Genetic Association in Austism Disorder

描述（由申请人提供）：自闭症是一种高度遗传的神经发育障碍，在三岁之前出现，并可能导致终身残疾。在拟议的研究中，将通过进行全基因组关联研究来识别与自闭症相关的SNP。将在100个受影响的同胞对和400个无关对照中对200，000个SNP进行基因分型。选择将用于该筛选的200，000个SNP标记是因为它们在基因组中均匀分布，并且在多个群体中具有大于10%的等位基因频率，使其成为全基因组关联研究的强大试剂。在第一阶段，25%的基因组将被扫描自闭症相关基因，通过对受影响和未受影响个体中的50，000个信息性SNP进行基因分型。这将允许检测和纠正存在的任何群体分层偏差，并识别基因组这一部分中的任何自闭症相关基因。在第二阶段，将扫描其余的基因组，对同一人群中受影响和未受影响的个体中剩余的150，000个SNP进行基因分型。这项研究设计将提供足够的能力（~ 80%）来识别所有主要的自闭症易感基因，从而识别与自闭症高风险相关的风险因素谱。这些SNP与自闭症的关联将通过在第二个独立人群中进行基因分型来确认。自闭症相关遗传标记的鉴定将允许诊断工具的开发，以识别患有自闭症的高风险个体，并最终导致治疗突破。

DESCRIPTION (provided by applicant): Autism is a highly-heritable neurodevelopmental disorder that presents before the age of three and can lead to life-long disability. In the proposed study, SNPs associated with autism will be identified by performing a genome-wide association study. 200,000 SNPs will be genotyped in 100 affected sib-pairs and 400 unrelated controls. The 200,000 SNP markers that will be used in this screen have been selected because they are uniformly distributed across the genome and have allele frequencies greater than 10% in multiple populations, making them a powerful reagent for whole genome association studies. In Phase I, 25% of the genome will be scanned for autism-associated genes, by genotyping 50,000 of the informative SNPs in the affected and unaffected individuals. This will allow the detection and correction of any population stratification bias that exists, and identification of any autism-associated genes in this portion of the genome. In Phase II, the rest of the genome will be scanned, by genotyping the remaining 150,000 SNPs in the same population of affected and unaffected individuals. This study design will provide sufficient power (-80%) to identify all the major autism susceptibility genes and thus identify risk factor profiles associated with a high risk for autism. The association of these SNPs to autism will then be confirmed by genotyping them in a second, independent population. The identification of autism-associated genetic markers will allow the development of diagnostic tools to identify individuals with high risk of developing autism, and could ultimately lead to therapeutic breakthroughs.