Summary:
Source: Zhang, Bingyu et al. Long COVID associated with SARS-CoV-2 reinfection among children and adolescents in the omicron era (RECOVER-EHR): a retrospective cohort study. The Lancet Infectious Diseases, Volume 0, Issue 0, Online first; September 30, 2025. https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(25)00476-1/fulltext (Full text)
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)
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)
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)
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)
Abstract:
Background: Fatigue is the most common symptom of Long COVID (LC), defined by persistent or newly emerging symptoms that develop at least three months after an initial SARS-CoV-2 infection, in the absence of other identifiable cause. This study investigates the prevalence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) as a potential comorbidity of LC.
Methods: The study enrolled 37 adult controls with no documented SARS-CoV-2 infection and 32 individuals with a history of infection, categorized as LC-yes (with LC symptoms) and LC-no (without LC symptoms). ME/CFS diagnosis was based on the International Consensus Criteria (ICC).
Results: Among LC-yes cases, the most frequently reported symptoms included post-exertional malaise (PEM); neurosensory, perceptual, or motor disturbances; cognitive impairment; sleep disturbances; pain; impaired thermoregulation; and flu-like symptoms, all occurring significantly more than in the LC-no or control groups. All individuals in the LC-yes group reported PEM. ME/CFS was diagnosed in three LC-yes cases (18.8%), one LC-no case (6.7%), and four control subjects (10.8%), with no statistically significant differences observed among groups. Experiencing more than six symptoms during acute infection, such as fatigue, loss of taste or smell, headache, fever, cough, myalgia, sore throat, shortness of breath, rhinorrhea, and diarrhea, was associated with a twofold higher risk of developing LC.
Conclusion: A substantial proportion of LC-yes individuals experienced PEM; neurosensory, perceptual, or motor disturbances; cognitive impairment; and sleep disturbances, with rates significantly exceeding those in the LC-no and control groups. Nevertheless, only a minority of LC-yes cases (18.8%) satisfied criteria for the ME/CFS, and the prevalence did not significantly differ from LC-no and controls. These findings suggest that while many symptoms of LC overlap with those of ME/CFS, only a subset of LC cases meet established ME/CFS diagnostic criteria.
Source: Kouyoumdjian JA, Yamamoto LA, Graca CR. Exploration of Intersections and Divergences of Long COVID and Chronic Fatigue Syndrome. Cureus. 2025 Aug 20;17(8):e90607. doi: 10.7759/cureus.90607. PMID: 40978825; PMCID: PMC12448662. https://pmc.ncbi.nlm.nih.gov/articles/PMC12448662/ (Full text)
Abstract:
COVID-19 has increased the likelihood of cognitive impairment in patients with post-acute sequelae of COVID-19 (PASC). There is a lack of direct evidence regarding the working memory performance of mild patients during the recovery period. This study employed functional near-infrared spectroscopy (fNIRS) to construct a mixed effects model for PASC patients performing the N-back task, assessing brain activation levels and brain connectivity.
PASC patients exhibited abnormally low activation in the parietal lobe (β = −0.21) and abnormally high activation in the occipital lobe (β = 0.40). There was a significant reduction in brain connectivity within the frontal–parietal and frontal–occipital networks.
These findings suggest that PASC patients experience impaired fronto-parietal network connectivity, rely more on the visual cortex to compensate for executive function deficits, and use this as a compensatory mechanism to reduce overall cerebral blood oxygenation. This study provides evidence of altered brain activation patterns in PASC patients during the recovery period due to cognitive impairment.
Source: , , , et al., “ Abnormal Brain Activation Patterns in Patients With Post-Acute Sequelae of COVID-19 (PASC) During Recovery: A fNIRS Study,” Journal of Biophotonics (2025): e202500206, https://doi.org/10.1002/jbio.202500206. https://onlinelibrary.wiley.com/doi/epdf/10.1002/jbio.202500206
Abstract:
Background: Incidence estimates of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, also known as long COVID, have varied across studies and changed over time. We estimated long COVID incidence among adult and pediatric populations in 3 nationwide research networks of electronic health records (EHRs) participating in the RECOVER (Researching COVID to Enhance Recovery) Initiative using different classification algorithms (computable phenotypes).
Methods: This EHR-based retrospective cohort study included adult and pediatric patients with documented acute SARS-CoV-2 infection and 2 control groups: contemporary coronavirus disease 2019 (COVID-19)-negative and historical patients (2019). We examined the proportion of individuals identified as having symptoms or conditions consistent with probable long COVID within 30-180 days after COVID-19 infection (incidence proportion). Each network (the National COVID Cohort Collaborative [N3C], National Patient-Centered Clinical Research Network [PCORnet], and PEDSnet) implemented its own long COVID definition. We introduced a harmonized definition for adults in a supplementary analysis.
Results: Overall, 4% of children and 10%-26% of adults developed long COVID, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 1.5% in children and ranged from 5% to 6% among adults, representing a lower-bound incidence estimation based on our control groups. Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants.
