Nature agingOct 23, 2026

Key gene activity patterns linked to aging in blood vessel lining cells revealed by single-cell analysis

Longevity & Aging Weekly Brief ↗PubMed ↗DOI ↗OA ↗

Updated Oct 25, 2026

Abstract

The Human Aging Endothelial Cell Atlas (HAECA) includes over 375,000 endothelial cells from 12 human tissues across adulthood.

Endothelial cells show tissue-specific roles that are critical for vascular health.
Aging is associated with a decline in angiogenic gene expression in venous endothelial cells.
Significant alterations were observed in gene expression related to the extracellular matrix and cellular response to mechanical forces.
A transcriptional program linked to the protein p21 was identified, suggesting a connection to cellular aging.
The atlas serves as a detailed reference for understanding endothelial function throughout the human lifespan.

Simplified

Endothelial cells (ECs) are critical regulators of vascular function and exhibit tissue-specialized roles. During aging, these cells become dysfunctional, resulting in increased susceptibility to cardiovascular disease. Although single-cell transcriptomics has revealed extensive endothelial heterogeneity, a comprehensive atlas of human EC transcriptomes over the course of the adult human lifespan has been lacking. Here, we present the Human Aging Endothelial Cell Atlas (HAECA), a harmonized single-cell transcriptomic compendium of over 375,000 ECs from 12 human tissues throughout adulthood. We identified age-associated transcriptional shifts, including a decline in angiogenic gene expression in venous ECs and widespread alterations in extracellular matrix and mechanotransduction-associated signatures. Furthermore, we uncovered a p21-linked transcriptional program in ECs, which we linked to cellular senescence in both in vitro and in vivo models. Together, our study provides a high-resolution transcriptomic reference of the human endothelium across tissues and age.

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Key gene activity patterns linked to aging in blood vessel lining cells revealed by single-cell analysis

Abstract

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