AI Reveals New Insights into Genetic Diseases and DNA

Scientists at the Icahn School of Medicine at Mount Sinai have developed an innovative artificial intelligence tool named V2P, which stands for Variant to Phenotype. This tool is capable of identifying disease-causing genetic mutations and predicting the types of diseases those mutations may trigger.

The findings were published on December 15 in Nature Communications. Current genetic analysis methods can only assess whether a mutation is harmful, but V2P addresses this limitation by linking genetic variants to their potential phenotypic outcomes, which means it can predict how a patient's DNA might influence their health.

According to Dr. David Stein, the first author of the study, the approach enables researchers to identify the genetic changes that are most pertinent to a patient's condition without having to sift through countless variants.

The V2P tool was trained on a substantial database of both harmful and benign genetic variants, enhancing its predictive accuracy by incorporating disease information. In tests using real, de-identified patient data, V2P frequently ranked the true disease-causing variant among the top ten candidates, demonstrating its potential to streamline genetic diagnostics.

Dr. Avner Schlessinger, co-senior and co-corresponding author, emphasized that V2P could also assist researchers and drug developers in pinpointing genes and pathways associated with specific diseases, which can facilitate the development of genetically tailored therapies, particularly for rare and complex conditions.

While V2P currently categorizes mutations into broad categories such as nervous system disorders or cancers, there are plans to refine the tool for more specific disease predictions and to integrate it with other data sources to support drug discovery.

This advancement is a significant step toward precision medicine, which aims to align treatments with a patient's genetic profile. The integration of AI into genetic research is yielding groundbreaking insights into diseases linked to DNA and enhancing our understanding of genetic disorders.