TY - JOUR
T1 - Multimodal landscape of atherosclerotic plaques
T2 - A spatial omics approach with mass spectrometry imaging
AU - Joshi, Robin
AU - Tang, Soon Yew
AU - Das, Ujjalkumar Subhash
AU - Boehmler, Daniel J.
AU - Mrčela, Antonijo
AU - Lordan, Ronan
AU - Petersson, E. James
AU - Weljie, Aalim M.
AU - FitzGerald, Garret A.
N1 - Publisher Copyright:
© 2025 The Authors
PY - 2025/12/15
Y1 - 2025/12/15
N2 - Atherosclerotic plaques are complex and heterogeneous structures, originating as fatty streaks in the vasculature and formed by the accumulation of lipids and foam cells. Over time, these lesions progress as inflammation, smooth muscle cell proliferation and phenotypic switching, and extracellular matrix deposition contribute to plaque growth, culminating in their fracture, reactive thrombogenesis, and a cardiovascular event such as myocardial infarction and stroke. Traditional bulk mass spectrometry (MS) analysis has yielded critical insights into the molecular mechanisms of plaque formation and disease progression, but it is unable to determine the spatial heterogeneity and microenvironmental complexity within the lesion. Recent advances in mass spectrometry imaging (MSI) based omics, including spatial lipidomics, proteomics, and metabolomics, have enabled unprecedented visualization of molecular distribution in atherosclerotic plaques at cellular resolution. These techniques promise to elucidate the distinct cellular crosstalk, lesion vulnerability, and sex-specific disease mechanisms that contribute to plaque development and rupture. This review examines the recent advances in MS-based spatial omics and their application to atherosclerotic plaques in both experimental models and human samples. We highlight recent findings, explore their implications for precision medicine and translational research, and discuss current challenges in sample preparation and data integration. Despite challenges, we suggest approaches for integration of MS-based spatial omics using artificial intelligence (AI) to enhance data integration, interpretation, and translational applications in atherosclerosis research. These advances promise to broaden our understanding of atherosclerosis and identify novel therapeutic targets to limit the burden of cardiovascular disease.
AB - Atherosclerotic plaques are complex and heterogeneous structures, originating as fatty streaks in the vasculature and formed by the accumulation of lipids and foam cells. Over time, these lesions progress as inflammation, smooth muscle cell proliferation and phenotypic switching, and extracellular matrix deposition contribute to plaque growth, culminating in their fracture, reactive thrombogenesis, and a cardiovascular event such as myocardial infarction and stroke. Traditional bulk mass spectrometry (MS) analysis has yielded critical insights into the molecular mechanisms of plaque formation and disease progression, but it is unable to determine the spatial heterogeneity and microenvironmental complexity within the lesion. Recent advances in mass spectrometry imaging (MSI) based omics, including spatial lipidomics, proteomics, and metabolomics, have enabled unprecedented visualization of molecular distribution in atherosclerotic plaques at cellular resolution. These techniques promise to elucidate the distinct cellular crosstalk, lesion vulnerability, and sex-specific disease mechanisms that contribute to plaque development and rupture. This review examines the recent advances in MS-based spatial omics and their application to atherosclerotic plaques in both experimental models and human samples. We highlight recent findings, explore their implications for precision medicine and translational research, and discuss current challenges in sample preparation and data integration. Despite challenges, we suggest approaches for integration of MS-based spatial omics using artificial intelligence (AI) to enhance data integration, interpretation, and translational applications in atherosclerosis research. These advances promise to broaden our understanding of atherosclerosis and identify novel therapeutic targets to limit the burden of cardiovascular disease.
KW - Artificial intelligence
KW - Atherosclerosis
KW - Lipids
KW - Mass spectrometry imaging (MSI)
KW - Proteins
KW - spatial omics
UR - https://www.scopus.com/pages/publications/105017425797
U2 - 10.1016/j.aca.2025.344723
DO - 10.1016/j.aca.2025.344723
M3 - Article
C2 - 41167886
AN - SCOPUS:105017425797
SN - 0003-2670
VL - 1379
JO - Analytica Chimica Acta
JF - Analytica Chimica Acta
M1 - 344723
ER -