Table 1:

Categories of Evidence Used in Genetic Variant Interpretation^*

Category	Examples
Population and patient data	• Variant prevalence higher than disease prevalence provides strong evidence for benign classification • Statistical increase in prevalence of variant among affected individuals provides strong evidence of pathogenicity; this criterion is challenging for rare variants. • Match of the patient’s clinical features with those of the condition associated with the gene supports pathogenicity.
Segregation data	• Lack of segregation of variant with disease provides strong evidence for benign classification • Segregation of variant with disease provides evidence of pathogenicity, with strength of evidence increasing with number of families studied
De novo data	• De novo variant (not present in either parent) in a relevant gene is more likely to be pathogenic; strength of evidence is increased if maternity and paternity are confirmed
Functional data	• Studies indicating no deleterious effect on gene function provide strong evidence for benign classification • Studies indicating a deleterious effect on gene function provide strong evidence for pathogenicity
Computational and predictive data	• Predictions of functional effects are compared across multiple algorithms that consider cross species conservation of protein sequence, protein folding, critical protein domains, size and change of amino acid substitutions, and predictions of splicing.
Other	• A variant observed in combination with another known pathogenic variant may provide evidence for benign classification (if disease is inherited as a dominant condition) or for pathogenicity (if disease is inherited as an autosomal recessive condition) • Categorization of a variant by a reputable source as benign or pathogenic provides supporting evidence for classification

^*Based on Richards et al. (8).