Contribution of the Saguenay–Lac-Saint-Jean asthma familial cohort in the omic landscape of asthma
Bibliographic record
Abstract
Asthma is a chronic respiratory disease afflicting patients of all ages and, despite recent therapeutic advances, still causes important morbidity and mortality. The implication of genetic alterations and the role for environmental factors in its pathogenesis are now accepted. The SLSJ asthma familial cohort from Quebec, Canada is well-recognized and includes data from 1394 individuals distributed in 271 independent families. A phenotypic profile including more than 75 characteristics was defined for each participant (lung function, allergies, etc). This project aims to provide a summary of all contributions of this young founder population to the genetic landscape of asthma and point-out new genes and methylation profiles that could be implicated in the development and progression of this disease. We identified 294 loci significantly associated with asthma and related phenotypes at the genomic, epigenomic or transcriptomic level. Among them, 16 were associated with asthma and related traits using direct integrative approaches (eQTL, mQTL, gene-gene interaction studies). Also, 5 genes were associated with asthma at all three levels: GSDMA (gasdermin A), IL33 (interleukin 33), IL1R2 (interleukin 1 receptor type 2), ORMDL3 (ORMDL sphingolipid biosynthesis regulator 3), ZPBP2 (zona pellucida binding protein 2). Our results contributed to document the omic landscape of asthma. The next step is to use integrative analyses to link genetic and functional data to help decipher and characterize asthma endotypes. We are also performing a 20-year follow-up data in the SLSJ familial cohort, which will allow to shed light on persistence and progression of asthma throughout life.
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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 | 0.000 | 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) | 0.000 | 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".