Lipid signature of advanced human carotid atherosclerosis assessed by mass spectrometry imaging.

Carotid atherosclerosis is a risk factor for ischemic stroke, one of the main causes of mortality and disability worldwide. The disease is characterized by plaques, heterogeneous deposits of lipids, and necrotic debris in the vascular wall, which grow gradually and may remain asymptomatic for decades. However, at some point a plaque can evolve to a high-risk plaque phenotype, which may trigger a cerebrovascular event. Lipids play a key role in the development and progression of atherosclerosis, but the nature of their involvement is not fully understood. Using matrix-assisted laser desorption/ionization mass spectrometry imaging, we visualized the distribution of approximately 200 different lipid signals, originating of >90 uniquely assigned species, in 106 tissue sections of 12 human carotid atherosclerotic plaques. We performed unsupervised classification of the mass spectrometry dataset, as well as a histology-directed multivariate analysis. These data allowed us to extract the spatial lipid patterns associated with morphological plaque features in advanced plaques from a symptomatic population, revealing spatial lipid patterns in atherosclerosis and their relation to histological tissue type. The abundances of sphingomyelin and oxidized cholesteryl ester species were elevated specifically in necrotic intima areas, whereas diacylglycerols and triacylglycerols were spatially correlated to areas containing the coagulation protein fibrin. These results demonstrate a clear colocalization between plaque features and specific lipid classes, as well as individual lipid species in high-risk atherosclerotic plaques.

Micro Spectroscopic Photoacoustic (µsPA) imaging of advanced carotid atherosclerosis.

Atherosclerosis is a lipid-driven and an inflammatory disease of the artery walls. The composition of atherosclerotic plaque stratifies the risk of a specific plaque to cause a cardiovascular event. In an optical resolution photoacoustic microscopy setup, of 45 µm resolution, we extracted plaque lipid photoacoustic (PA) spectral signatures of human endarterectomy samples in the range of 1150-1240 nm, using matrix assisted laser desorption ionization mass spectrometry imaging as a reference. We found plaque PA signals to correlate best with sphingomyelins and cholesteryl esters. PA signal spectral variations within the plaque area were compared to reference molecular patterns and absorption spectra of lipid laboratory standards. Variability in the lipid spectroscopic features extracted by principal component analysis of all samples revealed three distinct components with peaks at: 1164, 1188, 1196 and 1210 nm. This result will guide the development of PA-based atherosclerosis disease staging capitalizing on lipidomics of atherosclerotic tissue.

Data Processing Pipeline for Lipid Profiling of Carotid Atherosclerotic Plaque with Mass Spectrometry Imaging.

Atherosclerosis is a lipid and inflammation-driven disease of the arteries that is characterized by gradual buildup of plaques in the vascular wall. A so-called vulnerable plaque, consisting of a lipid-rich necrotic core contained by a thin fibrous cap, may rupture and trigger thrombus formation, which can lead to ischemia in the heart (heart attack) or in the brain (stroke). In this study, we present a protocol to investigate the lipid composition of advanced human carotid plaques using matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI), providing a framework that should enable the discrimination of vulnerable from stable plaques based on lipid composition. We optimized the tissue preparation and imaging methods by systematically analyzing data from three specimens: two human carotid endarterectomy samples (advanced plaque) and one autopsy sample (early stage plaque). We show a robust data reduction method and evaluate the variability of the endarterectomy samples. We found diacylglycerols to be more abundant in a thrombotic area compared to other plaque areas and could distinguish advanced plaque from early stage plaque based on cholesteryl ester composition. We plan to use this systematic approach to analyze a larger dataset of carotid atherosclerotic plaques.