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Genetic Landscape and Mitochondrial Metabolic Dysregulation in Patients Suffering From Severe Long COVID.

Long COVID represents a significant global health challenge with an unclear etiology. Alongside accumulating evidence of mitochondrial dysfunction in patients with acute SARS-CoV-2 infection, a symptomatic overlap exists between long COVID and mitochondrial disorders. However, the genetic underpinnings of mitochondrial dysfunction in long COVID have not been previously explored. We employed whole genome sequencing to analyze 13 patients with severe long COVID to identify genetic defects related to mitochondrial function. We performed extracellular bioenergetics flux analysis on peripheral blood mononuclear cells and proteomics to evaluate cellular bioenergetics and compared the results to those of healthy controls. Our investigation identified 10 variants classified as pathogenic or likely pathogenic and 83 variants of unknown significance affecting a wide range of mitochondria-associated biological functions. Bioenergetics flux analysis in peripheral blood mononuclear cells revealed an altered ATP production rate in four long COVID patients compared to healthy controls. This study presents initial evidence of a potential underlying genetic predisposition to mitochondrial dysfunction in long COVID while demonstrating altered cellular energy capacity in a subset of these patients. These findings open avenues for further research into the role of mitochondrial dysfunction and pathology in patients suffering from long COVID and may pave the way for targeted therapeutic strategies aimed at mitigating mitochondrial dysfunction.

Humans

VEGFA sex-specific signature is associated to long COVID symptom persistence.

BACKGROUND: Long COVID involves persistent symptoms after COVID-19 recovery, affecting multiple organ systems for months or years. Risk factors include female sex, prior chronic conditions, severe SARS-CoV-2 infection, reinfections, and lack of vaccination. As a major public health concern, ongoing research continues to investigate its causes, mechanisms, and long-term effects. METHODS: Proteomic expression analysis of 171 individuals, in two time points, with confirmed SARS-CoV-2 infection, including 133 long COVID patients from the deeply characterized COVICAT cohort, assessed 1395 protein biomarkers using Olink® technology. Statistical analyses with linear mixed models examined protein expression changes, long COVID status, and sex-specific differences. Functional analysis included gene set enrichment analysis and protein-protein interaction networks. RESULTS: Findings revealed VEGFA overexpression in long COVID patients (effect size 0.322, SE = 0.098, p = 0.0013), along with sex-specific expression patterns and the influence of sex-hormonal status in females, with significant overexpression of circulating VEGFA levels specifically in postmenopausal women (Mann-Whitney U test p value = 8.55 × 10-3). Network analysis identified 109 nodes and 274 edges, with VEGFA ranking highest in centrality. Dysregulated chemokine signaling, complement activation, and viral reactivation were also confirmed, consistent with prior studies. CONCLUSIONS: Using high-throughput proteomic profiling in a population-based cohort, we observed that vascular dysfunction, particularly involving VEGFA, is a key feature of long COVID, especially in milder cases, with significant overexpression of VEGFA in postmenopausal women. Sex-specific proteomic patterns suggest distinct recovery mechanisms, highlighting the need to consider sex, vascular health, and disease severity in the pathogenesis and management of long COVID.

Humans

Reproducibility of genetic risk factors identified for long COVID using combinatorial analysis across US and UK patient cohorts with diverse ancestries.

