Search Results (95)

Post-exertional malaise (PEM) and cognitive dysfunction (hereafter “cognitive dysfunction”, including the patient-reported syndrome often described as “brain fog”) are among the most disabling features of Long COVID; yet, approved disease-modifying treatments remain lacking. Emerging evidence implicates interacting disturbances in mitochondrial bioenergetics, redox regulation and neurovascular inflammation, although much of the supporting evidence remains indirect and derives from acute COVID-19, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), primary mitochondrial disease, inflammatory biology and mechanistic pharmacology rather than from direct Long COVID intervention trials. This hypothesis-generating narrative review develops a mechanism-based translational framework: that a pathway-targeted nutraceutical programme may modulate selected elements of these three axes, subject to prior demonstration of formulation quality, pharmacokinetic feasibility, target engagement and safety. Candidate modules comprise coenzyme Q10 and alpha-lipoic acid for bioenergetic/redox support; selenium, sulforaphane and resveratrol for Nrf2–thioredoxin-related redox regulation; and Boswellia serrata, luteolin and eicosapentaenoic acid for putative prostaglandin/resolution-pathway modulation. Sonlicromanol provides a conceptual mechanistic precedent for combined redox and prostaglandin-directed pharmacology, but it is not considered pharmacologically equivalent to an eight-agent nutraceutical combination. We summarise the mechanistic rationale, distinguish direct from indirect evidence, define qualitative evidence-grading criteria, outline safety and interaction considerations, and propose a staged translational research programme. This framework is intended to generate falsifiable hypotheses for future Long COVID studies, not to imply established clinical efficacy. Full article

Long COVID (LC) is a heterogeneous post-infectious syndrome characterized by persistent symptoms, yet the biological basis underlying its interindividual variability remains poorly understood. Given the clinical overlap between LC and myalgic encephalomyelitis (ME), and prior demonstration that haptoglobin (Hp) phenotypes modulate symptom severity in ME, we investigated whether Hp phenotypes similarly stratify post-exertional cognitive dysfunction in LC. In this longitudinal observational study, 44 individuals with LC and 20 short-course COVID controls, who recovered rapidly from SARS-CoV-2 infection without persistent symptoms or sequelae, underwent Hp phenotyping alongside metabolomic and physiological profiling before and after a standardized 90 min passive post-exertional challenge. Hp phenotypes identified clinically distinct LC subgroups. Compared with Hp1-1 individuals, Hp2 allele carriers exhibited greater fatigue, poorer physical function, and more severe post-exertional symptoms. Immediately following the challenge, Hp2-2 participants with LC showed significant cognitive decline, whereas Hp1-1 individuals demonstrated cognitive resilience and more favorable longitudinal cognitive trajectories. This differential susceptibility was accompanied by higher post-exertional cerebral fractional tissue oxygen extraction in the right hemisphere in Hp1-1 individuals and by distinct metabolic signatures, with Hp2 allele carriers exhibiting lower post-exertional plasma concentrations of citric acid, isethionate, and glucosamine. Lower metabolite levels were associated with poorer cognitive performance. These findings support Hp phenotypes as promising candidate biomarkers for biological stratification in Long COVID, pending validation in larger independent cohorts. Full article

