Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives
Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives
复制标题
DOI：
10.3389/fgene.2019.00601
复制
发表时间：
2019-06-25
影响因子：
3.7
通讯作者：
Wonkam, Ambroise
中科院分区：
文献类型：
--
作者：
Bope, Christian Domilongo;Chimusa, Emile R.;Wonkam, Ambroise
由于高通量技术能够快速检测和分析临床相关突变，基因组医学将极大地改善全球的临床护理。然而，电子预测方法的可变性和功能相关的遗传变异的分类在某些群体中可能会带来特殊的挑战。在电子突变方面，预测工具可能导致高的假阳性/阴性结果，特别是在遗传多样性最高的非洲基因组中，这些基因组在公共数据库和参考小组中的代表性不成比例地偏低。这些问题与最近增加的倡议特别相关，例如人类遗传与健康(H3 Africa)，这些倡议在缺乏政策指导基因组研究人员向研究参与者返回所谓可操作基因的变异结果的情况下产生了大量的基因组序列数据。这份报告(I)提供了一份非洲可公开获得的完整外显子组/基因组数据的清单，这有助于改进参考小组，探索可操作基因中致病变异的频率和相关挑战，(Ii)电子预测突变工具中可用的综述和新变异的致病分类标准，以及(Iii)为分析非洲基因组中的致病变异提出建议，以便在研究和临床实践中使用。总之，这项工作提出了在非洲人类基因研究和临床实践中确定突变致病性和可操作性的标准，并建议设立一个非洲专家小组来监督拟议的标准。
Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations. In silico mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available in silico prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria.