Cited by 328COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 ResearchSepsis Diagnosis and Treatment

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

Open access
Ahern, David J., Ai, Zhichao, Ainsworth, Mark, Allan, Chris, Allcock, Alice, Angus, Brian, Ansari, M. Azim, Arancibia-Cárcamo, Carolina V. +197 more·2022·Cell

Published version of a preprint

Abstract

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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  • Many studies have characterised complex patterns of viral-induced abnormalities in haematology biochemistry panels.

    “Many studies have characterised complex patterns of viral-induced abnormalities in haematology biochemistry panels,18, 19”

    From Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening (2022) · cites this paper as [18]

    The Discussion describes complex blood immune and proteomic changes in COVID-19 and influenza, and STAR Methods (Experimental model and subject details; page unavailable) lists routine blood-count and biochemical measurements collected for COVID-19 and sepsis patients. The paper therefore supports viral-associated blood abnormalities, but the cited passages do not show that it characterized complex patterns specifically in routine haematology and biochemistry panels. (LLM, conf=0.78)

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  • SASP-typical cytokines, extracellular matrix-active proteases, and SASP-related pro-coagulant and complement-activating factors are strongly elevated in the serum of COVID-19 patients compared with healthy controls.

    “were also strongly elevated in the serum of patients with COVID-19 compared to healthy controls28,52,67–70.”

    From COVID-19 and cellular senescence (2023) · cites this paper as [70]

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  1. Taguchi Y. One-class Differential Expression Analysis using Tensor Decomposition-based Unsupervised Feature Extraction Applied to Integrated Analysis of Multiple Omics Data from 26 Lung Adenocarcinoma Cell Lines. Paper presented at: 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) 2017

