Assigning credit where it’s due: An information content score to capture the clinical value of Multiplexed Assays of Variant Effect

Abstract

AbstractBackgroundA variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, we hypothesized that this measure of utility underrepresents the information gained from MAVEs and that an information theory approach which includes data that does not reclassify variants will better reflect true information gain. We used this information theory approach to evaluate the information gain, in bits, for MAVEs ofBRCA1, PTEN, andTP53. Here, one bit represents the amount of information required to completely classify a single variant starting from no information.ResultsBRCA1MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information inBRCA1and a 22-fold increase over the information that only contributed to VUS reclassification.PTENMAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information inPTENand an 85-fold increase over the information that contributed to VUS reclassification.TP53MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information inTP53and a 3.5-fold increase over the information that contributed to VUS reclassification.ConclusionsAn information content approach will more accurately portray information gained through MAVE mapping efforts than counting the number of variants reclassified. This information content approach may also help define the impact of modifying information definitions used to classify many variants, such as guideline rule changes.