Plasma proteomic biomarker signature of age predicts health and life span

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) was identified. 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 premise of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk for disease to be targeted for in depth diagnostic procedures and early interventions.

Effect of Aging on Homeostasis in the Soft Tissue of the Periodontium: A Narrative Review

“…Aging affects the composition and structural flexibility of ECM. Recently, Tanaka et al analyzed plasma proteins of all age groups and identified ~650 age-associated proteins in which extracellular matrix-related proteins were enriched [ 67 ]. Another recent study demonstrated that abundance of hyaluronan, an ECM glycosaminoglycan, gradually decreased with age, leading to the alteration in biomechanical properties of ECM [ 68 ].…”

Proteomics in aging research: A roadmap to clinical, translational research

“…To this end, a concerted effort has been undertaken to characterize the proteomic signature of chronological and biological age in plasma (Lehallier et al, 2019;Tanaka et al, 2018Tanaka et al, , 2020.…”

“…To this end, a concerted effort has been undertaken to characterize the proteomic signature of chronological and biological age in plasma (Lehallier et al, 2019; Tanaka et al, 2018, 2020). For example, we have recently published a plasma proteomic signature of age that includes 76 proteins highly correlated with chronological age, with growth differentiation factor 15 (GDF15) having the strongest, positive association with age (Tanaka et al, 2018).…”

Proteomics and Epidemiological Models of Human Aging

“…Cross-sectional studies are often nested in existing longitudinal cohorts. For example, Tanaka et al (2020a) studied plasma protein levels in samples of participants evaluated at baseline (1998)(1999)(2000) in the "Invecchiare in Chianti" (Aging in the Chianti Area, InCHIANTI) study, a community-based cohort study that has been followed longitudinally over more than two decades. Generally, cross-sectional studies can be performed relatively quickly on large populations.…”