Evidence map›Paper›PMID 42271180›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2026

Alzheimer's disease biological domain sub-stratification enhances the precision of functional analyses.

Gregory A Cary, Sai Sruthi Amirtha Ganesh, Laura Heath, Karina Leal, Martin Kampmann, Frank M Longo, Robert R Butler, Allan L Levey, Gregory W Carter, Jesse Wiley

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Gregory A CaryThe Jackson Laboratory, Bar Harbor, Maine, USA.ORCID https://orcid.org/0000-0003-3573-5229
Sai Sruthi Amirtha GaneshUniversity of Kansas, Lawrence, Kansas, USA.
Laura HeathSage Bionetworks, Seattle, Washington, USA.
Karina LealSage Bionetworks, Seattle, Washington, USA.
Martin KampmannUniversity of California San Francisco, San Francisco, California, USA.
Frank M LongoStanford University Medical School, Stanford, California, USA.
Robert R ButlerStanford University Medical School, Stanford, California, USA.
Allan L LeveyEmory University Medical School, Atlanta, Georgia, USA.
Gregory W CarterThe Jackson Laboratory, Bar Harbor, Maine, USA.ORCID https://orcid.org/0000-0002-2834-8186
Jesse WileyUniversity of Kansas, Lawrence, Kansas, USA.

Funding

TREAT AD Structural Biology CoreU54AG065187 · NIA · EMORY UNIVERSITY · PI Gregory W Carter, ALLAN I LEVEY · 2019 to 2026
$69.7M
NIA NIH HHS U54AG065187
6 · The paper itself

Abstract

introductionThe Target Enablement to Accelerate Therapy Development for AD (TREAT-AD) bioinformatics pipeline employs a rank-and-organize strategy. Disease-associated genes drive enrichment of large AD-linked endophenotypes. However, these biological areas were too large to promote hypothesis development or target identification. Here we delineate subdomains that map to, and enrich, specific biological processes.

methodsTo refine the biodomains into more focused areas, we built κ networks out of the Gene Ontology terms in the biodomain and employ shared gene annotation between terms to determine edge weights. κ-value filtration enabled us to identify data-driven subdomains, which we employed in an analysis of TREAT-AD harmonized datasets.

resultsThe subdomain enrichment highlights core areas of biological impairment within the biodomain space and facilitates a deeper interpretation of large-scale multiomic datasets. DISCUSSION: The subdomain mapping of AD-risk-associated processes may facilitate an open-source, open-science shareable resource for the comparison of large datasets for the formulation of future hypotheses and identification of therapeutic targets.

Indexed as

Alzheimer DiseaseComputational BiologyGene OntologyHumansMultiomicsAlzheimer's diseasebiodomainGene Ontologyproteomicspseudotimesubdomain

Identifiers

PMID42271180
PMCPMC13253357

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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.