Proteomic Architecture of Human Coronary and Aortic Atherosclerosis

Herrington, David M.; Mao, Chunhong; Parker, Sarah J.; Fu, Zhang; Yu, Guoqiang; Chen, Lulu; Venkatraman, Vidya; Fu, Yi; Wang, Yizhi; Howard, Timothy D.; Goo, Jun; Zhao, Caroline F; Liu, Yongmei; Saylor, Georgia; Spivia, Weston R.; Athas, Grace; Troxclair, Dana; Hixson, James E.; Heide, Richard S. Vander; Wang, Yue; Eyk, Jennifer E. Van

doi:10.1161/circulationaha.118.034365

Cited by 110 publications

(113 citation statements)

References 64 publications

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“…The number of SDEGs accounts for about one-third of all probesets (Roche: 39%, HUG: 34%). This result is expected because these subtypes are pure cell types and so more distinctive than would be seen with samples from multicellular complex tissues 9,21,22 . We also applied a Bonferroni multiple testing correction and a more stringent pvalue < 0.001; the number of SDEGs account for 10.7% and 2.7% of all probesets in Roche and HUG data sets, respectively (Table S4)…”

Section: Sdegs (Human Immune Cells)mentioning

confidence: 84%

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Data-driven detection of subtype-specific and differentially expressed genes

Chen

et al. 2019

Preprint

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Tissue or cell subtype-specific and differentially-expressed genes (SDEGs) are defined as being differentially expressed in a particular tissue or cell subtype among multiple subtypes. Detecting SDEGs plays a critical rolse in molecularly characterizing and identifying tissue or cell subtypes, and facilitating supervised deconvolution of complex tissues. Unfortunately, classic differential analysis assumes a convenient null hypothesis and associated test statistic that is subtype-non-specific and thus, resulting in a high false positive rate and/or lower detection power with respect to particular subtypes. Here we introduce One-Versus-Everyone Fold Change (OVE-FC) test for detecting SDEGs. To assess the statistical significance of such test, we also propose the scaled test statistic OVE-sFC together with a mixture null distribution model and a tailored permutation scheme. Validated with realistic synthetic data sets on both type 1 error and detection power, OVE-FC/sFC test applied to two benchmark gene expression data sets detects many known and de novo SDEGs. Subsequent supervised deconvolution results, obtained using the SDEGs detected by OVE-FC/sFC test, showed superior performance in deconvolution accuracy when compared with popular peer methods.

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Section: Sdegs (Human Immune Cells)mentioning

confidence: 84%

“…SDEGs play a critical role in molecularly characterizing and identifying tissue or cell subtypes, and facilitating the supervised deconvolution of complex tissues 5,8,9 . However, detecting SDEGs using tissue or cell-specific molecular expression profiles remains a challenging task 10 .…”

Section: Here We Introduce One-versus-everyone Fold Change (Ove-fc) Tmentioning

confidence: 99%

Data-driven detection of subtype-specific and differentially expressed genes

Chen

et al. 2019

Preprint

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“…While proteomics has been previously performed separately on atherosclerotic plaques (19, 20) or calcified stenotic aortic valves,(21) the proteomes of these diseased cardiovascular tissues have never been directly compared in any species. To identify shared or deviating mechanisms underlying disease pathogenesis in these two tissues, we performed label-free liquid-chromatography-mass spectrometry (LC-MS) on cryogenically-homogenized human atherosclerotic plaques from carotid endarterectomies and calcified aortic valves that had undergone surgical replacement.…”

Section: Resultsmentioning

confidence: 99%

Conserved and Divergent Modulation of Calcification in Atherosclerosis and Aortic Valve Disease by Tissue Extracellular Vesicles

