Comprehensive iTRAQ based proteomic Characterization of Coronary Artery Diseases
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Lian-Wen Qi
PROVIDER: PXD025017 | iProX | Wed Apr 04 00:00:00 BST 2018
REPOSITORIES: iProX
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Project description:We developed a coronary plaque sampling approach that could be applied broadly in live patients with coronary artery disease (CAD) to obtain molecular and cellular insights into human coronary atherosclerosis. Our approach combined RNA retrieval directly from balloons used in percutaneous coronary interventions (PCI) and inexpensive, low-input RNA-Seq using SMART-seq. We generated SMART-Seq libraries from coronary samples from 27 patients. Of the 27 patients, 13 were confirmed to have stable CAD (sCAD) and 14 confirmed to have been performed on lesions causing acute coronary syndrome (ACS). We applied CIBERSORTx to analyze the SMART-seq data from each of the 27 samples. We found fibroblasts and fibromyoctes were enriched, while smooth muscle cells were reduced, in samples from ACS compared with sCAD patients. We identified 371 genes as significantly differential expressed (q<0.05) between sCAD and ACS patients.
2023-07-10 | GSE236610 | GEO
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2024-03-01 | GSE250283 | GEO
Project description:Genetics play major roles in the development of atherosclerotic coronary artery disease (CAD). Despite tremendous efforts worldwide invested to decipher the genetic components controlling the development of CAD, the genetic architecture of CAD remains largely unclear. As part of an on-going effort to identify molecules and pathways involved in the development of atherosclerotic CAD, we propose to use rigorous angiographic criteria to define CAD phenotype for genomics and metabolomics study. We identified two extreme groups, namely “young CAD” group, who are very young individuals (age <= 40 years) proven to have severe CAD required revascularization, and “CAD-free elderly”, who are at very advanced age (Age >= 80 years) but have no angiographically apparent CAD. Phenotypically, these two groups are in sharp contrary. Conventional risk factors account for small portion of different phenotypes. We hypothesize that there are genetically programmed pathways and molecules accelerating atherosclerotic pathogenesis, in the “young CAD” patients and preventing the development of CAD in the “CAD-free elderly” patients. We sought to combine genomics and metabolomics approaches to profile and identify these pathways and molecules. Both plasma and urine samples from patients in these two groups, and their age matched control groups, will undergo unbiased metabolomics profiling with high throughput quantitative nuclear magnetic resonance (NMR) and mass spectrometry (MS) technology in RTI metabolomics core facility. Comprehensive statistic and multi-variant analytic approaches will be used to identify pathways and molecules significance to the pathogenesis of atherosclerosis. These data will be integrated with genomics data from next generation sequencing of genetic materials from the same groups of patients to further explore the molecular mechanisms underlying atherosclerosis and CAD.
2015-12-31 | ST000306 | MetabolomicsWorkbench
Project description:Monocytes and T-cells play an important role in the development of atherosclerotic coronary artery disease (CAD). Differences in transcriptional activity of these cells might reflect the individual's atherosclerotic burden. Transcriptome analysis of circulating mononuclear cells from carefully matched atherosclerotic and control patients will potentially provide insights into the pathophysiology of atherosclerosis and supply biomarkers for diagnostic purposes. From patients undergoing coronary angiography because of anginal symptoms, we carefully matched 18 patients with severe triple-vessel CAD to 13 control patients without signs of CAD on angiography. All patients were on statin and aspirin treatment. RNA from circulating CD4+ T-cells, CD14+ monocytes, lipopolysaccharide-stimulated monocytes, macrophages and CD34+ progenitor cells was subjected to genome-wide expression analysis. Only CD14+ monocytes demonstrated that a small number of genes involved in activation was overexpressed in control patients, which was verified by real-time polymerase-chain reaction. In this pilot study, cautious matching of patients with severe atherosclerotic CAD with control patients without angiographic signs of coronary atherosclerosis did not reveal differences in transcriptional activity in four out of five different mononuclear cell types. In resting monocytes from patients without overt CAD some inflammatory genes were overexpressed as compared to patients with severe CAD. Large inter-individual variability prevented the use of single differentially expressed genes as biomarkers. Keywords: disease-state analysis In total 153 arrays were analyzed with 6 technical replicates (147 biological samples). CD34+ stem cells, CD4+ T-cells, resting CD14+ monocytes, stimulated monocytes and macrophages were analyzed, all from patient with severe coronary atherosclerosis or controls that had no coronary atherosclerosis as determined angiographically, and which were carefully matched for age and gender.
