In vivo imaging of alpha-synuclein with antibody-based PET
Bibliographic record
Abstract
The protein alpha-synuclein (αSYN) plays a central role in synucleinopathies such as Parkinsons's disease (PD) and multiple system atrophy (MSA). Presently, there are no selective αSYN positron emission tomography (PET) radioligands that do not also show affinity to amyloid-beta (Aβ). We have previously shown that radiolabeled antibodies, engineered to enter the brain via the transferrin receptor (TfR), is a promising approach for PET imaging of intrabrain targets. In this study, we used this strategy to visualize αSYN in the living mouse brain. Five bispecific antibodies, binding to both the murine TfR and αSYN were generated and radiolabeled with iodine-125 or iodine-124. All bispecific antibodies bound to αSYN and mTfR before and after radiolabelling in an ELISA assay, and bound to brain sections prepared from αSYN overexpressing mice as well as human PD- and MSA subjects, but not control tissues in autoradiography. Brain concentrations of the bispecific antibodies were between 26 and 63 times higher than the unmodified IgG format 2 h post-injection, corresponding to about 1.5% of the injected dose per gram brain tissue. Additionally, intrastriatal αSYN fibrils were visualized with PET in an αSYN deposition mouse model with one of the bispecific antibodies, [124I]RmAbSynO2-scFv8D3. However, PET images acquired in αSYN transgenic mice with verified brain pathology injected with [124I]RmAbSynO2-scFv8D3 and [124I]RmAb48-scFv8D3 showed no increase in antibody retention compared to WT mice. Despite successful imaging of deposited extracellular αSYN using a brain-penetrating antibody-based radioligand with no cross-specificity towards Aβ, this proof-of-concept study demonstrates challenges in imaging intracellular αSYN inclusions present in synucleinopathies.
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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) | 0.003 | 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".