Gene–gene and gene-environment interactions on cord blood total IgE in Chinese Han children
Bibliographic record
Abstract
Abstract Background IL13, IL4, IL4RA, FCER1BandADRB2are susceptible genes of asthma and atopy. Our previous study has found gene–gene interactions on asthma between these genes in Chinese Han children. Whether the interactions begin in fetal stage, and whether these genes interact with prenatal environment to enhance cord blood IgE (CBIgE) levels and then cause subsequent allergic diseases have yet to be determined. This study aimed to determine whether there are gene–gene and gene-environment interactions on CBIgE elevation among the aforementioned five genes and prenatal environmental factors in Chinese Han population. Methods 989 cord blood samples from a Chinese birth cohort were genotyped for nine single-nucleotide polymorphisms (SNPs) in the five genes, and measured for CBIgE levels. Prenatal environmental factors were collected using a questionnaire. Gene–gene and gene-environment interactions were analyzed with generalized multifactor dimensionality methods. Results A four-way gene–gene interaction model (IL13rs20541,IL13rs1800925,IL4rs2243250 andADRB2rs1042713) was regarded as the optimal one for CBIgE elevation (testing balanced accuracy = 0.5805,P = 9.03 × 10–4). Among the four SNPs, onlyIL13rs20541 was identified to have an independent effect on elevated CBIgE (odds ratio (OR) = 1.36,P = 3.57 × 10–3), while the other three had small but synergistic effects. Carriers ofIL13rs20541 TT,IL13rs1800925 CT/TT,IL4rs2243250 TT andADRB2rs1042713 AA were estimated to be at more than fourfold higher risk for CBIgE elevation (OR = 4.14,P = 2.69 × 10–2). Gene-environment interaction on elevated CBIgE was found betweenIL4rs2243250 and maternal atopy (OR = 1.41,P = 2.65 × 10–2). Conclusions Gene–gene interaction betweenIL13rs20541,IL13rs1800925,IL4rs2243250 andADRB2rs1042713, and gene-environment interaction betweenIL4rs2243250 and maternal atopy begin in prenatal stage to augment IgE production in Chinese Han children.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".