Abstract
Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in people critically ill with COVID-19. Here, we present high-dimensional profiling of blood and respiratory samples from people with severe COVID-19 to examine the association between cell-linked molecular features and mortality outcomes. Peripheral transcriptional profiles by single-cell RNA sequencing (RNA-seq)-based deconvolution of immune states are associated with COVID-19 mortality. Further, persistently high levels of an interferon signaling module in monocytes over time lead to subsequent concerted upregulation of inflammatory cytokines. SARS-CoV-2-infected myeloid cells in the lower respiratory tract upregulate CXCL10 , leading to a higher risk of death. Our analysis suggests a pivotal role for viral-infected myeloid cells and protracted interferon signaling in severe COVID-19.
Keywords: COVID-19; COVID-19 outcome; gene modules; inflammatory cytokines; inflammatory monocytes; machine learning; severe COVID-19; single-cell RNA-seq; type I interferon.
【저자키워드】 COVID-19, severe COVID-19, machine learning, type I interferon, single-cell RNA-seq, Inflammatory cytokines, COVID-19 outcome, gene modules, inflammatory monocytes, 【초록키워드】 Mortality, CXCL10, type I interferon, Single-cell RNA sequencing, monocyte, outcomes, Critically ill, death, interferon signaling, single-cell, Blood, association, Analysis, Inflammatory, Lower respiratory tract, higher risk, upregulation, myeloid cell, peripheral, respiratory sample, subsequent, contribute, analyses, immune cell state, immune state, molecular feature, transcriptional profile, with COVID-19, 【제목키워드】 SARS-CoV-2, Mortality, Immune profile, lung, Critically ill, Predictive, viral burden, with COVID-19,