Buffolo

Halu

et al. 2020

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53 54 Background: Fewer than 50% of patients develop calcification of both atherosclerotic plaques 55 and aortic valves, implying differential pathogenesis. While circulating extracellular vesicles 56 (EVs) act as biomarkers of cardiovascular diseases, tissue-entrapped EVs associate with early 57 mineralization, but their contents, function, and contributions to disease remain unknown. 58 59 Results: Global proteomics of human carotid artery endarterectomies and calcified aortic valves 60 from a total of 27 donors/patients revealed significant over-representation of proteins with 61 vesicle-associated pathways/ontologies common to both diseases. We exploited enzymatic 62 digestion, serial (ultra)centrifugation and OptiPrep density-gradient separation to isolate EV 63 populations from diseased arteries and valves. Mass spectrometry found 22 EV marker proteins 64 to be highly enriched in the four least-dense OptiPrep fractions while extracellular matrix 65 proteins predominated in denser fractions, as confirmed by CD63 immunogold electron 66 microscopy and nanoparticle tracking analysis. Proteomics and miRNA-sequencing of OptiPrep-67 enriched tissue EVs quantified 1,104 proteins and 123 miR cargoes linked to 5,182 target 68 genes. Pathway networks of proteins and miR targets common to artery and valve tissue EVs 69 revealed a shared regulation of Rho GTPase and MAPK intracellular signaling cascades. 179 70 proteins and 5 miRs were significantly altered between artery and valve EVs; multi-omics 71 integration determined that EVs differentially modulated cellular contraction and p53-mediated 72 transcriptional regulation in diseased vascular vs. valvular tissue. 73 74 Conclusions: Our findings delineate a strategy to isolate, purify, and study protein and RNA 75 cargoes from EVs entrapped in fibrocalcific tissues. Multi-omics and network approaches 76 implicated tissue-resident EVs in human cardiovascular disease. 77 78 4 Keywords 79 80 Extracellular vesicles, exosomes, atherosclerosis, vascular calcification, calcific aortic valve 81 disease, proteomics, transcriptomics, miRNA, multi-omics integration, network analysis 82 83 84 Background 85 86Cardiovascular calcification directly correlates with incidence of cardiovascular events such as 87 myocardial infarction, stroke, and heart failure, and strongly predicts morbidity and mortality.(1) 88While aberrant mineralization of arteries and heart valves share numerous risk factors, only 25-89 50% of patients develop both vascular and valvular calcification, implying that they involve 90 differential drivers.(2) Histopathological studies described these two conditions as being grossly 91 comparable (3) and there has been little subsequent study of this apparent epidemiological 92 paradox. Despite the histological similarities, pharmacological therapies such as statins have 93 been successful in mitigating inflammation and lowering cholesterol in patients with 94 atherosclerosis but they failed to improve outcomes for aortic valve stenosisleaving patients 95 without effec...

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“…The following genes involved in the regulation of various pathways of inflammation, according to various GWAS, are significantly associated with atherosclerotic cardiovascular diseases (CVD): CXCL12, MCP-1, TLRs, SH2B3, HLA, IL-6R, IL-5, PECAM1, and others [70]. In studies based on the proteomics approach, the crucial role of inflammation was also shown by the example of the activation of the TNF-α pathway in the vascular wall, as well as the migration of monocytes into the subendothelial compartment (ANRIL) [71,72].…”

Section: Endotype Associatedmentioning

confidence: 99%

Conceptualization of Heterogeneity of Chronic Diseases and Atherosclerosis as a Pathway to Precision Medicine: Endophenotype, Endotype, and Residual Cardiovascular Risk

Генкель

Шапошник

2020

International Journal of Chronic Diseases

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The article discusses modern approaches to the conceptualization of pathogenetic heterogeneity in various branches of medical science. The concepts of endophenotype, endotype, and residual cardiovascular risk and the scope of their application in internal medicine and cardiology are considered. Based on the latest results of studies of the genetic architecture of atherosclerosis, five endotypes of atherosclerosis have been proposed. Each of the presented endotypes represents one or another pathophysiological mechanism of atherogenesis, having an established genetic substrate, a characteristic panel of biomarkers, and a number of clinical features. Clinical implications and perspectives for the study of endotypes of atherosclerosis are briefly reviewed.

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Proteomic Architecture of Human Coronary and Aortic Atherosclerosis

Cited by 110 publications

References 64 publications

Data-driven detection of subtype-specific and differentially expressed genes

Data-driven detection of subtype-specific and differentially expressed genes

Conserved and Divergent Modulation of Calcification in Atherosclerosis and Aortic Valve Disease by Tissue Extracellular Vesicles

Conceptualization of Heterogeneity of Chronic Diseases and Atherosclerosis as a Pathway to Precision Medicine: Endophenotype, Endotype, and Residual Cardiovascular Risk

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