Genetic heterogeneity in the impact of dairy product consumption on cholesterol metabolism in humans
Bibliographic record
Abstract
With the increased marketing and popularity of a range of dairy products in recent years, research has become widespread concerning the influence of dairy on human health. It is also becoming evident that an individual’s genetic make-up contributes to shaping their health responses to dietary intakes. This research was primarily designed to investigate the impact of genetic variability on responsiveness of cholesterol metabolism, a classic biomarker of cardiovascular health, to the recommended level of dairy consumption in Canada. A secondary objective was to assess the influence of dairy intake on systemic inflammation as an emerging risk factor for cardiovascular disease. In a multicentre, randomized, free-living crossover design, 124 healthy individuals consumed 3 servings/day of conventional low-fat and regular milk, yogurt, and cheese (DAIRY diet) or dairy-free control products (CONTROL diet), each for 28 days as part of a prudent background dietary protocol. At the end of the study, DAIRY was associated with increased plasma concentrations of two established fatty acid biomarkers of dairy fat, pentadecanoic acid (C15:0) and heptadecanoic acid (C17:0), as well as with small increases in serum total cholesterol (TC) and LDL-cholesterol (LDL-C) concentrations. Inter-individual variability in the cholesterol transport gene ABCG5, bile acid synthesis gene CYP7A1, and cholesterol synthesis gene DHCR7 contributed to shaping the degree of TC and LDL-C responsiveness to DAIRY; with higher cholesterol concentrations observed among ABCG5 rs6720173-G/G homozygotes, CYP7A1 rs3808607-G allele carriers, and DHCR7 rs760241-A allele carriers, relative to the C allele, T/T, and G/G carriers of these genes, respectively. Also, after DAIRY, the major allele T homozygosity of CYP7A1 rs3808607 and the minor allele A of DHCR7 rs760241 were associated with reduced plasma [3,4]13C cholesterol enrichment and deuterium incorporation, respectively, suggesting reduced cholesterol absorption and synthesis rates. DAIRY intake did not influence the inflammatory status. Overall, this research has provided evidence of a potential impact of the genomic architecture on responsiveness of cholesterol metabolism to dairy consumption. The novel findings are expected to advance knowledge of the inherited basis by which health biomarkers may be modified in response to whole foods, hence launching an important step towards an era of personalized nutrition.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".