Tag: 2025

Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling and heterogeneous disorder lacking validated biomarkers or targeted therapies. Clinical variability and elusive pathophysiology hinder progress toward effective diagnostics and treatment. Core symptoms include persistent fatigue, post-exertional malaise, unrefreshing sleep, cognitive dysfunction, and pain. We tested whether an individualized, “n-of-1” genomic and transcriptomic framework combined with comprehensive, participant-informed phenotyping could reveal molecular signatures unique to each patient.

Methods: Clinical-grade whole-genome sequencing was conducted in 31 affected individuals from 25 families, with RNA-seq performed on a subset (16 affected, 7 unaffected) using blood samples. Machine-learning assisted variant triage, transcript-aware damage prediction, and expert review identified pathogenic or likely pathogenic variants in 8 of 25 probands (32%) and 12 of 31 affected individuals (39%).

Results: Findings revealed marked genetic heterogeneity, including large-effect rare and more common variants. Implicated pathways included ATP generation, oxidative phosphorylation, fatty acid oxidation; regulation of glycolysis, amino acid and lipid turnover; ion and solute homeostasis; synaptic signaling, excitability, oxygen transport, and muscle integrity, resilience, and post-exertional recovery; previously implicated processes. Plausible modifiers influencing disease onset, severity, and relapsing–remitting patterns and possibly explaining intrafamilial variability and inconsistent findings across studies, were also identified. Despite gene-level diversity, downstream effects converged on impaired energy production, reduced stress resilience, and vulnerability to post-exertional metabolic failure; disruptions consistent with core ME/CFS symptoms of exertional intolerance, cognitive fog, and fatigue.

Conclusions: Our findings support the hypothesis that at least a subset of ME/CFS cases represent distinct molecular disorders that converge on shared physiological pathways. Validation in larger, more diverse cohorts will be essential to test this hypothesis and establish generalizability, but increase size alone is unlikely to resolve causation in a disorder defined by rarity, heterogeneity, and molecular complexity. We suggest that progress will require experimental designs that integrate individual-level genomic data with deep, participant-informed deep phenotyping, capturing the combined effects of rare and common variants and environmental modifiers on disease expression and progression. We believe that an individualized precision medicine framework will uncover molecular drivers and modifiers of ME/CFS previously obscured by heterogeneity, enabling biologically informed stratification, improved trial design, biomarker discovery, and targeted interventions in this historically neglected condition.

Source: Birch CL, Wilk BM, Gajapathy M, Hutchins SD, Kaur G, Brown DM, Mamidi TKK, Hodgin KS, Turgut A, Younger JW, Worthey EA. Uncovering the genetic architecture of ME/CFS: a precision approach reveals impact of rare monogenic variation. J Transl Med. 2025 Dec 24. doi: 10.1186/s12967-025-07586-w. Epub ahead of print. PMID: 41444612. https://link.springer.com/article/10.1186/s12967-025-07586-w (Full text available as PDF file)

Testing the Feasibility of a Self-Help Intervention That Includes Lymphatic Drainage to Reduce Fatigue-Related Symptoms Among Patients with Long COVID in General Practice: Experiences from Our Randomized Controlled Trial (RCT)

Abstract:

Introduction: Long COVID-related fatigue affects a large number of people across the world, with increasing numbers of people experiencing long-term disability as a consequence. We tested the feasibility of a self-help version of a manual osteopathic approach initially developed for people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) to treat people with long COVID-related fatigue.

Methods: Our feasibility study assessed recruitment into a 1:1 randomized controlled trial (RCT) to receive (i) self-help intervention (self-massage, mobility, flexibility, and breathing exercises, and alternating cold and warm packs to the top of the spine) or (ii) wait-list control group. Follow-up was assessed by online surveys at 3 and 6 months (indicating retention). Verbal feedback was obtained from participants.

