White Matter Hyperintensity as a Vascular Contribution to the AT(N) Framework
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Bibliographic record
Abstract
The AT(N) framework enables the classification of an individual within the biological Alzheimer's disease (AD) continuum by pairing the cognitive stage with the biomarker status of amyloid-beta (Aβ, A), tau (T) and neurodegeneration (N). AD is a multifactorial disease that may involve different pathogenic mechanisms such as cerebrovascular disease (CVD). Therefore, biomarkers of these mechanisms can be added to the AT(N) framework to enhance the biomarker characterization of individuals within the AD continuum. In AD, white matter hyperintensities (WMH) which are postulated to develop as a result of chronic ischemia from small vessel CVD are shown to play a role in the aetiology. However, the interplay of WMH with Aβ and tau pathophysiology in AD remains unclear. In this review, we summarized the studies that evaluated the associations between WMH and AD pathophysiology (Aβ and tau). We found that the evidence supporting the association of WMH with Aβ was mixed, and this may be explained by the relative contributions of WMH due to its differential load and anatomical distribution. More studies are also needed to determine the association of WMH with tau pathology. Future longitudinal studies with harmonized methodologies to quantify WMH and account for the anatomical differences of WMH are required to validate the relationship between WMH and AT(N) biomarkers. This will allow a clearer understanding of the utility of WMH as a vascular biomarker in the AT(N) framework. Novel CVD biomarkers will also have the potential to further elucidate the contributions of CVD to the AD pathophysiology.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it