Cytokine alterations are more strongly correlated with illness duration than with measures of illness severity. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is an unexplained incapacitating illness that may affect up to 4 million people in the United States alone. There are no validated laboratory tests for diagnosis or management despite global efforts to find biomarkers of disease. We considered the possibility that inability to identify such biomarkers reflected variations in diagnostic criteria and laboratory methods as well as the timing of sample collection during the course of the illness. Accordingly, we leveraged two large, multicenter cohort studies of ME/CFS to assess the relationship of immune signatures with diagnosis, illness duration, and other clinical variables. Controls were frequency-matched on key variables known to affect immune status, including season of sampling and geographic site, in addition to age and sex. We report here distinct alterations in plasma immune signatures early in the course of ME/CFS (n = 52) relative to healthy controls (n = 348) that are not present in subjects with longer duration of illness (n = 246). Analyses based on disease duration revealed that early ME/CFS cases had a prominent activation of both pro- and anti-inflammatory cytokines as well as dissociation of intercytokine regulatory networks. We found a stronger correlation of cytokine alterations with illness duration than with measures of illness severity, suggesting that the immunopathology of ME/CFS is not static. These findings have critical implications for discovery of interventional strategies and early diagnosis of ME/CFS.
Distinct plasma immune signatures in ME/CFS are present early in the course of illness
M. Hornig,J. Montoya,N. Klimas,S. Levine,D. Felsenstein,L. Bateman,Daniel L. Peterson,C. Gunnar Gottschalk,Andrew F. Schultz,X. Che,M. L. Eddy,A. Komaroff,W. I. Lipkin
Published 2015 in Science Advances
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- Publication year
2015
- Venue
Science Advances
- Publication date
2015-02-01
- Fields of study
Biology, Medicine
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- Source metadata
Semantic Scholar, PubMed
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