Classifying variants of XXXX using computational and laboratory studies.

@entity5 @entity321 @entity1167 @entity986
Variants in the @entity986 @entity5 suppressor are associated with @entity321 ( @entity321 ), although for many variants the linkage is weak. The effects of missense variants on protein function and pathogenicity are often unclear. Multiple methods (e.g., laboratory, computational, epidemiological) have been developed to analyze whether a missense variant is pathogenic or not. It is not yet clear how to integrate these data types into a strategy for variant classification. We studied 51 @entity986 missense variants using a cell cycle arrest assay. There was a continuum of results ranging from full wild-type effect through partial activity to @entity1167 . A reproducible decrease of 30% of cell cycle arrest activity correlated with @entity321 association. We analyzed missense @entity986 germline variants using a Bayesian method to combine multiple data types and derive a probability of pathogenicity. When equal to or more than two data types could be evaluated with this method, 22 of 25 @entity321 -associated variants and 8 of 15 variants of uncertain significance were classified as likely pathogenic with >95% probability. The other 10 variants were classified as uncertain (probability 5-95%). For most variants, there were insufficient data to draw a conclusion. The Bayesian model appears to be a sound method of classifying missense variants in @entity5 susceptibility genes.
