Evidence map›Paper›PMID 40769858›Full record

ArticleThe journal of prevention of Alzheimer's disease2025

Medical risk factors, ApoE haplotype, and Alzheimer's disease: a large-scale analysis.

Uri Elias, Lidor Gazit, Roei Zucker, Amos Stern, Michal Linial, Gilles Allali, Tamir Ben-Hur, Gad A Marshall, Shahar Arzy

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In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Uri EliasComputational Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
Lidor GazitComputational Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
Roei ZuckerThe Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Amos SternThe Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Michal LinialDepartment of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Gilles AllaliLeenaards Memory Center, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.. Electronic address: gilles.Allali@chuv.ch.
Tamir Ben-HurDepartment of Neurology, Hadassah Medical Center, Jerusalem, Israel.
Gad A MarshallCenter for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Shahar ArzyComputational Neuropsychiatry Lab, Department of Medical Neurosciences, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Neurology, Hadassah Medical Center, Jerusalem, Israel; Department of Brain and Cognition, Hebrew University of Jerusalem, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe multifactorial nature of Alzheimer's disease (AD) has become increasingly evident. In addition to well-established features like neurodegeneration, amyloid-beta and tau deposition, or glial changes, other processes-such as metabolic, circulatory, and inflammatory factors-may also play a key role in driving or accelerating AD-related pathology and cognitive decline. These factors represent important targets for slowing disease progression.

objectivesAlthough many studies have examined individual risk factors and meta-analyses have been performed, a large-scale, comprehensive comparison using formal medical data from a single, unified cohort is needed.

designA retrospective case-control study leveraging comprehensive health database.

settingData were obtained from the UK-Biobank, a large (∼500 K people) population-based biomedical database in the United Kingdom.

participantsThe study included participants aged 40-69 at enrollment between 2006 and 2010, comprising 3,843 individuals who were clinically diagnosed with AD by August 2022 and 387,275 individuals without dementia or cognitive-impairment diagnoses. MEASUREMENTS: ICD-10-coded diagnoses, recorded at least 10 years prior to AD diagnosis, were analyzed. Logistic regression was used to estimate the impact and significance of various medical conditions and their interactions with genetic risk factors, while accounting for demographic determinants.

resultsThe analysis identified 45 medical factors (96 ICD-10 entities) across multiple systems-particularly metabolic, circulatory, gastrointestinal, and sensorimotor-that significantly differentiated individuals with clinical AD from cognitively unimpaired individuals. Interaction analyses revealed that circulatory and metabolic factors had a weaker influence on AD risk in Apolipoprotein E ε4 carriers, suggesting a gene-environment interaction in disease susceptibility.

conclusionsThese findings enhance the understanding of system-level risk factors for clinical AD, highlight the relevance of less frequently reported factors in the AD prevention literature-such as gastrointestinal and sensorimotor disorders-and underscore the complex interplay between genetic susceptibility and vascular risk factors.

Indexed as

Alzheimer DiseaseApolipoproteins EHaplotypesAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsUnited KingdomApoE protein, humanApolipoproteins EApoEBig-dataInterventionModifiable risk factorsPreclinicalUK-biobank

Identifiers

PMID40769858
PMCPMC12501343

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Registered trials

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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.