Global Alzheimer's Association Interactive Network

---

The Global Alzheimer’s Association Interactive Network (GAAIN) is a federated data sharing platform that connects researchers around the world with Alzheimer’s data providers. The platform allows Alzheimer’s and dementia researchers to discover data, run preliminary analyses and form collaborations with other research groups.

History

GAAIN was launched in 2013 with funding from the Alzheimer’s Association. Beginning in September 2013, GAAIN began building the network's infrastructure, recruiting Data Partners and building its public presence. The included installing new server machines at the Laboratory of Neuro Imaging (LONI) data center to host the GAAIN data website and developing the Data Partner Client (DPC), a lightweight software client that connects each Data Partner to the GAAIN system.

In February 2015, two user interfaces were launched: the GAAIN Scoreboard, a public interface that enables cohort discovery and provides subject counts of available data, and the GAAIN Interrogator, a search interface used to visually compare user-defined groups of subject data across studies. The GAAIN Analysis Tool was also developed to support these interfaces, allowing researchers to virtually share analyses with Data Partner sites and makes analysis results from each Data Partner publicly available via the GAAIN search.

In 2017, the GAAIN 3 platform was developed. The new Interrogator interface allows users to perform preliminary analyses—including finding variables of interest and investigating their questions—without accessing the data directly. They can later connect directly with data partners to access full datasets for research purposes. The Cohort Scout, which searches across about 30,000 attributes, was also introduced in 2017.

GAAIN 3 differs from earlier versions in that users can explore attributes and run preliminary analyses. Previous versions limited searches to 24 attributes; the new version allows searchers of all subject-level data shared by partners.

GAAIN attends the Alzheimer’s Association International Conference (AAIC) each year to connect with researchers, clinicians and members of the care community for a global forum aimed at advancing dementia science.

Architecture

Each partner runs a local client (DPC), an executable Java jar file, that responds to data requests from GAAIN servers. Each DPC has an ON/OFF switch that will either securely connect the DPC to the GAAIN network or remove the partner and their data.

Datasets (participant demographics, clinical, imaging values, neurobattery test scores, family history etc.) are added to the GAAIN network using one or more comma-separated value (CSV) files. With the GAAIN 3 platform, any number or type of attributes that can be held in a CSV file are supported-some Data Partners share thousands of attributes. The CSV files are read into the DPC. The DPC will fulfill requests from the GAAIN server when researchers use GAAIN’s tools. GAAIN caches the data in its server memory so that it can fulfill GAAIN investigator search requests more quickly and never copies any data to disk drives. These caches are limited to the memory capacity of GAAIN computers and are temporary.

The new Interrogator interfaces with the GAAIN 3 platform and so that investigators can pool data sets from different partners together and to conduct preliminary analyses on those data sets. Data is explored, queried, harmonized, and visualized and cohorts are created in a drag-and-drop environment. GAAIN 3 supports the following analyses: logistic regression, Mantel-Haenszel meta-analysis, Cox proportional hazard regression, and linear regression. Users can work with data from partners, but analyses should not be used for publication. Direct collaboration with the Data Partner is required to obtain the raw data needed to run an in-depth analysis.

Funding

GAAIN is funded by the Alzheimer’s Association. In partnership with the Laboratory of Neuro Imaging (LONI) at USC and the National Center for Alzheimer’s Disease Research and Care in Geneva, the Alzheimer’s Association provided the support to launch GAAIN.

The NIH Big Data to Knowledge (BD2K) grant (Award Number U54EB020406) also contributed funding to help build the computational infrastructure behind the GAAIN Platform.

Leadership

Board of Governors

• Arthur W. Toga, PhD
• Maria C. Carrillo, PhD
• Giovanni B. Frisoni, MD
• William H. Thies, PhD

Scientific Advisory Board

• Paul Aisen, MD
• Heather Snyder, PhD
• Enrique Castro-Leon, PhD
• Alon Halevy, PhD
• William Klunk, MD
• Brady Davis
• Neil Buckholtz, PhD
• Rhett Alden, PhD

GAAIN Personnel

• Scott Neu, PhD
• Jyl Boline, PhD
• Karen Crawford

Partners

The goal of GAAIN is to unite Alzheimer’s research leaders from around the world to accelerate the pace of discovery in the field. GAAIN partners maintain control of their data at all times and are credited with their logo and link on all of GAAIN’s interfaces. GAAIN does not interfere with data tracking or user authorization processes.

GAAIN’s partners are around the world in North America, Europe, Asia and Australia.