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is an idiopathic, multisystem disorder marked by debilitating fatigue, post-exertional malaise, cognitive dysfunction and neuroinflammation. Its etiology remains unclear, yet emerging evidence implicates a complex interplay between immune dysregulation, metabolic impairment, mitochondrial bioenergetics, and environmental stressors such as viral infection or low-dose ionizing radiation (LDIR). To develop treatments for ME/CFS, it is essential to identify suitable targets for therapy. In this narrative review, we discuss recent findings on the overlap of ME/CFS with LDIR effects and examine potential mechanistic links that may arise from LDIR-induced bystander effects (RIBEs). We highlight potential candidate biomarkers that bridge these domains: mitochondrial respiratory dysfunction, altered ornithine transport via SLC25A15 (ORNT1), possible roles of CD38 in the context of immunity and NAD+ depletion, cyclin D1–dependent metabolic reprogramming and modulation of gene expression, and α-synuclein as a potential neuroinflammatory damage-associated molecular pattern (DAMP). While the involvement of these biomarkers in ME/CFS is yet to be confirmed experimentally, evidence from in vitro studies of irradiated cells, exosome profiling, and patient samples suggests that RIBEs can, in theory, produce prominent cellular ME/CFS phenotypes through associated mechanisms, including those exhibiting oxidative stress, impaired ATP production, and immune modulation. We propose a hypothetical, exploratory model wherein LDIR initiates or contributes to adaptive metabolic shifts (including CD38 upregulation and cyclin D1 stabilization) that, coupled with persistent bystander signaling, could potentially culminate in chronic fatigue and neurocognitive symptoms in some reported ME/CFS cases. Finally, we outline a research agenda encompassing the establishment of standardized diagnostic criteria, multi-omics profiling of patient cohorts, exosome analysis, functional mitochondrial assays, and targeted therapeutic trials focusing on possible anti-CD38 antibodies and NAD+ precursor therapy. By integrating recent findings in low-dose radiation biology with ME/CFS pathophysiology, this review aims to promote interdisciplinary investigations that may uncover mechanistic insights and novel biomarkers for diagnosis and treatment of ME/CFS. We further review steps in a proposed model taking us from low-dose radiation exposure to a number of possible targets. Full article

Background: Post-COVID-19 Condition (PCC) causes persistent multisystem symptoms, reduced quality of life, and high healthcare needs. Data on patient experiences in Switzerland are scarce. Objective: To assess healthcare access, treatment pathways, waiting times, and insurance-related burden among individuals with PCC in Switzerland. Methods: We conducted a nationwide anonymous online survey between July and October 2025. Adults living in Switzerland with symptoms persisting ≥12 weeks after SARS-CoV-2 infection were eligible. Recruitment was conducted through support groups, social media, and specialized PCC consultations at several Swiss hospitals. The multilingual questionnaire covered demographics, symptoms, healthcare utilization, treatment experiences, and insurance issues. Results: A total of 333 individuals participated (81.7% women; mean age 45.8 years). The most frequent symptoms were fatigue (98.5%), brain fog (92.5%), post-exertional malaise (91.0%), sleep disturbances (82.3%), and musculoskeletal pain (80.8%). Only 12.6% reported early and adequate medical support, whereas 45.0% had to actively seek care themselves and 24.6% had received no support. General practitioners were the most frequently consulted providers (77.5%), followed by specialized PCC clinics (39.0%). Waiting times were prolonged: 32.1% waited 4–6 months, 32.4% >6 months and 10.8% reported no available consultation service. Satisfaction with care was modest (3.02/5). Difficulties with social insurance were reported by 42.6%, including missing benefits, lack of recognition, and prolonged procedures. Conclusions: Individuals with PCC in Switzerland face major barriers to timely and coordinated care. Strengthening primary care competencies, expanding multidisciplinary services, and implementing structured patient-centered pathways are urgently needed to improve outcomes and reduce long-term disability. Full article

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating multisystem illness characterised by post-exertional malaise, non-restorative sleep, and cognitive impairment, yet no objective diagnostic biomarkers have been established. Untargeted plasma metabolomics provides a broad view of the biochemical disturbances underlying ME/CFS; however, the high dimensionality of omics datasets and the limited interpretability of conventional classifiers nevertheless hinder translation into clinical practice. This study evaluates three ensemble classifiers—Explainable Boosting Machine (EBM), XGBoost, and LightGBM—for binary ME/CFS classification using plasma metabolomic and lipidomic profiles from 197 participants (106 ME/CFS; 91 healthy controls; 888 features). Feature dimensionality was reduced using a Pareto-Guided Recursive Neural Network (PRNN) pipeline. Model performance was assessed via 50-repeat stratified hold-out validation. EBM achieved the highest accuracy (0.909; 95% CI: 0.868–0.949) and area under the receiver operating characteristic curve (AUC: 0.940; 95% CI: 0.909–0.983), with XGBoost and LightGBM performing comparably. Interpretability analyses revealed that pairwise metabolite interaction terms—particularly proline & indole-3-lactate, tyrosine & N-acetylornithine, and maleic acid & arachidic acid—contributed the greatest discriminative signal. An ablation analysis comparing the full interaction-augmented EBM (AUC = 0.940) with a main-effects-only EBM (AUC = 0.882) confirmed that pairwise metabolite co-variation contributes additional discriminative value beyond individual metabolite levels, implicating amino acid catabolism, tryptophan–kynurenine pathway dysregulation, mitochondrial energy impairment, and lipid remodelling as central pathophysiological features. Global and instance-level explanations jointly demonstrated population-level metabolic signatures alongside individual heterogeneity, highlighting the added clinical value of explainable artificial intelligence (XAI) in metabolomics. These findings support EBM-based metabolomic profiling as an internally validated approach for ME/CFS classification, subject to external validation, calibration assessment, and prospective testing. Full article

