Fig. 4

Subcluster analysis of peripheral blood Foxp3⁺ Treg cells in COVID-19 patients: activation following SARS-CoV-2 infection is dampened by CD24Fc treatment. We clustered 98,525 Foxp3⁺ Treg cells from HD (n = 17) and COVID-19 (n = 22) patients using an unbiased multivariate t-mixture model, which identified 8 Foxp3⁺ Treg sub-clusters that reflect statistically distinct cell activation states. We visualized the relative similarity of each cell and cell cluster on the two-dimensional UMAP space with a 10% downsampling (A). Using median expression of flow cytometry markers, we generated a cluster-by-marker heatmap to characterize the subsets (B) and visualized individual marker expression patterns on the UMAP space (C). To understand the effect of SARS-CoV-2 infection on cell population dynamics, we compared UMAP plots and cluster frequencies of HD vs. baseline COVID-19 patient samples (D and E; p < 0.001 for clusters 1–5, 7). We visualized samples from COVID-19 patients D2, 4, and 8 after CD24Fc vs. placebo using contour plots to represent the density of cells throughout regions of the UMAP space (F). We describe cluster population dynamics as fold change over baseline in each treatment group (G; sample distribution described in Fig. 1F; p < 0.001 for cluster 1, 4, 6–8; cluster 3, p = 0.004). To better characterize the activation status of Treg cells, we linearly transformed a subset of markers (Ki-67, TOX, CD25, ICOS, CTLA4) to create a univariate cell-level activation score (H), where highly activated cell clusters (such as clusters 6, 7, 8) had highest activation scores (I). We fit a GLMM to our longitudinal cell-level activation scores to assess the effect of CD24Fc on activation scores over time (J). The p-values in E and J were calculated using the Wilcoxon rank-sum test and the Kenward-Roger method, respectively. ***p < 0.001