Abstract
Severe aortic stenosis (AS) is prevalent in adults ≥ 65 years, a significant cause of morbidity and mortality, with no medical therapy. Lipid and proteomic alterations of human AS tissue were determined using mass spectrometry imaging (MSI) and liquid chromatography electrospray ionization tandem mass spectrometry (LC–ESI–MS/MS) to understand histopathology, potential biomarkers of disease, and progression from non-calcified to calcified phenotype. A reproducible MSI method was developed using healthy murine aortic valves (n = 3) and subsequently applied to human AS (n = 2). Relative lipid levels were spatially mapped and associated with different microdomains. Proteomics for non-calcified and calcified microdomains were performed to ascertain differences in expression. Increased pro-osteogenic and inflammatory lysophosphatidylcholine (LPC) 16:0 and 18:0 were co-localized with calcified microdomains. Proteomics analysis identified differential patterns in calcified microdomains with high LPC and low cholesterol as compared to non-calcified microdomains with low LPC and high cholesterol. Calcified microdomains had higher levels of: apolipoproteins (Apo) B-100 (p < 0.001) and Apo A-IV (p < 0.001), complement C3 and C4-B (p < 0.001), C5 (p = 0.007), C8 beta chain (p = 0.013) and C9 (p = 0.010), antithrombotic proteins alpha-2-macroglobulin (p < 0.0001) and antithrombin III (p = 0.002), and higher anti-calcific fetuin-A (p = 0.02), while the osteoblast differentiating factor transgelin (p < 0.0001), extracellular matrix proteins versican, prolargin, and lumican ( p < 0.001) and regulator protein complement factor H (p < 0.001) were higher in non-calcified microdomains. A combined lipidomic and proteomic approach provided insight into factors potentially contributing to progression from non-calcified to calcific disease in severe AS. Additional studies of these candidates and protein networks could yield new targets for slowing progression of AS.
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Acknowledgements
We acknowledge Edward Nieves’ assistance with mass spectrometry, Amanda Beck, Jeffrey Harding and Barbara Canella’s assistance in sectioning and photomicrography (all from the Montefiore Health System and Albert Einstein College of Medicine). We thank Genevieve T. Aguilan for composing Fig. 1.
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Funded by the Department of Medicine, Division of Cardiology at Montefiore Health System and Albert Einstein College of Medicine, with additional support from American Heart Association Mentored Clinical and Population Award 17MCPRP33630098, the Empire Clinical Research Investigator Program, and National Institutes of Health 1K23HL146982-01A1 (AEB), National Institutes of Health UL1TR001073, National Institutes of Health 1S10RR025128 and Shared Instrumentation Grant 1S10RR029398-01 (RHA).
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JL, JA, LMW, RHA, AEB: conception and design, collection and assembly of data, and data analysis and interpretation, manuscript writing, manuscript editing and final approval of manuscript; RS, FN: collection and assembly of data and final approval of manuscript.
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AEB served as site principal investigator for multi-center trials sponsored by Abbott and CSL-Behring in the past year, for which her institution received compensation and received an honorarium from ClearView Healthcare Partners, LLC.
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Lim, J., Aguilan, J.T., Sellers, R.S. et al. Lipid mass spectrometry imaging and proteomic analysis of severe aortic stenosis. J Mol Hist 51, 559–571 (2020). https://doi.org/10.1007/s10735-020-09905-5
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DOI: https://doi.org/10.1007/s10735-020-09905-5