Comprehensive metabolomics identifies the alarmin uric acid as a critical signal for the induction of peanut allergy
Bibliographic record
Abstract
BACKGROUND: Food allergy, in particular peanut allergy, is a growing concern in Western countries. The prevalence of allergy to peanut, which currently stands at 1.4%, nearly tripled between 1997 and 2008. Allergic sensitization is a particularly difficult process to study as it is clinically silent. We sought to identify key pathways and mediators critically involved in the induction of allergic sensitization to peanut. METHODS: Comprehensive metabolomics analysis with liquid chromatography-mass spectrometry was used to detect metabolite changes in mice (C57BL/6) undergoing sensitization. Loss-of-function and gain-of-function studies were performed in mice subjected to two models of peanut sensitization and anaphylaxis that involved either oral or epicutaneous sensitization. Flow cytometric analyses on dendritic cells (DCs) in vitro and in vivo were used to investigate the mechanisms of immune activation. RESULTS: Elevated levels of uric acid (UA) were detected in mice undergoing sensitization as well as in peanut-allergic children who were not challenged with peanut. In mice, the depletion of UA during sensitization prevented the development of peanut-specific immunoglobulins IgE and IgG1 as well as anaphylaxis while exogenous delivery of UA crystals (monosodium urate, MSU) restored the allergic phenotype. Monosodium urate enhanced CD86 and OX40L expression on DCs, independent of Toll-like receptors 2 and 4, the NLRP3 inflammasome, and IL-1β, via a PI3K signaling pathway. CONCLUSION: Overproduction of the UA alarmin in the local microenvironment plays a critical role in the induction of peanut-allergic sensitization, likely due to its ability to activate DCs. These finding suggest that cellular damage or tissue injury may be an essential requisite for the development of allergic sensitization to foods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".