Association and Interaction Effect between VEGF Receptor-2 (VEGFR-2) Gene Polymorphisms and Dietary Pattern on Blood Lipids in Malaysian Adults
Bibliographic record
Abstract
Background: Vascular endothelial growth factor receptor-2 (VEGFR-2) and diet are related to blood lipid health. Gene-diet interaction studies can identify the risks. The objectives are to determine associations, and interaction effects between VEGFR-2 gene polymorphisms (rs1870377 and rs2071559) and dietary patterns on blood lipids in multi-ethnic Malaysian adults. Methods: Dietary intakes of 509 (153 Malay, 179 Chinese, and 177 Indian) Malaysians were obtained from food frequency questionnaire for the construction of dietary patterns using factor analysis. Anthropometric measurements: body mass index and blood pressure; and biomarkers: glycated hemoglobin, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and total cholesterol/HDL-C ratio were determined. Genotyping of rs1870377 and rs2071559 was performed by real-time PCR using Taqman probes. Results: Two major dietary patterns were extracted from all subjects: ‘Vegetables, fruits, and soy diet’ (VFSD), and ‘Rice, egg, and fish diet’ (REFD). There were significant genetic associations for rs2071559 with TG (p=0.048) in Malays, and in Chinese for rs1870377 with TC (p=0.001) and LDL-C (p=0.007), and rs2071559 on LDL-C (p=0.048). The interaction effects of VEGFR-2 gene polymorphisms and dietary patterns were significant in Malays between rs2071559 and REFD on TG (p=0.005); and in Chinese between VFSD and rs1870377 on LDL-C (p=0.028) after adjusting for potential confounders. There were no significant genetic or dietary associations on blood lipids in Indians (p>0.05). Conclusion: The significant associations and gene-diet interaction effects between VEGFR-2 gene polymorphisms and dietary patterns on blood lipids may pose hyperlipidemia and hypercholesterolemia risks in Malay and Chinese Malaysians
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".