Astrocyte senescence may drive alterations in GFAPα, CDKN2A p14ARF, and TAU3 transcript expression and contribute to cognitive decline

Abstract

The accumulation of senescent cells in tissues is causally linked to the development of several agerelated diseases; the removal of senescent glial cells in animal models prevents Tau accumulation and cognitive decline. Senescent cells can arise through several distinct mechanisms; one such mechanism is dysregulation of alternative splicing. In this study, we characterised the senescent cell phenotype in primary human astrocytes in terms of SA-β-Gal staining and SASP secretion, and then assessed splicing factor expression and candidate gene splicing patterns. Finally, we assessed associations between expression of dysregulated isoforms and premature cognitive decline in 197 samples from the InCHIANTI study of ageing, where expression was present in both blood and brain. We demonstrate here that senescent astrocytes secrete a modified SASP characterised by increased IL8, MMP3, MMP10, and TIMP2 but decreased IL10 levels. We identified significant changes in splicing factor expression for 10/20 splicing factors tested in senescent astrocytes compared with early passage cells, as well as dysregulation of isoform levels for 8/13 brain or senescence genes tested. Finally, associations were identified between peripheral blood GFAPα, TAU3, and CDKN2A (P14 ARF) isoform levels and mild or severe cognitive decline over a 3-7year period. Our data are suggestive that some of the features of cognitive decline may arise from dysregulated splicing of important genes in senescent brain support cells, and that defects in alternative splicing or splicing regulator expression deserve exploration as points of therapeutic intervention in the future.

Astrocyte senescence contributes to cognitive decline

“…The authors first characterized the composition of the astrocyte SASP in terms of cytokine and MMP production. Senescent astrocytes demonstrated altered levels of several key SASP proteins such as elevated IL-8, GM-CSF, angiogenin, ENA78, GRO-ɑ, MMP-3, MMP-10, and TIMP2 levels and reduced IL-10 levels (Lye et al 2019). In their results, senescent astrocytes also displayed changes in splicing factor expression and patterns of alternative splicing.…”

“…The existing evidence presented suggests that future studies should continue to explore the functional consequences of astrocyte senescence and its relationship to declining cognitive function in aging with particular emphasis on the role of senescent astrocytes in the impairment of neurovascular coupling responses and the increase in blood-brain barrier permeability. It will still be also of great interest to determine whether similar transcriptional changes observed by Lye et al (Lye et al 2019) may also be occurring in other important proliferative brain cell types in the neurovascular unit such as endothelial cells. In conclusion, this work by Lye and coworkers provides an exciting step toward understanding how astrocyte senescence contributes to cognitive decline.…”

circRNAs expressed in human peripheral blood are associated with human aging phenotypes, cellular senescence and mouse lifespan

“…Early passage young cells were at population doubling (PD) of 24 for astrocytes, 28 for cardiomyocytes, 24 for endothelial cells and 25 for fibroblasts, whilst late passage senescent cells were at PD = 84 for astrocytes, 75 for cardiomyocytes, 65 for endothelial cells and 63 for fibroblasts. Senescent cell load in these samples was~75% for fibroblasts,~55% for endothelial cells,~38% for cardiomyocytes and~36% for cardiomyocytes(Latorre et al 2017; Latorre et al 2018a;Latorre et al 2018b;Latorre et al 2018c;Lye et al 2019). In all cases, growth of the culture had slowed to less than 0.5 PD/week.…”

“…Gene expression is regulated at many levels. Changes in the regulation and pattern of alternative splicing are associated with age in several human populations and are also evident in senescent cells of different lineages, where they may drive cellular senescence, since restoration of levels reverses multiple senescence phenotypes (Latorre et al 2017;Latorre et al 2018a;Latorre et al 2018b;Latorre et al 2018c;Lye et al 2019). Notably, non-coding RNAs also demonstrate associations with aging or senescence and may be of equal importance (Abdelmohsen et al 2012;Boulias and Horvitz 2012;Gorospe and Abdelmohsen 2011).…”

“…Statistical analysis was completed using StataSE15 (StataCorp, TX, USA). Figures were generated using GraphPad Prism 8.1.2 (GraphPad Software, San Diego, USA) Lye et al 2019)…”