Heterogeneity and progression of amyloid and vascular injury in Alzheimer's and Mixed dementia cohorts
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a heterogeneous disorder that is often comorbid with cerebral small vessel disease (SVD). Previous studies used highly characterized AD cohorts to identify imaging-derived subtypes to explain patient heterogeneity. Here, we studied two distinct dementia cohorts (one with a low SVD burden and one heterogeneous cohort with a Fazekas score >2) to define imaging-derived subtypes. We then determined, within each subtype, if amyloid or free-water could predict vascular lesions at baseline and over time. METHOD: We studied 262 individuals across two cohorts. The longitudinal TRIAD ("low-SVD") cohort included cognitively normal, MCI, and AD dementia (baseline, year2, year3: N = 202, 100, 70). The MITNEC-C6 ("high-SVD") cohort included real-world patients with mixed dementia and moderate-to-severe periventricular white matter hyperintensity (WMH) burden (N = 60). We quantified WMH and enlarged perivascular space (PVS) volumes based on FLAIR-MRI and T1w-MRI, respectively, in the white matter using our novel deep learning segmentation tool segCSVD (Gibson et al. 2024 HBM). Disease subtypes were identified through the Subtype and Stage Inference (SuStaIn) algorithm (Figure 1A) using the following markers: 18F-AZD4694 or 18F-AV45 amyloid-SUVR in the AD-signature regions, total WMH, total PVS, basal ganglia PVS, and DTI-derived free-water, fractional anisotropy and mean diffusivity in the normal-appearing white matter. RESULT: Both cohorts showed a 'vascular-first' subtype (green) and a 'mixed' subtype (purple) (Figure 1B-C). The low-SVD cohort additionally showed an 'amyloid-first' subtype (red). In both cohorts, greater amyloid was significantly associated with greater WMH volume in the 'mixed' subtypes (Figure 2A). Both cohorts also showed a positive association of free-water with WMH and PVS volume in each of the subtypes (Figure 2B). Finally, greater baseline amyloid predicted faster WMH growth in the 'vascular-first' subtype (Figure 3A). Whereas, in the 'mixed' subtype, greater baseline free-water but not amyloid predicted faster WMH growth (Figure 3B). Neither amyloid nor free-water predicted WMH growth in the 'amyloid-first' subtype nor did they predict PVS growth. CONCLUSION: In the mixed subtype, which is likely the most common subtype in memory clinics and community-based samples, amyloid was associated with WMH volume at baseline, but greater free-water levels predicted WMH growth over time.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".