Evidence map›Paper›PMID 38471053›Full record

ArticleNeurology2024

Identification of Distinct Brain MRI Phenotypes and Their Association With Long-Term Dementia Risk in Community-Dwelling Older Adults.

Jasmin Annica Keller, Sigurdur Sigurdsson, Bárbara Schmitz Abecassis, Ilse M J Kant, Mark A Van Buchem, Lenore J Launer, Matthias J P van Osch, Vilmundur Gudnason, Jeroen de Bresser

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In one paragraph

Article in Neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% of its field
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 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Healthy Behavior for Preventing Cognitive Disability in Older Persons.International journal of environmental research and public health · 2025
    Review
  3. Article
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 at 1 institution in 3 countries.

Jasmin Annica KellerFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.ORCID 0000-0001-7075-7525
Sigurdur SigurdssonFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
Bárbara Schmitz AbecassisFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
Ilse M J KantFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
Mark A Van BuchemFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
Lenore J LaunerFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.ORCID 0000-0002-3238-7612
Matthias J P van OschFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
Vilmundur GudnasonFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.ORCID 0000-0001-5696-0084
Jeroen de BresserFrom the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik.
University of Iceland · IS

Funding

Brain aging and cardiovascular risk factors and diseaseZIAAG007480 · NIA · NATIONAL INSTITUTE ON AGING · PI LAUNER, LENORE J · 2011 to 2025
$2.7M
6 · The paper itself

Abstract

BACKGROUND AND

objectivesIndividual brain MRI markers only show at best a modest association with long-term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We aimed to identify different brain MRI phenotypes by hierarchical clustering analysis based on combined neurovascular and neurodegenerative brain MRI markers and to determine the long-term dementia risk within the brain MRI phenotype subgroups.

methodsHierarchical clustering analysis based on 32 combined neurovascular and neurodegenerative brain MRI markers in community-dwelling individuals of the Age-Gene/Environment Susceptibility Reykjavik Study was applied to identify brain MRI phenotypes. A Cox proportional hazards regression model was used to determine the long-term risk for dementia per subgroup.

resultsWe included 3,056 participants and identified 15 subgroups with distinct brain MRI phenotypes. The phenotypes ranged from limited burden, mostly irregular white matter hyperintensity (WMH) shape and cerebral atrophy, mostly irregularly WMHs and microbleeds, mostly cortical infarcts and atrophy, mostly irregularly shaped WMH and cerebral atrophy to multiburden subgroups. Each subgroup showed different long-term risks for dementia (min-max range hazard ratios [HRs] 1.01-6.18; mean time to follow-up 9.9 ± 2.6 years); especially the brain MRI phenotype with mainly WMHs and atrophy showed a large increased risk (HR 6.18, 95% CI 3.37-11.32). DISCUSSION: Distinct brain MRI phenotypes can be identified in community-dwelling older adults. Our results indicate that distinct brain MRI phenotypes are related to varying long-term risks of developing dementia. Brain MRI phenotypes may in the future assist in an improved understanding of the structural correlates of dementia predisposition.

Indexed as

DementiaWhite MatterAgedAtrophyBrainHumansIndependent LivingMagnetic Resonance ImagingPhenotype

Identifiers

PMID38471053
PMCPMC11033985
OpenAlexW4392691652

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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.