Tag: 2025

Specialised care for severely affected ME/CFS patients

Abstract:

Introduction: A specialised care unit for severely and very severely ill ME/CFS patients opened in 2021. The results from the first 3 years are reported.

Methods: People with ME/CFS who were diagnosed according to the Canadian Consensus Criteria, who are aged 18 or above with severe or very severe ME/CFS according to the UK NICE guidelines, are eligible to stay at Røysumtunet. The study design is a retrospective review of medical records.

Results: Between June 2021 and June 2024, 24 ME/CFS patients, 20 women and 4 men with a confirmed diagnosis of ME, were admitted to the unit for stays of at least 3 months. Seventeen were very severely affected and 7 were severely affected. Ages ranged from 18 to 68 years, with mean (SD) 37.5 (12.8) years. Seven patients showed significant improvement (p < 0.01), and five others showed some improvement. In total 50% improved (p < 0.01). Patients who improved were borderline significantly younger than those who did not, with a mean age of 30.3 (SD 12.6) years compared to 39.8 (SD 11.8) years (p = 0.06). The mean duration of disease was 2.3 (1.3) years for those who improved versus 6.7 (3.9) years for those who did not improve (p < 0.05).

Conclusion: This is the first report of a specialised care unit for the most severely ill ME/CFS patients. Fifty per cent of patients showed significant or partial improvement. The mechanisms behind these improvements are discussed but require further exploration in future studies.

Source: Saugstad, O. D., Sollie, M. G., Torp, H. A., & Storla, D. G. (2025). Specialised care for severely affected ME/CFS patients. Fatigue: Biomedicine, Health &amp; Behavior, 1–13. https://doi.org/10.1080/21641846.2025.2565101 https://www.tandfonline.com/doi/full/10.1080/21641846.2025.2565101 (Full text)

Understanding Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Physical Fatigue Through the Perspective of Immunosenescence

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating illness marked by persistent fatigue, yet its mechanisms remain unclear. Growing evidence implicates immunosenescence-the age-related decline in immune function-in the onset and persistence of fatigue.

Methods: This review synthesizes clinical and experimental data to examine how immunosenescence contributes to ME/CFS. We focus on chronic inflammation, senescent immune phenotypes, mitochondrial dysfunction, and neuroendocrine imbalance, with emphasis on maladaptive crosstalk among immune, muscular, neuroendocrine, and vascular systems.

Results: Aging immune cells drive chronic inflammation that impairs mitochondrial ATP production and promotes muscle catabolism. Concurrently, HPA-axis suppression and β2-adrenergic dysfunction amplify immune dysregulation and energy imbalance. Together, these processes illustrate how immunosenescence sustains pathological cross-organ signaling underlying systemic fatigue.

Conclusion: Immunosenescence provides a unifying framework linking immune, metabolic, and neuroendocrine dysfunction in ME/CFS. Recognizing cross-organ communication highlights its clinical relevance, suggesting biomarkers such as cytokines and exhaustion markers, and supports integrated therapeutic strategies targeting immune and metabolic networks.

Source: Luo Y, Xu H, Xiong S, Ke J. Understanding Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Physical Fatigue Through the Perspective of Immunosenescence. Compr Physiol. 2025 Oct;15(5):e70056. doi: 10.1002/cph4.70056. PMID: 41017304. https://pubmed.ncbi.nlm.nih.gov/41017304/

The gut microbial composition is different in chronic fatigue syndrome than in healthy controls

Abstract:

The pathogenesis of Chronic Fatigue Syndrome (CFS) is yet unknown. This study aimed to assess the gut microbial composition in CFS patients versus in healthy controls (HCs).

The composition of fecal bacteria was examined in twenty-five CFS patients and sixteen HCs using Illumina sequencing of 16 S rRNA gene amplicons targeting the V3-V4 bacterial gene regions. 143 (46%) of the microbial genera were found only in the CFS. In addition, the gut microbial composition in the CFS patients contained a much higher proportion of the 10 most commonly found bacteria compared to the HCs group. A significantly lower observed number of operational taxonomic units (OTUs) was noted in CFS compared to HCs (p = 0.045).

