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首页> 外文期刊>Arteriosclerosis, thrombosis, and vascular biology >2018 George Lyman Duff Memorial Lecture Genetics and Genomics of Coronary Artery Disease: A Decade of Progress
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2018 George Lyman Duff Memorial Lecture Genetics and Genomics of Coronary Artery Disease: A Decade of Progress

机译:2018年乔治莱曼Duff纪念讲座遗传学和冠状动脉疾病的基因组学:十年进步

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Recent studies have led to a broader understanding of the genetic architecture of coronary artery disease and demonstrate that it largely derives from the cumulative effect of multiple common risk alleles individually of small effect size rather than rare variants with large effects on coronary artery disease risk. The tools applied include genome-wide association studies encompassing over 200 000 individuals complemented by bioinformatic approaches including imputation from whole-genome data sets, expression quantitative trait loci analyses, and interrogation of ENCODE (Encyclopedia of DNA Elements), Roadmap Epigenetic Project, and other data sets. Over 160 genome-wide significant loci associated with coronary artery disease risk have been identified using the genome-wide association studies approach, 90% of which are situated in intergenic regions. Here, I will describe, in part, our research over the last decade performed in collaboration with a series of bright trainees and an extensive number of groups and individuals around the world as it applies to our understanding of the genetic basis of this complex disease. These studies include computational approaches to better understand missing heritability and identify causal pathways, experimental approaches, and progress in understanding at the molecular level the function of the multiple risk loci identified and potential applications of these genomic data in clinical medicine and drug discovery.
机译:最近的研究导致对冠状动脉疾病的遗传建筑更广泛地了解,并证明它在很大程度上来自多种常见风险等位基因的累积效应小的效果大小,而不是对冠状动脉疾病风险的大量影响的罕见变种。应用的工具包括基因组 - 范围内的基因组关联研究,包括生物信息化方法,包括来自全基因组数据集的估算,表达定量性状点分析,以及编码(DNA元素的百科全书),路线图表述项目等的审讯数据集。已经使用基因组关联研究方法确定了与冠状动脉疾病风险相关的160多个基因组显着的基因座,其中90%位于非基因区域。在这里,我将部分地描述我们在过去十年中,与一系列明亮的学员和世界各地的广泛团体和个人合作,因为它适用于我们对这种复杂疾病的遗传基础的理解。这些研究包括更好地理解遗传性和识别因果途径,实验方法以及在分子水平的情况下识别的多种风险基因座的函数和潜在应用这些基因组数据在临床医学和药物发现中的潜在应用的方法。

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