Evidence map›Paper›PMID 37304174›Full record

ArticleFrontiers in neuroinformatics2023

The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI.

Arthur W Toga, Mukta Phatak, Ioannis Pappas, Simon Thompson, Caitlin P McHugh, Matthew H S Clement, Sarah Bauermeister, Tetsuyuki Maruyama, John Gallacher

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Advancing global dementia research through equity and inclusion.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. The informatics of ADNI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Review
  10. Review
  11. Article
  12. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Arthur W Toga *Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
Mukta Phatak *Alzheimer's Disease Data Initiative, Kirkland, WA, United States.
Ioannis PappasLaboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States.
Simon ThompsonDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
Caitlin P McHughAlzheimer's Disease Data Initiative, Kirkland, WA, United States.
Matthew H S ClementAlzheimer's Disease Data Initiative, Kirkland, WA, United States.
Sarah BauermeisterDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
Tetsuyuki MaruyamaAlzheimer's Disease Data Initiative, Kirkland, WA, United States.
John GallacherDepartment of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.

Funding

USCADRC Diversity Supplement PachicanoP30AG066530 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI HELENA Chang CHUI, ARTHUR W TOGA · 2020 to 2026
$27.8M
Medical Research Council MR/T033371/1NIA NIH HHS P30 AG066530
6 · The paper itself

Abstract

There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field: Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.

Indexed as

Alzheimer’s disease and neurodegenerationdata sharingdementia–Alzheimer’s diseasefederated data accessremote data

Identifiers

PMID37304174
PMCPMC10248126

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.