PMC9240225_01
Timeline of the clinical course. (A) Day 0 indicates the date of the COVID-19 symptom onset. The days post-onset at which COVID-19 related symptoms, hospitalization course, RT-PCR test results, convalescent plasma transfusions, and interventions are indicated. (B-E) Longitudinal analysis of (B) maximum body temperature, (C) C- Reactive protein (CRP) in plasma, (D) Titers of IgG against SARS-CoV-2 Spike Receptor binding domain (RBD), and (E) SARS-CoV-2 RNA in plasma. The y axis in each panel indicates the corresponding measurement unit. In all panels, the x axis indicates the day numbering as depicted in (A). In (B,C), the timeline in the x axis highlights the first hospitalization (days 14-25) and the second hospitalization (days 33-61), since the corresponding measurements were performed only in the hospital. In all panels, the vertical arrows indicate convalescent plasma transfusions from anonymous donor (1st) and from a patient's relative (2nd and 3rd). The asterisk indicates the drop in viral load recorded at day 57 (A). The low-level anti-RBD IgG seen pre-transfusion (D) are consistent with the lack of B cell detection in the patient's peripheral blood by clinical flow cytometry tests (data not shown), which are presumably due to the use of rituximab and/or methotrexate for MAS, since treatment with these drugs can reduce B cell frequencies and humoral immune responses. In (E), Ct, cycle threshold; N, SARS-CoV-2 nucleocapsid gene; RdRP, SARS-CoV-2 RNA-dependent RNA polymerase gene.
fmed-09-915367-g0001.jpg
PMC9240225_01_fmed-09-915367-g0001.jpg
F1
In March 2020, a 52-year-old white woman with multiple autoimmune syndrome (MAS), including rheumatoid arthritis and systemic lupus erythematosus developed flu-like symptoms (Figure 1A). The hospital course was complicated by hypotension (68/44 mm Hg) and hypothermia on day 17 (93.1 F) (Figure 1B), requiring transfer to the medical intensive care unit and pharmacologic blood pressure support. She continued to have high fevers twice daily, accompanied by increasing C-reactive protein (CRP) levels (Figures 1B,C). Plasma from a patient's relative, who had recovered from COVID-19, showed high anti-SARS-CoV-2 RBD IgG titers (Supplementary Figure S1) and was selected for donation (600 mL; on day 54). Concurrently, fevers abruptly resolved on day 57 (Figure 1B) and plasma markers of inflammation, such as CRP, decreased rapidly (Figure 1C). The SARS-CoV-2 PCR test remained stably negative after this transfusion for >20 days (Figure 1A), after which testing was discontinued. Antibody binding assays performed for >20 days after her discharge showed stable levels of anti-RBD IgG (Figure 1D). The SARS-CoV-2 RNAemia was observed before the beneficial transfusion and became undetectable post-transfusion (Figure 1E). Utilizing peripheral blood samples collected from the patient at multiple times pre- and post-transfusion with her relative's plasma (as indicated in Figure 1A), we performed cytokine and proteomic analysis of plasma collected from the patient collected from the patient on the day of (prior to) the first transfusion (i.e., day 54 post-symptom onset), and multiple times thereafter (see Figure 1A for blood collection points). We next utilized single-cell RNA sequencing to analyze transcriptional changes occurring in peripheral blood cells collected from the patient on the day of (prior to) the first transfusion with her relative's plasma (i.e., day 54 post-symptom onset), and multiple times thereafter (see Figure 1A for blood collection points).
Unsupervised hierarchical clustering and principal component analysis (PCA) of cytokines and proteins in the recipient's plasma before and after convalescent plasma transfusion. (A,B) Unsupervised hierarchical clustering was performed on plasma cytokine profile and proteomic data using MATLAB. Vertical arrows in (B) mark the set of proteins that decrease (orange arrow) or increase (green arrow) following transfusion. (C,D) PCA was conducted on plasma cytokine profile (C) and proteome (D). The variance accounted for by PC1 is shown on the x-axis and the variance accounted for by PC2 on the y-axis. Numbers indicate days post-symptom onset as shown in (A,B). Blue arrows illustrate the distribution of PC1 scores, which were self-organized in a temporal trajectory. (E,F) The top 10 enriched KEGG pathways for proteins that decrease (orange bars) (referred to as module A in Supplementary Figure S2 and in the text) or increase (green bars) (module B in Supplementary Figure S2 and in the text) using EnrichR Pathway Analysis.
