Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.
Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.
复制标题
DOI：
10.1038/gim.2017.210
复制
发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI)
中科院分区：
文献类型：
--
作者：
Tavtigian SV;Greenblatt MS;Harrison SM;Nussbaum RL;Prabhu SA;Boucher KM;Biesecker LG;ClinGen Sequence Variant Interpretation Working Group (ClinGen SVI)
我们评估了ACMG/AMP变异致病性指南的内部一致性和与贝叶斯统计推理的兼容性。ACMG/AMP标准被翻译成朴素贝叶斯分类器，假设四个证据水平和指数级致病性几率。我们用一系列先验概率和致病性几率测试了这个框架。我们使用生物学上合理的假设来模拟ACMG/AMP指南。大多数ACMG/AMP联合标准是相容的。一种ACMG/AMP可能的致病性组合在数学上等同于致病性，一种ACMG/AMP致病性组合实际上可能是致病性的。我们对包括支持和反对致病性的证据的组合进行了建模，表明我们的方法将一些组合评分为致病性或可能致病性，ACMG/AMP将其指定为VUS。通过将ACMG/AMP指南转换为贝叶斯框架，我们为定性启发式提供了数学基础。在现有的18个ACMG/AMP证据组合中，只有两个在数学上与整体框架不一致。致病性和良性证据的混合组合可能产生可能的致病性、可能的良性或VUS结果。该定量框架验证了ACMG/AMP采用的方法，提供了进一步完善证据类别和组合规则的机会，并支持自动化变异致病性评估组件的努力。
We evaluated the ACMG/AMP variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning. The ACMG/AMP criteria were translated into a naïve Bayesian classifier, assuming four levels of evidence and exponentially scaled odds of pathogenicity. We tested this framework with a range of prior probabilities and odds of pathogenicity. We modeled the ACMG/AMP guidelines using biologically plausible assumptions. Most ACMG/AMP combining criteria were compatible. One ACMG/AMP likely pathogenic combination was mathematically equivalent to pathogenic and one ACMG/AMP pathogenic combination was actually likely pathogenic. We modeled combinations that include evidence for and against pathogenicity, showing that our approach scored some combinations as pathogenic or likely pathogenic that ACMG/AMP would designate as VUS. By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only two of the 18 existing ACMG/AMP evidence combinations were mathematically inconsistent with the overall framework. Mixed combinations of pathogenic and benign evidence could yield a likely pathogenic, likely benign, or VUS result. This quantitative framework validates the approach adopted by the ACMG/AMP, provides opportunities to further refine evidence categories and combining rules, and supports efforts to automate components of variant pathogenicity assessments.
登录
查看更多内容
影响因子：
9.8
作者：
Easton, Douglas F.;Deffenbaugh, Amie M.;Goldgar, David E.
通讯作者：
Goldgar, David E.
影响因子：
3.9
作者：
Thompson, Bryony A.;Goldgar, David E.;Paterson, Carol;Clendenning, Mark;Walters, Rhiannon;Arnold, Sven;Parsons, Michael T.;Walsh, Michael D.;Gallinger, Steven;Haile, Robert W.;Hopper, John L.;Jenkins, Mark A.;LeMarchand, Loic;Lindor, Noralane M.;Newcomb, Polly A.;Thibodeau, Stephen N.;Young, Joanne P.;Buchanan, Daniel D.;Tavtigian, Sean V.;Spurdle, Amanda B.
通讯作者：
Spurdle, Amanda B.
影响因子：
9.8
作者：
Goldgar, DE;Easton, DF;Couch, FJ
通讯作者：
Couch, FJ
影响因子：
3.9
作者：
Tavtigian, Sean V.;Byrnes, Graham B.;Goldgar, David E.;Thomas, Alun
通讯作者：
Thomas, Alun
影响因子：
9.8
作者：
Thompson, D;Easton, DF;Goldgar, DE
通讯作者：
Goldgar, DE