Psychological flexibility in somatic symptom and related disorders: A case control study.

A key diagnostic criterion of Somatic Symptom and related Disorders (SSD) comprises significant distress and excessive time-and-energy consuming thoughts, feelings, and behavior pertaining to somatic symptoms. This diagnostic criterion is lacking in central sensitivity syndromes (CSS), such as fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome. This strong emphasis on disturbed psychological processing of somatic symptoms, suggests that psychological flexibility is low in SDD. Psychological flexibility is defined as the ability to approach difficult or challenging internal states (thoughts, emotions, and bodily sensations) in a non-judgmental, mindful way, and being committed to pursue one's values. To clarify the potential significance of psychological flexibility in SSD, we examined its levels in 154 people referred to specialized treatment for SDD, as compared to reference groups from the general population encompassing 597 people with CSS and 1422 people without SSD or CSS (controls). Mean levels of psychological flexibility (adjusted for demographic covariates) were lowest for SSD and highest for controls (F = 154.5, p < 0.001, pη2 = 0.13). Percentages of people with low psychological flexibility (<0.8 SD below the mean of controls) were: SSD 74%, CSS 42%, controls 21%. In SSD, higher psychological flexibility was associated with better mental health (ß = 0.56, p < 0.001), but interaction analysis rejected that psychological flexibility preserved health when having more severe somatic symptoms (ß ≤ 0.08, p ≥ 0.10). The results indicate that lower psychological flexibility is a prevalent problem in SSD that is associated with lower mental health. This suggests that it is worthwhile to take account of psychological flexibility in SSD in screening, monitoring, and therapy.

Reactivation of herpesvirus type 6 and IgA/IgM-mediated responses to activin-A underpin long COVID, including affective symptoms and chronic fatigue syndrome.

BACKGROUND: Persistent infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), reactivation of dormant viruses, and immune-oxidative responses are involved in long COVID. OBJECTIVES: To investigate whether long COVID and depressive, anxiety, and chronic fatigue syndrome (CFS) symptoms are associated with IgA/IgM/IgG to SARS-CoV-2, human herpesvirus type 6 (HHV-6), Epstein-Barr Virus (EBV), and immune-oxidative biomarkers. METHODS: We examined 90 long COVID patients and ninety healthy controls. We measured serum IgA/IgM/IgG against HHV-6 and EBV and their deoxyuridine 5'-triphosphate nucleotidohydrolase (duTPase), SARS-CoV-2, and activin-A, C-reactive protein (CRP), advanced oxidation protein products (AOPP), and insulin resistance (HOMA2-IR). RESULTS: Long COVID patients showed significant elevations in IgG/IgM-SARS-CoV-2, IgG/IgM-HHV-6, and HHV-6-duTPase, IgA/IgM-activin-A, CRP, AOPP, and HOMA2-IR. Neural network analysis yielded a highly significant predictive accuracy of 80.6% for the long COVID diagnosis (sensitivity: 78.9%, specificity: 81.8%, area under the ROC curve = 0.876); the topmost predictors were as follows: IGA-activin-A, IgG-HHV-6, IgM-HHV-6-duTPase, IgG-SARS-CoV-2, and IgM-HHV-6 (all positively) and a factor extracted from all IgA levels to all viral antigens (inversely). The top 5 predictors of affective symptoms due to long COVID were IgM-HHV-6-duTPase, IgG-HHV-6, CRP, education, IgA-activin-A (predictive accuracy of r = 0.636). The top 5 predictors of CFS due to long COVID were in descending order: CRP, IgG-HHV-6-duTPase, IgM-activin-A, IgM-SARS-CoV-2, and IgA-activin-A (predictive accuracy: r = 0.709). CONCLUSION: Reactivation of HHV-6, SARS-CoV-2 persistence, and autoimmune reactions to activin-A combined with activated immune-oxidative pathways play a major role in the pathophysiology of long COVID as well as the severity of its affective symptoms and CFS.

Time-dependent complexity characterisation of activity patterns in patients with Chronic Fatigue Syndrome.

