ArticleCell2020
Proteomic and Metabolomic Characterization of COVID-19 Patient Sera.
Article in Cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 973 papers, 5 of them syntheses that pooled it.
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
973 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Pooled it
- A bibliometric and text-mining analysis of lipidomics and metabolomics in human disease.Frontiers in physiology · 2026Pooled it
- Neurological Manifestations of SARS-CoV-2.Viruses · 2025Pooled it
- Metabolomic characteristics and related pathways in patients with different severity of COVID-19: a systematic review and meta-analysis.Journal of global health · 2025Pooled it
- Mucosal immune response in biology, disease prevention and treatment.Signal transduction and targeted therapy · 2025Pooled it
- Metabolic response to extended continuous positive airway pressure in premature infants.Pediatric research · 2026Trial
- Metabolomic signatures of hepatic steatosis reveal heterogeneity in cardiometabolic risk and responses to lifestyle interventions in type 2 diabetes: a post hoc analysis.Cardiovascular diabetology · 2026Trial
- Metabolic reprogramming of endothelial-related pathways in COVID-19 patients treated with hyperbaric oxygen therapy: a randomized clinical trial.Scientific reports · 2026Trial
- Levels of circulating kidney injury markers and IL-10 identify non-critically ill patients with COVID-19 at risk of death.JCI insight · 2026Trial
- Severity-dependent and sex-biased dysregulation of A-to-I RNA editing in COVID-19 reveals CTSS as a key regulatory target.RNA biology · 2026Article
- Plasma Metabolomic Alterations Are Associated with T-Cell Senescence, Cytokine Dysregulation, and Prognosis in Elderly COVID-19 Patients.Biomedicines · 2026Article
- Knowledge-driven interpretable neural networks provide mechanistic insight.Genome research · 2026Article
- Plasma Proteomic Signatures of Coagulopathy Following Traumatic Injury: Links to Biomechanics and Patient Outcomes.Shock (Augusta, Ga.) · 2026Article
- Integration of the circulating miRNome and clinical information to predict 90-day mortality in elderly COVID-19 subphenotypes.iScience · 2026Article
- β-Cell Dysfunction in COVID-19 and Post-COVID Syndrome: Molecular Mechanisms Linking Inflammation, Oxidative Stress, and Insulin Secretion.International journal of molecular sciences · 2026Review
- SPINK1-driven cellular heterogeneity and interaction networks in intrahepatic cholangiocarcinoma revealed by integrated multi-omics analysis.Journal of advanced research · 2026Article
- High-Resolution Mass Spectrometry Reveals Distinct Temporal Accumulation Patterns of Metabolites in Reproductive Organs of Purple- and White-FloweredLife (Basel, Switzerland) · 2026Article
- Proteomics and human microchips identify Thrombospondin-1 as a potential biomarker for calciphylaxis stem cell therapy.iScience · 2026Article
- KRT6A Is a Biomarker of PAS Progression and Enhances the Invasive Ability of Trophoblast Cells.Cells · 2026Article
- Will predictive AI make discovery research in metabolism obsolete.npj metabolic health and disease · 2026Article
913 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
40 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early detection and effective treatment of severe COVID-19 patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model was validated using 10 independent patients, 7 of which were correctly classified. Targeted proteomics and metabolomics assays were employed to further validate this molecular classifier in a second test cohort of 19 COVID-19 patients, leading to 16 correct assignments. We identified molecular changes in the sera of COVID-19 patients compared to other groups implicating dysregulation of macrophage, platelet degranulation, complement system pathways, and massive metabolic suppression. This study revealed characteristic protein and metabolite changes in the sera of severe COVID-19 patients, which might be used in selection of potential blood biomarkers for severity evaluation.
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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.