Fat-mass-related hormone, plasma leptin, predicts brain volumes in the elderly
Bibliographic record
Abstract
Leptin, a hormone produced by body fat tissue, acts on hypothalamic receptors in the brain to regulate appetite and energy expenditure, and on neurons in the arcuate nucleus to signal that an individual has had enough to eat. Leptin enters the central nervous system at levels that depend on an individual's body fat. Obese people, on average, show greater brain atrophy in old age, so it is valuable to know whether brain atrophy relates to leptin levels, which can be targeted by interventions. We therefore determined how plasma leptin levels, and BMI, relate to brain structure, and whether leptin levels might account for BMI's effect on the brain. We measured regional brain volumes using tensor-based morphometry, in MRI scans of 517 elderly individuals with plasma leptin measured (mean: 13.3±0.6 ng/ml; mean age: 75.2±7.3 years; 321 men/196 women). We related plasma leptin levels to brain volumes at every location in the brain after adjusting for age, sex, and diagnosis and, later, also BMI. Plasma leptin levels were significantly higher (a) in women than men, and (b) in obese versus overweight, normal or underweight individuals. People with higher leptin levels showed deficits in frontal, parietal, temporal and occipital lobes, brainstem, and the cerebellum, irrespective of age, sex, or diagnosis. These associations persisted after controlling for BMI. Greater brain atrophy may occur in people with central leptin insufficiency, a marker of obesity. Therapeutic manipulation of leptin may be a promising direction for slowing brain decline.
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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) | 0.001 | 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".