HeartMAP: A multi-chamber spatial framework for cardiac cell-cell communication

Understanding cell-cell communication within and between the four distinct cardiac chambers is fundamental to elucidating cardiac function and disease mechanisms. Each chamber exhibits unique cellular and molecular characteristics that reflect specialised physiological roles, yet existing frameworks for mapping chamber-specific intercellular networks have remained limited. Here, we present HeartMAP (Heart Multi-chamber Analysis Platform), a computational framework that infers cardiac cell-cell communication networks at chamber resolution through integration of single-cell RNA-seq co-expression patterns and ligand-receptor interaction databases. Using a dataset of 287,269 cells from seven healthy human heart donors (Single Cell Portal SCP498), we identified chamber-specific cell populations, communication networks, and therapeutic targets. HeartMAP employs a progressive three-tier analytical approach comprising basic pipeline analysis, advanced communication modelling and multi-chamber atlas construction to reveal both conserved and chamber-specific signalling pathways; cross-chamber correlation analysis demonstrated the highest similarity between ventricles (r = 0.985) and the lowest between left atrium and left ventricle (r = 0.870), reflecting functional specialisation. Communication hub analysis identified atrial cardiomyocytes and adipocytes as key signalling centres with hub scores of 0.037-0.047, while differential expression analysis revealed over 150 significantly different genes per chamber pair. These findings establish a molecular foundation for precision cardiology approaches, enabling chamber-specific therapeutic strategies that could improve treatment outcomes for cardiovascular diseases. HeartMAP is freely available as a Python package than can be installed using "pip install heartmap", the package's documentation can be found on https://pypi.org/project/heartmap/, it can also be accessed via a user-friendly web interface freely available at https://huggingface.co/spaces/Tumo505/heartmap-cell-analysis.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.11.015
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

HeartMAP: A multi-chamber spatial framework for cardiac cell-cell communication

Thanyani Pandelani, Harry Ngwangwa, Lulu Wang, Tumo Kgabeng
Computational and Structural Biotechnology Journal
Single-cell and spatial transcriptomics
article

HeartMAP: A multi-chamber spatial framework for cardiac cell-cell communication

Thanyani Pandelani, Harry Ngwangwa, Lulu Wang, Tumo Kgabeng
article en

Abstract

Understanding cell-cell communication within and between the four distinct cardiac chambers is fundamental to elucidating cardiac function and disease mechanisms. Each chamber exhibits unique cellular and molecular characteristics that reflect specialised physiological roles, yet existing frameworks for mapping chamber-specific intercellular networks have remained limited. Here, we present HeartMAP (Heart Multi-chamber Analysis Platform), a computational framework that infers cardiac cell-cell communication networks at chamber resolution through integration of single-cell RNA-seq co-expression patterns and ligand-receptor interaction databases. Using a dataset of 287,269 cells from seven healthy human heart donors (Single Cell Portal SCP498), we identified chamber-specific cell populations, communication networks, and therapeutic targets. HeartMAP employs a progressive three-tier analytical approach comprising basic pipeline analysis, advanced communication modelling and multi-chamber atlas construction to reveal both conserved and chamber-specific signalling pathways; cross-chamber correlation analysis demonstrated the highest similarity between ventricles (r = 0.985) and the lowest between left atrium and left ventricle (r = 0.870), reflecting functional specialisation. Communication hub analysis identified atrial cardiomyocytes and adipocytes as key signalling centres with hub scores of 0.037-0.047, while differential expression analysis revealed over 150 significantly different genes per chamber pair. These findings establish a molecular foundation for precision cardiology approaches, enabling chamber-specific therapeutic strategies that could improve treatment outcomes for cardiovascular diseases. HeartMAP is freely available as a Python package than can be installed using "pip install heartmap", the package's documentation can be found on https://pypi.org/project/heartmap/, it can also be accessed via a user-friendly web interface freely available at https://huggingface.co/spaces/Tumo505/heartmap-cell-analysis.

Computational and Structural Biotechnology JournalVol. 27
Reykjavík University (IS), University of South Africa (ZA)
Openalex Percentile: Top 70%
Single-cell and spatial transcriptomics
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