Project
Decoding human heart and kidney tissues using novel functional and spatial genomics tools
In our research we focus on human tissue data analysis to uncover novel principles of disease and to identify therapeutic approaches. A major focus is fibrosis—the maladaptive scarring response that drives organ failure across diseases. In the heart, fibrosis accompanies remodeling after injury and in chronic heart failure, yet its cellular origins and sustaining circuits in humans remain incompletely defined. We build large, well-annotated single-cell and spatial atlases from patient tissues to chart cellular states, their lineage relationships, and their spatial neighborhoods. Our central hypothesis is that specific cardiomyocyte states—particularly those associated with genome doubling and metabolic rewiring—emit cues that instruct stromal, vascular, and immune cells to form a non-regenerative, profibrotic niche. By integrating molecular readouts with histopathology and clinical metadata, we aim to expose causal interaction pathways and actionable targets that could interrupt fibrosis while preserving essential repair, ultimately informing precision diagnostics and anti-fibrotic therapies.
Project Details
Project term
July 18, 2024–August 8, 2025
Affiliations
RWTH Aachen University
Institute
Chair of Internal Medicine
Principal Investigator
Methods
We use molecular methods that characterize DNA, RNA, and protein at single-cell resolution and across intact tissue sections. Human myocardial samples are processed for single-nucleus RNA-seq and complementary chromatin accessibility profiling, combined with high-plex spatial transcriptomics and multiplexed immunofluorescence on adjacent sections. Histology-guided 3D reconstructions quantify scar architecture and microenvironments. Computationally, we perform stringent QC, batch-aware integration, and graph-based clustering; derive cell-state gene programs via non-negative matrix factorization; and apply pseudobulk and mixed-effects modeling for differential analyses. Pathway, regulatory-network, and ligand–receptor inference map putative intercellular circuits. Spatial statistics test neighborhood enrichment and gradient patterns around scar borders. Where available, DNA-content and image-based cytometry assess cardiomyocyte ploidy distributions. All analyses are reproducible through containerized workflows, with standardized metadata and versioned references to enable cross-cohort comparisons and future reuse.
Results
We generated a comprehensive human myocardial remodeling resource comprising >4 million nuclei/cells spanning health and diverse heart-disease etiologies. Interim analyses reveal robust identification of major cardiac lineages (cardiomyocytes, fibroblasts, endothelial cells, pericytes, smooth muscle cells, macrophages, lymphocytes) and dozens of conserved cell states. Within cardiomyocytes, we observe distinct transcriptional programs consistent with diploid-enriched and polyploid-enriched states, accompanied by metabolic re-patterning and stress-response modules. Spatial mapping shows these states are differentially positioned relative to fibrotic scars and vascular structures. Fibroblast heterogeneity includes activated myofibroblasts enriched for ECM synthesis and remodeling genes, co-localized with specific cardiomyocyte states. Inferred signaling highlights cardiomyocyte-to-fibroblast communication axes involving growth factors, cytokines, and ECM-modifying cues that are amplified in disease. Collectively, the data support a model in which specialized cardiomyocyte states help organize a profibrotic, non-regenerative tissue niche. We are finalizing analyses and preparing the resource and primary manuscript for submission.
Discussion
Our findings suggest a human, cell-resolved principle of myocardial disease: defined cardiomyocyte states—potentially linked to genome doubling and metabolic shifts—coordinate multicellular circuits that stabilize fibrosis. This reframes fibrosis as an emergent property of an ecosystem rather than a unidirectional fibroblast program, opening avenues to target upstream instructive signals. Immediate priorities include orthogonal validation (multiplex RNA/protein imaging, DNA-content assays, and spatial proteomics), perturbation in ex vivo human tissue slices and iPSC-derived cardiomyocyte–fibroblast co-cultures, and comparative analyses across etiologies to identify convergent, druggable pathways. Limitations include cross-sectional sampling, potential cohort biases, and the need to link molecular states to longitudinal outcomes. Next steps will integrate circulating biomarkers and machine-learning models for patient stratification. Longer-term, we will test whether modulating cardiomyocyte metabolic–transcriptional programs can tip the balance from scarring toward functional repair, with the conceptual and data resources made accessible to the community.
Additional Project Information
DFG classification: 205-12 Cardiology, Angiology
Cluster: CLAIX