Genome-wide linkage scan reveals multiple susceptibility loci influencing lipid and lipoprotein levels in the Québec Family Study
Bibliographic record
Abstract
A genome-wide linkage study was performed to identify chromosomal regions harboring genes influencing lipid and lipoprotein levels. Linkage analyses were conducted for four quantitative lipoprotein/lipid traits, i.e., total cholesterol, triglyceride, HDL-cholesterol (HDL-C), and LDL-C concentrations, in 930 subjects enrolled in the Québec Family Study. A maximum of 534 pairs of siblings from 292 nuclear families were available. Linkage was tested using both allele-sharing and variance-component linkage methods. The strongest evidence of linkage was found on chromosome 12q14.1 at marker D12S334 for HDL-C, with a logarithm of the odds (LOD) score of 4.06. Chromosomal regions harboring quantitative trait loci (QTLs) for LDL-C included 1q43 (LOD = 2.50), 11q23.2 (LOD = 3.22), 15q26.1 (LOD = 3.11), and 19q13.32 (LOD = 3.59). In the case of triglycerides, three markers located on 2p14, 11p13, and 11q24.1 provided suggestive evidence of linkage (LOD > 1.75). Tests for total cholesterol levels yielded significant evidence of linkage at 15q26.1 and 18q22.3 with the allele-sharing linkage method, but the results were nonsignificant with the variance-component method. In conclusion, this genome scan provides evidence for several QTLs influencing lipid and lipoprotein levels. Promising candidate genes were located in the vicinity of the genomic regions showing evidence of linkage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".