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在基因组学的新时代推断基因组变异的影响。

Inferring the effect of genomic variation in the new era of genomics.

机构信息

Department of Human Genetics, Emory University School of Medicine, Whitehead Biomedical Research Building Suite 301, Atlanta, Georgia.

出版信息

Hum Mutat. 2018 Jun;39(6):756-773. doi: 10.1002/humu.23427. Epub 2018 Apr 22.

DOI:10.1002/humu.23427
PMID:29633501
Abstract

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

摘要

准确而详细地了解基因组编码区和非编码区变异的影响,是个性化医疗新基因组时代的下一个重大挑战,特别是为了解决疾病遗传和表型异质性的新发现。这对于解决基因-变异-疾病关系、基因的致病变异谱、具有可变临床后果的致病变异以及多基因疾病是必要的。反过来,这将有助于为相关临床试验招募患者。在这篇综述中,我们描述了基础和临床基因组学交叉领域的研究趋势,旨在(a)克服分子诊断挑战,提高下一代测序(NGS)平台的临床实用性,(b)阐明与疾病相关的变异,(c)确定包括上位性在内的整体基因组复杂性、协同杂合性等复杂遗传模式、双基因/多基因遗传、修饰效应和罕见变异负荷。我们描述了新兴的综合功能基因组学领域,即体内或体外大规模功能方法,以及支持 NGS 基因组学数据解释变异以进行及时临床诊断和疾病管理的统计生物信息学算法。因此,促进了新的治疗或生物标志物选择的发现,以及它们在个性化医疗未来中的作用。

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