Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning.

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-1ß. 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.

CCR5 inhibition in critical COVID-19 patients decreases inflammatory cytokines, increases CD8 T-cells, and decreases SARS-CoV2 RNA in plasma by day 14.

OBJECTIVE: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is now a global pandemic. Emerging results indicate a dysregulated immune response. Given the role of CCR5 in immune cell migration and inflammation, we investigated the impact of CCR5 blockade via the CCR5-specific antibody leronlimab on clinical, immunological, and virological parameters in severe COVID-19 patients. METHODS: In March 2020, 10 terminally ill, critical COVID-19 patients received two doses of leronlimab via individual emergency use indication. We analyzed changes in clinical presentation, immune cell populations, inflammation, as well as SARS-CoV-2 plasma viremia before and 14 days after treatment. RESULTS: Over the 14-day study period, six patients survived, two were extubated, and one discharged. We observed complete CCR5 receptor occupancy in all donors by day 7. Compared with the baseline, we observed a concomitant statistically significant reduction in plasma IL-6, restoration of the CD4/CD8 ratio, and resolution of SARS-CoV2 plasma viremia (pVL). Furthermore, the increase in the CD8 percentage was inversely correlated with the reduction in pVL (r = -0.77, p = 0.0013). CONCLUSIONS: Our study design precludes clinical efficacy inferences but the results implicate CCR5 as a therapeutic target for COVID-19 and they form the basis for ongoing randomized clinical trials.