As of June 15, 2022, more than 540 million people are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the 2019 coronavirus disease (COVID-19), of which more than 6.3 million are died.
Age and the presence of certain co-morbidities have been associated with an increased risk of severe COVID-19 and death. Several other factors, including specific genetic predispositions, are also thought to increase a person’s chance of developing severe COVID-19; however, this association remains poorly understood.
Study: Multiomic analysis reveals cell type-specific molecular determinants of COVID-19 severity† Image Credit: Alpha Tauri 3D Graphics/Shutterstock
Previous observational studies have shown that the severity of COVID-19 may be correlated with elevated levels of several immune cells, including CD8 T cells, CD19 B cells, eosinophils, myeloid cells, as well as various immune cell subtypes, such as adaptive natural killer (NK ) cells. Similar findings have been confirmed with transcriptomic studies; however, these changes in immune cell types were likely due to the acute infection and do not necessarily represent a predictive marker for severe disease.
The hyperinflammatory response that occurs in the lungs of patients experiencing severe COVID-19 is a primary cause of morbidity and mortality in these patients. As a result, most interventions currently approved for use in the treatment of severe COVID-19 are repurposed drugs that aim to suppress this immune response.
As SARS-CoV-2 has become an endemic virus, it is essential for researchers to better understand the precise mechanisms involved in the pathogenesis of COVID-19, especially in severe cases. This information would then contribute to the development of more potent and effective therapies.
About the study
in a recent cell systems In this study, researchers used the RefMap machine learning algorithm to correlate known genomic variations for severe COVID-19 obtained from large-scale genome-wide association studies (GWAS) with single-cell multiome profiling of human lungs. One of the main advantages of this combined approach is that it allowed the researchers to identify functional regions within the genome associated with severe COVID-19 and integrate this information with cell type-specific functions.
In addition, RefMap reduces search space by modeling the entire genetic architecture of critical diseases through the use of a unified probabilistic model. Thus, by capturing more complex genetic structures, researchers can avoid a multiple test correction, ultimately increasing its statistical power.
For the human lung samples, both single-nucleus ribonucleic acid sequencing (snRNA-seq) and single-nucleus assay for transpose-accessible chromatin using sequencing (snATAC-seq) were performed.
A total of 19 different cell types were identified by these sequencing assays, including several epithelial, endothelial and hematopoietic cell types. RefMap was then used to correlate disease-related genomic regions from the COVID-19 GWAS data with reported peaks from these 19 cell types.
Scheme of the study design (AH) The COVID-19 GWAS and human lung unicellular multiome (A) are integrated by the RefMap model shown in (B), where gray nodes represent observations, green nodes represent local hidden variables and pink nodes represent global hidden variables (STAR methods). Cell type-specific risk genes are mapped using single-cell multiome profiling (C). Heredity analysis (D), Mendelian randomization (E), transcriptome analysis (F), and network analysis (G) together characterize the functional importance of RefMap genes, especially for NK cells, in severe COVID-19. Rare variant analysis (H) orthogonally supports the role of NK cells in severe disease. cCRE, candidate cis-regulatory element.
Together, the researchers identified 1,370 genes associated with severe COVID-19, with hematopoietic cells containing the greatest number of unique RefMap regions and genes of all cell types. These genes were responsible for 77% of the single nucleotide polymorphism (SNP)-based heritability for severe COVID-19. Some of the key RefMap COVID-19 genes associated with severe disease included increased expression of LZTFL1 in ciliated epithelial cells and increased activity of the metalloprotease ADAMP9.
The researchers were next interested in characterizing the functional roles of these severe COVID-19 genes. To this end, four transcriptional factors (TFs) including CUX1, TCF12, ZEB1, and ZEB2 binding motifs were found to be enriched in at least one of 19 cell types.
Notably, ZEB2 was only enriched in NK cell risk areas. Since ZEB2 plays an important role in NK cell maturation, the authors concluded that severe COVID-19 can arise from the failed maturation of NK cells.
Further analysis of the expression of NK cell subtypes in the severe COVID-19 genes led to the identification of an increased expression of CD56bright NK cells, especially when compared to the expression of CD56dim cells. While CD56bright NK cells are responsible for the production of cytokines and modulate the immune response, CD56dim NK cells are directly cytotoxic.
Compared to the total set of RefMap NK cell genes, CD56bright NK cell genes were found to be highly enriched in heritability for severe COVID-19 to a greater extent than that of any other profiled cell type. This finding indicates that altered function and/or deficiency of CD56bright NK cells inhibit the efficient production of important cytokines, especially interferon (IFN-γ).
The genetics-based approach used in the current study provided evidence that correlates with previous observational reports on the relationship between altered CD56bright NK cell function and severe COVID-19. Due to the important role of CD56bright NK cells in the innate immune response, their deficiency can accelerate the uncontrolled viral replication of SARS-CoV-2.
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