Aβ and tau form soluble complexes that may promote self aggregation of both into the insoluble forms observed in Alzheimer’s disease
Bibliographic record
Abstract
To date, there is no reasonable explanation as to why plaques and tangles simultaneously accumulate in Alzheimer's disease (AD). We demonstrate here by Western blotting and ELISA that a stable complex can form between tau and amyloid-beta protein (Abeta). This complex enhances tau phosphorylation by GSK3beta, but the phosphorylation then promotes dissociation of the complex. We have localized the sites of this interaction by using peptide membrane arrays. Abeta binds to multiple tau peptides, especially those in exons 7 and 9. This binding is sharply reduced or abolished by phosphorylation of specific serine and threonine residues. Conversely, tau binds to multiple Abeta peptides in the mid to C-terminal regions of Abeta. This binding is also significantly decreased by GSK3beta phosphorylation of tau. We used surface plasmon resonance to determine the binding affinity of Abeta for tau and found it to be in the low nanomolar range and almost 1,000-fold higher than tau for itself. In soluble extracts from AD and control brain tissue, we detected Abeta bound to tau in ELISAs. We also found by double immunostaining of AD brain tissue that phosphorylated tau and Abeta form separate insoluble complexes within the same neurons and their processes. We hypothesize that in AD, an initial step in the pathogenesis may be the intracellular binding of soluble Abeta to soluble nonphosphorylated tau, thus promoting tau phosphorylation and Abeta nucleation. Blocking the sites where Abeta initially binds to tau might arrest the simultaneous formation of plaques and tangles in AD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".