Rational design of a vaccine for Alzheimer’s disease using computationally-derived conformational B cell epitopes to selectively target toxic amyloid-beta oligomers (S26.004)
Bibliographic record
Abstract
Objective: Design an optimal amyloid-beta (Abeta) vaccine to elicit a robust and durable antibody response against toxic Abeta oligomers (ABO) without inducing potentially detrimental B or T cell responses against plaque or normal Abeta. Background: Abeta vaccines have the potential to protect against disease but also carry the risk of eliciting proinflammatory T cell responses causing meningoencephalitis, and plaque-reactive antibodies that can increase the risk of brain edema (ARIA-E). To circumvent these issues and induce an antibody response that selectively targets soluble toxic ABO, we designed a vaccine consisting of a computationally-derived conformational B cell epitope of ABO, coupled to KLH as a carrier protein to provide T cell help. Design/Methods: Mice received 3 immunizations, 4 weeks apart, with vaccine conjugate in alum or QS-21 as adjuvants. Serum titers and IgG subtypes of antibodies to the peptide epitope were measured by ELISA. The selectivity of serum antibodies for toxic ABO versus monomers or plaque was assessed by SPR and immunohistochemistry, respectively. T helper responses to the peptide and to KLH were evaluated by ELISPOT analysis of splenic lymphocytes. Results: A robust antibody response against the ABO epitope was observed with both adjuvants and was remarkably maintained unabated out to 6 months after the last immunization. The serum antibodies reacted with ABO only, not monomers or plaque. ELISPOT analysis showed T helper cytokine production in response to stimulation with KLH but not the ABO epitope thereby confirming that the peptide only contains a B cell epitope. Conclusions: A vaccine consisting of an ABO-restricted conformational B cell epitope conjugated to KLH produced a strong Abeta antibody response with no measurable pro-inflammatory T cell response against Abeta. In addition, the oligomer selectivity of the antibodies focused the response on pathogenic ABO, potentially reducing the risk of ARIA-E associated with binding to plaque and vascular deposits of Abeta. Disclosure: Dr. Kaplan has received personal compensation for serving as an employee of ProMIS Neurosciences. Dr. Kaplan has stock in ProMIS Neurosciences. Dr. Kaplan has received intellectual property interests from a discovery or technology relating to health care. The institution of Dr. Napper has received research support from Weston Family Foundation. Ms. Scruten has nothing to disclose. Dr. Gibbs has received personal compensation in the range of $50,000-$99,999 for serving as a Consultant for Promis Neuroscinces. Ms. Coutts has nothing to disclose. Dr. Cashman has received personal compensation for serving as an employee of ProMIS Neurosciences. Dr. Cashman has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Mitsubishi-Tanabe. Dr. Cashman has stock in ProMIS Neurosciences. The institution of Dr. Cashman has received research support from ProMIS Neurosciences. Dr. Cashman has received intellectual property interests from a discovery or technology relating to health care. Dr. Cashman has a non-compensated relationship as a BoD memeber with ALS Society of BC that is relevant to AAN interests or activities.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".