Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
McGill University and Genome Quebec Innovation Centre, Montreal, Quebec, Canada.
Hum Mutat. 2018 Feb;39(2):197-201. doi: 10.1002/humu.23374. Epub 2017 Dec 14.
A significant challenge facing clinical translation of exome sequencing is meaningful and efficient variant interpretation. Each exome contains ∼500 rare coding variants; laboratories must systematically and efficiently identify which variant(s) contribute to the patient's phenotype. In silico filtering is an approach that reduces analysis time while decreasing the chances of incidental findings. We retrospectively assessed 55 solved exomes using available datasets as in silico filters: Online Mendelian Inheritance in Man (OMIM), Orphanet, Human Phenotype Ontology (HPO), and Radboudumc University Medical Center curated panels. We found that personalized panels produced using HPO terms for each patient had the highest success rate (100%), while producing considerably less variants to assess. HPO panels also captured multiple diagnoses in the same individual. We conclude that custom HPO-derived panels are an efficient and effective way to identify clinically relevant exome variants.
外显子组测序的临床转化面临的一个重大挑战是有意义且高效的变异解释。每个外显子组包含约 500 个罕见的编码变异;实验室必须系统且高效地确定哪些变异(s)导致了患者的表型。计算筛选是一种可以减少分析时间并降低偶然发现的可能性的方法。我们使用现有的数据集作为计算筛选器,对 55 个已解决的外显子组进行了回顾性评估:在线孟德尔遗传数据库(OMIM)、孤儿疾病数据库、人类表型本体(HPO)和拉德堡德大学医学中心 curated 面板。我们发现,针对每个患者使用 HPO 术语生成的个性化面板具有最高的成功率(100%),同时评估的变异数量也显著减少。HPO 面板还可以在同一个体中捕获多个诊断。我们得出结论,定制的 HPO 衍生面板是一种有效且高效的方法,可以识别临床上相关的外显子变异。