{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T02:38:22Z","timestamp":1790735902901,"version":"4.1.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T00:00:00Z","timestamp":1761091200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      COVID-19, including its post-acute sequelae (Long COVID), is increasingly recognized as involving persistent immune dysregulation and chronic inflammation. Severe and prolonged disease states are often accompanied by sustained cytokine release, immune cell exhaustion, and ongoing cell-cell communication that shapes the inflammatory milieu. Among immune subsets, CD8\n                      <jats:sup>+<\/jats:sup>\n                      T cells play a central role in antiviral defense, yet the molecular mechanisms linking their dysfunction to prolonged inflammation remain incompletely understood.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We analyzed 73,110 peripheral blood mononuclear cells (PBMCs) from individuals across four disease states (Healthy, Exposed, Infected, and Hospitalized) using single-cell RNA sequencing. Immune cell subsets were annotated, and T cell heterogeneity was profiled. Cytokine and inflammatory scores were calculated to assess immune activation. Differentially expressed genes (DEGs) underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Cell-cell communication was evaluated to map ligand-receptor networks. Additionally, nine machine learning models were trained on a bulk RNA-seq cohort, and the SHapley Additive exPlanations (SHAP) framework was applied to interpret key predictive genes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Progressive disease severity was associated with a decline in T cell proportions, enrichment of pro-inflammatory myeloid cells, and elevated cytokine expression, particularly IL-32. Memory CD8\n                      <jats:sup>+<\/jats:sup>\n                      T cells showed increased exhaustion and inflammatory scores while maintaining a central position in MHC-I-mediated communication networks. Persistent activation of immune and metabolic pathways, including antigen presentation and oxidative phosphorylation, was observed in prolonged disease states. Seven genes (RPS26, RPS29, RPL36, RPL39, RPS28, RPS21, and CD3E) were identified as strong predictors of chronic immune dysregulation, with the XGBoost model achieving the highest AUC. SHAP analysis confirmed their contributions to disease classification.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>\n                      This study maps the immune landscape of COVID-19 and Long COVID at single-cell resolution, revealing that persistent immune cell communication, particularly involving memory CD8\n                      <jats:sup>+<\/jats:sup>\n                      T cells, may sustain chronic inflammation beyond the acute phase. The identified molecular signatures offer potential biomarkers and therapeutic targets for mitigating post-viral inflammatory syndromes.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1689507","type":"journal-article","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T04:17:32Z","timestamp":1761106652000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Immune cell communication networks and memory CD8+ T cell signatures sustaining chronic inflammation in COVID-19 and Long COVID"],"prefix":"10.3389","volume":"16","author":[{"given":"Hengrui","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zewen","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilayda","family":"Karsidag","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panpan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jieling","family":"Weng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,10,22]]},"reference":[{"key":"B1","article-title":"Weekly epidemiological update on COVID-19\u201313 June 2023","year":"2023"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2034577","article-title":"Safety and efficacy of the BNT162b2 mRNA covid-19 vaccine","volume":"383","author":"Polack Fernando","year":"2020","journal-title":"New Engl J Med"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2021.3370","article-title":"COVID-19 vaccines vs variants, determining how much immunity is enough","volume":"325","author":"Rubin","year":"2021","journal-title":"JAMA"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1038\/s41579-023-00878-2","article-title":"The evolution of SARS-coV-2","volume":"21","author":"Markov","year":"2023","journal-title":"Nat Rev Microbiol"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0952-y","article-title":"Disease and healthcare burden of COVID-19 in the United States","volume":"26","author":"Miller","year":"2020","journal-title":"Nat Med"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1093\/cid\/ciaa1787","article-title":"Impact of sex and metabolic comorbidities on coronavirus disease 2019 (COVID-19) mortality risk across age groups: 66\u2013646 inpatients across 613 U.S. Hospitals","volume":"73","author":"Goodman","year":"2020","journal-title":"Clin Infect Dis"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.202112-2761OC","article-title":"COVID-19 in patients with pulmonary hypertension: A national prospective cohort study","volume":"206","author":"Montani","year":"2022","journal-title":"Am J Respir Crit Care Med"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1210\/clinem\/dgad165","article-title":"COVID-19 as a trigger for type 1 diabetes","volume":"108","author":"Wang","year":"2023","journal-title":"J