ArticleCell reports. Medicine2021
Longitudinal metabolomics of human plasma reveals prognostic markers of COVID-19 disease severity.
Article in Cell reports. Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 96 papers, 1 of them a synthesis that pooled it.
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Who cites it
96 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers.International journal of molecular sciences · 2023Pooled it
- Metabolic response to extended continuous positive airway pressure in premature infants.Pediatric research · 2026Trial
- Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.NPJ systems biology and applications · 2025Trial
- Worksite-based intensive lifestyle therapy has profound cardiometabolic benefits in people with obesity and type 2 diabetes.Cell metabolism · 2022Trial
- Metabolic Signatures Associated with COVID-19 Vaccination in Serum from Healthy Individuals.Vaccines · 2026Article
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- Knowledge-driven interpretable neural networks provide mechanistic insight.Genome research · 2026Article
- Gut mycobiota alteration contributes to the pathogenesis of Pneumocystis pneumonia.Journal of translational medicine · 2026Article
- Severe Hospitalization-Requiring Viral Infection With Influenza or COVID-19: Metabolic Pathway Analysis.Open forum infectious diseases · 2026Article
- A quantitative metabolic signature of host response during SARS-CoV-2 infection and recovery.iScience · 2026Article
- A longitudinal comparative analysis of serum metabolomic signatures in children with SARS-CoV-2 infection and MIS-C.Communications medicine · 2026Article
- Transient exposure to bisphenol F in early life affects the metabolic health of adults.Exposome · 2026Article
- COVID-19 in hemodialysis patients: New insights into metabolomic profile dynamics from 60 days pre- to 60 days post-diagnosis.PloS one · 2026Observational
- mzLearn as a data-driven LC/MS signal detection algorithm that enables pre-trained generative models for untargeted metabolomics.Communications chemistry · 2025Article
- Article
- Metabolomic and clinical feature analyses of plasma from influenza A patients.Scientific reports · 2025Article
- Preoptic activation induces a torpor-like hypothermic and hypometabolic state that is cerebroprotective.bioRxiv : the preprint server for biology · 2025Article
- Dynamic sensor selection for biomarker discovery.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Metabolomics and Cytokine Signatures in COVID-19: Uncovering Immunometabolism in Pathogenesis.Metabolites · 2025Article
- Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets.Metabolomics : Official journal of the Metabolomic Society · 2025Article
36 more citing papers are in PubMed but not listed here.
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13 authors.
Funding
Abstract
There is an urgent need to identify which COVID-19 patients will develop life-threatening illness so that medical resources can be optimally allocated and rapid treatment can be administered early in the disease course, when clinical management is most effective. To aid in the prognostic classification of disease severity, we perform untargeted metabolomics on plasma from 339 patients, with samples collected at six longitudinal time points. Using the temporal metabolic profiles and machine learning, we build a predictive model of disease severity. We discover that a panel of metabolites measured at the time of study entry successfully determines disease severity. Through analysis of longitudinal samples, we confirm that most of these markers are directly related to disease progression and that their levels return to baseline upon disease recovery. Finally, we validate that these metabolites are also altered in a hamster model of COVID-19.
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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.