Associations between the Leptin Receptor Gene and Adiposity in Middle-Aged Caucasian Males from the HERITAGE Family Study<sup>1</sup>
Bibliographic record
Abstract
Linkage and association studies between three exonic polymorphisms in the leptin receptor gene and body composition variables in the HERITAGE Family Study were undertaken. Polymorphisms K109R, Q223R, and K656N have been analyzed with body mass index (BMI), sum of height skinfolds (SF8), fat mass (FM), percent body fat (%FAT), fat free mass, and plasma leptin level. Single-point linkage analysis and covariance analysis across genotypes were performed, by race, on phenotypes adjusted for age and sex. Blacks (88 parents; 231 adult offspring) from 115 nuclear families (72-119 sibpairs) and Caucasians (192 parents; 330 adult offspring) from 99 nuclear families (319-364 sibpairs) were used for these analyses. In Caucasians, BMI and FM showed suggestive linkages with K109R (P = 0.02 and P = 0.05, respectively) and associations with Q223R (P = 0.005 and P = 0.03, respectively). In blacks, no statistically significant linkage or association was observed. In Caucasians, associations with Q223R were observed in parents, but not in offspring, for BMI, FM, and %FAT (0.04< or =P< or =0.0001). Males, not females, showed differences across genotypes for the same phenotypes plus SF8 and leptin (0.03< or = P< or =0.0002). Carriers of the R223 allele showed higher values than noncarriers for BMI (+4 U, P = 0.0001), SF8 (+30 mm, P = 0.01), FM (+7 kg, P = 0.0004), %FAT (+5%, P = 0.0002), and leptin (+4 ng/mL, P = 0.0006). These results indicate a significant effect of leptin receptor on adiposity in middle-aged Caucasian males.
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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) | 0.001 | 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".