BACKGROUND: Chronic Fatigue Syndrome patients suffer from symptoms that cannot be explained by a single underlying biological cause. It is sometimes claimed that these symptoms are a manifestation of a disrupted autonomic nervous system. Prior works studying this claim from the complex adaptive systems perspective, have observed a lower average complexity of physical activity patterns in chronic fatigue syndrome patients compared to healthy controls. To further study the robustness of such methods, we investigate the within-patient changes in complexity of activity over time. Furthermore, we explore how these changes might be related to changes in patient functioning. METHODS: We propose an extension of the allometric aggregation method, which characterises the complexity of a physiological signal by quantifying the evolution of its fractal dimension. We use it to investigate the temporal variations in within-patient complexity. To this end, physical activity patterns of 7 patients diagnosed with chronic fatigue syndrome were recorded over a period of 3 weeks. These recordings are accompanied by physicians' judgements in terms of the patients' weekly functioning. RESULTS: We report significant within-patient variations in complexity over time. The obtained metrics are shown to depend on the range of timescales for which these are evaluated. We were unable to establish a consistent link between complexity and functioning on a week-by-week basis for the majority of the patients. CONCLUSIONS: The considerable within-patient variations of the fractal dimension across scales and time force us to question the utility of previous studies that characterise long-term activity signals using a single static complexity metric. The complexity of a Chronic Fatigue Syndrome patient's physical activity signal does not suffice to characterise their high-level functioning over time and has limited potential as an objective monitoring metric by itself.

Long COVID: Long-Term Impact of SARS-CoV2.

Four years post-pandemic, SARS-CoV-2 continues to affect many lives across the globe. An estimated 65 million people suffer from long COVID, a term used to encapsulate the post-acute sequelae of SARS-CoV-2 infections that affect multiple organ systems. Known symptoms include chronic fatigue syndrome, brain fog, cardiovascular issues, autoimmunity, dysautonomia, and clotting due to inflammation. Herein, we review long COVID symptoms, the proposed theories behind the pathology, diagnostics, treatments, and the clinical trials underway to explore treatments for viral persistence, autonomic and cognitive dysfunctions, sleep disturbances, fatigue, and exercise intolerance.

Association of circulating biomarkers with illness severity measures differentiates myalgic encephalomyelitis/chronic fatigue syndrome and post-COVID-19 condition: a prospective pilot cohort study.

BACKGROUND: Accumulating evidence suggests that autonomic dysfunction and persistent systemic inflammation are common clinical features in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID. However, there is limited knowledge regarding their potential association with circulating biomarkers and illness severity in these conditions. METHODS: This single-site, prospective, cross-sectional, pilot cohort study aimed to distinguish between the two patient populations by using self-reported outcome measures and circulating biomarkers of endothelial function and systemic inflammation status. Thirty-one individuals with ME/CFS, 23 individuals with long COVID, and 31 matched sedentary healthy controls were included. All study participants underwent non-invasive cardiovascular hemodynamic challenge testing (10 min NASA lean test) for assessment of orthostatic intolerance. Regression analysis was used to examine associations between outcome measures and circulating biomarkers in the study participants. Classification across groups was based on principal component and discriminant analyses. RESULTS: Four ME/CFS patients (13%), 1 with long COVID (4%), and 1 healthy control (3%) presented postural orthostatic tachycardia syndrome (POTS) using the 10-min NASA lean test. Compared with matched healthy controls, ME/CFS and long COVID subjects showed higher levels of ET-1 (p < 0.05) and VCAM-1 (p < 0.001), and lower levels of nitrites (NOx assessed as NO2- + NO3-) (p < 0.01). ME/CFS patients also showed higher levels of serpin E1 (PAI-1) and E-selectin than did both long COVID and matched control subjects (p < 0.01 in all cases). Long COVID patients had lower TSP-1 levels than did ME/CFS patients and matched sedentary healthy controls (p < 0.001). As for inflammation biomarkers, both long COVID and ME/CFS subjects had higher levels of TNF-α than did matched healthy controls (p < 0.01 in both comparisons). Compared with controls, ME/CFS patients had higher levels of IL-1ß (p < 0.001), IL-4 (p < 0.001), IL-6 (p < 0.01), IL-10 (p < 0.001), IP-10 (p < 0.05), and leptin (p < 0.001). Principal component analysis supported differentiation between groups based on self-reported outcome measures and biomarkers of endothelial function and inflammatory status in the study population. CONCLUSIONS: Our findings revealed that combining biomarkers of endothelial dysfunction and inflammation with outcome measures differentiate ME/CFS and Long COVID using robust discriminant analysis of principal components. Further research is needed to provide a more comprehensive characterization of these underlying pathomechanisms, which could be promising targets for therapeutic and preventive strategies in these conditions.

