Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Whole Blood Cell Gene Expression Profiling in Patients with Coronary Artery Disease from the PREDICT Trial

ABSTRACT: Expression profiling of whole blood cells isolated from patients piror to undergoing cardiac catheterization. PREDICT is a prospective, multi-center coronary catheter-lab trial being run in the US for the purpose of identifying biomarkers associated with coronary disease. A summary of the trial can be found at http://clinicaltrials.gov (identifier # NCT00500617). 2 condition, paired experiment: Cases (1) are patients with ≥50% stenosis in >= 1 major vessel by quantitative coronary angiography (QCA), Controls (0) have luminal stenosis of < 50% by QCA. Samples were paired based on case/control status, age, and gender.

ORGANISM(S): Homo sapiens

SUBMITTER: James Wingrove

PROVIDER: E-GEOD-20681 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Background: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography either by invasive catheterization (ICA) or computed tomography (CTA). Prior studies employed single-molecule, amplification-independent RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. The present studies employed Illumina RNAseq and network co-expression analysis to identify systematic changes underlying CAD. Methods: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by Illumina total RNA sequencing (RNAseq) to identify transcripts associated with CAD (iTRACs) in 177 patients presenting for elective invasive coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs) and to identify patterns of changes through whole genome co-expression network analysis (WGCNA). Results: The correlation between Illumina amplified RNAseq and the prior SeqLL unamplified RNAseq was quite strong (r=0.87), but there was only 9% overlap in the DEGs identified. Consistent with the prior RNAseq, the majority (93%) of DEGs were down-regulated ~1.7-fold in patients with mild to severe CAD (>20% stenosis). DEGs were predominantly related to T cells, consistent with known reductions in Tregs in CAD. Network analysis did not identify pre-existing modules with a strong association with CAD, but patterns of T cell dysregulation were evident. iTRACs were enriched for transcripts associated with ciliary and synaptic transcripts, consistent with changes in the immune synapse of developing T cells. Conclusions: These studies confirm and extend a novel mRNA signature of a Treg-like defect in CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Project description:Rationale: Epicardial adipose tissue (EAT) has been independently associated with non-calcified, high-risk coronary plaques in low-to intermediate risk subjects. Recently, a bidirectional communication was shown between EAT and diseased coronary arteries. In high-risk patients it is unknown whether quantitative measures of EAT can capture, and which molecular players are involved in this mutual interplay. Objective: In a high-risk population, we aimed to determine how the volume of EAT is linked to coronary artery disease (CAD) and to identify potential EAT-deregulated pathways in CAD patients specifically related to coronary artery calcification (CAC). Methods and Results: In a prospective cohort of 574 degenerative severe aortic stenosis patients referred to cardiac surgery, we quantified fat depots by computed tomography (CT) and performed a comparative quantitative proteomics of thoracic fat, including EAT, mediastinal (MAT) and subcutaneous (SAT) adipose tissues. We did not find an independent association of EAT volume with the severity, distribution and complexity of coronary stenosis in invasive coronary angiography. Although, EAT volume was correlated with high CAC, its cardiovascular risk factors-adjusted association was not significant. Taking as reference non-CAD matched-patients and compared to MAT and SAT, EAT proteomic signature of CAD was characterized by up-regulation of pro-calcifying annexins (Annexin A2, ANXA2), fatty acid binding transporters (FABP4) and inflammatory signaling proteins, and by down-regulation of fetuin-A and redox state regulatory enzymes. In EAT, ANXA2 regulation was positively correlated with CAC. EAT gene expression studies confirmed overexpression of ANXA2 and FABP4 in CAD, but no expression of FETUA was detected. Compared with non-CAD, fetuin-A circulating levels were higher in CAD, whereas no fetuin-A pericardial fluid differences were found. Conclusions: In this high-risk cohort, EAT presented an imbalance of pro-calcifying, pro-inflammatory and lipid transporters mediators. These local EAT-mediated regulatory mechanisms were not reflected by the CT volume of EAT alone.

Dataset Information

Whole Blood Cell Gene Expression Profiling in Patients with Coronary Artery Disease from the PREDICT Trial

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets