Higher Serum BDNF Levels are Associated with Lower Risk of Cognitive Decline in Older Adults :The Otassha Study
Bibliographic record
Abstract
Abstract Introduction: There has been growing interest in the use of circulating levels of brain-derived neurotrophic factor (BDNF) in the blood as a biomarker in the context of patients with Alzheimer’s and other neurodegenerative diseases. Prospective data on cognitive decline in the broad older population, however, remain limited. We assessed the relationship of serum BDNF levels with short-term decline in cognitive functioning of community-dwelling older adults. Methods. Prospective study of 405 adults 65-84 years old without dementia in Tokyo, Japan. The Montreal Cognitive Assessment-Japanese version (MoCA-J) and its subscales were used. Linear regression assessed standardized differences in test score differences between baseline (2011) and follow-up (2013) visits, according to baseline serum BDNF quartiles, with adjustment for baseline demographics, disease indicators, and cognitive scores. Results: Among participants who performed on the MoCA-J at baseline (scores in bottom quartile), cognitive decline was .65 (95% CI: .08 - 1.2; p=.025) standard deviations (SD) more pronounced in those with lowest than highest BDNF levels. Decline in executive function, but not in other subdomains, was also most pronounced in those with lowest baseline serum BDNF levels (difference: .32 SD; 95%CI: .08-.55; p=.007) Conclusion: Lower serum BDNF levels were associated with greater 2-year cognitive decline in community-dwelling older Japanese adults. Decline varied among cognitive subdomains, and baseline cognition. Research seeking to evaluate the added-value of serum BDNF for screening and/or health promotion initiatives involving physical activity, which has been linked to increment in BDNF levels, is warranted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".