Abstract 11993: Integrative Analysis of Single-Cell Transcriptomics and Polygenic Risk Scores Uncovers Vascular Smooth Muscle Cell Heterogeneity in Human Aortic Aneurisms

Abstract

Background: Atherosclerosis is accompanied by distinct vascular phenotypes that underly its initiation and progression, though their contribution to its pathogenesis is currently unknown. By integrating polygenetic risk profiles from genome-wide association studies (GWAS) of vascular disease with single-cell transcriptional analyses, it is possible to implicate causal cellular subpopulations and functional states. Hypothesis: We sought to build a more precise understanding of the cellular mechanisms underlying vascular disease in humans by combining single-nuclear RNA-sequencing (snRNA-seq) data from vascular tissue with known polygenic risk loci associated with vascular disease. Methods: We performed snRNA-seq on five flash-frozen human aortas, implementing a novel dissociation method to isolate and sequence 14,228 quality-controlled nuclei from three thoracic aortic aneurysms and two samples without known aortopathy, obtained from patients aged 37-70 years. Cell types were defined using canonical gene markers, and non-linear dimensional reduction via tSNE was employed to identify transcriptional sub-phenotypes. The identified pathological programs were validated using polygenic risk and by integrating GWAS data from other vascular single-nuclear transcriptomic datasets. Results: Our analysis revealed ten distinct clusters representing all major vascular cell populations, with vascular smooth muscle cells (VSMCs) and myofibroblasts emerging as the most relevant cell types in relation to vascular disease based on polygenic risk. Within the VSMC population, two distinct subpopulations exhibited differential expression of genes related to the extracellular matrix, contractility, and proliferation. RNA-trajectory analysis further uncovered a continuum of gene expression linking VSMC1, VSMC2, and myofibroblast transcriptional clusters. Conclusions: This study validates novel methods for identifying pathologic VSMC states associated with vascular disease and implicates phenotypic switching as a pathogenic mechanism. We highlight genes and pathways associated with endothelial cell and VSMC state transitions that are enriched in GWAS of coronary artery disease (CAD).