BACKGROUND: Long COVID is a major public health burden causing a diverse array of debilitating symptoms in tens of millions of patients globally. In spite of this overwhelming disease prevalence, staggering cost, severe impact on patients' lives and intense global research efforts, study of the disease has proved challenging due to its complexity. Genome-wide association studies (GWAS) have identified only four loci potentially associated with the disease, although these results did not statistically replicate between studies. A previous combinatorial analysis study identified a total of 73 genes that were highly associated with two long COVID cohorts in the predominantly (>&#x2009;91%) white European ancestry Sano GOLD population, and we sought to reproduce these findings in the independent and ancestrally more diverse All of Us (AoU) population. METHODS: We assessed the reproducibility of the 5343 long COVID disease signatures from the original study in the AoU population. Because the very small population sizes provide very limited power to replicate findings, we initially tested whether we observed a statistically significant enrichment of the Sano GOLD disease signatures that are also positively correlated with long COVID in the AoU cohort after controlling for population substructure. RESULTS: For the Sano GOLD disease signatures that have a case frequency greater than 5% in AoU, we consistently observed a significant enrichment (77-83%, p&#x2009;<&#x2009;0.01) of signatures that are also positively associated with long COVID in the AoU cohort. These encompassed 92% of the genes identified in the original study. At least five of the disease signatures found in Sano GOLD were also shown to be individually significantly associated with increased long COVID prevalence in the AoU population. Rates of signature reproducibility are strongest among self-identified white patients, but we also observe significant enrichment of reproducing disease associations in self-identified black/African-American and Hispanic/Latino cohorts. Signatures associated with 11 out of the 13 drug repurposing candidates identified in the original Sano GOLD study were reproduced in this study. CONCLUSION: These results demonstrate the reproducibility of long COVID disease signal found by combinatorial analysis, broadly validating the results of the original analysis. They provide compelling evidence for a much broader array of genetic associations with long COVID than previously identified through traditional GWAS studies. This strongly supports the hypothesis that genetic factors play a critical role in determining an individual's susceptibility to long COVID following recovery from acute SARS-CoV-2 infection. It also lends weight to the drug repurposing candidates identified in the original analysis. Together these results may help to stimulate much needed new precision medicine approaches to more effectively diagnose and treat the disease. This is also the first reproduction of long COVID genetic associations across multiple populations with substantially different ancestry distributions. Given the high reproducibility rate across diverse populations, these findings may have broader clinical application and promote better health equity. We hope that this will provide confidence to explore some of these mechanisms and drug targets and help advance research into novel ways to diagnose the disease and accelerate the discovery and selection of better therapeutic options, both in the form of newly discovered drugs and/or the immediate prioritization of coordinated investigations into the efficacy of repurposed drug candidates.

Humans

Targeting the SARS-CoV-2 reservoir in long COVID.

There are no approved treatments for post-COVID-19 condition (also known as long COVID), a debilitating disease state following SARS-CoV-2 infection that is estimated to affect tens of millions of people. A growing body of evidence shows that SARS-CoV-2 can persist for months or years following COVID-19 in a subset of individuals, with this reservoir potentially driving long-COVID symptoms or sequelae. There is, therefore, an urgent need for clinical trials targeting persistent SARS-CoV-2, and several trials of antivirals or monoclonal antibodies for long COVID are underway. However, because mechanisms of SARS-CoV-2 persistence are not yet fully understood, such studies require important considerations related to the mechanism of action of candidate therapeutics, participant selection, duration of treatment, standardisation of reservoir-associated biomarkers and measurables, optimal outcome assessments, and potential combination approaches. In addition, patient subgroups might respond to some interventions or combinations of interventions, making post-hoc analyses crucial. Here, we outline these and other key considerations, with the goal of informing the design, implementation, and interpretation of trials in this rapidly growing field. Our recommendations are informed by knowledge gained from trials targeting the HIV reservoir, hepatitis C, and other RNA viruses, as well as precision oncology, which share many of the same hurdles facing long-COVID trials.

Humans

Genome-wide association study of long COVID.

Infections can lead to persistent symptoms and diseases such as shingles after varicella zoster or rheumatic fever after streptococcal infections. Similarly, severe acute respiratory syndrome coronavirus 2 (SARS&#x2011;CoV&#x2011;2) infection can result in long coronavirus disease (COVID), typically manifesting as fatigue, pulmonary symptoms and cognitive dysfunction. The biological mechanisms behind long COVID remain unclear. We performed a genome-wide association study for long COVID including up to 6,450 long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We discovered an association of FOXP4 with long COVID, independent of its previously identified association with severe COVID-19. The signal was replicated in 9,500 long COVID cases and 798,835 population controls. Given the transcription factor FOXP4's role in lung physiology and pathology, our findings highlight the importance of lung function in the pathophysiology of long COVID.

Humans

Long COVID in Elderly COPD Patients: Clinical Features, Pulmonary Function Decline, and Proteomic Insights.

