Evidence map›Paper›PMID 39368996›Full record

ArticleTranslational psychiatry2024

Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum.

Junhao Wen, Zhijian Yang, Ilya M Nasrallah, Yuhan Cui, Guray Erus, Dhivya Srinivasan, Ahmed Abdulkadir, Elizabeth Mamourian, Gyujoon Hwang, Ashish Singh and 40 more

Abstract read
In one paragraph

Article in Translational psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  7. Sleep chart of biological aging clocks across organs and omics.medRxiv : the preprint server for health sciences · 2025
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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

50 authors.

Junhao WenLaboratory of AI and Biomedical Science (LABS), University of Southern California, Los Angeles, CA, USA. Junhao.wen89@gmail.com.ORCID 0000-0003-2077-3070
Zhijian YangArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ilya M NasrallahArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0003-2346-7562
Yuhan CuiArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Guray ErusArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.ORCID 0000-0001-6633-4861
Dhivya SrinivasanArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ahmed AbdulkadirArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Elizabeth MamourianArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Gyujoon HwangArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Ashish SinghArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Mark BergmanArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Jingxuan BaoDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0001-7127-3258
Erdem VarolDepartment of Statistics, Center for Theoretical Neuroscience, Zuckerman Institute, Columbia University, New York, NY, USA.
Zhen ZhouArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Aleix Boquet-PujadasLaboratory of AI and Biomedical Science (LABS), University of Southern California, Los Angeles, CA, USA.
Jiong ChenArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Arthur W TogaLaboratory of NeuroImaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
Andrew J SaykinRadiology and Imaging Sciences, Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana Alzheimer's Disease Research Center and the Melvin and Bren Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, USA.ORCID 0000-0002-1376-8532
Timothy J HohmanVanderbilt Memory and Alzheimer's Center, Vanderbilt Genetics Institute, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-3377-7014
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA.
Sylvia VilleneuveDouglas Mental Health University Institute, McGill University, Montréal, QC, Canada.
Randy GollubAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.ORCID 0000-0002-9434-4044
Aristeidis SotirasDepartment of Radiology and Institute for Informatics, Washington University School of Medicine, St. Louis, MO, USA.ORCID 0000-0003-0795-8820
Katharina WittfeldDepartment of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.ORCID 0000-0003-4383-5043
Hans J GrabeDepartment of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
Duygu TosunDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.ORCID 0000-0001-8644-7724
Murat BilgelLaboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, USA.ORCID 0000-0001-5042-7422
Yang AnLaboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, USA.
Daniel S MarcusDepartment of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
Pamela LaMontagneDepartment of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
Tammie L BenzingerDepartment of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
Susan R HeckbertCardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA.
Thomas R AustinCardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, USA.
Lenore J LaunerNeuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA.ORCID 0000-0002-3238-7612
Mark EspelandSticht Center for Healthy Aging and Alzheimer's Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Colin L MastersFlorey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia.
Paul MaruffFlorey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia.
Jurgen FrippCSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, QLD, Australia.
Sterling C JohnsonWisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.ORCID 0000-0002-8501-545X
John C MorrisKnight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.
Marilyn S AlbertDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
R Nick BryanDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Susan M ResnickLaboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, USA.ORCID 0000-0003-1115-7145
Luigi FerrucciTranslational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 S. Hanover Street, Baltimore, MD, 21225, USA.ORCID 0000-0002-6273-1613
Yong FanArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Mohamad HabesGlenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.ORCID 0000-0001-9447-5805
David WolkArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Li ShenDepartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.ORCID 0000-0002-5443-0503
Haochang ShouArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Christos DavatzikosArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Christos.Davatzikos@pennmedicine.upenn.edu.ORCID 0000-0002-1025-8561

Funding

USCADRC Diversity Supplement PachicanoP30AG066530 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Hussein N Yassine · 2020 to 2026
$27.8M
South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Sudha Seshadri · 2021 to 2026
$24.0M
Machine Learning and Large-scale Imaging analytics for dimensional representations of brain trajectories in aging and preclinical Alzheimer's Disease: The brain aging chart and the iSTAGING consortiumRF1AG054409 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVATZIKOS, CHRISTOS · 2017 to 2023
$6.3M
Cerebral tau deposition and comorbid cerebrovascular disease across the Alzheimer's disease continuum in Mexican AmericansR01AG085571 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI GONZALES, MITZI MICHELLE, HABES, MOHAMAD · 2024 to 2025
$5.7M
CARDIA Year 35 Brain MRI RenewalR01AG062819 · NIA · UNIVERSITY OF PENNSYLVANIA · PI BRYAN, R N · 2019 to 2022
$4.8M
Fast and robust deep learning tools for analysis of neuroimaging data of Alzheimer's diseaseR01AG066650 · NIA · UNIVERSITY OF PENNSYLVANIA · PI FAN, YONG · 2021 to 2025
$3.4M
Multiethnic machine learning brain signatures of ADRDR01AG080821 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI HABES, MOHAMAD · 2022 to 2025
$2.9M
Cognitive Aging, Alzheimers disease, and Cancer-related Cognitive DeclineR01AG068193 · NIA · GEORGETOWN UNIVERSITY · PI MANDELBLATT, JEANNE, SAYKIN, ANDREW J · 2020 to 2023
$2.8M
Advanced machine learning algorithms that integrate multi-modal neuroimaging to quantify the heterogeneity in Alzheimer's DiseaseR01AG067103 · NIA · WASHINGTON UNIVERSITY · PI SOTIRAS, ARISTEIDIS · 2021 to 2025
$2.8M
Vascular Imaging Biomarker Relationships to Alzheimer’s disease (VIBRA)R01AG083865 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Mohamad Habes, Timothy M. Hughes · 2024 to 2026
$2.3M
High Capacity, High Performance Storage System for NeuroscienceS10OD032285 · OD · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TOGA, ARTHUR W · 2022 to 2022
$1.7M
NIA NIH HHS P30 AG066530NIA NIH HHS P30 AG066546NIA NIH HHS R01 AG062819NIA NIH HHS R01 AG066650NIA NIH HHS R01 AG067103NIA NIH HHS R01 AG068193NIA NIH HHS R01 AG080821NIA NIH HHS R01 AG083865NIA NIH HHS R01 AG085571NIA NIH HHS RF1 AG054409NIH HHS S10 OD032285
6 · The paper itself

Abstract

Alzheimer's disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE ε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction-driven by genes different from APOE-which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/ .

Indexed as

Alzheimer DiseaseAtrophyCognitive DysfunctionGenome-Wide Association StudyAgedAged, 80 and overApolipoprotein E4BrainFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedTemporal LobeApolipoprotein E4

Identifiers

PMID39368996
PMCPMC11455841

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.