Identification of Marker Genes for Differential Diagnosis of Chronic Fatigue Syndrome – Source: Molecular Medicine, Jul 3, 2008; free access article in PubMed

[Note: You may read the full text of this article free in PubMed Central. ]

Chronic fatigue syndrome (CFS) is a clinically defined condition characterized by long-lasting disabling fatigue. Because of the unknown mechanism underlying this syndrome, there is still 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 significantly changed in CFS patients. ['Messenger' RNA – molecule that transfers chemical blueprint for synthesis of a protein from DNA to cell cytoplasm.]

Of these 12 genes, quantitative real-time PCR validated the changes in 9 genes encoding granzyme [secretion to destroy virus infected cells] 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 of pathological responses in CFS patients and for differential diagnosis of this syndrome.

Source: Molecular Medicine. July 3, 2008. [E-pub ahead of print] PMID: 18596870, by Saiki T, Kawai T, Morita K, Ohta M, Saito T, Rokutan K, Ban N. Department of Stress Science, Institute of Health Biosciences, University of Tokushima Graduate School, Tokushima, Japan. [E-mail:]

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