Significant between-group differences in the gut microbial composition in CFS compared to HCs were noted. The three most discriminating Amplicon Sequencing Variants (ASVs): ASV 191, ASV 44, and ASV 75, were identified as significantly more abundant in the healthy control group compared to the patient group. In addition, the Neural Network (multilayer perceptron) was able to discriminate gut microbial composition from CFS versus HCs with excellent performance (AUC = 0.935).

The gut microbial composition is different in CFS patients compared to HCs. Further studies should assess the pathophysiological consequences of these differences as well as the effectiveness of therapies aimed at modifying the gut microbial composition in CFS patients.

Source: Prylińska-Jaśkowiak M, Tabisz H, Kujawski S, Godlewska BR, Słomko J, Januszko-Giergielewicz B, Murovska M, Morten KJ, Sokołowski Ł, Zalewski P. The gut microbial composition is different in chronic fatigue syndrome than in healthy controls. Sci Rep. 2025 Sep 26;15(1):33075. doi: 10.1038/s41598-025-16438-y. PMID: 41006438. https://www.nature.com/articles/s41598-025-16438-y (Full text)

Evidence of clinical and brain recovery in post-COVID-19 condition: a three-year follow-up study

Abstract:

Fatigue and cognitive dysfunction linked to persistent brain changes have been reported for up to two years after COVID-19. In this study, we followed the clinical, neuroimaging and fluid biomarker trajectories over three years post SARS-CoV-2 infection to evaluate potential signs and underlying factors of brain recovery.

We conducted a monocentric, longitudinal study using resting-state functional and structural T1-weighted magnetic resonance imaging data from 51 patients with Post-COVID-19 Condition (mean age 50 years, 33 female) collected at a mean time of 6, 23 and 38 months after COVID-19 infection. The trajectory of brain changes was compared to 23 age- and sex-matched healthy controls (mean age 37 years, 13 female) with similar time intervals between brain scans and analysed in relation to clinical, neuropsychological and fluid biomarkers including interleukins and neurodestruction markers at all timepoints. In addition, hand grip strength to evaluate muscular fatigue, was assessed at the final follow-up visit.

Self-reported fatigue improved over time but was still moderate on average three years after COVID-19 infection, while measures of hand grip strength and cognitive performance were largely unaffected. We found a significant increase of both lateral ventricles (∼8%) and the third (∼6%) ventricle accompanied by a structural volume reduction in adjacent areas including the thalamus, pallidum, caudate nucleus and putamen. An increased neuronal activation pattern was widespread and pronounced in these areas. The brainstem no longer exhibited volume loss as reported in our pervious study, but enhanced functional connectivity. Laboratory markers including interleukins and neuronal injury markers remained within the normal reference ranges across all study timepoints.

Our study revealed an overall slow but evident clinical improvement, including improved fatigue, regular muscular strength and recovery as well as normal cognitive function without signs of systemic inflammation three years after COVID-19. Clinical improvement is reflected by a pattern of brain recovery along periventricular regions. This pattern is characterized by structural stabilization and increased connectivity starting in the brainstem as well as efficient neuronal recruitment and increased activation in the basal ganglia, with no evidence of neuronal injury. These results highlight the positive long-term recovery trajectory in post-COVID patients.

