Blood contains countless different proteins secreted from different cell populations throughout the body. Different cell types tend to secrete different mixes of proteins. Researchers have recently made inroads into constructing organ-specific aging clocks from protein levels in blood, using machine learning to identify patterns that predict the health, disease risk, and disease status of specific organs. This is still in the relatively early stages when compared to other clocks, but it seems to be going fairly well so far. The results are as useful as more general aging clocks, which is to say that there are still hurdles to overcome before they can be used by an individual to reliably assess health or in a study to rapidly assess outcomes of a new therapy.
Senescent cells accumulate with age in tissues throughout the body, and secrete a pro-inflammatory, disruptive mix of proteins that actively degrades tissue structure and function. Animal studies demonstrate that cellular senescence is an important contributing cause of degenerative aging. Researchers here make use of the approach taken to produce organ-specific proteomic aging clocks to attempt to map the burden of cellular senescence in different tissues using only a blood sample. This is possible because senescent cells of different types and origins produce meaningfully different mixes of secreted proteins, just like other cells. Only here, those secretions are much more harmful when sustained over the long term.
Cellular senescence becomes more common with age as healthy cells encounter sublethal environmental and genotoxic stress or accrue other types of damage, and is implicated in age-related decline. Senescence is characterized in part by proteomic expression changes, including the secretions of pro-inflammatory cytokines and other proteins. These senescence-associated proteins (SAPs) have since proven to be heterogeneous by cell type and senescence-inducing stimulus.
In this study, senescence signatures from the Senescence Catalog (SenCat), including 14 human cell types were examined in circulation for clinical relevance in two longitudinal studies – 1,275 participants of the Baltimore Longitudinal Study of Aging (BLSA) and 997 participants of the Invecchiare in Chianti (InCHIANTI) study. This study undertook the first investigation of cell type-specific (senotype-specific) senescence signatures and their possible clinical relevance across two human cohorts. SAPs were associated with diverse aging phenotypes in the BLSA and InCHIANTI cohorts, and outperformed other circulating non-SAPs in predicting many clinical parameters, including age, walking pace, and hypertension.
Overall, this study comprehensively evaluates and identifies clinically relevant “core” and cell type senescence signatures with cross-study validation and lays a foundation for future exploration of cell type senescence biomarkers in circulation. We demonstrate that senescence markers generally outperformed non-senescence markers in predicting clinical traits and illustrate key examples of cell type senescence signatures with unique relevance to corresponding organ systems and functions. This study highlights the potential translational use of senescence markers.
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