Cholesteryl ester transfer protein gene polymorphisms increase the risk of fatty liver in females independent of adiposity
Bibliographic record
Abstract
BACKGROUND AND AIM: Environmental factors including excessive caloric intake lead to disordered lipid metabolism and fatty liver disease (FLD). However, FLD demonstrates heritability suggesting genetic factors are also important. We aimed to use a candidate gene approach to examine the association between FLD and single nucleotide polymorphisms (SNPs) in lipid metabolism genes in the adolescent population-based Western Australian Pregnancy (Raine) Cohort. METHODS: A total 951 seventeen year-olds underwent hepatic ultrasound, anthropometric and biochemical characterization, DNA extraction and genotyping for 57 SNPs in seven lipid metabolism genes (ApoB100, ATGL, ABHD5, MTTP, CETP, SREBP-1c, PPARα). Associations were adjusted for metabolic factors and Bonferroni corrected. RESULTS: The prevalence of FLD was 16.2% (11.4% male vs 21.2% female, P=0.001). Multivariate analysis of metabolic factors found suprailiac skinfold thickness (SST) to be the major predictor of FLD in females and males (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.08-1.15, P=1.7×10(-10) and OR 1.17, 95%CI 1.13-1.22, P=2.4×10(-11) , respectively). In females, two SNPs in linkage disequilibrium from the CETP gene were associated with FLD: rs12447924 (OR 2.16, 95%CI 1.42-3.32, P=0.0003) and rs12597002 (OR=2.22, 95%CI 1.46-3.41 P=0.0002). In lean homozygotes, the probability of FLD was over 30%, compared with 10-15% in lean heterozygotes and 3-5% in lean wild-types. However, these associations were modified by SST, such that for obese individuals, the probability of FLD was over 30% in all genotype groups. CONCLUSIONS: Cholesteryl ester transfer protein gene polymorphisms are associated with an increased risk of FLD in adolescent females. The effect is independent of adiposity in homozygotes, thereby placing lean individuals at a significant risk of FLD.
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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) | 0.001 | 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".