Related Experiment Video
Updated: Jun 14, 2025
Isolation and Profiling of Human Primary Mesenteric Arterial Endothelial Cells at the Transcriptome Level
Published on: March 14, 2022
Single-cell spatial transcriptomics in cardiovascular development, disease, and medicine
Songjie Han1, Qianqian Xu1, Yawen Du1
1Key Laboratory of Chinese Internal Medicine of Ministry of Education, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China.
Insights
Single-cell RNA sequencing and spatial transcriptomics offer new insights into cardiovascular diseases (CVDs). Combining these powerful techniques aids in understanding disease mechanisms and developing precise, individualized treatments for better patient outcomes.
Area of Science:
- Cardiovascular Research
- Molecular Biology
- Genomics
Background:
- Cardiovascular diseases (CVDs) remain a leading cause of global mortality despite advances in treatment.
- Current understanding of CVDs lacks detailed cellular and spatial resolution, hindering precise risk stratification and targeted therapies.
- New transcriptomic technologies offer unprecedented opportunities to explore cardiovascular biology and disease mechanisms.
Purpose of the Study:
- To review the applications of single-cell RNA sequencing and spatial transcriptomics in cardiovascular research.
- To highlight how these technologies advance the understanding of cardiovascular disease (CVD) mechanisms and cellular heterogeneity.
- To emphasize the potential for improved diagnosis, risk stratification, and personalized treatment of CVDs.
Main Methods:
- Review of single-cell RNA sequencing (scRNA-seq) for high-resolution cellular analysis.
- Overview of spatial transcriptomics for mapping gene expression within tissue context.
- Integration of scRNA-seq and spatial transcriptomics for comprehensive cardiovascular research.
Main Results:
- Single-cell RNA sequencing reveals cellular and molecular heterogeneity in the heart.
- Spatial transcriptomics provides crucial information on cell localization and intercellular interactions.
- Combined approaches enhance understanding of disease progression and identify key cell populations involved in CVDs.
Conclusions:
- Integrating single-cell RNA sequencing and spatial transcriptomics provides a multi-dimensional view of cardiovascular disease (CVD) progression.
- These advanced techniques are crucial for deciphering complex disease pathways and patient subgroup variations.
- The findings support the development of precise, individualized therapies for cardiovascular diseases (CVDs).
Abstract:
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.