BACKGROUND: Elderly patients with chronic obstructive pulmonary disease (COPD) face a heightened risk of developing long coronavirus disease (COVID); however the exact clinical characteristics and underlying mechanisms remain unclear. METHODS: We enrolled 85 elderly COPD patients, of whom 43 reported newly onset persistent fatigue (the most dominant complaint of long COVID) within 1 year after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, and they were allocated to the Long-COVID group. The remaining 42 patients were assigned to the Control group. Patients completed questionnaires, pulmonary function tests, chest CT, routine laboratory tests, and blood proteomic analysis. RESULTS: Long-COVID patients had a longer course of COPD (> 5 years, 76.8% vs 52.4%) and duration of SARS-CoV-2 infection (10.0 days vs 7.0 days) (All P < 0.05), higher symptom burden, worse pulmonary ventilation function and a more rapid decrease in DLCO (All P < 0.05). Proteomic analysis indicated disruptions in inflammation and energy metabolism, potentially underlying long COVID in these patients. The machine learning model identified wheezing, the duration of SARS-CoV-2 infection, EIF2S3 (eukaryotic translation initiation factor 2 subunit gamma), current FEV1/FVC (%), and the course of COPD as key features distinguishing Long-COVID patients, and exhibited excellent performance. CONCLUSION: Elderly COPD patients with a longer COPD course and duration of COVID-19 are more prone to develop long COVID, with decreased pulmonary ventilation and diffusion ability. Disordered inflammation regulation and energy metabolism may be the potential mechanisms, highlighting the importance of monitoring inflammation and metabolic dysregulation in elderly COPD patients after recovery from COVID-19.

Humans

Beyond genes: EpiSwitch&#xae; and Orion platform-powered 3D genome architecture biomarkers reveal shared biology across ME/CFS, long COVID, PTSD, rheumatoid arthritis, and multiple sclerosis.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Long COVID (LC19), post-traumatic stress disorder (PTSD), rheumatoid arthritis (RA), and multiple sclerosis (MS) are clinically distinct disorders that share substantial symptom overlap, including persistent fatigue, cognitive impairment, autonomic dysfunction, and immune dysregulation. Although these conditions differ in diagnosis and clinical presentation, their underlying biological mechanisms remain poorly understood and may involve convergent regulatory pathways. METHODS: The EpiSwitch&#xae; 3D genomics platform and Orion knowledgebase were used to integrate chromosome conformation signatures with genome-wide association study (GWAS)-derived datasets across ME/CFS, LC19, PTSD, RA, and MS. Three-dimensional genomic anchors were mapped to coding genes and analysed using STRING protein-protein interaction networks and Cytoscape-based systems biology approaches. Disease-specific anchor datasets were generated and compared at both gene and network levels to identify shared biological processes and regulatory mechanisms. RESULTS: Analysis of the ME/CFS dataset identified 552 unique 3D genomic anchors mapped to 567 genes, with analogous disease-specific anchor sets generated for LC19, PTSD, RA, and MS. Direct overlap between disease-associated genes was limited; however, higher-order network analyses revealed substantial interconnectivity and convergence across conditions. Shared biological pathways included immune and cytokine signalling, interferon responses, mitochondrial function, metabolic regulation, and neuroendocrine processes. Highly connected hub genes included immune regulatory nodes such as LAG3 and components of the mTOR signalling pathway, implicating T-cell exhaustion, chronic immune activation, and immunometabolic dysregulation as common mechanisms underlying these disorders. CONCLUSIONS: These findings support a systems-level model in which clinically overlapping fatigue-associated syndromes arise from perturbations of interconnected regulatory networks rather than discrete disease-specific pathways. Despite limited genetic overlap, substantial convergence at the network level suggests shared biological architecture across ME/CFS, LC19, PTSD, RA, and MS. The identification of common regulatory pathways provides a mechanistic framework for the development of cross-disease diagnostic and therapeutic strategies. By capturing dynamic regulatory states, 3D genomic biomarkers offer significant potential for objective blood-based diagnostics, patient stratification, and the identification of shared therapeutic targets across complex chronic disorders. These findings support the application of precision medicine approaches and may accelerate the development of novel interventions for fatigue-associated multisystem diseases.

Humans

Proteomic Analysis of 442 Clinical Plasma Samples From Individuals With Symptom Records Revealed Subtypes of Convalescent Patients Who Had COVID-19.

