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分子特征的遗传关联:有助于识别复杂疾病中的因果变异。

Genetic association of molecular traits: A help to identify causative variants in complex diseases.

机构信息

Univ Paris Diderot, Sorbonne Paris Cité, Paris, France.

出版信息

Clin Genet. 2018 Mar;93(3):520-532. doi: 10.1111/cge.13187.

Abstract

In the past 15 years, major progresses have been made in the understanding of the genetic basis of regulation of gene expression. These new insights have revolutionized our approach to resolve the genetic variation underlying complex diseases. Gene transcript levels were the first expression phenotypes that were studied. They are heritable and therefore amenable to genome-wide association studies. The genetic variants that modulate them are called expression quantitative trait loci. Their study has been extended to other molecular quantitative trait loci (molQTLs) that regulate gene expression at the various levels, from chromatin state to cellular responses. Altogether, these studies have generated a wealth of basic information on the genome-wide patterns of gene expression and their inter-individual variation. Most importantly, molQTLs have become an invaluable asset in the genetic study of complex diseases. Although the identification of the disease-causing variants on the basis of their overlap with molQTLs requires caution, molQTLs can help to prioritize the relevant candidate gene(s) in the disease-associated regions and bring a functional interpretation of the associated variants, therefore, bridging the gap between genotypes and clinical phenotypes.

摘要

在过去的 15 年中,人们在理解基因表达调控的遗传基础方面取得了重大进展。这些新的认识彻底改变了我们解决复杂疾病遗传变异的方法。基因转录水平是第一个被研究的表达表型。它们是可遗传的,因此适合进行全基因组关联研究。调节它们的遗传变异被称为表达数量性状基因座。对它们的研究已经扩展到其他分子数量性状基因座(molQTLs),这些基因座可以在从染色质状态到细胞反应的各个水平上调节基因表达。总的来说,这些研究为全基因组基因表达模式及其个体间变异提供了丰富的基础信息。最重要的是,molQTLs 已成为复杂疾病遗传研究中非常宝贵的资源。虽然根据与 molQTLs 的重叠来识别致病变异需要谨慎,但 molQTLs 可以帮助在疾病相关区域中确定相关候选基因,并对相关变异进行功能解释,从而弥合基因型和临床表型之间的差距。

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