Modeling the ACMG/AMP Variant Classification Guidelines as a Bayesian Classification Framework

By Sean V. Tavtigian, M. Greenblatt, S. Harrison, R. Nussbaum, Snehit Prabhu, K. Boucher, Leslie G. Biesecker. Genetics in Medicine, 2018

498 citations recorded by the source corpus.

We evaluated the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) variant pathogenicity guidelines for internal consistency and compatibility with Bayesian statistical reasoning. The ACMG/AMP criteria were translated into a naive 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 variant of uncertain significance (VUS). By transforming the ACMG/AMP guidelines into a Bayesian framework, we provide a mathematical foundation for what was a qualitative heuristic. Only 2 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.

Subfields: Genetics, Pathology and Forensic Medicine

View Paper: https://www.semanticscholar.org/paper/3242cf9d54c562c611ea604e4db1354c291dfd3f

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Citations in the corpus

Adaptation and Validation of the ACMG/AMP variant classification framework for MYH7-associated inherited cardiomyopathies: Recommendations by ClinGen’s Inherited Cardiomyopathy Expert Panel (2018, unknown): “Allowing a variant to reach a likely benign classification based on BS1 alone represents a revision of the original ACMG/AMP framework by ClinGen’s Sequence Variant Interpretation Working Group 17 .”
Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion (2018, background): “It is relevant to note that in the Bayesian SVI formulation (Tavtigian et al., 2018), a very strong criterion alone generates a posterior probability of 0.”