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Updated: Dec 3, 2025
Author Spotlight: Advancing the Analysis of Plasma Extracellular Vesicle Proteome for Cardiovascular Biomarker Studies
Published on: January 31, 2025
Plasma Proteomics Identify Biomarkers and Pathogenesis of COVID-19
Ting Shu1, Wanshan Ning2, Di Wu3
1Joint Laboratory of Infectious Diseases and Health, Wuhan Institute of Virology & Wuhan Jinyintan Hospital, Wuhan Jinyintan Hospital, Wuhan, Hubei 430023, China; State Key Laboratory of Virology, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences (CAS), Wuhan, Hubei 430071, China; Center for Translational Medicine, Wuhan Jinyintan Hospital, Wuhan, Hubei 430023, China.
Insights
Researchers identified 11 key plasma protein biomarkers for coronavirus disease 2019 (COVID-19) using machine learning. These biomarkers accurately predict patient outcomes and reveal insights into COVID-19 pathogenesis and potential therapeutic targets.
Area of Science:
- Proteomics
- Immunology
- Machine Learning
Background:
- The COVID-19 pandemic presents a significant global health challenge.
- Understanding the pathogenesis and identifying reliable biomarkers for COVID-19 are crucial but remain limited.
Purpose of the Study:
- To profile host responses in COVID-19 patients through plasma proteomics.
- To identify and validate protein biomarkers for predicting COVID-19 outcomes and understanding disease mechanisms.
Main Methods:
- Plasma proteomics analysis of COVID-19 patients (non-survivors, mild, and severe survivors).
- Development of a machine-learning pipeline to identify protein biomarkers.
- Validation of identified biomarkers using an independent cohort and ELISA.
Main Results:
- Numerous COVID-19-associated plasma protein alterations were discovered.
- A set of 11 protein biomarkers and combinations were identified and validated, accurately distinguishing and predicting COVID-19 outcomes.
- Altered proteins are involved in immune responses, coagulation, and metabolism, contributing to COVID-19 pathogenesis.
Conclusions:
- The study provides valuable insights into COVID-19 biomarkers.
- Findings shed light on the pathogenesis of COVID-19 and identify potential therapeutic targets.
- Validated protein biomarkers can aid in predicting disease progression and outcomes.
Abstract:
The coronavirus disease 2019 (COVID-19) pandemic is a global public health crisis. However, little is known about the pathogenesis and biomarkers of COVID-19. Here, we profiled host responses to COVID-19 by performing plasma proteomics of a cohort of COVID-19 patients, including non-survivors and survivors recovered from mild or severe symptoms, and uncovered numerous COVID-19-associated alterations of plasma proteins. We developed a machine-learning-based pipeline to identify 11 proteins as biomarkers and a set of biomarker combinations, which were validated by an independent cohort and accurately distinguished and predicted COVID-19 outcomes. Some of the biomarkers were further validated by enzyme-linked immunosorbent assay (ELISA) using a larger cohort. These markedly altered proteins, including the biomarkers, mediate pathophysiological pathways, such as immune or inflammatory responses, platelet degranulation and coagulation, and metabolism, that likely contribute to the pathogenesis. Our findings provide valuable knowledge about COVID-19 biomarkers and shed light on the pathogenesis and potential therapeutic targets of COVID-19.
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