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.
The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. That non-classical monocytes may be a source of inflammation in PASC warrants further study.
28Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of 29 coronavirus disease 2019 , is now pandemic with nearly three million cases 30 reported to date 1 . Although the majority of COVID-19 patients experience only mild or 31 moderate symptoms, a subset will progress to severe disease with pneumonia and acute 32 respiratory distress syndrome (ARDS) requiring mechanical ventilation 2 . Emerging results 33 indicate a dysregulated immune response characterized by runaway inflammation, 34including cytokine release syndrome (CRS), as the major driver of pathology in severe 35 -19 3,4 . With no treatments currently approved for COVID-19, therapeutics to 36 prevent or treat the excessive inflammation in severe disease caused by SARS-CoV-2 37 infection are urgently needed. Here, in 10 terminally-ill, critical COVID-19 patients we 38 report profound elevation of plasma IL-6 and CCL5 (RANTES), decreased CD8+ T cell 39 levels, and SARS-CoV-2 plasma viremia. Following compassionate care treatment with 40 the CCR5 blocking antibody leronlimab, we observed complete CCR5 receptor 41 occupancy on macrophage and T cells, rapid reduction of plasma IL-6, restoration of the 42 CD4/CD8 ratio, and a significant decrease in SARS-CoV-2 plasma viremia. Consistent 43 with reduction of plasma IL-6, single-cell RNA-sequencing revealed declines in 44 transcriptomic myeloid cell clusters expressing IL-6 and interferon-related genes. These 45 results demonstrate a novel approach to resolving unchecked inflammation, restoring 46 immunologic deficiencies, and reducing SARS-CoV-2 plasma viral load via disruption of 47 COVID MAIN TEXT 51 52Since the initial cases of COVID-19 were reported from Wuhan, China in December 53 2019 2 , SARS-CoV-2 has emerged as a global pandemic with an ever-increasing number 54 of severe cases requiring invasive external ventilation that threatens to overwhelm health 55
Background We sought to determine the immunologic abnormalities in patients following SARS-CoV-2 vaccines who experience post-acute sequelae of COVID-19 (PASC)-like symptoms > 4 weeks post vaccination. In addition, we investigated whether the potential etiology was similar to PASC. Design: We enrolled 50 post-vaccination individuals who experience PASC-like symptoms, 10 healthy individuals, and 35 individuals post-vaccination without symptoms. We performed multiplex cytokine/chemokine profiling with machine learning as well as SARS-CoV-2 S1 protein detection on monocyte subsets using flow cytometry and mass spectrometry. Results We determined that post-vaccination individuals with PASC-like symptoms had similar symptoms to PASC patients. When analyzing their immune profile, post-vaccination individuals had statistically significant elevations of sCD40L, CCL5, IL-6, and IL-8. SARS-CoV-2 S1 and S2 protein were detected in CD16 + monocytes using flow cytometry and mass spectrometry on sorted cells. Conclusions Post-vaccination individuals with PASC-like symptoms exhibit markers of platelet activation and pro-inflammatory cytokine production which may be driven by the persistence of SARS-CoV-2 S1 protein persistence in intermediate and non-classical monocytes.
Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined as S1 = (IFN-γ + IL-2)/ CCL4-MIP-1β. Second, a score specific for the severe COVID-19 patients was defined as S2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic 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.SummaryImmunologic Modeling of Severity and Chronicity of COVID-19
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), is now pandemic with nearly three million cases reported to date1. Although the majority of COVID-19 patients experience only mild or moderate symptoms, a subset will progress to severe disease with pneumonia and acute respiratory distress syndrome (ARDS) requiring mechanical ventilation2. Emerging results indicate a dysregulated immune response characterized by runaway inflammation, including cytokine release syndrome (CRS), as the major driver of pathology in severe COVID-193,4. With no treatments currently approved for COVID-19, therapeutics to prevent or treat the excessive inflammation in severe disease caused by SARS-CoV-2 infection are urgently needed. Here, in 10 terminally-ill, critical COVID-19 patients we report profound elevation of plasma IL-6 and CCL5 (RANTES), decreased CD8+ T cell levels, and SARS-CoV-2 plasma viremia. Following compassionate care treatment with the CCR5 blocking antibody leronlimab, we observed complete CCR5 receptor occupancy on macrophage and T cells, rapid reduction of plasma IL-6, restoration of the CD4/CD8 ratio, and a significant decrease in SARS-CoV-2 plasma viremia. Consistent with reduction of plasma IL-6, single-cell RNA-sequencing revealed declines in transcriptomic myeloid cell clusters expressing IL-6 and interferon-related genes. These results demonstrate a novel approach to resolving unchecked inflammation, restoring immunologic deficiencies, and reducing SARS-CoV-2 plasma viral load via disruption of the CCL5-CCR5 axis, and support randomized clinical trials to assess clinical efficacy of leronlimab-mediated inhibition of CCR5 for COVID-19.
Background Post-acute sequelae of COVID-19 (PASC) is a growing healthcare and economic concern affecting as many as 10%-30% of those infected with COVID-19. Though the symptoms have been well-documented, they significantly overlap with other common chronic inflammatory conditions which could confound treatment and therapeutic trials. Methods A total of 236 patients including 64 with post-acute sequelae of COVID-19 (PASC), 50 with myalgic encephalomyelitis-chronic fatigue syndrome (ME-CFS), 29 with post-treatment Lyme disease (PTLD), and 42 post-vaccine individuals with PASC-like symptoms (POVIP) were enrolled in the study. We performed a 14-plex cytokine/chemokine panel previously described to generate raw data that was normalized and run in a decision tree model using a Classification and Regression Tree (CART) algorithm. The algorithm was used to classify these conditions in distinct groups despite their similar symptoms. Results PASC, ME-CSF, POVIP, and Acute COVID-19 disease categories were able to be classified by our cytokine hub based CART algorithm with an average F1 score of 0.61 and high specificity (94%). Conclusions Proper classification of these inflammatory conditions with very similar symptoms is critical for proper diagnosis and treatment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.