Source: Ravi Dadsena, Sophie Wetz, Anna Hofmann, Ana Sofia Costa, Sandro Romanzetti, Stella Andrea Lischewski, Christina Krockauer, Carolin Balloff, Ferdinand Binkofski, Jörg B Schulz, Kathrin Reetz, Julia Walders, Evidence of clinical and brain recovery in post-COVID-19 condition: a three-year follow-up study, Brain Communications, 2025;, fcaf366, https://doi.org/10.1093/braincomms/fcaf366 https://academic.oup.com/braincomms/advance-article/doi/10.1093/braincomms/fcaf366/8262587 (Full study available as PDF file)

Gulf War Illness, Fibromyalgia, Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID Overlap in Common Symptoms and Underlying Biological Mechanisms: Implications for Future Therapeutic Strategies

Abstract:

Although Gulf War Illness (GWI), fibromyalgia (FM), myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID have distinct origins, in this article we have reviewed evidence that these disorders comprise a group of so-called low-energy associated disorders with overlapping common symptoms underlying pathology.

In particular, evidence for mitochondrial dysfunction, oxidative stress, inflammation, immune dysregulation, neuroendocrine dysfunction, disrupted brain-gut-microbiome axis, apoptosis/ferroptosis and telomere shortening as common features in the pathogenesis of these disorders has been identified.

Given the role of coenzyme Q10 (CoQ10) in promoting normal mitochondrial function, as an antioxidant, antiinflammatory and antiapoptotic and antiferroptotic agent, there is a rationale for supplementary CoQ10 in the management of these disorders. The reported benefits of supplementary CoQ10 administration in GWI, FM, ME/CFS and long COVID have been reviewed; the potential benefit of supplementary CoQ10 in reducing telomere shortening and improving the efficiency of stem cell transfer relevant has also been identified as promising therapeutic strategies in these disorders.

This review advances beyond previous systematic reviews and consensus statements on overlapping similar symptoms and underlying biological pathomechanisms in these complex disorders.

Source: Mantle D, Domingo JC, Golomb BA, Castro-Marrero J. Gulf War Illness, Fibromyalgia, Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Long COVID Overlap in Common Symptoms and Underlying Biological Mechanisms: Implications for Future Therapeutic Strategies. Int J Mol Sci. 2025 Sep 17;26(18):9044. doi: 10.3390/ijms26189044. PMID: 41009608. https://www.mdpi.com/1422-0067/26/18/9044 (Full text)

Endometriosis and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Systematic Review and Meta-Analysis

Abstract:

Background/Objectives: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and endometriosis are debilitating conditions that share overlapping features of chronic inflammation and immune dysregulation, yet their epidemiological relationship remains poorly characterized. The objective of this study was to investigate the association between ME/CFS and endometriosis, examining shared risk factors, clinical correlates, and epidemiological patterns.

Methods: We conducted a systematic review and meta-analysis. Two independent reviewers screened 236 records after duplicate removal, with seventeen studies undergoing full-text review and thirteen meeting inclusion criteria for meta-analysis. Data were extracted using standardized forms and analyzed using random-effects models in R, with heterogeneity assessed using I2 statistics and the risk of bias evaluated using the JBI critical appraisal tool.

Results: Our meta-analysis of five studies (n = 2261 participants) revealed that women with endometriosis had 2.79-fold higher odds (95% CI: 2.00-3.89) of developing ME/CFS compared to controls. Similarly, our fixed-effects meta-analysis of two studies assessing the association of ME/CFS and endometriosis yielded a pooled OR of 2.52 (95% CI: 2.45-2.60, p < 0.001). There was minimal statistical heterogeneity (I2 = 0.0%, p > 0.7969) for both meta-analyses.

Conclusions: This study demonstrates a significant bidirectional association between endometriosis and ME/CFS, driven by shared mechanisms of immune dysregulation and chronic inflammation. Despite high heterogeneity, the consistent effect sizes support clinical vigilance for comorbidity. Future research should prioritize standardized diagnostic criteria to elucidate causal pathways. These findings underscore the need for integrated care approaches to address overlapping symptomatology in affected patients.

