Transcription profiling of stroke-susceptible and asymptomatic human carotid plaques
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Jani Saksi
PROVIDER: E-MEXP-2257 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:We compared gene expression profiles between asymptomatic and symptomatic atherosclerotic plaques from the same patient. This was accomplished by analyzing carotid plaques from four patients with bilateral high-grade carotid artery stenoses one being symptomatic (TIA or stroke) and the other asymptomatic.
2006-02-10 | E-MEXP-268 | biostudies-arrayexpress
Project description:Atherosclerosis is causally related to disturbed flow through low and oscillatory shear stress. In order to study the miR expression profile in atherosclerotic plaques induced by disturbed flow, partial ligation of the carotid artery was performed. This procedure results acutely in severly reduced blood flow and in stenotic lesion formation within 6 weeks in apoe-/- mice on a high fat diet. We compared the miR expression profile in partially ligated left carotid arteries with the untreated right carotid artery to identify miRs which are involved in plaque formation through flow disturbances. The left carotid arteries of 6 female apoe-/- mice (6-8 weeks) were partially ligated (i.e. the external and internal carotid artery as well as the occipital artery were occluded; blood flow out of the common carotid artery occurs mainly through the superior thyroid artery). Following partial ligation the animals were fed a high fat diet for 6 weeks. Total RNA was isolated from partially ligated left carotid arteries and untreated right carotid arteries (control). MiRs expression profile of the partially ligated carotid arteries were compared with the control group. Biological replicates: 6 per group. One replicate per array.
2012-12-26 | E-GEOD-26555 | biostudies-arrayexpress
Project description:Background: Using proteomics, we strove to reveal novel molecular subtypes of human atherosclerotic lesions, study their associations with histology and imaging and relate them to long-term cardiovascular outcomes. Methods: 219 samples were obtained from 120 patients undergoing carotid endarterectomy. Sequential protein extraction was combined with multiplexed, discovery proteomics. Parallel reaction monitoring for 135 proteins was deployed for targeted validation. A combination of statistical, bioinformatics and machine learning methods was used to perform differential expression, network, pathway enrichment analysis and train and evaluate prognostic models. Results: Our extensive proteomics analysis from the core and periphery of plaques doubled the coverage of the plaque proteome compared to the largest proteomics study on atherosclerosis thus far. Plaque inflammation and calcification signatures were inversely correlated and validated with targeted proteomics. The inflammation signature was enriched with neutrophil-derived proteins, including calprotectin (S100A8/9) and myeloperoxidase. The calcification signature contained fetuin-A, osteopontin, and gamma-carboxylated proteins. Sex differences in the proteome of atherosclerosis were explained by a higher proportion of calcified plaques in women. Single-cell RNA sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages and the calcification signature to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in the plaque, i.e., fetuin-A. Echogenic lesions reflect the collagen content and calcification of plaque but carotid Duplex ultrasound fails to capture the extent of inflammatory protein changes in symptomatic plaques. Applying dimensionality reduction and machine learning on the proteomics data defined 4 distinct plaque phenotypes and revealed key protein signatures linked to smooth muscle cell content, plaque calcification and structural extracellular matrix, which improved the 9-year prognostic AUC by 25% compared to ultrasound and histology. A biosignature of four proteins (CNN1, PROC, SERPH, and CSPG2) independently predicted the progression of atherosclerosis and cardiovascular mortality with an AUC of 75% Conclusion: We combined discovery and targeted proteomics with network reconstruction and clustering techniques to provide molecular insights into protein changes in atherosclerotic plaques. The application of proteomics and machine learning techniques revealed distinct clusters of plaques that inform on disease progression and future adverse cardiovascular events.
