Genetic Counseling

School of Health and Human Sciences

Taylor ZuckIdentifying Pathogenic Gene Variants Associated With Seizure Disorders Through Whole Exome Sequencing
Capstone Project Committee: Jonathan Berg, MD, PhD, Kate Foreman, MS, CGC, Randi Stewart, MS, CGC
Background: Over 50% of epilepsy has a genetic basis, yet genetic testing for epilepsy and seizure disorders is complex and involves many different genes. Whole Exome Sequencing (WES) is a technology that allows one to sequence many genes and identify thousands of gene variants with one test. Whole Exome Sequencing has the potential to provide diagnostic information for patients with epilepsy and seizure disorders. Understanding the genetic basis of epilepsy and effectively identifying pathogenic gene variants can help with diagnosis as well as disease management. Purpose: This study aimed to utilize WES to identify pathogenic genetic variants in well-described genes and candidate disease-causing variants in novel genes in participants with seizure disorders. Methods: WES data of participants enrolled in the NCGENES research study with seizure disorders was analyzed using two different approaches: a gene-first approach and a variant-first approach. The gene-first approach involved utilizing diagnostic gene lists consisting of genes known to be associated with specific phenotypes as filters to identify variants of potential interest for further analysis. The previously curated seizures diagnostic gene list was updated as a part of this study to include all genes known to be associated with seizures. This was done by identifying genes included on clinically available Next-Generation Sequencing gene panels and searching the literature. The variant-first approach to WES analysis involved performing research sweeps of WES data variant characteristics such as allele frequency and variant effect in addition to the proposed pattern of inheritance to identify variants of potential interest for further analysis. Further analysis of variants for both approaches included review of the literature and utilizing various bioinformatics websites and databases. Results: An updated seizures diagnostic gene list consisting of 804 genes associated with seizures was established. Diagnostic analyses using a gene-first approach of WES data for 5 participants were conducted. A molecular diagnosis was identified for 1 of the 5 participants. Three research sweep analyses were conducted. Multiple potential genes of interest were identified through these analyses although no novel seizure genes were identified. Conclusion: This study demonstrated that WES can be used effectively to identify a molecular cause for patients presenting with seizures and that there are various methods of WES data analysis each with different strengths and limitations. Future studies should continue to examine the effectiveness of WES as a diagnostic tool for seizure disorders and novel seizure gene discovery and also evaluate the effectiveness of different methods of WES data analysis.
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