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

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Highlights

Authors: Sai Zhang, Johnathan Cooper-Knock, Annika K. Weimer, Minyi Shi, Lina Kozhaya, Derya Unutmaz, Calum Harvey, Thomas H. Julian, Simone Furini, Elisa Frullanti, Francesca Fava, Alessandra Renieri, Peng Gao, Xiaotao Shen, Ilia Sarah Timpanaro, Kevin P. Kenna, J. Kenneth Baillie, Mark M. Davis, Michael P. Snyder

• Machine learning combines GWAS with single-cell omics to discover COVID-19 risk genes
• Discovering that severe COVID-19 risk genes account for 77% of the observed heritability
• Genetic risk for severe COVID-19 is focused within NK cells and T cellsMendelian randomization and single-cell multiomics highlight CD56^bright NK cells

Summary

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 CD56^bright NK cells, which are key cytokine producers during the innate immune response. Rare variant analysis confirms the enrichment of severe-disease-associated genetic variation within NK-cell risk genes. Our study provides insights into the pathogenesis of severe COVID-19 with potential therapeutic targets.

Keywords

• COVID-19
• genome-wide association study
• GWAS
• machine learning
• single-cell multiomic profiling
• NK cell
• gene discovery
• network analysis
• rare variant analysis
• Mendelian randomization

Introduction

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) giving rise to coronavirus disease 2019 (COVID-19) has caused a global pandemic with almost unprecedented morbidity and mortality (Dong et al., 2020). Severity of COVID-19 is markedly variable ranging from an asymptomatic infection to fatal multiorgan failure. Severity correlates with age and comorbidities (Shang et al., 2020) but not exclusively (Li et al., 2020). Host genetics is thought to be an essential determinant of severity (The COVID-19 Host Genetics Initiative, 2020), but this is poorly understood. Improved tools to identify individuals at risk of severe COVID-19 could facilitate life-saving precision medicine.

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Figure 2A