Proteomic blood profiling in mild, severe and critical COVID-19 patients

Patel H, Ashton NJ, Dobson RJ, Anderson LM, Yilmaz A, Blennow K, Gisslen M, Zetterberg H

Sci Rep 11 (1) - [2021-04-23; online 2021-03-18]

The recent SARS-CoV-2 pandemic manifests itself as a mild respiratory tract infection in the majority of individuals leading to COVID-19 disease. However, in some infected individuals, this can progress to severe pneumonia and acute respiratory distress syndrome (ARDS), leading to multi-organ failure and death. The purpose of this study is to explore the proteomic differences between mild, severe and critical COVID-19 positive patients. Blood protein profiling was performed on 59 COVID-19 mild (n=26), severe (n=9) or critical (n=24) cases and 28 controls using the OLINK inflammation, autoimmune, cardiovascular and neurology panels. Differential expression analysis was performed within and between disease groups to generate nine different analyses. From the 368 proteins measured per individual, more than 75% were observed to be significantly perturbed in COVID-19 cases. Six proteins (IL6, CKAP4, Gal-9, IL-1ra, LILRB4 and PD-L1) were identified to be associated with disease severity. The results have been made readily available through an interactive web-based application for instant data exploration and visualization, and can be accessed at https://phidatalab-shiny.rosalind.kcl.ac.uk/COVID19/. Our results demonstrate that dynamic changes in blood proteins that associate with disease severity can potentially be used as early biomarkers to monitor disease severity in COVID-19 and serve as potential therapeutic target.

Category: Health

Funder: KAW/SciLifeLab

Funder: VR

Research Area: Biobanks for COVID-19 research

Research Area: Biomarkers and systems immunology

Type: Journal article

DOI https://doi.org/10.1038/s41598-021-85877-0

Crossref https://doi.org/10.1038/s41598-021-85877-0

Data analysis script
BioStudies S-BSST416: Proteomic data
Interactive web-based application for data exploration and visualization


Publications 7.1.2