2008-12-01 | E-GEOD-9820 | biostudies-arrayexpress
Project description:Gene expression profile in circulating leukocytes identifies patients with coronary artery disease Peter Sinnaeve, Mark Donahue, Peter Grass, Jacky Vonderscher, David Seo, Pascal Goldschmidt, Christopher Granger Department of Medicine, Duke University, Durham, NC, USA, Novartis Institute for Biomedical Research, Cambridge, Boston, MA, USA Introduction Systemic and local inflammation plays a prominent pathogenetic role in atherosclerotic coronary artery disease (CAD), but the relationship of phenotypic changes in circulating leukocytes and extent of CAD remains unclear. We have investigated whether gene expression patterns in circulating leukocytes are associated with presence and extent of CAD. Methods Patients undergoing coronary angiography were selected according to their Duke CAD index (CADi), a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from 110 patients with CAD (CADi>23) and from 112 partially matched controls without CAD (CADi=0). Gene expression was assessed using Affymetrix U133A chips. Genes correlating with CAD were identified using Spearman’s rank correlation, and predictive gene expression patterns were identified using a partial least squares (PLS) regression analysis. Results 160 individual genes were found to significantly correlate with CADi (rho>0.2, P<0.0027), although changes in individual gene expression were relatively small (1.2 to 1.5 fold). Using these 160 genes, the PLS multivariate regression resulted in a highly predictive model (r2=0.764, P<0.001). Cross-validation showed that most of the predictive model was carried by only 8 genes (r2=0.752) (table 1). Conclusion Simultaneous expression pattern of 8 genes appears to be highly predictive for CAD. Peripheral leukocyte gene expression pattern could be a novel non-invasive biomarker for CAD and lead to new pathophysiologic insights. parallel group design
2008-10-31 | E-GEOD-12288 | biostudies-arrayexpress
Project description:Coronary artery disease (CAD) is the leading cause of human morbidity and mortality worldwide, underscoring the need to improve diagnostic strategies. Platelets play a major role, not only in the process of acute thrombosis during plaque rupture, but also in the formation of atherosclerosis itself. MicroRNAs are endogenous small non-coding RNAs that control gene expression and are expressed in a tissue and disease-specific manner. Therefore they have been proposed to be useful biomarkers. It remains unknown whether differences in miRNA expression levels in platelets can be found between patients with premature CAD and healthy controls. Methodology/Principal Findings In this case-control study we measured relative expression levels of platelet miRNAs using microarrays from 12 patients with premature CAD and 12 age- and sex-matched healthy controls. Six platelet microRNAs were significantly upregulated (miR340*, miR451, miR454*, miR545:9.1. miR615-5p and miR624*) and one miRNA (miR1280) was significantly downregulated in patients with CAD as compared to healthy controls. To validate these results, we measured the expression levels of these candidate miRNAs by qRT-PCR in platelets of individuals from two independent cohorts; validation cohort I consisted of 40 patients with premature CAD and 40 healthy controls and validation cohort II consisted of 27 patients with artery disease and 40 healthy relatives. MiR340* and miR624* were confirmed to be upregulated in patients with CAD as compared to healthy controls in both validation cohorts. Conclusion/Significance Two miRNAs in platelets are significantly upregulated in patients with CAD as compared to healthy controls. miRNA array analysis of isolated platelets from subjects with premature coronary artery disease compared to healthy control subjects.
