The Peroxisome Proliferator‐Activated Receptor α L162V Mutation Is Associated with Reduced Adiposity
Bibliographic record
Abstract
OBJECTIVE: To determine the contribution of the peroxisome proliferator-activated receptor alpha (PPARalpha) L162V mutation to the variation of several indexes of body fatness obtained from healthy adults who participated in the Quebec Family Study. RESEARCH METHODS AND PROCEDURES: The PPARalpha L162V mutation was determined by a mismatch polymerase chain reaction method. Adiposity phenotypes were obtained by standardized anthropometric measurements, underwater weighing technique, and computed tomography. RESULTS: For all adiposity phenotypes, subjects carrying the V162 allele had lower values compared with L162 homozygotes (HMZs) [BMI (kg/m(2)): 27.8 +/- 7.6 vs. 26.0 +/- 5.6, p < 0.05; percentage body fat: 28.5 +/- 10.7 vs. 25.7 +/- 10.1, p < 0.05; waist circumference (cm): 89.0 +/- 18.1 vs. 85.7 +/- 15.8, p = 0.07; total computed tomography abdominal fat areas (cm(2)): 406 +/- 221 vs. 359 +/- 192, p = 0.15; means +/- SD for L162 HMZs vs. V162 carriers, respectively]. Differences in cross-sectional abdominal adipose tissue areas and waist circumference were abolished after adjustment for total body fat mass. Similar trends were observed when results were analyzed by gender, although associations seemed stronger in women. The odds ratio of having a BMI above 30 kg/m(2) reached 1.77 (1.02; 3.07, 95% confidence intervals) for L162 HMZs. This risk could be considered marginal on an individual basis, but because 85% of the subjects are affected by this small risk, the impact on the population is important. DISCUSSION: The PPARalpha V162 allele is associated with reduced adiposity and has a substantial population-attributable risk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".