Evidence map›Paper›PMID 41332834›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Genetic drivers of progression in Alzheimer's disease are distinct from disease risk.

Celeste E Cohen, Shane Fernandez, Umran Yaman, Ahmad R Ehyaei, Tenielle Porter, Eleanor O'Brien, Australian Imaging Biomarkers and Lifestyle Study, Alzheimer’s Disease Neuroimaging Initiative, Paul Maruff, John A Hardy and 3 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Celeste E CohenWellcome Sanger Institute, Cambridge, United Kingdom.
Shane FernandezCentre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.
Umran YamanUK Dementia Research Institute, University College London, London, United Kingdom.
Ahmad R EhyaeiMax-Planck-Institute for Intelligent Systems, Tubingen, Germany.
Tenielle PorterCentre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.
Eleanor O'BrienCentre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.
Australian Imaging Biomarkers and Lifestyle Study
Alzheimer’s Disease Neuroimaging Initiative
Paul MaruffFlorey Department of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
John A HardyUK Dementia Research Institute, University College London, London, United Kingdom.ORCID 0000-0002-3122-0423
Simon M LawsCentre for Precision Health, Edith Cowan University, Joondalup, Western Australia, Australia.
Dervis SalihDepartment of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom.ORCID 0000-0001-7651-8998
Maryam ShoaiUK Dementia Research Institute, University College London, London, United Kingdom.ORCID 0000-0003-2499-8533

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MICHAEL W WEINER · 2016 to 2026
$226.7M
NIA NIH HHS U19 AG024904
6 · The paper itself

Abstract

Background: Recent trials in Alzheimer's disease (AD) demonstrate encouraging outcomes. These trials target risk mechanisms identified through genetic analysis whilst directly aiming to reduce progression rates. Evidence from other neurodegenerative diseases suggests the genetics of progression is distinct from risk of disease. To expand these initial successes and improve clinical outcomes further we need to understand genetics of progression of disease. These can be deduced through rigorous analysis of meticulously phenotyped longitudinal cohorts. In this study we first looked at known genetic drivers of risk, namely polygenic risk scores for AD and Methods: A total of 387 individuals with, genetic data, amyloid positivity and in active decline (ADNI (n=222) and AIBL(n=165)) were used to perform generalised mixed effects linear model genome wide association studies of longitudinal cognitive decline as measured by mini mental state examination. The resulting summary statistics were subjected z, and colocalization analyses. Results: Established AD risk factors, including Conclusion: These findings enhance our understanding of the biological underpinnings of AD progression, opening new avenues for therapeutic intervention.

Indexed as

Alzheimer’s diseaseAPOE ε4Genome-wide association studiesPolygenic risk scoreProgression

Identifiers

PMID41332834
PMCPMC12668088

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.