2011-09-30 | E-GEOD-28858 | biostudies-arrayexpress
Project description:Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans.
2023-11-14 | GSE225650 | GEO
Project description:Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AS) are the heart diseases accounting for the highest proportion of cardiac surgeries. Routine biomarkers for an earl detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis and to evaluate their severity with imaging techniques before they become advanced to the point where intervention or surgery have limited therapeutic benefit. Urine is an attractive biofluid for biomarker assessment, provided the noninvasive nature of its collection. Therefore, we conducted a shotgun proteomics analysis of urine collected from 12 CAD and/or AS patients and 11 cardiovascular disease-free controls, aiming at identification of putative molecular candidates that could differentiate these diseases from healthy subjects
2022-12-18 | PXD036800 | Pride
Project description:Monocytes and T-cells play an important role in the development of atherosclerotic coronary artery disease (CAD). Differences in transcriptional activity of these cells might reflect the individual's atherosclerotic burden. Transcriptome analysis of circulating mononuclear cells from carefully matched atherosclerotic and control patients will potentially provide insights into the pathophysiology of atherosclerosis and supply biomarkers for diagnostic purposes. From patients undergoing coronary angiography because of anginal symptoms, we carefully matched 18 patients with severe triple-vessel CAD to 13 control patients without signs of CAD on angiography. All patients were on statin and aspirin treatment. RNA from circulating CD4+ T-cells, CD14+ monocytes, lipopolysaccharide-stimulated monocytes, macrophages and CD34+ progenitor cells was subjected to genome-wide expression analysis. Only CD14+ monocytes demonstrated that a small number of genes involved in activation was overexpressed in control patients, which was verified by real-time polymerase-chain reaction. In this pilot study, cautious matching of patients with severe atherosclerotic CAD with control patients without angiographic signs of coronary atherosclerosis did not reveal differences in transcriptional activity in four out of five different mononuclear cell types. In resting monocytes from patients without overt CAD some inflammatory genes were overexpressed as compared to patients with severe CAD. Large inter-individual variability prevented the use of single differentially expressed genes as biomarkers. Keywords: disease-state analysis
2008-12-01 | GSE9820 | GEO
Project description:Gene expression profile in circulating leukocytes identifies patients with coronary artery disease Peter Sinnaeve, Mark Donahue, Peter Grass, Jacky Vonderscher, David Seo, Pascal Goldschmidt, Christopher Granger Department of Medicine, Duke University, Durham, NC, USA, Novartis Institute for Biomedical Research, Cambridge, Boston, MA, USA Introduction Systemic and local inflammation plays a prominent pathogenetic role in atherosclerotic coronary artery disease (CAD), but the relationship of phenotypic changes in circulating leukocytes and extent of CAD remains unclear. We have investigated whether gene expression patterns in circulating leukocytes are associated with presence and extent of CAD. Methods Patients undergoing coronary angiography were selected according to their Duke CAD index (CADi), a validated angiographical measure of the extent of coronary atherosclerosis that correlates with outcome. RNA was extracted from 110 patients with CAD (CADi>23) and from 112 partially matched controls without CAD (CADi=0). Gene expression was assessed using Affymetrix U133A chips. Genes correlating with CAD were identified using Spearman’s rank correlation, and predictive gene expression patterns were identified using a partial least squares (PLS) regression analysis. Results 160 individual genes were found to significantly correlate with CADi (rho>0.2, P<0.0027), although changes in individual gene expression were relatively small (1.2 to 1.5 fold). Using these 160 genes, the PLS multivariate regression resulted in a highly predictive model (r2=0.764, P<0.001). Cross-validation showed that most of the predictive model was carried by only 8 genes (r2=0.752) (table 1). Conclusion Simultaneous expression pattern of 8 genes appears to be highly predictive for CAD. Peripheral leukocyte gene expression pattern could be a novel non-invasive biomarker for CAD and lead to new pathophysiologic insights.
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