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Unique Human and Mouse β-Cell Senescence-Associated Secretory Phenotype (SASP) Reveal Conserved Signaling Pathways and Heterogeneous Factors

Authors: Ayush Midha; Hui Pan; Cristian Abarca; Joshua Andle; Priscila Carapeto; Susan Bonner-Weir; Cristina Aguayo-Mazzucato;

Unique Human and Mouse β-Cell Senescence-Associated Secretory Phenotype (SASP) Reveal Conserved Signaling Pathways and Heterogeneous Factors

Abstract

The aging of pancreatic β-cells may undermine their ability to compensate for insulin resistance, leading to the development of type 2 diabetes (T2D). Aging β-cells acquire markers of cellular senescence and develop a senescence-associated secretory phenotype (SASP) that can lead to senescence and dysfunction of neighboring cells through paracrine actions, contributing to β-cell failure. In this study, we defined the β-cell SASP signature based on unbiased proteomic analysis of conditioned media of cells obtained from mouse and human senescent β-cells and a chemically induced mouse model of DNA damage capable of inducing SASP. These experiments revealed that the β-cell SASP is enriched for factors associated with inflammation, cellular stress response, and extracellular matrix remodeling across species. Multiple SASP factors were transcriptionally upregulated in models of β-cell senescence, aging, insulin resistance, and T2D. Single-cell transcriptomic analysis of islets from an in vivo mouse model of reversible insulin resistance indicated unique and partly reversible changes in β-cell subpopulations associated with senescence. Collectively, these results demonstrate the unique secretory profile of senescent β-cells and its potential implication in health and disease.

Keywords

Mice, Diabetes Mellitus, Type 2, Insulin-Secreting Cells, Animals, Humans, Biomarkers, Cellular Senescence, DNA Damage, Signal Transduction

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 1%
Top 10%
Top 1%
hybrid