Plasma proteomic biomarker signature of age predicts health and life span

Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (5...

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Published in:	eLife Vol. 9
Main Authors:	Tanaka, Toshiko, Basisty, Nathan, Fantoni, Giovanna, Candia, Julián, Moore, Ann Z, Biancotto, Angelique, Schilling, Birgit, Bandinelli, Stefania, Ferrucci, Luigi
Format:	Journal Article
Language:	English
Published:	England eLife Sciences Publications, Ltd 19.11.2020 eLife Sciences Publications Ltd
Subjects:	Adult Aged Aged, 80 and over aging Aging - blood Aging - physiology biomarker Biomarkers - blood Blood Proteins - physiology Computational and Systems Biology Epidemiology and Global Health Female healthspan Humans Male Middle Aged Proteomics Risk Factors Young Adult computational biology global health systems biology epidemiology proteomics aging biomarker healthspan human
ISSN:	2050-084X, 2050-084X
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Abstract	Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis -epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.
AbstractList	Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis -epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions. Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions. Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions. Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial -epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.
Author	Fantoni, Giovanna Tanaka, Toshiko Moore, Ann Z Bandinelli, Stefania Schilling, Birgit Basisty, Nathan Candia, Julián Biancotto, Angelique Ferrucci, Luigi
Author_xml	– sequence: 1 givenname: Toshiko orcidid: 0000-0002-4161-3829 surname: Tanaka fullname: Tanaka, Toshiko organization: Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, United States – sequence: 2 givenname: Nathan surname: Basisty fullname: Basisty, Nathan organization: The Buck Institute for Research on Aging, Novato, United States – sequence: 3 givenname: Giovanna surname: Fantoni fullname: Fantoni, Giovanna organization: National Institute on Aging, Intramural Research Program, Clinical Research Core, NIH, Baltimore, United States – sequence: 4 givenname: Julián orcidid: 0000-0001-5793-8989 surname: Candia fullname: Candia, Julián organization: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, United States – sequence: 5 givenname: Ann Z surname: Moore fullname: Moore, Ann Z organization: Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, United States – sequence: 6 givenname: Angelique surname: Biancotto fullname: Biancotto, Angelique organization: Precision Immunology, Immunology & Inflammation Research Therapeutic Area, Sanofi, Cambridge, United States – sequence: 7 givenname: Birgit orcidid: 0000-0001-9907-2749 surname: Schilling fullname: Schilling, Birgit organization: The Buck Institute for Research on Aging, Novato, United States – sequence: 8 givenname: Stefania surname: Bandinelli fullname: Bandinelli, Stefania organization: Geriatric Unit, Azienda Sanitaria toscana centro, Firenze, Italy – sequence: 9 givenname: Luigi orcidid: 0000-0002-6273-1613 surname: Ferrucci fullname: Ferrucci, Luigi organization: Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, United States
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Snippet	Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic...
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SubjectTerms	Adult Aged Aged, 80 and over aging Aging - blood Aging - physiology biomarker Biomarkers - blood Blood Proteins - physiology Computational and Systems Biology Epidemiology and Global Health Female healthspan Humans Male Middle Aged Proteomics Risk Factors Young Adult
Title	Plasma proteomic biomarker signature of age predicts health and life span
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