Tag: long covid vs ME/CFS

Shared autonomic phenotype of long COVID and myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

Introduction: Long COVID and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are relatively common and disabling multisystem disorders that share overlapping features, including post-infectious onset and similar clinical manifestations such as brain fog, fatigue, muscle pain, and dysautonomia with orthostatic intolerance. These similarities suggest that Long COVID and ME/CFS may share common pathophysiological mechanisms, though the underlying mechanisms remain poorly understood, partly due to the difficulty in quantifying many of the symptoms.

Materials and methods: This retrospective study evaluated Long COVID and pre-COVID ME/CFS patients who completed autonomic testing between 2018 and 2023 at the Brigham and Women’s Faulkner Hospital Autonomic Laboratory. The evaluations included autonomic tests (Valsalva maneuver, deep breathing, tilt-table test, and sudomotor function) with capnography and transcranial Doppler monitoring of cerebral blood flow velocity (CBFv) in the middle cerebral artery, neuropathic assessment through skin biopsies for small fiber neuropathy (SFN), invasive cardiopulmonary exercise testing (ICPET), and laboratory analyses covering metabolic, inflammatory, autoimmune, and hormonal profiles.

Results: A total of 143 Long COVID and 170 ME/CFS patients were analyzed and compared to 73 healthy controls and 290 patients with hypermobile Ehlers-Danlos syndrome (hEDS). Tests revealed extensive similarities between Long COVID and ME/CFS, including reduced orthostatic CBFv (92%/88% in Long COVID/ME/CFS), mild-to-moderate widespread autonomic failure (95%/89%), presence of SFN (67%/53%), postural tachycardia syndrome (POTS) (22%/19%), neurogenic orthostatic hypotension (15%/15%) and preload failure (96%/92%, assessed in 25/66 Long COVID/ME/CFS). Patients with hEDS exhibited more severe peripheral neurodegeneration compared to the other groups. Laboratory tests did not distinguish between the conditions.

Conclusion: Both Long COVID and ME/CFS demonstrate dysregulation in cerebrovascular blood flow, autonomic reflexes, and small fiber neuropathy, suggesting that these conditions may share a common underlying pathophysiology. However, differing distributions of findings in patients with hEDS raise the question of whether these conditions represent distinct but overlapping syndromes or reflect a shared underlying pathway. Further research is required to clarify the relationship between these conditions and the potential underlying pathophysiological mechanisms.

Source: Novak P, Systrom DM, Witte A, Marciano SP, Felsenstein D, Milunsky JM, Milunsky A, Krier J, Fishman MC. Shared autonomic phenotype of long COVID and myalgic encephalomyelitis/chronic fatigue syndrome. PLoS One. 2026 Jan 23;21(1):e0341278. doi: 10.1371/journal.pone.0341278. PMID: 41576003. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0341278 (Full text)

Distinct functional connectivity patterns in myalgic encephalomyelitis and long COVID patients during cognitive fatigue: a 7 Tesla task-fMRI study

Abstract:

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and long COVID are chronic debilitating illnesses featuring fatigue, post-exertional malaise (PEM) and neurocognitive deficits. Temporal correlation of neural activity between distinct brain regions, also referred to as functional connectivity (FC), can provide insights into how brain networks coordinate, at rest or during task. Therefore, we explored intrinsic FC correlates of cognitive fatigue in ME/CFS and long COVID patients during two Stroop-colour-word paradigms on 7 Tesla fMRI.

Methods: 450 sagittal volumes were acquired from seventy-eight participants: 32 patients with MECFS (pwME/CFS); 19 long COVID (pwLC) and 27 healthy controls (HC) during performance of baseline or Pre (before/during fatigue build-up) and repeat Post (fatigue set-in) Stroop tasks. Structural and functional data were analysed using the CONN toolbox.

