Abstract 4361412: Comparative metabolic signatures of arterial calcification in human cadaver coronary arteries and a porcine model via MALDI mass spectrometry

Introduction: Arterial calcification contributes significantly to cardiovascular morbidity, yet its metabolic mechanisms remain poorly understood. This study aimed to characterize the spatial metabolic landscape of vascular calcification using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in both human and animal tissues. Methods: Fresh calcified coronary arteries from cadaver hearts (n=8) and femoral arteries from a porcine model of arterial calcification (n=10, including calcified and controls) were snap-frozen and underwent untargeted metabolomic profiling using a UV-laser MALDI source (Spectroglyph LLC) coupled with a Thermo Q Exactive HF-X Orbitrap MS. Adjacent tissue sections were stained with Von Kossa to identify calcified regions (VK+), which were annotated and co-registered with MALDI-MSI datasets to correlate spatial metabolic features with mineralization. Metabolite analysis (>1550 features) was performed using QuPath and SCiLS, with statistical comparison by PCA and Pearson correlation (p<0.001). Results: In human coronary arteries, PCA plot indicated distinct metabolic profile between VK- and VK+ samples (Fig.1A). Spatial metabolomics analysis revealed a distinct set of 79 metabolites adjacent to calcified regions, primarily glycerophospholipids (38), sphingolipids (6), amino acid derivatives (5), fatty acids (3), and nucleosides&nucleotides (2), with 49 significantly elevated and spatially localized to calcified regions. In the porcine model, difference between VK+ and VK- regions was found (Fig.1B) and a robust panel of 90 metabolites was significantly associated with calcification (|r|>0.5), the majority of which were amino acid derivatives (32), fatty acids (6), nucleosides and nucleosides (5), and glycerophospholipids (4), consistent with human coronary artery results. Notably, 22 metabolites, including adenosine monophosphate, pyruvate, and phosphatidylinositol (20:2/16:0), were associated with pathways such as glycolysis and purine metabolism, mirrored the metabolic alterations observed in human tissues, supporting the translational relevance of the model. Conclusion: This study demonstrates the power of MALDI-MSI for high-resolution spatial metabolomic profiling of arterial calcification. The identified metabolite signatures provide new insights into the pathobiology of arterial calcification and may inform future therapeutic strategies targeting vascular mineralization and early biomarker discovery.

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Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4361412
Primary Topic
Cardiovascular Disease and Adiposity
Type
article
Field-Weighted Citation Impact
0.00
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article

Abstract 4361412: Comparative metabolic signatures of arterial calcification in human cadaver coronary arteries and a porcine model via MALDI mass spectrometry

Aleksandra Gruslova, Marc Feldman, Shiqi Zhang, Ian M. Tamayo et al.
Circulation
Cardiovascular Disease and Adiposity
article

Abstract 4361412: Comparative metabolic signatures of arterial calcification in human cadaver coronary arteries and a porcine model via MALDI mass spectrometry

Aleksandra Gruslova, Marc Feldman, Shiqi Zhang, Ian M. Tamayo, Kumar Sharma
article en

Abstract

Introduction: Arterial calcification contributes significantly to cardiovascular morbidity, yet its metabolic mechanisms remain poorly understood. This study aimed to characterize the spatial metabolic landscape of vascular calcification using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) in both human and animal tissues. Methods: Fresh calcified coronary arteries from cadaver hearts (n=8) and femoral arteries from a porcine model of arterial calcification (n=10, including calcified and controls) were snap-frozen and underwent untargeted metabolomic profiling using a UV-laser MALDI source (Spectroglyph LLC) coupled with a Thermo Q Exactive HF-X Orbitrap MS. Adjacent tissue sections were stained with Von Kossa to identify calcified regions (VK+), which were annotated and co-registered with MALDI-MSI datasets to correlate spatial metabolic features with mineralization. Metabolite analysis (>1550 features) was performed using QuPath and SCiLS, with statistical comparison by PCA and Pearson correlation (p<0.001). Results: In human coronary arteries, PCA plot indicated distinct metabolic profile between VK- and VK+ samples (Fig.1A). Spatial metabolomics analysis revealed a distinct set of 79 metabolites adjacent to calcified regions, primarily glycerophospholipids (38), sphingolipids (6), amino acid derivatives (5), fatty acids (3), and nucleosides&nucleotides (2), with 49 significantly elevated and spatially localized to calcified regions. In the porcine model, difference between VK+ and VK- regions was found (Fig.1B) and a robust panel of 90 metabolites was significantly associated with calcification (|r|>0.5), the majority of which were amino acid derivatives (32), fatty acids (6), nucleosides and nucleosides (5), and glycerophospholipids (4), consistent with human coronary artery results. Notably, 22 metabolites, including adenosine monophosphate, pyruvate, and phosphatidylinositol (20:2/16:0), were associated with pathways such as glycolysis and purine metabolism, mirrored the metabolic alterations observed in human tissues, supporting the translational relevance of the model. Conclusion: This study demonstrates the power of MALDI-MSI for high-resolution spatial metabolomic profiling of arterial calcification. The identified metabolite signatures provide new insights into the pathobiology of arterial calcification and may inform future therapeutic strategies targeting vascular mineralization and early biomarker discovery.

CirculationVol. 152(Suppl_3)
The University of Texas at San Antonio Health Science Center (US), The University of Texas at San Antonio (US), The University of Texas Health Science Center at Houston (US)
Openalex Percentile: Top 51%
Cardiovascular Disease and Adiposity
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