<i>BDNF</i> Val66Met moderates episodic memory decline and tau biomarker increases in early sporadic Alzheimer’s disease
Bibliographic record
Abstract
OBJECTIVE: Allelic variation in the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism has been shown to moderate rates of cognitive decline in preclinical sporadic Alzheimer's disease (AD; i.e., Aβ + older adults), and pre-symptomatic autosomal dominant Alzheimer's disease (ADAD). In ADAD, Met66 was also associated with greater increases in CSF levels of total-tau (t-tau) and phosphorylated tau (p-tau181). This study sought to determine the extent to which BDNF Val66Met is associated with changes in episodic memory and CSF t-tau and p-tau181 in Aβ + older adults in early-stage sporadic AD. METHOD: Aβ + Met66 carriers (n = 94) and Val66 homozygotes (n = 192) enrolled in the Alzheimer's Disease Neuroimaging Initiative who did not meet criteria for AD dementia, and with at least one follow-up neuropsychological and CSF assessment, were included. A series of linear mixed models were conducted to investigate changes in each outcome over an average of 2.8 years, covarying for CSF Aβ42, APOE ε4 status, sex, age, baseline diagnosis, and years of education. RESULTS: Aβ + Met66 carriers demonstrated significantly faster memory decline (d = 0.33) and significantly greater increases in CSF t-tau (d = 0.30) and p-tau181 (d = 0.29) compared to Val66 homozygotes, despite showing equivalent changes in CSF Aβ42. CONCLUSIONS: These findings suggest that reduced neurotrophic support, which is associated with Met66 carriage, may increase vulnerability to Aβ-related tau hyperphosphorylation, neuronal dysfunction, and cognitive decline even prior to the emergence of dementia. Additionally, these findings highlight the need for neuropsychological and clinicopathological models of AD to account for neurotrophic factors and the genes which moderate their expression.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".