Detailed methods are provided in the Supplemental Material . The data are available through https://cics.bwh.harvard.edu/multiomics_databases 11 .
In total, 25 AVs were used in this study. AV leaflets were obtained from AV replacement surgeries for severe AV stenosis (Brigham and Women’s Hospital (BWH) approved IRB protocol number: 2011P001703). Written informed consent was provided. In brief, human stenotic AVs were segmented into stages of disease progression: (1) non-diseased, (2) fibrotic, and (3) calcific under the guidance of near-infrared molecular imaging. Transition zones were excluded from all analyses. In total, 27 sub-samples were prepared for label-free proteomics and 9 for transcriptomics.
AVs obtained from three additional patients with severe aortic valve stenosis were used for tissue layer tandem mass tagging (TMT) proteomics and AVs from autopsy donors served as controls. Anatomical layer-specificity was facilitated by laser capture microdissection.
Side-specific in vitro layer calcification potential was evaluated through a migration assay on AV leaflets from eight additional patients with severe AV stenosis after inspection by a pathologist to distinguish the fibrosa from the ventricularis side, and calcification was assessed by Alizarin Red staining at day 21. All cells which underwent proteomics were cultured and passaged in vitro prior to protein collection.
AV whole tissue label-free peptide samples were examined with the Q Exactive mass spectrometer. AV tissue layer TMT and in vitro migration label-free peptide samples were analyzed with the LTQ-Orbitrap Elite mass spectrometer.
For pathway analysis, the protein sets corresponding to each layer and stage were tested for enrichment by a hypergeometric test and adjusted for multiple comparisons using the Benjamini-Hochberg method for controlling the false discovery rate (FDR). Pathway networks were constructed based on their gene overlap. Layer- and stage-specific subnetworks were generated from literature-curated physical protein interactions. The closeness of the calcific stage subnetwork to human diseases was evaluated using average shortest network distance.
In total, 25 AVs were used in this study. AV leaflets were obtained from AV replacement surgeries for severe AV stenosis (Brigham and Women’s Hospital (BWH) approved IRB protocol number: 2011P001703). Written informed consent was provided. In brief, human stenotic AVs were segmented into stages of disease progression: (1) non-diseased, (2) fibrotic, and (3) calcific under the guidance of near-infrared molecular imaging. Transition zones were excluded from all analyses. In total, 27 sub-samples were prepared for label-free proteomics and 9 for transcriptomics.
AVs obtained from three additional patients with severe aortic valve stenosis were used for tissue layer tandem mass tagging (TMT) proteomics and AVs from autopsy donors served as controls. Anatomical layer-specificity was facilitated by laser capture microdissection.
Side-specific in vitro layer calcification potential was evaluated through a migration assay on AV leaflets from eight additional patients with severe AV stenosis after inspection by a pathologist to distinguish the fibrosa from the ventricularis side, and calcification was assessed by Alizarin Red staining at day 21. All cells which underwent proteomics were cultured and passaged in vitro prior to protein collection.
AV whole tissue label-free peptide samples were examined with the Q Exactive mass spectrometer. AV tissue layer TMT and in vitro migration label-free peptide samples were analyzed with the LTQ-Orbitrap Elite mass spectrometer.
For pathway analysis, the protein sets corresponding to each layer and stage were tested for enrichment by a hypergeometric test and adjusted for multiple comparisons using the Benjamini-Hochberg method for controlling the false discovery rate (FDR). Pathway networks were constructed based on their gene overlap. Layer- and stage-specific subnetworks were generated from literature-curated physical protein interactions. The closeness of the calcific stage subnetwork to human diseases was evaluated using average shortest network distance.
