An innovative AI-based tool leverages varied symptom descriptions, along with evidence from the scientific literature and genomic datasets, to pinpoint disease-associated gene variants.
In a major step towards untangling the genetic complexities of rare diseases, KAUST researchers have unveiled a tool that could aid in the diagnosis of these enigmatic conditions.
"STARVar stands a unique and efficient tool that has the advantage of prioritizing genomic variants by using flexibly expressed patient symptoms in free-form text," says Șenay Kafkas, a bioinformatics researcher at KAUST and the first author of a new report that details the innovative tool. Designed by KAUST computer scientist Robert Hoehndorf and members of his team, the method can interpret symptom data recorded in either standardized or natural language formats.
Out of nearly 800 suspect gene variants uncovered by genomic sequencing, STARVar deftly narrowed down the possibilities to a solitary mutation. This mutation, in a gene called MMP2, was already known to be pathogenic and thus was implicated as the likely driver of the girl's condition.