Serum levels of adipokines and insulin are associated with markers of brain atrophy and cognitive decline in the spectrum of Alzheimer’s Disease
Bibliographic record
Abstract
ABSTRACT The discovery that metabolic alterations often coexist with neurodegenerative conditions has sparked interest in the examination of gastrointestinal factors as potential modulators of brain health. Here, we examined the role of adipokines (leptin, adiponectin, resistin, and IL6) and insulin on different markers of brain atrophy in participants on the spectrum of Alzheimer’s Disease. We included 566 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset with 1063 follow-up time points (average follow-up: one year); and examined the association between gastrointestinal factors and volumetric MRI values, white matter hyperintensities, and measures of cognitive impairment. Higher leptin, resistin, IL6, and insulin were associated with markers of cerebral atrophy, such as lower total brain volume, or higher ventricular volume. Higher leptin and resistin were also associated with greater impairment in daily life activities. Higher adiponectin was associated with lower ventricle volume. There was no association between adipokines or insulin with white matter hyperintensities. Our findings indicate a co-occurrence between alterations in gastrointestinal factors and in brain volume along the preclinical to clinical spectrum of Alzheimer’s Disease. These results suggest that strategies aimed at promoting metabolic health may positively impact brain health.
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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 | 0.001 | 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 | 0.001 | 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".