Abhijeet Rajendra Sonawane
Michel Pucéat
Hanjoong Jo- 1Center for Interdisciplinary Cardiovascular Sciences and Center for Excellences in Vascular Biology, Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
- 2INSERM, Cardiovascular and Nutrition Center (C2VN), Aix-Marseille University, Marseille, France
- 3Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States
Editorial on the Research Topic
Single-cell OMICs analyses in cardiovascular diseases
Single-cell technologies have revolutionized the understanding of biological and pathological processes. They are now the driving force of cellular profiling across cardiovascular diseases (CVD) (1–5). They have enabled analysis of cellular composition with tissues and cell cultures, revealing the subtle nuances of heterogeneity among cell types and uncovering the dynamic changes in communication and signaling patterns triggered by disease.
Various omics modalities data can be generated now at single-cell resolution including joint and concomitant assays such as single cell RNA-sequencing (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) for transcriptomics profiling, single cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) for cell type specific profiling of epigenetic, and in turn, regulatory landscape, and cellular indexing of transcriptomes and epitopes-seq (CITE-seq) for profiling the surface proteins on different cell types. Recent advances, including spatial transcriptomics and single cell proteomics (6, 7) have allowed us to spatially resolve cell subtypes in active areas of disease tissues. These multiomics data types allow us to develop novel computational and bioinformatics methods to obtain a multidimensional view of the disease to uncover mechanisms, explain etiologies, and discover biomarkers. Single-cell data analysis tools such as Seurat (8, 9), and SingleCellExperiment (10) have democratized the capability of single cell analysis by beckoning researchers of all backgrounds to embark on a journey of exploration, regardless of their level of bioinformatics expertise. Applications such as SCHNAPPs have also enabled bench scientists to perform basic single cell analyses (11).
Understanding the impact of single cell research on CVD, including vascular and heart valve diseases, is crucial as it allows us to evaluate advancements in the field. Specific cells such as immune cells as well as cell-cell communication play a significant role in disease pathogenesis. Identifying unique cell types (cell subpopulations) and their behavior in the diseased tissue can elucidate their role in altering tissue structure and function.
In this special research topic, we intended to create a forum for current advances in single-cell techniques applied to cardiovascular disease areas. We invited articles on single cell technique and methods development, probing cellular heterogeneity, modern laboratory and in silico techniques, and its application to various vascular and valvular diseases. We received 18 submissions, out of which we selected 10 high quality peer reviewed articles for our collections. Below, we provide a brief overview of articles in this collection.
The systematic review conducted according to PRISMA standards from McQueen et al. provides us with extensive overview of the current state of single-cell research in cardiovascular medicine. Using proper exclusion and inclusion criterion, addressing the risk of bias analyses using tools, they provide a narrative synthesis of 34 articles (out of 791). They provide a comprehensive review of studies which include various single cell omics modalities such as scRNA-seq, scATAC-seq, CITE-seq, or combination thereof. They also include cell-type-specific discussions of the progress done in the research in cardiovascular diseases including, smooth muscle cells, macrophages, endothelial cells, and lymphocytes. Results from tissue and blood-specific analyses which included atherosclerotic lesions, cardiac and adventitial tissues, and blood, are also summarized to provide the reader important processes involved in atherosclerosis development and progression. Hu et al. review recent advances in scRNA-seq technology along with comparison of various gene amplification methods. They also discuss some of the standard workflow associated with single cell studies applied in CVD medicine. Su et al. present a focused review on role of diversity and abundance of immune cells such as macrophages, dendritic cells, and T cells, in cardiac homeostasis and effect of their infiltration on the diseased areas. They focus on immune heterogeneity in atherosclerosis, myocardial ischemia, and heart failure along with suggesting potentially new marker genes.
