Circulation research最新文献

The cardiovascular system, composed of the heart and vasculature, is essential for blood circulation, nutrient exchange, and waste removal. In the past, our understanding of cardiovascular development and function has largely been shaped by bulk tissue analyses, which obscures cellular heterogeneity. The emergence of single-cell omics has transformed the field by enabling unbiased transcriptional profiling of individual cells, revealing the diversity of stem cells and progenitor cells driving embryogenesis, resulting in the various mature cardiovascular cell types in the adult heart and vasculature. This technology has provided unprecedented insights into the molecular mechanisms governing cardiovascular development and function by identifying novel cell subpopulations, characterizing their unique properties, and tracing their temporal evolution through advanced analytical approaches. In this review, we discuss how single-cell omics has reshaped our understanding of cardiovascular developmental biology, highlight key analytical tools and emerging approaches, examine preclinical models that have facilitated these discoveries, and explore how these technologies have defined the cellular landscape of the heart and vasculature. We conclude by looking ahead to emerging technologies such as spatial transcriptomics and clonal barcoding for lineage tracing, as well as new strategies in addressing the gender gap in cardiovascular research.

Single-cell and spatial transcriptomics technologies have transformed the landscape of cardiovascular research, leading to novel insights into cellular heterogeneity and tissue architecture in health and disease. These technologies enable researchers to deconvolute complex tissues and map gene expression patterns within their spatial contexts, providing critical information on the interplay between cell types and pathways affecting tissue regeneration or progression to fibrosis. This review presents an overview of the recently developed applications of single-cell and spatial transcriptomics methods and their impact on cardiovascular research. We discuss the principles underlying emerging solutions to process fixed and low-integrity RNA samples like formalin-fixed paraffin-embedded tissues. In addition, we highlight advances in high-resolution spatial transcriptomics assays, from imaging-based techniques like MERFISH (multiplexed error-robust fluorescence in situ hybridization) and Xenium to sequencing-based platforms like Visium HD, Stereo-seq, and Open-ST, each contributing unique strengths for tissue-level analysis. The integration of these technologies with machine learning and multiomics approaches further enhances the ability to uncover novel biology. These approaches have already led to the discovery of spatially resolved gene expression patterns in human atherosclerosis, hypertrophic cardiomyopathy, myocardial infarction, and myocarditis. These case studies showcase how these methods can be applied to decode the cellular and molecular dynamics of human disease processes, identify potential novel therapeutic targets, and enable predictive modeling of cellular perturbations and patient disease trajectories. We provide a comprehensive overview of the growing data repository landscape, the principles and applications of novel machine learning approaches, which are becoming more and more standard analytical tools. Integrating these areas underscores how recent advancements in single-cell and spatial transcriptomics are offering an increasingly detailed and comprehensive understanding of the cellular landscape of cardiovascular disease while also highlighting the challenges and future directions that will shape innovations in cardiovascular biology and medicine.