After the coronavirus disease 2019 (COVID-19) pandemic, the postacute effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have gradually attracted attention. To precisely evaluate the health status of convalescent patients with COVID-19, we analyzed symptom and proteome data of 442 plasma samples from healthy controls, hospitalized patients, and convalescent patients 6 or 12 months after SARS-CoV-2 infection. Symptoms analysis revealed distinct relationships in convalescent patients. Results of plasma protein expression levels showed that C1QA, C1QB, C2, CFH, CFHR1, and F10, which regulate the complement system and coagulation, remained highly expressed even at the 12-month follow-up compared with their levels in healthy individuals. By combining symptom and proteome data, 442 plasma samples were categorized into three subtypes: S1 (metabolism-healthy), S2 (COVID-19 retention), and S3 (long COVID). We speculated that convalescent patients reporting hair loss could have a better health status than those experiencing headaches and dyspnea. Compared to other convalescent patients, those reporting sleep disorders, appetite decrease, and muscle weakness may need more attention because they were classified into the S2 subtype, which had the most samples from hospitalized patients with COVID-19. Subtyping convalescent patients with COVID-19 may enable personalized treatments tailored to individual needs. This study provides valuable plasma proteomic datasets for further studies associated with long COVID.

Humans

Proteomic analysis identifies pathways related to immune dysregulation in patients with hematologic malignancies after COVID-19 infection.

Patients with hematologic malignancies (HMs) are particularly vulnerable to coronavirus disease 2019 (COVID-19) because of underlying immune dysfunction and treatment-related immunosuppression. However, proteomic features associated with different clinical trajectories in this population remain insufficiently characterized. We performed serum proteomic analysis in 40 HM patients with COVID-19 and 15 healthy controls. Compared with controls, HM patients showed impaired immune-related responses during the acute phase of COVID-19. Acute-phase proteomic patterns differed across outcome groups; however, because outcome groups were closely intertwined with initial COVID-19 severity, ICU admission, and systemic illness, and because multivariable adjustment was not performed due to the limited sample size, these patterns should be interpreted as severity- and outcome-associated profiles rather than independent trajectory-specific markers. Fatal cases showed evidence of dysregulated immune activation, whereas patients later classified as having long COVID exhibited broader suppression of immune-related pathways. In addition to immune alterations, pathways related to platelet activation and cardiac-related dysfunction were associated with adverse clinical trajectories. Enzyme-linked immunosorbent assay validation supported the association of selected proteins with outcome groups during acute infection. These findings provide a proteomic overview of COVID-19 in HM patients and offer a basis for future mechanistic studies and larger external validation cohorts.IMPORTANCEPatients with hematologic malignancies are highly vulnerable to severe coronavirus disease 2019 (COVID-19), acute death, and long COVID due to preexisting immune dysfunction. However, the proteomic signatures linked to adverse clinical trajectories remain poorly understood. Our serum proteomic study identifies distinct acute-phase immune profiles associated with different outcomes: broad immune suppression characterizes long COVID, while dysregulated immune activation is associated with fatal cases. Platelet activation and cardiac-related pathways are also linked to poor outcomes. These findings provide key molecular insights for this high-risk population, supporting future biomarker development, risk stratification, and targeted clinical management.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05683353.

Humans

Molecular profiling of exhaled breath condensate in respiratory diseases.

BACKGROUND: Respiratory disorders, , continue to pose a major global health burden. Their complexity and heterogeneity challenge accurate diagnosis, effective monitoring, and therapeutic decision-making. Exhaled breath condensate (EBC) provides a reliable, non-invasive means of sampling the molecular environment of the airways. AIM: This review presents the state-of-the-art in EBC-based omics approaches-particularly metabolomics and proteomics-to characterize molecular signatures associated with chronic respiratory (e.g. asthma, chronic obstructive pulmonary disease, and rhinitis) and infectious diseases (e.g. COVID-19). RESULTS: We critically examine findings from studies applying nuclear magnetic resonance (NMR), mass spectrometry (MS), and sensor-based technologies to analyze EBC across various respiratory conditions. NMR, valued for its reproducibility and minimal sample preparation, consistently discriminates among disease phenotypes, identifies distinct metabotypes, and monitors treatment response over time. MS-based approaches afford enhanced sensitivity and specificity, enabling detailed profiling of inflammatory mediators, such as lipid-derived eicosanoids and amino acid derivatives. Proteomic studies reveal protein-level alterations associated with inflammation and tissue remodeling. In COVID-19 and long COVID, metabolomic and volatile compound profiling distinguishes affected individuals from healthy controls suggesting clinical potential. However, inconsistent sample processing and lack of analytical standardization remain limiting factors. CONCLUSIONS: EBC profiling shows clear promise for improving diagnosis, monitoring, and stratification in respiratory medicine. Yet, translation into clinical practice is hindered by limited standardization and validation. Broader, longitudinal studies will be essential to establish robust molecular signatures across disease states. This review underscores the timely need to implement breathomics investigations to gain mechanistic insight into the underlying biology of respiratory diseases.

