Relationship Between Therapeutic Activity and Preferential Targeting of Toxic Soluble Aggregates by Amyloid-Beta-Directed Antibodies
Bibliographic record
Abstract
ABSTRACT Background Amyloid-beta (Aβ)-directed antibodies tested clinically for therapeutic activity against Alzheimer’s disease (AD) have shown varying degrees of efficacy. Although all of these antibodies target the Aβ peptide, their binding profile to different molecular species of Aβ differs and may underlie the observed variability in clinical outcomes. Objective Explore the relationship between targeting of soluble toxic Aβ species and therapeutic efficacy. Methods Surface plasmon resonance (SPR) was used to conduct a side-by-side comparison of the binding of various Aβ-directed antibodies to monomers and soluble Aβ oligomers from AD brains. Immunohistochemistry was performed to assess reactivity with plaque. Preclinical activity was assessed in human amyloid precursor protein (APP) transgenic mouse models of AD. Results Non-selective, pan-Aβ reactive antibodies such as crenezumab and gantenerumab, which have failed to produce a clinical benefit, bound all forms of Aβ tested. In a competition assay, these antibodies lost the ability to bind toxic AD brain oligomers when exposed to monomers. Aggregate-selective antibodies such as aducanumab, lecanemab and donanemab, showed reduced monomer binding and a greater ability to withstand monomer competition which correlated with their reported inhibition of cognitive decline. Of the antibodies in earlier stages of clinical testing, ACU193 and PMN310 displayed the greatest ability to retain binding to toxic AD brain oligomers while PRX h2731 was highly susceptible to monomer competition. Plaque binding was observed with all aggregate-reactive antibodies with the exception of PMN310, which was strictly selective for soluble oligomers. Targeting of oligomers by PMN310 protected cognition and was not associated with microhemorrhages in mouse models of AD. Conclusions Overall, these results suggest that selectivity for soluble toxic Aβ oligomers may be a driver of clinical efficacy, with a potentially reduced risk of ARIA if engagement with plaque is minimized.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".