Project description:Coronary artery disease (CAD) is a complex inflammatory disease of the vessel wall and often leads to myocardial infarction. Genome-wide association studies (GWAS) have now identified over 200 genetic loci associated with CAD. The majority of CAD-associated variants are located in noncoding regions of the genome, many of which are predicted to regulate chromatin accessibility and gene expression. In this study, we performed ATAC-seq in human coronary artery patient samples to identify novel chromatin accessibility QTLs (caQTLs) and gain additional insights into CAD regulatory mechanisms in vivo.
Project description:Transcriptomic analysis of fresh breast cancer tissue versus normal tissues. The Study comprising 45 Saudi-Arabian subjects was designed to take advantage of transcriptomics to prospectively explore the roles of lifestyle and genetic susceptibility in the occurrence of breast cancer.
Project description:19 paired human left ventricular apex samples were harvested at the time of implant of a left ventricular assist device (PRE) and at the time of explant (POST). The cohort included patients that were clinically classified as ischemic (I) showing evidence of coronary artery disease, non-ischemic (N) no evidence of coronary artery disease or acute Myocardial infarction (IM) myocardial infarction within 10 days of the implant. Tissue was processed and hybridized to the Affymetrix HG-U133A chip.
Project description:Transcriptomic analysis of fresh breast cancer tissue versus normal tissues. The Study comprising 45 Saudi-Arabian subjects was designed to take advantage of transcriptomics to prospectively explore the roles of lifestyle and genetic susceptibility in the occurrence of breast cancer. Total RNA isolated from 45 surgically resected breast cancer tissues and 8 healthy breast tissues (3 from Affymetrix) and purified, labeled, and hybridized to Affymetrix Human Gene 1.0 ST Array.
Project description:Genome-wide association studies (GWAS) have identified hundreds of loci associated with vascular diseases such as coronary artery disease (CAD) and myocardial infarction (MI), and hypertension. However, the biological roles for many of these loci enriched in the vessel wall remains unknown. Among these, UFL1-FHL5 (chr6q16.1) emerged as a genome-wide significant locus in a recent CAD/MI meta-analysis. Here, we use an integrative approach leveraging human genetics, epigenomic profiling, and in vitro functional and ex vivo imaging analyses to prioritize FHL5 as the top candidate causal gene and reveal the molecular mechanisms of its pleiotropic genetic associations. Notably, FHL5 overexpression in coronary artery smooth muscle cells (SMC) increased vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites genome-wide using CUT&RUN, we identified regulatory interactions with downstream disease loci having putative roles in SMC phenotypic modulation. Together, these trans-acting mechanisms may account for a portion of the heritable risk for CAD/MI and other complex vascular diseases.
Project description:Coronary artery disease (CAD) is the leading cause of mortality and morbidity driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with CAD and myocardial infarction (MI) susceptibility in multi-ethnic populations. The majority of these variants reside in non-coding regulatory regions and are co-inherited with hundreds of candidate regulatory SNPs. Herein, we use integrative genomic, epigenomic, and transcriptomic fine-mapping in human coronary artery smooth muscle cells (HCASMC) and tissues to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps we prioritize 65 candidate variants and perform allele-specific binding and expression analyses on 7 top candidates. We validate our findings in two independent cohorts of diseased human arterial expression quantitative trait loci (eQTL), which together demonstrate fundamental links between CAD associations and regulatory function in the appropriate disease context.
Project description:Recent technological advances have made transcriptome sequencing (RNA-seq) possible in cells with low RNA copy number including platelets. Resulting studies have used RNA-seq in platelets isolated from healthy individuals to characterize the platelet transcriptome. However, platelets, possibly through gene expression changes, contribute to the etiology of and response to cardiovascular disease and events. To address this, we performed the largest human platelet RNA-seq analysis to date in 34 platelet samples: 16 ST-segment elevation myocardial infarction (STEMI), 16 non-STEMI (NSTEMI), and 2 controls. RNA-seq of platelet samples from 34 individuals: 16 with ST-elevation myocardial infarction (STEMI), 16 with non-STEMI, and 2 non-myocardial infarction controls
Project description:Myocardial interstitial fibrosis is a common thread in multiple cardiovascular diseases including heart failure, atrial fibrillation, conduction disease and sudden cardiac death. To investigate the biologic pathways that underlie interstitial fibrosis in the human heart, we developed a machine learning model to measure myocardial T1 time, a marker of myocardial interstitial fibrosis, in 41,505 UK Biobank participants. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Mendelian randomization analysis supported a potential causal role for diabetes mellitus type 1 in myocardial interstitial fibrosis. In genome-wide association analysis, we identified 11 independent loci associated with native myocardial T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Transcriptome-wide association studies highlighted the role of expression of ADAMTSL1 and SLC2A12 in human cardiac tissue in modulating myocardial interstitial fibrosis. Using a TGFβ1-mediated cardiac fibroblast activation assay, we found that 9 out of the 11 genome-wide significant loci comprised genes that exhibited temporal changes in expression and/or open chromatin conformation supporting the biological relevance of these loci to myocardial fibrosis and myofibroblast cell state acquisition. Harnessing machine learning to perform large-scale phenotyping of interstitial fibrosis in the human heart, our results yield novel insights into biologically relevant pathways to myocardial fibrosis and prioritize a number of pathways for further investigation.
Project description:Despite the significant reduction in the overall burden of cardiovascular disease (CVD) over the past decade, CVD still accounts for a third of all deaths in the United States and worldwide each year. While efforts to identify and reduce risk factors for atherosclerotic heart disease (i.e. hypertension, dyslipidemia, diabetes mellitus, cigarette smoking, inactivity) remain the focus of primary prevention, the inability to accurately and temporally predict acute myocardial infarction (AMI) impairs our ability to further improve patient outcomes. Our diagnostic evaluation for the presence of coronary artery disease relies on functional testing, which detects flow-limiting coronary stenosis, but we have known for decades that most lesions underlying AMI are only of mild to moderate luminal narrowings, not obstructing coronary blood flow. Accordingly, there is a dire need of improved diagnostics for underlying arterial plaque dynamics, fissure and rupture. Here we describe the designation of a specific gene expression pattern acting as a molecular signature for acute myocardial infarction present in whole blood of patients that was determined using microarray analysis of enriched circulating endothelial cells (CEC). We isolated circulating endothelial cells from patients experience acute myocardial infartion and healthy cohorts, and measured gene expression using the HG-133U_PLUS_2 microarray Circulating endothelial cells were isolated from patients experiencing acute myocardial infarction (n=49) and from healthy cohorts (n=50). The patients were separated into a discovery cohort (n=43) for biomarker discovery and model training; and into a validation cohort (n=56) for biomarker validation and model testing.
Project description:19 paired human left ventricular apex samples were harvested at the time of implant of a left ventricular assist device (PRE) and at the time of explant (POST). The cohort included patients that were clinically classified as "ischemic" (I) showing evidence of coronary artery disease, "non-ischemic" (N) no evidence of coronary artery disease or "acute Myocardial infarction" (IM) myocardial infarction within 10 days of the implant. Tissue was processed and hybridized to the Affymetrix HG-U133A chip. Keywords: other