Spatial proteomics of the human atherosclerotic microenvironment reveals heterogeneity in intra-plaque proteomes and extracellular matrix remodeling

The heterogeneity of atherosclerotic plaques is critical for their vulnerability to rupture and the associate risk of cardiovascular events. Most proteomic studies have only examined bulk changes, potentially obscuring key spatial differences in protein content and abundance. Here we report a high-resolution spatial proteomics workflow that allows exploration of the molecular landscape of human plaques and murine myocardial tissue. This combines laser capture microdissection of tissue areas (50,000 µm² from 10 µm-thick sections, corresponding to < 30 cells), with high-sensitivity ion-mobility mass spectrometry, allowing spatial profiling of cellular and extracellular matrix (ECM) proteomes. Over 2700 proteins were detected, revealing substantial intra-plaque proteome heterogeneity across distinct regions (lipid-rich, media layers, shoulder regions, necrotic core, intima) and distance from the lumen into the artery wall. Strong inverse correlations were detected between proteases (e.g. cathepsin-B) and core structural ECM components (e.g. perlecan, HSPG2) consistent with active ECM remodeling. Analysis of media layers indicated distinct protein signatures associated with smooth muscle contraction and cell-cell communication. Blood coagulation signatures, including platelet degranulation and fibrin clot formation were enriched at the intimal surface. Inflammatory markers (clusters of differentiation 4 and 68, CD4/CD68; vascular cell adhesion molecular 1, VCAM1) and vascular damage markers (tenascin-C, TNC) were enriched in shoulder regions. The necrotic core was dominated by blood proteins, consistent with intra-plaque hemorrhage. The capacity of this workflow to resolve changes over modest distances (225 µm) provides unprecedented insights into the spatial organisation of the atherosclerotic microenvironment, offering a powerful tool for elucidating plaque biology and identifying potential therapeutic targets.