Abstract Body (Do not enter title and authors here): Introduction
Calcific aortic valve disease (CAVD) is a progressive condition with no effective pharmacological therapy, while the pathogenesis remains unclear. This study aims to construct an multi-omics atlas of CAVD in cell level by genomic sequencing and single-cell RNA sequencing (scRNA) across a multi-center large cohort.
Hypothesis
Genetic variations, cellular heterogeneity, and transcriptional changes in blood and valve tissue contribute to CAVD. Large-scale multi-omics sequencing will provide a comprehensive view of pathogenesis.
Aims:
Describe scRNA and genomic landscape of CAVD in multi-center large cohort.
Methods
Total of 164 participants from four centers in China were enrolled in this study. Calcified valve samples and matching blood samples were collected from CAVD patients undergoing valve replacement. Control valve samples were obtained from heart transplant and Bentall procedure recipients without Marfan syndrome, while control blood samples were collected from control valve donors and healthy volunteers. Participants with bicuspid aortic valves, chronic kidney diseases, or diabetes mellitus were also included. The scRNA with 10X coverage was performed on the valve and blood samples immediately after collection, and genomic sequencing at 30X coverage was conducted on blood samples in the same instance.
Results
Ultimately 370 samples underwent omics sequencing, including 276 blood samples and 94 valve samples. Genomic sequencing identified novel loci associated with CAVD beyond previous reports. Unsupervised clustering of 641,064 valve cells identified five major cell types and 30 minor subpopulations in detailed subdivision, from which the synaptic-like valvular interstitial cells (VICs) were newly evidenced (6.5% in VICs). Similarly, 382,226 blood cells were clustered into four major cell types and 18 minor subpopulations in detail, with significant transcriptional alterations observed in monocytes, T cells, and B cells compared to controls. RNA velocity and CellChat analysis highlighted developing trajectories and adhesion of myeloid immune cells in blood and interactions with VICs.
Conclusion
This study established the largest multi-center CAVD cohort for genome and scRNA sequencing, revealing novel loci, transcriptional shifts, cell subpopulations and interaction between valve and blood in CAVD. The integration of data from genome and scRNA will describe a comprehensive single-cell expression quantitative trait loci (eQTL) atlas for CAVD.