Single-cell immune profiling reveals long-term changes in myeloid cells and identifies a novel subset of CD9+ monocytes associated with COVID-19 hospitalization

Abstract

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can result in severe immune dysfunction, hospitalization, and death. Many patients also develop long-COVID-19, experiencing symptoms months after infection. Although significant progress has been made in understanding the immune response to acute SARS-CoV-2 infection, gaps remain in our knowledge of how innate immunity influences disease kinetics and severity. We hypothesized that cytometry by time-of-flight analysis of PBMCs from healthy and infected subjects would identify novel cell surface markers and innate immune cell subsets associated with COVID-19 severity. In this pursuit, we identified monocyte and dendritic cell subsets that changed in frequency during acute SARS-CoV-2 infection and correlated with clinical parameters of disease severity. Subsets of nonclassical monocytes decreased in frequency in hospitalized subjects, yet increased in the most severe patients and positively correlated with clinical values associated with worse disease severity. CD9, CD163, PDL1, and PDL2 expression significantly increased in hospitalized subjects, and CD9 and 6-Sulfo LacNac emerged as the markers that best distinguished monocyte subsets amongst all subjects. CD9⁺ monocytes remained elevated, whereas nonclassical monocytes remained decreased, in the blood of hospitalized subjects at 3-4 months postinfection. Finally, we found that CD9⁺ monocytes functionally released more IL-8 and MCP-1 after LPS stimulation. This study identifies new monocyte subsets present in the blood of COVID-19 patients that correlate with disease severity, and links CD9⁺ monocytes to COVID-19 progression.

Keywords: CyTOF; SARS-CoV-2; Slan; T cells; long-COVID-19; nonclassical monocytes.

FIGURE 1

Experimental layout. Flowchart of experimental design (A). Chart of every subject included in our analysis, with their condition (healthy, nonhospitalized, and hospitalized), age, sex, date of symptom onset, date of positive SARS‐CoV‐2 test, ITU status, span of hospital admission, and date of blood draw (B). List of markers used in immunoprofiling CyTOF panel grouped by their biologic roles (C)

FIGURE 2

CyTOF‐mediated identification of changes in immune cell cluster frequencies and surface marker expression in convalescent COVID‐19 subjects. CD45⁺ Dump^– leukocytes from healthy and COVID‐19 subjects clustered and projected onto a UMAP (A). Expression of cell surface markers projected onto the UMAP of (A) as feature plots (B). Heatmap displaying each cluster's scaled median expression for 34 markers (C). Box and whisker plots showing median expression of CD9 and CD45RA within the CD45⁺ Dump^– cells for healthy, nonhospitalized, and hospitalized subjects (D). Box and whisker plots of individual cell clusters as a proportion of CD45⁺ Dump^– cells between healthy, nonhospitalized, and hospitalized subjects (E). Statistically significant (p ≤ 0.05) changes were calculated using adjusted p values generated after a multiple‐comparisons correction. Changes in cluster frequencies were calculated using GLMM while changes in marker expression were calculated with LIMMA

FIGURE 3

Changes in monocyte and dendritic cell surface marker expression, subset frequencies and monocyte subset cytokine release in COVID‐19 subjects. Monocyte and dendritic cell clusters from Figure 2(A) were subclustered and displayed in their own UMAP (A). Heatmap displaying each subcluster's scaled median expression of 34 markers (B). Box and whisker plots showing median expression of cell surface markers within all monocytes and dendritic cells used in this subclustering analysis for healthy, nonhospitalized, and hospitalized subjects (C). Box and whisker plots of individual cell clusters as a proportion of all cells in this subclustering analysis between healthy, nonhospitalized, and hospitalized subjects (D). CD9⁺ and CD9^– human monocytes were sorted from healthy human blood and 0.5 × 10⁶ monocytes were incubated with 100 ng/ml of LPS or vehicle control for 16 h. Cell supernatants were collected and used in Luminex analysis for cytokine release quantification (E). Stacked violin plots displaying median expression of CD9, Slan, PDL1, and PDL2 in healthy, nonhospitalized, and hospitalized subjects in each subcluster of monocytes and dendritic cells. The dots represent each individual's median expression levels and the black horizontal bars represent the median expression levels of each condition (F). Statistically significant (p ≤ 0.05) changes were calculated using adjusted p values generated after a multiple‐comparisons correction. Changes in cluster frequencies were calculated using GLMM, changes in marker expression were calculated with LIMMA and changes in cytokine release were calculated with one‐way ANOVA with a post hoc Tukey's test