Results: Regions of interest (ROI-to-ROI) analysis revealed significantly increased FC in subcortical regions in HC for Pre vs Post. Relative to HC, pwLC showed significantly reduced FC between nucleus accumbens and vermis 3 (p = 0.02) in Pre and increased FC in the prefrontal cortex and hippocampus (p = 0.02) in Post. pwME/CFS showed a significantly increased FC between the left cuneiform nucleus and right medulla (p = 0.03). Compared to HC, reduced FC was significant in pwLC during Pre, and between medulla and hippocampus (p = 0.04) and between nucleus accumbens and vermis (p = 0.001) during Post. Aberrant FC was significant for pwME/CFS in core networks during Pre. Core network FC to the cerebellum, amygdala, caudate and red nucleus correlated with symptom scores for cognition in both pwME/CFS and pwLC. Hippocampus and cerebellar FC correlated with duration of illness in pwME/CFS.

Conclusions: Our findings of reduced dopaminergic hippocampal-nucleus-accumbens connectivity imply blunted motivation and cognition. Extensive FC differences in subcortical and core networks in patient cohorts were detected relative to an increased FC in HC. High regional communication indicative of greater task engagement by HC was distinctive while FC differences in ME/CFS and long COVID patients indicated reduced and dysregulated regional coordination that may serve as candidate biomarkers of symptomatology in long COVID and ME/CFS.

Source: Inderyas M, Thapaliya K, Marshall-Gradisnik S, Barnden L. Distinct functional connectivity patterns in myalgic encephalomyelitis and long COVID patients during cognitive fatigue: a 7 Tesla task-fMRI study. J Transl Med. 2026 Jan 20. doi: 10.1186/s12967-026-07708-y. Epub ahead of print. PMID: 41559785. https://link.springer.com/article/10.1186/s12967-026-07708-y (Full text)

Virus-induced endothelial senescence as a cause and driving factor for ME/CFS and long COVID: mediated by a dysfunctional immune system

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID are two post-viral diseases, which share many common symptoms and pathophysiological alterations. Yet a mechanistic explanation of disease induction and maintenance is lacking. This hinders the discovery and implementation of biomarkers and treatment options, and ultimately the establishment of effective clinical resolution. Here, we propose that acute viral infection results in (in)direct endothelial dysfunction and senescence, which at the blood-brain barrier, cerebral arteries, gastrointestinal tract, and skeletal muscle can explain symptoms.

The endothelial senescence-associated secretory phenotype (SASP) is proinflammatory, pro-oxidative, procoagulant, primed for vasoconstriction, and characterized by impaired regulation of tissue repair, but also leads to dysregulated inflammatory processes. Immune abnormalities in ME/CFS and long COVID can account for the persistence of endothelial senescence long past the acute infection by preventing their clearance, thereby providing a mechanism for the chronic nature of ME/CFS and long COVID.

The systemic and tissue-specific effects of endothelial senescence can thus explain the multisystem involvement in and subtypes of ME/CFS and long COVID, including dysregulated blood flow and perfusion deficits. This can occur in all tissues, but especially the brain as evidenced by findings of reduced cerebral blood flow and impaired perfusion of various brain regions, post-exertional malaise (PEM), gastrointestinal disturbances, and fatigue.

Paramount to this theory is the affected endothelium, and the bidirectional sustainment of immune abnormalities and endothelial senescence. The recognition of endothelial cell dysfunction and senescence as a core element in the aetiology of both ME/CFS and Long COVID should aid in the establishment of effective biomarkers and treatment regimens.

Source: Nunes M, Kell L, Slaghekke A, Wüst RC, Fielding BC, Kell DB, Pretorius E. Virus-induced endothelial senescence as a cause and driving factor for ME/CFS and long COVID: mediated by a dysfunctional immune system. Cell Death Dis. 2026 Jan 9;17(1):16. doi: 10.1038/s41419-025-08162-2. PMID: 41513611; PMCID: PMC12789617. https://pmc.ncbi.nlm.nih.gov/articles/PMC12789617/ (Full text)

Overlapping Clinical Presentation of Long COVID and Postacute COVID-19 Vaccination Syndrome: Phenotypes, Severity, and Biomarkers

Abstract:

Background: Postacute sequelae of COVID-19 (PASC), also known as long COVID, and postacute COVID-19 vaccination syndrome (PACVS) present overlapping but distinct clinical challenges. We hypothesize that PASC and PACVS share clinical features but differ in symptom patterns and biomarker profiles. This study aims to identify differences in presentation and distinguish immunologic biomarkers relevant to general clinical practice.

