Genome-Wide Gene by Environment Interaction Analysis Identifies Common SNPs at 17q21.2 that Are Associated with Increased Body Mass Index Only among Asthmatics
Bibliographic record
Abstract
Asthmatics have an increased risk of being overweight/obese. Although the underlying mechanisms of this are unclear, genetic factors are believed to play an essential role. To identify common genetic variants that are associated with asthma-related BMI increase, we performed a genome-wide gene by environment (asthma) interaction analysis for the outcome of BMI in the Multi-Ethnic Study of Atherosclerosis (MESA) study (N = 2474 Caucasians, 257 asthmatics), and replicated findings in the Framingham Heart Study (FHS) offspring cohort (N = 1408 Caucasians, 382 asthmatics). The replicable tagging SNP, rs2107212, was further examined in stratified analyses. Seven SNPs clustered in 17q21.2 were identified to be associated with higher BMI among asthmatics (interaction p < 5×10-7 in MESA and p < 0.05 in FHS). In both MESA and FHS asthmatics, subjects carrying the A allele on rs2107212 had significantly higher odds of obesity than non-carriers, which was not the case for non-asthmatics. We further examined BMI change subsequent to asthma diagnosis over a period of 26 years in FHS and demonstrated greater BMI increase among asthmatics compared to non-asthmatics. Asthmatics carrying the A allele at rs2107212 had significantly greater net BMI increase over the 26-year period compared to non-asthmatics. In this study, we found that common genetic variants on 17q21.2 are associated with post-asthma BMI increase among Caucasians. This finding will help elucidate pathways involved in the comorbidity of asthma and obesity.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".