Sijunzi decoction, a classical Chinese herbal formula, improves fatigue symptoms with changes in gut microbiota in chronic fatigue syndrome: A randomized, double-blind, placebo-controlled, multi-center clinical trial.

BACKGROUD: Chronic fatigue syndrome (CFS) severely impact patients' quality of life and lacks well-acknowledged drug therapy. Sijunzi decoction (SJZD), a classical Chinese herbal formula, has been widely used for spleen deficiency syndrome like fatigue in China. However, there is a lack of evidence on the efficacy of SJZD in treating CFS. PURPOSE: To evaluate the efficacy and safety of SJZD for CFS. STUDY DESIGN: A multi-center, double-blinded, randomized controlled trial. METHODS: Participants with definite diagnoses of CFS and spleen deficiency syndrome were randomly assigned in 1:1 ratio to receive SJZD or placebo granules for 2 months. The primary outcome was the change of Chalder fatigue questionnaire (CFQ) scoring after treatment. Other outcomes included changes in short form-36 physical function (SF36-PF) score, spleen deficiency scale score, Euroqol Questionnaire-Visual Analogue Scale (ED-VAS) score, and clinical global impression (CGI) evaluating by corresponding questionnaires. Fecal metagenome sequencing was conducted to explore the potential mechanism of SJZD effect. RESULTS: From June 2020 to July 2021, 105 of 127 participants completed the study at four hospitals in China. After a 2-month treatment, intention-to-treat (ITT) analysis found participants who received SJZD had larger reduction than placebo control (mean change 6.65 [standard deviation (SD) 6.11] points vs. 5.31 [SD 5.19] points; difference 1.34, 95 % confidence interval [CI] -0.65 to 3.33). Per-protocol (PP) analysis reported confirmative results with a significant difference between SJZD and placebo groups (2.24, 95 % CI 0.10 to 4.39). SJZD also significantly improved overall health status compared with placebo in per-protocol population (p = 0.009). No significant difference was found between groups in changes of SF36-PF, spleen deficiency scale scoring, and CGI. Fecal metagenome sequencing and correlation analyses indicated that the beneficial effect of SJZD may be related to the abundance change of Pediococcus acidilactici. No serious adverse event or abnormal laboratory test was found during the whole study. CONCLUSION: Our results indicated that SJZD can improve fatigue symptom and overall health status in patients with CFS under good medication adherence. Potential therapeutic effects may be related to the regulation of gut microbiota. Large-scale trials with longer intervention period are encouraged to further support SJZD's application. CLINICAL TRIAL REGISTRATION: (ID, ISRCTN23930966, URL = https://www.isrctn.com/ISRCTN23930966).

Impaired Hand Grip Strength Correlates with Greater Disability and Symptom Severity in Post-COVID Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Background: Post-COVID syndrome (PCS) encompasses a diverse array of symptoms persisting beyond 3 months after acute SARS-CoV-2 infection, with mental as well as physical fatigue being the most frequent manifestations. Methods: In 144 female patients with PCS, hand grip strength (HGS) parameters were assessed as an objective measure of muscle fatigue, with 78 meeting the Canadian Consensus Criteria for postinfectious myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The severity of disability and key symptoms was evaluated using self-reported questionnaires. Results: Patients with ME/CFS exhibited heightened overall symptom severity, including lower physical function (p < 0.001), a greater degree of disability (p < 0.001), more severe fatigue (p < 0.001), postexertional malaise (p < 0.001), and autonomic dysfunction (p = 0.004) compared to other patients with PCS. While HGS was impaired similarly in all patients with PCS and exhibited a significant correlation with physical function across the entire patient group, HGS of patients with ME/CFS uniquely demonstrated associations with key symptoms. Conclusions: Thus, impaired HGS serves as an objective marker of physical function in patients with PCS. Only in patients meeting ME/CFS criteria is impaired HGS also associated with the severity of hallmark symptoms. This suggests a common mechanism for muscle fatigue and other symptoms in the ME/CFS subtype, distinct from that in other types of PCS.

