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Children's Hospital of Philadelphia Researchers Use AI-Powered Method to Identify Genetic Epilepsies Much Earlier than Genetic Diagnosis
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PHILADELPHIA, July 30, 2024 ~ In a groundbreaking study, researchers from Children's Hospital of Philadelphia (CHOP) have utilized machine learning and artificial intelligence to identify early clinical features that could suggest a genetic diagnosis of epilepsy. The results of their study, published in the journal Genetics in Medicine, could significantly improve the time to diagnosis and treatment for individuals with genetic epilepsies.

Led by Peter D. Galer, MSc, a researcher with the Epilepsy Neurogenetics Initiative at CHOP, the team used Natural Language Processing (NLP) to analyze 89 million timestamped clinical annotations from 4,572,783 clinical notes of 32,112 individuals with childhood epilepsy. This included 1,925 individuals with known or presumed genetic epilepsies.

The researchers identified 47,774 age-dependent associations of clinical features with genetic epilepsies a median of 3.6 years prior to when those diagnoses were confirmed with a genetic test. This suggests that these early clinical features could serve as key indicators for a later genetic diagnosis.

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"We wanted to determine whether the type of information captured in electronic medical records prior to genetic testing could provide clinicians with clues for a later diagnosis," explained Galer. "In this instance, we found that a wide range of genetic epilepsies have key clinical features that present prior to genetic testing and diagnosis."

The study also revealed that neurodevelopmental differences observed between the ages of 6 and 9 months increased the likelihood of a later genetic diagnosis fivefold. This highlights the importance of early detection and intervention for individuals with these types of epilepsies.

According to senior study author Ingo Helbig, MD, pediatric neurologist in the Division of Neurology at CHOP and co-director of ENGIN, this research has significant implications for precision medicine. "By examining a very large dataset of individuals with childhood epilepsies, we believe that our results could be used prospectively for new diagnoses," said Helbig. "Since most clinicians use Electronic Medical Records, we believe this system could be widely adapted and utilized even in patient populations where genetic testing is not immediately available after symptom onset."

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The study was made possible through the resources of Arcus Omics, an institution-wide initiative that allows for genomics and clinical data at CHOP to be analyzed jointly. "In the era of precision medicine, quicker, more accurate prognoses could make an enormous difference in the lives of individuals living with genetic epilepsies," added Helbig.

This study was supported by the National Institute of Neurological Disorders and Stroke. The findings were published online on July 14, 2024 in Genet Med. DOI: 10.1016/j.gim.2024.101211.

With more than 100 epilepsies caused by a single gene mutation identified and several therapies being designed to target these genes, timely diagnosis is crucial for effective treatment. However, as seen in Dravet Syndrome, one of the most common genetic epilepsies, diagnosis often occurs years after symptoms first appear.

The researchers at CHOP are hopeful that their findings will lead to earlier diagnoses and improved outcomes for individuals with genetic epilepsies. With further research and development, this method could potentially be used in other patient populations where genetic testing is not readily available.
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