Genetic interaction between ATP2A2 and ORMDL3, a calcium handling origin of asthma
Bibliographic record
Abstract
Background Calcium homeostasis contributes to increased airway smooth muscle contraction, a core feature of asthma. Several candidate genes exist affecting calcium homeostasis. Two of these genes interact functionally, ATP2A2 and ORMDL3 ( Cantero-Recasens G et al Hum Mol Gen 2010;19:111-121). Aim To study interactions between SNPs in ATP2A2 and ORMDL3 in asthma and their association with gene expression in lung tissue. Methods SNPs tagging ATP2A2 (n=3) and ORMDL3 (n=12) were selected in a birth cohort (PIAMA: 111 asthma; 468 controls) and adult asthmatics(775 asthma; 468 controls). Genetic associations of SNPs with asthma and gene expression were tested using univariate and interaction models. Results Seven SNPs in ORMDL3 were significantly associated with asthma. Rs3026445 in ATP2A2 and 6 ORMDL3 SNPs had significant interactions in childhood asthma only. All ORMDL3 SNPs changed ORMDL3 gene-expression. Rs3026445 was not associated with ATP2A2 gene expression. Significant interactions between ATP2A2 and ORMDL3 SNPs were found on gene expression of both ATP2A2 and ORMDL3 (table1). Conclusion We found no association of ATP2A2 SNPs with asthma, but significant genetic interaction between ATP2A2 and ORMDL3 with asthma and gene expression in lung tissue. Thus, SNPs without univariate association with asthma or gene expression, may still be important since their modifying potential in associations of SNPs in another gene with these outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".