Background/objectives: Long COVID is associated with persistent, multi-system symptoms, yet little is known about how it affects individuals with intersecting vulnerabilities, such as a racialized identity and pre-existing mental health conditions. This study aimed to descriptively characterize the symptom burden, functional outcomes and mental health in this population. Methods: A cross-sectional, exploratory study was conducted among 51 adults in Canada who self-identified as racialized and as having a pre-existing mental health condition and reported long COVID symptoms. Participants completed an online survey, including validated measures of symptoms, fatigue, post-exertional malaise, cognitive function, mental health and disability. Descriptive statistics were used to summarize outcomes. Results: Participants reported a slight to moderate overall symptom burden, with the highest scores in respiratory and psychological domains. Functional impairment was moderate across work, social and daily activities (Work and Social Adjustment Scale mean = 17.35; World Health Organization Disability Assessment Schedule 2.0 mean = 16.61; Post COVID-19 Functional Status Scale mean = 2.20). Fatigue and post-exertional malaise were notable (Modified Fatigue Impact Scale mean = 43.39; DePaul Symptom Questionnaire—Post-Exertional Malaise mean = 22.47), and cognitive difficulties were commonly reported (Perceived Deficits Questionnaire mean = 33.43). Anxiety and depression scores were in the mild to moderate range respectively (General Anxiety Disorder-7 mean = 9.27; Patient Health Questionnaire-9 mean = 11.43). Conclusions: Clinically relevant fatigue, post-exertional malaise, and depression were found, alongside moderate functional limitations across life domains. The findings support the conceptualization of long COVID as a syndemic condition and underscore the need for equity-informed research, rehabilitation and public health strategies. Full article

Myalgic encephalomyelitis (ME) is characterized by profound fatigue, post-exertional malaise (PEM), and cognitive dysfunction. Despite its clinical significance, the pathophysiology of PEM and disease heterogeneity remain unclear, and no validated biomarkers are available for rapid diagnosis or monitoring. We aimed to develop a screening approach combining label-free Raman spectroscopy (RS) and machine learning modeling (ML) to detect biomolecular changes in blood plasma and differentiate patients with ME from sedentary healthy controls. Blood plasma was collected from 115 patients with ME and 45 controls at rest (T0) and 90 min after a standardized, non-invasive stress test designed to induce PEM. Plasma samples were analyzed by RS, and ML models were developed independently at each time point to differentiate patients with ME and controls. The RS-ML models identified spectral features consistent with contributions from proteins, lipids, and low-molecular-weight metabolites. At T0 and T90, the area under the receiver operating characteristic curve, accuracy, specificity and sensitivity were 0.85 and 0.83, 79% and 84%, 82% and 90%, and 73% and 69%, respectively. RS-ML provides a rapid, low-cost approach to detect ME-associated biomolecular signatures in plasma and capture biochemical alterations associated with standardized stress. Full article