Humans

A distinct effector B cell population drives autoantibody production in SARS-CoV-2 infection.

Autoantibodies (autoAbs) are linked to mortality and Long COVID, yet their cellular origins remain unclear. We analyzed the INCOV cohort and identified 12 age- and sex-matched participants with varying autoAb abundance and integrated single-cell RNA-seq and ATAC-seq data from B cells, plasma proteomics, proteome-wide autoAb profiling, clinical data, and in vitro assays. AutoAb abundance inversely correlated with neutralizing IgG and declined as infection resolved, paralleling the contraction of atypical memory B cells (AtMs). In vitro, AtMs preferentially differentiated into autoAb-producing antibody-secreting cells upon TLR7/8 stimulation. CD11c+ AtMs (double-negative 2, DN2s) in autoAb-high individuals exhibited increased TLR7 signaling, oxidative stress, and isotype switching, regulated by transcription factors T-bet and XBP1. Integrated genetic and genomic analyses showed that DN2s had the strongest enrichment for autoimmune trait heritability and inferred regulatory effects of autoimmune risk variants among B cell subsets. These findings identify DN2s as key precursors of autoAb-producing cells during SARS-CoV-2 infection.

B cell

Transcriptome changes in circulating immune cells of critical COVID-19 patients predict a specific metabolic and epigenetic imprint.

BACKGROUND: The progression to critical COVID-19 arises predominantly from a dysregulated host immune response although the underlying regulatory mechanisms still remain partially elusive. This limits a prompt prediction of the disease progression, reduces the therapeutic options and restrains our understanding of &#x201c;long COVID&#x201d;. METHODS: Here, we analyzed the transcriptome of peripheral blood mononuclear cells (PBMCs) collected from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients enrolled in the clinical trial COntAGIouS as well as independent bulk RNA-seq, single-cell RNA-seq and proteomic datasets. RESULTS: In critical COVID-19 patients, the integrative analysis of transcriptomic data revealed an altered regulatory network involving microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and coding genes that control mRNA translation-related genes, epigenetics, and metabolism. In parallel, we observed an upregulation of tRNA aminoacylation genes in critical COVID-19 patients by the analysis of either bulk or single-cell RNA-seq data from publicly available independent cohorts. Additionally, we found increased expression of coding genes enriched for the cognate amino acids (glycine, alanine, isoleucine and tyrosine), all related to protein localization, post-translational modifications, and cell metabolism in our cohort. Similar alterations in amino acid frequency were found in an independent proteomic dataset. CONCLUSIONS: Collectively, our findings indicate a broad perturbation of the gene expression landscape that characterizes the aberrant host immune response in critical COVID-19 patients and is potentially coordinated by miRNA and tRNA metabolism alterations. TRIAL REGISTRATION: COntAGIouS, NCT04327570. Registered 26 March 2020, https://clinicaltrials.gov/ct2/show/NCT04327570 .

Female

From Infection Control to Healthcare System Resilience: Lessons Learned from SARS-CoV-2 Research in Healthcare Workers.

