Genetics of speech disorders

描述（由申请人提供）：本研究旨在通过应用一种新的基因发现方法，即下一代外显子组测序和生物信息学基因过滤，识别影响语音障碍（SSD）的基因。在没有已知原因的情况下，患有口吃障碍的儿童难以说出易于被他人理解的言语。有证据表明SSD具有高度遗传性，但致病基因尚不清楚。最近对来自许多家庭的患有SSD的儿童兄弟姐妹的研究已经证实了一些候选区域，但有证据表明SSD可能由不同家庭的不同基因引起。为了提高我们的知识，常见病/罕见变异（CDRV）模型是基因鉴定的另一种框架，使用一次只关注一种遗传机制的方法。最近对儿童时期患有SSD的成年人进行的语言研究，加上基于外显子组的基因发现方法，现在可以在单个扩展的多代家庭中识别因果基因。除了在目前的试点项目中已经确定的家庭外，拟议的研究将确定多达两个具有SSD单基因遗传证据的家庭。表型分析和统计建模将提供SSD遗传模式的估计，并描述每个家庭的相关特征。将在每个家庭中选择三个远亲，受影响的成员进行外显子组测序。外显子组核苷酸序列将被筛选到具有新的非同义变体的候选基因的核心，这些变体最大程度地由测序的外显子组共享，并且在拷贝数方面符合估计的遗传模式。如果每个家族存在多个候选基因，则将选择位点和/或功能合理性最高的基因在受影响和未受影响的对照中进行验证。这项研究具有现实的潜力，可以首次识别与SSD相关的单个或主要基因，并为未来研究其他SSD变体以及其他CDRV模式的通信和神经发育障碍提供基础，所有这些都比以前可能的效率高得多，成本低得多。结果将流入更大的研究努力，以确定SSD家庭中的其他罕见变异，并创建基于生物学的SSD亚型分类。

DESCRIPTION (provided by applicant): This research aims to identify genes that influence speech sound disorder (SSD) by applying a newly available approach to gene discovery, next-generation exome sequencing followed by bioinformatic gene filtering. Children with SSD have difficulty producing speech that is readily understood by others, in the absence of known causes. There is evidence that SSD is highly heritable, but the causal genes are not yet known. Recent studies in child sib pairs with SSD from many families have confirmed a number of candidate regions, but there is evidence that SSD can result from different genes in different families. To advance our knowledge, the common disease/rare variant (CDRV) model is an alternative framework for gene identification, using approaches that focus on only one genetic mechanism at a time. Recent insights from speech studies in adults who had SSD during childhood, coupled with an exome-based gene discovery approach, now make it possible to identify causal genes in single extended multigenerational families. The proposed research will identify up to two such families with evidence of single-gene inheritance of SSD, in addition to those already ascertained in a current pilot project. Phenotyping and statistical modeling will provide an estimate of the mode of inheritance of SSD and characterize associated traits in each family. Three distantly related, affected members will be selected for exome sequencing in each family. Exomic nucleotide sequences will be filtered to a core of candidate genes with novel nonsynonymous variants that are maximally shared by the sequenced exomes and fit the estimated mode of inheritance in terms of copy numbers. If more than one candidate gene per family remains, the one with the highest locus and/or functional plausibility will be selected for validation in affected and unaffected controls. This research has the realistic potential to identify single or major genes associated with SSD for the first time and provide the basis for future studies investigating other SSD variants and, by extension, other communication and neuro-developmental disorders with a CDRV pattern, all with substantially higher efficiency and lower cost than previously possible. Results will flow into a larger research endeavor to identify other rare variants in families with SSD and create a biologically based SSD subtype classification.