Takayuki Sugawara, Shuichi Yoshida, Naoko Onodera, K. Wada, S. Hirose, S. Kaneko
{"title":"自定义重序列阵列检测婴儿重症肌阵挛性癫痫患者SCN1A突变","authors":"Takayuki Sugawara, Shuichi Yoshida, Naoko Onodera, K. Wada, S. Hirose, S. Kaneko","doi":"10.1515/JOEPI-2015-0001","DOIUrl":null,"url":null,"abstract":"Summary Introduction Very few epilepsy phenotypes have been associated with causative genes; nevertheless, it is becoming possible, for some epilepsy phenotypes, to predict the most efficacious anti-epileptic drugs for patients based on their genetic makeup. The development of individualized medicine based on genetic information and the genetic diagnosis of epilepsy are expected to greatly improve the diagnosis and treatment of epilepsy. Here, we developed a DNA array (resequencing array) for the genetic diagnosis of epilepsies in which 14 epilepsy – related genes (SCN1A, SCN1B, CHRNA4, CHRNA7, CHRNB2, GABRA1, GABRD, GABRG2, CACNB4, CLCN2, KCNQ2, KCNQ3, CACNA1A, and CACNA1H) have been mounted. Aim The aim of the present study is to evaluate the performance of our custom array in detecting the SCN1A mutations in patients with severe myoclonic epilepsy in infancy. Material and methods We compared mutation data generated by DNA array sequencing of DNA samples from patients with severe myoclonic epilepsy in infancy to the data generated by capillary sequencing. Results Heterozygosity was detected in 44 of 48 patients (92%). We successfully identified epilepsy mutations, and the results of DNA array analyses were largely consistent with the results of capillary sequencing analysis. Conclusion These findings indicate that this DNA array is likely to be a useful tool in clinical settings.","PeriodicalId":15683,"journal":{"name":"Journal of Epileptology","volume":"8 1","pages":"5 - 13"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Detection of SCN1A mutations in patients with severe myoclonic epilepsy in infancy by custom resequence array\",\"authors\":\"Takayuki Sugawara, Shuichi Yoshida, Naoko Onodera, K. Wada, S. Hirose, S. Kaneko\",\"doi\":\"10.1515/JOEPI-2015-0001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary Introduction Very few epilepsy phenotypes have been associated with causative genes; nevertheless, it is becoming possible, for some epilepsy phenotypes, to predict the most efficacious anti-epileptic drugs for patients based on their genetic makeup. The development of individualized medicine based on genetic information and the genetic diagnosis of epilepsy are expected to greatly improve the diagnosis and treatment of epilepsy. Here, we developed a DNA array (resequencing array) for the genetic diagnosis of epilepsies in which 14 epilepsy – related genes (SCN1A, SCN1B, CHRNA4, CHRNA7, CHRNB2, GABRA1, GABRD, GABRG2, CACNB4, CLCN2, KCNQ2, KCNQ3, CACNA1A, and CACNA1H) have been mounted. Aim The aim of the present study is to evaluate the performance of our custom array in detecting the SCN1A mutations in patients with severe myoclonic epilepsy in infancy. Material and methods We compared mutation data generated by DNA array sequencing of DNA samples from patients with severe myoclonic epilepsy in infancy to the data generated by capillary sequencing. Results Heterozygosity was detected in 44 of 48 patients (92%). We successfully identified epilepsy mutations, and the results of DNA array analyses were largely consistent with the results of capillary sequencing analysis. Conclusion These findings indicate that this DNA array is likely to be a useful tool in clinical settings.\",\"PeriodicalId\":15683,\"journal\":{\"name\":\"Journal of Epileptology\",\"volume\":\"8 1\",\"pages\":\"5 - 13\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Epileptology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/JOEPI-2015-0001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Epileptology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/JOEPI-2015-0001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of SCN1A mutations in patients with severe myoclonic epilepsy in infancy by custom resequence array
Summary Introduction Very few epilepsy phenotypes have been associated with causative genes; nevertheless, it is becoming possible, for some epilepsy phenotypes, to predict the most efficacious anti-epileptic drugs for patients based on their genetic makeup. The development of individualized medicine based on genetic information and the genetic diagnosis of epilepsy are expected to greatly improve the diagnosis and treatment of epilepsy. Here, we developed a DNA array (resequencing array) for the genetic diagnosis of epilepsies in which 14 epilepsy – related genes (SCN1A, SCN1B, CHRNA4, CHRNA7, CHRNB2, GABRA1, GABRD, GABRG2, CACNB4, CLCN2, KCNQ2, KCNQ3, CACNA1A, and CACNA1H) have been mounted. Aim The aim of the present study is to evaluate the performance of our custom array in detecting the SCN1A mutations in patients with severe myoclonic epilepsy in infancy. Material and methods We compared mutation data generated by DNA array sequencing of DNA samples from patients with severe myoclonic epilepsy in infancy to the data generated by capillary sequencing. Results Heterozygosity was detected in 44 of 48 patients (92%). We successfully identified epilepsy mutations, and the results of DNA array analyses were largely consistent with the results of capillary sequencing analysis. Conclusion These findings indicate that this DNA array is likely to be a useful tool in clinical settings.