A genome-wide association study to detect genetic variation for schizophrenia

描述(由申请人提供)：识别增加精神分裂症易感性的特定基因变异对于进一步了解其病理生理学和开发有效的治疗方法非常重要。为此，有必要在整个基因组中筛选与精神分裂症相关的许多标记。这样的全基因组关联(GWA)研究目前已在CATIE样本中完成，另一项针对精神分裂症的GWA将于2007年年中由Gain完成。然而，这些目前的GWAS可能更好地被视为“筛查”研究，可能需要一系列设计良好的复制研究来消除假阳性并验证已发现的标志物与疾病的关联。在这一应用中，我们将试图为精神分裂症的常见病/常见病模型的严格评估做出贡献。与其使用非最佳样本量和任意规则，如小于0.05的P值表明重复，我们将设计一系列具有成本效益的后续研究，使用我们的适应性多阶段研究的统计框架，将WGA数据与其他信息来源整合的系统生物信息学方法，以及与专家小组举行的为期两天的会议。最初的复制工作涉及美国病例对照样本(在5,000个样本中有16K个SNP，病例和对照相同)，目标是以尽可能低的成本检测增加精神分裂症易感性的常见遗传变异的80%，同时将FDR控制在0.1水平。为了验证病例对照样本中已确定的关联不是人口分层/确定人工产物的结果，并研究这些基因的影响中可能存在的群体差异，随后进行了“基于基因的复制”研究，对来自1,400个家庭的5,500个个体的300个SNP进行了基因分型。最后，我们将不仅测试主效应，还将搜索基因型和环境变量之间的相互作用以及抗精神病药物的影响，使用我们的人工智能“模型发现”软件来搜索具有不同遗传和环境病因的精神分裂症亚型，并搜索拷贝数多态性。所有的基因分型和临床数据都将公之于众。我们试图为严格评估精神分裂症的常见病/常见基因变异模型做出贡献，这是进一步了解其病理生理机制和开发有效治疗方法的关键。

DESCRIPTION (provided by applicant): The identification of the specific genetic variants that increase susceptibility to schizophrenia is important to further understand its pathophysiology and develop effective treatments. For this purpose it will be necessary to screen many markers across the whole genome for association with schizophrenia. Such a genome-wide association (GWA) study is currently completed in the CATIE sample and another GWA for schizophrenia will be completed by GAIN in the middle of 2007. However, these current GWAs are perhaps better viewed as "screening" studies and a series of well- designed replication studies may be required to eliminate false positives and validate discovered marker-disease associations. In this application, we will attempt to contribute to the rigorous evaluation of the common disease/common variant model for schizophrenia. Rather than using non- optimal sample sizes and arbitrary rules such as P-values smaller than 0.05 suggest a replication, we will design a series of cost-effective follow up studies using our statistical framework for adaptive multi-stage studies, a systematic bioinformatic approach to integrate WGA data with other sources of information, and a two-day meeting with a panel of experts. The initial replication effort involves US case-control samples (16K SNPs in 5,000 samples with equal cases and controls) where the goal is to detect, with the lowest possible costs, 80 percent of the common genetic variants that increase susceptibility to schizophrenia while controlling the FDR at the 0.1 level. To verify that the identified associations in the case-control samples are not the result of population stratification/ascertainment artifacts and to study possible population differences in the effects of these genes, this is followed by "gene-based replication" study genotyping 300 SNPs in 5,500 individuals from 1,400 families. Finally, instead of merely testing for main effects, we will search for interactions between genotypes and environmental variables plus effects of anti-psychotic medication, use our artificial intelligent "model discovery" software to search for schizophrenia subtypes with different genetic and environment etiology, and search for copy number polymorphisms. All genotype and clinical data will be deposited in the public domain. We attempt to contribute to the rigorous evaluation of the common disease/common genetic variant model for schizophrenia, which is key to further understand its pathophysiology and develop effective treatments.