Affinity of Tau antibodies for solubilized pathological Tau species but not their immunogen or insoluble Tau aggregates predicts in vivo and ex vivo efficacy
Bibliographic record
Abstract
BACKGROUND: A few tau immunotherapies are now in clinical trials with several more likely to be initiated in the near future. A priori, it can be anticipated that an antibody which broadly recognizes various pathological tau aggregates with high affinity would have the ideal therapeutic properties. Tau antibodies 4E6 and 6B2, raised against the same epitope region but of varying specificity and affinity, were tested for acutely improving cognition and reducing tau pathology in transgenic tauopathy mice and neuronal cultures. RESULTS: Surprisingly, we here show that one antibody, 4E6, which has low affinity for most forms of tau acutely improved cognition and reduced soluble phospho-tau, whereas another antibody, 6B2, which has high affinity for various tau species was ineffective. Concurrently, we confirmed and clarified these efficacy differences in an ex vivo model of tauopathy. Alzheimer's paired helical filaments (PHF) were toxic to the neurons and increased tau levels in remaining neurons. Both toxicity and tau seeding were prevented by 4E6 but not by 6B2. Furthermore, 4E6 reduced PHF spreading between neurons. Interestingly, 4E6's efficacy relates to its high affinity binding to solubilized PHF, whereas the ineffective 6B2 binds mainly to aggregated PHF. Blocking 4E6's uptake into neurons prevented its protective effects if the antibody was administered after PHF had been internalized. When 4E6 and PHF were administered at the same time, the antibody was protective extracellularly. CONCLUSIONS: Overall, these findings indicate that high antibody affinity for solubilized PHF predicts efficacy, and that acute antibody-mediated improvement in cognition relates to clearance of soluble phospho-tau. Importantly, both intra- and extracellular clearance pathways are in play. Together, these results have major implications for understanding the pathogenesis of tauopathies and for development of immunotherapies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".