Clin Endocrinol Metab"},{"key":"B9","doi-asserted-by":"publisher","first-page":"21195","DOI":"10.1038\/s41598-024-70659-1","article-title":"Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals ubiquitin promotes pulmonary fibrosis in chronic pulmonary diseases","volume":"14","author":"Wen","year":"2024","journal-title":"Sci Rep"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.bja.2022.01.024","article-title":"Breathing face down","volume":"128","author":"Lamperti","year":"2022","journal-title":"Br J Anaesthesia"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1097\/aln.0000000000003571","article-title":"Acute respiratory distress syndrome","volume":"134","author":"Williams","year":"2021","journal-title":"Anesthesiology"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1038\/s41577-020-0311-8","article-title":"The trinity of COVID-19: immunity, inflammation and intervention","volume":"20","author":"Tay","year":"2020","journal-title":"Nat Rev Immunol"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2022.104245","article-title":"Long COVID symptoms in exposed and infected children, adolescents and their parents one year after SARS-CoV-2 infection: A prospective observational cohort study","volume":"84","author":"Haddad","year":"2022","journal-title":"EBioMedicine"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0869-5","article-title":"Temporal dynamics in viral shedding and transmissibility of COVID-19","volume":"26","author":"He","year":"2020","journal-title":"Nat Med"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1172\/jci137244","article-title":"Clinical and immunological features of severe and moderate coronavirus disease 2019","volume":"130","author":"Chen","year":"2020","journal-title":"J Clin Invest"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30628-0","article-title":"COVID-19: consider cytokine storm syndromes and immunosuppression","volume":"395","author":"Mehta","year":"2020","journal-title":"Lancet"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1038\/s41590-020-0762-x","article-title":"Single-cell landscape of immunological responses in patients with COVID-19","volume":"21","author":"Zhang","year":"2020","journal-title":"Nat Immunol"},{"key":"B18","doi-asserted-by":"publisher","first-page":"5838","DOI":"10.1016\/j.cell.2021.10.023","article-title":"COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas","volume":"184","author":"Ren","year":"2021","journal-title":"Cell"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2020.00827","article-title":"Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19)","volume":"11","author":"Diao","year":"2020","journal-title":"Front Immunol"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0944-y","article-title":"A single-cell atlas of the peripheral immune response in patients with severe COVID-19","volume":"26","author":"Wilk","year":"2020","journal-title":"Nat Med"},{"key":"B21","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41421-020-0168-9","article-title":"Immune cell profiling of COVID-19 patients in the recovery stageby single-cell sequencing","volume":"6","author":"Wen","year":"2020","journal-title":"Cell Discov"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01386-7","article-title":"CD8+ T cells contribute to survival in patients with COVID-19 and hematologic cancer","volume":"27","author":"Bange","year":"2021","journal-title":"Nat Med"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3920","article-title":"Machine learning applications in genetics and genomics","volume":"16","author":"Libbrecht","year":"2015","journal-title":"Nat Rev Genet"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1705.07874","article-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017"},{"key":"B25","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat Mach Intell"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3058537","article-title":"& Zeng, J. A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19)","volume":"9","author":"Islam","year":"2021","journal-title":"IEEE Access"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03631-y","article-title":"Diverse functional autoantibodies in patients with COVID-19","volume":"595","author":"Wang","year":"2021","journal-title":"Nature"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2588-y","article-title":"Longitudinal analyses reveal immunological misfiring in severe COVID-19","volume":"584","author":"Lucas","year":"2020","journal-title":"Nature"},{"key":"B29","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.cels.2020.10.003","article-title":"Large-scale multi-omic analysis of COVID-19 severity","volume":"12","author":"Overmyer","year":"2021","journal-title":"Cell Syst"},{"key":"B30","doi-asserted-by":"publisher","first-page":"3573","DOI":"10.1016\/j.cell.2021.04.048","article-title":"Integrated analysis of multimodal single-cell data","volume":"184","author":"Hao","year":"2021","journal-title":"Cell"},{"key":"B31","doi-asserted-by":"publisher","first-page":"e8746","DOI":"10.15252\/msb.20188746","article-title":"Current best practices in single-cell RNA-seq analysis: a tutorial","volume":"15","author":"Luecken","year":"2019","journal-title":"Mol Syst Biol"},{"key":"B32","doi-asserted-by":"publisher","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive integration of single-cell data","volume":"177","author":"Stuart","year":"2019","journal-title":"Cell"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btac681","article-title":"Evaluation