Heterogeneity in Measures of Illness among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Not Explained by Clinical Practice: A Study in Seven U.S. Specialty Clinics.

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients' standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. Relying on case-control study designs without subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms.

Personalized Management of Fatigue in Individuals With Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID Using a Smart Digital mHealth Solution: Protocol for a Participatory Design Approach.

BACKGROUND: Fatigue is the most common symptom in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID, impacting patients' quality of life; however, there is currently a lack of evidence-based context-aware tools for fatigue self-management in these populations. OBJECTIVE: This study aimed to (1) address fatigue in ME/CFS and long COVID through the development of digital mobile health solutions for self-management, (2) predict perceived fatigue severity using real-time data, and (3) assess the feasibility and potential benefits of personalized digital mobile health solutions. METHODS: The MyFatigue project adopts a patient-centered approach within the participatory health informatics domain. Patient representatives will be actively involved in decision-making processes. This study combines inductive and deductive research approaches, using qualitative studies to generate new knowledge and quantitative methods to test hypotheses regarding the relationship between factors like physical activity, sleep behaviors, and perceived fatigue in ME/CFS and long COVID. Co-design methods will be used to develop a personalized digital solution for fatigue self-management based on the generated knowledge. Finally, a pilot study will evaluate the feasibility, acceptance, and potential benefits of the digital health solution. RESULTS: The MyFatigue project opened to enrollment in November 2023. Initial results are expected to be published by the end of 2024. CONCLUSIONS: This study protocol holds the potential to expand understanding, create personalized self-management approaches, engage stakeholders, and ultimately improve the well-being of individuals with ME/CFS and long COVID. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50157.

Machine learning algorithms for detection of visuomotor neural control differences in individuals with PASC and ME.

The COVID-19 pandemic has affected millions worldwide, giving rise to long-term symptoms known as post-acute sequelae of SARS-CoV-2 (PASC) infection, colloquially referred to as long COVID. With an increasing number of people experiencing these symptoms, early intervention is crucial. In this study, we introduce a novel method to detect the likelihood of PASC or Myalgic Encephalomyelitis (ME) using a wearable four-channel headband that collects Electroencephalogram (EEG) data. The raw EEG signals are processed using Continuous Wavelet Transform (CWT) to form a spectrogram-like matrix, which serves as input for various machine learning and deep learning models. We employ models such as CONVLSTM (Convolutional Long Short-Term Memory), CNN-LSTM, and Bi-LSTM (Bidirectional Long short-term memory). Additionally, we test the dataset on traditional machine learning models for comparative analysis. Our results show that the best-performing model, CNN-LSTM, achieved an accuracy of 83%. In addition to the original spectrogram data, we generated synthetic spectrograms using Wasserstein Generative Adversarial Networks (WGANs) to augment our dataset. These synthetic spectrograms contributed to the training phase, addressing challenges such as limited data volume and patient privacy. Impressively, the model trained on synthetic data achieved an average accuracy of 93%, significantly outperforming the original model. These results demonstrate the feasibility and effectiveness of our proposed method in detecting the effects of PASC and ME, paving the way for early identification and management of the condition. The proposed approach holds significant potential for various practical applications, particularly in the clinical domain. It can be utilized for evaluating the current condition of individuals with PASC or ME, and monitoring the recovery process of those with PASC, or the efficacy of any interventions in the PASC and ME populations. By implementing this technique, healthcare professionals can facilitate more effective management of chronic PASC or ME effects, ensuring timely intervention and improving the quality of life for those experiencing these conditions.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

Research progress in the treatment of chronic fatigue syndrome through interventions targeting the hypothalamus-pituitary-adrenal axis.

