Early changes in basal forebrain volume and cognitive function in preclinical autosomal dominant Alzheimer's disease
Bibliographic record
Abstract
Abstract Background The basal forebrain (BF), home to cholinergic neurons essential for attention and memory undergoes structural changes in sporadic Alzheimer's Disease and in at‐risk individuals, contributing to cognitive decline. To investigate whether BF volume is reduced in preclinical autosomal‐dominant Alzheimer's disease (ADAD), we studied cognitively‐unimpaired carriers of the PSEN1 E280A mutation from the Colombian kindred, the largest ADAD cohort with a single mutation, known for early cognitive decline (mild cognitive impairment at age 44, dementia at 49). Age was used as a proxy for disease progression to analyze BF volume and its relationship with age and cognitive performance. Method This study included 127 cognitively‐unimpaired individuals from the PSEN1 Colombian kindred (60 carriers, 67 non‐carriers; mean‐age: 30.67 ± 6.65 years; mean‐education: 12.24 ± 3.06 years). Unimpaired status was defined by Functional Assessment Staging (FAST) scores <2. Participants underwent structural MRI and cognitive testing, with BF volumes measured using a cholinergic nuclei map. Cognition was assessed with the Mini‐Mental State Examination (MMSE) and the CERAD Word List Learning (WLL) task. BF volume differences between groups were assessed using a t‐test, and partial Pearson correlations (adjusted for sex, education, and intracranial volume) were used to evaluate relationships between BF volume, age, and cognition. Result BF volumes did not differ significantly between carriers (693.83 ± 68.3 mm3) and non‐carriers (694.00 ± 65.24 mm3) ( p = 0.82). Age was negatively correlated with BF volume in the overall sample ( r = ‐0.41, p = 2.7e‐06), carriers ( r = ‐0.41, p = 0.001), and non‐carriers ( r = ‐0.44, p = 2.6e‐04). However, BF volume showed no significant correlation with MMSE or WLL in the overall sample, carriers, or non‐carriers. Conclusion These findings suggest that Alzheimer's‐related volumetric changes in the basal forebrain may not manifest during the early preclinical stages of ADAD. This highlights the importance of future studies incorporating longitudinal measures to track BF changes over time, spanning the continuum from preclinical to clinical stages. Such research could provide critical insights into the temporal dynamics of BF involvement and its potential as a marker for early detection or therapeutic target in ADAD.
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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 | 0.000 |
| 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".