AIMS: With the availability of genome-wide genotype data from GWAS studies, it is now possible to compute the genetic relatedness among individuals and estimate its contribution (SNP-based heritability) to phenotypic variance using Mixed-Linear-Models (MLMs). The estimated heritability can be partitioned according to biological features to gain insight into the genetic architecture of a disease. Here, we aimed to examine the genetic structure of coronary artery disease (CAD). METHODS AND RESULTS: We investigated the genetic structure of CAD using 3,163,082 autosomal genome-wide SNPs (MAF ≥ 0.01) and MLMs in a sample of genetically 'unrelated' 4535 cases and 2977 controls. We find that genome-wide SNPs explain 22% of liability to CAD (55% of narrow-sense heritability) and sex-differences in CAD is not due to common SNPs on autosomal chromosomes. Heritability was proportionally distributed across the allele frequency spectrum and notably enriched among genic SNPs. We identified a number of modules that are significantly associated with CAD including: Dendritic cells stimulation; Basigin interactions; and a Cancer module. Of note, genes involved in inflammation account for one-fifth of SNP-based heritability. Heritability-enrichment analysis showed significant enrichment in epigenetic sites associated with transcriptionally activity; namely, enhancers, H3K9ac/H3K27ac/H3K4me1/H3K4me3 histone modifications, and Fetal DNase I hypersensitivity sites whereas heritability was highly depleted in transcriptionally repressed regions. CONCLUSIONS: More individual SNP associations will be detected for CAD as sample size increases. The identified modules provide further biological insight for CAD and highlight the importance of immune-mediated processes in CAD pathogenesis. Finally, we showed that genetic liability to CAD is mainly attributed to epigenetic sites associated with transcriptional activity which encourage the design of custom sequencing/genotyping panels based on transcriptionally active regions. Published on behalf of the European Society of Cardiology. All rights reserved.
AIMS: With the availability of genome-wide genotype data from GWAS studies, it is now possible to compute the genetic relatedness among individuals and estimate its contribution (SNP-based heritability) to phenotypic variance using Mixed-Linear-Models (MLMs). The estimated heritability can be partitioned according to biological features to gain insight into the genetic architecture of a disease. Here, we aimed to examine the genetic structure of coronary artery disease (CAD). METHODS AND RESULTS: We investigated the genetic structure of CAD using 3,163,082 autosomal genome-wide SNPs (MAF ≥ 0.01) and MLMs in a sample of genetically 'unrelated' 4535 cases and 2977 controls. We find that genome-wide SNPs explain 22% of liability to CAD (55% of narrow-sense heritability) and sex-differences in CAD is not due to common SNPs on autosomal chromosomes. Heritability was proportionally distributed across the allele frequency spectrum and notably enriched among genic SNPs. We identified a number of modules that are significantly associated with CAD including: Dendritic cells stimulation; Basigin interactions; and a Cancer module. Of note, genes involved in inflammation account for one-fifth of SNP-based heritability. Heritability-enrichment analysis showed significant enrichment in epigenetic sites associated with transcriptionally activity; namely, enhancers, H3K9ac/H3K27ac/H3K4me1/H3K4me3 histone modifications, and Fetal DNase I hypersensitivity sites whereas heritability was highly depleted in transcriptionally repressed regions. CONCLUSIONS: More individual SNP associations will be detected for CAD as sample size increases. The identified modules provide further biological insight for CAD and highlight the importance of immune-mediated processes in CAD pathogenesis. Finally, we showed that genetic liability to CAD is mainly attributed to epigenetic sites associated with transcriptional activity which encourage the design of custom sequencing/genotyping panels based on transcriptionally active regions. Published on behalf of the European Society of Cardiology. All rights reserved.
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