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Authors
Ahern, D. J., Ai, Z., Ainsworth, M., Allan, C., Allcock, A., Angus, B., Ansari, M. A., Arancibia-Cárcamo, C. V., Aschenbrenner, D., Attar, M., Baillie, J. K., Barnes, E., Bashford-Rogers, R., Bashyal, A., Beer, S., Berridge, G., Beveridge, A., Bibi, S., Bicanic, T., Blackwell, L., Bowness, P., Brent, A., Brown, A., Broxholme, J., Buck, D., Burnham, K. L., Byrne, H., Camara, S., Candido Ferreira, I., Charles, P., Chen, W., Chen, Y.-L., Chong, A., Clutterbuck, E. A., Coles, M., Conlon, C. P., Cornall, R., Cribbs, A. P., Curion, F., Davenport, E. E., Davidson, N., Davis, S., Dendrou, C. A., Dequaire, J., Dib, L., Docker, J., Dold, C., Dong, T., Downes, D., Drakesmith, H., Dunachie, S. J., Duncan, D. A., Eijsbouts, C., Esnouf, R., Espinosa, A., Etherington, R., Fairfax, B., Fairhead, R., Fang, H., Fassih, S., Felle, S., Fernandez Mendoza, M., Ferreira, R., Fischer, R., Foord, T., Forrow, A., Frater, J., Fries, A., Gallardo Sanchez, V., Garner, L. C., Geeves, C., Georgiou, D., Godfrey, L., Golubchik, T., Gomez Vazquez, M., Green, A., Harper, H., Harrington, H. A., Heilig, R., Hester, S., Hill, J., Hinds, C., Hird, C., Ho, L.-P., Hoekzema, R., Hollis, B., Hughes, J., Hutton, P., Jackson-Wood, M. A., Jainarayanan, A., James-Bott, A., Jansen, K., Jeffery, K., Jones, E., Jostins, L., Kerr, G., Kim, D., Klenerman, P., Knight, J. C., Kumar, V., Kumar Sharma, P., Kurupati, P., Kwok, A., Lee, A., Linder, A., Lockett, T., Lonie, L., Lopopolo, M., Lukoseviciute, M., Luo, J., Marinou, S., Marsden, B., Martinez, J., Matthews, P. C., Mazurczyk, M., McGowan, S., McKechnie, S., Mead, A., Mentzer, A. J., Mi, Y., Monaco, C., Montadon, R., Napolitani, G., Nassiri, I., Novak, A., O'Brien, D. P., O'Connor, D., O'Donnell, D., Ogg, G., Overend, L., Park, I., Pavord, I., Peng, Y., Penkava, F., Pereira Pinho, M., Perez, E., Pollard, A. J., Powrie, F., Psaila, B., Quan, T. P., Repapi, E., Revale, S., Silva-Reyes, L., Richard, J.-B., Rich-Griffin, C., Ritter, T., Rollier, C. S., Rowland, M., Ruehle, F., Salio, M., Sansom, S. N., Sanches Peres, R., Santos Delgado, A., Sauka-Spengler, T., Schwessinger, R., Scozzafava, G., Screaton, G., Seigal, A., Semple, M. G., Sergeant, M., Simoglou Karali, C., Sims, D., Skelly, D., Slawinski, H., Sobrinodiaz, A., Sousos, N., Stafford, L., Stockdale, L., Strickland, M., Sumray, O., Sun, B., Taylor, C., Taylor, S., Taylor, A., Thongjuea, S., Thraves, H., Todd, J. A., Tomic, A., Tong, O., Trebes, A., Trzupek, D., Tucci, F. A., Turtle, L., Udalova, I., Uhlig, H., van Grinsven, E., Vendrell, I., Verheul, M., Voda, A., Wang, G., Wang, L., Wang, D., Watkinson, P., Watson, R., Weinberger, M., Whalley, J., Witty, L., Wray, K., Xue, L., Yeung, H. Y., Yin, Z., Young, R. K., Youngs, J., Zhang, P., & Zurke, Y.-X.
ORCID
Venue
Cell
Publisher
Elsevier BV
Published
2022-03
Volume
185
Issue
5
Pages
916-938.e58
ISSN
0092-8674 (ISSN-L)
OpenAlex
W4220939068
Cited by
328
References
155
Citations by year
2026: 37 · 2025: 62 · 2024: 71 · 2023: 99 · 2022: 52 · 2021: 7
FWCI
35.02
Type
journal article
Language
en
Open access
Locations
  • Cell (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • VU Research Portal (publishedVersion, other-oa)
  • CentAUR (University of Reading) (acceptedVersion)
  • St George's Online Research Archive (St George's University of London) (acceptedVersion)
  • Research Portal (King's College London) (submittedVersion, cc-by)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by)
Funders
  • Chinese Academy of Medical Sciences (CRUK C130623/A249471, IFMS 2018-I2M-2-002)
  • National Institutes of Health (U192U19AI082630 R24DK106766)
  • Gilead Sciences (KENN151612 KENN192004 KENN171803)
  • Engineering and Physical Sciences Research Council (EP/R018472/1 EP/R005125/1 EP/T001968/1)
  • National Institute for Health Research
  • Wellcome Trust
  • UK Research and Innovation (MR/S005471/1)
  • Medical Research Council (MCUU00016/14 12009/14 MR/S035850/1 MCPC19059)
  • Kennedy Trust for Rheumatology Research
  • University of Oxford
  • Rosetrees Trust
  • Chinese Academy of Sciences
  • British Heart Foundation
  • United Kingdom Department of Health and Social Care
  • Royal Society
  • Cancer Research UK
Topics
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
Keywords
COVID-19 pandemic, disease severity, multi-omics, immune signatures, immune activation, plasma proteome, patient phenotyping, influenza, sepsis, immune repertoire, coagulation, acute phase response, immunometabolism, tensor decomposition, matrix factorization
MeSH terms
Machine Learning, COVID-19, SARS-CoV-2, Adult, Blood Proteins, Female, Humans, Influenza, Human, Lymphocytes, Male, Middle Aged, Monocytes, Severity of Illness Index, Biomarkers, Cell Cycle Proteins, Sepsis, Transcription Factor AP-1, Proteome, Principal Component Analysis, Mitogen-Activated Protein Kinase 14

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