Single-cell spatial transcriptomics in cardiovascular development, disease, and medicine

• Published in: Genes & diseases 2024-11, Vol.11 (6), p.101163, Article 101163
• Main Authors: Han, Songjie, Xu, Qianqian, Du, Yawen, Tang, Chuwei, Cui, Herong, Xia, Xiaofeng, Zheng, Rui, Sun, Yang, Shang, Hongcai
• Format: Article
• Language: English
• Subjects: Cardiovascular disease; Precision medicine; Review; Single-cell spatial transcriptomics; Single-cell transcriptome; Spatial transcriptome; Transcriptomics
• ISSN: 2352-3042; 2352-4820; 2352-3042
• DOI: 10.1016/j.gendis.2023.101163

Cardiovascular diseases (CVDs) impose a significant burden worldwide. Despite the elucidation of the etiology and underlying molecular mechanisms of CVDs by numerous studies and recent discovery of effective drugs, their morbidity, disability, and mortality are still high. Therefore, precise risk stratification and effective targeted therapies for CVDs are warranted. Recent improvements in single-cell RNA sequencing and spatial transcriptomics have improved our understanding of the mechanisms and cells involved in cardiovascular phylogeny and CVDs. Single-cell RNA sequencing can facilitate the study of the human heart at remarkably high resolution and cellular and molecular heterogeneity. However, this technique does not provide spatial information, which is essential for understanding homeostasis and disease. Spatial transcriptomics can elucidate intracellular interactions, transcription factor distribution, cell spatial localization, and molecular profiles of mRNA and identify cell populations causing the disease and their underlying mechanisms, including cell crosstalk. Herein, we introduce the main methods of RNA-seq and spatial transcriptomics analysis and highlight the latest advances in cardiovascular research. We conclude that single-cell RNA sequencing interprets disease progression in multiple dimensions, levels, perspectives, and dynamics by combining spatial and temporal characterization of the clinical phenome with multidisciplinary techniques such as spatial transcriptomics. This aligns with the dynamic evolution of CVDs (e.g., “angina–myocardial infarction–heart failure” in coronary artery disease). The study of pathways for disease onset and mechanisms (e.g., age, sex, comorbidities) in different patient subgroups should improve disease diagnosis and risk stratification. This can facilitate precise individualized treatment of CVDs.