Low-Density Lipoprotein Particle Size Loci in Familial Combined Hyperlipidemia
Bibliographic record
Abstract
OBJECTIVE: Low-density lipoprotein (LDL) size is associated with vascular disease and with familial combined hyperlipidemia (FCHL). METHODS AND RESULTS: We used logarithm of odds (lod) score and Bayesian Markov chain Monte Carlo (MCMC) linkage analysis methods to perform a 10-cM genome scan of LDL size, measured as peak particle diameter (PPD) and adjusted for age, sex, body mass index, and triglycerides in 4 large families with FCHL (n=185). We identified significant evidence of linkage to a chromosome 9p locus (multipoint lod(max)=3.70; MCMC intensity ratio [IR]=21) in a single family, and across all 4 families to chromosomes 16q23 (lod(max)=3.00; IR=43) near cholesteryl ester transfer protein (CETP) and to 11q22 (lod(max)=3.71; IR=120). Chromosome 14q24-31, a region with previous suggestive LDL PPD linkage evidence, yielded an IR of 71 but an lod(max)=1.79 in the combined families. CONCLUSIONS: These results of significant evidence of linkage to 3 regions (9p, 16q, and 11q) and confirmatory support of previous reported linkage to 14q in large FCHL pedigrees demonstrate that LDL size is a trait influenced by multiple loci and illustrate the complementary use of lod score and MCMC methods in analysis of a complex trait.
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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 | 0.002 |
| 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) | 0.002 | 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".