Literature DB >> 15490094

Differential-display PCR of peripheral blood for biomarker discovery in chronic fatigue syndrome.

Martin Steinau1, Elizabeth R Unger, Suzanne D Vernon, James F Jones, Mangalathu S Rajeevan.   

Abstract

We used differential-display PCR of peripheral blood mononuclear cells (PBMCs) to search for candidate biomarkers for chronic fatigue syndrome (CFS). PBMCs were collected from a subject with CFS and an age- and sex-matched control before and 24 h after exercise. RNA expression profiles were generated using 46 primer combinations, and the similarity between the individuals was striking. Differentially expressed bands were excised, reamplified, and sequenced, yielding 95 nonredundant sequences, of which 50 matched to known gene transcripts, 38 matched to genes with unknown functions, and 7 had no similarity to any database entry. Most (86%) of the differences between the two subjects were present at baseline. Differential expression of ten genes was verified by real-time reverse-transcription PCR: five (cystatin F, MHC class II, platelet factor 4, fetal brain expressed sequence tag, and perforin) were downregulated, and the remaining five genes (cathepsin B, DNA polymerase epsilon4, novel EST PBMC191MSt, heparanase precursor, and ORF2/L1 element) were upregulated in the subject with CFS. Many of these genes have known functions in defense and immunity, thus supporting prior suggestions of immune dysregulation in the pathogenesis of CFS. Differential-display PCR is a powerful tool for identification of candidate biomarkers. Investigation of these markers in samples from well-designed epidemiological studies of CFS will be required to determine the validity of these candidate biomarkers. The real-time reverse-transcription PCR assays that we developed for assay of these biomarkers will facilitate high-throughput testing of these additional samples.

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Year:  2004        PMID: 15490094     DOI: 10.1007/s00109-004-0586-4

Source DB:  PubMed          Journal:  J Mol Med (Berl)        ISSN: 0946-2716            Impact factor:   4.599


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