ArticleFrontiers in immunology
Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning.
Article in Frontiers in immunology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 4 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
109 citing papers in PubMed, 4 syntheses or guidelines pooled it, 203 citations in OpenAlex.
- Blood Biomarkers of Long COVID: A Systematic Review.Molecular diagnosis & therapy · 2024Pooled it
- The Vitamin D Serum Levels in Pregnant Women Affected by COVID-19: A Systematic Review and Meta-Analysis.Nutrients · 2023Pooled it
- Increased interleukin-6 is associated with long COVID-19: a systematic review and meta-analysis.Infectious diseases of poverty · 2023Pooled it
- Biomarkers in long COVID-19: A systematic review.Frontiers in medicine · 2023Pooled it
- COVID-19 Is Airborne AIDS: Provocative Oversimplification, Emerging Science, or Something in Between?AJPM focus · 2026Review
- Current status and future perspectives on the mechanistic and pathophysiological understanding of long COVID.Communications medicine · 2026Article
- Evaluation of the choroidal structural and vasculature changes following COVID-19 infection and vaccination using optical coherence tomography angiography.International journal of retina and vitreous · 2026Article
- Associations of selective serotonin reuptake inhibitors and long COVID risk in patients with depression: a retrospective cohort study.Infection · 2026Article
- Cognition, Cytokines, Blood-Brain Barrier, and Beyond in COVID-19: A Narrative Review.International journal of molecular sciences · 2026Review
- Lingering echoes of SARS-CoV-2: mechanistic insights and management of long COVID syndrome.Inflammopharmacology · 2026Review
- The Central Role of Macrophages in Long COVID Pathophysiology.International journal of molecular sciences · 2025Review
- Detection of S1 spike protein in CD16+ monocytes up to 245 days in SARS-CoV-2-negative post-COVID-19 vaccine syndrome (PCVS) individuals.Human vaccines & immunotherapeutics · 2025Article
- Article
- Long COVID and Type I IFN Signature in Working-Age Adults: A Cross-Sectional Study.International journal of molecular sciences · 2025Article
- Article
- The silent legacy of COVID-19: exploring genomic instability in long-term COVID-19 survivors.BMC infectious diseases · 2025Article
- Perioperative and anesthetic considerations for post-acute sequelae of COVID (PASC)/long COVID.Perioperative medicine (London, England) · 2025Review
- Cytokine profiles associated with persisting symptoms of post-acute sequelae of COVID-19.The Korean journal of internal medicine · 2025Article
- Vaxtherapy, a Multiphase Therapeutic Protocol Approach for Longvax, the COVID-19 Vaccine-Induced Disease: Spike Persistence as the Core Culprit and Its Downstream Effects.Diseases (Basel, Switzerland) · 2025Article
- Long COVID and Biomarker Dysregulation-A Shift Toward Immune Exhaustion?Medicina (Kaunas, Lithuania) · 2025Article
49 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Expression of CCR5 and its cognate ligands have been implicated in COVID-19 pathogenesis, consequently therapeutics directed against CCR5 are being investigated. Here, we explored the role of CCR5 and its ligands across the immunologic spectrum of COVID-19. We used a bioinformatics approach to predict and model the immunologic phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 224 individuals including healthy controls and patients spanning the COVID-19 disease continuum. We assessed the plasma and isolated peripheral blood mononuclear cells (PBMCs) from 29 healthy controls, 26 Mild-Moderate COVID-19 individuals, 48 Severe COVID-19 individuals, and 121 individuals with post-acute sequelae of COVID-19 (PASC) symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients from each group. B-cells were significantly elevated compared to healthy control individuals (P<0.001) as was the CD14+, CD16+, CCR5+ monocytic subset (P<0.001). CD4 and CD8 positive T-cells expressing PD-1 as well as T-regulatory cells were significantly lower than healthy controls (P<0.001 and P=0.01 respectively). CCL5/RANTES, IL-2, IL-4, CCL3, IL-6, IL-10, IFN-γ, and VEGF were all significantly elevated compared to healthy controls (all P<0.001). Conversely GM-CSF and CCL4 were in significantly lower levels than healthy controls (P=0.01). Data were further analyzed and the classes were balanced using SMOTE. With a balanced working dataset, we constructed 3 random forest classifiers: a multi-class predictor, a Severe disease group binary classifier and a PASC binary classifier. Models were also analyzed for feature importance to identify relevant cytokines to generate a disease score. Multi-class models generated a score specific for the PASC patients and defined as S1 = (IFN-γ + IL-2)/CCL4-MIP-1β. Second, a score for the Severe COVID-19 patients was defined as S2 = (IL-6+sCD40L/1000 + VEGF/10 + 10*IL-10)/(IL-2 + IL-8). Severe COVID-19 patients are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While PASC patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.