Yi Li, David Lee, Cynthia Peng, Jacqueline E Summers Stromberg, Carly E Siskind, Kimford J Meador, Scheherazade Le, Babak Razavi
{"title":"Genetic Testing in Adult Patients With Epilepsy: Genetic Risk Index for Seizure Etiology for Identifying Optimal Candidates.","authors":"Yi Li, David Lee, Cynthia Peng, Jacqueline E Summers Stromberg, Carly E Siskind, Kimford J Meador, Scheherazade Le, Babak Razavi","doi":"10.1212/CPJ.0000000000200624","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objectives: </strong>Although genetic testing is recommended as a standard component of the diagnostic evaluation for epilepsies with unknown etiology, its optimal application in adult populations remains poorly defined. The aim of this study was to assess the diagnostic yield of genetic testing in adult patients with epilepsy, identify associated risk factors, and develop a clinical score to guide patient selection for testing.</p><p><strong>Methods: </strong>A single-center cross-sectional study was conducted at Stanford University. The Stanford electronic health record cohort discovery tool and manual chart review were used to identify eligible patients aged ≥18 years who were evaluated between 2018 and 2024. Multivariable logistic regression analysis was used to investigate the association between the clinical phenotypes and the probability of detecting pathogenic genetic variants, which served as the basis for the Genetic Risk Index for Seizure Etiology (Gen-RISE).</p><p><strong>Results: </strong>A total of 508 patients were included. A significant delay in genetic testing after seizure onset (11.2 ± 11.1 years) was observed, with no significant difference between those with and without a genetic etiology (<i>p</i> = 0.89). Pathogenic variants were identified in 32.9% of patients, with 2.6% having unrelated pathogenic variants as secondary findings. Low-frequency (<1%) pathogenic variants in the cohort accounted for over 50% of positive findings. Exome sequencing had the highest yield (41.7%), followed by genetic panels (30.3%) and microarray testing (21.8%). Intellectual disability/developmental delay (OR, 3.41, 95% CI [2.18-5.32]), seizure onset before age 3 years (OR, 1.96, 95% CI [1.27-3.02]), and abnormal EEG findings (OR, 1.29, 95% CI [1.00-1.26]) were associated with the diagnosis of genetic epilepsy. Subsequently, we developed Gen-RISE, a clinical tool to estimate the probability of a pathogenic variant related to epilepsy. Gen-RISE above 0 predicted a >50% likelihood of identifying a pathogenic variant, with a sensitivity of 98.6% in an independent literature-based validation cohort.</p><p><strong>Discussion: </strong>Genetic testing for epilepsy is underused, evidenced by marked testing delays. It should be considered for adult epilepsy patients with unknown or suspected genetic etiology because approximately one-third may have identifiable genetic variants. We developed Gen-RISE, a novel and practical, publicly available tool to identify optimal candidates for genetic testing, enhancing diagnostic efficiency and patient care.</p>","PeriodicalId":19136,"journal":{"name":"Neurology. Clinical practice","volume":"16 4","pages":"e200624"},"PeriodicalIF":3.7000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13343400/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurology. Clinical practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1212/CPJ.0000000000200624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/7 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background and objectives: Although genetic testing is recommended as a standard component of the diagnostic evaluation for epilepsies with unknown etiology, its optimal application in adult populations remains poorly defined. The aim of this study was to assess the diagnostic yield of genetic testing in adult patients with epilepsy, identify associated risk factors, and develop a clinical score to guide patient selection for testing.
Methods: A single-center cross-sectional study was conducted at Stanford University. The Stanford electronic health record cohort discovery tool and manual chart review were used to identify eligible patients aged ≥18 years who were evaluated between 2018 and 2024. Multivariable logistic regression analysis was used to investigate the association between the clinical phenotypes and the probability of detecting pathogenic genetic variants, which served as the basis for the Genetic Risk Index for Seizure Etiology (Gen-RISE).
Results: A total of 508 patients were included. A significant delay in genetic testing after seizure onset (11.2 ± 11.1 years) was observed, with no significant difference between those with and without a genetic etiology (p = 0.89). Pathogenic variants were identified in 32.9% of patients, with 2.6% having unrelated pathogenic variants as secondary findings. Low-frequency (<1%) pathogenic variants in the cohort accounted for over 50% of positive findings. Exome sequencing had the highest yield (41.7%), followed by genetic panels (30.3%) and microarray testing (21.8%). Intellectual disability/developmental delay (OR, 3.41, 95% CI [2.18-5.32]), seizure onset before age 3 years (OR, 1.96, 95% CI [1.27-3.02]), and abnormal EEG findings (OR, 1.29, 95% CI [1.00-1.26]) were associated with the diagnosis of genetic epilepsy. Subsequently, we developed Gen-RISE, a clinical tool to estimate the probability of a pathogenic variant related to epilepsy. Gen-RISE above 0 predicted a >50% likelihood of identifying a pathogenic variant, with a sensitivity of 98.6% in an independent literature-based validation cohort.
Discussion: Genetic testing for epilepsy is underused, evidenced by marked testing delays. It should be considered for adult epilepsy patients with unknown or suspected genetic etiology because approximately one-third may have identifiable genetic variants. We developed Gen-RISE, a novel and practical, publicly available tool to identify optimal candidates for genetic testing, enhancing diagnostic efficiency and patient care.
期刊介绍:
Neurology® Genetics is an online open access journal publishing peer-reviewed reports in the field of neurogenetics. The journal publishes original articles in all areas of neurogenetics including rare and common genetic variations, genotype-phenotype correlations, outlier phenotypes as a result of mutations in known disease genes, and genetic variations with a putative link to diseases. Articles include studies reporting on genetic disease risk, pharmacogenomics, and results of gene-based clinical trials (viral, ASO, etc.). Genetically engineered model systems are not a primary focus of Neurology® Genetics, but studies using model systems for treatment trials, including well-powered studies reporting negative results, are welcome.