2023-11-15 | PXD031052 | Pride
Project description:Background: Using proteomics, we strove to reveal novel molecular subtypes of human atherosclerotic lesions, study their associations with histology and imaging and relate them to long-term cardiovascular outcomes. Methods: 219 samples were obtained from 120 patients undergoing carotid endarterectomy. Sequential protein extraction was combined with multiplexed, discovery proteomics. Parallel reaction monitoring for 135 proteins was deployed for targeted validation. A combination of statistical, bioinformatics and machine learning methods was used to perform differential expression, network, pathway enrichment analysis and train and evaluate prognostic models. Results: Our extensive proteomics analysis from the core and periphery of plaques doubled the coverage of the plaque proteome compared to the largest proteomics study on atherosclerosis thus far. Plaque inflammation and calcification signatures were inversely correlated and validated with targeted proteomics. The inflammation signature was enriched with neutrophil-derived proteins, including calprotectin (S100A8/9) and myeloperoxidase. The calcification signature contained fetuin-A, osteopontin, and gamma-carboxylated proteins. Sex differences in the proteome of atherosclerosis were explained by a higher proportion of calcified plaques in women. Single-cell RNA sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages and the calcification signature to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in the plaque, i.e., fetuin-A. Echogenic lesions reflect the collagen content and calcification of plaque but carotid Duplex ultrasound fails to capture the extent of inflammatory protein changes in symptomatic plaques. Applying dimensionality reduction and machine learning on the proteomics data defined 4 distinct plaque phenotypes and revealed key protein signatures linked to smooth muscle cell content, plaque calcification and structural extracellular matrix, which improved the 9-year prognostic AUC by 25% compared to ultrasound and histology. A biosignature of four proteins (CNN1, PROC, SERPH, and CSPG2) independently predicted the progression of atherosclerosis and cardiovascular mortality with an AUC of 75% Conclusion: We combined discovery and targeted proteomics with network reconstruction and clustering techniques to provide molecular insights into protein changes in atherosclerotic plaques. The application of proteomics and machine learning techniques revealed distinct clusters of plaques that inform on disease progression and future adverse cardiovascular events.
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Project description:The rupture of unstable atherosclerotic plaques, leading to debilitating or fatal thrombotic events, is a major health burden worldwide. Limited understanding as to the molecular drivers of plaque instability and rupture hinders efforts in diagnosis and treatment prior to thrombotic events. Utilising an advanced pre-clinical mouse model (Tandem stenosis (TS) model), which presents human-like unstable atherosclerotic disease, we apply high-end omic methods to characterize the molecular signatures associated with plaque instability in atherosclerotic arteries. Through quantitative proteomic profiling, we depict unique proteome signatures of unstable plaques compared to stable plaques and healthy arteries. Coupled with single-cell RNA-sequencing of leukocytes, we describe the heterodimer complex S100a8/S100a9 as unique to unstable plaque, with neutrophils implicated as the transcriptional drivers of S100a8/a9 expression. We confirm S100a9 expression in human carotid atherosclerotic plaques and we further utilise the TS pre-clinical model to pharmacologically inhibit S100a8/S100a9, resulting in plaque stabilisation. Thus, we establish the TS model as a sophisticated translational tool for the profiling of unstable atherosclerotic plaques and demonstrate that unstable and stable atherosclerosis are highly different disease entities.
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Project description:Identification of novel pathophysiological mechanisms of carotid artery disease at systemic level by studying the gene expression profile of peripheral blood of affected patients with respect to control subjects.
2009-06-30 | E-MEXP-2113 | biostudies-arrayexpress
Project description:Recently, we showed that disturbed flow caused by a partial ligation ofmouse carotid artery rapidly induces atherosclerosis. Analysis of mechanosenstive microRNA in the mouse carotid endothelium. In this study, we examined the microRNAs that respond differentially to blood flow pattern in the mouse carotid endothelium. We surgically induced disturbed blood flow in the left common carotid cartery (LCA) using partial carotid ligation surgery while the right carotid artery was left undisturbed. The hypothesis tested here is that turbulent or disturbed blood flow across the left carotid artery endothelium will affect endothelial genes and microRNAS. Identifying flow-sensitive microRNAs will provide important information about how endothelium responds to d-flow and regulates endothelial function and progression of atherosclerosis. Deter- mining the functional importance of these novel mechanosensitive microRNAS may provide important insights into understanding vascular biology and atherosclerosis. We used 6- to 8-week-old male C57Bl/6 mice (The Jackson Laboratory) according to the approved Institutional Animal Care and Use Committee protocol by Emory University. Mice were subjected to partial carotid ligation surgery under anesthesia. Briefly, 3 of 4 caudal branches of LCA (left external carotid, internal carotid, and occipital artery) were ligated with 6-0 silk suture, although the superior thyroid artery was left intact. Development of low and oscillatory blood flow in the Left Carotid Artery of each mouse was determined by ultrasound measurements.
2014-01-13 | E-GEOD-52243 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE23303: Gene expression profiling of human atherosclerotic plaque: Laser capture microscopy of smooth muscle cells and macrophages GSE23304: Gene expression profiling of human atherosclerotic plaque: 101 peripheral plaques GSE24495: Gene expression profiling of human atherosclerotic plaque: Carotid plaque GSE24702: Gene expression profiling of human atherosclerotic plaque: 290 peripheral plaques Refer to individual Series
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2008-06-10 | E-MEXP-1278 | biostudies-arrayexpress
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