Structural heterogeneity and intersubject variability of Aβ in familial and sporadic Alzheimer’s disease
Bibliographic record
Abstract
Point mutations in the amyloid-β (Aβ) coding region produce a combination of mutant and WT Aβ isoforms that yield unique clinicopathologies in familial Alzheimer's disease (fAD) and cerebral amyloid angiopathy (fCAA) patients. Here, we report a method to investigate the structural variability of amyloid deposits found in fAD, fCAA, and sporadic AD (sAD). Using this approach, we demonstrate that mutant Aβ determines WT Aβ conformation through prion template-directed misfolding. Using principal component analysis of multiple structure-sensitive fluorescent amyloid-binding dyes, we assessed the conformational variability of Aβ deposits in fAD, fCAA, and sAD patients. Comparing many deposits from a given patient with the overall population, we found that intrapatient variability is much lower than interpatient variability for both disease types. In a given brain, we observed one or two structurally distinct forms. When two forms coexist, they segregate between the parenchyma and cerebrovasculature, particularly in fAD patients. Compared with sAD samples, deposits from fAD patients show less intersubject variability, and little overlap exists between fAD and sAD deposits. Finally, we examined whether E22G (Arctic) or E22Q (Dutch) mutants direct the misfolding of WT Aβ, leading to fAD-like plaques in vivo. Intracerebrally injecting mutant Aβ40 fibrils into transgenic mice expressing only WT Aβ induced the deposition of plaques with many biochemical hallmarks of fAD. Thus, mutant Aβ40 prions induce a conformation of WT Aβ similar to that found in fAD deposits. These findings indicate that diverse AD phenotypes likely arise from one or more initial Aβ prion conformations, which kinetically dominate the spread of prions in the brain.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".