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Abstract
Produced by senescent cells, the senescence-associated secretory phenotype (SASP) is a potential driver of age-related dysfunction. We tested whether circulating concentrations of SASP proteins reflect age and medical risk in humans. We first screened senescent endothelial cells, fibroblasts, preadipocytes, epithelial cells, and myoblasts to identify candidates for human profiling. We then tested associations between circulating SASP proteins and clinical data from individuals throughout the life span and older adults undergoing surgery for prevalent but distinct age-related diseases. A community-based sample of people aged 20–90 years (retrospective cross-sectional) was studied to test associations between circulating SASP factors and chronological age. A subset of this cohort aged 60–90 years and separate cohorts of older adults undergoing surgery for severe aortic stenosis (prospective longitudinal) or ovarian cancer (prospective case-control) were studied to assess relationships between circulating concentrations of SASP proteins and biological age (determined by the accumulation of age-related health deficits) and/or postsurgical outcomes. We showed that SASP proteins were positively associated with age, frailty, and adverse postsurgery outcomes. A panel of 7 SASP factors composed of growth differentiation factor 15 (GDF15), TNF receptor superfamily member 6 (FAS), osteopontin (OPN), TNF receptor 1 (TNFR1), ACTIVIN A, chemokine (C-C motif) ligand 3 (CCL3), and IL-15 predicted adverse events markedly better than a single SASP protein or age. Our findings suggest that the circulating SASP may serve as a clinically useful candidate biomarker of age-related health and a powerful tool for interventional human studies.
Introduction
Aging is the strongest risk factor for the majority of chronic diseases. Recent scientific advances have led to the transformative hypothesis that interventions targeting the fundamental biology of aging have the potential to delay, if not prevent, the onset of age-associated conditions and extend human health span (1). Notably, there is now compelling evidence that cellular senescence, a state of stable growth arrest caused by diverse forms of cellular and molecular damage, contributes to aging, in part, through the senescence-associated secretory phenotype (SASP) (2–4). Senescent cells accumulate with advancing age (5–7). Preclinical studies in rodents have established that transgenic strategies and drugs that selectively kill senescent cells improve numerous yet pathologically distinct conditions of aging, including idiopathic pulmonary fibrosis (8), cardiovascular disease (9, 10), hepatic steatosis (11), osteoporosis (12), diabetes (13), physical decline (14, 15), and brain dysfunction (16–18). Importantly, reducing SASP abundance and subsequent action is a likely mechanism by which senescent cell elimination improves aging conditions (8, 10, 19, 20). Consequently, there is great interest in human translation (21).
Dramatic variability is inherent to aging. Many older adults of a given chronological age experience multiple chronic conditions and functional limitations, while paired-age counterparts may have low or no disease burden and comparatively greater functional independence. Individuals with cumulatively more age-related impairments may be characterized as frail or biologically older according to a standardized accumulation-of-deficits index (22). Advanced biological age may be linked to a greater burden of senescent cells in one or multiple organs. Core properties of senescent cells include upregulation of cyclin-dependent kinase inhibitors, morphological changes, activation of antiapoptosis pathways, and a SASP composed of cytokines, chemokines, matrix remodeling proteins, and growth factors (23). Senescent cell properties can be quantified in isolated tissues; however, this poses practical challenges for human application. Since the SASP is a key pathogenic feature of senescent cells, leveraging the circulating SASP as an indicator of systemic senescent cell burden may offer considerable utility. In clinical research, it can help identify persons who may be most responsive to emerging therapies and serve as surrogate endpoints in associated clinical trials. In clinical practice, SASP quantification may identify persons of advanced biological age and guide clinical decision making. We hypothesize that SASP abundance may be associated with chronological aging and accelerated biological aging.
Herein, we sought to take advantage of the circulating SASP as a candidate biomarker of advanced age and/or medical risk. Based on the robust and dynamic SASP of several human cell types, we first established a candidate panel of 24 SASP proteins that can be reliably measured in human blood, and then studied associations with chronological age in a population-based sample of persons 20 to 90 years of age. We next examined associations between circulating SASP proteins and clinical manifestations of biological age using a frailty index (22) in 3 distinct cohorts of older adults. Finally, we assessed the extent to which circulating SASP factors predict adverse health outcomes after surgery for distinct age-related diseases.