Source: Compton S, Alkabalan R, Cadet J, Mastali A, Ramdass PVAK. Endometriosis and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Systematic Review and Meta-Analysis. Diagnostics (Basel). 2025 Sep 15;15(18):2332. doi: 10.3390/diagnostics15182332. PMID: 41008704. https://www.mdpi.com/2075-4418/15/18/2332 (Full text)

The genetic architecture of fibromyalgia across 2.5 million individuals

Abstract:

Fibromyalgia is a common and debilitating chronic pain syndrome of poorly understood etiology. Here, we conduct a multi-ancestry genome-wide association study meta-analysis across 2,563,755 individuals (54,629 cases and 2,509,126 controls) from 11 cohorts, identifying the first 26 risk loci for fibromyalgia.

The strongest association was with a coding variant in HTT , the causal gene for Huntington’s disease. Gene prioritization implicated the HTT regulator GPR52 , as well as diverse genes with neural roles, including CAMKV ,  DCC ,  DRD2 / NCAM1 ,   MDGA2 , and CELF4 . Fibromyalgia heritability was exclusively enriched within brain tissues and neural cell types.

Fibromyalgia showed strong, positive genetic correlation with a wide range of chronic pain, psychiatric, and somatic disorders, including genetic correlations above 0.7 with low back pain, post-traumatic stress disorder and irritable bowel syndrome. Despite large sex differences in fibromyalgia prevalence, the genetic architecture of fibromyalgia was nearly identical between males and females.

This work provides the first robust genetic evidence defining fibromyalgia as a central nervous system disorder, thereby establishing a biological framework for its complex pathophysiology and extensive clinical comorbidities.

Source: Kerrebijn I, Bjornsdottir G, Arbabi K, Urpa L, Haapaniemi H, Thorleifsson G, Stefansdottir L, Frangakis S, Valliere J, Kunorozva L, Abner E, Ji C, Aagaard B, Bliddal H, Brunak S, Bruun MT, Didriksen M, Erikstrup C, Geirsson AJ, Gudbjartsson DF, Hansen TF, Jonsdottir I, Knight S, Knowlton KU, Mikkelsen C, Nadauld LD, Olafsdottir TA, Ostrowski SR, Pedersen OB, Saevarsdottir S, Skuladottir AT, Sørensen E, Stefansson H, Sulem P, Sveinsson OA, Thorlacius GE, Thorsteinsdottir U, Ullum H, Vikingsson A, Werge TM; Chronic Pain Genomics Consortium; FinnGen; DBDS Genomic Consortium; Estonian Biobank Research Team; Genes & Health Research Team; Saxena R, Stefansson K, Brummett CM, Glintborg B, Clauw DJ, Thorgeirsson TE, Williams FM, Sinnott-Armstrong N, Ollila HM, Wainberg M. The genetic architecture of fibromyalgia across 2.5 million individuals. medRxiv [Preprint]. 2025 Sep 19:2025.09.18.25335914. doi: 10.1101/2025.09.18.25335914. PMID: 41001472; PMCID: PMC12458511. https://pmc.ncbi.nlm.nih.gov/articles/PMC12458511/ (Full text available as PDF file)

The health and economic burden on family caregivers of persons with me/cfs diagnosis: a register data study from Norway

Abstract:

Background: Myalgic encephalomyelitis is an illness that affects the labor capability and need for services among those affected. Interventions and services for comparable illnesses are either inaccessible or ineffective for this group. Partners and parents may take on the caregiver burden, affecting their labor capability and health.

Objective: This study tested how limited treatment and support options available to persons with myalgic encephalomyelitis is associated to work participation, health, and use of public transfers among partners and parents of those affected.

Methods: We used administrative data from Norwegian patient registries from 2009 to 2018 on the diagnostic code G93.3, matched with population register income and health data from Statistics Norway. The dataset made it possible to identify a sample of partners and parents of persons with the diagnosis. The data included a control group drawn from the general population. We used optimal pair matching to construct separate datasets for pairs of matched individuals from the control group and the group of G93.3 cases, their mothers, fathers, and male and female partners.

