Assigning credit where it's due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect.
Assigning credit where it's due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect.
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分配应有的信用：信息内容评分，以捕获变异效应多重测定的临床价值。
DOI：
10.1101/2023.10.20.562794
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Shirts,BrianH
中科院分区：
文献类型：
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作者：
Ranola,JohnMichaelO;Horton,Carrie;Pesaran,Tina;Fayer,Shawn;Starita,LeaM;Shirts,BrianH
背景变异体可以是致病性的，也可以是良性的，与人类疾病有关。目前从良性到致病的分类类别反映了目前理解的概率总结。变异效应多重检测（MAVE）临床实用性的主要指标是可从不确定显著性（VUS）中重新分类的变异数量。然而，这种效用衡量方法的一个缺陷是，它低估了从MAVE获得的信息。本研究的目的是开发一种改进的量化指标MAVE效用。我们建议采用一种信息含量方法，其中包括不对变体进行重新分类的数据，这将更好地反映真实的信息增益。我们采用信息量方法来评估BRCA 1、PTEN和TP 53的MAVE的信息增益（以比特为单位）。这里，1比特表示从没有信息开始完全分类单个变异所需的信息量。PTENMAVEs产生了2059.6 bits的信息，占BRCA 1错误信息总量的32.8%。TP53 MAVEs产生了277.8比特的信息，占TP 53中总错义信息的6.22%，占TP 53中总错义信息的3.5%。倍增加的信息，有助于VUS重新分类。结论信息内容的方法将更准确地描绘通过MAVE绘图工作获得的信息比通过计算重新分类的变体的数量更重要。这种信息含量方法还可以帮助定义指南变更的影响，这些变更修改了用于对变异组进行分类的信息定义。
BackgroundA variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of the current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, a gap in this measure of utility is that it underrepresents the information gained from MAVEs. The aim of this study was to develop an improved quantification metric for MAVE utility. We propose adopting an information content approach that includes data that does not reclassify variants will better reflect true information gain. We adopted an information content approach to evaluate the information gain, in bits, for MAVEs ofBRCA1,PTEN, andTP53.Here, one bit represents the amount of information required to completely classify a single variant starting from no information.ResultsBRCA1MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information inBRCA1and a 22-fold increase over the information that only contributed to VUS reclassification.PTENMAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information inPTENand an 85-fold increase over the information that contributed to VUS reclassification.TP53MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information inTP53and a 3.5-fold increase over the information that contributed to VUS reclassification.ConclusionsAn information content approach will more accurately portray information gained through MAVE mapping efforts than by counting the number of variants reclassified. This information content approach may also help define the impact of guideline changes that modify the information definitions used to classify groups of variants.