Li et al. continue the discussion on heart failure using the role of, relatively little explored, neutrophile extracellular traps (NET). Using conventional bioinformatic analysis on bulk and single cell RNA-seq datasets, they identify differentially expressed NET-related genes followed by neutrophile cell heterogeneity in heart failure and normal cardiac tissues followed by cellular differentiation and communication analyses identifying biomarkers associated with NETs in heart failure. Zhang et al. study myocardial infarction (MI) using public datasets and standard bioinformatics pipeline to identify IL1B and TLR2 as differentially expressed genes (DEGs) with most neighbors in protein-protein interaction network (PPI) in MI. While their findings provide valuable insights, there is a need for cautious interpretation due to the limitations inherent in the utilization of public datasets. Additionally, several seminal scRNA-seq studies highlighted the importance of sexual differences at the cell level in CVD. Marrero et al. study on sexual differences in peripheral artery disease (PAD) etiology utilizing scRNA-seq data. Mizrak et al. (12) using spatial transcriptomics uncovered male-specific smooth muscle cells subpopulation playing a key role in human thoracic aortic aneurysm. ScRNA-seq data from Shin et al. (13) allow to delineate the sex-difference in endothelial cells characteristics and function providing new clues about atherosclerotic diseases. These studies show that inclusion of biological sex in a proper experimental design (14) is of utmost importance to consider representativeness of the sample population and potential confounding variables.
Autoimmune conditions like cardiac and pulmonary sarcoidosis (CS/PS) are understudied yet potentially impactful on cardiovascular health. Daoud et al. conducted a systematic review using single-cell RNA-seq datasets to investigate PS and CS. They found increased immune cells and stromal populations in sarcoidosis tissues compared to controls, with sarcoidosis T cells and macrophages showing attenuated activation profiles. Abdominal aortic aneurysm (AAA) involves complex immune cell interactions and may exhibit autoimmune characteristics. Elster et al. studied the clonal expansion of T cells and B cells in AAA tissue using sc-RNA T cell receptor (TCR) and B cell receptor (BCR) sequencing using porcine pancreatic elastase mouse model. Wu et al. investigated macrophage regulation in AAA using scRNA-seq datasets from mouse models and humans. They identified IL-1B and THBS1 as co-upregulated genes across datasets, highlighting the complex immune involvement in AAA. Similarly, thoracic arch aneurysm (TAA), linked to bicuspid aortic valves (BAV), was investigated by Liu et al., revealing potential therapeutic genes. These studies enhance our grasp of aortic aneurysm pathophysiology, urging further investigation for improved cardiovascular disease management.
To summarize, the emergence of single-cell technologies has completely transformed our comprehension of cellular dynamics within cardiovascular disorders, notably in dissecting the intricate cellular compositions, diversities, and signaling modifications associated with diseases such as heart valve diseases and atherosclerosis. Through thorough assessments and leading-edge investigations, researchers have elucidated the presence and functions of diverse vascular and immune cell populations, indicated novel biomarkers, and underlined the molecular pathways influencing disease progression. These studies now complemented with spatial transcriptomics indicate the need of development of sophisticated bioinformatics tools for the integration of multiomics methodologies, which are needed to unravel the intricate complexities of cardiovascular pathophysiology, that will open avenues for targeted treatments and enhanced patient outcomes.
Author contributions
ARS: Writing – original draft, Writing – review & editing. MP: Writing – review & editing. HJ: Writing – review & editing.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article.
ARS acknowledges funding support from American Heart Association (23CDA1052394/Sonawane AR/2023). HJ's work was supported by funding from National Institutes of Health grants HL119798, HL139757, and HL151358 and a Wallace H. Coulter Distinguished Faculty Chair Fund.
