Evidence of Major Genes for Plasma HDL, LDL Cholesterol and Triglyceride Levels at Baseline and in Response to 20 Weeks of Endurance Training: The HERITAGE Family Study
Bibliographic record
Abstract
This study assessed major gene effects for baseline HDL-C, LDL-C, TG, and their training responses (post-training minus baseline) in 527 individuals from 99 White families and 326 individuals from 113 Black families in the HERITAGE Family Study. The baseline phenotypes were adjusted for the effects of age and BMI, and the training response phenotypes were adjusted for the effects of age, BMI, and their respective baseline values, within each of the sex-by-generation-by-race groups, prior to genetic analyses. In Whites, we found that LDL-C at baseline and HDL-C training response were under influence of major recessive genes (accounting for 2--30 % of the variance) and multifactorial (polygenic and familial environmental) effects. Interactions of these major genes with sex, age, and BMI were tested, and found to be nonsignificant. In Blacks, we found that baseline HDL-C was influenced by a major dominant gene without a multifactorial component. This major gene effect accounted for 45 % of the variance, and exhibited no significant genotype-specific interactions with age, sex, and BMI. Evidence of major genes for the remaining phenotypes at baseline and in response to endurance training were not found in both races, though some were influenced by major effects that did not follow Mendelian expectations or were with ambiguous transmission from parents to offspring. In summary, major gene effects that influence baseline plasma HDL-C and LDL-C levels as well as changes in HDL-C levels in response to regular exercise were detected in the current study.
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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) | 0.001 | 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 | 0.000 | 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".