Multiomic analysis reveals cell-type-specific molecular determinants of COVID-19 severity

Abstract

The determinants of severe COVID-19 in healthy adults are poorly understood, which limits the opportunity for early intervention. We present a multiomic analysis using machine learning to characterize the genomic basis of COVID-19 severity. We use single-cell multiome profiling of human lungs to link genetic signals to cell-type-specific functions. We discover >1,000 risk genes across 19 cell types, which account for 77% of the SNP-based heritability for severe disease. Genetic risk is particularly focused within natural killer (NK) cells and T cells, placing the dysfunction of these cells upstream of severe disease. Mendelian randomization and single-cell profiling of human NK cells support the role of NK cells and further localize genetic risk to CD56bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated …

Publication
Cell systems
Prof. Sai Zhang
Prof. Sai Zhang
Assistant Professor
Prof. Peng Gao
Prof. Peng Gao
Assistant Professor
Xiaotao SHEN/申小涛
Xiaotao SHEN/申小涛
Nanyang Assistant Professor

Metabolomics, Multi-omics, Bioinformatics, Systems Biology.