Thongnak Chuphong, Hnoonual Areerat, Tangviriyapaiboon Duangkamol, Silvilairat Suchaya, Puangpetch Apichaya, Pasomsub Ekawat, Chantratita Wasun, Limprasert Pornprot, Sukasem Chonlaphat
Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC), Ramathibodi Hospital, Bangkok, Thailand.
Int J Genomics. 2018 May 17;2018:8231547. doi: 10.1155/2018/8231547. eCollection 2018.
Autism spectrum disorder (ASD) has a strong genetic basis, although the genetics of autism is complex and it is unclear. Genetic testing such as microarray or sequencing was widely used to identify autism markers, but they are unsuccessful in several cases. The objective of this study is to identify causative variants of autism in two Thai families by using whole-exome sequencing technique. Whole-exome sequencing was performed with autism-affected children from two unrelated families. Each sample was sequenced on SOLiD 5500xl Genetic Analyzer system followed by combined bioinformatics pipeline including annotation and filtering process to identify candidate variants. Candidate variants were validated, and the segregation study with other family members was performed using Sanger sequencing. This study identified a possible causative variant for ASD, c.2951G>A, in the gene. We demonstrated the potential for ASD genetic variants associated with ASD using whole-exome sequencing and a bioinformatics filtering procedure. These techniques could be useful in identifying possible causative ASD variants, especially in cases in which variants cannot be identified by other techniques.
自闭症谱系障碍(ASD)具有很强的遗传基础,尽管自闭症的遗传学很复杂且尚不清楚。诸如微阵列或测序等基因检测被广泛用于识别自闭症标记,但在一些病例中并不成功。本研究的目的是通过使用全外显子组测序技术来识别两个泰裔家庭中自闭症的致病变异。对来自两个无亲缘关系家庭的自闭症患儿进行全外显子组测序。每个样本在SOLiD 5500xl基因分析仪系统上进行测序,随后进行包括注释和过滤过程的联合生物信息学流程,以识别候选变异。对候选变异进行验证,并使用桑格测序法对其他家庭成员进行分离研究。本研究在该基因中鉴定出一个可能的ASD致病变异,即c.2951G>A。我们通过全外显子组测序和生物信息学过滤程序证明了与ASD相关的ASD基因变异的可能性。这些技术可能有助于识别可能的ASD致病变异,特别是在其他技术无法识别变异的情况下。