Results
Senescent cells produce a robust and distinct SASP. To develop a candidate panel of SASP biomarkers for human application, conditioned media were collected from 5 senescent versus nonsenescent human cell types: endothelial and epithelial cells, preadipocytes, fibroblasts, and myoblasts. Irradiation-induced senescence was confirmed by senescence-associated β-galactosidase (SA–β-Gal) staining and real-time PCR analysis of senescence-activated genes (Figure 1A and Supplemental Figure 1; supplemental material available online with this article; https://doi.org/10.1...ght.133668DS1).A biased approach, based on the molecular knowledge of the SASP obtained in model systems, was used to select candidate proteins. High levels of both distinct and overlapping SASP factors, including cytokines, chemokines, matrix remodeling proteins, and growth factors, were identified in all senescent cells assayed relative to nonsenescent cells (Figure 1B and Supplemental Table 1). Senescent endothelial cells, preadipocytes, and fibroblasts produced a more robust SASP relative to epithelial cells and myoblasts, with distinct proteins increased per cell type (Figure 1, B and C; and Supplemental Tables 1 and 2). GDF15, OPN, and IL-8 were abundantly produced and secreted by senescent endothelial cells, whereas higher levels of IL-15, IL-6, PAI2, and ACTIVIN A were produced and secreted by senescent preadipocytes (Figure 1, B and C; and Supplemental Table 2). Thus, distinct cell types throughout the body may uniquely contribute to a dynamic SASP in vivo.
Figure 1. Senescent human cells secrete a heterogeneous SASP. (A) SA–β-Gal staining confirmed senescence induction in irradiated versus sham-treated human cells (scale bar: 200 μm). (B) Fold change in concentration of secreted SASP proteins by irradiated senescent cells (SnC) normalized to the sham control © samples for each cell type. © Absolute secreted protein concentration from 1 million senescent versus nonsenescent control cells. Abbreviations: endothelial cells (endo), preadipocytes (pre), fibroblasts (fibro), epithelial cells (epi), and myoblasts (myo). Mean is depicted; 2-tailed t tests with significance indicated as *P < 0.05, **P < 0.01, and ***P < 0.001; n = 3 replicates per cell type). See Supplemental Tables 1 and 2 for supportive data.
Circulating SASP factors are associated with advanced chronological age. Building on the premise that senescent cells accumulate with chronological age, the panel of 24 SASP proteins identified as biologically relevant in vitro was measured in the plasma of a random sample of 267 Mayo Clinic biobank participants (24). The sample was equivalently distributed by sex and age from 20 to 90 years (Supplemental Table 3). Circulating concentrations of 19 SASP proteins were associated with chronological age, and associations between 17 SASP factors and chronological age remained significant after adjusting for sex and BMI (Supplemental Table 4), highlighting the potential influence of sex and body composition on the biology of aging. Unadjusted Spearman’s correlation analyses indicated that GDF15 and ACTIVIN A were the strongest candidate biomarkers of chronological age, followed by TNFR1, CCL4, FAS, CCL3, TNF-α, and IL-6, all of which individually explained at least 10% of the variance in chronological age (Figure 2). GDF15, ACTIVIN A, CCL4, FAS, CCL3, and TNF-α remained significantly associated with age after adjusting for sex and BMI (Supplemental Table 4).
Figure 2. Circulating SASP factors are associated with chronological age. Circulating concentrations of SASP proteins demonstrating the strongest unadjusted FDR-corrected Spearman’s correlations with chronological age are depicted among Mayo Clinic biobank participants age 20–90 years. Women (n = 137) are indicated by pink circles, and men (n = 130) are indicated by blue circles. See Supplemental Table 4 for supportive data.
Circulating SASP factors are associated with advanced biological age. The principal exploratory sample used to test associations between plasma levels of the panel of 24 SASP factors and biological age, as measured by the frailty index, was composed of older adults undergoing surgery for severe aortic stenosis (n = 97). To determine whether associations between biological age and circulating SASP factors were disease agnostic, plasma SASP factor concentrations were also assessed in a limited case-control study of older women undergoing surgery for ovarian cancer, in which women with a greater burden of age-associated deficits based on the frailty index were compared with counterparts with lower deficit burden, yet of similar age and disease severity (n = 36). Plasma SASP factor concentrations and frailty index associations were also studied in the subset of 267 Mayo Clinic biobank sample participants age 60–90 years (n = 115). Demographic information for all 3 samples is presented in Supplemental Tables 5 and 6.
In unadjusted analyses, 8 SASP factors, ACTIVIN A, CCL4, GDF15, IL-6, IL-15, OPN, TNF-α, and TNFR1, were positively associated with the frailty index in any one of the 3 participant groups (Table 1; Model 1). GDF15 and OPN increased in association with the frailty index in all 3 participant groups and remained significant after adjusting for chronological age, BMI, and/or sex as potential confounding or effect-modifying variables (Table 1). Similarly, after adjustment for age, BMI, and/or sex, TNFR1 was associated with a higher frailty index across all 3 groups. Increased CCL4 and TNF-α were associated with advanced biological age in both surgical groups and remained significant after adjustment, but were not significantly associated with the frailty index in aged, nonsurgical participants. IL-15 was positively associated with the frailty index in only the aortic stenosis and nonsurgical participant groups before and after adjustment. Using both unadjusted and adjusted models, ACTIVIN A and IL-6 were positively associated with the frailty index in the nonsurgical participants (Table 1).
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