Human Genetic Variants Associated with COVID-19 Severity are Enriched in Immune and Epithelium Regulatory Networks.

Human genetic variants can influence the severity of symptoms infected with SARS-COV-2. Several genome-wide association studies have identified human genomic risk single nucleotide polymorphisms (SNPs) associated with coronavirus disease 2019 (COVID-19) severity. However, the causal tissues or cell types underlying COVID-19 severity are uncertain. In addition, candidate genes associated with these risk SNPs were investigated based on genomic proximity instead of their functional cellular contexts. Here, we compiled regulatory networks of 77 human contexts and revealed those risk SNPs' enriched cellular contexts and associated risk SNPs with transcription factors, regulatory elements, and target genes. Twenty-one human contexts were identified and grouped into two categories: immune cells and epithelium cells. We further aggregated the regulatory networks of immune cells and epithelium cells. These two aggregated regulatory networks were investigated to reveal their association with risk SNPs' regulation. Two genomic clusters, the chemokine receptors cluster and the oligoadenylate synthetase (OAS) cluster, showed the strongest association with COVID-19 severity, and they had different regulatory programs in immune and epithelium contexts. Our findings were supported by analysis of both SNP array and whole genome sequencing-based genome wide association study (GWAS) summary statistics. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00066-x.

Innate immune imprints in SARS-CoV-2 Omicron variant infection convalescents.

SARS-CoV-2 Omicron variant infection generally gives rise to asymptomatic to moderate COVID-19 in vaccinated people. The immune cells can be reprogrammed or "imprinted" by vaccination and infections to generate protective immunity against subsequent challenges. Considering the immune imprint in Omicron infection is unclear, here we delineate the innate immune landscape of human Omicron infection via single-cell RNA sequencing, surface proteome profiling, and plasma cytokine quantification. We found that monocyte responses predominated in immune imprints of Omicron convalescents, with IL-1ß-associated and interferon (IFN)-responsive signatures with mild and moderate symptoms, respectively. Low-density neutrophils increased and exhibited IL-1ß-associated and IFN-responsive signatures similarly. Mild convalescents had increased blood IL-1ß, CCL4, IL-9 levels and PI3+ neutrophils, indicating a bias to IL-1ß responsiveness, while moderate convalescents had increased blood CXCL10 and IFN-responsive monocytes, suggesting durative IFN responses. Therefore, IL-1ß- or IFN-responsiveness of myeloid cells may indicate the disease severity of Omicron infection and mediate post-COVID conditions.

Human Genetic Variants Associated with COVID-19 Severity are Enriched in Immune and Epithelium Regulatory Networks

Human genetic variants can influence the severity of symptoms infected with SARS-COV-2. Several genome-wide association studies have identified human genomic risk single nucleotide polymorphisms (SNPs) associated with coronavirus disease 2019 (COVID-19) severity. However, the causal tissues or cell types underlying COVID-19 severity are uncertain. In addition, candidate genes associated with these risk SNPs were investigated based on genomic proximity instead of their functional cellular contexts. Here, we compiled regulatory networks of 77 human contexts and revealed those risk SNPs’ enriched cellular contexts and associated risk SNPs with transcription factors, regulatory elements, and target genes. Twenty-one human contexts were identified and grouped into two categories: immune cells and epithelium cells. We further aggregated the regulatory networks of immune cells and epithelium cells. These two aggregated regulatory networks were investigated to reveal their association with risk SNPs’ regulation. Two genomic clusters, the chemokine receptors cluster and the oligoadenylate synthetase (OAS) cluster, showed the strongest association with COVID-19 severity, and they had different regulatory programs in immune and epithelium contexts. Our findings were supported by analysis of both SNP array and whole genome sequencing-based genome wide association study (GWAS) summary statistics. Supplementary Information The online version contains supplementary material available at 10.1007/s43657-022-00066-x.

Identification of Distinct Immune Cell Subsets Associated With Asymptomatic Infection, Disease Severity, and Viral Persistence in COVID-19 Patients.

The cell-mediated protective and pathogenic immune responses to SARS-CoV-2 infection remain largely elusive. Here we identified 76 distinct cell subsets in the PBMC samples that were associated with various clinical presentations of COVID-19 using scRNA-seq technology coupled with a deep and comprehensive analysis of unique cell surface markers and differentially expressed genes. We revealed that (TRAV1-2+CD8+)MAIT cells and (NCAM1hiCD160+)NK cells significantly enriched in the asymptomatic subjects whereas (LAG3+CD160+CD8+)NKT cells increased in the symptomatic patients. We also observed that (CD68-CSF1R-IL1BhiCD14+)classical monocytes were positively correlated with the disease severity. Moreover, (CD33-HLA-DMA-CD14+)classical monocytes and (CLEC10A-S100A9lo)pDC were associated with the viral persistence. The GO and KEGG analyses identified enriched pathways related to immune responses, inflammation, and apoptosis. These findings may enhance our understanding of the immunopathogenesis of COVID-19 and help develop novel strategies against SARS-CoV-2 infection.

SARS-CoV-2 exacerbates proinflammatory responses in myeloid cells through C-type lectin receptors and Tweety family member 2.

Despite mounting evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) engagement with immune cells, most express little, if any, of the canonical receptor of SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2). Here, using a myeloid cell receptor-focused ectopic expression screen, we identified several C-type lectins (DC-SIGN, L-SIGN, LSECtin, ASGR1, and CLEC10A) and Tweety family member 2 (TTYH2) as glycan-dependent binding partners of the SARS-CoV-2 spike. Except for TTYH2, these molecules primarily interacted with spike via regions outside of the receptor-binding domain. Single-cell RNA sequencing analysis of pulmonary cells from individuals with coronavirus disease 2019 (COVID-19) indicated predominant expression of these molecules on myeloid cells. Although these receptors do not support active replication of SARS-CoV-2, their engagement with the virus induced robust proinflammatory responses in myeloid cells that correlated with COVID-19 severity. We also generated a bispecific anti-spike nanobody that not only blocked ACE2-mediated infection but also the myeloid receptor-mediated proinflammatory responses. Our findings suggest that SARS-CoV-2-myeloid receptor interactions promote immune hyperactivation, which represents potential targets for COVID-19 therapy.

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.