FIGURE 3

Changes in monocyte and dendritic cell surface marker expression, subset frequencies and monocyte subset cytokine release in COVID‐19 subjects. Monocyte and dendritic cell clusters from Figure 2(A) were subclustered and displayed in their own UMAP (A). Heatmap displaying each subcluster's scaled median expression of 34 markers (B). Box and whisker plots showing median expression of cell surface markers within all monocytes and dendritic cells used in this subclustering analysis for healthy, nonhospitalized, and hospitalized subjects (C). Box and whisker plots of individual cell clusters as a proportion of all cells in this subclustering analysis between healthy, nonhospitalized, and hospitalized subjects (D). CD9⁺ and CD9^– human monocytes were sorted from healthy human blood and 0.5 × 10⁶ monocytes were incubated with 100 ng/ml of LPS or vehicle control for 16 h. Cell supernatants were collected and used in Luminex analysis for cytokine release quantification (E). Stacked violin plots displaying median expression of CD9, Slan, PDL1, and PDL2 in healthy, nonhospitalized, and hospitalized subjects in each subcluster of monocytes and dendritic cells. The dots represent each individual's median expression levels and the black horizontal bars represent the median expression levels of each condition (F). Statistically significant (p ≤ 0.05) changes were calculated using adjusted p values generated after a multiple‐comparisons correction. Changes in cluster frequencies were calculated using GLMM, changes in marker expression were calculated with LIMMA and changes in cytokine release were calculated with one‐way ANOVA with a post hoc Tukey's test

FIGURE 4

Monocyte and dendritic cell subsets in hospitalized subjects correlate with clinical parameters associated with COVID‐19 severity. Spearman correlation heatmaps and plots showing correlations between classical, intermediate and nonclassical monocyte clusters from Figure 2 and the clinical parameters (D‐Dimer, INR, LDH, and Ferritin values) obtained from 18 of the hospitalized subjects (A). Spearman Correlation heatmap and plots for correlations between monocyte and dendritic cell subclusters from Figure 3(A) and COVID‐19 clinical values as in Figure 4(A) and 4(B). R values are presented at the center of each heatmap block

FIGURE 5

Changes in monocyte and dendritic cell subsets and surface marker expression in moderate and severe hospitalized COVID‐19 subjects. Box and whisker plots of individual cell clusters as a proportion of all cells in the Figure 3 subclustering analysis for moderate and severe hospitalized COVID‐19 subjects (A). Box and whisker plots showing median expression of cell surface markers within all monocytes and dendritic cells used in the Figure 3 subclustering analysis for moderate and severe hospitalized COVID‐19 subjects (B). Statistically significant (p ≤ 0.05) changes were calculated using adjusted p‐values generated after a multiple‐comparisons correction. Changes in marker expression were calculated with LIMMA

FIGURE 6

Comparison of immune cell cluster frequencies in hospitalized COVID‐19 patient blood through time and characterization of CD9+ monocyte cytokine release. PBMCs from healthy (n = 8) and SARS‐CoV‐2‐infected hospitalized (n = 11) individuals collected at the initial blood draw plotted in Figure 1(A) (Day 0) or approximately 3 months after initial blood collection (∼Day 90). CyTOF files were gated in Flowjo as shown in Figures S4 and S5. Relative changes in immune cell frequencies between healthy, hospitalized at Day 0 and hospitalized at ∼Day 90 PBMCs were calculated using GLMM and displayed in box and whisker plots (A–H). Statistically significant (p ≤ 0.05) changes calculated using one‐way ANOVA with Tukey's post hoc test for the comparisons between healthy, Day 0 or ∼Day 90 hospitalized subjects or Welch's T‐test for the comparison between only Day 0 or ∼Day 90 hospitalized subjects