ArticleFrontiers in physiology2021
Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.
Article in Frontiers in physiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.
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Who cites it
42 citing papers in PubMed, 1 synthesis or guideline pooled it, 79 citations in OpenAlex.
- Comprehensive proteomics and meta-analysis of COVID-19 host response.Nature communications · 2023Pooled it
- Pro-regenerative fingerprints identified in a sub-population of adult mouse cardiomyocytes by integrative single-cell proteomics.Genome biology · 2026Article
- Computational proteomics to enhance personalized treatment of COVID-19 and Long COVID.Clinical proteomics · 2026Review
- Mass spectrometry combined with machine learning identifies novel protein signatures as demonstrated with multisystem inflammatory syndrome in children.Scientific reports · 2025Article
- Can Biomarkers Predict Kidney Function Recovery and Mortality in Patients with Critical COVID-19 and Acute Kidney Injury?Diagnostics (Basel, Switzerland) · 2025Article
- Article
- ProPickML: Advancing Clinical Diagnostics with Automated Peak Picking in Label-Free Targeted Proteomics.Journal of proteome research · 2025Article
- Functional mass spectrometry indicates anti-protease and complement activity increase with COVID-19 severity.Experimental biology and medicine (Maywood, N.J.) · 2025Article
- What Can Proteomics Tell us About COVID-19 Infections? Mass Spectrometry as a Tool to Find New Proteins as Biomarkers.Current protein & peptide science · 2025Review
- Proteomic Profiling of COVID-19 Patients Sera: Differential Expression with Varying Disease Stage and Potential Biomarkers.Diagnostics (Basel, Switzerland) · 2024Article
- Cytosolic serpins act in a cytoprotective feedback loop that limits ESX-1-dependent death ofmBio · 2024Article
- Plasma Proteins Associated with COVID-19 Severity in Puerto Rico.International journal of molecular sciences · 2024Article
- COVID-19 and Comorbidities: What Has Been Unveiled by Metabolomics?Metabolites · 2024Review
- Immunohistochemical Expression of the SERPINA3 Protein in Uterine Fibroids.Current pharmaceutical biotechnology · 2024Article
- Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches.Scientific reports · 2023Article
- Plasma proteomics show altered inflammatory and mitochondrial proteins in patients with neurologic symptoms of post-acute sequelae of SARS-CoV-2 infection.Brain, behavior, and immunity · 2023Article
- Article
- Exploration of the common pathogenic link between COVID-19 and diabetic foot ulcers: An in silico approach.Health science reports · 2023Article
- A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.Clinical proteomics · 2023Article
- Changes in the Proteome of Platelets from Patients with Critical Progression of COVID-19.Cells · 2023Article
Corrections and comments
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Authors and funding
25 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an
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