Evidence for a Gene Influencing High-Density Lipoprotein Cholesterol on Chromosome 4q31.21
Bibliographic record
Abstract
OBJECTIVE: A low level of plasma high-density lipoprotein cholesterol (HDL-C) is a major risk factor for coronary atherosclerosis. To identify novel genes regulating plasma HDL-C levels, we investigated 13 multigenerational French Canadian families with an average of 12 affected individuals per family for genome-wide signals, which we subsequently fine mapped. METHODS AND RESULTS: We genotyped a total of 362 individuals, including 151 affected subjects for 485 autosomal microsatellite markers. In parametric 2-point linkage analyses, the highest 2-point logarithm of odds (lod) score of 4.6 was observed with marker D4S424 on chromosome 4q31.21 (at approximately 142 Mb). The multipoint analysis of this region resulted in a lod score of 3.8 and a lod -1 region of 12.2 cM, containing 40 known genes. The results were obtained by allowing for genetic heterogeneity among these extended pedigrees, and approximately 50% of families were linked to this region with the highest single-pedigree lod score being 3.6. We further restricted the linked region from 12.2 to 2.9 cM (2.37 Mb) by genotyping 15 additional markers in the 3 families with the highest lod scores. We sequenced 4 genes with a likely role in lipid metabolism as well as 2 genes residing directly under the linkage peak but found no evidence for a causative variant. None of the genes residing in the significantly restricted 2.37-Mb region has been associated previously with HDL-C metabolism. CONCLUSIONS: This study provides significant evidence for a gene influencing HDL-C on chromosome 4q31.21.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".