Evidence map›Paper›PMID 35216673›Full record

ArticleCell2022

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

COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. Electronic address: julian.knight@well.ox.ac.uk, COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium

Abstract read
In one paragraph

Article in Cell, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 213 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
213citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

213 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  13. VDJ-REMIX: REpertoire Module Identification and eXploration.Bioinformatics (Oxford, England) · 2026
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153 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium. Electronic address: julian.knight@well.ox.ac.uk
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium

Funding

VISION: ValIdated Systematic IntegratiON of epigenomic dataR24DK106766 · NIDDK · PENNSYLVANIA STATE UNIVERSITY, THE · PI BLOBEL, GERD A, BODINE, DAVID M. · 2016 to 2020
$6.2M
Cancer Research UK 26988Cancer Research UK 27125Cancer Research UK 27723Cancer Research UK 28051Cancer Research UK 29034Medical Research Council G84/6443Medical Research Council MC_PC_19025Medical Research Council MC_PC_19059Medical Research Council MC_PC_20002Medical Research Council MC_UU_00008/10Medical Research Council MC_UU_00008/5Medical Research Council MC_UU_00008/6Medical Research Council MC_UU_00016/14Medical Research Council MR/L006340/1Medical Research Council MR/S005471/1Medical Research Council MR/S020918/1Medical Research Council MR/S025308/1Medical Research Council MR/T014067/1Medical Research Council MR/V010182/1Medical Research Council MR/X001210/1NIDDK NIH HHS R24 DK106766Versus Arthritis 22252Wellcome Trust 201488/Z/16/ZWellcome Trust 204290/Z/16/ZWellcome Trust 204969/Z/16/ZWellcome Trust 208750/Z/17/Z
6 · The paper itself

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.

Indexed as

AdultBiomarkersBlood ProteinsCell Cycle ProteinsCOVID-19FemaleHumansInfluenza, HumanLymphocytesMachine LearningMaleMiddle AgedMitogen-Activated Protein Kinase 14MonocytesPrincipal Component AnalysisProteomeBiomarkersBlood ProteinsCell Cycle ProteinsMitogen-Activated Protein Kinase 14ProteomeTranscription Factor AP-1bloodcoronavirusCOVID-19epigeneticsimmunemulti-omicspersonalized medicineproteomicsSARS-CoV-2transcriptomics

Identifiers

PMID35216673
PMCPMC8776501

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.