PT  - JOURNAL ARTICLE
AU  - Yingxin Lin
AU  - Lipin Loo
AU  - Andy Tran
AU  - Cesar Moreno
AU  - Daniel Hesselson
AU  - Greg Neely
AU  - Jean Y.H. Yang
TI  - Characterization of cell-cell communication in COVID-19 patients
AID  - 10.1101/2020.12.30.424641
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.12.30.424641
4099  - http://biorxiv.org/content/early/2020/12/30/2020.12.30.424641.short
4100  - http://biorxiv.org/content/early/2020/12/30/2020.12.30.424641.full
AB  - COVID-19 patients display a wide range of disease severity, ranging from asymptomatic to critical symptoms with high mortality risk. Our ability to understand the interaction of SARS-CoV-2 infected cells within the lung, and of protective or dysfunctional immune responses to the virus, is critical to effectively treat these patients. Currently, our understanding of cell-cell interactions across different disease states, and how such interactions may drive pathogenic outcomes, is incomplete. Here, we developed a generalizable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes and use it to examine five public single-cell RNA-seq datasets with a total of 85 individual samples. By characterizing the cell-cell interaction patterns across epithelial and immune cells in lung tissues for patients with varying disease severity, we illustrate diverse communication patterns across individuals, and discover heterogeneous communication patterns among moderate and severe patients. We further illustrate patterns derived from cell-cell interactions are potential signatures for discriminating between moderate and severe patients.Competing Interest StatementThe authors have declared no competing interest.