Associations of Two Common Polymorphisms in <i>MTHFR</i> Gene with Blood Lipidsand Therapeutic Efficacy of Simvastatin
Bibliographic record
Abstract
BACKGROUND: Cardio-cerebrovascular disease is an important public health challenge worldwide, and its complex etiology has not been elucidated fully. The study investigated the relationship between two common polymorphisms, C677T and A1298C in the methylenetetrahydrofolate reductase (MTHFR) gene, baseline lipids and the lipid-lowering efficacy of simvastatin in a Chinese hyperlipidemic population. METHODS: All participants were recruited from Anhui, China. By the extreme sampling method, we selected subjects with a low response (n=108) and high response (n=106) based on their adjusted lipid-lowering response to simvastatin administrated for 8 consecutive weeks. Both MTHFR C677T and A1298C loci were genotyped by the MALDI-TOF MS platform. Serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were measured at baseline and after 8 weeks of oral 20 mg/d tablets of simvastatin. RESULTS: Patients with the 677TT genotype had significantly higher baseline TC, HDL-C, and change in HDL-C (ΔHDL-C) levels after treatment than those with 677CC+CT genotypes (β = 0.207, P = 0.045; β = 0.182, P = 0.026; and β = 0.16, P = 0.002, respectively). Patients with 1298AC+CC genotypes had significantly higher baseline LDL-C and change in LDL-C (ΔLDL-C) levels (β = 0.276, P =0.043; β = 0.359, P = 0.025, respectively) than those with 1298AA genotype. We found statistical interactions between the two SNPs in association with baseline HDL-C (P for interaction = 0.034), TC (P for interaction = 0.069), and TG (P for interaction = 0.034). Baseline TC (P = 0.027) and HDL-C (P = 0.046) and change in HDL-C (P = 0.019) were different among those with the MTHFR A-T haplotype compared with A-C. CONCLUSION: Our major findings suggest that both MTHFR C677T and A1298C polymorphisms could be important genetic determinants of lipid traits and drug efficacy of simvastatin. This will contribute to a better understanding of strategies for personalized medication in Chinese patients with dyslipidemia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".