Article ; Online: Immune network analysis of cerebrospinal fluid in myalgic encephalomyelitis/chronic fatigue syndrome with atypical and classical presentations.
2017 Volume 7, Issue 4, Page(s) e1080
Abstract: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a persistent and debilitating disorder marked by cognitive and sensory dysfunction and unexplained physical fatigue. Classically, cases present after a prodrome consistent with infection; ... ...
| Abstract | Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a persistent and debilitating disorder marked by cognitive and sensory dysfunction and unexplained physical fatigue. Classically, cases present after a prodrome consistent with infection; however, some cases are atypical and have a different presentation and comorbidities that pose challenges for differential diagnosis. We analyzed cerebrospinal fluid (CSF) from 32 cases with classical ME/CFS and 27 cases with atypical ME/CFS using a 51-plex cytokine assay. Atypical subjects differed in cytokine profiles from classical subjects. In logistic regression models incorporating immune molecules that were identified as potential predictor variables through feature selection, we found strong associations between the atypical ME/CFS phenotype and lower CSF levels of the inflammatory mediators, interleukin 17A and CXCL9. Network analysis revealed an absence of inverse inter-cytokine relationships in CSF from atypical patients, and more sparse positive intercorrelations, than classical subjects. Interleukin 1 receptor antagonist appeared to be a negative regulator in classical ME/CFS, with patterns suggestive of disturbances in interleukin 1 signaling and autoimmunity-type patterns of immune activation. Immune signatures in the central nervous system of ME/CFS patients with atypical features may be distinct from those with more typical clinical presentations. |
|---|---|
| Language | English |
| Publishing date | 2017-04-04 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 2609311-X |
| ISSN | 2158-3188 ; 2158-3188 |
| ISSN (online) | 2158-3188 |
| ISSN | 2158-3188 |
| DOI | 10.1038/tp.2017.44 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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