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Oh HSH, Rutledge J, Nachun D, Pálovics R, Abiose O, Moran-Losada P, Channappa D, Urey DY, Kim K, Sung YJ, Wang L, Timsina J, Western D, Liu M, Kohlfeld P, Budde J, Wilson EN, Guen Y, Maurer TM, Haney M, Yang AC, He Z, Greicius MD, Andreasson KI, Sathyan S, Weiss EF, Milman S, Barzilai N, Cruchaga C, Wagner AD, Mormino E, Lehallier B, Henderson VW, Longo FM, Montgomery SB, Wyss-Coray T. Organ aging signatures in the plasma proteome track health and disease. Nature 2023; 624:164-172. [PMID: 38057571 PMCID: PMC10700136 DOI: 10.1038/s41586-023-06802-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 10/31/2023] [Indexed: 12/08/2023]
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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Affiliation(s)
- Hamilton Se-Hwee Oh
- Graduate Program in Stem Cell and Regenerative Medicine, Stanford University, Stanford, CA, USA
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Jarod Rutledge
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Graduate Program in Genetics, Stanford University, Stanford, CA, USA
| | - Daniel Nachun
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Róbert Pálovics
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Olamide Abiose
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Patricia Moran-Losada
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Divya Channappa
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Deniz Yagmur Urey
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University School of Engineering, Stanford, CA, USA
| | - Kate Kim
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Dan Western
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Menghan Liu
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Edward N Wilson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Yann Guen
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Taylor M Maurer
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Haney
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Andrew C Yang
- Departments of Neurology and Anatomy, University of California San Francisco, San Francisco, CA, USA
- Gladstone Institute of Neurological Disease, Gladstone Institutes, San Francisco, CA, USA
- Bakar Aging Research Institute, University of California San Francisco, San Francisco, CA, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Katrin I Andreasson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Sanish Sathyan
- Departments of Medicine and Genetics, Institute for Aging Research, Albert Einstein College of Medicine, New York, NY, USA
| | - Erica F Weiss
- Department of Neurology, Montefiore Medical Center, New York, NY, USA
| | - Sofiya Milman
- Departments of Medicine and Genetics, Institute for Aging Research, Albert Einstein College of Medicine, New York, NY, USA
| | - Nir Barzilai
- Departments of Medicine and Genetics, Institute for Aging Research, Albert Einstein College of Medicine, New York, NY, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Anthony D Wagner
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Victor W Henderson
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Frank M Longo
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Stephen B Montgomery
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Tony Wyss-Coray
- The Phil and Penny Knight Initiative for Brain Resilience, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA.
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Wang L, Western D, Timsina J, Repaci C, Song WM, Norton J, Kohlfeld P, Budde J, Climer S, Butt OH, Jacobson D, Garvin M, Templeton AR, Campagna S, O’Halloran J, Presti R, Goss CW, Mudd PA, Ances BM, Zhang B, Sung YJ, Cruchaga C. Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways. iScience 2023; 26:106408. [PMID: 36974157 PMCID: PMC10010831 DOI: 10.1016/j.isci.2023.106408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/21/2023] [Accepted: 03/10/2023] [Indexed: 03/14/2023] Open
Abstract
Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
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Affiliation(s)
- Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Charlie Repaci
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Won-Min Song
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Sharlee Climer
- Department of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Michael Garvin
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Alan R. Templeton
- Department of Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Shawn Campagna
- Department of Chemistry, University of Tennessee, Knoxville, TN, USA
| | - Jane O’Halloran
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Rachel Presti
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Charles W. Goss
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A. Mudd
- Department of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
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3
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Wang L, Western D, Timsina J, Repaci C, Song WM, Norton J, Kohlfeld P, Budde J, Climer S, Butt OH, Jacobson D, Garvin M, Templeton AR, Campagna S, O’Halloran J, Presti R, Goss CW, Mudd PA, Ances BM, Zhang B, Sung YJ, Cruchaga C. Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways. medRxiv 2022:2022.07.25.22278025. [PMID: 35923315 PMCID: PMC9347279 DOI: 10.1101/2022.07.25.22278025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.
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Affiliation(s)
- Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Dan Western
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Charlie Repaci
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Won-Min Song
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Sharlee Climer
- Department of Computer Science, University of Missouri-St. Louis, St. Louis, MO, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Daniel Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Michael Garvin
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Alan R Templeton
- Department of Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Shawn Campagna
- Department of Chemistry, University of Tennessee, Knoxville, TN, USA
| | - Jane O’Halloran
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Rachel Presti
- Division of Infectious Diseases, Washington University School of Medicine, St Louis, MO, USA
| | - Charles W. Goss
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Philip A. Mudd
- Department of Emergency Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Beau M. Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
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