The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics.
The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics.
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DOI：
10.1002/humu.23644
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发表时间：
2018-11
期刊：
影响因子：
3.9
通讯作者：
Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group (ADWG)
中科院分区：
文献类型：
--
作者：
Popejoy AB;Ritter DI;Crooks K;Currey E;Fullerton SM;Hindorff LA;Koenig B;Ramos EM;Sorokin EP;Wand H;Wright MW;Zou J;Gignoux CR;Bonham VL;Plon SE;Bustamante CD;Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group (ADWG)
临床基因组资源(Clingen)祖先和多样性工作组强调需要制定关于种族、民族和祖先(REA)数据收集和在临床基因组学中使用的指南。我们提供了定量和定性的证据来表征：1)通过临床实验室申请表获取REA数据，以及2)基因组聚合数据库(GnomAD)中临床相关位置的信息差异(从ClinVar中的注释确定)。我们的申请表分析显示，在临床实验室确定REA方面存在实质性的异质性，并且用于定义REA类别的术语之间存在明显的不一致。在不同的REA人群中，有关gnomAD临床相关变异的信息量也存在显著差异。欧洲祖先群体构成了观察(55.8%)、等位基因计数(59.7%)和私有等位基因(56.1%)的大多数，在ClinVar中有550个基因座的“致病”和“可能致病”变异。我们的发现强调了实施和支持增加基因组测序和临床基因组学多样性的计划的重要性，以及测量用于变异解释的种群水平数据集的不确定性。最后，我们建议有必要通过伙伴关系和合作开发标准化的REA数据收集框架，并在临床基因组学中采用。
The Clinical Genome Resource (ClinGen) Ancestry and Diversity Working Group highlights the need to develop guidance on race, ethnicity, and ancestry (REA) data collection and use in clinical genomics. We present quantitative and qualitative evidence to characterize: 1) acquisition of REA data via clinical laboratory requisition forms, and 2) information disparity across populations in the Genome Aggregation Database (gnomAD) at clinically relevant sites ascertained from annotations in ClinVar. Our requisition form analysis showed substantial heterogeneity in clinical laboratory ascertainment of REA, as well as marked incongruity among terms used to define REA categories. There was also striking disparity across REA populations in the amount of information available about clinically relevant variants in gnomAD. European ancestral populations constituted the majority of observations (55.8%), allele counts (59.7%), and private alleles (56.1%) in gnomAD at 550 loci with “pathogenic” and “likely pathogenic” expert-reviewed variants in ClinVar. Our findings highlight the importance of implementing and supporting programs to increase diversity in genome sequencing and clinical genomics, as well as measuring uncertainty around population-level datasets that are used in variant interpretation. Finally, we suggest the need for a standardized REA data collection framework to be developed through partnerships and collaborations and adopted across clinical genomics.
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