COX5B, and DBI), proteasome subunits (PSMA3 and PSMA4), putative protein kinase c inhibitor (HINT ), GTPase (ARHC), and signal transducers and activators of transcription 5A (STAT5A). Next, we performed the same microarray analysis on 3 additional CFS patients and 20 other patients with the chief complaint of long-lasting fatigue related to other disorders (non-CFS patients) and found that the relative mRNA expression of 9 genes classified 79% (11/14) of CFS and 85% (17/20) of the non-CFS patients. Finally, real-time PCR measurements of the levels of the 9 involved mRNAs were done in another group of 18 CFS and 12 non-CFS patients. The expression pattern correctly classified 94% (17/18) of CFS and 92% (11/12) of non-CFS patients. Our results suggest that the defined gene cluster (9 genes) may be useful for detecting pathological responses in CFS patients and for differential diagnosis of this syndrome.

Figure 1. Identification of 12 CFS-associated genes in patients with CFS

The expressions of 1072 genes were compared between 11 patients with CFS and age- and sex-matched healthy controls, and 12 common genes were identified that were significantly changed in CFS patients according to the paired t-test using the cyber-T stats program (Bonferroni wide false positive rate = 0.05). Heatmap values represent the relative ratios of gene expressions between CFS and age- and sex-matched healthy controls. Hierarchical clustering was performed by the results of average linkage and distance metric of cosine θ. Gene symbols, P-values, GenBank accession numbers, and names of the 12 genes are listed. P-values are based on paired t-tests. Patient’s numbers indicated at the bottom of column are corresponding to the numbers in Table 1.

Figure 2. Relative expression of 10 marker genes in patients with CFS by microarray and real-time PCR

RNA prepared from 11 patients with CFS and age- and sex-matched healthy controls was subjected to TaqMan real-time PCR as described in the method section. Of the 12 genes, 10 mRNA levels were measured and then normalized to GAPDH mRNA expression. After the relative ratios of 10 mRNAs between CFS patients and control subjects were calculated, they were compared between microarray (empty bars) and real time PCR results (solid bars). Values are mean fold changes ± SD (n = 11). ^#P < 0.05 by the paired t-test.

Figure 3. Expression of 9 marker genes in CFS and non-CFS cases

RNA was prepared from whole blood of 3 additionally enrolled patients with CFS and 20 patients with the chief complaint of general fatigue related to other disorders, and subjected to the microarray analysis. The expression patterns of 9 genes in these patients were compared with those of the initially enrolled 11 patients with CFS by hierarchical cluster analysis. CFS and non-CFS cases are indicated as red and yellow bars, respectively. Patient’s numbers indicated at the bottom of columns are corresponding to the numbers in Table 1. ^# Three newly enrolled patients with CFS.

Figure 4. Differentiation of CFS and non-CFS cases by expression levels of 9 marker genes. (A)

The expressions of 9 marker genes were validated by real-time PCR, and their mean values were compared in 18 newly enrolled CFS patients (indicated as “C”) with 12 non-CFS patients (indicated as “N”). Values are mean fold changes ± SD. ^#P < 0.05 by the unpaired t-test. (B) The expression levels of 9 genes from 18 CFS and 12 non-CFS patients were differentiated using hierarchical cluster analysis by the results of average linkage and distance metric of cosine θ. CFS and non-CFS patients are indicated as red and yellow bars, respectively. Patient’s numbers indicated at the bottom of columns are corresponding to the numbers in Table 1.