Single-Cell Omics Reveals Dyssynchrony of the Innate and Adaptive Immune System in Progressive COVID-19

Abstract

A dysregulated immune response against the SARS-CoV-2 virus plays a critical role in severe COVID-19. However, the molecular and cellular mechanisms by which the virus causes lethal immunopathology are poorly understood. Here, we utilize multi-omics single-cell analysis to probe dynamic immune responses in patients with stable or progressive manifestations of COVID-19, and assess the effects of tocilizumab, an anti-IL-6 receptor monoclonal antibody. Coordinated profiling of gene expression and cell lineage protein markers reveals a prominent type-1 interferon response across all immune cells, especially in progressive patients. An anti-inflammatory innate immune response and a pre-exhaustion phenotype in activated T cells are hallmarks of progressive disease. Skewed T cell receptor repertoires in CD8 T cells and uniquely enriched V(D)J sequences are also identified in COVID-19 patients. B cell repertoire and somatic hypermutation analysis are consistent with a primary immune response, with possible contribution from memory B cells. Our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19, which may contribute to delayed virus clearance and has implications for therapeutic intervention.

Post-infectious inflammatory disease in MIS-C features elevated cytotoxicity signatures and autoreactivity that correlates with severity

“…Consistent with previous scRNAseq studies, COVID19-A samples also showed an elevated S100A score compared to A.HD (Figure 3d) 19 . Pathway enrichment on shared down-regulated genes in monocytes and neutrophils revealed a significant reduction in antigen-presentation and processing, and as in COVID-19 23 , MIS-C patients had significantly reduced HLA class II (HLA-DP, DQ, and DR) expression ( Figure 3e there was a significant enrichment in myeloid-derived proteins among the differentially expressed proteins in serum (p = 1.7x10 -12 ) (Figure 3g).…”

Longitudinal immune profiling of mild and severe COVID-19 reveals innate and adaptive immune dysfunction and provides an early prediction tool for clinical progression

“…While proof-of-principle, our classifier of severe disease shows robustness and overall value in predicting disease progression based on immune profiling and near-real-time disease monitoring. Thus, it may be valuable to inform clinical action like that proposed in chronic diseases with other high-dimensional assays [50][51][52] . Moreover, we demonstrated that a classifier with a limited number of markers retains good performance.…”

“…While this may not necessarily imply absolute changes in cell numbers, we observed good overall agreement between changes in proportions and absolute counts when comparing severe and mild disease status ( Supplementary Figure 6 and Supplementary Table 7). This highlights the importance of studies employing orthogonal modalities such as cytokine profiling 51 , single-cell RNA sequencing [52][53][54][55][56] , and their integration 57,58 . Nevertheless, even without orthogonal studies, our machine learning approach for predicting disease severity demonstrates predictive potential, although it should be tested in a validation cohort before use in a clinical setting.…”

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

“…ARID5A, SOCS3, PIM1, BCL3, BATF, MYC that are associated with the IL-6 pathway 56 . Cytotoxicity associated genes include PRF1, GZMH, IFNG, NKG7, KLRG1, PRF1 56 and GNLY, GZMB, GZMK 78 .…”