A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.
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DOI:
10.1016/j.cell.2022.01.012
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发表时间:
2022-03-03
期刊:
影响因子:
64.5
通讯作者:
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium
中科院分区:
生物学1区
文献类型:
--
作者:
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. Electronic address: julian.knight@well.ox.ac.uk;COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium

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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. Blood atlas delineating innate and adaptive immune dysregulation in COVID-19 Shared and specific immune signatures of COVID-19, influenza and all cause sepsis Multi-omic immune profiling differentiates hospitalized patient severity in COVID-19 Immune activation and proliferation involving AP-1/p38MAPK associated with COVID-19 A multi-omic analysis of patient blood samples reveals both similarities and specific features of COVID-19 when compared with samples obtained from sepsis or influenza patients, which could yield better targeted therapies for severe COVID-19.
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