Small-molecule metabolome identifies potential therapeutic targets against COVID-19
Bibliographic record
Abstract
Abstract Background 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 asymptomatic controls. The nasopharyngeal metabolome was characterized using an LC-MS/MS-based small-molecule 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 2 =0.771, Q 2 =0.72). A second model identified 5 analytes to differentiate COVID19-infected patients from those with INFA or RSV with an accuracy of 85% (R 2 =0.442, Q 2 =0.301). Specifically, LysoPCaC18:2 concentration was significantly increased in COVID19 patients (P< 0.0001), whereas beta-hydroxybutyric acid, Met SO, succinic acid, and carnosine concentrations were significantly decreased (P< 0.0001). This study demonstrates that COVID19 infection results in a unique NP metabolomic signature with carnosine and LysoPCaC18:2 as potential therapeutic targets. Significance Statement Efforts to elucidate how SARS-CoV-2 interacts with the host has become a global priority. To identify biomarkers for potential therapeutic interventions, we used a targeted metabolomics approach evaluating metabolite profiles in the nasal mucosa of COVID-19 patients and compared metabolite profiles to those of other respiratory viruses (influenza A, RSV). We identified a COVID-19-specific signature characterized by changes to LysoPCaC18:2, beta-hydroxybutyric acid, Met SO, succinic acid, and carnosine. Carnosine is a promising potential target against SARS-CoV-2 as it has been shown to interfere with binding of SARS-CoV-2 to the ACE2 receptor. This study provides compelling evidence for the use of metabolomics as an avenue for the identification of novel drug targets for viral respiratory infections in the nasopharynx.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".