npj AgingCell BiologyPeer-reviewed journal article
Uncovering senescent fibroblast heterogeneity connects DNA damage response to idiopathic pulmonary fibrosis
Jun‐Wei B. HughesiD, Akshay PujariiD, Anja Sandholm, Duncan Croll, Lea B. Monk, Isaac Joshua, Rachel Butterfield, Corrigan Horton, Kevin SchneideriD, Fiona SenchynaiD, Ian Brown, Zhixin A. Zhang, T. Ho, Tsung-Che Ho, Hideto DeguchiiD, Ryo Higuchi‐SanabriaiD, Claude Jourdan Le SauxiD, Stefanie Deinhardt‐EmmeriD, Lisa EllerbyiD, Alberto Vitari, David FurmaniD, Cory M. HogaboamiD, Alex Laslavic, Pierre‐Yves DespreziD, Marco QuartaiD, Judith CampisiiD
Abstract
Cellular senescence is a largely heterogeneous state of cell stress that deleteriously accumulates with age. Many types of heterogeneity in senescence have been described; however, cellular senescence within the same cell type has only started to be documented. Here, we show primary, human lung fibroblasts from donors who are healthy or diagnosed with idiopathic pulmonary fibrosis (IPF) exhibit a subtle form of heterogeneity over time after DNA damage. Moreover, senescent IPF lung fibroblasts display a dysregulated transcriptional-protein DNA damage response (DDR). Weighted gene correlation network analysis (WGCNA) reveals unique and known targets linking senescent IPF lung fibroblast heterogeneity to genes associated with DNA damage and repair, cytokine and chemokine responses, and extracellular matrix (ECM) signaling. We combine our healthy and IPF senescent gene expression signatures to develop a novel gene set of senescence-associated genes that identify disease-relevant cells in human single-cell RNA-seq (scRNA-seq) data. Collectively, our results uncover human-relevant senescence signatures, highlight IPF-specific DDR, cytokine and chemokine, and ECM targets, and expand our understanding of how a dysregulated DDR contributes to senescent cell heterogeneity in IPF.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- approach: statistical model
- Citations
- 1
- FWCI
- 4.62
- Field percentile
- top 12%
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