对于单例全外显子组测序(WES)数据的诊断分析,一个临床驱动的变异优先级排序框架优于单纯的计算方法。

A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data.

作者信息

Stark Zornitza, Dashnow Harriet, Lunke Sebastian, Tan Tiong Y, Yeung Alison, Sadedin Simon, Thorne Natalie, Macciocca Ivan, Gaff Clara, Oshlack Alicia, White Susan M, James Paul A

机构信息

Murdoch Childrens Research Institute, Melbourne, Australia.

University of Melbourne, Melbourne, Australia.

出版信息

Eur J Hum Genet. 2017 Nov;25(11):1268-1272. doi: 10.1038/ejhg.2017.123. Epub 2017 Aug 23.

Abstract

Rapid identification of clinically significant variants is key to the successful application of next generation sequencing technologies in clinical practice. The Melbourne Genomics Health Alliance (MGHA) variant prioritization framework employs a gene prioritization index based on clinician-generated a priori gene lists, and a variant prioritization index (VPI) based on rarity, conservation and protein effect. We used data from 80 patients who underwent singleton whole exome sequencing (WES) to test the ability of the framework to rank causative variants highly, and compared it against the performance of other gene and variant prioritization tools. Causative variants were identified in 59 of the patients. Using the MGHA prioritization framework the average rank of the causative variant was 2.24, with 76% ranked as the top priority variant, and 90% ranked within the top five. Using clinician-generated gene lists resulted in ranking causative variants an average of 8.2 positions higher than prioritization based on variant properties alone. This clinically driven prioritization approach significantly outperformed purely computational tools, placing a greater proportion of causative variants top or in the top 5 (permutation P-value=0.001). Clinicians included 40 of the 49 WES diagnoses in their a priori list of differential diagnoses (81%). The lists generated by PhenoTips and Phenomizer contained 14 (29%) and 18 (37%) of these diagnoses respectively. These results highlight the benefits of clinically led variant prioritization in increasing the efficiency of singleton WES data analysis and have important implications for developing models for the funding and delivery of genomic services.

摘要

快速识别具有临床意义的变异是下一代测序技术在临床实践中成功应用的关键。墨尔本基因组健康联盟(MGHA)的变异优先级框架采用了基于临床医生生成的先验基因列表的基因优先级指数,以及基于稀有性、保守性和蛋白质效应的变异优先级指数(VPI)。我们使用了80例接受单例全外显子测序(WES)患者的数据,来测试该框架对致病变异进行高排名的能力,并将其与其他基因和变异优先级工具的性能进行比较。在59例患者中鉴定出了致病变异。使用MGHA优先级框架,致病变异的平均排名为2.24,其中76%被列为最优先变异,90%排在前五位。使用临床医生生成的基因列表导致致病变异的排名比仅基于变异特性的优先级平均高出8.2个位置。这种临床驱动的优先级方法显著优于纯计算工具,将更大比例的致病变异排在首位或前五位(置换P值=0.001)。临床医生在其先验鉴别诊断列表中纳入了49例WES诊断中的40例(81%)。PhenoTips和Phenomizer生成的列表分别包含了这些诊断中的14例(29%)和18例(37%)。这些结果凸显了临床主导的变异优先级在提高单例WES数据分析效率方面的益处,并且对开发基因组服务的资金投入和提供模式具有重要意义。

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