Spatiotemporal Multi-Omics–Derived Atlas of Calcific Aortic Valve Disease

HomeCirculationVol. 138, No. 4Spatiotemporal Multi-Omics–Derived Atlas of Calcific Aortic Valve Disease Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBSpatiotemporal Multi-Omics–Derived Atlas of Calcific Aortic Valve Disease Aldrin V. Gomes, PhD Aldrin V. GomesAldrin V. Gomes Aldrin V. Gomes, PhD, 187 Briggs Hall, One Shields Ave, Department of Neurobiology, Physiology, and Behavior, University of California, Davis, Davis, CA 95616. E-mail E-mail Address: [email protected] Department of Neurobiology, Physiology, and Behavior (A.V.G.) Department of Physiology and Membrane Biology (A.V.G.), University of California, Davis. Search for more papers by this author Originally published23 Jul 2018https://doi.org/10.1161/CIRCULATIONAHA.118.035431Circulation. 2018;138:394–396This article is a commentary on the followingSpatiotemporal Multi-Omics Mapping Generates a Molecular Atlas of the Aortic Valve and Reveals Networks Driving DiseaseArticle, see p 377Calcified aortic valve disease (CAVD) is complex and poorly understood and is an important disease to investigate, because it often results in aortic valve stenosis, which affects up to 13% of the US population.1–3 Calcification of the aortic valve results in impaired biomechanical functions and ultimately heart failure. The narrowing of the aortic valve opening by calcification leads to reduced blood flow and is referred to as aortic stenosis or aortic valve stenosis. The financial cost of monitoring and treating mild to severe aortic valve stenosis is substantial, because no early diagnostic test or pharmacological therapy is available for CAVD.4 In this issue of Circulation, Schlotter et al5 analyzed 25 human stenotic aortic valves by using transcriptomics and proteomics (both unlabeled and label-based tandem-mass–tagged approaches), which is the first application of multi-omics for CAVD. By using their extensive data and the human protein-protein interaction network, they were able to elucidate a comprehensive repository of potential molecular drivers of CAVD and to provide a high-resolution spatiotemporal atlas of the combined valvular cell, layer, and tissue proteome, as well.5Research on aortic valves (AVs) or heart values, in general, is limited by several factors, including intra- and interdonor variability, the heterogeneity of the leaflet’s layered structure (which is often ignored in analyses), and the lack of suitable in vitro culture models. What makes the investigation by Schlotter et al5 unique is the comprehensive approach that examined different CAVD disease stages (nondiseased and 2 disease stage–specific stages [fibrotic and calcific]), 3 CAVD anatomic tissue microlayers (fibrosa, spongiosa, and ventricularis), and CAVD fibrosa and ventricularis valvular interstitial cells (VICs). Investigation of CAVD at different disease stages is essential because this is a progressive disease with tissue remodeling occurring over many years.3 Added to the complexity of being a progressive disease is the aortic leaflet architecture that has not been previously investigated in significant detail.The AV is composed of 3 layers that all contain VICs: a collagenous fibrosa layer, an intermediate glycosaminoglycan-rich spongiosa layer, and an elastin-enriched ventricularis layer. VICs are mainly quiescent fibroblasts that are important in maintaining valvular homeostasis and leaflet mechanical properties.6,7 However, under pathological conditions, VICs differentiate into osteoblastic and myofibroblastic phenotypes. Previous research suggests that the critical features of CAVD include calcific mineral deposition, increased leaflet stiffness, and thickening resulting in decreased ability of the leaflets to open and close fully. Experimental data suggest that these features may be attributable to myofibroblastic VICs synthesizing fibrotic extracellular matrix and osteoblastic VICs depositing calcium-rich mineral. However, the mechanism by which VICs are converted into either myofibroblastic or osteoblastic VICs is unclear.Experiments using fibrosa and ventricularis side–specific cell cultures (in vitro), and fibrosa side–specific cells that were subjected to different calcifying stimuli and subsequent comparative-omics–based identification resulted in the elucidation of cell culture models that better recapitulate in vivo valvular calcification.5 Current AV cell culture models (and all valve models, in general) are challenging to work with because it is difficult to achieve osteogenic mineral deposition in vitro by using VICs. However, recently engineered environments that better mimic early CAVD have been reported.8 Cultured VICs showed similar microlayer-specific proteomes, because VICs isolated from AV and VICs exposed to calcifying stimuli showed distinct proteome profiles that overlap with protein profiles obtained from the whole tissue.5 These AV microlayers manifested unique proteome profiles that were sustained through disease progression and identified (GFAP) glial fibrillary acidic protein as a specific marker of spongiosa layer–derived VICs.5 This study is the first to show that both secreted (such as CLU, HTRA1, and SPARC) and structural matrix (COMP, FN1, and VTN) proteins in the fibrosa are involved in the calcification process. This in vitro study showed that fibrosa-derived VICs had greater calcification potential than ventricularis-derived VICs.5With the use of near-infrared molecular imaging, 9 donor leaflets were separated into 27 subsamples (nondiseased, fibrotic, and calcific) for label-free proteomics and 3 donor leaflets (9 subsamples) for transcriptomics.5 This global proteomics and transcriptomics approach allows for an unbiased expression profile of the AV proteome across different experimental conditions. A major limitation of global proteomic approaches is the difficulty of detecting low-abundance peptides. The subsamples and cell culture models typically allow lower-abundance peptides to be identified more readily. Although the correlation between transcriptomics and proteomics was low, this investigation of stage-specific valvular