What is the ACMG/AMP framework for variant classification, and what are the major evidence categories?

• A. A structured set of criteria including population data, computational predictions, functional data, segregation, de novo status, allelic data, and more to classify variants as pathogenic, likely pathogenic, VUS, likely benign, or benign.
• B. It relies solely on population frequency data.
• C. It uses exclusive functional assay results.
• D. It is based on clinician intuition without standardized criteria.

Answer: (A)

The ACMG/AMP framework provides a standardized, evidence-based way to classify genetic variants by integrating multiple lines of evidence rather than relying on a single test. The major categories of evidence include population data (how common the variant is in the general population and whether that frequency argues against pathogenicity), computational data (in silico predictions about impact on protein function or splicing, which support but do not determine classification), functional data (experimental studies showing an effect on gene or protein function), segregation data (whether the variant co-segregates with disease in families), de novo status (a variant that arises anew in an affected individual can strongly support pathogenicity in certain diseases), and allelic data (consideration of other known pathogenic variants in the same gene or in known hotspot regions). Additionally, case-control or observational data from the literature can inform interpretation. Each piece of evidence is given a strength (very strong, strong, moderate, or supporting), and the combination of evidence across these categories leads to the final five-tier classification: pathogenic, likely pathogenic, variant of uncertain significance, likely benign, or benign. This approach ensures variant interpretation reflects the total body of evidence rather than any single data source, guiding consistent and clinically meaningful decisions.