Identifying Endogenous Drivers of Chronic Disease Using Novel Computational Methods

terile inflammation, “inflammaging”, is a hallmark of aging and contributes to many age-associated diseases. Targeting the underlying mechanisms of inflammaging could have significant implications for the treatment of many chronic diseases. Cellular senescence (CS) and transposable elements (TEs) are two endogenous drivers of inflammation that are both dysregulated in aging and inflammatory disease. Senescent cells accumulate in tissues with age and release a potent mix of inflammatory signals into their surrounding milieu. TEs are diverse and abundant mobile elements within the genome that remain mostly dormant under normal conditions. TEs become derepressed with age and activate innate inflammatory pathways within cells. Both processes amplify disease and are induced by disease. However, CS and TEs are rarely considered together even though they have the potential to be mutual activators and cause autoinflammatory loops in aging and disease. Studying CS is challenging because the in vivo phenotypes of CS are incredibly heterogeneous. Additionally, most markers and gene sets derived to study CS come from culture experiments that poorly recapitulate the phenotypes in living tissues. We used large-scale single-cell datasets from many cell types spanning the aging spectrum to create a database of cell-type-specific signatures of CS. We created a first-of-its-kind algorithm to identify senescent cells in single-cell data. We validated the databases and algorithms against multiple ground-truth in vivo models of CS. We used our algorithm to map the characteristics of senescent cells in aging, cancer, heart disease, and COVID-19. TEs were long relegated as “junk DNA” and are recently gaining traction as critical components in disease and as regulatory elements within cells. Yet, they are difficult to study because they are highly repetitive, which challenges most high-throughput sequencing methods. Instead, we employed long-read sequencing to accurately characterize TE expression and polymorphisms. We pulsed lung microvascular endothelial cells with TNFα and observed a significant activation of TEs over a 24-hour time course. These changes coincided with the prolonged amplification of innate immune and CS pathways, despite the absence of an exogenous stimulus. Likewise, in an Alzheimer's Disease (AD) mouse model, we observed activated TEs, associated with a CS phenotype. We next explored TE polymorphisms between individuals and identified previously uncharacterized regulatory elements within the genome that influence transposition events and the location of TEs. We also found important aspects of TE expression, like their proximity to transcriptionally stimulated regions. We also broadly characterized TE dysregulation in human AD and found genetic variants that are causally linked to the expression of genes, including MAPT (Tau). Our efforts suggest that CS and TEs are bidirectional mutual activators that amplify each other, while also contributing to disease and inflammaging. CS drives NF-κB internally and in neighboring cells. We show that TEs are broadly activated by NF-κB signaling. CS can be activated by sustained interferon signaling. We showed that expressed TEs sustain interferon signaling. We also show that important mediators of CS are coexpressed with TEs in multiple contexts. This work sets the stage for future analyses aimed at understanding the direct role of TEs in the CS phenotype. We developed novel computational tools and workflows to study these phenomena with increased sensitivity and fidelity.

Author dc:creator

• Mark A. Sanborn (24399962)

• cellular senescence
• transposable elements
• aging
• inflammation
• bioinformatics

Statement dc:rights

• In Copyright
• Open Access after 2028-05-01

DOI dc:identifier

https://doi.org/10.25417/uic.32994971.v1

OAI identifier oai:identifier

oai:figshare.com:article/32994971