proteome and transcriptome revealed several common fibrotic and calcific signatures that were previously identified (tissue-nonspecific alkaline phosphatase, and apolipoprotein B, matrix metalloproteinase activation, and mitogen-activated protein kinase signaling), confirming the power of a well-conceived and conducted multi-omics strategy. The multi-omics approach also showed protein expression changes that were unique to each CAVD disease state (such as SOD3 [superoxide dismutase 3] and MGP [matrix Gla protein] in fibrotic, and SERPINA1 and VWF [von Willebrand factor] in calcific).5 The data also suggest that inflammation is likely to be a significant contributor to CAVD progression, because inflammatory signatures were detected in both the diseased fibrosa (C8A, C8B, and SLPI) and the calcific stage (ELANE, HLA-DRA, and CD14) of CAVD. A recent publication using VICs from calcified leaflet values similarly provided strong evidence for involvement of inflammatory mechanisms in CAVD.6Separately, AVs obtained from 3 patients with severe aortic valve stenosis and autopsy donors (controls) were separated into the 3 tissue layers by laser capture microdissection and used for tandem-mass–tagged proteomics. Several proteins were found to be enriched in the fibrosa (eg, APOM, APOC1, and ANGPTL2), spongiosa (GFAP), and ventricularis (CNN1, MYH11, and TAGLN2) of CAVD samples in comparison with nondiseased samples (see Center for Interdisciplinary Cardiovascular Sciences website9 for Excel files of the data). To corroborate the proteomic data, Schlotter et al5 used immunofluorescence staining and confocal microscopy to determine the localization of several proteins not previously implicated in CAVD.Although echocardiography has a poor predictive value for CAVD progression and affords little in the way of understanding of the pathophysiology of CAVD, it is currently the primary diagnosis method used for CAVD. At present, B-type natriuretic peptide is the only biomarker that has demonstrated clinical utility for CAVD management.10 More biomarkers are needed to allow better risk stratification of patients and identification of underlying factors for the disease. Several studies suggest that other potential biomarkers, including fetuin-A, osteocalcin, and C-reactive protein, are associated with CAVD.11Although transcriptomics is a powerful method to investigate gene expression changes in disease, understanding protein expression changes is important, because it is the proteins that are ultimately responsible for changes in cellular processes. However, the high cost of proteomic studies on large population numbers is a major limitation that currently limits the discovery of biomarkers for cardiovascular diseases such as CAVD. Meta-analysis of proteomic data is in its infancy,12 with new tools recently being developed.13 As meta-analyses of proteomic data become more common, this type of approach will help to address the problem of low population numbers. Meta-analysis of transcriptomic data has already proven to be a robust approach to discover novel pathways. One example for CAVD involves the use of the expression profiles of 15 calcific and 14 normal human AV samples from 2 gene expression data sets resulting in the discovery of several gene products (phospholipid phosphatase 3, collagen triple helix repeat containing 1, and secretogranin II) that are predicted to participate in CAVD development and progression.14The work by Schlotter et al5 is a powerful example of how the integration of proteomics and transcriptomics can result in the elucidation of novel pathways; it also provides a template for how multi-omics studies on complex tissue types (tissues with complex microarchitecture) and temporal variation in disease development could be performed. The results from this work also raise new questions. What mechanism(s) are responsible for upregulation of the layer- and disease stage–specific mRNAs and proteins? Because each layer of the leaflet manifests unique changes during CAVD progression, what are the most important proteins that are upregulated during CAVD progression? Can some of the proteins overexpressed during CAVD progression be used as informative biomarkers? With continual improvements in proteomic and transcriptomic data acquisition and analysis, and reductions in the cost of these technologies, as well, larger multi-omics studies will become commonplace, potentially providing comprehensive insights into CAVD and other cardiovascular diseases. Large-scale studies involving more patients with aortic valve stenosis will result in better statistical power and uncover more detailed insights into pathways not previously discovered. The investigation of posttranslational modifications that change during CAVD is also likely to be important in understanding the progression of this disease. However, as the amount of data generated by multi-omics approaches increases, new bioinformatic and multidimensional network analysis techniques will be required.Sources of FundingDr Gomes received support from the National Institutes of Health (grant R01-HL096819) and the American Heart Association (16GRNT31350040).DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.https://www.ahajournals.org/journal/circAldrin V. Gomes, PhD, 187 Briggs Hall, One Shields Ave, Department of Neurobiology, Physiology, and Behavior, University of California, Davis, Davis, CA 95616. E-mail [email protected]eduReferences1. Ruiz JL, Hutcheson JD, Aikawa E. Cardiovascular calcification: current controversies and novel concepts.Cardiovasc Pathol. 2015; 24:207–212. doi: 10.1016/j.carpath.2015.03.002.CrossrefMedlineGoogle Scholar2. 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Circulation. 2018;138:377-393 July 24, 2018Vol 138, Issue 4 Advertisement Article InformationMetrics © 2018 American Heart Association, Inc.https://doi.org/10.1161/CIRCULATIONAHA.118.035431PMID: 30571374 Originally publishedJuly 23, 2018 Keywordsvascular calcificationconstriction, pathologicaortic valve stenosisaortic valuetranscriptomeEditorialsproteomicsPDF download Advertisement SubjectsCardiovascular DiseaseOmicsProteomicsValvular Heart Disease