Evidence mapPaperPMID 40419465Full record

ArticleNature communications2025

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk.

MULTI consortium, Filippos Anagnostakis, Sarah Ko, Mehrshad Saadatinia, Jingyue Wang, Christos Davatzikos, Junhao Wen

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Observational
  3. Supplementation via DAF-16 andbioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Cytotoxic T Cells: Kill, Memorize, and Mask to Maintain Immune Homeostasis.International journal of molecular sciences · 2025
    Review
  16. Article
  17. Sleep chart of biological aging clocks across organs and omics.medRxiv : the preprint server for health sciences · 2025
    Article
  18. 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

7 authors.

MULTI consortium
Filippos AnagnostakisLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.ORCID http://orcid.org/0000-0001-7374-8798
Sarah KoLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Mehrshad SaadatiniaLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Jingyue WangLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, 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.ORCID http://orcid.org/0000-0002-1025-8561
Junhao WenLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA. junhao.wen89@gmail.com.ORCID http://orcid.org/0000-0003-2077-3070

Funding

Multi-Organ Chart of Personalized Susceptibility to Alzheimer's Disease and AgingRF1AG092412 · COLUMBIA UNIVERSITY HEALTH SCIENCES · 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 · UNIVERSITY OF PENNSYLVANIA · 2025 to 2025
$706k
NIA NIH HHS R01 AG054409NIA NIH HHS RF1 AG054409NIA NIH HHS RF1 AG092412
6 · The paper itself

Abstract

Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25<r < 0.42). Crucially, including composite metabolites (e.g. sums or ratios of raw metabolites) results in poor generalizability to independent test data due to multicollinearity. Genome-wide associations identify 405 MetBAG-locus pairs (P < 5 × 10

Indexed as

AgingCardiovascular DiseasesMetabolic DiseasesMetabolomeAdultAgedAged, 80 and overFemaleGenome-Wide Association StudyHumansMaleMendelian Randomization AnalysisMetabolomicsMiddle AgedPolymorphism, Single NucleotideUnited Kingdom

Identifiers

PMID40419465
PMCPMC12106725

What Socratic 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 Socratic graph.