TY - JOUR TI - Plasma proteomic biomarker signature of age predicts health and life span AU - Tanaka, Toshiko AU - Basisty, Nathan AU - Fantoni, Giovanna AU - Candia, Julián AU - Moore, Ann Z AU - Biancotto, Angelique AU - Schilling, Birgit AU - Bandinelli, Stefania AU - Ferrucci, Luigi A2 - Hägg, Sara A2 - Akhmanova, Anna VL - 9 PY - 2020 DA - 2020/11/19 SP - e61073 C1 - eLife 2020;9:e61073 DO - 10.7554/eLife.61073 UR - https://doi.org/10.7554/eLife.61073 AB - 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. KW - proteomics KW - aging KW - healthspan KW - biomarker JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -