ArticleiScience2022
Integrative metabolomic and proteomic signatures define clinical outcomes in severe COVID-19.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 20 citations in OpenAlex.
- Cholesterol metabolism dysregulated by key HBV mutations revealed through multi-omics profiling.iScience · 2026Article
- Characterisation of a cohort of opportunistically recruited patients with COVID-19 and approaches to patient stratification.BMC infectious diseases · 2026Article
- mzLearn as a data-driven LC/MS signal detection algorithm that enables pre-trained generative models for untargeted metabolomics.Communications chemistry · 2025Article
- Critical risks of haemoadsorption for COVID-19 patients and directions for future evaluations: a nationwide propensity score matched cohort study.Scientific reports · 2025Observational
- Machine Learning based Model Reveals the Metabolites Involved in Coronary Artery Disease.Biomedical engineering and computational biology · 2025Article
- Research Trends in Proteomic Studies Using Serum from COVID-19 Patients: A Bibliometric Analysis.Current medicinal chemistry · 2025Article
- Comprehensive clinical and metabolomics profiling of COVID-19 Mexican patients across three epidemiological waves.Frontiers in molecular biosciences · 2025Article
- Longitudinal Metabolomics Reveals Metabolic Dysregulation Dynamics in Patients with Severe COVID-19.Metabolites · 2024Article
- Metabolomic Insights into COVID-19 Severity: A Scoping Review.Metabolites · 2024Article
- The Impact of Serum/Plasma Proteomics on SARS-CoV-2 Diagnosis and Prognosis.International journal of molecular sciences · 2024Review
- Using the power of innate immunoprofiling to understand vaccine design, infection, and immunity.Human vaccines & immunotherapeutics · 2023Review
- Serum butyrylcholinesterase as a marker of COVID-19 mortality: Results of the monocentric prospective observational study.Chemico-biological interactions · 2023Observational
- The 2022 Report on the Human Proteome from the HUPO Human Proteome Project.Journal of proteome research · 2023Review
- Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome patients.Frontiers in immunology · 2023Article
- Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19.Frontiers in molecular biosciences · 2023Review
- Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.PLoS pathogens · 2022Article
- Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.medRxiv : the preprint server for health sciences · 2022Article
- A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research.Metabolites · 2022Review
Corrections and comments
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Authors and funding
23 authors at 4 institutions in 3 countries.
Funding
Abstract
The coronavirus disease-19 (COVID-19) pandemic has ravaged global healthcare with previously unseen levels of morbidity and mortality. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a network of protein-metabolite interactions through targeted metabolomic and proteomic profiling in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity. Finally, we developed a novel composite outcome measure for COVID-19 disease severity based on metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and shows high predictive power of 0.83-0.93 in two independent datasets.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.