• Alzheimer’s Disease Neuroimaging Initiative (ADNI)
• AddNeuroMed
• The Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageine (AIBL)
• Alzheimer’s Disease Repository Without Borders (ARWIBO)
• Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD)
• French National Alzheimer’s Database (BNA)
• The Brain Health Registry (BHR)
• Canadian Longitudinal Study on Aging (CLSA)
• Coalition Against Major Diseases (CAMD)
• Center for Neurodegenerative Disease Research (CNDR)
• Dementia and Aging Research of Taiwan (DART)
• Development of Screening Guidelines and Criteria for Predementia Alzheimer’s Disease (DESCRIPA)
• Dominantly Inherited Alzheimer Network (DIAN)
• Dominantly Inherited Alzheimer Network Trials Unit (DIAN TU)
• European Alzheimer’s Disease Neuroimaging Initiative (E-ADNI or PharmaCog)
• European Diffusion Tensor Imaging Study in Dementia (EDSD)
• Fundacio ACE: Institut Catala de Neurociencies Aplicades (F ACE)
• The Framingham Heart Study (FHS)
• Hellenic Longitudinal Investigation of Aging and Diet (HELIAD)
• Health and Retirement Study (HRS
• Italian Alzheimer’s Disease Neuroimaging Initiative (I-ADNI)
• Integrative Neurodegenerative Disease Databases
• Korean Longitudinal Study on Cognitive Aging and Dementia
• Layton Aging and Alzheimer’s Disease Center (LAADC)
• Laboratory of Magnetic Resonance Research
• Laboratory of Neuro Imaging (LONI)
• National Alzheimer’s Coordinating Center (NACC)
• National Cell Repository for Alzheimer’s Disease (NCRAD)
• neuGRID for You (N4U
• The National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS)
• Open Access Series of Imaging Studies (OASIS)
• The Personality and Total Health (PATH) Through Life Project
• Quantitative Imaging Biomarker Alliance (QIBA)
• Sydney Memory & Ageing Study
• Vienna Transdanube Aging Study
• Wisconsin Longitudinal Study (WLS)
• White Matter Hyperintensities in Alzheimer’s Disease (WMH-AD)
• Wisconsin Registry for Alzheimer’s Prevention (WRAP)

Publications

In August 2017, GAAIN published the largest study of APOE with nearly 58,000 subjects from the platform's Data Partners. The study demonstrated that men and women with the APOE ε3/ε4 genotype have nearly the same odds of developing AD across the age span of 55 to 85 years, but women have an increased risk during the decade between 65 and 75 years old. The research counters previous research findings, which suggested that women were more vulnerable at all ages, and demonstrates the impact of a large sample size in a retrospective study.

The following publications have been fueled by GAAIN data.

• Ashish, N., Dewan, P., & Toga, A. W. (2015). The GAAIN Entity Mapper: An Active-Learning System for Medical Data Mapping. Frontiers in Neuroinformatics, 9, 30.
• Toga, A. W., Bhatt, P., & Ashish, N. (2016). Global data sharing in Alzheimer’s disease research. Alzheimer Disease and Associated Disorders, 30(2), 160–168.
• Toga, A. W., Neu, S. C., Bhatt, P., Crawford, K. L., & Ashish, N. (2016). The Global Alzheimer’s Association Interactive Network. Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 12(1), 49–54.
• Ashish, N., & Toga, A. W. (2015). Medical data transformation using rewriting. Frontiers in Neuroinformatics, 9, 1.
• Ashish, N., Dewan, P., Ambite, J.-L., & Toga, A. W. (2015). GEM: The GAAIN Entity Mapper. Data Integration in the Life Sciences : … International Workshop, DILS … : Proceedings. DILS (Conference), 9162, 13–27.
• Neu, S. C., Crawford, K. L., & Toga, A. W. (2016). Sharing Data In The Global Alzheimer’s Association Interactive Network. NeuroImage, 124(0 0), 1168–1174.
• Neu S.C., Pa J., Kukull W., Beekly D., Kuzma A., Gangadharan P., Wang L., Romero K., Arneric S.P., Redolfi A., Orlandi D., Frisoni G.B., Au R., Devine S., Auerbach S., Espinosa A., Boada M., Ruiz A., Johnson S.C., Koscik R., Wang J., Hsu W., Chen Y., & Toga A.W (2017). Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease. JAMA Neurol. Published online August 28, 2017. 

References

This article "Global Alzheimer's Association Interactive Network" is from Wikipedia. The list of its authors can be seen in its historical and/or the page Edithistory:Global Alzheimer's Association Interactive Network. Articles copied from Draft Namespace on Wikipedia could be seen on the Draft Namespace of Wikipedia and not main one.

---