Mapping novel pathways in cardiovascular disease using eQTL data: the past, present, and future of gene expression analysis
Mapping novel pathways in cardiovascular disease using eQTL data: the past, present, and future of gene expression analysis
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DOI：
10.3389/fgene.2012.00232
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发表时间：
2013-01-01
影响因子：
3.7
通讯作者：
Musunuru, Kiran
中科院分区：
文献类型：
--
作者：
Gupta, Rajat M.;Musunuru, Kiran
全基因组关联研究（GWAS）已经发现了与许多心血管和代谢疾病相关的遗传变异。新发现的与心肌梗死、血脂异常、高血压、糖尿病和胰岛素抵抗相关的多态性提示了这些和其他复杂疾病的新机制途径。考虑到迄今为止鉴定的非编码变体的数量，确定GWAS中鉴定的多态性与其生物学机制之间的联系尤其具有挑战性。在这篇综述中，我们讨论了表达数量性状基因座（eQIL）数据库在研究非编码变异体与心血管和代谢表型的效用。最近成功地使用eQTL数据与功能候选基因的变异链接将进行审查，这种方法的缺点将概述。最后，我们讨论了新兴的下一代eQTL的研究，利用的能力，从人口队列产生诱导多能干细胞系。
Genome-wide association studies (GWAS) have identified genetic variants associated with numerous cardiovascular and metabolic diseases. Newly identified polymorphisms associated with myocardial infarction, dyslipidemia, hypertension, diabetes, and insulin resistance suggest novel mechanistic pathways that underlie these and other complex diseases. Working out the connections between the polymorphisms identified in GWAS and their biological mechanisms has been especially challenging given the number of non-coding variants identified thus far. In this review, we discuss the utility of expression quantitative trait locus (eQIL) databases in the study of non-coding variants with respect to cardiovascular and metabolic phenotypes. Recent successes in using eQTL data to link variants with functional candidate genes will be reviewed, and the shortcomings of this approach will be outlined. Finally, we discuss the emerging next generation of eQTL studies that take advantage of the ability to generate induced pluripotent stem cell lines from population cohorts.