ABSTRACT
We describe a large-scale community effort to build an open-access, interoperable, and computable repository of COVID-19 molecular mechanisms - the COVID-19 Disease Map. We discuss the tools, platforms, and guidelines necessary for the distributed development of its contents by a multi-faceted community of biocurators, domain experts, bioinformaticians, and computational biologists. We highlight the role of relevant databases and text mining approaches in enrichment and validation of the curated mechanisms. We describe the contents of the Map and their relevance to the molecular pathophysiology of COVID-19 and the analytical and computational modelling approaches that can be applied for mechanistic data interpretation and predictions. We conclude by demonstrating concrete applications of our work through several use cases and highlight new testable hypotheses.
ABSTRACT
The pandemic spread of the potentially life-threatening disease COVID-19 requires a thorough understanding of the longitudinal dynamics of host responses. Temporal resolution of cellular features associated with a severe disease trajectory will be a pre-requisite for finding disease outcome predictors. Here, we performed a longitudinal multi-omics study using a two-centre German cohort of 13 patients (from Cologne and Kiel, cohort 1). We analysed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. The results from single-cell and bulk transcriptome analyses were validated in two independent cohorts of COVID-19 patients from Bonn (18 patients, cohort 2) and Nijmegen (40 patients, cohort 3), respectively. We observed an increase of proliferating, activated plasmablasts in severe COVID-19, and show a distinct expression pattern related to a hyperactive cellular metabolism of these cells. We further identified a notable expansion of type I IFN-activated circulating megakaryocytes and their progenitors, indicative of emergency megakaryopoiesis, which was confirmed in cohort 2. These changes were accompanied by increased erythropoiesis in the critical phase of the disease with features of hypoxic signalling. Finally, projecting megakaryocyte- and erythroid cell-derived co-expression modules to longitudinal blood transcriptome samples from cohort 3 confirmed an association of early temporal changes of these features with fatal COVID-19 disease outcome. In sum, our longitudinal multi-omics study demonstrates distinct cellular and gene expression dynamics upon SARS-CoV-2 infection, which point to metabolic shifts of circulating immune cells, and reveals changes in megakaryocytes and increased erythropoiesis as important outcome indicators in severe COVID-19 patients.
