Invitae, San Francisco, California, USA.
Volunteer Clinical Faculty, University of California, San Francisco, California, USA.
Genet Med. 2017 Oct;19(10):1118-1126. doi: 10.1038/gim.2017.60. Epub 2017 Jun 1.
PurposeClinVar is increasingly used as a resource for both genetic variant interpretation and clinical practice. However, controversies exist regarding the consistency of classifications in ClinVar, and questions remain about how best to use these data. Our study systematically examined ClinVar to identify common sources of discordance and thus inform ongoing practices.MethodsWe analyzed variants that had multiple classifications in ClinVar, excluding benign polymorphisms. Classifications were categorized by potential actionability and pathogenicity. Consensus interpretations were calculated for each variant, and the properties of the discordant outlier classifications were summarized.ResultsOur study included 74,065 classifications of 27,224 unique variants in 1,713 genes. We found that (i) concordance rates differed among clinical areas and variant types; (ii) clinical testing methods had much higher concordance than basic literature curation and research efforts; (iii) older classifications had greater discordance than newer ones; and (iv) low-penetrance variants had particularly high discordance.ConclusionRecent variant classifications from clinical testing laboratories have high overall concordance in many (but not all) clinical areas. ClinVar can be a reliable resource supporting variant interpretation, quality assessment, and clinical practice when factors uncovered in this study are taken into account. Ongoing improvements to ClinVar may make it easier to use, particularly for nonexpert users.
目的
ClinVar 越来越多地被用作遗传变异解释和临床实践的资源。然而,ClinVar 中的分类一致性存在争议,关于如何最好地使用这些数据的问题仍然存在。我们的研究系统地检查了 ClinVar,以确定常见的不一致来源,从而为正在进行的实践提供信息。
方法
我们分析了 ClinVar 中具有多个分类的变异,排除良性多态性。分类按潜在的可操作性和致病性进行分类。为每个变体计算了共识解释,并总结了不一致的异常分类的属性。
结果
我们的研究包括 1713 个基因中的 27224 个独特变体的 74065 个分类。我们发现:(i)临床领域和变异类型之间的一致性率不同;(ii)临床检测方法的一致性明显高于基本文献整理和研究工作;(iii)旧分类的不一致性大于新分类;(iv)低外显率变体的不一致性特别高。
结论
在许多(但不是全部)临床领域,来自临床检测实验室的最新变异分类具有很高的总体一致性。当考虑到本研究中发现的因素时,ClinVar 可以成为支持变异解释、质量评估和临床实践的可靠资源。ClinVar 的持续改进可能使其更易于使用,尤其是对于非专家用户。