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本文引用的文献

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Genome-wide significance testing of variation from single case exomes.单例外显子组变异的全基因组显著性检验。
Nat Genet. 2016 Dec;48(12):1455-1461. doi: 10.1038/ng.3697. Epub 2016 Oct 24.
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Analysis of protein-coding genetic variation in 60,706 humans.对60706名人类的蛋白质编码基因变异进行分析。
Nature. 2016 Aug 18;536(7616):285-91. doi: 10.1038/nature19057.
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The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities.孟德尔表型的遗传基础:发现、挑战与机遇
Am J Hum Genet. 2015 Aug 6;97(2):199-215. doi: 10.1016/j.ajhg.2015.06.009. Epub 2015 Jul 9.
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ClinGen--the Clinical Genome Resource.ClinGen——临床基因组资源。
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A new initiative on precision medicine.一项关于精准医学的新倡议。
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6
Guidelines for investigating causality of sequence variants in human disease.人类疾病中序列变异因果关系研究指南。
Nature. 2014 Apr 24;508(7497):469-76. doi: 10.1038/nature13127.
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Statistical power and significance testing in large-scale genetic studies.大规模遗传研究中的统计功效和显著性检验。
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Targeted and genomewide NGS data disqualify mutations in MYO1A, the "DFNA48 gene", as a cause of deafness.靶向和全基因组的二代测序数据排除了“DFNA48基因”即肌球蛋白1A(MYO1A)中的突变是导致耳聋的原因。
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ClinVar: public archive of relationships among sequence variation and human phenotype.ClinVar:序列变异与人类表型之间关系的公共档案。
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评估基因与疾病关联的临床有效性:临床基因组资源开发的循证框架

Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource.

作者信息

Strande Natasha T, Riggs Erin Rooney, Buchanan Adam H, Ceyhan-Birsoy Ozge, DiStefano Marina, Dwight Selina S, Goldstein Jenny, Ghosh Rajarshi, Seifert Bryce A, Sneddon Tam P, Wright Matt W, Milko Laura V, Cherry J Michael, Giovanni Monica A, Murray Michael F, O'Daniel Julianne M, Ramos Erin M, Santani Avni B, Scott Alan F, Plon Sharon E, Rehm Heidi L, Martin Christa L, Berg Jonathan S

机构信息

Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.

Autism & Developmental Medicine Institute, Geisinger Health System, Danville, PA 17837, USA.

出版信息

Am J Hum Genet. 2017 Jun 1;100(6):895-906. doi: 10.1016/j.ajhg.2017.04.015. Epub 2017 May 25.

DOI:10.1016/j.ajhg.2017.04.015
PMID:28552198
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5473734/
Abstract

With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: "Definitive," "Strong," "Moderate," "Limited," "No Reported Evidence," or "Conflicting Evidence." Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.

摘要

随着基因组测序技术的进步,已报道的基因与疾病关系的数量迅速增加。然而,支持这些关系的证据差异很大,这使得在临床环境中对基因组变异进行准确评估变得复杂。尽管迫切需要区分临床有效关系和证据不足的关系,但目前尚不存在此类评估的标准指南。美国国立卫生研究院资助的临床基因组资源(ClinGen)已经开发了一个框架,用于定义和评估各种孟德尔疾病中基因与疾病对的临床有效性。在本手稿中,我们描述了一个提议的框架,用于评估支持或反驳基因与疾病关系的相关遗传和实验证据,以及随后使用一组代表性基因与疾病对来验证该框架。该框架为基因与疾病关系的证据强度提供了一种半定量测量方法,该方法与定性分类相关:“确定”、“强”、“中等”、“有限”、“无报告证据”或“矛盾证据”。在ClinGen结构中,基于该框架得出的分类将根据适当疾病专家的临床专业知识进行审查、确认或调整。我们的网站上提供了使用此框架的详细指南以及访问管理界面的途径。这种基于证据的、系统的评估基因与疾病关系强度的方法将有助于在临床和研究环境中更明智地利用基因组变异。