Review: Cerebral amyloid angiopathy, prion angiopathy, <scp>CADASIL</scp> and the spectrum of protein elimination failure angiopathies (<scp>PEFA</scp>) in neurodegenerative disease with a focus on therapy
Bibliographic record
Abstract
Failure of elimination of proteins from the brain is a major feature in many neurodegenerative diseases. Insoluble proteins accumulate in brain parenchyma and in walls of cerebral capillaries and arteries. Cerebral amyloid angiopathy (CAA) is a descriptive term for amyloid in vessel walls. Here, we adopt the term protein elimination failure angiopathy (PEFA) to focus on mechanisms involved in the pathogenesis of a spectrum of disorders that exhibit both unique and common features of protein accumulation in blood vessel walls. We review (a) normal pathways and mechanisms by which proteins and other soluble metabolites are eliminated from the brain along 100- to 150-nm-thick basement membranes in walls of cerebral capillaries and arteries that serve as routes for lymphatic drainage of the brain; (b) a spectrum of proteins involved in PEFA; and (c) changes that occur in artery walls and contribute to failure of protein elimination. We use accumulation of amyloid beta (Aβ), prion protein and granular osmiophilic material (GOM) in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) as examples of different factors involved in the aetiology and pathogenesis of PEFA. Finally, we discuss how knowledge of factors involved in PEFA may help to focus on new therapies for neurodegenerative diseases. When Aβ (following immunotherapy) and prion protein are released from brain parenchyma they deposit in walls of cerebral capillaries and arteries; GOM in CADASIL accumulates primarily in artery walls. Therefore, the focus of therapy for protein clearance in neurodegenerative disease should perhaps be on facilitating perivascular elimination of proteins and reducing PEFA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".