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Chronic Fatigue Syndrome > Publications > Pathophysiology >

Neuroendocrine and immune network re-modeling in chronic fatigue syndrome: An exploratory analysis.

Fuite J, Vernon SD, Broderick G
Genomics 2008 doi:10.1016/j.ygeno.2008.08.008.

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 sophisticated mathematical models to examine patterns of endocrine status (adrenal, thyroid, and gonadal) with gene expression activity.  The theoretical networks their model identified are what would be expected with chronic inflammation and blunted HPA axis responsiveness. 

Abstract

This work investigates the significance of changes in association patterns linking indicators of neuroendocrine and immune activity in patients with chronic fatigue syndrome (CFS). Gene sets preferentially expressed in specific immune cell isolates were integrated with neuroendocrine data from a large population-based study. Co-expression patterns linking immune cell activity with hypothalamic–pituitary adrenal (HPA), thyroidal (HPT) and gonadal (HPG) axis status were computed using mutual information criteria. Networks in control and CFS subjects were compared globally in terms of a weighted graph edit distance. Local re-modeling of node connectivity was quantified by node degree and eigenvector centrality measures. Results indicate statistically significant differences between CFS and control networks determined mainly by re-modeling around pituitary and thyroid nodes as well as an emergent immune sub-network. Findings align with known mechanisms of chronic inflammation and support possible immune-mediated loss of thyroid function in CFS exacerbated by blunted HPA axis responsiveness.

Page last modified on October 27, 2008

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