Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome.
Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome.
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DOI：
10.1126/scitranslmed.3009262
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发表时间：
2014-09-03
影响因子：
17.1
通讯作者：
Robinson PN
中科院分区：
文献类型：
--
作者：
Zemojtel T;Köhler S;Mackenroth L;Jäger M;Hecht J;Krawitz P;Graul-Neumann L;Doelken S;Ehmke N;Spielmann M;Oien NC;Schweiger MR;Krüger U;Frommer G;Fischer B;Kornak U;Flöttmann R;Ardeshirdavani A;Moreau Y;Lewis SE;Haendel M;Smedley D;Horn D;Mundlos S;Robinson PN
只有不到一半的疑似遗传病患者得到了分子诊断。因此，我们将下一代测序(NGS)、生物信息学和临床数据整合到一个有效的诊断工作流程中。我们使用2741个已建立的孟德尔疾病基因[疾病相关基因组(DAG)]中的变异来开发有针对性的浓缩DAG小组(7.1Mb)，它实现了对98%的碱基的20倍或更高的覆盖。此外，我们建立了一种计算方法[外显子组的表型解释(Phenix)]，该方法根据人类表型本体论(HPO)术语描述的患者表型与3991种孟德尔疾病的表型的致病性和语义相似性来评估和排序变体。在计算机模拟中，根据变异分数对基因进行排序，将真实基因放在第一位的可能性不到5%；而菲尼克斯将正确基因放在第一位的可能性超过86%。在对52名之前发现的突变和已知诊断的患者进行的Phenix回顾测试中，正确的基因平均排名为2.1。在一项对40名没有诊断的人进行的前瞻性研究中，菲尼克斯分析使11例(28%，平均排名2.4)得到了诊断。因此，DAG的NGS和表型驱动的生物信息学分析可以快速有效地在医学遗传学中进行鉴别诊断。
Less than half of patients with suspected genetic disease receive a molecular diagnosis. We have therefore integrated next-generation sequencing (NGS), bioinformatics, and clinical data into an effective diagnostic workflow. We used variants in the 2741 established Mendelian disease genes [the disease-associated genome (DAG)] to develop a targeted enrichment DAG panel (7.1 Mb), which achieves a coverage of 20-fold or better for 98% of bases. Furthermore, we established a computational method [Phenotypic Interpretation of eXomes (PhenIX)] that evaluated and ranked variants based on pathogenicity and semantic similarity of patients’ phenotype described by Human Phenotype Ontology (HPO) terms to those of 3991 Mendelian diseases. In computer simulations, ranking genes based on the variant score put the true gene in first place less than 5% of the time; PhenIX placed the correct gene in first place more than 86% of the time. In a retrospective test of PhenIX on 52 patients with previously identified mutations and known diagnoses, the correct gene achieved a mean rank of 2.1. In a prospective study on 40 individuals without a diagnosis, PhenIX analysis enabled a diagnosis in 11 cases (28%, at a mean rank of 2.4). Thus, the NGS of the DAG followed by phenotype-driven bioinformatic analysis allows quick and effective differential diagnostics in medical genetics.