Evidence map›Paper›PMID 40832429›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Sleep chart of biological aging clocks across organs and omics.

MULTI study, Cliodhna Kate O'Toole, Zhiyuan Song, Filippos Anagnostakis, Zhijian Yang, Ye Ella Tian, Michael R Duggan, Chunrui Zou, Yue Leng, Yi Cai and 17 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

5 · Who and what money

Authors and funding

27 authors.

MULTI study
Cliodhna Kate O'TooleLaboratory 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.
Filippos AnagnostakisLaboratory of AI and Biomedical Science (LABS), Columbia University, New York, NY, USA.
Zhijian YangGE Healthcare, Bellevue, WA, USA.
Ye Ella TianDepartment 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.
Chunrui ZouDepartment of Radiology, Columbia University, New York, NY, USA.
Yue LengDepartment of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California, USA.ORCID 0000-0001-5826-4031
Yi CaiDepartment of Otolaryngology-Head and Neck Surgery, Columbia University, New York, NY, USA.
Wenjia BaiDepartment of Brain Sciences and Department of Computing, Imperial College London, London, UK.
Cynthia H Y FuSchool of Psychology, University of East London, London, UK.ORCID 0000-0003-4313-3500
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.
Gao WangDepartment of Neurology, Columbia University, New York, NY, USA.
Philip L De JagerCenter for Translational & Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0002-8057-2505
Jian ZengInstitute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia.ORCID 0000-0001-8801-5220
Hamilton Se-Hwee OhNash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID 0000-0001-8192-7593
Xia ZhouDepartment of Computer Science, Columbia University, 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
Daniel W BelskyRobert N Butler Columbia Aging Center and Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA.ORCID 0000-0001-5463-2212
Andrew ZaleskyDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Victoria, Australia.
Eleanor M SimonsickLongitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA.
Susan M ResnickLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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.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
Training Program in Social Neuroscience ResearchT32MH135853 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Hirofumi Morishita, SCOTT JAMES RUSSO · 2024 to 2026
$684k
NIA NIH HHS RF1 AG054409NIA NIH HHS RF1 AG092412NIMH NIH HHS T32 MH135853
6 · The paper itself

Abstract

Optimal sleep plays a vital role in promoting healthy aging and enhancing longevity. This study proposes a Sleep Chart to assess the relationship between sleep duration and 23 biological aging clocks across 17 organ systems or tissues and 3 omics data types (imaging, proteomics, and metabolomics). First, a systemic, U-shaped pattern shows that both short (<6 hours) and long (>8 hours) sleep duration are linked to elevated biological age gaps (BAGs) across 9 brain and body systems and 3 omics types, with optimal sleep time varying by organ and sex ([6.4-7.8] hours). Furthermore, short and long sleep duration, compared to a normal sleep duration ([6-8] hours), are consistently linked to increased risk of systemic diseases beyond the brain and all-cause mortality, with evidence from genetic correlations and time to incident disease predictions, such as migraine, depression, and diabetes. Finally, short and long sleep duration are associated with late-life depression via distinct pathways: long sleep may contribute indirectly through biological aging processes, while short sleep shows a more direct link. Although our Mendelian randomization does not show strong causal effects from disease to sleep disturbances, it does not fully rule out the possibility that sleep disturbances may, in part, reflect underlying disease burden. Our findings suggest that the U-shaped relationship is likely driven by modifiable sleep disturbances rather than genetic predisposition, highlighting the potential of sleep optimization to support healthy aging, lower disease risk, and extend longevity. An interactive web portal is available to explore the Sleep Chart at: https://labs-laboratory.com/sleepchart.

Identifiers

PMID40832429
PMCPMC12363694

What OpenQuestion 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 OpenQuestion graph.