ArticleScientific reports2022
Small-molecule metabolome identifies potential therapeutic targets against COVID-19.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 15 citations in OpenAlex.
- Lipid metabolism, viral infection, and antiviral immunity: a new host-pathogen interface.Frontiers in cellular and infection microbiology · 2026Review
- A Comprehensive Machine Learning Approach for COVID-19 Target Discovery in the Small-Molecule Metabolome.Metabolites · 2025Article
- Potential role of serological biomarkers in the diagnosis and prediction of community-acquired pneumonia in elderly individuals.Frontiers in medicine · 2025Review
- Enhancing Influenza Detection through Integrative Machine Learning and Nasopharyngeal Metabolomic Profiling: A Comprehensive Study.Diagnostics (Basel, Switzerland) · 2024Article
- Exploratory Untargeted Metabolomics of Dried Blood Spot Samples from Newborns with Maple Syrup Urine Disease.International journal of molecular sciences · 2024Article
- 1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit.International journal of molecular sciences · 2024Article
- Metabolomics-directed nanotechnology in viral diseases management: COVID-19 a case study.Pharmacological reports : PR · 2023Review
- Diagnostic, Prognostic and Mechanistic Biomarkers of COVID-19 Identified by Mass Spectrometric Metabolomics.Metabolites · 2023Review
- Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19.Frontiers in molecular biosciences · 2023Review
- Machine Learning and COVID-19: Lessons from SARS-CoV-2.Advances in experimental medicine and biology · 2023Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Respiratory viruses are transmitted and acquired via the nasal mucosa, and thereby may influence the nasal metabolome composed of biochemical products produced by both host cells and microbes. Studies of the nasal metabolome demonstrate virus-specific changes that sometimes correlate with viral load and disease severity. Here, we evaluate the nasopharyngeal metabolome of COVID-19 infected individuals and report several small molecules that may be used as potential therapeutic targets. Specimens were tested by qRT-PCR with target primers for three viruses: Influenza A (INFA), respiratory syncytial virus (RSV), and SARS-CoV-2, along with unaffected controls. The nasopharyngeal metabolome was characterized using an LC-MS/MS-based screening kit capable of quantifying 141 analytes. A machine learning model identified 28 discriminating analytes and correctly categorized patients with a viral infection with an accuracy of 96% (R
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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.