of efficiency prediction algorithms and development of ensemble model for CRISPR\/Cas9 gRNA selection","volume":"38","author":"Chen","year":"2022","journal-title":"Bioinformatics"},{"key":"B34","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1186\/s12915-023-01728-6","article-title":"Single-cell Mayo Map (scMayoMap): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis","volume":"21","author":"Yang","year":"2023","journal-title":"BMC Biol"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1126\/science.abe6474","article-title":"Pan-cancer single-cell landscape of tumor-infiltrating T cells","volume":"374","author":"Zheng","year":"2021","journal-title":"Science"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1246","DOI":"10.1038\/s41467-022-28803-w","article-title":"Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data","volume":"13","author":"Ianevski","year":"2022","journal-title":"Nat Commun"},{"key":"B37","doi-asserted-by":"publisher","first-page":"4706","DOI":"10.1038\/s41467-019-12464-3","article-title":"Single-cell transcriptomics of human T cells reveals tissue and activation signatures in health and disease","volume":"10","author":"Szabo","year":"2019","journal-title":"Nat Commun"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1089\/omi.2011.0118","article-title":"clusterProfiler: an R package for comparing biological themes among gene clusters","volume":"16","author":"Yu","year":"2012","journal-title":"OMICS: A J Integr Biol"},{"key":"B39","doi-asserted-by":"publisher","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","article-title":"Inference and analysis of cell-cell communication using CellChat","volume":"12","author":"Jin","year":"2021","journal-title":"Nat Commun"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1038\/nri3084","article-title":"Towards a systems understanding of MHC class I and MHC class II antigen presentation","volume":"11","author":"Neefjes","year":"2011","journal-title":"Nat Rev Immunol"},{"key":"B41","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1186\/s13059-015-0844-5","article-title":"MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data","volume":"16","author":"Finak","year":"2015","journal-title":"Genome Biol"},{"key":"B42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building predictive models in R using the caret package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J Stat Softw"},{"key":"B43","author":"Chen","year":"2016"},{"key":"B44","doi-asserted-by":"publisher","first-page":"eabc8511","DOI":"10.1126\/science.abc8511","article-title":"Deep immune profiling of COVID-19 patients reveals distinct immunotypes with therapeutic implications","volume":"369","author":"Mathew","year":"2020","journal-title":"Science"},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.1038\/s41577-020-0402-6","article-title":"T cell responses in patients with COVID-19","volume":"20","author":"Chen","year":"2020","journal-title":"Nat Rev Immunol"},{"key":"B46","doi-asserted-by":"publisher","DOI":"10.1016\/j.cyto.2022.155804","article-title":"Cytokine profiles in the detection of severe lung involvement in hospitalized patients with COVID-19: The IL-8\/IL-32 axis","volume":"151","author":"Bergantini","year":"2022","journal-title":"Cytokine"},{"key":"B47","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1038\/s41421-020-00225-2","article-title":"The differential immune responses to COVID-19 in peripheral and lung revealed by single-cell RNA sequencing","volume":"6","author":"Xu","year":"2020","journal-title":"Cell Discov"},{"key":"B48","doi-asserted-by":"publisher","first-page":"992","DOI":"10.1016\/j.chom.2020.04.009","article-title":"Complex immune dysregulation in COVID-19 patients with severe respiratory failure","volume":"27","author":"Giamarellos-Bourboulis","year":"2020","journal-title":"Cell Host Microbe"},{"key":"B49","doi-asserted-by":"publisher","first-page":"1488860","DOI":"10.1101\/2020.07.31.20165647","article-title":"Magnitude and dynamics of the T-cell response to SARS-coV-2 infection at both individual and population levels","volume":"15","author":"Snyder","year":"2020","journal-title":"medRxiv"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.1038\/s41423-021-00699-4","article-title":"Ribosomal protein S26 serves as a checkpoint of T-cell survival and homeostasis in a p53-dependent manner","volume":"18","author":"Chen","year":"2021","journal-title":"Cell Mol Immunol"},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2022.1045236","article-title":"Deficiency of ribosomal protein S26, which is mutated in a subset of patients with Diamond Blackfan anemia, impairs erythroid differentiation","volume":"13","author":"Piantanida","year":"2022","journal-title":"Front Genet"}],"updated-by":[{"DOI":"10.3389\/fimmu.2025.1739646","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000}}],"container-title":["Frontiers in Immunology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1689507\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T13:24:28Z","timestamp":1763040268000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2025.1689507\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,22]]},"references-count":51,"alternative-id":["10.3389\/fimmu.2025.1689507"],"URL":"https:\/\/doi.org\/10.3389\/fimmu.2025.1689507","relation":{},"ISSN":["1664-3224"],"issn-type":[{"value":"1664-3224","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,22]]},"article-number":"1689507"}}