Abstract

AbstractBackgroundThe Global Alzheimer’s Association Interactive Network (GAAIN) and the Critical Path for Alzheimer’s Disease (CPAD) Consortium have undertaken a collaborative effort to establish a mechanism that can help evaluate the relationship between fluid‐based, morphometric imaging biomarkers and clinical trajectories of disease progression, across datasets and analyses pipelines housed by CPAD and GAAIN. Additionally, this collaboration will demonstrate the feasibility of bidirectional integration of data management models and will guide development of a federated image analysis pipeline model across these two platforms.MethodTo enable interoperability, GAAIN’s original architecture is expanded to accommodate the LONI brain structural imaging pipeline. Under this new framework, GAAIN researchers can initiate brain imaging‐related analyses on their servers directly from GAAIN’s graphical interface with the results integrating back into GAAIN for further analyses. Feasibility was demonstrated for the determination of correlations for CPAD’s biomarker and imaging volumetric data. GAAIN’s brain imaging pipeline was executed on CPAD data, allowing for quantification of volumetric images. In turn, blood and volumetric data were inserted in GAAIN allowing further evaluation and analyses.ResultBased on the results, we provide guidelines for a future framework for a federated analysis model that can be utilized from GAAIN and CPAD to establish relationships between blood and brain markers. In this model, for a cohort of interest, analyses of relevant brain marker data can be remotely done in CPAD servers via GAAINs’ federated platform after which results can be inserted back to GAAIN alongside CPAD’s blood marker data. The full capabilities of this federated model will be explored in subsequent work.ConclusionAs data sharing becomes increasingly prominent and mature, the partnership between GAAIN and CPAD will yield ever greater benefits and knowledge and will continue to grow and evolve in response to the changing Alzheimer’s disease landscape. As such, it represents a non‐exclusive door for researchers to make use of the data sets and advanced analytical tools and is intended to leverage the unique competencies of these organizations and lead to the continued evolution of bringing meaningful and high‐impact advances in Alzheimer’s disease.

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