背景:遗传变异数据库有助于临床医生和研究人员解释遗传变异。然而,这些数据库包含一些错误分类的变体。随着这些数据库的迅速发展和实施新的指南,变体错误分类是否正在减弱尚不清楚。
方法:使用ClinVar和HGMD的档案,我们调查了6年来变异错误分类的变化,跨越不同的祖先群体。我们将在新生儿中筛查的先天性代谢错误(IEM)视为模型系统,因为这些疾病通常对新生儿表型具有高度渗透性。我们使用来自1000基因组计划(1KGP)的样本来鉴定具有被数据库分类为致病性的基因型的个体。由于IEM的稀有性,几乎所有此类分类的致病基因型都表明ClinVar或HGMD中可能存在变异错误分类。
结果:虽然ClinVar和HGMD的假阳性率随着时间的推移有所改善,HGMD变体目前暗示1KGP中受影响的个体比ClinVar变体多两个数量级。我们观察到,当使用HGMD变体时,非洲血统个体被错误地指示受筛选的IEM影响的机会显着增加。然而,一旦根据最近的变异分类指南去除常见变异,这种影响非洲血统基因组的偏倚就不再显著.我们发现分类为致病性或可能致病性的ClinVar变体的重新分类频率比DM或DM?HGMD中的变体高六倍,这可能导致ClinVar的假阳性率较低。
结论:考虑到已被重新分类的错误分类变异,揭示了我们对罕见遗传变异的认识不断提高。我们发现,变异分类指南和包含遗传多样性样本的等位基因频率数据库是重新分类的重要因素。我们还发现,在欧洲和南亚个体中常见的ClinVar变体更有可能被重新分类为较低的置信度类别。可能是由于这些变体被多个提交者分类的机会增加。我们讨论了变体分类数据库的功能,这些功能将支持它们的持续改进。
Curated databases of genetic variants assist clinicians and researchers in interpreting genetic variation. Yet, these databases contain some misclassified variants. It is unclear whether variant misclassification is abating as these databases rapidly grow and implement new guidelines.
Using archives of
ClinVar and HGMD, we investigated how variant misclassification has changed over 6 years, across different ancestry groups. We considered inborn errors of metabolism (IEMs) screened in newborns as a model system because these disorders are often highly penetrant with neonatal phenotypes. We used samples from the 1000 Genomes Project (1KGP) to identify individuals with genotypes that were classified by the databases as pathogenic. Due to the rarity of IEMs, nearly all such classified pathogenic genotypes indicate likely variant misclassification in
ClinVar or HGMD.
While the false-positive rates of both ClinVar and HGMD have improved over time, HGMD variants currently imply two orders of magnitude more affected individuals in 1KGP than
ClinVar variants. We observed that African ancestry individuals have a significantly increased chance of being incorrectly indicated to be affected by a screened IEM when HGMD variants are used. However, this bias affecting genomes of African ancestry was no longer significant once common variants were removed in accordance with recent variant classification guidelines. We discovered that ClinVar variants classified as Pathogenic or Likely Pathogenic are reclassified sixfold more often than DM or DM? variants in HGMD, which has likely resulted in
ClinVar\'s lower false-positive rate.
Considering misclassified variants that have since been reclassified reveals our increasing understanding of rare genetic variation. We found that variant classification guidelines and allele frequency databases comprising genetically diverse samples are important factors in reclassification. We also discovered that
ClinVar variants common in European and South Asian individuals were more likely to be reclassified to a lower confidence category, perhaps due to an increased chance of these variants being classified by multiple submitters. We discuss features for variant classification databases that would support their continued improvement.