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Updated: Nov 6, 2025
TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
Published on: June 8, 2020
Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell
Michael R Filbin1,2,3, Arnav Mehta3,4,5,6, Alexis M Schneider3,7
1Department of Emergency Medicine, Massachusetts General Hospital, Boston, MA, USA.
Insights
Severe COVID-19 involves complex immune and non-immune protein changes. Understanding these plasma protein dynamics offers insights into disease mechanisms and survival, aiding future research.
Area of Science:
- Immunology
- Proteomics
- Virology
Background:
- Mechanisms of severe COVID-19 remain unclear.
- Understanding the role of plasma proteins in disease progression is crucial.
Purpose of the Study:
- To analyze plasma proteome changes in COVID-19 patients.
- To identify proteins associated with severe disease and survival.
- To elucidate cellular contributions to COVID-19 pathogenesis.
Main Methods:
- Longitudinal proteomic analysis of plasma from COVID-19 patients and controls.
- Integration with single-cell RNA sequencing data for cell deconvolution.
- Analysis of tissue-specific and cell-type-specific death signatures.
Main Results:
- Identified numerous immune and non-immune proteins linked to COVID-19.
- Revealed contributions of circulating immune and tissue cells to the plasma proteome.
- Discovered proteins, including exocrine pancreatic proteases, associated with survival.
- Proposed a model of myeloid, epithelial, and T-cell interactions driving tissue damage.
Conclusions:
- Plasma proteomic profiling provides critical insights into severe COVID-19.
- Cellular interactions and specific protein signatures are key to understanding disease severity and outcomes.
- This study offers a valuable resource for COVID-19 research.
Abstract:
Mechanisms underlying severe coronavirus disease 2019 (COVID-19) disease remain poorly understood. We analyze several thousand plasma proteins longitudinally in 306 COVID-19 patients and 78 symptomatic controls, uncovering immune and non-immune proteins linked to COVID-19. Deconvolution of our plasma proteome data using published scRNA-seq datasets reveals contributions from circulating immune and tissue cells. Sixteen percent of patients display reduced inflammation yet comparably poor outcomes. Comparison of patients who died to severely ill survivors identifies dynamic immune-cell-derived and tissue-associated proteins associated with survival, including exocrine pancreatic proteases. Using derived tissue-specific and cell-type-specific intracellular death signatures, cellular angiotensin-converting enzyme 2 (ACE2) expression, and our data, we infer whether organ damage resulted from direct or indirect effects of infection. We propose a model in which interactions among myeloid, epithelial, and T cells drive tissue damage. These datasets provide important insights and a rich resource for analysis of mechanisms of severe COVID-19 disease.
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