Heritability of LDL peak particle diameter in the Quebec Family Study
Bibliographic record
Abstract
LDL size has been associated with the risk of coronary heart disease. The objective of the present study was to verify whether familial factors influence LDL peak particle diameter (LDL-PPD), a quantitative trait reflecting the size of the major LDL subclass. LDL-PPD was measured by 2-16% polyacrylamide gradient gel electrophoresis in 681 members of 236 nuclear families participating in the Quebec Family Study. LDL-PPD was adjusted for age (LDL-PPD1), age and body mass index (LDL-PPD2), or age, body mass index, and plasma triglyceride levels (LDL-PPD3) separately in men and women. The residual scores were used to test for familial aggregation, using an ANOVA and to compute maximum likelihood estimates of familial correlations. The ANOVA test revealed that family lines accounted for 47.4%, 46.7%, and 48.9% of the variance in the LDL-PPD1, LDL-PPD2, and LDL-PPD3 phenotypes, respectively. The pattern of familial correlations revealed no significant spouse correlations but significant parent-offspring and sibling correlations for the three LDL-PPD phenotypes, with maximal heritability estimates of 59%, 58%, and 52% for LDL-PPD1, LDL-PPD2, and LDL-PPD3, respectively. These results suggest that LDL-PPD strongly aggregates in families, and that the familial resemblance appears to be primarily attributable to genetic factors. Genes responsible for this genetic contribution remain to be identified.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".