ANMerge: A comprehensive and accessible Alzheimer's disease patient-level dataset
ANMerge: A comprehensive and accessible Alzheimer's disease patient-level dataset
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ANMerge：全面且可访问的阿尔茨海默病患者级数据集
DOI：
10.1101/2020.08.04.20168229
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Birkenbihl C
中科院分区：
文献类型：
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作者：
Birkenbihl C
背景可访问的数据集对于阿尔茨海默病（AD）研究的发展至关重要。AddNeuroMed联盟进行了一项纵向观察性队列研究，旨在发现AD生物标志物。在本研究期间，测量了广泛的数据模式选择，包括临床评估、磁共振成像、基因分型、转录组学分析和血浆蛋白质组学。一些收集的数据与第三方研究人员共享。然而，这些数据是不完整的，错误的，缺乏互操作性。ObjectiveTo提供一个可访问的，多模态的，患者级AD队列dataset.MethodsWe系统地解决了几个限制的原始共享资源，并提供额外的未发布的数据，以提高dataset.ResultsIn这项工作，我们发布和描述ANMerge，一个新版本的AddNeuroMed数据集。ANMerge包括来自1,702名研究参与者的多模态数据，研究社区可以通过一个集中的portal.ConclusionANMerge是一个信息丰富的患者级数据资源，可以作为一个发现和验证队列数据驱动的AD研究，例如，机器学习和人工智能的方法。
BackgroundAccessible 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.ObjectiveTo provide the research community with an accessible, multimodal, patient-level AD cohort dataset.MethodsWe systematically addressed several limitations of the originally shared resources and provided additional unreleased data to enhance the dataset.ResultsIn this work, we publish and describe ANMerge, a new version of the AddNeuroMed dataset. ANMerge includes multimodal data from 1,702 study participants and is accessible to the research community via a centralized portal.ConclusionANMerge 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.