Acknowledgments
The editors would like to thank all the authors and expert reviewers who have participated in the preparation and evaluation of manuscripts presented in this Research Topic.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
The handling editor MR declared a past co-authorship with the author ARS.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Iqbal F, Schlotter F, Becker-Greene D, Lupieri A, Goettsch C, Hutcheson JD, et al. Sortilin enhances fibrosis and calcification in aortic valve disease by inducing interstitial cell heterogeneity. Eur Heart J. (2023) 44(10):885–898. doi: 10.1093/eurheartj/ehac818
2. Sonawane AR, Aikawa E, Aikawa M. Connections for matters of the heart: network medicine in cardiovascular diseases. Front Cardiovasc Med. (2022) 9:873582. doi: 10.3389/fcvm.2022.873582
3. Kumar S, Andueza A, Kim J, Kang DW, Jo H. Isolation of endothelial cells from the lumen of mouse carotid arteries for single-cell multi-omics experiments. J Vis Exp. (2021) (176). doi: 10.3791/63128
4. Andueza A, Kumar S, Kim J, Kang DW, Mumme HL, Perez JI, et al. Endothelial reprogramming by disturbed flow revealed by single-cell RNA and chromatin accessibility study. Cell Rep. (2020) 33:108491. doi: 10.1016/j.celrep.2020.108491
5. Kalluri AS, Vellarikkal SK, Edelman ER, Nguyen L, Subramanian A, Ellinor PT, et al. Single-cell analysis of the normal mouse aorta reveals functionally distinct endothelial cell populations. Circulation. (2019) 140:147–63. doi: 10.1161/CIRCULATIONAHA.118.038362
6. Tian L, Chen F, Macosko EZ. The expanding vistas of spatial transcriptomics. Nat Biotechnol. (2023) 41:773–82. doi: 10.1038/s41587-022-01448-2
7. Gatto L, Aebersold R, Cox J, Demichev V, Derks J, Emmott E, et al. Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments. Nat Methods. (2023) 20:375–86. doi: 10.1038/s41592-023-01785-3
8. Stuart T, Satija R. Integrative single-cell analysis. Nat Rev Genet. (2019) 20:257–72. doi: 10.1038/s41576-019-0093-7
9. Butler A, Hoffman P, Smibert P, Papalexi E, Satija R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat Biotechnol. (2018) 36:411–20. doi: 10.1038/nbt.4096
10. Amezquita RA, Lun ATL, Becht E, Carey VJ, Carpp LN, Geistlinger L, et al. Orchestrating single-cell analysis with bioconductor. Nat Methods. (2020) 17:137–45. doi: 10.1038/s41592-019-0654-x
11. Jagla B, Libri V, Chica C, Rouilly V, Mella S, Puceat M, et al. SCHNAPPs - single cell sHiNy APPlication(s). J Immunol Methods. (2021) 499:113176. doi: 10.1016/j.jim.2021.113176
12. Mizrak D, Zhao Y, Feng H, Macaulay J, Tang Y, Sultan Z, et al. Single-molecule spatial transcriptomics of human thoracic aortic aneurysms uncovers calcification-related CARTPT-expressing smooth muscle cells. Arterioscler Thromb Vasc Biol. (2023) 43:2285–97. doi: 10.1161/ATVBAHA.123.319329
13. Shin J, Hong J, Edwards-Glenn J, Krukovets I, Tkachenko S, Adelus ML, et al. Unraveling the role of sex in endothelial cell dysfunction: evidence from lineage tracing mice and cultured cells. Arterioscler Thromb Vasc Biol. (2024) 44:238–53. doi: 10.1161/ATVBAHA.123.319833
Keywords: cardiovascular diseases, single-cell omics, data analysis, atherosclerosis, heart valve disease (HVD)
Citation: Sonawane AR, Pucéat M and Jo H (2024) Editorial: Single-cell OMICs analyses in cardiovascular diseases. Front. Cardiovasc. Med. 11:1413184. doi: 10.3389/fcvm.2024.1413184
Received: 6 April 2024; Accepted: 23 April 2024;
Published: 6 May 2024.
Edited and Reviewed by: Maximillian A. Rogers, Intellia Therapeutics, Inc., United States
© 2024 Sonawane, Pucéat and Jo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Abhijeet Rajendra Sonawane asonawane@bwh.harvard.edu