CADD score has limited clinical validity for the identification of pathogenic variants in noncoding regions in a hereditary cancer panel
CADD score has limited clinical validity for the identification of pathogenic variants in noncoding regions in a hereditary cancer panel
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DOI：
10.1038/gim.2016.44
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发表时间：
2016-12-01
影响因子：
8.8
通讯作者：
Shirts, Brian H.
中科院分区：
文献类型：
--
作者：
Mather, Cheryl A.;Mooney, Sean D.;Shirts, Brian H.
目的：几种计算机工具已被证明具有合理的研究敏感性和特异性，用于分类编码区域的序列变异。最近开发的联合注释依赖耗尽（CADD）方法可以对基因组所有区域（包括非编码区域）的单核苷酸变异（snv）产生预测分数。我们寻找非编码变异来确定常见CADD评分的临床有效性。方法：我们评估了624例患者样本中的12,391个独特的snv，这些样本在癌症相关基因小组中进行了种系突变检测。通过基因组区域分层，我们比较了罕见snv、患者群体中常见snv的CADD评分分布，以及所有可能snv的零分布。结果：罕见snv和常见snv的内含子变异和非同义变异的中位CADD评分差异有统计学意义（P < 0.0001）。尽管存在这些不同的分布，但在得分最高的罕见内含子变异中，没有个体变异被确定为合理的致病因素。非编码变异的受试者工作特征（ROC）曲线下面积（AUC）不大，在面板测试中发现，CADD对intronic变异的阳性预测值为0.088。结论：具有较高预测价值的集中计算机评分系统在临床基因组学应用中是必要的。
Purpose: Several in silico tools have been shown to have reasonable research sehsitivity and specificity for classifying sequence variants in coding regions. The recently developed combined annotation dependent depletion (CADD) method generates predictive scores for single-nucleotide variants (SNVs) in all areas of the genome, including noncoding regions. We sought for non-coding variants to determine the clinical validity of common CADD scores.Methods: We evaluated 12,391 unique SNVs in 624 patient samples submitted for germ-line mutation testing in a cancer-related gene panel. Stratifying by genomic region, we compared the distributions of CADD scores of rare SNVs, SNVs common in our patient population, and the null distribution of all possible SNVs.Results: The median CADD scores of intronic and nonsynonymous variants were significantly different between rare and common SNVs (P < 0.0001). Despite these different distributions, no individual variants could be identified as plausibly causative among the rare intronic variants with the highest scores. The receiver-operating characteristics (ROC) area under the curve (AUC) for noncoding variants is modest, and the positive predictive value of CADD for intronic variants in panel testing was found to be 0.088.Conclusion: Focused in silico scoring systems with much higher predictive value will be necessary for clinical genomic applications.