Association of <i>Lipin 1</i> Gene Polymorphisms with Measures of Energy and Glucose Metabolism
Bibliographic record
Abstract
OBJECTIVE: To examine the importance of lipin 1 (LPIN1) gene variation in energy and glucose metabolism. Transgenic animal models have shown that lipin, a protein encoded by the LPIN1 gene, promotes fat synthesis and storage in adipose tissue while decreasing energy expenditure and lipid oxidation in skeletal muscle. Lpin1 was identified as the mutated gene in the fatty liver dystrophy mouse, which exhibits lipin deficiency and features of human lipodystrophy. RESEARCH METHODS AND PROCEDURES: We genotyped five LPIN1 polymorphisms and tested for association with resting metabolic rate (RMR), fat oxidation, fasting plasma insulin and glucose concentration, and obesity-related phenotypes, including BMI, body fat percentage, sum of six skinfolds, and waist circumference in 712 subjects of the Quebec Family Study. RESULTS: The strongest results were generation-specific. In parents, RMR of the G/G IVS13 + 3333A>G homozygotes was 107 kcal/d higher than in A/A homozygotes and 39 kcal/d higher than in A/G heterozygotes (p = 0.0003). In offspring, carriers of the C allele of the IVS18 + 181C>T variant had significantly higher (p < 0.0003) insulin levels than T/T homozygotes. These associations remained significant after adjusting for multiple testing. Several other associations between body composition measures and the IVS18 + 181C>T variant were significant (p = 0.05 to 0.003), suggesting a strong pattern of relationships. DISCUSSION: These findings support the hypothesis that sequence variation in the LPIN1 gene contributes to variation in RMR and obesity-related phenotypes potentially in an age-dependent manner.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".