bioRxivCell BiologyPreprint
Organ-resolved endothelial regulatory programs link aging and metabolic overload to vascular immune remodeling
Masataka YokoyamaiD, Akitoshi Nakayama, Yuki TakiiD, Mingyang Chen, Yingbo Gong, Moeko Shiina, Takashi KonoiD, Masanori FujimotoiD, Kaoru ItoiD, Jun‐ichiro Ikeda, Tomoaki TanakaiD
Abstract
Systemic aging and metabolic overload remodel the vasculature; however, how endothelial cells integrate these stresses across organs remains unclear. Using multi-organ single-cell and spatial transcriptomics with functional validation, we mapped endothelial and hematopoietic responses in adipose tissue, skeletal muscle, liver, and heart. Organ-specific endothelial transcriptional features were relatively preserved, whereas chronic stress selectively reconfigured regulatory programs: aging induced a conserved Irf/Stat-centered endothelial program, while high-fat diet engaged organ-biased lipid and remodeling programs. Spatial analysis revealed perivascular niches centered on aging-associated interferon-stimulated endothelial activation, with neighboring immune and stromal cells expressing C3 and LRP1-associated signals. Rather than simply amplifying inflammation, these niches contained mechanisms that restrained IFN activation, as C3 depletion upregulated vascular IRF7 expression. In parallel, the IFN downstream effector BST2 promoted anti-inflammatory macrophage differentiation and suppressed atherosclerosis. These findings define vascular inflammaging as an organ-resolved niche process in which endothelial IFN activation is coupled to local inflammatory restraint. HighlightsO_LIAging induces a shared endothelial type I IFN program across organs. C_LIO_LIA high-fat diet triggers organ-biased endothelial remodeling programs. C_LIO_LIPerivascular interferon niches couple inflammation with local restraint. C_LIO_LIIFN-induced endothelial BST2 promotes CD200R-associated macrophage regulatory features. C_LI
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
- Citations
- 0
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