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Amyloid imaging to Prevent Alzheimer’s Disease – Sofia ref.: 115952

Periodic Reporting for period 6 - AMYPAD (Amyloid imaging to Prevent Alzheimer’s Disease – Sofia ref.: 115952)

Berichtszeitraum: 2021-10-01 bis 2022-09-30

AMYPAD aims to determine the value of β-amyloid imaging as a diagnostic and therapeutic marker for Alzheimer’s disease (AD) (amypad.eu). After 6 years, the project has achieved its objectives, which are described hereinafter. The first goal is to gain better understanding of the impact of amyloid-PET imaging utilization on diagnostic thinking and patient management (DPMS), by determining its value regarding diagnostic confidence, decision trees, change in diagnosis, patient management, and healthcare resource utilization. This milestone was achieved, and results can be checked following this link (https://pubmed.ncbi.nlm.nih.gov/35715930/). Also, the DPMS is the largest European study implementing amyloid-PET in clinical practice. The second goal is to better understand the natural history of AD in its preclinical and prodromal stages (PNHS). To achieved this goal, AMYPAD established a pan-European collaboration with cohorts to study the earliest stages of AD in a longitudinal and multi-modal fashion. Also, it provided longitudinal data for over 1600 unique subjects from over a total of 11 parent cohorts. And finally, the PNHS succeeded in prospectively recruiting 1,321 participants by the end of the project. This data is accessible through this link (https://portal.addi.ad-datainitiative.org/) and on the AMYPAD website (https://amypad.eu/news/recent-news/amypad-announces-last-patient-out-in-its-prognostic-study/). Lastly, the third goal is to support current and future trials in the selection of subjects for proof-of-concept studies aiming at preventing AD, by ensuring more targeted enrolment and providing alternative measures of treatment effect. As a result, AMYPAD established robust measures of amyloid accumulation and predictors of cognitive decline to help in the planning and monitoring of treatment.
Overall, AMYPAD developed key assets such as: the NiftyPET, NiftyPAD, AmyPET, the ADDI workbench, and XNAT. Also, the project was able to promote the engagement and interaction with regulatory bodies (EMA, NICE, and FDA), with projects and external initiatives (e.g. EPAD, NEURONET, and IDEAS), and showcased its results at different scientific conferences, such as AEC, HAI, EANM, CTAD, NRM, AD/PD, SNMMI, EAN, and AAIC. In total, 62 posters and 56 talks were presented, and 38 papers have been published. All these goals could only be achieved through our pan-European collaborative framework we established over the IMI running period. The paper https://www.frontiersin.org/articles/10.3389/fneur.2022.1063598/full is a full description of the consortium collaborations.
Currently, the AMYPAD DPMS is the largest European study implementing amyloid-PET in clinical practice. A total of 844 patients were randomized out of 900 originally planned. The study recruited 245 people with Subjective Cognitive Decline, 342 with Mild Cognitive Impairment and 258 with dementia. Similarly, significant work has been put into finalizing the PNHS by the engagement of additional sites and Parent Cohorts. By October 2022, 1,419 participants were prospectively recruited. This study has involved collaborations among 8 European countries, 17 sites, and 11 parent cohorts: EPAD LCS, EMIF-AD (60++ and 90+), ALFA+, FACEHBI, FPACK, UCL 2010-412, Microbiota, AMYPAD DPMS (VUMC), H70, and Delcode. Consequently, longitudinal, integrated, and harmonized data of more than 1600 unique subjects is available through the ADDI workbench.
In parallel, technical and operational aspects have been established and optimized. Some critical aspects are the harmonization of data across radiotracers and scanners at the different sites, their qualifications, and the optimization of data accuracy for high-quality standard of results. From the previous period, a dedicated team developed pipelines for the harmonization of PET quantification to ensure robust and valid findings. In addition, a strong focus has been put into developing open-source imaging processing pipelines, which already have been and will be provided to the community.
For the post-IMI period several, actions have been taken on dissemination and exploitation of results:
- The research network and expert knowledge gathered from the Consortium will continue with monthly scientific meetings among WP2, WP3, WP4, and WP5.
- AMYPAD governance is working in an ‘Aims and Rules’ document that provides an overall guidance and exploitation of AMYPAD assets including datasets, software’s, knowledge base, scientific collaboration, and network.
- The standardized PET methodology software’s are open-access available on Github.
- Dataset (harmonized data, cognitive domains, scans, etc) will be maintained. Thanks to a 5-year partnership between the AMYPAD consortium and ADDI, the PNHS dataset will become available to the research community beyond the project duration, with the first public release planned by the end of Q1 2023.
- Integration and enhancement of PNHS dataset. Additional cohorts and biomarkers/variables readily available in the current parent cohorts will be integrated to enhance the value of the data-set for disease modelling effort.
The regulatory approval of amyloid-PET tracers for clinical use and their increasing implementation illustrates its relevance as a non-invasive tool to study one of the key molecules associated with the development of AD. For the clinical routine, reimbursement of amyloid PET is lagging due to the absence of definitive evidence on its clinical utility and cost-effectiveness. Consequently, it has not been reimbursed in any major market, limiting its clinical use. AMYPAD has performed amyloid-PET scans on an unprecedented scale across the AD continuum and with a focus on the early stages of AD. Data collected determine the clinical added value in diagnosis and patient monitoring. Novel elements of AMYPAD include longitudinal imaging in ~50% of subjects and quantitative analyses by performing dynamic scans in a large subset of participants. It is differentiated from other initiatives both by its large scale, and by focusing on subjects with very early stages of AD. In doing so, it will also bridge a gap between US and Australian initiatives that study either healthy aging (A4 and AIBL) or focus on more established disease stages (ADNI and IDEAS), often in elderly subjects. Overall, key AMYPAD results are: Prognostic Study integrated dataset (https://fair.addi.ad-datainitiative.org/) Diagnostic Study dataset which is stored on an archive portal Yareta (https://yareta.unige.ch/home/detail/7825f61b-6f8e-4fc2-a9df-cadfbc84d2b2) the Image Database (PET/MRI), and different software and pipelines (https://niftypet.readthedocs.io/en/latest/ https://pubmed.ncbi.nlm.nih.gov/36622500/ and https://github.com/AMYPAD/AmyPET).
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