Evidence map›Paper›PMID 41451870›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025

Structural similarity networks reveal brain vulnerability in dementia.

Marcella Montagnese, Amir Ebneabbasi, Natalia García-San-Martín, Clara Pecci-Terroba, Rafael Romero-García, Sarah E Morgan, James H Cole, Jakob Seidlitz, Timothy Rittman, Richard A I Bethlehem

Abstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Structural similarity networks reveal brain vulnerability in dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Marcella MontagneseDepartment of Psychology, University of Cambridge, Cambridge, UK.ORCID 0000-0001-5467-0104
Amir EbneabbasiDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Natalia García-San-MartínDepartment of Medical Physiology and Biophysics, University of Seville, Sevilla, Spain.ORCID 0000-0002-2071-2289
Clara Pecci-TerrobaDepartment of Psychology, University of Cambridge, Cambridge, UK.
Rafael Romero-GarcíaDepartment of Medical Physiology and Biophysics, University of Seville, Sevilla, Spain.ORCID 0000-0002-5199-4573
Sarah E MorganSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.ORCID 0000-0002-1261-5884
James H ColeDepartment of Computer Science, Hawkes Institute, University College London, London, UK.ORCID 0000-0003-1908-5588
Jakob SeidlitzLifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-8164-7476
Timothy RittmanDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.ORCID 0000-0003-1063-6937
Richard A I BethlehemDepartment of Psychology, University of Cambridge, Cambridge, UK.ORCID 0000-0002-0714-0685

Funding

National Alzheimer's Coordinating CenterU24AG072122 · NIA · UNIVERSITY OF WASHINGTON · PI STEPHENS, KARI A · 2021 to 2025
$45.8M
Research Education ComponentP30AG062422 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Katherine P Rankin · 2019 to 2026
$36.9M
Research Education ComponentP30AG062421 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI BRADFORD C DICKERSON · 2019 to 2026
$36.5M
UCSD Shiley-Marcos Alzheimer's Disease Research Center P30P30AG062429 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DOUGLAS R GALASKO · 2019 to 2026
$34.9M
Wisconsin Alzheimer's Disease Research CenterP30AG062715 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Sanjay Asthana · 2019 to 2026
$34.5M
Research Education ComponentP30AG062677 · NIA · MAYO CLINIC ROCHESTER · PI KEJAL KANTARCI · 2019 to 2026
$33.5M
Research Education ComponentP30AG066514 · NIA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Margaret Sewell · 2020 to 2026
$31.0M
Yale Alzheimer Disease Research CenterP30AG066508 · NIA · YALE UNIVERSITY · PI STEPHEN M STRITTMATTER · 2020 to 2026
$30.2M
Research Education CoreP30AG066462 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PHILIP L DE JAGER · 2020 to 2026
$30.1M
Research Education ComponentP30AG066468 · NIA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI C. Elizabeth Shaaban · 2020 to 2026
$29.4M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
University of Washington Alzheimer's Disease Research CenterP30AG066509 · NIA · UNIVERSITY OF WASHINGTON · PI Amanda D. Boyd · 2020 to 2026
$29.0M
Academy of Medical Science Springboard AwardAlzheimer's Research UK East Network Centre ARUK-NC2021-EASTNIA NIH HHS P20 AG068082NIA NIH HHS P30 AG062421NIA NIH HHS P30 AG062422NIA NIH HHS P30 AG062429NIA NIH HHS P30 AG062677NIA NIH HHS P30 AG062715NIA NIH HHS P30 AG066444NIA NIH HHS P30 AG066462NIA NIH HHS P30 AG066468NIA NIH HHS P30 AG066506NIA NIH HHS P30 AG066507NIA NIH HHS P30 AG066508NIA NIH HHS P30 AG066509NIA NIH HHS P30 AG066511NIA NIH HHS P30 AG066512NIA NIH HHS P30 AG066514NIA NIH HHS P30 AG066515NIA NIH HHS P30 AG066518NIA NIH HHS P30 AG066519NIA NIH HHS P30 AG066530NIA NIH HHS P30 AG066546NIA NIH HHS P30 AG072931NIA NIH HHS P30 AG072946NIA NIH HHS P30 AG072947NIA NIH HHS P30 AG072958NIA NIH HHS P30 AG072959NIA NIH HHS P30 AG072972NIA NIH HHS P30 AG072973NIA NIH HHS P30 AG072975NIA NIH HHS P30 AG072976NIA NIH HHS P30 AG072977NIA NIH HHS P30 AG072978NIA NIH HHS P30 AG072979NIA NIH HHS P30 AG086401NIA NIH HHS P30 AG086404NIA NIH HHS R01 AG079280NIA NIH HHS U24 AG072122
6 · The paper itself

Abstract

introductionAlzheimer's disease (AD) is characterized by inter-individual heterogeneity in brain degeneration, limiting diagnostic and prognostic precision. We present a novel framework integrating Morphometric Inverse Divergence (MIND) networks with hierarchical Bayesian large-scale population modeling to identify individual-level neuroanatomical deviations.

methodsMIND networks quantify similarity between brain regions using multivariate magnetic resonance imaging (MRI) features. A normative model of regional MIND values trained on UK Biobank (N = 35,133) was applied to the National Alzheimer's Coordinating Center cohort (N = 3,567). We examined brain deviations across clinical stages, apolipoprotein E (APOE) genotypes, mortality risk, and neuropathological burden.

resultsNegative deviations (reduced MIND) stratified disease stages (p < 0.01) and were concentrated in specific functional networks in AD. Greater negative deviations characterized APOE ε4 homozygotes and correlated with post mortem neuropathological severity (p = 0.032). Spatially, deviation patterns were associated with maps of neurotransmitter receptor density. DISCUSSION: This population neuroimaging modeling enables individualized brain mapping with direct utility for diagnosis, prognosis, and understanding of biological mechanisms. HIGHLIGHTS: MIND networks were systematically integrated with normative modeling in AD. Negative deviations stratify clinical stages and correlate with neuropathology. Negative deviation count distinguishes APOE genotypes, highest in ε4 homozygotes. Deviations align with neurotransmitter maps. Individual brain maps enable precision medicine approaches in dementia.

Indexed as

Alzheimer DiseaseBrainDementiaNerve NetAgedAged, 80 and overApolipoprotein E4Apolipoproteins EBayes TheoremCohort StudiesFemaleHumansMagnetic Resonance ImagingMaleNeuroimagingApolipoprotein E4Apolipoproteins EAlzheimer's diseasebrain networksMorphometric Inverse Divergence (MIND) networksmorphometric similarityneurodegenerationneuropathologynormative modelingpersonalized medicinestructural magnetic resonance imaging

Identifiers

PMID41451870
PMCPMC12741943

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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.