Cells become senescent constantly, ceasing to replicate and generating inflammatory signaling. This occurs when cells reach the Hayflick limit on replication, and in response to damage, injury, and toxicity. Senescence helps to draw the attention of the immune system to where it is needed, and in youth senescent cells are efficiently destroyed by immune cells once that task is accomplished. With age, however, the immune system becomes progressively less efficient while the environment becomes more damaged. As a consequence a burden of lingering senescent cells grows over time, and their contribution to the chronic inflammation of aging disrupts tissue structure and function.
Usefully measuring the burden of senescence in older people in a low-cost, non-invasive way remains a work in progress. In principle different tissues may be burdened to different degrees, and only looking at immune cells in a blood sample can be misleading with regarding to the situation in other organs and systems. Nonetheless, blood samples are largely what the research community aims to work with when building assays; it is what the medical community is geared to focus on, and data from blood samples is largely what one finds in epidemiological databases.
In today's open access paper, researchers report on the results of applying a number of approaches to deriving a score for the burden of cellular senescence based on gene expression data to the data from a large epidemiological study. While some of these assessments can be conducted in multiple tissues, the study gene expression data is from blood samples only, so the usual caveats apply as to whether this is representative of the whole body. Nonetheless, the researchers do find correlations with other metrics of health and aging, suggesting that there is value in these efforts to produce practical measures of the burden of cellular senescence.
Cellular senescence is one of the molecular/cellular-level hallmarks of aging that accumulates with advancing age and plays an important pathogenic role in a number of adverse health outcomes. In response to damage, senescent cells stop proliferating and enter into a generally irreversible state of growth arrest. However, senescent cells are still metabolically active; they release a wide range of pro-inflammatory cytokines, chemokines, proteases, growth factors, and other bioactive molecules to the local microenvironment. Such proinflammatory secretion is termed Senescence-Associated Secretory Phenotype (SASP), and is thought to mediate downstream aging outcomes.
Recent work has suggested a more comprehensive approach to capturing the entire effect of cellular senescence rather than solely relying on SASP. In addition to SASP, other key aspects of cellular senescence include cell cycle arrest (CCA) and macromolecular damage (MD). To profile these distinct aspects of cellular senescence, researchers developed three lists of genes that are involved in the canonical senescence pathway (CSP), senescence initiating pathway (SIP), and senescence response pathway (SRP) to respectively represent CCA, MD, and SASP. These gene lists were tested and validated in two independent RNA sequencing datasets, and were associated with senescence in previous studies based on various cell and tissue types in human and mouse brains. Another gene list reflecting intracellular changes specific to senescent immune cells, termed SenMayo, was also recently developed. SenMayo includes genes involved in CCA, MD, and SASP, and thus has the potential to measure cellular senescence comprehensively.
Using RNA sequencing data from the U.S. representative Health and Retirement Study (HRS) sample (N = 3,580), we examine how CSP, SIP, SRP, and SenMayo relate to sociobehavioral factors and aging-related outcomes. Results show that senescence scores generally increase with age except for CSP. Higher scores are observed in women and individuals with class II obesity. All scores, except for CSP, are associated with accelerated epigenetic aging, physiological dysregulation, multimorbidity, cognitive decline, and 6-year mortality. These associations largely persist after adjustment for the pace of aging clock DunedinPACE. Our findings suggest that cellular senescence gene expression composite scores capture meaningful variation in aging-related health and complement existing epigenetic aging biomarkers.
View the full article at FightAging