Genetic Testing in Adult Patients With Epilepsy: Genetic Risk Index for Seizure Etiology for Identifying Optimal Candidates.

IF 3.7 Q3 CLINICAL NEUROLOGY
Neurology. Clinical practice Pub Date : 2026-08-01 Epub Date: 2026-07-07 DOI:10.1212/CPJ.0000000000200624
Yi Li, David Lee, Cynthia Peng, Jacqueline E Summers Stromberg, Carly E Siskind, Kimford J Meador, Scheherazade Le, Babak Razavi
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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.

成年癫痫患者的基因检测:确定最佳候选人癫痫病因的遗传风险指数。
背景和目的:虽然基因检测被推荐为病因不明的癫痫诊断评估的标准组成部分,但其在成人人群中的最佳应用仍不明确。本研究的目的是评估基因检测对成年癫痫患者的诊断率,确定相关的危险因素,并制定临床评分来指导患者选择检测。方法:在斯坦福大学进行单中心横断面研究。使用斯坦福电子健康记录队列发现工具和手动图表审查来识别2018年至2024年间评估的年龄≥18岁的符合条件的患者。采用多变量logistic回归分析,探讨临床表型与致病基因变异检出率之间的关系,并以此作为癫痫病因学遗传风险指数(Gen-RISE)的基础。结果:共纳入508例患者。癫痫发作后基因检测明显延迟(11.2±11.1年),有和没有遗传病因的患者无显著差异(p = 0.89)。在32.9%的患者中发现了致病变异,其中2.6%的患者有不相关的致病变异作为次要发现。在一个独立的基于文献的验证队列中,识别致病变异的可能性为50%,灵敏度为98.6%。讨论:癫痫基因检测未得到充分利用,检测明显延迟就是明证。对于未知或怀疑遗传病因的成人癫痫患者应考虑使用这种药物,因为大约三分之一的患者可能有可识别的遗传变异。我们开发了Gen-RISE,这是一种新颖实用的公开工具,用于确定基因检测的最佳候选,提高诊断效率和患者护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neurology. Clinical practice
Neurology. Clinical practice CLINICAL NEUROLOGY-
CiteScore
4.00
自引率
0.00%
发文量
77
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.
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