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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:eLife Ročník 9
Hlavní autoři: Tanaka, Toshiko, Basisty, Nathan, Fantoni, Giovanna, Candia, Julián, Moore, Ann Z, Biancotto, Angelique, Schilling, Birgit, Bandinelli, Stefania, Ferrucci, Luigi
Médium: Journal Article
Jazyk:angličtina
Vydáno: England eLife Sciences Publications, Ltd 19.11.2020
eLife Sciences Publications Ltd
Témata:
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
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2050-084X
2050-084X
DOI:10.7554/eLife.61073