Heritability and genetic correlations of obesity indices with ambulatory and office beat-to-beat blood pressure in the Oman Family Study
Bibliographic record
Abstract
OBJECTIVE: To more precisely and comprehensively estimate the genetic and environmental correlations between various indices of obesity and BP. METHODS: We estimated heritability and genetic correlations of obesity indices with BP in the Oman family study (n = 1231). Ambulatory and office beat-to-beat BP was measured and mean values for SBP and DBP during daytime, sleep, 24-h and 10 min at rest were calculated. Different indices were used to quantify obesity and fat distribution: BMI, percentage of body fat (%BF), waist circumference and waist-to-height ratio (WHtR). SOLAR software was used to perform univariate and bivariate quantitative genetic analyses adjusting for age, age, sex, age-sex and age--sex interactions. RESULTS: Heritabilities of BP ranged from 30.2 to 38.2% for ambulatory daytime, 16.8--21.4% for sleeping time, 32.1--40.4% for 24-h and 22--24.4% for office beat-to-beat measurements. Heritabilities for obesity indices were 67.8% for BMI, 52.2% for %BF, 37.3% for waist circumference and 37.9% for WHtR. All obesity measures had consistently positive phenotypic correlations with ambulatory and office beat-to-beat SBP and DBP (r-range: 0.14--0.32). Genetic correlations of obesity indices with SBP and DBP were higher than environmental correlations (rG: 0.16--0.50; rE: 0.01--0.31). CONCLUSION: The considerable genetic overlap between a variety of obesity indices and both ambulatory and office beat-to-beat BP highlights the relevance of pleiotropic genes. Future GWAS analyses should discover the specific genes both influencing obesity indices and BP to help unravel their shared genetic background.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".