Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19.
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COVID-19, SARS-CoV-2, blood, coronavirus, epigenetics, immune, multi-omics, personalized medicine, proteomics, transcriptomics, Adult, Biomarkers, Blood Proteins, COVID-19, Cell Cycle Proteins, Female, Humans, Influenza, Human, Lymphocytes, Machine Learning, Male, Middle Aged, Mitogen-Activated Protein Kinase 14, Monocytes, Principal Component Analysis, Proteome, SARS-CoV-2, Sepsis, Severity of Illness Index, Transcription Factor AP-1