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The Cardiogenics study

Cardiogenics is an European collaborative project, it started in January 2007 and was funded by the European Commission through its Sixth Framework Program (reference LSHM -CT-2006-037593) until 2011. It involved several laboratories from France (INSERM UMRS937), Germany (Lübeck University; Regensburg University), United Kingdom (the Welcome Trust Sanger Institute; University of Leicester) and Sweden (Uppsala University Hospital) and was coordinated by a management group composed of scientists from these different institutions. Under the coordination of the management group the laboratories are still developing projects using Cardiogenics data sets. As part of the Cardiogenics project, RNA from monocytes and macrophages of 363 patients with coronary artery disease and 395 healthy individuals was prepared and genome-wide expression was assessed in both cell types using the Illumina HumanRef 8 v3 Beadchip . The DNA of all these individuals was genotyped using the Human 610 Quad custom arrays. Both data sets were used to conduct eQTL analyses. A subsample of subjects included in an allelic-imbalance substudy were also genotyped using the Illumina Human Custom 1.2M array. Detailed description of these datasets can be found in Shah S et al. Circ Cardiovs Genet 2011; Rotival M et al. Plos Genet 2011, Almlöf et al. Plos One 2012 and Garnier S et al. Plos Genet 2013

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Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00010000446 Illumina Human-Ref-8 v3 beadchip 758
EGAD00010000448 Illumina Human-Ref-8 v3 beadchip 758
EGAD00010000450 Illumina Human Custom 1,2M and Human 610 Quad Custom arrays 758
Publications Citations
Four genetic loci influencing electrocardiographic indices of left ventricular hypertrophy.
Circ Cardiovasc Genet 4: 2011 626-635
28
Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.
PLoS Genet 7: 2011 e1002367
122
Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases.
Hum Mol Genet 24: 2015 3305-3313
132
Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression.
Genome Biol 17: 2016 33
23
Preservation Analysis of Macrophage Gene Coexpression Between Human and Mouse Identifies PARK2 as a Genetically Controlled Master Regulator of Oxidative Phosphorylation in Humans.
G3 (Bethesda) 6: 2016 3361-3371
12
Prioritizing Parkinson's disease genes using population-scale transcriptomic data.
Nat Commun 10: 2019 994
130
Tensor decomposition of stimulated monocyte and macrophage gene expression profiles identifies neurodegenerative disease-specific trans-eQTLs.
PLoS Genet 16: 2020 e1008549
17
A framework for integrating directed and undirected annotations to build explanatory models of cis-eQTL data.
PLoS Comput Biol 16: 2020 e1007770
2
Integration of Alzheimer's disease genetics and myeloid genomics identifies disease risk regulatory elements and genes.
Nat Commun 12: 2021 1610
215
Defining functional variants associated with Alzheimer's disease in the induced immune response.
Brain Commun 3: 2021 fcab083
25