Dataset Information

A comparison of sex-specific immune signatures in Gulf War illness and chronic fatigue syndrome.

ABSTRACT: BACKGROUND:Though potentially linked to the basic physiology of stress response we still have no clear understanding of Gulf War Illness (GWI), a debilitating condition presenting complex immune, endocrine and neurological symptoms. Here we compared male (n = 20) and female (n = 10) veterans with GWI separately against their healthy counterparts (n = 21 male, n = 9 female) as well as subjects with chronic fatigue syndrome/ myalgic encephalomyelitis (CFS/ME) (n = 12 male, n = 10 female). METHODS:Subjects were assessed using a Graded eXercise Test (GXT) with blood drawn prior to exercise, at peak effort (VO2 max) and 4-hours post exercise. Using chemiluminescent imaging we measured the concentrations of IL-1a, 1b, 2, 4, 5, 6, 8, 10, 12 (p70), 13, 15, 17 and 23, IFN?, TNF? and TNF? in plasma samples from each phase of exercise. Linear classification models were constructed using stepwise variable selection to identify cytokine co-expression patterns characteristic of each subject group. RESULTS:Classification accuracies in excess of 80% were obtained using between 2 and 5 cytokine markers. Common to both GWI and CFS, IL-10 and IL-23 expression contributed in an illness and time-dependent manner, accompanied in male subjects by NK and Th1 markers IL-12, IL-15, IL-2 and IFN?. In female GWI and CFS subjects IL-10 was again identified as a delineator but this time in the context of IL-17 and Th2 markers IL-4 and IL-5. Exercise response also differed between sexes: male GWI subjects presented characteristic cytokine signatures at rest but not at peak effort whereas the opposite was true for female subjects. CONCLUSIONS:Though individual markers varied, results collectively supported involvement of the IL-23/Th17/IL-17 axis in the delineation of GWI and CFS in a sex-specific way.

SUBMITTER: Smylie AL

PROVIDER: S-EPMC3698072 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A comparison of sex-specific immune signatures in Gulf War illness and chronic fatigue syndrome.

Smylie Anne Liese AL Broderick Gordon G Fernandes Henrique H Razdan Shirin S Barnes Zachary Z Collado Fanny F Sol Connie C Fletcher Mary Ann MA Klimas Nancy N

BMC immunology 20130625

<h4>Background</h4>Though potentially linked to the basic physiology of stress response we still have no clear understanding of Gulf War Illness (GWI), a debilitating condition presenting complex immune, endocrine and neurological symptoms. Here we compared male (n = 20) and female (n = 10) veterans with GWI separately against their healthy counterparts (n = 21 male, n = 9 female) as well as subjects with chronic fatigue syndrome/ myalgic encephalomyelitis (CFS/ME) (n = 12 male, n = 10 female).< ...[more]

PMID: 23800166

Similar Datasets

Project description:BACKGROUND:Gulf War Illness (GWI) remains a serious health consequence for at least 11,000 veterans of the first Gulf War in the early 1990s. Our understanding of the health consequences that resulted remains inadequate, and this is of great concern with another deployment to the same theater of operations occurring now. Chronic immune cell dysfunction and activation have been demonstrated in patients with GWI, although the literature is not uniform. We exposed GWI patients and matched controls to an exercise challenge to explore differences in immune cell function measured by classic immune assays and gene expression profiling. METHODS:This pilot study enrolled 9 GWI cases identified from the Department of Veterans Affairs GWI registry, and 11 sedentary control veterans who had not been deployed to the Persian Gulf and were matched to cases by sex, body mass index (BMI) and age. We measured peripheral blood cell numbers, NK cytotoxicity, cytokines and expression levels of 20,000 genes immediately before, immediately after and 4 hours following a standard bicycle ergometer exercise challenge. RESULTS:A repeated-measures analysis of variance revealed statistically significant differences for three NK cell subsets and NK cytotoxicity between cases and controls (p < 0.05). Linear regression analysis correlating NK cell numbers to the gene expression profiles showed high correlation of genes associated with NK cell function, serving as a biologic validation of both the in vitro assays and the microarray platform. Intracellular perforin levels in NK and CD8 T-cells trended lower and showed a flatter profile in GWI cases than controls, as did the expression levels of the perforin gene PRF1. Genes distinguishing cases from controls were associated with the glucocorticoid signaling pathway. CONCLUSION:GWI patients demonstrated impaired immune function as demonstrated by decreased NK cytotoxicity and altered gene expression associated with NK cell function. Pro-inflammatory cytokines, T-cell ratios, and dysregulated mediators of the stress response (including salivary cortisol) were also altered in GWI cases compared to control subjects. An interesting and potentially important observation was that the exercise challenge augments these differences, with the most significant effects observed immediately after the stressor, possibly implicating some block in the NK and CD8 T-cells ability to respond to "stress-mediated activation". This has positive implications for the development of laboratory diagnostic tests for this syndrome and provides a paradigm for exploration of the immuno-physiological mechanisms that are operating in GWI, and similar complex syndromes. Our results do not necessarily elucidate the cause of GWI, but they do reveal a role for immune cell dysfunction in sustaining illness.

Project description:Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS) are two debilitating disorders that share similar symptoms of chronic pain, fatigue, and exertional exhaustion after exercise. Many physicians continue to believe that both are psychosomatic disorders and to date no underlying etiology has been discovered. As such, uncovering objective biomarkers is important to lend credibility to criteria for diagnosis and to help differentiate the two disorders. We assessed cognitive differences in 80 subjects with GWI and 38 with CFS by comparing corresponding fMRI scans during 2-back working memory tasks before and after exercise to model brain activation during normal activity and after exertional exhaustion, respectively. Voxels were grouped by the count of total activity into the Automated Anatomical Labeling (AAL) atlas and used in an "ensemble" series of machine learning algorithms to assess if a multi-regional pattern of differences in the fMRI scans could be detected. A K-Nearest Neighbor (70%/81%), Linear Support Vector Machine (SVM) (70%/77%), Decision Tree (82%/82%), Random Forest (77%/78%), AdaBoost (69%/81%), Naïve Bayes (74%/78%), Quadratic Discriminant Analysis (QDA) (73%/75%), Logistic Regression model (82%/82%), and Neural Net (76%/77%) were able to differentiate CFS from GWI before and after exercise with an average of 75% accuracy in predictions across all models before exercise and 79% after exercise. An iterative feature selection and removal process based on Recursive Feature Elimination (RFE) and Random Forest importance selected 30 regions before exercise and 33 regions after exercise that differentiated CFS from GWI across all models, and produced the ultimate best accuracies of 82% before exercise and 82% after exercise by Logistic Regression or Decision Tree by a single model, and 100% before and after exercise when selected by any six or more models. Differential activation on both days included the right anterior insula, left putamen, and bilateral orbital frontal, ventrolateral prefrontal cortex, superior, inferior, and precuneus (medial) parietal, and lateral temporal regions. Day 2 had the cerebellum, left supplementary motor area and bilateral pre- and post-central gyri. Changes between days included the right Rolandic operculum switching to the left on Day 2, and the bilateral midcingulum switching to the left anterior cingulum. We concluded that CFS and GWI are significantly differentiable using a pattern of fMRI activity based on an ensemble machine learning model.

Dataset Information

A comparison of sex-specific immune signatures in Gulf War illness and chronic fatigue syndrome.

Publications

A comparison of sex-specific immune signatures in Gulf War illness and chronic fatigue syndrome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets