Longitudinal Analysis of Biologic Correlates of COVID-19 Resolution: Case Report

Abstract

While the biomarkers of COVID-19 severity have been thoroughly investigated, the key biological dynamics associated with COVID-19 resolution are still insufficiently understood. We report a case of full resolution of severe COVID-19 due to convalescent plasma transfusion. Following transfusion, the patient showed fever remission, improved respiratory status, and rapidly decreased viral burden in respiratory fluids and SARS-CoV-2 RNAemia. Longitudinal unbiased proteomic analysis of plasma and single-cell transcriptomics of peripheral blood cells conducted prior to and at multiple times after convalescent plasma transfusion identified the key biological processes associated with the transition from severe disease to disease-free state. These included (i) temporally ordered upward and downward changes in plasma proteins reestablishing homeostasis and (ii) post-transfusion disappearance of a subset of monocytes characterized by hyperactivated Interferon responses and decreased TNF-α signaling. Monitoring specific dysfunctional myeloid cell subsets in peripheral blood may provide prognostic keys in COVID-19.

Keywords: RNAemia; convalescent plasma therapy; plasma proteomics; severe COVID-19; single-cell transcriptomics.

Figure 1

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 (13, 14). In (E), Ct, cycle threshold; N, SARS-CoV-2 nucleocapsid gene; RdRP, SARS-CoV-2 RNA-dependent RNA polymerase gene.

Figure 2

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.

Figure 3

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).