Methods: This cross-sectional study analyzed 181 patients from a PASC clinic at Columbia University Irving Medical Center. Patients were divided into PASC with myalgic encephalomyelitis/chronic fatigue syndrome (MECFS), PASC without MECFS (LC), and PACVS groups. Prevalence and severity of self-reported symptoms, as well as immunologic abnormalities, were compared across groups.

Results: Fatigue was the most common symptom (Total: 88.95%; MECFS: 100.00%; PACVS: 92.86%; LC: 78.05%). The MECFS group generally reported more symptoms across all organ systems. The PACVS group reported higher rates of atypical chief complaints such as peripheral neuropathy (17.9%), tinnitus (7.1%), and rash (10.7%) compared to the other groups (P = <.01). Functional impairment was comparable between the MECFS and PACVS groups and less severe in the LC group. All groups had high rates of autoantibody positivity and cytokine elevation. The PACVS group showed significantly higher rates of anticardiolipin IgM (PACVS 42.9%, LC 11.6%; P = .02) and anti-U1-RNP (PACVS 21.4%, LC 2.3%; P = .04) positivity compared to the LC group.

Conclusions: PASC and PACVS share symptom overlap but exhibit distinct biomarker patterns, particularly elevated autoantibody levels in PACVS. These findings suggest autoimmune involvement, warranting further investigation for targeted therapies.

Source: Purpura L, Heisler T, Palmer S, Shah J, Graham A, Seo GY, Sturiza A, Javier X, Pinto G, Rosa A, Bosco J, Reis K, Sobieszczyk ME, Yin MT. Overlapping Clinical Presentation of Long COVID and Postacute COVID-19 Vaccination Syndrome: Phenotypes, Severity, and Biomarkers. Clin Infect Dis. 2026 Jan 9:ciaf624. doi: 10.1093/cid/ciaf624. Epub ahead of print. PMID: 41510565. https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaf624/8417802 (Full text)

Comparable Immune Alterations and Inflammatory Signatures in ME/CFS and Long COVID

Abstract:

Background: Chronic Fatigue Syndrome (CFS), also known as Myalgic Encephalomyelitis (ME), is a debilitating condition characterized by persistent fatigue and multisystemic symptoms, such as cognitive impairment, musculoskeletal pain, and post-exertional malaise. Recently, parallels have been drawn between ME/CFS and Long COVID, a post-viral syndrome following infection with SARS-CoV-2, which shares many clinical features with CFS. Both conditions involve chronic immune activation, raising questions about their immunopathological overlap.

Objectives: This study aimed to compare immune biomarkers between patients with ME/CFS or Long COVID and healthy controls to explore shared immune dysfunction.

Methods: We analyzed lymphocyte subsets, cytokine profiles, psychological status and their correlations in 190 participants, 65 with CFS, 54 with Long COVID, and 70 healthy controls.

Results: When compared to healthy subjects, results in both conditions were marked by lower levels of lymphocytes (CFS-2.472 × 109/L, p = 0.006, LC-2.051 × 109/L, p = 0.009), CD8+ T cells (CFS-0.394 × 109/L, p = 0.001, LC-0.404 × 109/L, p = 0.001), and NK cells (CFS-0.205 × 109/L, p = 0.001, LC-0.180 × 109/L, p = 0.001), and higher levels of proinflammatory cytokines such as IL-6 (CFS-3.35 pg/mL, p = 0.050 LC-4.04 pg/mL, p = 0.001), TNF (CFS-2.64 pg/mL, p = 0.023, LC-2.50 pg/mL, p = 0.025), IL-4 (CFS-3.72 pg/mL, p = 0.041, LC-3.45 pg/mL, p = 0.048), and IL-10 (CFS-2.29 pg/mL, p = 0.039, LC-2.25 pg/mL, p = 0.018).

Conclusions: Notably, there were no significant differences between CFS and Long COVID patients in the tested biomarkers. These results demonstrate that ME/CFS and Long COVID display comparable immune and inflammatory profiles, with no significant biomarker differences observed between the two groups.

