Hypertension in Obesity and the Leptin Receptor Gene Locus<sup>1</sup>
Bibliographic record
Abstract
Recent animal studies indicate that leptin is involved in the regulation of blood pressure through the leptin receptor. Therefore, 51-yr-old men (N = 284) were selected; and anthropometric, endocrine, metabolic, and hemodynamic variables were examined in relation to polymorphisms of the leptin receptor gene (LEPR), by restriction fragment length polymorphism technique. Three polymorphisms were examined: Lys109Arg in exon 4, Gln223Arg in exon 6, and Lys656Asn in exon 14. In comparison with Lys109 homozygotes, Arg109 homozygotes (9%) showed lower body mass index (BMI) and abdominal sagittal diameter, as well as lower systolic (10.0 mm Hg) and diastolic (7.8 mm Hg) blood pressure. Additionally, Arg223 homozygotes (26.8%) showed lower blood pressure (7.6/5.7 mm Hg) than Gln223 homozygotes. These lower blood pressure levels were independent of other variables. No differences were found with the Lys656Asn polymorphism. Measurements of body fat mass correlated with leptin concentration in Lys109 homozygotes and in Lys109 heterozygotes but not in Arg109 homozygotes. Blood pressure correlated with leptin only in men carrying the wild-type allele Lys109. With both elevated BMI and leptin, Lys109 homozygotes had higher blood pressure than the Arg109 homozygous men (12.4/6.9 mm Hg). Men with blood pressure > or = 140/90 mm Hg had, in comparison with normotensive men, increased BMI and leptin levels, and Lys109 homozygotes were significantly more prevalent. These results suggest that leptin is associated with blood pressure regulation in men through the leptin receptor. When BMI and leptin are elevated, increased blood pressure is found only with the most prevalent LEPR genotype at codons 109 and 223, whereas variants of this receptor seem to protect from hypertension. This might explain why not all obese men are hypertensive.
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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 | 0.000 | 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) | 0.002 | 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".