Interaction between Common Genetic Variants and Total Fat Intake on Low-Density Lipoprotein Peak Particle Diameter: A Genome-Wide Association Study
Bibliographic record
Abstract
BACKGROUND/AIM: Total fat intake has an important impact on the low-density lipoprotein (LDL) peak particle diameter (LDL-PPD) and may interact with nutrient-sensitive single nucleotide polymorphisms (SNPs). The objective was to examine whether there is suggestive evidence of SNP × dietary fat intake interaction effects influencing the LDL-PPD in the Quebec Family Study (QFS) in order to generate hypotheses to be tested in larger studies. METHODS: SNPs from a genome-wide association study (GWAS) using Illumina Human610-Quad BeadChip, total fat intake derived from a 3-day weighted food record, and SNP × total fat intake interaction effects were examined on LDL-PPD in 541 QFS subjects. RESULTS: The GWAS analyses 29 identified independent SNP × total fat intake interaction effects on the LDL-PPD at p < 10(-5), including SNPs in the following genes: ABCG2, CPA3, FNBP1, KCNQ3, NBAS, NCALD, OPRL1, NKAIN2, SH3BGRL2, SOX5, and SUSD4. CONCLUSIONS: This observational study suggests that multiple SNPs interact with dietary fat intake to influence variation in the LDL-PPD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".