Results: Of the 138 eligible survey participants, 126 (90.6%) agreed to participate in two RCTs, achieving the required sample size of 100. Follow-up rates of 79.3% and 59.4% were achieved at 3 and 6 months, respectively. Improvements in Chalder Fatigue Questionnaire (CFQ) scores were observed in both groups between 0 and 3 months (- 4.6 and – 2.9, respectively), to a greater degree in the intervention group (p = 0.01). Feedback showed a cohort keen to engage with the intervention, although some found the intervention onerous at times.

Conclusions: We have reported the results of a feasibility study examining a potentially beneficial intervention for people with long COVID. There were indications of benefit in a patient group with often intractable symptoms. Based on this feasibility study, we believe that the low-cost self-help intervention in isolation could help support fatigue reduction in some people. This has implications for the treatment of both long COVID and ME/CFS.

Source: Riste L, Perrin R, Mulholland T, Hann M, McDonald O, Heald A. Testing the Feasibility of a Self-Help Intervention That Includes Lymphatic Drainage to Reduce Fatigue-Related Symptoms Among Patients with Long COVID in General Practice: Experiences from Our Randomized Controlled Trial (RCT). Infect Dis Ther. 2025 Dec 24. doi: 10.1007/s40121-025-01287-z. Epub ahead of print. PMID: 41442105. https://link.springer.com/article/10.1007/s40121-025-01287-z (Full text)

Metabolomics-Based Machine Learning Diagnostics of Post-Acute Sequelae of SARS-CoV-2 Infection

Abstract:

Background: COVID-19 has taken millions of lives and continues to affect people worldwide. Post-Acute Sequelae of SARS-CoV-2 Infection (also known as Post-Acute Sequelae of COVID-19 (PASC) or more commonly, Long COVID) occurs in the aftermath of COVID-19 and is poorly understood despite its widespread effects.

Methods: We created a machine-learning model that distinguishes PASC from PASC-similar diseases. The model was trained to recognize PASC-dysregulated metabolites (p ≤ 0.05) using molecular descriptors.

Results: Our multi-layer perceptron model accurately recognizes PASC-dysregulated metabolites in the independent testing set, with an AUC-ROC of 0.8991, and differentiates PASC from myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Lyme disease, postural orthostatic tachycardia syndrome (POTS), and irritable bowel syndrome (IBS). However, it was unable to differentiate fibromyalgia (FM) from PASC.

Conclusions: By creating and testing models pairwise on each of these diseases, we elucidated the unique strength of the similarity between FM and PASC relative to other PASC-similar diseases. Our approach is unique to PASC diagnosis, and our use of molecular descriptors enables our model to work with any metabolite where molecular descriptors can be identified, as these descriptors can be generated and compared for any metabolite. Our study presents a novel approach to PASC diagnosis that partially circumvents the lengthy process of exclusion, potentially facilitating faster interventions and improved patient outcomes.

Source: Cai E, Kouznetsova VL, Tsigelny IF. Metabolomics-Based Machine Learning Diagnostics of Post-Acute Sequelae of SARS-CoV-2 Infection. Metabolites. 2025 Dec 17;15(12):801. doi: 10.3390/metabo15120801. PMID: 41441042; PMCID: PMC12734907. https://pmc.ncbi.nlm.nih.gov/articles/PMC12734907/ (Full text)

Diagnosis of chronic fatigue syndrome using beat-to-beat autonomic measurements

Abstract:

Background: An artificial intelligence (AI) pipeline was used to differentiate patients suffering from Chronic Fatigue Syndrome (CFS) from healthy controls (HC) based on high-frequency, large-scale data obtained using beat-to-beat measurement of the autonomic nervous system (ANS) and cardiovascular function.

Methods: This prospective, case-control study included a cohort of 112 CFS patients and 61 HCs examined. Heart rate (HR), high-frequency R-to-R interval (HF RRI), diastolic blood pressure (dBP), stroke volume (SV), and SV index (SV/FFM) were measured using the Task Force Monitor. A novel sequential learning approach was applied: first, a Transformer model was trained, followed by an XGBoost classifier that learned from the errors of the Transformer. Matthews correlation coefficient (MCC), accuracy, and Area Under the Receiver Operating Characteristic Curve (ROC AUC) were assessed. Model classifications were explained globally.

