Alzheimer's disease: The influence of age on clinical heterogeneity through the human brain connectome
Bibliographic record
Abstract
INTRODUCTION: One major factor that influences the heterogeneity of Alzheimer's disease (AD) is age: younger AD patients more frequently exhibit atypical forms of AD. We propose that this age-related heterogeneity can be understood better by considering age-related differences in atrophy in the context of large-scale brain networks subserving cognitive functions that contribute to memory. METHODS: We examined data from 75 patients with mild AD dementia from Alzheimer's Disease Neuroimaging Initiative. These individuals were chosen because they have cerebrospinal fluid amyloid and p-tau levels in the range suggesting the presence of AD neuropathology, and because they were either younger than age 65 years early-onset AD (EOAD) or age 80 years or older late-onset AD (LOAD). RESULTS: In the EOAD group, the most prominent atrophy was present in the posterior cingulate cortex, whereas in the LOAD group, atrophy was most prominent in the medial temporal lobe. Structural covariance analysis showed that the magnitude of atrophy in these epicenters is strongly correlated with a distributed atrophy pattern similar to distinct intrinsic connectivity networks in the healthy brain. An examination of memory performance in EOAD dementia versus LOAD dementia demonstrated relatively more prominent impairment in encoding in the EOAD group than in the LOAD group, with similar performance in memory storage in LOAD and EOAD but greater impairment in semantic memory in LOAD than in EOAD. DISCUSSION: The observations provide novel insights about age as a major factor contributing to the heterogeneity in the topography of AD-related cortical atrophy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".