The lipoprotein/lipid profile is modulated by a gene–diet interaction effect between polymorphisms in the liver X receptor-α and dietary cholesterol intake in French-Canadians
Bibliographic record
Abstract
Genetic and nutritional factors interact together and modulate the plasma lipid profile. We identified variations in the gene encoding the liver X receptor alpha (LXRalpha) and investigated their effects on the plasma lipoprotein/lipid profile. We also examined whether the association between cholesterol intake and plasma lipid profile was modulated by LXRalpha variants. The LXRalpha gene was sequenced in thirty-five French-Canadian men with high plasma total cholesterol (>5.0 mmol/l) and LDL-cholesterol (>3.5 mmol/l) concentrations. dietary cholesterol was obtained from a food-frequency questionnaire. The LXRalpha c.-115G>A, c.-840C>A and c.-1830T>C genotypes were determined by direct sequencing in 732 subjects. Molecular screening of the LXRalpha gene revealed sixteen variants. Genotypes c.-115G>A, c.-840C>A and c.-1830T>C (rare allele frequency of 14.3%, 14.2% and 11.0%, respectively) were analysed further. Plasma total cholesterol concentrations were higher in carriers of the -115A, -840A and -1830C allele, compared with the -115G/G, -840C/C and -1830T/T homozygotes (P< or =0.05). In a model including the c.-115G>A polymorphism, cholesterol intake, the interaction term c.-115G>A x cholesterol intake (mg/d) and covariates, LXRalpha-115G>A explained 1.8% and 2.1% of the variance in total cholesterol and LDL-cholesterol concentrations (P=0.02 and P=0.01), whereas the interaction term explained 2.9% (P=0.002) and 2.8% (P=0.005), respectively. When subjects were divided into four groups according to the median of cholesterol (290.8 mg) and -115G>A genotypes, high cholesterol intake was associated with higher cholesterol levels in -115A carriers. Similar results were observed for c.-840C>A and c.-1830T>C. These results suggest that cholesterol intake interacts with LXRalpha variants to modulate the plasma lipid profile.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".