Systemic Hyperalgesia in Females with Gulf War Illness, Chronic Fatigue Syndrome and Fibromyalgia.
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ABSTRACT:
SUBMITTER: Surian AA
PROVIDER: S-EPMC7113257 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Systemic Hyperalgesia in Females with Gulf War Illness, Chronic Fatigue Syndrome and Fibromyalgia.
Surian Amber A AA Baraniuk James N JN
Scientific reports 20200401 1
Pain is a diagnostic criterion for Gulf War Illness (GWI), Chronic Fatigue Syndrome (CFS), and fibromyalgia (FM). The physical sign of systemic hyperalgesia (tenderness) was assessed in 920 women who were stratified by 2000 Kansas GWI, 1994 CFS, and 1990 FM criteria. Pressure was applied by dolorimetry at 18 traditional tender points and the average pressure causing pain determined. GWI women were the most tender (2.9 ± 1.6 kg, mean ± SD, n = 70), followed by CFS/FM (3.1 ± 1.4 kg, n = 196), FM ( ...[more]
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Project description:Gulf War Illness affects 25-30% of American veterans deployed to the 1990-91 Persian Gulf War and is characterized by cognitive post-exertional malaise following physical effort. Gulf War Illness remains controversial since cognitive post-exertional malaise is also present in the more common Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. An objective dissociation between neural substrates for cognitive post-exertional malaise in Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome would represent a biological basis for diagnostically distinguishing these two illnesses. Here, we used functional magnetic resonance imaging to measure neural activity in healthy controls and patients with Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome during an N-back working memory task both before and after exercise. Whole brain activation during working memory (2-Back?>?0-Back) was equal between groups prior to exercise. Exercise had no effect on neural activity in healthy controls yet caused deactivation within dorsal midbrain and cerebellar vermis in Gulf War Illness relative to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients. Further, exercise caused increased activation among Myalgic Encephalomyelitis/Chronic Fatigue Syndrome patients within the dorsal midbrain, left operculo-insular cortex (Rolandic operculum) and right middle insula. These regions-of-interest underlie threat assessment, pain, interoception, negative emotion and vigilant attention. As they only emerge post-exercise, these regional differences likely represent neural substrates of cognitive post-exertional malaise useful for developing distinct diagnostic criteria for Gulf War Illness and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.
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2017-02-01 | PXD005185 | Pride
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| S-EPMC5681566 | biostudies-literature
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Project description:BACKGROUND:More than twenty years following the end of the 1990-1991 Gulf War it is estimated that approximately 300,000 veterans of this conflict suffer from an unexplained chronic, multi-system disorder known as Gulf War Illness (GWI). The etiology of GWI may be exposure to chemical toxins, but it remains only partially defined, and its case definition is based only on symptoms. Objective criteria for the diagnosis of GWI are urgently needed for diagnosis and therapeutic research. OBJECTIVE:This study was designed to determine if blood biomarkers could provide objective criteria to assist diagnosis of GWI. DESIGN:A surveillance study of 85 Gulf War Veteran volunteers identified from the Department of Veterans Affairs Minnesota Gulf War registry was performed. All subjects were deployed to the Gulf War. Fifty seven subjects had GWI defined by CDC criteria, and 28 did not have symptomatic criteria for a diagnosis of GWI. Statistical analyses were performed on peripheral blood counts and assays of 61 plasma proteins using the Mann-Whitney rank sum test to compare biomarker distributions and stepwise logistic regression to formulate a diagnostic model. RESULTS:Lymphocyte, monocyte, neutrophil, and platelet counts were higher in GWI subjects. Six serum proteins associated with inflammation were significantly different in GWI subjects. A diagnostic model of three biomarkers-lymphocytes, monocytes, and C reactive protein-had a predicted probability of 90% (CI 76-90%) for diagnosing GWI when the probability of having GWI was above 70%. SIGNIFICANCE:The results of the current study indicate that inflammation is a component of the pathobiology of GWI. Analysis of the data resulted in a model utilizing three readily measurable biomarkers that appears to significantly augment the symptom-based case definition of GWI. These new observations are highly relevant to the diagnosis of GWI, and to therapeutic trials.
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Project description:BACKGROUND: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. METHODS: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. RESULTS: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. CONCLUSION:We concluded that CFS and GWI are significantly differentiable using a pattern of fMRI activity based on an ensemble machine learning model.
| S-EPMC7407325 | biostudies-literature
Project description:Gulf War Illness (GWI) is a complex condition that involves multiple organ systems and is characterized by an abrupt or delayed onset of persistent/relapsing symptomatology such as memory and other neurological problems, muscle and joint pain, gastrointestinal issues, hormonal imbalance, immune dysfunction and debilitating fatigue. Currently, treatment of the condition relies solely on management of symptomatology and improvement in quality of life due to a lack of knowledgeof the underlying mechanisms of disease onset and progression. An improved understanding of the key mechanisms of GWI and dysfunction within regulatory systems will lead to more objective diagnosis methods and adequate management of patients by providing targeted approaches to treatment. Disruption of DNA methylation patterns has been tied to various immune, neurological and endocrine disease states; however, the status of this epigenetic mark in GWI remains uncertain. This study aimed at identifying biomarkers of GWI by gaining knowledge on DNA methylation patterns of GWI in an effort to determine therapeutic targets of disease activity and provide insight into disease onset and progression. Methods: Genomic DNA from 10 GWI patients and 10 healthy controls [HC] (“experimental cohort”) prepared from PBMCs was analyzed with ELISA-based DNA methylation assays and Illumina MethylationEPIC microarrays. These arrays allow measuring the methylation status at 850,000 CpG sites. Methylation changes in promoter regions were separately analyzed and used as input data in ingenuity pathway analysis software to identify altered functional pathways. Relevant differentially methylated CpG sites (DMS) were validated by pyrosequencing. Results: Global DNA methylation levels using the ELISA-based assay on the DNA isolated from PBMCs of GWI patients were similar to those of HC. However, deeper evaluation using microarray-based genome-wide technology allowed detection of DMS in GWI patients with respect to HC. As an overall 10,767 CpG sites presented with differential DNA methylation levels across promoters, gene regulatory elements and within coding regions of genes. Majority of these DMS were hypermethylated in GWI patients as compared to the HC, and more than half of these sites localized to promoters and gene regulatory elements, relative to distribution of DMSin the network as a whole, indicating gene regulatory potential. Functional pathway analysis of the 776 genes with differentially methylated promoters (DMPs) fulfilling FDR≤0.2 criteriafollowing a genomic region-based approachlinks GWI to defects in at least 15 different pathways mostly related to cell signaling with a strong immune component. Conclusions: This is the first study that has explored genome-wide epigenetic changes associated with GWI using the new MethylationEPIC microarrays covering about 850,000 CpG sites; which builds on previous methylation preliminary reports. The data obtained are consistent with previous evidence for dysregulation of the immune system in GWI and suggests a role of this epigenetic modification on the DNA pathobiology of GWI. They are also consistent with previous reports showing a Th1- to Th2-mediated immune response shift in GWI in addition to altered immune system function. Future validation studies in larger cohorts of GWI patients and evaluation of the effects of these methylation patterns on gene expression regulation are granted.
2019-03-15 | GSE112905 | GEO