Source: Petrov S, Bozhkova M, Ivanovska M, Kalfova T, Dudova D, Nikolova R, Vaseva K, Todorova Y, Aleksova M, Nikolova M, Taskov H, Murdjeva M, Maes M. Comparable Immune Alterations and Inflammatory Signatures in ME/CFS and Long COVID. Biomedicines. 2025 Dec 8;13(12):3001. doi: 10.3390/biomedicines13123001. PMID: 41463013. https://www.mdpi.com/2227-9059/13/12/3001 (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)

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)

Identification of Novel Reproducible Combinatorial Genetic Risk Factors for Myalgic Encephalomyelitis in the DecodeME Patient Cohort and Commonalities with Long COVID

Abstract:

Background: Myalgic encephalomyelitis (also known as ME/CFS or simply ME) has severely impacted the lives of tens of millions of people globally, but the disease currently has no accurate diagnostic tools or effective treatments. Identifying the biological causes of ME has proven challenging due to its wide range of symptoms and affected organs, and the lack of reproducible genetic associations across ME populations. This has prolonged misunderstanding, lack of awareness, and denial of the disease, further harming patients.

Methods: We used the PrecisionLife combinatorial analytics platform to identify disease signatures (i.e., combinations of 1-4 SNP-genotypes) that are significantly enriched in two cohorts of ME participants from DecodeME relative to controls from UK Biobank (UKB). We tested whether the number of these signatures possessed by an individual is significantly associated with increased prevalence of ME in a third disjoint cohort of DecodeME participants. We characterized a number of drug repurposing opportunities for a set of candidate core genes whose disease signatures had the strongest association with ME and which were linked to different mechanisms. We then tested gene overlap between the ME signatures identified and previous studies in long COVID, using two independent approaches to explore these shared genetic commonalities.

Results: We identified 22,411 reproducible disease signatures, comprising combinations of 7,555 unique SNPs, that are consistently associated with increased prevalence of ME in three disjoint patient cohorts. The count of reproducible signatures was significantly associated with increased prevalence of ME (p = 4×10-21), and participants with a top 10% signature count had an odds ratio of disease 1.64 times greater than participants with a bottom 10% signature count, confirming that these genetic signatures increase susceptibility for developing ME. These disease signatures map to 2,311 genes. We identified substantial overlap between the genes found by this combinatorial analysis and previous studies. We found that the 259 candidate core genes most strongly associated with ME are enriched in disease mechanisms including neurological dysregulation, inflammation, cellular stress responses and calcium signaling. We demonstrated that 76 out of 180 genes previously linked to long COVID in UKB and the US All of Us cohorts are also significantly associated with ME in the DecodeME cohort. These findings allowed identification of many existing and novel repurposing opportunities, including candidates linked to several genes with shared etiology for long COVID.

Conclusion: These findings provide further evidence that ME is a complex multisystemic condition where the risk of developing the disease has a very clear genetic and biological basis. They give a substantially deeper level of insight into the genetic risk factors and mechanisms involved in ME. The discovery of so many multiply reproducible genetic associations implies that ME is highly polygenic, which has important consequences for its future study and the delivery of clinical care to patients. The striking overlap in genes and mechanisms between long COVID and ME (76 / 180 long COVID genes tested) suggests the potential for development of novel or repurposed drug therapies that could be used to successfully treat either condition. However, although they share significant genetic commonalities, long COVID and ME appear to be best considered as partially overlapping but different diseases.

Source: Lu J, Sun W, Li S, Qu Y, Liu T, Guo S, Feng C, Yang T. Assessment of symptoms in myalgic encephalomyelitis/chronic fatigue syndrome: a comparative study of existing scales. Front Neurol. 2025 Nov 18;16:1618272. doi: 10.3389/fneur.2025.1618272. PMCID: PMC12668935. https://pmc.ncbi.nlm.nih.gov/articles/PMC12668935/ (Full text available as PDF file)

Differential Characteristics and Comparison Between Long-COVID Syndrome and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Abstract:

Long-COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome are disabling diseases characterised by ongoing fatigue, post-exertional malaise, cognitive impairment, and autonomic dysfunction. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome typically follows viral infections, whereas Long-COVID exclusively follows SARS-CoV-2 infection, with overlapping but distinct features. This review uses comprehensive searches of online databases to compare their clinical presentations, pathophysiologies, and treatments.