Conclusions: Our findings indicate that preventing and mitigating long COVID remains a public health priority. Examining temporal patterns and risk factors for long COVID incidence informs our understanding of etiology and can improve prevention and management.
Source: Mandel H, Yoo YJ, Allen AJ, Abedian S, Verzani Z, Karlson EW, Kleinman LC, Mudumbi PC, Oliveira CR, Muszynski JA, Gross RS, Carton TW, Kim C, Taylor E, Park H, Divers J, Kelly JD, Arnold J, Geary CR, Zang C, Tantisira KG, Rhee KE, Koropsak M, Mohandas S, Vasey A, Mosa ASM, Haendel M, Chute CG, Murphy SN, O’Brien L, Szmuszkovicz J, Guthe N, Santana JL, De A, Bogie AL, Halabi KC, Mohanraj L, Kinser PA, Packard SE, Tuttle KR, Hirabayashi K, Kaushal R, Pfaff E, Weiner MG, Thorpe LE, Moffitt RA. Long COVID Incidence Proportion in Adults and Children Between 2020 and 2024: An Electronic Health Record-Based Study From the RECOVER Initiative. Clin Infect Dis. 2025 Jul 18;80(6):1247-1261. doi: 10.1093/cid/ciaf046. PMID: 39907495; PMCID: PMC12272849. https://pubmed.ncbi.nlm.nih.gov/39907495/
Abstract:
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Long-COVID are complex, disabling conditions that have emerged as significant public health challenges, affecting millions worldwide. Despite their growing prevalence, effective diagnostics and treatments remain limited, largely due to an incomplete understanding of their underlying pathophysiology. Both conditions share hallmark symptoms of chronic fatigue, cognitive dysfunction, and postexertional malaise, but their biological underpinnings remain to be elucidated. Neuroimaging offers a promising, noninvasive window into the brain’s metabolic landscape and has the potential to uncover objective biomarkers for these conditions.
In this mini review, we highlight recent advancements in metabolic neuroimaging, particularly positron emission tomography and magnetic resonance imaging/magnetic resonance spectroscopy, that reveal alterations in glucose and oxygen metabolism, neurotransmitter balance, and oxidative stress. These insights point toward shared disruptions in brain energy metabolism and neuroinflammatory processes, which may underlie the persistent symptoms in both ME/CFS and Long-COVID.
Importantly, while some findings overlap, inconsistencies in metabolite profiles between ME/CFS and Long-COVID underscore the need for further stratification and longitudinal research. Standardizing definitions, such as identifying Long-COVID patients who meet ME/CFS diagnostic criteria, could help improve study comparability.
By summarizing current imaging evidence, this review underscores the potential of neuroimaging to identify imaging biomarkers to advance the clinical diagnosis of Long-COVID and identify therapeutic targets for treatment development. As we continue to face the growing burden of Long-COVID and ME/CFS, metabolic imaging may serve as a powerful tool to bridge gaps in knowledge and accelerate progress toward effective care.
Source: Zhu Y, Quan P, Yamazaki T, Norweg A, Natelson B, Xu X. Metabolic neuroimaging of myalgic encephalomyelitis/chronic fatigue syndrome and Long-COVID. Immunometabolism (Cobham). 2025 Sep 12;7(4):e00068. doi: 10.1097/IN9.0000000000000068. PMID: 40958852; PMCID: PMC12435251. https://pmc.ncbi.nlm.nih.gov/articles/PMC12435251/ (Full text)
Abstract:
Background. Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods. We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics “recovery factor”, trained on patient-reported physical function survey scores. Immune profiling data included PBMC transcriptomics, serum O-link and plasma proteomics, plasma metabolomics, and blood CyTOF protein levels. Recovery factor scores were tested for association with LC, disease severity, clinical parameters, and immune subset frequencies. Enrichment analyses identified biologic pathways associated with recovery factor scores.
Results. LC participants had lower recovery factor scores compared to recovered participants. Recovery factor scores predicted LC as early as hospital admission, irrespective of acute COVID-19 severity. Biologic characterization revealed increased inflammatory mediators, elevated signatures of heme metabolism, and decreased androgenic steroids as predictive and ongoing biomarkers of LC. Lower recovery factor scores were associated with reduced lymphocyte and increased myeloid cell frequencies. The observed signatures are consistent with persistent inflammation driving anemia and stress erythropoiesis as major biologic underpinnings of LC.
Conclusion. The multi-omics recovery factor identifies patients at risk of LC early after SARS-CoV-2 infection and reveals LC biomarkers and potential treatment targets.
Trial Registration. ClinicalTrials.gov NCT04378777.
Funding. This study was funded by NIH, NIAID and NSF.
Source: Gisela Gabernet, Leying Guan, Lauren I.R. Ehrlich, et al. A multi-omics recovery factor predicts long COVID in the IMPACC study. J Clin Invest. September 9, 2025. https://doi.org/10.1172/JCI193698. https://www.jci.org/articles/view/193698/ (Full study available as PDF file)