Genomic Disorders in Neurodevelopmental Disease

描述(由申请人提供)：神经发育障碍(NDDS)影响相当一部分人口，给社会带来巨大的经济和医疗保健系统负担。遗传异常，包括拷贝数变异(CNV)和序列变异，是NDDS最常见的病因。了解这种异常的形成机制、发育起源和易发生这种异常的基因组结构元素，可以改善临床对诊断的解释以及对受影响的患者和家属的遗传咨询。基因组中的重复元件，特别是Alu家族的重复元件，已经被发现介导人类CNV，我们假设它们可能是CNV形成的未被识别的底物。为了探索这一点，我们将通过计算识别内含子和侧翼基因组区域中Alu含量显著增加的基因，并将该基因列表与人类CNV数据库进行比较。NDD背后的从头突变，包括那些由重复元件介导的突变，经典地被认为发生在生殖系中；然而，有丝分裂细胞分裂也是突变过程的一个大靶点。根据从我们实验室鉴定的家系中获得的数据，我们假设父母在有丝分裂细胞分裂期间的突变是其后代致病等位基因的更频繁的来源，而不是目前的检测所表明的。我们将前瞻性地对一大群家庭三人组进行未被识别的、低水平的体细胞嵌合体的基因组缺失筛查，以估计频率。近年来，全基因组技术加速了对NDDS的基因组变异的识别。然而，由于在每个个体中检测到大量的变异，临床解释变得困难。确定有害等位基因的经典方法是基于患者和对照组之间的发病率差异。然而，由于最近人类人口的扩张，个体中的大多数变异都是罕见的，而且仅限于家族谱系或家族之间，这使得区分稀有和致病变异具有挑战性。我们假设，整合多种知识来源，包括基因特异性、基因组结构和种群发病率数据，将导致对全基因组诊断的更准确、更有效的解释。为此，我们将从大量患者中识别潜在的致病等位基因，通过染色体微阵列测试以及对患有NDDS的家系进行外显子组测序。然后，我们将利用生物信息学和统计学将多个信息源结合在一起，为每个变体开发特定表型的“致病概率”。这些分数还将被用来调查单个变异的遗传负荷在多大程度上导致或不导致人类疾病。总之，这项建议旨在阐明CNV的形成机制，描述突变过程的时间，并评估已识别的变异的危害性，以改进对NDDS患者基因组诊断的解释。

DESCRIPTION (provided by applicant): Neurodevelopmental disorders (NDDs) affect a considerable fraction of the population resulting in substantial economic and healthcare system burdens to society. Genetic aberrations, including copy number variations (CNVs) and sequence variants, are the most common etiology of NDDs. Understanding the mechanism of formation, developmental origin, and genomic architectural elements that predispose to such aberrations could improve clinical interpretation of diagnostics as well as genetic counseling of affected patients and families. Repetitive elements in the genome, and specifically those of the Alu family, have been found to mediate human CNVs, and we hypothesize that they could be under-recognized substrates for CNV formation. To explore this, we will computationally identify genes with significantly increased Alu content in introns and flanking genomic regions and compare this gene list to databases of human CNVs. De novo mutations, including those mediated by repetitive elements, that underlie NDDs are classically thought of as occurring in the germ line; however, mitotic cell divisions also represent a large target for mutagenic processes. Based on data obtained from families identified in our laboratory, we hypothesize that mutations during mitotic cell divisions in parents are a more frequent source of pathogenic alleles in their offspring than current detection suggests. We will prospectively screen a large cohort of family trios for unrecognized, low-level somatic mosaicism for genomic deletions to estimate the frequency. In recent years, genome-wide technologies have accelerated the identification of genomic variations underlying NDDs. However, clinical interpretation is made difficult due to the large number of variants detected in each individual. The classic method for determining detrimental alleles is based on incidence differences between patients and controls. Yet, because of recent human population expansion, most variation in an individual is rare and restricted among family lineages or clans, making distinction between rare and pathogenic variants challenging. We hypothesize that integration of multiple knowledge sources, including gene-specific, genome architecture, and population incidence data will result in more accurate, efficient interpretation of genome-wide diagnostics. To this end, we will identify potentially pathogenic alleles from both a large cohort of patients tested by chromosomal microarray as well as by performing exome sequencing of families with NDDs. We will then utilize bioinformatics and statistics to combine multiple information sources together to develop phenotype-specific "pathogenicity probability" for each variant. Such scores will also be used to investigate the extent to which the genetic load of individual variants do or do not contribute to human disease. Overall, this proposal aims to elucidate mechanisms of CNV formation, delineate the timing of mutagenic processes, and assess the deleteriousness of identified variants to improve interpretation of genomic diagnostics for patients with NDDs.