Abstract：
OBJECTIVE: Genetic variants in the SCN8A gene underlie a wide spectrum of neurodevelopmental phenotypes including several distinct seizure types and a host of comorbidities. One of the major challenges facing clinicians and researchers alike is to identify genotype-phenotype (G-P) correlations that may improve prognosis, guide treatment decisions, and lead to precision medicine approaches.
METHODS: We investigated G-P correlations among 270 participants harboring gain-of-function (GOF) variants enrolled in the International SCN8A Registry, a patient-driven online database. We performed correlation analyses stratifying the cohort by clinical phenotypes to identify diagnostic features that differ among patients with varying levels of clinical severity, and that differ among patients with distinct GOF variants.
RESULTS: Our analyses confirm positive correlations between age at seizure onset and developmental skills acquisition (developmental quotient), rate of seizure freedom, and percentage of cohort with developmental delays, and identify negative correlations with number of current and weaned antiseizure medications. This set of features is more detrimentally affected in individuals with a priori expectations of more severe clinical phenotypes. Our analyses also reveal a significant correlation between a severity index combining clinical features of individuals with a particular highly recurrent variant and an independent electrophysiological score assigned to each variant based on in vitro testing.
CONCLUSIONS: This is one of the first studies to identify statistically significant G-P correlations for individual SCN8A variants with GOF properties. The results suggest that individual GOF variants (1) are predictive of clinical severity for individuals carrying those variants and (2) may underlie distinct clinical phenotypes of SCN8A disease, thus helping to explain the wide SCN8A-related epilepsy disease spectrum. These results also suggest that certain features present at initial diagnosis are predictive of clinical severity, and with more informed treatment plans, may serve to improve prognosis for patients with SCN8A GOF variants.
METHODS: We investigated G-P correlations among 270 participants harboring gain-of-function (GOF) variants enrolled in the International SCN8A Registry, a patient-driven online database. We performed correlation analyses stratifying the cohort by clinical phenotypes to identify diagnostic features that differ among patients with varying levels of clinical severity, and that differ among patients with distinct GOF variants.
RESULTS: Our analyses confirm positive correlations between age at seizure onset and developmental skills acquisition (developmental quotient), rate of seizure freedom, and percentage of cohort with developmental delays, and identify negative correlations with number of current and weaned antiseizure medications. This set of features is more detrimentally affected in individuals with a priori expectations of more severe clinical phenotypes. Our analyses also reveal a significant correlation between a severity index combining clinical features of individuals with a particular highly recurrent variant and an independent electrophysiological score assigned to each variant based on in vitro testing.
CONCLUSIONS: This is one of the first studies to identify statistically significant G-P correlations for individual SCN8A variants with GOF properties. The results suggest that individual GOF variants (1) are predictive of clinical severity for individuals carrying those variants and (2) may underlie distinct clinical phenotypes of SCN8A disease, thus helping to explain the wide SCN8A-related epilepsy disease spectrum. These results also suggest that certain features present at initial diagnosis are predictive of clinical severity, and with more informed treatment plans, may serve to improve prognosis for patients with SCN8A GOF variants.
摘要：
目的：SCN8A基因的遗传变异是一系列神经发育表型的基础，包括几种不同的癫痫发作类型和多种合并症。临床医生和研究人员面临的主要挑战之一是确定可能改善预后的基因型-表型（G-P）相关性。指导治疗决策，并导致精准医学方法。
方法：我们调查了在国际SCN8A注册中登记的270名具有功能增益（GOF）变异的参与者的基因型-表型相关性，患者驱动的在线数据库。我们进行了相关分析，根据临床表型对队列进行分层，以确定不同临床严重程度患者的诊断特征。并且在具有不同GOF变体的患者之间存在差异。
结果：我们的分析证实了癫痫发作年龄与发育技能获得（DQ）之间的正相关关系，癫痫发作自由率，以及发育迟缓队列的百分比，并确定与当前和断奶抗癫痫药物（ASM）数量的负相关。这组特征在具有更严重临床表型的先验预期的个体中更不利地影响。我们的分析还揭示了结合具有特定高度复发性变体的个体的临床特征的严重性指数（SI）与基于体外测试分配给每个变体的独立电生理评分（ES）之间的显着相关性。
结论：这是确定具有GOF特性的单个SCN8A变体的统计学显著G-P相关性的首批研究之一。结果表明，单个GOF变体1）可预测携带这些变体的个体的临床严重程度，和2)可能是SCN8A疾病不同临床表型的基础，从而有助于解释广泛的SCN8A相关癫痫疾病谱。这些结果还表明，最初诊断时存在的某些特征可以预测临床严重程度。有了更明智的治疗计划，可能有助于改善SCN8AGOF变异患者的预后。
方法：我们调查了在国际SCN8A注册中登记的270名具有功能增益（GOF）变异的参与者的基因型-表型相关性，患者驱动的在线数据库。我们进行了相关分析，根据临床表型对队列进行分层，以确定不同临床严重程度患者的诊断特征。并且在具有不同GOF变体的患者之间存在差异。
结果：我们的分析证实了癫痫发作年龄与发育技能获得（DQ）之间的正相关关系，癫痫发作自由率，以及发育迟缓队列的百分比，并确定与当前和断奶抗癫痫药物（ASM）数量的负相关。这组特征在具有更严重临床表型的先验预期的个体中更不利地影响。我们的分析还揭示了结合具有特定高度复发性变体的个体的临床特征的严重性指数（SI）与基于体外测试分配给每个变体的独立电生理评分（ES）之间的显着相关性。
结论：这是确定具有GOF特性的单个SCN8A变体的统计学显著G-P相关性的首批研究之一。结果表明，单个GOF变体1）可预测携带这些变体的个体的临床严重程度，和2)可能是SCN8A疾病不同临床表型的基础，从而有助于解释广泛的SCN8A相关癫痫疾病谱。这些结果还表明，最初诊断时存在的某些特征可以预测临床严重程度。有了更明智的治疗计划，可能有助于改善SCN8AGOF变异患者的预后。