Myalgic Encephalomyelitis (ME) is a chronic, multisystem disease characterized by systemic metabolic dysfunction and post-exertional malaise (PEM). In this study, we investigated the dysregulation of irisin, an exercise-induced myokine, and its potential antagonism by thrombospondin-1 (TSP-1). In a cross-sectional study (92 ME patients vs. 44 sedentary healthy controls), plasma irisin and TSP-1 levels were measured at baseline and after a 90 min mechanical stress challenge applied to induce PEM. ME patients exhibited significantly lower baseline irisin (p < 0.05) and a blunted exertional response (p < 0.05). Paradoxically, baseline irisin was an independent predictor of fatigue severity (β = 0.728, p = 0.018), with moderate-to-severe patients showing elevated levels of both irisin and TSP-1 (p < 0.05), suggesting a compensatory but ineffective response. Functional cellular dielectric spectroscopy indicated that TSP-1 inhibits irisin signaling in a concentration-dependent manner. Irisin signaling was markedly reduced by both αvβ5 blockade and HSP90α inhibition in this experimental system, consistent with a diminished ability to counteract TSP-1. Collectively, these findings support a model in which dysregulation of the irisin–TSP-1 axis contributes to metabolic dysfunction in ME. Elevated circulating TSP-1 levels are associated with symptom severity and are linked to impaired irisin signaling in an HSP90α- and αvβ5-dependent context. This interaction is consistent with defective metabolic adaptation and highlights a potential therapeutic target that warrants further validation to restore energy homeostasis. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease characterized by a multitude of symptoms across various organ systems. Diagnosis has relied heavily on heterogeneous clinical symptom presentation and evolving case definitions, with treatment focused on addressing presenting symptoms due to the paucity of validated biomarkers. Meanwhile, advances have been made in understanding the underlying pathophysiology through strong epidemiologic, clinical, and basic science studies. This narrative review synthesizes recent advances that are likely to drive a shift in understanding from symptom-based classification toward a molecularly defined understanding of the disease. This shift in understanding will likely provide the foundation for future research efforts focused on targeting diagnosis and treatment more effectively. Specifically, we reference the identification of rare genetic risk variants through the HEAL2 deep learning framework, the large-scale DecodeME genome-wide association study, and dynamic epigenetic markers of disease state. In addition, the findings revealed the downstream consequences of this genetic and epigenetic priming: chronic innate immune activation, CD8+ T cell exhaustion characterized by upregulation of the exhaustion-driving transcription factors Thymocyte Selection-Associated HMG Box (TOX) and Eomesodermin (EOMES), and a cellular energy crisis centered on mitochondrial dysfunction. Furthermore, results of recent studies have revealed sex-specific transcriptomic and proteomic signatures of maladaptive recovery. We also highlight the role of machine learning and artificial intelligence integrations in translating high-dimensional multi-omics data into actionable biological insights, including the identification of monocyte subsets via Positive Unlabeled Learning, circulating cell-free RNA diagnostic signatures, and integrated multi-modal disease models such as BioMapAI. The combination of these findings, which highlight multiple identifiable mechanisms of molecular activity, support the feasibility of molecular subtyping, precision diagnostics, and targeted therapeutic strategies for ME/CFS. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and post-COVID-19 syndrome share a symptom profile, including severe fatigue, cognitive dysfunction, exertional intolerance, sleep disturbances, hypervigilance, and the paradoxical state of being “wired but tired.” A well-established finding is sympathetic hyperactivity with reduced vagal tone, typically interpreted as autonomic nervous system dysfunction. Emerging evidence, however, suggests a broader disturbance across multiple neurotransmitter systems. This paper reviews current knowledge on neurotransmitter systems implicated in ME/CFS and Long COVID, focusing on potential mechanisms of dysregulation and their roles in disease pathology and symptom generation, as well as implications for treatment. In addition to abnormalities of the noradrenergic system, disturbances in serotonergic, GABAergic, and glutamatergic signaling have been reported. Contributing factors may include autoimmunity, neuroinflammation, gut dysbiosis, epigenetic influences, and stressors such as orthostatic intolerance, metabolic strain, and pain. A shift favoring excitatory over inhibitory neurotransmission can lead to excessive neural activation, autonomic dysfunction, sensory hypersensitivities, sleep disturbances, and cognitive impairment. Reduced GABAergic tone combined with increased glutamatergic and noradrenergic activity may elevate skeletal muscle tone, contributing to calcium overload, mitochondrial dysfunction, exertional intolerance, and post-exertional malaise. Various pharmacological treatments may partially rebalance these neurotransmitter systems, but limited efficacy highlights the need for systematic investigation and individualized strategies. Full article

