Usage Information
Citation Information: JCI Insight. 2020;5(12):e133668. https://doi.org/10.1172/jci.insight.133668.
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.
Authors
Marissa J. Schafer, Xu Zhang, Amanika Kumar, Elizabeth J. Atkinson, Yi Zhu, Sarah Jachim, Daniel L. Mazula, Ashley K. Brown, Michelle Berning, Zaira Aversa, Brian Kotajarvi, Charles J. Bruce, Kevin L. Greason, Rakesh M. Suri, Russell P. Tracy, Steven R. Cummings, Thomas A. White, Nathan K. LeBrasseur
Usage data is cumulative from July 2021 through July 2022.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 6,198 | 872 |
| 898 | 263 | |
| Figure | 720 | 15 |
| Table | 249 | 0 |
| Supplemental data | 429 | 58 |
| Citation downloads | 161 | 0 |
| Totals | 8,655 | 1,208 |
| Total Views | 9,863 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
