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超越全基因组显著性:用于解释和扩展酒精使用障碍全基因组关联研究结果的综合方法。

Beyond genome-wide significance: integrative approaches to the interpretation and extension of GWAS findings for alcohol use disorder.

机构信息

Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA.

Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.

出版信息

Addict Biol. 2019 Mar;24(2):275-289. doi: 10.1111/adb.12591. Epub 2018 Jan 9.

Abstract

Alcohol use disorder (AUD) is a heritable complex behavior. Due to the highly polygenic nature of AUD, identifying genetic variants that comprise this heritable variation has proved to be challenging. With the exception of functional variants in alcohol metabolizing genes (e.g. ADH1B and ALDH2), few other candidate loci have been confidently linked to AUD. Genome-wide association studies (GWAS) of AUD and other alcohol-related phenotypes have either produced few hits with genome-wide significance or have failed to replicate on further study. These issues reinforce the complex nature of the genetic underpinnings for AUD and suggest that both GWAS studies with larger samples and additional analysis approaches that better harness the nominally significant loci in existing GWAS are needed. Here, we review approaches of interest in the post-GWAS era, including in silico functional analyses; functional partitioning of single nucleotide polymorphism heritability; aggregation of signal into genes and gene networks; and validation of identified loci, genes and gene networks in postmortem brain tissue and across species. These integrative approaches hold promise to illuminate our understanding of the biological basis of AUD; however, we recognize that the main challenge continues to be the extremely polygenic nature of AUD, which necessitates large samples to identify multiple loci associated with AUD liability.

摘要

酒精使用障碍(AUD)是一种遗传性复杂行为。由于 AUD 的高度多基因性质,确定构成这种遗传性变异的遗传变异一直具有挑战性。除了酒精代谢基因中的功能变异(例如 ADH1B 和 ALDH2)外,很少有其他候选基因座被可靠地与 AUD 相关联。AUD 和其他与酒精相关的表型的全基因组关联研究(GWAS)要么产生了很少具有全基因组意义的命中,要么在进一步研究中未能复制。这些问题强调了 AUD 遗传基础的复杂性,并表明需要更大样本的 GWAS 研究以及更好地利用现有 GWAS 中名义上显著基因座的其他分析方法。在这里,我们回顾了 GWAS 后时代的几种研究方法,包括计算功能分析、单核苷酸多态性遗传功能划分、信号在基因和基因网络中的聚集,以及在死后脑组织和跨物种中对鉴定出的基因座、基因和基因网络的验证。这些综合方法有望阐明我们对 AUD 生物学基础的理解;然而,我们认识到,主要挑战仍然是 AUD 的高度多基因性质,这需要大量样本才能确定与 AUD 易感性相关的多个基因座。

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