Chronic fatigue syndrome (CFS) causes great harm to individuals and society. Elucidating the pathogenesis of CFS and developing safe and effective treatments are urgently needed. This paper reviews the functional changes in the hypothalamus-pituitary-adrenal (HPA) axis in patients with CFS and the associated neuroendocrine mechanisms. Despite some controversy, the current mainstream research evidence indicates that CFS patients have mild hypocortisolism, weakened daily variation in cortisol, a weakened response to the HPA axis, and an increase in negative feedback of the HPA axis. The relationship between dysfunction of the HPA axis and the typical symptoms of CFS are discussed, and the current treatment methods are reviewed.

Effect of electroacupuncture on behavior and hippocampal inflammatory factors in rats with chronic fatigue syndrome. / ç”µé’ˆå¯¹æ ¢æ€§ç–²åŠ³ç»¼åˆå¾å¤§é¼ è¡Œä¸ºå­¦åŠæµ·é©¬ç‚Žæ€§å› å­çš„å½±å“.

OBJECTIVES: To observe the effect of electroacupuncture (EA) on the changes of behavior and hippocampal inflammatory factors in rats with chronic fatigue syndrome (CFS), so as to explore its possible mechanisms in the treatment of CFS. METHODS: Twenty-seven SD rats were randomly divided into control, model and electroacupuncture (EA) groups (n=9 rats in each group). The CFS model was established by multi-factor compound stress stimulation method. Rats of the EA group received EA (10 Hz) at "Shenting" (GV24) penetrating "Baihui" (GV20), "Dazhui" (GV14) for 15 min, twice a day for 14 days. The general conditions, Morris water maze test, open field test, the exhausted running platform were conducted for determining the rats' locomotor and learning-memory activities. H.E. staining was used to observe the morphological structure of neurons in hippocampal CA1 region. The contents of interleukin (IL)-10, IL-17 and transforming growth factor (TGF) ß1 in hippocampus and serum of rats were detected by ELISA, and the positive expressions of IL-10, IL-17 and TGF-ß1 in hippocampal CA1 region were detected by immunofluorescence staining. RESULTS: Compared with the control group, the score of general condition was increased (P<0.05), the escape latency was prolonged (P<0.05), the number of crossing the original platform was decreased (P<0.05), the numbers of crossing the grid and entering the central area were increased (P<0.05), and the exhaustive treadmill time was shortened (P<0.05) in the model group. The contents of IL-10 in the hippocampus and serum were decreased (P<0.05), while IL-17 and TGF-ß1 contents were increased (P<0.05). The immunofluorescence intensity of IL-10 in the hippocampus was decreased (P<0.05), while the intensity of IL-17 and TGF-ß1 were increased (P<0.05). After treatment, compared with the model group, the score of general condition was decreased (P<0.05), the escape latency was shortened (P<0.05), the number of crossing the original platform was increased (P<0.05), the numbers of crossing the grid and entering the central area were decreased (P<0.05), and the exhaustive treadmill time was prolonged (P<0.05) in the EA group. The contents of IL-10 in the hippocampus and serum were increased (P<0.05), while IL-17 and TGF-ß1 levels were decreased (P<0.05). The immunofluorescence intensity of IL-10 in the hippocampus was increased (P<0.05), while the intensity of IL-17 and TGF-ß1 were decreased (P<0.05). H.E. staining showed that in the model group, the number of neurons in the hippocampus decreased, with disordered arrangement and loose structure, and a small numbers of neuronal nuclei were missing. The degree of tissue damage of the EA group was milder than that of the model group. CONCLUSIONS: EA can alleviate fatigue and spatial learning and memory impairment in CFS rats, which may be related to the regulation of peripheral and central inflammation.

Association between fatigue, peripheral serotonin, and L-carnitine in hypothyroidism and in chronic fatigue syndrome.

