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Data · dataset · 2022

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

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The biological determinants underlying the range of COVID-19 clinical manifestations are not fully understood.

Description

Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients.

Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Examination of informative model features reveals novel biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks in addition to recapitulating known hallmarks of COVID-19.

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These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

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Stated by source
Basic medicine
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Mass spectrometry
Inferred from text
Oncology and carcinogenesis 70%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
DataCite10.5061/dryad.9cnp5hqmn14 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].anzsrc:group:3211enrichment · DataCitetaxonomy-embedding@1.1.0title+keywords+description (70%)
concepts[field].fos:basic-medicinesource · DataCiteconnector:datacite@1.0.0
concepts[modality].local:modality:mass-spectrometrymapping · DataCitevocabulary-mapper@1.0.0keywords['Proteomics']
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