bioRxivImmunology
Low baseline pulmonary levels of cytotoxic lymphocytes as a predisposing risk factor for severe COVID-19
Abstract
COVID-19 is caused by the coronavirus SARS-CoV-2 and currently has detrimental human health, community and economic impacts around the world. It is unclear why some SARS-CoV-2-positive individuals remain asymptomatic, while others develop severe symptoms. Baseline pulmonary levels of anti-viral leukocytes, already residing in the lung prior to infection, may orchestrate an effective early immune response and prevent severe symptoms. Using "in silico flow cytometry", we deconvoluted the levels of all seven types of anti-viral leukocytes in 1,927 human lung tissues. Baseline levels of CD8+ T cells, resting NK cells and activated NK cells, as well as cytokines that recruit these, are significantly lower in lung tissues with high expression of the SARS-CoV-2 entry receptor ACE2. We observe this in univariate analyses, in multivariate analyses, and in two independent datasets. Relevantly, ACE2 mRNA and protein levels very strongly correlate in human cells and tissues. Above findings also largely apply to the SARS-CoV-2 entry protease TMPRSS2. Both SARS-CoV-2-infected lung cells and COVID-19 lung tissues show upregulation of CD8+ T cell- and NK cell-recruiting cytokines. Moreover, tissue-resident CD8+ T cells and inflammatory NK cells are significantly more abundant in bronchoalveolar lavages from mildly affected COVID-19 patients, compared to severe cases. This suggests that these lymphocytes are important for preventing severe symptoms. Elevated ACE2 expression increases sensitivity to coronavirus infection. Thus, our results suggest that some individuals may be exceedingly susceptible to develop severe COVID-19 due to concomitant high pre-existing ACE2 and TMPRSS expression and low baseline cytotoxic lymphocyte levels in the lung.
- organism: human
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
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