Common Low-Density Lipoprotein Receptor p.G116S Variant Has a Large Effect on Plasma Low-Density Lipoprotein Cholesterol in Circumpolar Inuit Populations
Bibliographic record
Abstract
BACKGROUND: Inuit are considered to be vulnerable to cardiovascular disease because their lifestyles are becoming more Westernized. During sequence analysis of Inuit individuals at extremes of lipid traits, we identified 2 nonsynonymous variants in low-density lipoprotein receptor (LDLR), namely p.G116S and p.R730W. METHODS AND RESULTS: Genotyping these variants in 3324 Inuit from Alaska, Canada, and Greenland showed they were common, with allele frequencies 10% to 15%. Only p.G116S was associated with dyslipidemia: the increase in LDL cholesterol was 0.54 mmol/L (20.9 mg/dL) per allele (P=5.6×10(-49)), which was >3× larger than the largest effect sizes seen with other common variants in other populations. Carriers of p.G116S had a 3.02-fold increased risk of hypercholesterolemia (95% confidence interval, 2.34-3.90; P=1.7×10(-17)), but did not have classical familial hypercholesterolemia. In vitro, p.G116S showed 60% reduced ligand-binding activity compared with wild-type receptor. In contrast, p.R730W was associated with neither LDL cholesterol level nor altered in vitro activity. CONCLUSIONS: LDLR p.G116S is thus unique: a common dysfunctional variant in Inuit whose large effect on LDL cholesterol may have public health implications.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".