The BDNF Val66Met Polymorphism Modulates Resilience of Neurological Functioning to Brain Ageing and Dementia: A Narrative Review
Bibliographic record
Abstract
Brain-derived neurotropic factor (BDNF) is an abundant and multi-function neurotrophin in the brain. It is released following neuronal activity and is believed to be particularly important in strengthening neural networks. A common variation in the BDNF gene, a valine to methionine substitution at codon 66 (Val66Met), has been linked to differential expression of BDNF associated with experience-dependent plasticity. The Met allele has been associated with reduced production of BDNF following neuronal stimulation, which suggests a potential role of this variation with respect to how the nervous system may respond to challenges, such as brain ageing and related neurodegenerative conditions (e.g., dementia and Alzheimer’s disease). The current review examines the potential of the BDNF Val66Met variation to modulate an individual’s susceptibility and trajectory through cognitive changes associated with ageing and dementia. On balance, research to date indicates that the BDNF Met allele at this codon is potentially associated with a detrimental influence on the level of cognitive functioning in older adults and may also impart increased risk of progression to dementia. Furthermore, recent studies also show that this genetic variation may modulate an individual’s response to interventions targeted at building cognitive resilience to conditions that cause dementia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".