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Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood.

Aspler AL, Bolshin C, Vernon SD, Broderick G.
Behavioral and Brain Functions 2008;4:44 doi:10.1186/1744-9081-4-44.
The complete electronic version of this article is available at http://www.behavioralandbrainfunctions.com/content/4/1/44

Summary

Following the 2005 Cold Spring Harbor - Banbury Center CFS Computational Challenge (C3) Workshop, CDC provided data sets from the Wichita in-hospital clinical study to Duke University for use in the Sixth International Conference for the Critical Assessment of Microarray Data Analysis (CAMDA 2006).  Duke University founded CAMDA to provide a forum to critically assess different techniques used in microarray data mining.  CAMDA’s aim is to establish the state-of-the-art in microarray data mining and to identify progress and highlight the direction for future effort.  CAMDA utilizes a community-wide experiment approach, letting the scientific community analyze the same standard data sets.  Researchers worldwide are invited to take the CAMDA challenge and those whose results are accepted are invited to present a 25 minute oral presentation.  The 2006 CAMDA was the first to use a single common challenge data set, which contained all clinical, gene expression, SNP, and proteomics data from the Wichita clinical study.

To date 10 peer reviewed publications have resulted from the CAMDA challenge.  This publication from Gordon Broderick’s group at the University of Alberta, Canada utilized a mathematical modeling approach to construct theoretical correlation networks based on gene activity levels.  The findings are what would be expected in persistent inflammation were involved in CFS.

Abstract

Background: Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS) however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood.

Methods: Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention) and unsupervised latent cluster analysis (LCA). Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in coexpression identified from topological evaluation of linear correlation networks.

Results: Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p=0.01) due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p<0.05, patterns of co-expression in each group differed markedly. Significant co-expression of CD14+ monocyte with CD16+ neutrophil (p=0.01) and CD19+ B cell sets (p=0.00) characterized CFS and fatigue phenotype groups. Also in CFS was a significant negative correlation between CD8+ and both CD19+ up-regulated (p=0.02) and NK gene sets (p=0.08). These patterns were absent in controls.

Conclusions: Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

Page last modified on October 27, 2008

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