Background: Post-exertional malaise (PEM), which is the cardinal feature of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), is also reported in a proportion of patients with post-COVID-19 syndrome (PCS). Our objective was to identify determinants that may be linked to the emergence of PEM in PCS patients. Methods: Patients fulfilling the World Health Organization definition for PCS who attended the post-COVID unit of the Internal Medicine Department of Angers University Hospital, France, between June 2020 and December 2023 were included retrospectively. Their medical records were reviewed to extract information on COVID-19 infection history, characteristics of post-exertional malaise (PEM), fatigue severity, and relevant epidemiological variables. Results: The study included 220 patients, grouped according to whether post-exertional malaise was present (PCS/PEM+) or absent (PCS/PEM–). PEM was observed in 26.4% of patients and was significantly linked to earlier COVID onset in 2020/2021 (OR 5.68 (95% CI: 1.66–19.45), p = 0.006), as well as higher fatigue levels (OR 2.07 (95% CI: 1.22–3.50), p = 0.007). Conclusions: Patients who contracted COVID-19 during the pre-Omicron period reported PEM more frequently than those infected in later waves. This observation could reflect differences in viral characteristics following the emergence of the Omicron variant; however, alternative explanations—such as increasing vaccination coverage, accumulating post-infectious immunity, or other unmeasured factors—cannot be ruled out. Based on the observed link between PEM and symptom severity, PCS patients should be systematically assessed for the presence of PEM. Full article

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder, characterized by symptoms such as post-exertional malaise (PEM) and cognitive impairments. This study assessed reaction time (RT) metrics in three-dimensional (3D) visual tasks with the aim of objectively quantifying the cognitive impairments in ME/CFS patients compared to controls. Methods: A total of 120 participants (60 ME/CFS patients and 60 controls) were recruited at the Department of Ophthalmology, Universität of Erlangen-Nürnberg. RT was assessed using a virtual reality–oculomotor test system, presenting 3D stimuli at three disparity levels (275″, 550″, and 1100″) within three gaming repetitions (R1, R2, and R3). Mixed-effects models were used to evaluate group differences, with age and gender as covariates. Pairwise contrasts were calculated to assess changes across repetitions. Fatigue self-assessments were recorded by validated questionnaires, (FACIT Fatigue Scale, Chalder Fatigue Scale, Bell Score and Health Assessment Questionnaire), and their correlation with RT metrics was portrayed using a Spearman correlation matrix. Results: Estimated means (EM-means) for RT were significantly prolonged in ME/CFS patients compared to controls at disparity 275″ (1969 ms vs. 1384 ms; p = 0.0001), 550″ (1409 vs. 1071 ms; p = 0.0012) and 1100″ (1126 ms vs. 891 ms; p = 0.00223). Age was a significant covariate (p < 0.001), while gender showed no effect. Both groups demonstrated improvements in RT over repetitions; however, ME/CFS patients showed a significantly lower improvement compared to controls, reaching significance in R3 (p = 0.0042). RT metrics did not correlate with patients’ self-assessment scores. Conclusions: ME/CFS patients showed consistently slower RTs compared to controls, particularly in later, easier gaming repetitions, potentially reflecting the impact of fatigue. Full article