Results: The applied classifier achieved a subject-level accuracy of 0.89, an MCC of 0.79, and an AUC of 1.00. Lower values of beat-to-beat difference in HR and raw HF RRI (indicating reduced cardiac vagal tone) and higher values of dBP difference (more beat-to-beat increases, indicating higher sympathetic vascular tone) were related to being more likely classified as CFS patients. Low values of SV difference and low values of SV/FFM (both indicating less effective cardiac hemodynamics) were related to being more likely classified as CFS patients.

Conclusions: The AI-driven classifier demonstrates remarkable proficiency in distinguishing between patients with CFS and HC. By leveraging this automated pipeline, beat-to-beat measurements of the ANS can significantly enhance the objective assessment of CFS diagnosis.

Source: Kujawski S, Tabisz H, Morten KJ, Modlińska A, Słomko J, Zalewski P. Diagnosis of chronic fatigue syndrome using beat-to-beat autonomic measurements. J Transl Med. 2025 Dec 23;23(1):1413. doi: 10.1186/s12967-025-07433-y. PMID: 41437251; PMCID: PMC12729017. https://pmc.ncbi.nlm.nih.gov/articles/PMC12729017/ (Full text)

Evaluation of an online patient education program for children and young people with ME/CFS and their parents within the BAYNET FOR MECFS Study

Abstract:

Background: ME/CFS (Myalgic Encephalomyelitis/Chronic Fatigue Syndrome) poses challenges for affected children and young people (CYP) and their parents. There is often a lack of knowledge about the illness. Education programs can help address this by providing knowledge and supporting the independent management of the condition. For this reason, two online education programs – one for affected CYP and one for their parents – were developed, implemented, and evaluated in terms of acceptance, format, and benefits.

Methods: 24 CYP aged of up to 20 years with ME/CFS and their parents were recruited for this study. Of these 22 CYP with ME/CFS and 20 parents participated in the online education program. After development and conduction of the programs, six affected CYP were interviewed using written questions, which were answered via an audio device. Furthermore, 6 semi-structured interviews were obtained with parents. All parents also received an online questionnaire to evaluate the program. Data were analyzed using both quantitative and qualitative methods.

Results: Both CYP and their parents expressed overall satisfaction with the program highlighting aspects such as knowledge acquisition or reinforcement and, importantly, the opportunity to connect with other affected CYP or their parents. The online format was also perceived very positively.

Discussion: The online education program met the expectations and needs of both affected CYP and parents regarding content and format. It facilitated exchange and provided practical knowledge. In this format, the online program appears to be a valuable component of care for those affected.

Source: Keicher F, Thomann J, Erlenwein J, Schottdorf M, Wiejaczka K, Reiter NL, Scholz-Schwärzler N, Vogel B, Stojanov S, Augustin S, Saramandic M, Dettmer K, Englbrecht S, Jaeschke R, Schanz L, Dodel V, Zipper C, Schieweck N, Ernst G, Behrends U, Spiegler J. Evaluation of an online patient education program for children and young people with ME/CFS and their parents within the BAYNET FOR MECFS Study. Neuropediatrics. 2025 Dec 23. doi: 10.1055/a-2773-9655. Epub ahead of print. PMID: 41435903. https://www.thieme-connect.com/products/ejournals/abstract/10.1055/a-2773-9655 (Full text available as PDF file)

A patient perspective on enduring symptoms – the unmet need

Abstract:

This short paper illustrates the lived experience of individuals with severe enduring symptoms: chronic, often debilitating conditions for which no clear medical explanation currently exists. Drawing on qualitative interviews, the paper highlights the profound suffering, isolation, and lack of medical support experienced by this underserved population. It examines the systemic barriers to care, including stigma, the absence of follow-up services, and the traumatising nature of some healthcare encounters, which can lead to healthcare avoidance even in the face of potentially life-threatening symptoms. It concludes with a call for improved training for clinicians, increased capacity within NHS services, and ring-fenced funding for biomedical research.
Source: Katharine Cheston. A patient perspective on enduring symptoms – the unmet need. Future Healthcare Journal: Volume 12, Issue 4, 2025, 100465. ISSN 2514-6645. https://doi.org/10.1016/j.fhj.2025.100465. https://www.sciencedirect.com/science/article/pii/S2514664525002462 (Full text)

Long COVID: a long road ahead

Abstract:

The SARS-CoV-2 pandemic caused an estimated 400 million people worldwide to experience Long COVID and post-COVID complications leading to significant chronic illness and disability with its devastating physical, societal and economic consequences. Since post-acute infectious syndromes have not been given adequate consideration prior to the pandemic, many millions of people with Long COVID worldwide have been left disabled as currently available therapies are largely symptomatic and only partially effective.

A case of a previously healthy woman with Long COVID and post-COVID autonomic dysfunction and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is presented here from the perspective of a physician-patient relationship and a broader context of medical care and public health. Immunologic and autonomic mechanistic factors and therapies as these relate to Long COVID are highlighted.

Complexities and issues pertaining to patient care, public health and education of neurologists and other specialists regarding Long COVID, dysautonomia and ME/CFS diagnosis and treatment are discussed, in conjunction with the need to develop and diversify effective therapies for people living with these highly disabling conditions.

Source: Blitshteyn S. Long COVID: a long road ahead. Oxf Open Immunol. 2025 Dec 13;6(1):iqaf010. doi: 10.1093/oxfimm/iqaf010. PMID: 41426345; PMCID: PMC12718103. https://pmc.ncbi.nlm.nih.gov/articles/PMC12718103/ Full text)

Inefficient energy consumption is related to post exertional malaise during cardiopulmonary exercise testing in long COVID

Abstract:

Background: Dyspnea, fatigue and post-exertional malaise (PEM) are hallmark features of long Covid and emerging evidence suggests that abnormal energy metabolism may contribute to these symptoms. A cardiopulmonary exercise test (CPET) provides a detailed physiologic assessment of ventilatory and cardiovascular function and can offer insights into metabolic substrate utilization energy at rest and during exertion. Our aim was to evaluate patterns of energy metabolism at rest and during exercise during a CPET in patients with long Covid.

Methods: We conducted a cross-sectional study of consecutive non-selected patients that had been referred for a CPET. We included two groups: a long COVID and a control group. The CPET was performed on a cycle ergometer and we measured standard variables including oxygen uptake (V̇O₂), respiratory exchange ratio (RER), breathing reserve, heart rate, O2 pulse, and anaerobic threshold. We used RER to calculate indirect calorimetry estimating the use of carbohydrates and fat at rest and exertion. We analyzed the association between long COVID symptom severity symptoms including fatigue and post-exertional malaise (PEM) with patterns of energy consumption. We used logistic regression and area under the receiver operating characteristic curve to determine which CPET variables were most associated with long COVID.

Results: CPET results were analyzed for 50 patients who met the definition of long COVID and 45 patients controls. Long COVID patients and controls had similar peak V̇O₂, heart rate on exertion and V̇O₂ at anaerobic threshold. Seventy-three percent of patients with long COVID had predominant energy use of carbohydrates rather than fat at rest compared to 20% of controls. In multivariable models the odds ratio of using fat as energy source at rest was 0.99; 95% CI 0.99–0.99; p = 0.04. Patients with long COVID and severe fatigue as well as severe PEM had higher usage of carbohydrates (p < 0.01) and similar use of fat.

Conclusion: Patients with long COVID use energy inefficiently and this pattern could serve as a diagnostic feature in certain presentations of long COVID.

