Loss-of-function variants in the filaggrin gene are a significant risk factor for peanut allergy
Bibliographic record
Abstract
BACKGROUND: IgE-mediated peanut allergy is a complex trait with strong heritability, but its genetic basis is currently unknown. Loss-of-function mutations within the filaggrin gene are associated with atopic dermatitis and other atopic diseases; therefore, filaggrin is a candidate gene in the etiology of peanut allergy. OBJECTIVE: To investigate the association between filaggrin loss-of-function mutations and peanut allergy. METHODS: Case-control study of 71 English, Dutch, and Irish oral food challenge-positive patients with peanut allergy and 1000 non peanut-sensitized English population controls. Replication was tested in 390 white Canadian patients with peanut allergy (defined by food challenge, or clinical history and skin prick test wheal to peanut ≥ 8 mm and/or peanut-specific IgE ≥ 15 kUL(-1)) and 891 white Canadian population controls. The most prevalent filaggrin loss-of-function mutations were assayed in each population: R501X and 2282del4 in the Europeans, and R501X, 2282del4, R2447X, and S3247X in the Canadians. The Fisher exact test and logistic regression were used to test for association; covariate analysis controlled for coexistent atopic dermatitis. RESULTS: Filaggrin loss-of-function mutations showed a strong and significant association with peanut allergy in the food challenge-positive patients (P = 3.0 × 10(-6); odds ratio, 5.3; 95% CI, 2.8-10.2), and this association was replicated in the Canadian study (P = 5.4 × 10(-5); odds ratio, 1.9; 95% CI, 1.4-2.6). The association of filaggrin mutations with peanut allergy remains significant (P = .0008) after controlling for coexistent atopic dermatitis. CONCLUSION: Filaggrin mutations represent a significant risk factor for IgE-mediated peanut allergy, indicating a role for epithelial barrier dysfunction in the pathogenesis of this disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".