Subgroup delineation in genetic epilepsies and developmental brain disorders

遗传性癫痫和发育性脑疾病的亚组划分

• 批准号: 10658750
• 负责人: Ingo Helbig
• 金额: $ 77.44万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10658750
• 关键词: Accounting; Address; Age; Age Factors; Anticonvulsants; Brain Diseases; Clinical; Clinical Data; Comparative Effectiveness Research; Complex; Consumption; Data; Data Analyses; Dedications; Demographic Factors; Development; Diagnostic; Disease; Epilepsy; Freedom; Frequencies; Future; Genes; Genetic; Genetic Predisposition to Disease; Genotype; Goals; Human; Individual; Intervention; Knowledge; Language; Manuals; Maps; Measurement; Methods; Mission; National Institute of Neurological Disorders and Stroke; Natural History; Nerve; Neurodevelopmental Disorder; Ontology; Operative Surgical Procedures; Outcome; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Positioning Attribute; Prognosis; Public Health; Rare Diseases; Recording of previous events; Research; SCN8A gene; Saint Jude Children' s Research Hospital; Seizures; Sodium Channel Blockers; Standardization; Stratification; Subgroup; Therapeutic; Time; Translating; Variant; childhood epilepsy; clinical care; clinical practice; cohort; computerized tools; data harmonization; dietary; effective therapy; genetic variant; implantation; improved; ketogenic diet; longitudinal analysis; loss of function; nervous system disorder; novel strategies; outcome prediction; oxcarbazepine; personalized medicine; phenotypic data; programs; reconstruction; response; treatment and outcome; treatment choice; treatment comparison; treatment response; treatment strategy

PROJECT SUMMARY Over the last decade, there has been an exponential increase in identified genetic causes of neurodevelopmental disorders and epilepsy. With more than 100 genes identified, understanding how phenotypes relate to specific genetic variants is critical given the clinical complexity of developmental brain disorders. Given that treatment and prognosis is dependent on understanding genotype-phenotype correlations, there is a critical need to better assess clinical features in genetic epilepsies. However, phenotyping is a time-consuming, manual task with limited throughput. To overcome this bottleneck, we have developed a novel approach, based on the Human Phenotype Ontology (HPO) to capture and analyze longitudinal phenotypic data. In our preliminary data for STXBP1- and SCN8A-related disorders, which we have reconstructed for >550 patient months, we identified unique natural histories, outcomes, and distinct response patterns to specific treatment strategies. Natural history and treatment response in pediatric epilepsies are deeply intertwined and often difficult to disentangle. Accordingly, a comprehensive assessment of genetic epilepsies needs to account for two factors, subgroups with common clinical trajectories as well as gene-specific treatment responses. Our suggested project therefore has two aims. First, we plan to detect relevant subgroups in genetic epilepsies based on longitudinal clinical data (Aim #1). We will reconstruct longitudinal trajectories and outcomes in the 15 most common genetic epilepsies with 50-75 individuals per gene to delineate longitudinal seizure burden, seizures types, and developmental milestones. Based on this, we will then identify subgroups defined by clinical features and global clinical resemblance, as well as variant and gene groups. In addition (Aim #2), we will identify specific treatment responses in genetic epilepsies using standardized phenotypes. We will combine reconstructed natural history with treatment data to compare reduction in seizure frequencies and effect on maintaining seizure freedom across >20 treatment strategies with the goal to identify the most effective treatment strategy when adjusting for age and seizure type. Finally, we will also compare medication response across major variant classes and across all genetic etiologies combined. Our team has previously pioneered computational phenotype analysis in the epilepsies, positioning us uniquely to address these questions. Our analysis, mapping longitudinal clinical data to a harmonized format will provide unprecedented granularity in deciphering the trajectory of genetic epilepsies, informing clinical practice in these conditions. We hope that these results will provide a template for the analysis of the limited clinical data in rare diseases in order to maximize treatment-relevant information, especially in conditions with complex, longitudinal disease histories.

项目摘要 在过去的十年里，神经发育障碍的遗传原因呈指数级增长。 疾病和癫痫。随着100多个基因的鉴定，了解表型如何与特定的 鉴于发育性脑疾病的临床复杂性，遗传变异是至关重要的。鉴于这种治疗 预后取决于对基因型-表型相关性的理解，因此迫切需要更好地 评估遗传性癫痫的临床特征。然而，表型分型是一项耗时的手动任务， 有限的吞吐量。为了克服这一瓶颈，我们开发了一种新的方法，基于人类 表型本体（HPO）捕获和分析纵向表型数据。在我们的初步数据中， STXBP 1和SCN 8A相关疾病，我们已经重建了>550个患者月，我们确定了 独特的自然史、结果和对特定治疗策略的不同反应模式。自然历史 和治疗反应是深深交织在一起，往往难以解开。 因此，对遗传性癫痫的综合评估需要考虑两个因素， 具有共同的临床轨迹以及基因特异性治疗反应。因此，我们建议的项目 有两个目的。首先，我们计划根据纵向临床数据检测遗传性癫痫的相关亚组 (Aim#1）。我们将重建15种最常见的遗传性癫痫的纵向轨迹和结果 每个基因50-75个个体，以描绘纵向癫痫负荷、癫痫类型和发育 里程碑在此基础上，我们将确定由临床特征和全球临床特征定义的亚组， 相似性，以及变异和基因组。此外（目标2），我们将确定具体的治疗方法 使用标准化表型的遗传性癫痫的反应。我们将联合收割机 使用治疗数据比较癫痫发作频率的降低和对维持无癫痫发作的影响 在>20种治疗策略中，目标是在调整 年龄和发作类型最后，我们还将比较主要变异类别和不同类别之间的药物反应。 所有遗传病因的综合我们的团队以前曾在计算表型分析方面处于领先地位， 癫痫病，使我们能够独特地解决这些问题。我们的分析，绘制纵向临床数据 统一的格式将提供前所未有的粒度在破译遗传癫痫的轨迹， 在这些条件下通知临床实践。我们希望这些结果将为分析提供一个模板 罕见病的有限临床数据，以最大限度地提高治疗相关信息，特别是 具有复杂的纵向病史的条件。