Dataset Information

Genome wide association study for early onset coronary disease and related phenotypes (ADVANCE)

ABSTRACT:

ADVANCE (Atherosclerotic Disease, VAscular functioN, and genetiC Epidemiology) is a large epidemiological study of genetic and non-genetic determinants of coronary artery disease (CAD) that started in 2000 as a collaborative effort between researchers at Stanford University and Kaiser Permanente of Northern California. The overarching goal of the study is to improve our ability to prevent, diagnose and treat CAD. The initial study included recruitment of over 3600 subjects (including 1873 subjects with incident clinically significant coronary disease and 1745 control subjects) from multiple race/ethnic backgrounds. A subset of ~ 500 subjects with very early onset coronary disease (men < 45 and women < 55) and ~ 500 similar aged controls were genotyped using the Illumina 550K platform as part of an NIH funded effort within the STAMPEED consortium.

PROVIDER: phs000423.v1.p1 | EGA |

REPOSITORIES: EGA

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Publications

Genome-wide meta-analyses identify multiple loci associated with smoking behavior.

Nature genetics 20100425 5

Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n > 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest associ ...[more]

PMID: 20418890

Publication: 1/13

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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

Genome wide association study for early onset coronary disease and related phenotypes (ADVANCE)

Publications

Genome-wide meta-analyses identify multiple loci associated with smoking behavior.

Similar Datasets

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