fmed-09-915367-g0002.jpg
PMC9240225_01_fmed-09-915367-g0002.jpg
F2
Unbiased hierarchical clustering analysis and principal component analysis revealed dynamic changes in plasma cytokine and protein concentrations over four temporal phases following transfusion (Figures 2A-D). Changes in the abundance of plasma proteins became detectable between days 56 and 61 (Figures 2A,B):a few days after the transfusion, and slightly preceded those in plasma cytokines. Plasma proteins exhibited a more complex behavior, with some proteins decreasing (Figure 2B, orange vertical arrow) and others increasing (Figure 2B, green vertical arrow) following transfusion. B, respectively (see Supplementary Figure S2 for contribution to Principal Component 1 of the two Modules). Pathway enrichment analysis using the Enrichr tool identified "complement and coagulation cascades" as top term in both Module A and Module B (Figures 2E,F), reflecting the known complement and coagulation disorders associated with severe disease by SARS-CoV-2 and other pathogenic coronaviruses. Proteins included in this term in Module A (Figure 2E) were predominantly components of the complement cascade (Table 1), consistent with complement hyperactivation potentially causing host tissue damage and disease and being associated with severe COVID-19. The second top term in Module A is "pertussis" (Figure 2E). The third pathway in Module A was "antigen processing and presentation" (Figure 2E). As mentioned above, the top term in the pathway analysis in Module B, which increased with convalescent plasma transfusion, was also "complement and coagulation cascades" (Figure 2F). The second pathway in Module B is "Extracellular matrix (ECM) receptor interaction" (Figure 2F; Table 1). Proteins associated with ECM receptors and focal adhesion (the fourth topmost pathway in Module B, Figure 2F) have been found decreased in the lung tissue of patients deceased with COVID-19 pneumonia, suggesting dysregulation of the lung extracellular microenvironment. First, the pre-transfusion high levels of TNF-alpha in plasma (data included in Figure 2A) were likely produced by cell types other than this unique monocyte cluster.
Single cell transcriptomics of recipient's peripheral blood mononuclear cells before and after convalescent plasma transfusion. (A) Uniform Manifold Approximation and Projection (UMAP) distribution of single cells grouped by time-post-transfusion sample. Day 0 is the sample obtained just before the first transfusion with the relative's convalescent plasma. (B) Cell types were determined using Seurat's MapQuery function along with their PBMC reference dataset. It is worth noting that none of the cell types identified in (B) could be assigned to B cells, both prior to the transfusion and for the duration of the post-transfusion analysis, in agreement with flow cytometry data recorded in the patient's hospital chart, as mentioned in the legend to Figure 1. (C) Histogram of Hallmark gene set enrichment analysis (GSEA) using differentially expressed genes of the unique monocyte cluster identified at day 0 compared to monocytes across other data clusters. (D) Heatmap showing the expression levels of type I Interferon-regulated genes in predicted T cells, monocytes, and NK cells. The color code of the "days post-transfusion" bar corresponds to the color code in (A).
fmed-09-915367-g0003.jpg
PMC9240225_01_fmed-09-915367-g0003.jpg
F3
Unsupervised clustering identified one data cluster that was observed pre-transfusion but was absent at subsequent days (Figure 3A). Cell type identification analysis using the Seurat package identified this data cluster as being constituted by monocytes (Figure 3B). The top hits among upregulated genes [positive normalized enrichment score (NES)] included genes involved in responses to interferon (IFN) alpha (type I), IFN gamma (type II), inflammatory responses, and complement and coagulation (Figure 3C). TNF-alpha (Figure 3C). The downregulation of MYC targets is difficult to interpret given the highly diverse cellular functions of the ~ 400 genes in this gene set. The finding that TNF-alpha signaling is decreased in the monocyte cluster unique to the pre-transfusion state leads to two sets of considerations. T cell subsets, and that this strong IFN response was dampened post-transfusion also in these cell types (Figure 3D). Together, these data show that the beneficial effects of the relative's plasma transfusion were accompanied by the elimination of a unique population of disease-associated, hyperinflammatory monocytes.