Background: Fatigue of unknown origin is a hallmark symptom in chronic fatigue syndrome (CFS) and is also found in 20% of hypothyroidism patients despite appropriate levothyroxine treatment. Here, we suggest that in these disorders, peripheral serotonin levels are low, and elevating them to normal range with L-carnitine is accompanied with reduced fatigue. Methods: We conducted a retrospective analysis of follow-up clinical data (CFS N=12; hypothyroidism with fatigue N=40) where serum serotonin and fatigue levels were compared before vs. after 7 weeks of oral L-carnitine supplementation. Results: After L-carnitine, serotonin increased (8-fold in CFS, Sig. = 0.002, 6-fold in hypothyroidism, Sig. < 0.001) whereas fatigue decreased (2-fold in both CFS and hypothyroidism, Sig. = 0.002 for CFS, Sig. < 0.001 for hypothyroidism). There was a negative correlation between serotonin level and fatigue (for CFS, rho = -0.49 before and -0.67 after L-carnitine; for hypothyroidism, rho = -0.24 before and -0.83 after L-carnitine). Conclusions: These findings suggest a new link between low peripheral serotonin, L-carnitine, and fatigue.

Recent Research Trends in Neuroinflammatory and Neurodegenerative Disorders.

Neuroinflammatory and neurodegenerative disorders including Alzheimer's disease (AD), Parkinson's disease (PD), traumatic brain injury (TBI) and Amyotrophic lateral sclerosis (ALS) are chronic major health disorders. The exact mechanism of the neuroimmune dysfunctions of these disease pathogeneses is currently not clearly understood. These disorders show dysregulated neuroimmune and inflammatory responses, including activation of neurons, glial cells, and neurovascular unit damage associated with excessive release of proinflammatory cytokines, chemokines, neurotoxic mediators, and infiltration of peripheral immune cells into the brain, as well as entry of inflammatory mediators through damaged neurovascular endothelial cells, blood-brain barrier and tight junction proteins. Activation of glial cells and immune cells leads to the release of many inflammatory and neurotoxic molecules that cause neuroinflammation and neurodegeneration. Gulf War Illness (GWI) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are chronic disorders that are also associated with neuroimmune dysfunctions. Currently, there are no effective disease-modifying therapeutic options available for these diseases. Human induced pluripotent stem cell (iPSC)-derived neurons, astrocytes, microglia, endothelial cells and pericytes are currently used for many disease models for drug discovery. This review highlights certain recent trends in neuroinflammatory responses and iPSC-derived brain cell applications in neuroinflammatory disorders.

In major dysmood disorder, physiosomatic, chronic fatigue and fibromyalgia symptoms are driven by immune activation and increased immune-associated neurotoxicity.

Major depressive disorder (MDD) is accompanied by activated neuro-immune pathways, increased physiosomatic and chronic fatigue-fibromyalgia (FF) symptoms. The most severe MDD phenotype, namely major dysmood disorder (MDMD), is associated with adverse childhood experiences (ACEs) and negative life events (NLEs) which induce cytokines/chemokines/growth factors. To delineate the impact of ACE + NLEs on physiosomatic and FF symptoms in first episode (FE)-MDMD, and examine whether these effects are mediated by immune profiles. ACEs, NLEs, physiosomatic and FF symptoms, and 48 cytokines/chemokines/growth factors were measured in 64 FE-MDMD patients and 32 normal controls. Physiosomatic, FF and gastro-intestinal symptoms belong to the same factor as depression, anxiety, melancholia, and insomnia. The first factor extracted from these seven domains is labeled the physio-affective phenome of depression. A part (59.0%) of the variance in physiosomatic symptoms is explained by the independent effects of interleukin (IL)-16 and IL-8 (positively), CCL3 and IL-1 receptor antagonist (inversely correlated). A part (46.5%) of the variance in physiosomatic (59.0%) symptoms is explained by the independent effects of interleukin (IL)-16, TNF-related apoptosis-inducing ligand (TRAIL) (positively) and combined activities of negative immunoregulatory cytokines (inversely associated). Partial least squares analysis shows that ACE + NLEs exert a substantial influence on the physio-affective phenome which are partly mediated by an immune network composed of interleukin-16, CCL27, TRAIL, macrophage-colony stimulating factor, and stem cell growth factor. The physiosomatic and FF symptoms of FE-MDMD are partly caused by immune-associated neurotoxicity due to T helper (Th)-1 polarization and M1 macrophage activation and relative lowered compensatory immunoregulatory protection.

