Genetic variants of the lipoprotein lipase gene and myocardial infarction in the Central Valley of Costa Rica
Bibliographic record
Abstract
To assess common variants of the LPL gene that could influence susceptibility to myocardial infarction (MI), we assessed three functional single-nucleotide polymorphisms (SNPs), D9N, N291S, and S447X, in 1,321 survivors of a first acute MI and 1,321 population-based controls, matched for age, gender, and area of residence, all living in the Central Valley of Costa Rica. Conditional logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (CI). The frequency of the X447 mutant allele was significantly lower in cases than in controls (6.2% vs. 7.6%; P < 0.01), whereas no association with MI was found for D9N or N291S. The OR (95% CI) for carriers vs. noncarriers of the X447 allele was 0.80 (0.63-1.01); when considering the haplotype that contained X447 and normal alleles of D9N and N291S, the OR (95% CI) was 0.66 (0.48-0.91). Twelve other SNPs were assessed in a subgroup of the population, of which the four functional SNPs were found to be monomorphic, and no correlation with MI was observed for the other eight neutral SNPs. The X447 mutant allele of the LPL gene may protect from MI risk, although this effect is small.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".