Associations of Rs3744841 and Rs3744843 Polymorphisms in Endothelial Lipase Gene with Risk of Coronary Artery Disease and Lipid Levels in a Chinese Population
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to assess the association between the 2037T/C and 2237G/A polymorphisms in the EL gene and the risk of CAD and lipid levels in a Chinese population. METHODS: A case-control study including 706 patients with CAD and 315 controls was performed. The polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was used to identify the genotypes. RESULTS: The EL 2037 T/C polymorphism was associated with CAD risk and HDL-C levels. No significant differences were found between the EL 2237 G/A genotypes and CAD risk and lipid levels in the whole population. However, carriers of the 2237 A allele had higher Apo A1 levels than those with the 2237 GG genotype and in the CAD subgroup (P = 0.044). The CAD cases have a significantly lower frequency of the C-G haplotypes than the controls, and the T-A haplotype was significantly more common in the CAD patients than in the controls. CONCLUSIONS: Our study concluded that the EL 2037 T/C polymorphism was associated with CAD risk and HDL-C levels, and that the C allele might be a protective factor against CAD in the Chinese Han population. In addition, the EL 2237 A allele might be associated with an increased Apo A1 level in CAD subjects.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".