Heritability and genetic and environmental correlations of heart rate variability and baroreceptor reflex sensitivity with ambulatory and beat-to-beat blood pressure
Bibliographic record
Abstract
Abstract This family study from Oman (n = 1231) explored the heritability and genetic and environmental correlations of heart rate variability (HRV) and baroreceptor reflex sensitivity (BRS) with ambulatory and beat-to-beat blood pressure (BP). Ambulatory BP was measured for 24 hours to calculate mean values for daytime and sleep separately. Time and frequency domain HRV indices, BRS, office beat-to-beat BP, and heart rate (HR) were measured for 10 minutes at rest. SOLAR software was used to perform univariate and bivariate quantitative genetic analyses adjusting for age, age2, sex, their interactions and BMI. Heritability of SBP and DBP ranged from 16.8% to 40.4% for daytime, sleeping, 24-hour and office beat-to-beat measurements. HR and BRS showed a heritability of 31.9% and 20.6%, respectively, and for HRV indices heritability ranged from 11.1% to 20.5%. All HRV measurements and BRS were found to be negatively correlated with BP, but phenotypic correlation coefficients were relatively weak; HR was positively correlated with BP. None of the genetic correlations were statistically significant while environmental factors explained most of the correlations for all HRV indices with BP. Our study found consistent but weak correlations among HRV, HR, BRS and ambulatory/office beat-to-beat BP. However, environmental rather than genetic factors contributed most to those correlations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".