Results: Having a partner or child with the G93.3 diagnosis contributes to strengthening traditional gender roles. Female family members worked less, and male family members worked more. Whereas female family members more often ended up depending on public transfers, male family members did so less often. All caregiver groups experienced increased personal health problems.

Conclusions: When tailoring support for the patient group, welfare services should consider how especially female family caregivers may be adversely affected by insufficient or inadequate support.

Source: Kielland, A., Liu, J. & Anthun, K.S. The health and economic burden on family caregivers of persons with me/cfs diagnosis: a register data study from Norway. Discov Public Health 22, 567 (2025). https://doi.org/10.1186/s12982-025-00936-5 https://link.springer.com/article/10.1186/s12982-025-00936-5 (Full text)

Burden of Disease in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Scoping Review

Abstract:

Objective: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a serious chronic and complex multi-system disease characterised by symptoms such as post-exertional malaise, fatigue, cognitive impairment and pain. Diagnosis is based on international consensus criteria, and no curative treatment is available. In the USA, its prevalence is estimated at 0.42% among adults, with women affected three times as often as men. Prevalence is expected to increase due to the COVID-19 pandemic. In addition to its severe symptoms, ME/CFS has a substantial economic impact. This scoping review aimed to systematically examine the global health, social and economic burden of ME/CFS.

Methods: We conducted a systematic literature search following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) guidelines in six databases and supplemented it with a citation search. We assessed study quality using a modified version of the Mixed Methods Appraisal Tool.

Results: We included 20 studies that assessed costs (n = 16), disability-adjusted life years (DALYs) (n = 3), employment rates (n = 1), and school attendance (n = 1) as indicators of disease burden. Reported costs per patient ranged from USD 2,916 to USD 119,611, with indirect costs accounting for the largest proportion. DALYs reported for the USA ranged from 0.714 million in 2016 to 5.77 million in 2022.

Conclusion: ME/CFS imposes a substantial health, social and economic burden of disease. Discrepancies in estimates are probably due to differences in study samples, methodologies, cost components, and healthcare systems. Because ME/CFS is assumed to be underdiagnosed, its true burden may be even higher.

Source: Vester P, Boudouroglou-Walter S, Schreyögg J, Wieting C, Blome C. Burden of Disease in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS): A Scoping Review. Appl Health Econ Health Policy. 2025 Sep 23. doi: 10.1007/s40258-025-01006-2. Epub ahead of print. PMID: 40986167. https://link.springer.com/article/10.1007/s40258-025-01006-2 (Full text)

Advancing Digital Precision Medicine for Chronic Fatigue Syndrome through Longitudinal Large-Scale Multi-Modal Biological Omics Modeling with Machine Learning and Artificial Intelligence

Abstract:

We studied a generalized question: chronic diseases like ME/CFS and long COVID exhibit high heterogeneity with multifactorial etiology and progression, complicating diagnosis and treatment. To address this, we developed BioMapAI, an explainable Deep Learning framework using the richest longitudinal multi-omics dataset for ME/CFS to date.

This dataset includes gut metagenomics, plasma metabolome, immune profiling, blood labs, and clinical symptoms. By connecting multi-omics to a symptom matrix, BioMapAI identified both disease- and symptom-specific biomarkers, reconstructed symptoms, and achieved state-of-the-art precision in disease classification.

We also created the first connectivity map of these omics in both healthy and disease states and revealed how microbiome-immune-metabolome crosstalk shifted from healthy to ME/CFS.

Source: Xiong R. Advancing Digital Precision Medicine for Chronic Fatigue Syndrome through Longitudinal Large-Scale Multi-Modal Biological Omics Modeling with Machine Learning and Artificial Intelligence. ArXiv [Preprint]. 2025 Jun 18:arXiv:2506.15761v1. PMID: 40980765; PMCID: PMC12447721. https://pmc.ncbi.nlm.nih.gov/articles/PMC12447721/ (Full text available as PDF file)