Organ-specific proteomic aging clocks predict disease and longevity across diverse populations

Yunhe Wang^#^{1

2

3}, Sihao Xiao^#⁴, Bowen Liu⁴, Rongtao Jiang^{5

6}, Yuxi Liu^{7

8

9}, Yian Hang¹⁰, Li Chen¹¹, Runsen Chen¹², Michael V Vitiello¹³, Derrick Bennett⁴, Baihan Wang⁴, Jun Lv^{11

14

15}, Canqing Yu^{11

14

15}, Danielle E Haslam^{8

16}, Qianyan Zheng¹⁶, Robert E Gerszten¹⁷, Yanping Bao^{11

18}, Jie Shi¹⁸, Junqing Xie¹⁹, Lin Lu^{18

20

21}, Liming Li^{11

14

15}, Cornelia M van Duijn⁴, Dong D Wang^{7

8

16}, Zhengming Chen⁴, Andrew T Chan^{8

22}

Affiliations

¹ Nuffield Department of Population Health, University of Oxford, Oxford, UK. yunhe.wang@channing.harvard.edu.
² Broad Institute of MIT and Harvard, Cambridge, MA, USA. yunhe.wang@channing.harvard.edu.
³ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. yunhe.wang@channing.harvard.edu.
⁴ Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁵ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁶ Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
⁹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biology, University of Oxford, Oxford, UK.
¹¹ School of Public Health, Peking University, Beijing, China.
¹² Vanke School of Public Health and Institute for Healthy China, Tsinghua University, Beijing, China.
¹³ Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA.
¹⁴ Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
¹⁵ Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
¹⁶ Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁷ Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹⁸ National Institute on Drug Dependence, Peking University, Beijing, China.
¹⁹ Centre for Statistics in Medicine and NIHR Biomedical Research Centre Oxford, NDORMS, University of Oxford, Oxford, UK.
²⁰ Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing, China.
²¹ Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
²² Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

^# Contributed equally.

PMID: 41299092
DOI: 10.1038/s43587-025-01016-8

Organ-specific proteomic aging clocks predict disease and longevity across diverse populations

Yunhe Wang et al. Nat Aging. 2025.

. 2025 Nov 26.

doi: 10.1038/s43587-025-01016-8. Online ahead of print.

Authors

Affiliations

¹ Nuffield Department of Population Health, University of Oxford, Oxford, UK. yunhe.wang@channing.harvard.edu.
² Broad Institute of MIT and Harvard, Cambridge, MA, USA. yunhe.wang@channing.harvard.edu.
³ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. yunhe.wang@channing.harvard.edu.
⁴ Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁵ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁶ Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
⁹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Biology, University of Oxford, Oxford, UK.
¹¹ School of Public Health, Peking University, Beijing, China.
¹² Vanke School of Public Health and Institute for Healthy China, Tsinghua University, Beijing, China.
¹³ Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA.
¹⁴ Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
¹⁵ Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
¹⁶ Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁷ Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹⁸ National Institute on Drug Dependence, Peking University, Beijing, China.
¹⁹ Centre for Statistics in Medicine and NIHR Biomedical Research Centre Oxford, NDORMS, University of Oxford, Oxford, UK.
²⁰ Institute of Mental Health, National Clinical Research Center for Mental Disorders, Key Laboratory of Mental Health and Peking University Sixth Hospital, Peking University, Beijing, China.
²¹ Peking-Tsinghua Center for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
²² Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

^# Contributed equally.

PMID: 41299092
DOI: 10.1038/s43587-025-01016-8

Abstract

Aging and age-related diseases share convergent pathways at the proteome level. Here, using plasma proteomics and machine learning, we developed organismal and ten organ-specific aging clocks in the UK Biobank (n = 43,616) and validated their high accuracy in cohorts from China (n = 3,977) and the USA (n = 800; cross-cohort r = 0.98 and 0.93). Accelerated organ aging predicted disease onset, progression and mortality beyond clinical and genetic risk factors, with brain aging being most strongly linked to mortality. Organ aging reflected both genetic and environmental determinants: brain aging was associated with lifestyle, the GABBR1 and ECM1 genes, and brain structure. Distinct organ-specific pathogenic pathways were identified, with the brain and artery clocks linking synaptic loss, vascular dysfunction and glial activation to cognitive decline and dementia. The brain aging clock further stratified Alzheimer's disease risk across APOE haplotypes, and a super-youthful brain appears to confer resilience to APOE4. Together, proteomic organ aging clocks provide a biologically interpretable framework for tracking aging and disease risk across diverse populations.

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Conflict of interest statement

Competing interests: The authors declare no competing interests.

References

1. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. The hallmarks of aging. Cell 153, 1194–1217 (2013). - PubMed - PMC - DOI
1. Ahadi, S. et al. Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nat. Med. 26, 83–90 (2020). - PubMed - PMC - DOI
1. Oh, H. S.-H. et al. Organ aging signatures in the plasma proteome track health and disease. Nature 624, 164–172 (2023). - PubMed - PMC - DOI
1. Prattichizzo, F. et al. Organ-specific biological clocks: ageotyping for personalized anti-aging medicine. Ageing Res. Rev. 96, 102253 (2024). - PubMed - DOI
1. Moqri, M. et al. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 186, 3758–3775 (2023). - PubMed - PMC - DOI

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Organ-specific proteomic aging clocks predict disease and longevity across diverse populations

Affiliations

Organ-specific proteomic aging clocks predict disease and longevity across diverse populations

Authors

Affiliations

Abstract

Conflict of interest statement

References

LinkOut - more resources

Full Text Sources

Miscellaneous