Evidence map›Paper›PMID 40832432›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart.

MULTI consortium, Aleix Boquet-Pujadas, Filippos Anagnostakis, Zhijian Yang, Ye Ella Tian, Michael R Duggan, Guray Erus, Dhivya Srinivasan, Cassandra M Joynes, Wenjia Bai and 5 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

15 authors.

MULTI consortium
Aleix Boquet-PujadasLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Filippos AnagnostakisLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Zhijian YangGE Healthcare, Bellevue, WA, USA.
Ye Ella TianMelbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-3107-5550
Michael R DugganLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Guray ErusArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Dhivya SrinivasanArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Cassandra M JoynesLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Wenjia BaiDepartment of Brain Sciences and Department of Computing, Imperial College London, London, UK.
Praveen J PatelNIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and Institute of Ophthalmology, University College London, London, UK.
Keenan A WalkerLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.ORCID 0000-0002-5989-9853
Andrew ZaleskyLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Christos DavatzikosArtificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AID), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Junhao WenLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.ORCID 0000-0003-2077-3070

Funding

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
Multi-Organ Chart of Personalized Susceptibility to Alzheimer's Disease and AgingRF1AG092412 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WEN, JUNHAO · 2025 to 2025
$3.5M
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 consortiumR01AG054409 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos · 2025 to 2026
$1.4M
NIA NIH HHS R01 AG054409NIA NIH HHS RF1 AG054409NIA NIH HHS RF1 AG092412
6 · The paper itself

Abstract

Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease entities and overlook shared mechanisms across conditions

Identifiers

PMID40832432
PMCPMC12363687

What OpenQuestion holds

Textmetadata
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.