Evidence-based calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for clinical use of PP3/BP4 criteria
Evidence-based calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for clinical use of PP3/BP4 criteria
复制标题
错义变异致病性分类计算工具的循证校准和 PP3/BP4 标准临床使用的 ClinGen 建议
DOI：
10.1101/2022.03.17.484479
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
S. Brenner
中科院分区：
文献类型：
--
作者：
V. Pejaver;Alicia B. Byrne;B. Feng;K. Pagel;S. Mooney;R. Karchin;A. O’Donnell;S. Harrison;S. Tavtigian;M. Greenblatt;L. Biesecker;P. Radivojac;S. Brenner
美国医学遗传学和基因组学学院以及分子病理学协会 (ACMG/AMP) 关于解释序列变异的建议指定使用计算预测因子作为分别使用标准 PP3 和 BP4 的致病性或良性证据的支持级别。然而，工具开发人员定义的评分区间以及需要多个预测变量达成共识的 ACMG/AMP 建议缺乏定量支持。之前，我们描述了一个概率框架，用于量化 ACMG/AMP 建议中的证据强度（支持、中等、强、非常强）。我们已将此框架扩展到计算预测器，并引入了一个新标准，可将工具的分数转换为 PP3 和 BP4 证据强度。我们的方法基于估计局部阳性预测值，并且可以校准任何计算工具或任何变异类型的其他连续规模证据。我们使用精心组装的独立数据集，估计了与十三个错义变异解释工具的致病性和良性证据强度相对应的阈值（评分区间）。大多数工具使用新建立的阈值实现了致病性和良性分类的支持证据水平。多种工具达到了中等程度的分数阈值，并且有几种工具达到了强有力的证据水平。一种工具对于某些变体的良性分类达到了非常强的证据级别。基于这些发现，我们使用单独的工具和未来对临床解释计算方法的评估，为 PP3 和 BP4 ACMG/AMP 标准的循证修订提供建议。
Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as Supporting level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (Supporting, Moderate, Strong, Very Strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool’s scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved Supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying Moderate and several reached Strong evidence levels. One tool reached Very Strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.
影响因子：
7
作者：
Pollard, Katherine S.;Hubisz, Melissa J.;Siepel, Adam
通讯作者：
Siepel, Adam
影响因子：
9.8
作者：
Ioannidis, Nilah M.;Rothstein, Joseph H.;Sieh, Weiva
通讯作者：
Sieh, Weiva
影响因子：
5.6
作者：
Peterson, Thomas A.;Doughty, Emily;Kann, Maricel G.
通讯作者：
Kann, Maricel G.