Baseline serum brain-derived neurotrophic factor association with future cognition in community-dwelling older adults undergoing annual memory screening
Bibliographic record
Abstract
Objectives It has been shown that peripheral measures of brain-derived neurotrophic factor (BNDF), an important neurotrophin instrumental to the biology of learning, may contribute to predicting cognitive decline. However, the two primary forms of BDNF, mature (mBDNF) and pro (proBDNF), and how they contribute to cognition longitudinally has not been well studied.Methods Eighty-two older adults (average age 72.2 ± 6.4 years) provided blood samples at two time points separated on average by 4.2 years while participating in an annual memory screening that included the MoCA (Montreal Cognitive Assessment) and GDS (Geriatric Depression Scale). Both mBDNF and proBDNF from serum were quantified at each time point. Whole blood samples were genotyped for APOE and BDNF Val66Met.Results Using logistic regression analysis controlling for age, sex, baseline MoCA score, APOE, and BDNF, higher baseline mBDNF was associated with subjects whose screening score was near maximum or maximum (as defined by MoCA score of 29 or 30) at the second collection visit. APOE was a significant contributing factor; however, BDNF Val66Met was not. Using a similar logistic regression analysis, baseline proBDNF was not found to be associated with future cognition.Discussion This study further supports that mBDNF measured in the serum of older adults may reflect a protective role while proBDNF requires further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".