Evidence map›Paper›PMID 40672508›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Multi-organ MRI digitizes biological aging clocks across proteomics, metabolomics, and genetics.

MULTI Consortium, Huizi Cao, Zhiyuan Song, Michael R Duggan, Guray Erus, Dhivya Srinivasan, Ye Ella Tian, Wenjia Bai, Michael S Rafii, Paul Aisen and 6 more

Abstract readPreprint
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

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

16 authors.

MULTI Consortium
Huizi CaoLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Zhiyuan SongLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
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.
Ye Ella TianSystems Lab, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-3107-5550
Wenjia BaiDepartment of Brain Sciences and Department of Computing, Imperial College London, London, UK.
Michael S RafiiAlzheimer's Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA 92121, USA.
Paul AisenAlzheimer's Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA 92121, USA.
Daniel W BelskyRobert N Butler Columbia Aging Center and Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.
Keenan A WalkerLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.ORCID 0000-0002-5989-9853
Andrew ZaleskySystems Lab, Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia.
Luigi FerrucciNational 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.

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
NIA NIH HHS RF1 AG054409
6 · The paper itself

Abstract

Leveraging clinical phenotypes

Identifiers

PMID40672508
PMCPMC12265779

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.