[IC‐P‐100]: MOVING AWAY FROM SINGLE AD‐SIGNATURE ROI: ASSESSING THE RELATIONSHIP BETWEEN WHOLE‐BRAIN GRAY MATTER PATTERN, AD PATHOLOGY, AND COGNITION IN HEALTHY ELDERLY AT RISK OF AD
Bibliographic record
Abstract
Hippocampal volume (HV) is often used to indicate neurodegeneration in Alzheimer's disease (AD) (Sperling et al., 2011). Hippocampal atrophy is not specific to AD, however (Bartsch & Wulff, 2015), and we investigated whether whole-brain (wb) gray matter (GM) pattern is better related to CSF biomarkers of AD or cognition than single metrics such as HV. We obtained structural MR images from 296 members of the PREVENT-AD cohort of cognitively normal adults with a parental or multiple-sibling history of AD dementia (mean age=64). We compared these with reference groups of 198 young individuals from the Cambridge dataset and 270 from the Human Connectome Project (both aged ≈35), as well as cognitively impaired ADNI participants (50 with early MCI, 65 with late MCI, and 72 with AD dementia (mean age ≈74)). We derived 24 GM regions of interest (ROI) from an independent components analysis across all groups. Next we assessed the mean GM density in all ROI separately for each reference group. Then, for each PREVENT-AD participant, we correlated the ROI–specific GM density pattern vs. that among the reference groups (Figure 1). We evaluated HV using patch-based segmentation (Coupé et al., 2011). Finally, we used general linear models to examine if the wbGM pattern similarity of each PREVENT-AD participant with the corresponding pattern of the reference groups, the HV, or individual ROIs, was associated with CSF Ab42 and p-tau levels, as well as cognitive domain scores on the RBANS. The wbGM pattern metrics, but not individual ROIs GM or HV, were associated with CSF biomarkers and cognition. A wbGM pattern similar to that of the young groups was related to better immediate memory, language and attention (all p ≤0.03), while a pattern similar to the cognitively impaired groups was associated with increased amyloid burden (p<0.05, Table 1). In healthy elderly with a family history of AD, wbGM pattern appears more potent as a predictor of cognitive performance and amyloid burden than HV or individual ROI metrics. Evaluation of whole-brain structural changes may therefore hold particular interest for early identification of AD in those at risk. Mean GM density per ROI in each group
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".