MARKERS AND BIOMARKERS OF DEMENTIA BDNF GENOTYPE AND CHANGES IN WHITE MATTER HYPERINTENSITIES AND HIPPOCAMPAL MICROSTRUCTURE IN OLDER MEN AND WOMEN
Bibliographic record
Abstract
Abstract Brain-derived neurotrophic factor (BDNF) may protect against cerebral gray and white matter impairments in older age. The val66met genetic polymorphism of BDNF is recently emerging as an early marker of brain structural integrity. However, evidence is sparse, cross-sectional, and mostly in men. In a longitudinal cohort study of community-dwelling older adults (N=139, mean age=81.6, 58% female, 58% white, mean follow-up=3.4 years), we estimated the overall and sex-stratified effects of BDNF val66met polymorphism on changes in cognition and gray and white matter macro- and micro-structure. Annualized percent change was computed for volume of white matter (WM) hyperintensities and gray matter (GM), fractional anisotropy of normal appearing WM, and mean diffusivity (MD) of GM in whole brain and memory and executive control function networks. Significant associations were adjusted for variables differing by genotype (race, APOE4, diabetes, triglycerides, smoking). Compared to met carriers, val homozygotes had slower annual whole brain WMH accrual (median (IQR) 31.4% (61.7) vs. 60.7% (92.4)), stronger in women. Met carriers had slower annual accrual of hippocampal MD (median (IQR) 1.26% (0.92) vs. 1.85% (1.09) for right hippocampus, stronger for women, and 1.45% (1.06) vs. 1.97% (1.22) for left hippocampus, stronger for men) compared to val homozygotes. Associations were robust to covariates’ adjustment. BDNF polymorphism was not associated with cognitive changes. BDNF polymorphism may help in early identification of those more likely to resist accrual of WMH and loss of hippocampal microstructural integrity, with effects varying by sex.
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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 | 0.001 | 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".