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 Timsina, Dan Western, Menghan Liu, Pat Kohlfeld, John Budde, Edward N. Wilson, Yann Guen, Taylor M. Maurer, Michael Haney, Andrew C. Yang, Zihuai He, Michael D. Greicius, Katrin I. Andreasson, Sanish Sathyan, Erica F. Weiss, Sofiya Milman, Nir Barzilai, Carlos Cruchaga, Anthony D. Wagner, Elizabeth Mormino, Benoit Lehallier, Victor W. Henderson, Frank M. Longo, Stephen B. Montgomery, Tony Wyss-Coray
{"title":"血浆蛋白质组中的器官衰老特征跟踪健康和疾病。","authors":"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 Timsina, Dan Western, Menghan Liu, Pat Kohlfeld, John Budde, Edward N. Wilson, Yann Guen, Taylor M. Maurer, Michael Haney, Andrew C. Yang, Zihuai He, Michael D. Greicius, Katrin I. Andreasson, Sanish Sathyan, Erica F. Weiss, Sofiya Milman, Nir Barzilai, Carlos Cruchaga, Anthony D. Wagner, Elizabeth Mormino, Benoit Lehallier, Victor W. Henderson, Frank M. Longo, Stephen B. Montgomery, Tony Wyss-Coray","doi":"10.1038/s41586-023-06802-1","DOIUrl":null,"url":null,"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. Blood plasma protein data was combined with machine learning models for a simple method to determine differences in organ-specific aging; the study provides a basis for the prediction of diseases and aging effects using plasma proteomics.","PeriodicalId":18787,"journal":{"name":"Nature","volume":"624 7990","pages":"164-172"},"PeriodicalIF":48.5000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10700136/pdf/","citationCount":"0","resultStr":"{\"title\":\"Organ aging signatures in the plasma proteome track health and disease\",\"authors\":\"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 Timsina, Dan Western, Menghan Liu, Pat Kohlfeld, John Budde, Edward N. Wilson, Yann Guen, Taylor M. Maurer, Michael Haney, Andrew C. Yang, Zihuai He, Michael D. Greicius, Katrin I. Andreasson, Sanish Sathyan, Erica F. Weiss, Sofiya Milman, Nir Barzilai, Carlos Cruchaga, Anthony D. Wagner, Elizabeth Mormino, Benoit Lehallier, Victor W. Henderson, Frank M. Longo, Stephen B. Montgomery, Tony Wyss-Coray\",\"doi\":\"10.1038/s41586-023-06802-1\",\"DOIUrl\":null,\"url\":null,\"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. 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Organ aging signatures in the plasma proteome track health and disease
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. Blood plasma protein data was combined with machine learning models for a simple method to determine differences in organ-specific aging; the study provides a basis for the prediction of diseases and aging effects using plasma proteomics.
期刊介绍:
Nature is a prestigious international journal that publishes peer-reviewed research in various scientific and technological fields. The selection of articles is based on criteria such as originality, importance, interdisciplinary relevance, timeliness, accessibility, elegance, and surprising conclusions. In addition to showcasing significant scientific advances, Nature delivers rapid, authoritative, insightful news, and interpretation of current and upcoming trends impacting science, scientists, and the broader public. The journal serves a dual purpose: firstly, to promptly share noteworthy scientific advances and foster discussions among scientists, and secondly, to ensure the swift dissemination of scientific results globally, emphasizing their significance for knowledge, culture, and daily life.