The COVID-19 pandemic placed unprecedented pressure on healthcare systems and exposed healthcare workers (HCWs) to biological hazards, organizational pressures, and psychological strain. Evidence generated during the emergency shows that HCW protection cannot rely on isolated measures, but requires an integrated framework combining epidemiological surveillance, contact tracing, infection prevention and control, vaccination, occupational health, and workforce support. Contact tracing helped identify occupational exposures and clarify how duration, proximity, and inadequate use of personal protective equipment jointly shaped infection risk. Subsequent studies of reinfection showed that susceptibility reflected the interaction of viral circulation, individual immunity, and vaccination status. Vaccination reduced the clinical impact of SARS-CoV-2 and supported service continuity, although uptake depended on trust, communication, and management of adverse event concerns. The pandemic also highlighted substantial economic consequences and a high burden of psychological distress and burnout among HCWs. Building on this evidence, future preparedness should translate these lessons into permanent, adaptable infrastructure rather than temporary emergency arrangements, integrating interoperable, AI-assisted surveillance capable of combining occupational, diagnostic, vaccination, and genomic data to detect emerging risks early, while ensuring robust data governance and human oversight. Equally central is the need to address long-term workforce vulnerabilities, including Long COVID, attrition, and burnout, through early identification, rehabilitation, flexible return-to-work models, and sustained psychosocial support. Achieving this requires structured multidisciplinary collaboration among occupational medicine, infection control, epidemiology, mental health, and digital health specialists, moving from fragmented infection-control protocols to an integrated, proactive, and learning-oriented preparedness strategy. Protecting HCWs is therefore not only an occupational safety priority but a foundational prerequisite for safe, equitable, and sustainable healthcare delivery during future infectious threats.

Humans

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (&#x3b2;&#x2005;=&#x2005;-262.405, P&#x2005;=&#x2005;.041) and severity (&#x3b2;&#x2005;=&#x2005;-177.676, P&#x2005;=&#x2005;.049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans

High-Dimensional Immunophenotyping of Post-COVID-19 and Post-Influenza Patients Reveals Persistent and Specific Immune Signatures After Acute Respiratory Infection.

Long-term consequences of SARS-CoV-2 infection are unknown since recovered individuals can experience symptoms and latent viral reactivation for months. Indeed, acute post-infection sequelae have also been observed in other respiratory viral infections, including influenza. To characterize post-COVID-19 and post-influenza induced alterations to the cellular immunome, peripheral blood mononuclear cells (PBMCs) were obtained from patients 3 months after recovery from COVID-19 (n&#x2009;=&#x2009;93) or influenza (n&#x2009;=&#x2009;25), and from pre-pandemic healthy controls (n&#x2009;=&#x2009;25). PBMCs were characterized using a 40-plex mass cytometry panel. Principal component analysis (PCA), classification models, and K-means clustering were subsequently applied. PCA identified distinct immune profiles between cohorts, with both post-COVID and post-flu patients displaying an altered chemokine receptor expression compared to pre-pandemic healthy controls. These alterations were more prominent in post-COVID patients since they exhibited highly increased expression of chemokine receptors CXCR3 and CCR6 by various lymphoid populations, while post-influenza patients mainly showed a decrease in CCR4 expression by na&#xef;ve T cells, monocytes, and conventional dendritic cells. Classification models using immunophenotyping data confirm the three groups, while K-means clustering revealed two subgroups among post-COVID patients, with younger patients showing more pronounced immune alterations in the chemokine receptor profile, independently of long COVID symptoms. In conclusion, post-COVID and post-influenza patients exhibit distinct and unique persistent immune alterations. Understanding these altered immune profiles can guide targeted therapies for post-COVID syndrome and highlight differences in immune recovery from various respiratory infections.

Humans

SARS-CoV-2-related immune dysregulation and biologically plausible pathways to lymphomagenesis: a PRISMA-ScR-based scoping review.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related immune dysregulation has generated interest in diagnostic pathology because infection-related inflammation, long coronavirus disease (COVID)-related immune disturbance, and post-vaccination lymphoid reactions may overlap with lymphoid-biological mechanisms and complicate the distinction between reactive lymphoid proliferations and lymphoid neoplasia. AIM: This scoping review aimed to map biologically plausible pathways through which SARS-CoV-2-associated immune perturbation may intersect with lymphomagenesis-related mechanisms, emphasizing diagnostic implications rather than causality. MATERIALS AND METHODS: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). PubMed&#x2215;MEDLINE, Scopus, and Web of Science were searched from January 2020 to March 2026, with selected pre-2020 sources retained for mechanistic or diagnostic relevance. Sources were charted across mechanistic, immunological, virological, clinicopathological, and diagnostic domains. RESULTS: After screening and eligibility assessment, 63 sources were retained for thematic synthesis. Evidence clustered around lymphoma-relevant but non-specific mechanisms, including inflammatory signaling, impaired immune surveillance, latent oncogenic viral reactivation, prolonged germinal-center activity with activation-induced cytidine deaminase (AID)-related genomic vulnerability, and lymphoid microenvironment remodeling. These mechanisms appear most relevant in predisposed hosts with chronic immune dysregulation, latent viral infection, defective deoxyribonucleic acid (DNA) repair, or occult abnormal lymphoid clones. Infection and vaccination are distinct contexts, because infection may produce broader immune disruption, whereas most post-vaccination nodal events are reactive and self-limited. CONCLUSIONS: Current evidence supports biological plausibility rather than a direct or generalizable causal relationship. The main diagnostic implication is careful clinicopathological correlation and distinction between reactive lymphoid proliferations and lymphoid neoplasia in post-COVID-19 and post-vaccination settings.

