Filaggrin gene mutations and new SNPs in asthmatic patients: a cross-sectional study in a Spanish population
Bibliographic record
Abstract
BACKGROUND: Several null-mutations in the FLG gene that produce a decrease or absence of filaggrin in the skin and predispose to atopic dermatitis and ichthyosis vulgaris have been described. The relationship with asthma is less clear and may be due to the influence of atopy in patients with associated asthma. METHODS: Four hundred individuals were included, 300 patients diagnosed with asthma divided into two groups according to their phenotype (allergic and non-allergic asthma) and 100 strictly characterized controls. The coding region and flanking regions of the FLG gene were amplified by PCR. We proceeded to the characterization of potential gene variants in that region by RFLP and sequencing and analysed their association with lung function parameters, asthma control and severity, and quality of life. RESULTS: We identified two null-mutations (R501X and 2282del4), seven SNPs previously described in databases and three SNPs that had not been previously described. One of the SNP identified in this study (1741A > T) was more frequently detected in patients with non-allergic asthma, worse FVC, FEV1 and PEF values and a higher treatment step. In addition, lowered spirometric values were observed in the non-allergic group carrying any of the nonsynonymous SNPs. CONCLUSIONS: In the association study of genetic variants of the FLG gene in our population the 1741A > T polymorphism seems to be associated with non-allergic asthma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".