← BioTransfer GEO Dataset Finder
GEO series

Single-Cell RNA Sequencing Unveils Macrophage Involvement in Aortic Valve Stenosis Progression

GSE291890 Homo sapiens Expression profiling by high throughput sequencing 33 samples 2026/03/01 GPL34281GPL24676
Summary
Introduction: Calcific aortic stenosis (AS) is an age-related progressive disease with increasing global prevalence. Although chronic inflammation is a key factor in its pathogenesis, the detailed immune cell profiles and their interactions with non-immune cells remain poorly understood. This study aimed to characterize the immune cell landscape in calcific AS at a single-cell level and evaluate the potential of anti-inflammatory therapy. Methods: Human aortic valve samples were obtained from four patients with non-calcified aortic regurgitation (AR) and 11 patients with AS undergoing surgical aortic valve replacement. Single-cell 3’ gene expression sequencing (scRNA-seq (3’)) was performed on CD45+ immune cells, while single-cell RNA sequencing Flex (scRNA-seq (Flex)) and bulk RNA sequencing were conducted on unsorted cells. Additionally, an anti-TNFα antibody experiment was performed in a murine AS model induced by aortic valve wire injury. Results: In myeloid cells, LYVE1 resident macrophages were significantly decreased, whereas classical monocytes expressing pro-inflammatory genes and C1Q macrophages were increased in AS valves compared to AR valves. These macrophages exhibited strong interactions with valve interstitial cells, particularly with chondrogenic subtypes expressing COMP and SPARC. Anti-TNFα treatment in the murine model significantly reduced aortic valve calcification without hematopoietic complications. Conclusions: This study is the first to integrate scRNA-seq (3’) and scRNA-seq (Flex) analyses of human aortic valves, revealing single cell-level characteristics of immune cells and their interactions with non-immune cells in calcific AS. These findings suggest that anti-inflammatory therapy could be a therapeutic target for calcific AS.
Download
NCBI GEO page ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.