The VUS Problem in Genetic Testing: Can AI Provide a Solution?

Genetic testing has advanced rapidly, but the interpretation of 'variants of unknown significance' (VUS) remains a major challenge in clinical genetics. VUS, genetic variations with unclear health implications, cause significant patient anxiety. This article explores strategies to tackle the VUS problem, focusing on multiplexed assays of variant effect (MAVE) to generate large functional datasets and leverage AI to improve prediction tools. While a complete solution remains elusive, MAVE and AI offer hope for precision medicine, promising to greatly enhance the diagnostic accuracy of genetic testing in the future.