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic, multisystemic disorder characterized by severe, persistent fatigue not alleviated by rest and worsened by minimal exertion, often accompanied by post-exertional malaise (PEM), unrefreshing sleep, cognitive dysfunction, and autonomic disturbances. Despite decades of research, its pathophysiology remains incompletely understood, and skeletal muscle involvement has only recently gained attention. This review aims to provide a historical and pathophysiological synthesis of ME/CFS, emphasizing the pivotal role of skeletal muscle in the onset and persistence of symptoms, and to integrate molecular, cellular, and pathophysiological evidence into a coherent explanatory framework. This is a narrative review of published literature (1990–2025) with critical integration of clinical, biochemical, and experimental data on oxidative stress, mitochondrial dysfunction, Excitation–Contraction (E-C coupling) dysregulation, and muscle secretome alterations in ME/CFS also in relation to post-viral syndromes (e.g., Long COVID). Evidence consistently points to mitochondrial oxidative stress, redox imbalance, impaired Ca²⁺ handling, and altered signaling pathways in skeletal muscle of patients with ME/CFS. Historical milestones show an evolution from psychogenic interpretations toward recognition of ME/CFS as a biological disorder with neuromuscular and metabolic underpinnings. ME/CFS can be interpreted as a skeletal muscle–metabolic disorder characterized by oxidative distress, mitochondrial dysfunction, and impaired energy regulation, leading to the clinical picture of exercise intolerance and post-exertional malaise. Integrating basic and clinical research through a translational approach provides the foundation for new diagnostic tools, targeted therapies, and biomarkers. Full article

Background and Objectives: Post-COVID-19 syndrome (PCS), characterized by persistent fatigue, can develop after a SARS-CoV-2 infection. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, post-infectious condition marked by severe fatigue and post-exertional malaise. This study aimed to determine the incidence and characteristics of PCS and ME/CFS in a cohort of hospital employees (HEs) with SARS-CoV-2 infections. Materials and Methods: All HEs who tested SARS-CoV-2-positive between March 2020 and May 2021 who later reported persistent fatigue were invited for an assessment from July to December 2022. Canadian Consensus Criteria were used for the diagnosis of ME/CFS. Assessments included the Montreal Cognitive Assessment (MoCA), and determination of coagulation factors, Epstein–Barr virus (EBV) antibodies and autoantibodies (AABs) against G-protein-coupled receptors (GPCRs). Results: Of the 221 HEs, 11.8% (95% confidence interval (CI95%) 7.8–16.8, 26/221) still reported persistent fatigue and 3.2% (CI95% 1.3–6.4, 7/221) were diagnosed with ME/CFS. In total, 19 HEs (median age 51.0 years, 89.4% female, 63.1% possible or confirmed nosocomial infection) participated in our assessment. In 42.1% (8/19) MoCA results were below normal. Laboratory values showed increased GPCR AABs in 66.6% (12/18), possible EBV reactivation in 86.7% (13/15) and coagulation parameters suggesting inflammatory processes in 38.9% (7/18). Conclusions: Our study was able to determine lower-bound incidences of PCS with fatigue and ME/CFS and demonstrated a diagnostic pathway for HEs following SARS-CoV-2 infections. Possible EBV reactivation, increased GPCR AABs and potential coagulation cascade activation may play a pathogenic role. Full article

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, multisystem disease characterized by post-exertional malaise and persistent fatigue. The cause of ME/CFS is not well understood, and there are no established biomarkers or FDA-approved pharmacotherapies. The clinical heterogeneity of ME/CFS presents challenges to diagnosis and treatment and necessitates collaborative efforts to generate robust findings. This study leveraged gene and protein expression data from the mapMECFS data repository and the DecodeME Genome-Wide Association Study (GWAS) to assess consistent gene signatures across studies. The mitochondrial genes MT-RNR1 and MT-RNR2 exhibited lower expression in ME/CFS cases in two studies. Combining this with increased expression of mitochondrial genes in platelets from another study, this supports mitochondrial dysregulation as having a role in ME/CFS. Furthermore, ME/CFS-associated genes were mapped to compounds in drug databases as possible treatments for further investigation. In muscle gene expression data, 107 approved compounds target 26 genes with functions relevant to mitochondrial support and immunomodulators. From the DecodeME GWAS, 83 approved compounds target 24 genes with functions related to energy metabolism and mitochondrial function. Though little consistency in specific genes was observed across studies, which highlights the need for larger studies, mitochondrial dysfunction in ME/CFS cases was evident across studies. Full article