Source: Leonardo Tamariz, Brian Garnet, Santiago Avecillas et al. Inefficient energy consumption is related to post exertional malaise during cardiopulmonary exercise testing in long COVID, 15 December 2025, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-8072121/v1] https://www.researchsquare.com/article/rs-8072121/v1 (Full text)

Altered brain tissue microstructure and neurochemical profiles in long COVID and recovered COVID-19 individuals: A multimodal MRI study

Abstract:

Background: Diverse neurological symptoms are experienced by long COVID and COVID-19 recovered individuals. However, the long-term effects of SARS-CoV-2 in the brain of both groups are underexplored. This study aimed to investigate changes in tissue microstructural and brain neurochemical levels in long COVID and recovered COVID-19 patients compared to healthy controls.

Methods: We recruited 47 participants (long COVID = 19, COVID-recovered healthy controls = 12, and healthy controls without COVID-19 infection = 16) who underwent 3T MRI scans. We acquired T1 and T2 weighted images to assess myelin signal, diffusion weighted images to assess tissue microstructure, and magnetic resonance spectroscopy data to estimate brain neurochemical levels.

Findings: Our multimodal MRI study showed altered T1w/T2w signal between long COVID vs COVID-recovered-healthy controls, long COVID vs healthy controls, and COVID-recovered-healthy controls vs healthy controls. Furthermore, T1w/T2w signal intensity was significantly correlated with physical and cognitive function. Diffusion weighted imaging also showed altered tissue microstructure in these three group comparisons. However, brain neurochemicals were only significantly different between long COVID vs COVID-recovered-healthy controls.

Interpretation: This is one of the first studies to report different myelin signal and brain neurochemical changes between long COVID, COVID-recovered-healthy controls, and healthy controls without SARS-CoV-2 infection. These brain changes provide compelling evidence for the long-term effects of SARS-CoV-2 on brain function.

Source: Thapaliya K, Marshall-Gradisnik S, Inderyas M, Barnden L. Altered brain tissue microstructure and neurochemical profiles in long COVID and recovered COVID-19 individuals: A multimodal MRI study. Brain Behav Immun Health. 2025 Nov 25;50:101142. doi: 10.1016/j.bbih.2025.101142. PMID: 41404601; PMCID: PMC12704066. https://pmc.ncbi.nlm.nih.gov/articles/PMC12704066/ (Full text)

Mapping the complexity of ME/CFS: Evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disorder with undefined mechanisms, no diagnostic tools and treatments. To investigate concurrent system dysfunctions, we recruited age- and sex-matched ME/CFS patients and healthy controls for a multimodal analysis of energy metabolism, immune profiles, and plasma proteomics.

Immune cells from ME/CFS patients show elevated adenosine monophosphate (AMP) and adenosine diphosphate (ADP) with a reduced ATP/ADP ratio, indicating decreased ATP generation and cellular energy stress. Immune profiling reveals skewing toward less mature effector subsets of CD4+, CD8+, and γδ T cells, with reduced CD1c+CD141– conventional DC type 2 and CD56lowCD16+ terminal natural killer cells.

Elevated levels of plasma proteins associated with thrombus formation and vascular reactivity may contribute to the endothelial dysfunction observed in ME/CFS patients. Classification and regression tree modeling identifies variables with strong predictive potential for ME/CFS. Together, this study provides insights into the somatic symptoms and underlying biology of ME/CFS.

Source: Heng B, Gunasegaran B, Krishnamurthy S, Bustamante S, Pires AS, Chow S, Ahn SB, Paul-Heng M, Maciver Y, Smith K, Tran DP, Howley PP, Bilgin AA, Sharland A, Schloeffel R, Guillemin GJ. Mapping the complexity of ME/CFS: Evidence for abnormal energy metabolism, altered immune profile, and vascular dysfunction. Cell Rep Med. 2025 Dec 16;6(12):102514. doi: 10.1016/j.xcrm.2025.102514. PMID: 41406947. https://www.sciencedirect.com/science/article/pii/S2666379125005877 (Full text)