Low density lipoprotein receptor (LDLR) gene mutations in Canadian subjects with familial hypercholesterolemia, but not of French descent
Bibliographic record
Abstract
Heterozygous familial hypercholesterolemia (FH) is a relatively common autosomal dominant disorder, which is characterized by elevated plasma concentrations of low density lipoprotein (LDL) cholesterol and early coronary heart disease. FH results from mutations in the gene encoding the LDL receptor (LDLR). In Canada, there is a founder effect for LDLR mutations in FH among individuals of French descent, most of whom reside in the province of Quebec. However, the spectrum of mutations in other regions, specifically in the populous and predominantly English-speaking province of Ontario, has not been studied. We sequenced the coding regions, promoter and intron-exon boundaries of the LDLR gene in 60 Ontario FH subjects from a variety of ethnic backgrounds other than French Canadian. We found 25 LDLR mutations in 34 subjects. Eleven LDLR mutations were novel, including two in-frame deletions of a single amino acid (one each in exons 2 and 4), two larger deletions that shifted the reading frame (one each in exons 4 and 10), five missense mutations (C42R, A370T, T413M, L561P and E760D) and two splice acceptor mutations (one each in introns 3 and 8). The results indicate that FH is more genetically diverse in Ontario than in Quebec. The results are also consistent with findings from investigations of the LDLR in FH conducted in other countries, in which PCR-based, exon-by-exon sequencing uncovers small mutations in about half of the subjects screened. The gap in molecular diagnosis suggests that lesions not found by this sequencing strategy, such as larger scale LDLR mutations that cannot be amplified, may underlie a substantial number of cases of FH. Alternatively, there might be genetic heterogeneity underlying the FH phenotype, with contributions from other single or multiple genes. Hum Mutat 18:359, 2001.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".