Plasma proteomic signature of age in healthy humans

Abstract

To characterize the proteomic signature of chronological age, 1,301 proteins were measured in plasma using the SOMAscan assay (SomaLogic, Boulder, CO, USA) in a population of 240 healthy men and women, 22–93 years old, who were disease‐ and treatment‐free and had no physical and cognitive impairment. Using a p ≤ 3.83 × 10−5 significance threshold, 197 proteins were positively associated, and 20 proteins were negatively associated with age. Growth differentiation factor 15 (GDF15) had the strongest, positive association with age (GDF15; 0.018 ± 0.001, p = 7.49 × 10−56). In our sample, GDF15 was not associated with other cardiovascular risk factors such as cholesterol or inflammatory markers. The functional pathways enriched in the 217 age‐associated proteins included blood coagulation, chemokine and inflammatory pathways, axon guidance, peptidase activity, and apoptosis. Using elastic net regression models, we created a proteomic signature of age based on relative concentrations of 76 proteins that highly correlated with chronological age (r = 0.94). The generalizability of our findings needs replication in an independent cohort.

Undulating changes in human plasma proteome across lifespan are linked to disease

“…1e, Supplementary Table 6). Conversely, an extensive list of aging proteins identified enrichment for blood-related pathways such as heparin and glycosaminoglycan binding, as recently reported 20 .…”

“…To determine whether these findings are representative of the general population, we compared changes identified in this study with findings from 4 small independent cohorts (n=171, age range 21-107y, Supplementary Fig. 1d) and with findings from an independent study 20 . Even though these independent studies used an older version of the SomaScan assay measuring only a subset of the current proteins (1, 305 proteins; Supplementary Table 2), we observed high consistency of the aging and sex proteomes across cohorts ( Supplementary Fig.…”

“…To provide confidence in the reproducibility of the protein assays, we compared our findings with the associations with age reported by Tanaka et al 20 . To this end, we merged our results with those from Tanaka et al using "SomaId".…”

Measuring biological aging in humans: A quest

“…Senescence has been studied successfully in T lymphocytes, skin, and intramuscular fat, and high-throughput methods will be available soon (Evangelou et al, 2016;Lozano-Torres et al, 2017). In addition, specific patterns of circulating proteins may exist that indirectly estimate the burden of senescence (Angelini et al, 2017;Hoffman, Lyu, Pletcher, & Promislow, 2017;Kadota et al, 2018;Menni et al, 2014;Tanaka et al, 2018;Yousefzadeh et al, 2017). Similarly, measures of autophagy are routinely used in mammalian studies and should be applicable to humans (Klionsky, 2014;Klionsky, Cuervo, & Seglen, 2007;Menzies, Moreau, Puri, Renna, & Rubinsztein, 2012).…”

Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches

“…The SOMAscan‐based proteomic measurements of 1301 plasma proteins in a population of 240 healthy men and women (22–93 years old) identified growth differentiation factor 15 (GDF15) as the strongest biomarker, positively associated with age. [ 130 ] The proteomic age predictor was developed based on relative concentrations of 76 proteins that highly correlated with chronological age using elastic net regression models (Table S1, Supporting Information).…”