The Alzheimer's disease 5xFAD mouse model is best suited to investigate pretargeted imaging approaches beyond the blood-brain barrier

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Alzheimer's disease (AD) is the most common neurodegenerative disease, with an increasing prevalence. Currently, there is no ideal diagnostic molecular imaging agent for diagnosing AD. Antibodies (Abs) have been proposed to close this gap as they can bind selectively and with high affinity to amyloid β (Aβ)—one of the molecular hallmarks of AD. Abs can even be designed to selectively bind Aβ oligomers or isoforms, which are difficult to target with small imaging agents. Conventionally, Abs must be labeled with long-lived radionuclides which typically results in in high radiation burden to healthy tissue. Pretargeted imaging could solve this challenge as it allows for the use of short-lived radionuclides. To develop pretargeted imaging tools that can enter the brain, AD mouse models are useful as they allow testing of the imaging approach in a relevant animal model that could predict its clinical applicability. Several mouse models for AD have been developed with different characteristics. Commonly used models are: 5xFAD, APP/PS1 and tg-ArcSwe transgenic mice. In this study, we aimed to identify which of these models were best suited to investigate pretargeted imaging approaches beyond the blood brain barrier. We evaluated this by pretargeted autoradiography using the Aβ-targeting antibody 3D6 and an 111In-labeled Tz. Evaluation criteria were target-to-background ratios and accessibility. APP/PS1 mice showed Aβ accumulation in high and low binding brain regions and is as such less suitable for pretargeted purposes. 5xFAD and tg-ArcSwe mice showed similar uptake in high binding regions whereas low uptake in low binding regions and are better suited to evaluate pretargeted imaging approaches. 5xFAD mice are advantaged over tg-ArcSwe mice as pathology can be traced early (6 months compared to 18 months of age) and as 5xFAD mice are commercially available
Original languageEnglish
Article number1001722
JournalFrontiers in Nuclear Medicine
Volume2
Number of pages7
DOIs
Publication statusPublished - 2023

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