Variants in the IL17 pathway genes are associated with atopic asthma and atopy makers in a South American population
Bibliographic record
Abstract
Asthma is a complex disorder with multiple phenotypes which can influence its severity and response to treatment. The T H 17 lymphocytes producing IL-17A and IL17-F cytokines, may have a role on asthma inflammation. The aim of our study was to evaluate the association between genetic variants in IL17 pathway genes with asthma and atopy markers. Genotyping was performed using a commercial panel in 1245 participants of SCAALA cohort. The study included 91 SNVs in IL-17 pathway genes. Logistic regressions for asthma and atopy markers were performed using PLINK 1.9. In silico analyses were performed using rSNPbase, RegulomeDB, and Gtex portal for in silico gene expression. The T allele of rs1974226 in IL17A was positively associated with asthma (OR: 1.37; 95% CI 1.02–1.82). Also, the T allele of rs279548 was positively associated with asthma (OR: 1.30; 95% CI 1.02–1.64), atopy (OR: 1.62; 95% CI 1.05–2.50) and increased expression of the IL17RC in lung and whole blood tissues. The others genetic variants in the IL 17 pathways genes were associated with both protection and risk for asthma development as well as with IgE levels. The genetic variants in IL-17-related genes are associated with the atopic asthma phenotype and IgE production.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".