A time-resolved proteomic and prognostic map of COVID-19
Artikel i vetenskaplig tidskrift, 2021

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

patient trajectories

disease prognosis

physiological parameters

clinical disease progression

machine learning

longitudinal profiling

COVID-19

proteomics

biomarkers

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Publicerad i

Cell Systems

24054712 (ISSN) 24054720 (eISSN)

Vol. 12 Nummer/häfte 8 s. 780-794.e7

Kategorisering

Ämneskategorier (SSIF 2011)

Klinisk laboratoriemedicin

Biomedicinsk laboratorievetenskap/teknologi

Farmakologi och toxikologi

Identifikatorer

DOI

10.1016/j.cels.2021.05.005

PubMed

34139154

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Senast uppdaterat

2022-04-05