Manrai Arjun K, Funke Birgit H, Rehm Heidi L, Olesen Morten S, Maron Bradley A, Szolovits Peter, Margulies David M, Loscalzo Joseph, Kohane Isaac S
From the Departments of Biomedical Informatics (A.K.M., D.M.M., I.S.K.), Pathology (B.H.F.), and Medicine (B.A.M., J.L.), Harvard Medical School, the Departments of Pathology, Massachusetts General Hospital (B.H.F.), and the Department of Pathology (H.L.R.), Division of Cardiovascular Medicine (B.A.M.), and Department of Medicine (B.A.M., J.L.), Brigham and Women's Hospital, Boston, and the Division of Health Sciences and Technology, Harvard-Massachusetts Institute of Technology (MIT) (A.K.M., I.S.K.), the Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine (B.H.F., H.L.R.), and the Computer Science and Artificial Intelligence Laboratory, MIT (P.S.), Cambridge - all in Massachusetts; and the Laboratory of Molecular Cardiology, Department of Cardiology, the Heart Center, University Hospital of Copenhagen, Rigshospitalet, and the Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen (M.S.O.) - both in Copenhagen.
N Engl J Med. 2016 Aug 18;375(7):655-65. doi: 10.1056/NEJMsa1507092.
For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified.
Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory.
Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature.
The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).
十多年来,靶向基因检测增强了肥厚型心肌病的风险分层。临床医生利用测序结果常规评估患者亲属患肥厚型心肌病的风险,并对临床表现不明确的患者进行诊断。然而,基因检测在带来益处的同时,也存在变异可能被错误分类的风险。
利用公开可得的外显子组数据,我们识别出先前被认为是肥厚型心肌病致病原因且在普通人群中过度出现的变异。我们在不同人群中研究了这些变异,并重新评估了医学文献中对它们的最初认定。我们查阅了一家领先基因检测实验室近十年历史中的患者记录,以查找这些变异的出现情况。
多名患者(均为非洲裔或未明确祖籍)收到了阳性报告,基于检测时的认知,变异被错误分类为致病性的。随后,所有报告的变异都被重新分类为良性。在普通人群中最常见的突变在美国黑人中比在美国白人中明显更常见(P<0.001)。模拟结果表明,即使在对照队列中纳入少量美国黑人,可能也会防止这些错误分类。我们发现了医学文献中导致这些错误的方法学缺陷。
我们在研究中发现的将良性变异错误分类为致病性变异的情况表明,无论是在无症状对照人群还是受检患者人群中,都需要对不同人群的基因组进行测序。这些结果扩展了当前的指南,该指南建议使用与祖籍匹配的对照来解释变异。随着更多不同祖籍背景的人群进行测序,我们预计变异的重新分类将会增加,特别是对于历史上研究较少的祖籍群体。(由美国国立卫生研究院资助。)