Leptin receptor Gln223Arg variant is associated with a cluster of metabolic abnormalities in response to long‐term overfeeding
Bibliographic record
Abstract
Abstract. Ukkola O, Tremblay A, Després J‐P, Chagnon YC, Campfield LA, Bouchard C (Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA; University of Oulu, Oulu, Finland; Laval University, Ste‐Foy, Québec, Canada; and University of Colorado Health Sciences Center, Denver, Colorado, USA). Leptin receptor Gln223Arg variant is associated with a cluster of metabolic abnormalities in response to long‐term overfeeding. J Intern Med 2000; 248: 435–439. Objectives. The role of the leptin receptor (LEPR) gene Gln223Arg polymorphism on the metabolic and body composition changes in response to overfeeding was studied. Subjects. Twelve pairs of male monozygotic twins ate a 4.2 MJ day–1 energy surplus, 6 days week–1, during a period of 100 days. Results. Overfeeding induced a significantly greater increase in glucose (P = 0.001 for percentage change) and insulin (P = 0.038) areas under the curve during oral glucose tolerance tests (OGTTs) in the GlnGln (n = 10) than in the GlnArg/ArgArg (n = 14) subjects. In addition, the GlnGln genotype was associated with a greater increase in plasma levels of leptin (P = 0.037) and total triglycerides (P = 0.003), as well as a greater decrease in high‐density lipoprotein cholesterol (P = 0.010), than for the combined GlnArg/ArgArg genotypes. Body composition changes were not different between the genotypes. Conclusions. We conclude that the GlnGln subjects of the LEPR gene polymorphism are more susceptible to metabolic abnormalities when they are exposed to long‐term positive energy balance. These findings provide new information on the genetic basis of individual differences in response to chronically elevated food intake.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".