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<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Accessible datasets are of fundamental importance to the advancement of Alzheimer’s disease (AD) research. The AddNeuroMed consortium conducted a longitudinal observational cohort study with the aim to discover AD biomarkers. During this study, a broad selection of data modalities was measured including clinical assessments, magnetic resonance imaging, genotyping, transcriptomic profiling and blood plasma proteomics. Some of the collected data were shared with third-party researchers. However, this data was incomplete, erroneous and lacking in interoperability.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We systematically addressed several limitations of the originally shared data and provide additional unreleased data to enhance the patient-level dataset.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In this work, we publish and describe ANMerge, a new version of the AddNeuroMed dataset. ANMerge includes multimodal data from 1702 study participants and is accessible to the research community via a centralized portal.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>ANMerge is an information rich patient-level data resource that can serve as a discovery and validation cohort for data-driven AD research, such as for example machine learning and artificial intelligence approaches.</jats:p><jats:p>ANMerge can be downloaded here: <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://doi.org/10.7303/syn22252881">https://doi.org/10.7303/syn22252881</jats:ext-link></jats:p></jats:sec>

Original publication

DOI

10.1101/2020.08.04.20168229

Type

Journal article

Publisher

Cold Spring Harbor Laboratory

Publication Date

06/08/2020