Multidimensional profiling of cellular interactions in heart failure (HF) patients.

Abstract

Heart failure (HF) remains a major global health burden, with its subcellular pathophysiology still not fully understood. This thesis establishes an optimised Imaging Mass Cytometry (IMC) platform tailored to cardiac tissue, introducing a novel methodology combining imaging with time-of-flight mass cytometry into cardiac research. The aim is to deepen understanding of the HF tissue landscape through single-cell profiling and spatial analysis.

We recruited patients with ischaemic cardiomyopathy (ICM, n=8) and dilated cardiomyopathy (DCM, n=8), collecting apical left ventricular (LV) tissue during LV assist device implantation. A 37-marker metal-conjugated antibody panel specific to cardiac tissue was developed, alongside optimised tissue processing and staining protocols. An automated pre-processing and deep learning cell segmentation pipeline was established to identify cardiac cell types. Using unbiased clustering, we characterised macrophage, T cell, fibroblast, and cardiomyocyte subpopulations, along with other immune and neuronal cells. Spatial interaction data were extracted from fibrotic regions.

The IMC platform enabled high-resolution, multiplexed imaging across all markers, offering detailed insight into HF tissue composition. Notably, we identified a previously unreported cardiomyocyte population expressing ACTN2 and podoplanin in ICM patients. DCM hearts showed greater infiltration of pro-inflammatory cells (e.g. M1 macrophages, cytotoxic T cells) and increased lymphatic vessel formation, while ICM tissues had more heterogeneous fibroblast populations. A myofibroblast-like population correlated with scar proportion, suggesting potential as a fibrosis predictor. We also defined distinct cellular niches and interactions.

This work demonstrates a powerful IMC approach for single-cell, spatially resolved cardiac profiling. Our findings offer novel insight into HF pathogenesis and highlight cell populations with potential for aetiology-specific therapies.