Researchers have developed an innovative artificial intelligence approach aimed at identifying genes linked to neurodevelopmental disorders such as autism spectrum disorder, epilepsy, and developmental delay.

This AI-driven model is designed to validate emerging genes from sequencing studies that previously lacked sufficient statistical evidence of their involvement in these disorders.

The research involved contributions from several institutions, including Baylor College of Medicine and Texas Children's Hospital, and received support from multiple grants from organizations like the NIH and the Hevolution Foundation.

The study incorporated over 300 biological features to strengthen predictive models, including gene mutation intolerance and interactions with known disease-associated genes.

The study identified that some top-ranking genes were found to be supported by existing literature 45 to 500 times more than lower-ranking genes, enhancing their credibility and potential significance in research.

The study, published in The American Journal of Human Genetics on February 26, 2025, seeks to improve molecular diagnosis and targeted therapies for these conditions.

This computational tool is crucial for enhancing the genetic understanding of neurodevelopmental disorders, which is essential for achieving accurate diagnoses and developing targeted therapies.

Dr. Ryan S. Dhindsa, the first author and an assistant professor at Baylor College of Medicine, emphasized that many patients still do not have genetic diagnoses, suggesting the presence of undiscovered genes.