Local genotype influences DNA methylation at two asthma-associated regions, 5q31 and 17q21, in a founder effect population
Bibliographic record
Abstract
BACKGROUND: Two asthma-associated regions 17q12-q21 and 5q31.1 harbour genes that show strong effect of genotype on expression levels. DNA methylation has an important role in gene regulation; therefore, we examined DNA methylation at promoters of 12 genes from 5q31 and 17q12-q21 regions. Our goal was to determine whether DNA methylation was associated with predisposition to asthma and whether such a relationship was independent from genetic association. METHODS: Using sodium bisulfite sequencing and pyrosequencing methylation assays, we examined the effect of genotype on DNA methylation in peripheral blood cells from individuals from the Saguenay-Lac-Saint-Jean asthma familial collection and lymphoblastoid cell lines. RESULTS: The local genotype influenced methylation levels of solute carrier family 22 (organic 3 cation/carnitine transporter) member 5 (SLC22A5), zona pellucida binding protein 2 (ZPBP2) and gasdermin A (GSDMA) promoter regions. The genotype had a dominant effect on ZPBP2 and GSDMA methylation with lower methylation levels in individuals that carry the asthma-predisposing alleles. Males also had lower methylation at the ZPBP2 promoter than females. We did not observe an effect of asthma status that would be independent of the genotype and the sex effects in the GSDMA, ZPBP2 and SLC22A5 regions; however, GSDMA and ZPBP2 data were suggestive of interaction between asthma and methylation levels in females and SLC22A5 in males. CONCLUSIONS: The local genotype influences methylation levels at SLC22A5 and ZPBP2 promoters independently of the asthma status. Further studies are necessary to confirm the relationship between GSDMA-ZPBP2 and SLC22A5 methylation and asthma in females and males separately.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".