Both Long-COVID and ME/CFS appear to involve multifactorial mechanisms, including viral persistence, immune dysregulation, endothelial dysfunction, and autoimmunity, though their relative contributions remain uncertain. Symptom management strategies are consistent, however. Cognitive behaviour therapy has been successful, and there are minimal drug treatments. Graded exercise therapy occupies a contested place, recommending individualised pacing and multidisciplinary rehabilitation.

Common and exclusive mechanisms must be identified to formulate valuable therapies. A more significant body of research focusing on immune dysfunction as a pathogenic mechanism for advancing the disease and enabling more effective therapies and diagnostics is needed.

Source: Ivanovska M, Homadi MS, Angelova G, Taskov H, Murdjeva M. Differential Characteristics and Comparison Between Long-COVID Syndrome and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). Biomedicines. 2025 Nov 17;13(11):2797. doi: 10.3390/biomedicines13112797. PMID: 41301889; PMCID: PMC12650534. https://pmc.ncbi.nlm.nih.gov/articles/PMC12650534/ (Full text)

Urinary Peptidomic Profiling In Post-Acute Sequelae of SARS-CoV-2 Infection: A Case-Control Study

Abstract:

Post-acute sequelae of severe acute respiratory syndrome coronavirus 2-infection (PASC) is challenging to diagnose and treat, and its molecular pathophysiology remains unclear. Urinary peptidomics can provide valuable information on urine peptides that may enable improved and specified PASC diagnosis.
Using standardized capillary electrophoresis-MS, we examined the urinary peptidomes of 50 patients with PASC 10 months after COVID-19 and 50 controls, including healthy individuals (n = 42) and patients with non-COVID-19-associated myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) (n = 8).Based on peptide abundance differences between cases and controls, we developed a diagnostic model using a support vector machine. The abundance of 195 urine peptides among PASC patients significantly differed from that in controls, with a predominant abundance of collagen alpha chains. This molecular signature (PASC195) effectively distinguished PASC cases from controls in the training set (AUC of 0.949 [95% CI 0.900–0.998; p < 0.0001]) and independent validation set (AUC of 0.962 [95% CI 0.897–1.00]; p < 0.0001]). In silico assessment suggested exercise, GLP-1RAs and mineralocorticoid receptor antagonists (MRAs) as potentially efficacious interventions. We present a novel and non-invasive diagnostic model for PASC. Reflecting its molecular pathophysiology, PASC195 has the potential to advance diagnostics and inform therapeutic interventions.

Statement of Significance of the Study

Despite the recent emergence of omics-derived candidates for post-acute sequelae of SARS-CoV-2 infection (PASC), the pending validation of proposed markers and lack of consensus result in the continuous reliance on symptom-based criteria, being subject to diagnostic uncertainties and potential recall bias. Building upon prior findings of renal involvement in acute COVID-19 pathophysiology and PASC-associated alterations, we hypothesized that the use of urinary peptides for PASC-specific biomarker discovery, unlike conventional specimens that have been utilized thus far, may offer complementary information on putative disease mechanisms.

In the present study, 195 significantly expressed peptides were used to form a classifier termed PASC195, which effectively discriminated PASC from non-PASC (p < 0.0001), including healthy individuals and non-COVID-19-associated myalgic encephalomyelitis/chronic fatigue syndrome, in both the derivation (n = 60) and an independent validation set (n = 40). The peptidome profile associated with PASC was consistent with a shift in collagen turnover, with most PASC195 peptides derived from alpha chains. Ongoing inflammatory responses, hemostatic imbalances, and endothelial damage were indicated by cross-sectional variations in endogenous peptide excretion.

Source: Gülmez D, Siwy J, Kurz K, Wendt R, Banasik M, Peters B, Dudoignon E, Depret F, Salgueira M, Nowacki E, Kurnikowski A, Mussnig S, Krenn S, Gonos S, Löffler-Ragg J, Weiss G, Mischak H, Hecking M, Schernhammer E, Beige J; UriCoV Working Group. Urinary Peptidomic Profiling In Post-Acute Sequelae of SARS-CoV-2 Infection: A Case-Control Study. Proteomics. 2025 Nov 21:e70074. doi: 10.1002/pmic.70074. Epub ahead of print. PMID: 41273049. https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.70074 (Full text)