The Head-Up Tilt Table Test as a Measure of Autonomic Functioning among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) often experience autonomic symptoms. In the present study, we evaluated 193 adults seeking treatment for ME/CFS, who were recruited from an outpatient clinic. The participants completed a head-up tilt table test to assess two common types of orthostatic intolerance, namely, postural orthostatic tachycardia syndrome (POTS) and orthostatic hypotension (OH). During the tilt test, 32.5% of the participants demonstrated POTS or OH. The participants with either of these two common types of orthostatic intolerance were found to have more problems with sleep and post-exertional malaise as assessed by the DePaul Symptom Questionnaire; these patients also reported more physical and health function limitations. The implications of the findings are discussed.

Bao Yuan decoction alleviates fatigue by restraining inflammation and oxidative stress via the AMPK/CRY2/PER1 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Baoyuan Decoction (BYD) was initially recorded in the classic of "Bo Ai Xin Jian" in the Ming dynasty. It is traditionally used for treating weakness and cowardice, and deficiency of vital energy. In researches related to anti-fatigue effects, the reciprocal regulation of AMPK and circadian clocks likely plays an important role in anti-fatigue mechanism, while it has not yet been revealed. Therefore, we elucidated the anti-fatigue mechanism of BYD through AMPK/CRY2/PER1 pathway. AIM OF THE STUDY: To investigate the effect and mechanism of BYD in reducing fatigue, using pharmacodynamics, network pharmacology and transcriptomics through the AMPK/CRY2/PER1 signaling pathway. MATERIALS AND METHODS: Firstly, the chemical constituents of BYD were qualitatively identified by UHPLC-Q-Exactive Orbitrap/MS, establishing a comprehensive strategy with an in-house library, Xcalibur software and Pubchem combined. Secondly, a Na2SO3-induced fatigue model and 2,2'-Azobis (2-methylpropionamidine) dihydrochloride (AAPH)-induced oxidative stress model were developed to evaluate the anti-fatigue and anti-oxidant activities of BYD using AB zebrafish. The anti-inflammatory activity of BYD was evaluated using CuSO4-induced and tail cutting-induced Tg (lyz: dsRed) transgenic zebrafish inflammation models. Then, target screening was performed by Swiss ADME, GeneCards, OMIM and DrugBank databases, the network was constructed using Cytoscape 3.9.0. Transcriptome and network pharmacology technology were used to investigate the related signaling pathways and potential mechanisms after treatment with BYD, which were verified by real-time quantitative PCR (RT-qPCR). RESULTS: In total, 114 compounds from the water extract of BYD were identified as major compounds. Na2SO3-induced fatigue model and AAPH-induced oxidative stress model indicated that BYD has significant anti-fatigue and antioxidant effects. Meanwhile, BYD showed significant anti-inflammatory effects on CuSO4-induced and tail cutting-induced zebrafish inflammation models. The KEGG result of network pharmacology showed that the anti-fatigue function of BYD was mainly effected through AMPK signaling pathway. Besides, transcriptome analysis indicated that the circadian rhythm, AMPK and IL-17 signaling pathways were recommended as the main pathways related to the anti-fatigue effect of BYD. The RT-qPCR results showed that compared with a model control group, the treatment of BYD significantly elevated the expression mRNA of AMPK, CRY2 and PER1. CONCLUSION: Herein, we identified 114 chemical constituents of BYD, performed zebrafish activity validation, while demonstrated that BYD can relieve fatigue by AMPK/CRY2/PER1 signaling pathway through network pharmacology and transcriptome.

Graded exercise therapy compared to activity management for paediatric chronic fatigue syndrome/myalgic encephalomyelitis: pragmatic randomized controlled trial.