Humans

Acute COVID-19 severity and impaired cognitive function up to 32&#xa0;months after diagnosis: an observational study.

BACKGROUND: Cognitive dysfunction ("brain fog") is a commonly reported post-COVID-19 symptom. Leveraging data from five general population cohorts across four European countries (Estonia, Iceland, Norway, and Sweden), we assessed long-term prevalence of impaired subjective cognitive function among individuals diagnosed with COVID-19 by acute illness severity. METHODS: The included cohorts consisted of adult participants recruited from March 2020 and followed with self-report measures of cognitive function and past COVID-19 infection (except one cohort consisting of clinically confirmed COVID-19 cases) through February 2023. In a cross-sectional analysis we contrasted the prevalence of impaired cognitive function among individuals with and without a COVID-19 diagnosis, overall and by illness severity up to 32&#xa0;months post-diagnosis. We adjusted for age, gender, education, relationship status, binge drinking, body mass index, previous psychiatric diagnosis, number of chronic medical conditions, and response period. In a longitudinal analysis, we assessed potential changes in cognitive function scores before and after COVID-19 diagnosis. RESULTS: The study population consisted of 153,841 participants (71% women), with 31,359 (20.4%) reporting a positive COVID-19 test. Overall, a COVID-19 diagnosis was not statistically significantly associated with increased prevalence ratio (PR) of impaired cognitive function (PR 1.30 [95% CI: 0.98-1.71]). Individuals bedridden due to COVID-19 for 1-6&#xa0;days (PR 1.38 [95% CI 0.96-1.99]) or&#x2009;&#x2265;&#x2009;7&#xa0;days (2.59 [1.55-4.33]) had higher prevalence of impaired cognitive function compared to those never diagnosed, while individuals never bedridden had a lower prevalence to those never diagnosed with COVID-19 (0.89 [0.80-1.00]). These findings were corroborated in the longitudinal analysis where a pre- to post diagnosis decline in cognitive function was observed among individuals bedridden due to COVID-19 (p&#x2009;<&#x2009;0.0001). CONCLUSIONS: The data indicates that a severe COVID-19 acute illness course is associated with impaired cognitive function up to 18-32&#xa0;months after COVID-19 diagnosis.

Adult

Dynamic Molecular Changes in Brain, Lung, and Heart of Hamsters Infected With SARS-CoV-2: Insights From a Severe and Recovery Phase Model.

The Global pandemic of coronavirus disease 2019 was initiated by the emergence of severe acute respiratory syndrome coronavirus 2. In addition to conventional pulmonary lesions, a range of neurological injury symptoms have been identified in clinical practice, but the aetiology of neurological disorders linked to SARS-CoV-2 infection remains poorly understood. Syrian hamsters, which are highly susceptible to SARS-CoV-2 infection, exhibit a disease phenotype similar to that observed in human COVID-19 patients. In this study, a hamster model of COVID-19 infection was used to analyze molecular changes in different tissues at various time points post infection with distinct strains using proteomic and phosphoproteomic approaches. Multi-omics analysis showed that SARS-COV-2 infection triggers sustained downregulation of the abundance and phosphorylation levels of neuronal and synapse-associated proteins in the brain, suggesting that neuronal damage persists even during the recovery period. Additionally, infections with SARS-CoV-2 may contribute to the onset of long-term symptoms of COVID-19 by impacting energy metabolism, neurotransmitter release, and synaptic transmission pathways. This study provides a comprehensive molecular profile of hamsters infected with different SARS-CoV-2 strains in different tissues, offering foundational insights into the pathogenic mechanisms of COVID-19.

Animals