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Organ aging signatures in the plasma proteome track health and disease

Author

Listed:
  • Hamilton Se-Hwee Oh

    (Stanford University
    Stanford University
    Stanford University)

  • Jarod Rutledge

    (Stanford University
    Stanford University
    Stanford University)

  • Daniel Nachun

    (Stanford University School of Medicine)

  • Róbert Pálovics

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Olamide Abiose

    (Stanford University
    Stanford University School of Medicine)

  • Patricia Moran-Losada

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Divya Channappa

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Deniz Yagmur Urey

    (Stanford University
    Stanford University School of Engineering)

  • Kate Kim

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Yun Ju Sung

    (Washington University in St Louis
    Washington University School of Medicine)

  • Lihua Wang

    (Washington University in St Louis
    Washington University School of Medicine)

  • Jigyasha Timsina

    (Washington University in St Louis
    Washington University School of Medicine)

  • Dan Western

    (Washington University in St Louis
    Washington University School of Medicine
    Washington University School of Medicine)

  • Menghan Liu

    (Washington University in St Louis
    Washington University School of Medicine)

  • Pat Kohlfeld

    (Washington University in St Louis
    Washington University School of Medicine)

  • John Budde

    (Washington University in St Louis
    Washington University School of Medicine)

  • Edward N. Wilson

    (Stanford University
    Stanford University School of Medicine)

  • Yann Guen

    (Stanford University School of Medicine
    Stanford University School of Medicine)

  • Taylor M. Maurer

    (Stanford University School of Medicine)

  • Michael Haney

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

  • Andrew C. Yang

    (University of California San Francisco
    Gladstone Institutes
    University of California San Francisco)

  • Zihuai He

    (Stanford University School of Medicine)

  • Michael D. Greicius

    (Stanford University School of Medicine)

  • Katrin I. Andreasson

    (Stanford University
    Stanford University School of Medicine
    Chan Zuckerberg Biohub)

  • Sanish Sathyan

    (Albert Einstein College of Medicine)

  • Erica F. Weiss

    (Montefiore Medical Center)

  • Sofiya Milman

    (Albert Einstein College of Medicine)

  • Nir Barzilai

    (Albert Einstein College of Medicine)

  • Carlos Cruchaga

    (Washington University in St Louis
    Washington University School of Medicine)

  • Anthony D. Wagner

    (Stanford University
    Stanford University)

  • Elizabeth Mormino

    (Stanford University School of Medicine)

  • Benoit Lehallier

    (Stanford University School of Medicine)

  • Victor W. Henderson

    (Stanford University
    Stanford University School of Medicine
    Stanford University)

  • Frank M. Longo

    (Stanford University
    Stanford University School of Medicine)

  • Stephen B. Montgomery

    (Stanford University School of Medicine
    Stanford University School of Medicine
    Stanford University School of Medicine)

  • Tony Wyss-Coray

    (Stanford University
    Stanford University
    Stanford University School of Medicine)

Abstract

Animal studies show aging varies between individuals as well as between organs within an individual1–4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20–50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer’s disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

Suggested Citation

  • Hamilton Se-Hwee Oh & Jarod Rutledge & Daniel Nachun & Róbert Pálovics & Olamide Abiose & Patricia Moran-Losada & Divya Channappa & Deniz Yagmur Urey & Kate Kim & Yun Ju Sung & Lihua Wang & Jigyasha T, 2023. "Organ aging signatures in the plasma proteome track health and disease," Nature, Nature, vol. 624(7990), pages 164-172, December.
  • Handle: RePEc:nat:nature:v:624:y:2023:i:7990:d:10.1038_s41586-023-06802-1
    DOI: 10.1038/s41586-023-06802-1
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    Cited by:

    1. Patricia R. Pitrez & Luis M. Monteiro & Oliver Borgogno & Xavier Nissan & Jerome Mertens & Lino Ferreira, 2024. "Cellular reprogramming as a tool to model human aging in a dish," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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