The MAGENTA pragmatic parallel groups randomized controlled trial compared graded exercise therapy (GET) with activity management (AM) in treating paediatric myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS). Children aged 8-17 years with mild/moderate ME/CFS and presenting to NHS specialist paediatric services were allocated at random to either individualised flexible treatment focussing on physical activity (GET, 123 participants) or on managing cognitive, school and social activity (AM, 118 participants) delivered by NHS therapists. The primary outcome was the self-reported short-form 36 physical function subscale (SF-36-PFS) after 6 months, with higher scores indicating better functioning. After 6 months, data were available for 201 (83%) participants who received a mean of 3.9 (GET) or 4.6 (AM) treatment sessions. Comparing participants with measured outcomes in their allocated groups, the mean SF-36-PFS score changed from 54.8 (standard deviation 23.7) to 55.7 (23.3) for GET and from 55.5 (23.1) to 57.7 (26.0) for AM giving an adjusted difference in means of -2.02 (95% confidence interval -7.75, 2.70). One hundred thirty-five participants completed the mean SF-36-PFS at 12 months, and whilst further improvement was observed, the difference between the study groups remained consistent with chance. The two study groups showed similar changes on most of the secondary outcome measures: Chalder Fatigue, Hospital Anxiety and Depression Scale: Depression, proportion of full-time school attended, a visual analogue pain scale, participant-rated change and accelerometer measured physical activity, whether at the 6-month or 12-month assessment. There was an isolated finding of some evidence of an improvement in anxiety in those allocated to GET, as measured by the Hospital Anxiety and Depression Scale at 6 months, with the 12-month assessment, and the Spence Children's Anxiety scale being aligned with that finding. There was weak evidence of a greater risk of deterioration with GET (27%) than with AM (17%; p = 0.069). At conventional UK cost per QALY thresholds, the probability that GET is more cost-effective than AM ranged from 18 to 21%. Whilst completion of the SF-36-PFS, Chalder Fatigue Scale and EQ-5D-Y was good at the 6-month assessment point, it was less satisfactory for other measures, and for all measures at the 12-month assessment.  Conclusion: There was no evidence that GET was more effective or cost-effective than AM in this setting, with very limited improvement in either study group evident by the 6-month or 12-month assessment points.  Trial registration: The study protocol was registered at www.isrctn.com (3rd September 2015; ISRCTN 23962803) before the start of enrolment to the initial feasibility phase.

IA-PACS-CFS: a double-blinded, randomized, sham-controlled, exploratory trial of immunoadsorption in patients with chronic fatigue syndrome (CFS) including patients with post-acute COVID-19 CFS (PACS-CFS).

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severely debilitating condition which markedly restricts activity and function of affected people. Since the beginning of the COVID-19 pandemic ME/CFS related to post-acute COVID-19 syndrome (PACS) can be diagnosed in a subset of patients presenting with persistent fatigue 6 months after a mostly mild SARS-CoV-2 infection by fulfillment of the Canadian Consensus Criteria (CCC 2003). Induction of autoimmunity after viral infection is a mechanism under intensive investigation. In patients with ME/CFS, autoantibodies against thyreoperoxidase (TPO), beta-adrenergic receptors (ß2AR), and muscarinic acetylcholine receptors (MAR) are frequently found, and there is evidence for effectiveness of immunomodulation with B cell depleting therapy, cyclophosphamide, or intravenous immunoglobulins (IVIG). Preliminary studies on the treatment of ME/CFS patients with immunoadsorption (IA), an apheresis that removes antibodies from plasma, suggest clinical improvement. However, evidence from placebo-controlled trials is currently missing. METHODS: In this double-blinded, randomized, sham-controlled, exploratory trial the therapeutic effect of five cycles of IA every other day in patients with ME/CFS, including patients with post-acute COVID-19 chronic fatigue syndrome (PACS-CFS), will be evaluated using the validated Chalder Fatigue Scale, a patient-reported outcome measurement. A total of 66 patients will be randomized at a 2:1 ratio: 44 patients will receive IA (active treatment group) and 22 patients will receive a sham apheresis (control group). Moreover, safety, tolerability, and the effect of IA on patient-reported outcome parameters, biomarker-related objectives, cognitive outcome measurements, and physical parameters will be assessed. Patients will be hospitalized at the clinical site from day 1 to day 10 to receive five IA treatments and medical visits. Four follow-up visits (including two visits at site and two visits via telephone call) at month 1 (day 30), 2 (day 60), 4 (day 120), and 6 (day 180; EOS, end of study visit) will take place. DISCUSSION: Although ME/CFS including PACS-CFS causes an immense individual, social, and economic burden, we lack efficient therapeutic options. The present study aims to investigate the efficacy of immunoadsorption and to contribute to the etiological understanding and establishment of diagnostic tools for ME/CFS. TRIAL REGISTRATION: Registration Number: NCT05710770 . Registered on 02 February 2023.