Individual and Joint Associations of Methylenetetrahydrofolate Reductase C677T Genotype and Plasma Homocysteine With Dyslipidemia in a Chinese Population With Hypertension
Bibliographic record
Abstract
We aimed to examine the cross-sectional associations of plasma total homocysteine (tHcy) concentrations and methylenetetrahydrofolate reductase ( MTHFR) C677T genotype with dyslipidemia. A total of 231 patients with mild-to-moderate essential hypertension were enrolled from the Huoqiu and Yuexi communities in Anhui Province, China. Plasma tHcy levels were measured by high-performance liquid chromatography. Genotyping was performed by TaqMan allelic discrimination technique. Compared with MTHFR 677 CC + CT genotype carriers, TT genotype carriers had higher odds of hypercholesterolemia (adjusted odds ratio [OR] [95% confidence interval (CI)]: 2.7 [1.4-5.2]; P = .004) and higher odds of abnormal low-density lipoprotein cholesterol (adjusted OR [95% CI]: 2.3 [1.1-4.8]; P = .030). The individuals with the TT genotype had higher concentrations of log(tHcy) than those with the 677 CC + CT genotype (adjusted β [standard error]: .2 [0.03]; P < .001). Patients with tHcy ≥ 10 μmol/L had significantly higher odds of hypercholesterolemia (adjusted OR [95% CI]: 2.4 [1.2-4.7]; P = .010). Furthermore, patients with both the TT genotype and the tHcy ≥ 10 μmol/L had the highest odds of hypercholesterolemia (adjusted OR [95% CI]: 4.1 [1.8-9.4]; P = .001) and low-density lipoprotein cholesterol (adjusted OR [95% CI]: 2.4 [1.0-6.0]; P = .064). This study suggests that both tHcy and the MTHFR C677T gene polymorphism may be important determinants of the incidence of dyslipidemia in Chinese patients with essential hypertension. Further studies are needed to confirm the role of tHcy and the MTHFR C677T mutation in the development of dyslipidemia in a larger sample.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".