Mapping epistatic modifiers of human psychiatric risk using mouse genetics

描述(申请人提供)：双相情感障碍和精神分裂症是高度可遗传的疾病，很可能是由于大量基因的作用。全基因组关联研究在人类中已经确定了一些关键的候选基因，但它们加在一起只解释了遗传性的一小部分。CACNA1C是最强大和复制最好的候选基因之一，已被证明与双相情感障碍、精神分裂症和严重抑郁症的疾病风险显著相关。在模式生物中，遗传相互作用在确定许多特征方面很重要，也可能解释了人类精神疾病中缺失遗传性的原因。尽管有这样的前景，但由于对整个基因组的所有成对相互作用进行测试的统计负担，在理解上位性方面取得的进展甚微。该项目的关键长期目标是利用小鼠遗传学来识别影响人类精神疾病风险的上位性修饰基因。我们将使用CACNA1C+/-(杂合基因敲除)小鼠，这种小鼠表现出与几种精神疾病有关的关键表型。我们将创建一组等基因F1(第一代子代)后代，在各种近交背景下表达CACNA1C+/-等位基因。众所周知，转基因的表型效应在不同的遗传背景下是不同的，我们将利用不同背景的CACNA1C+/-小鼠的表型差异来定位它们背后的遗传变异。所有F1的一半基因组将是同源的，他们在B6背景上遗传CACNA1C+/-或+/+等位基因；另一半将是可变近交系。具体目标1我们将在不同的近交背景下产生携带CACNA1C突变体或野生型等位基因的F1后代。我们将在一系列行为测试中对F1小鼠小组进行表型，这些测试模拟了与双相情感障碍和精神分裂症相关的神经精神疾病的特定方面，并已知在CACNA1C+/-小鼠中会发生改变。在具体目标2中，我们将使用这些表型数据，使用我们为这项研究开发的统计模型来进行GWAS。除了CACNA1C等位基因的基因外，每个F1的基因数据将从公共数据库中获得。我们的GWAS分析将揭示与表型性状本身相关的标记，类似于常规GWAS研究的结果，以及在一些但不是其他F1中观察到的改变对CACNA1C影响的敏感性或弹性的标记。然后，我们将使用生物信息学资源对候选基因座进行优先排序并缩小范围；使用F1小鼠大脑的基因表达分析来验证候选基因；并通过在我们将通过合作访问的人类基因数据集中进行测试来进行最终验证。这是第一个大规模、高效的贴图修改器方法 精神错乱。这项工作的发现将被直接转化为人类数据集，在那里它们可能被证明解释个人精神障碍的风险，并产生新的精神疾病的生物学见解和治疗方案。

DESCRIPTION (provided by applicant): Bipolar disorder and schizophrenia are highly heritable disorders that are likely due to the actions of a large number of genes. Genome-wide association studies (GWAS) in humans have identified some key candidate genes, but together they explain only a fraction of the heritability. One of the strongest and best replicated candidat genes is CACNA1C, which has been shown to significantly contribute to disease risk for bipolar disorder, schizophrenia, and major depression. Genetic interactions are important in determining a number of traits in model organisms, and may also account for missing heritability in human psychiatric disease. Despite this promise, little progress has been made in understanding epistasis due to the statistical burden of testing for all pairwise interactions across the genome. The key long-term goal of this project is to use mouse genetics to identify epistatic modifier genes that influence risk for psychiatric disease in humans. We will use the Cacna1c+/- (heterozygous knockout) mouse, which exhibits key phenotypes involved in several psychiatric diseases. We will create a panel of isogenic F1 (first filial generation) offspring tha express the Cacna1c+/- allele on a variety of inbred backgrounds. As the phenotypic effects of transgenes are well known to differ across genetic backgrounds, we will take advantage of the phenotypic differences in Cacna1c+/- mice of different backgrounds to map the genetic variants that underlie them. All F1s will be isogenic for half their genome on which they inherit the Cacna1c +/- or +/+ allele on a B6 background; the other half will be of a variable inbred strain. I Specific Aim 1 we will generate this panel of F1 offspring harboring the Cacna1c mutant or wild-type allele on a variety of inbred backgrounds. We will phenotype the panel of F1 mice on a battery of behavioral tests that model specific aspects of neuropsychiatric disease relevant to bipolar disorder and schizophrenia and are already known to be altered in Cacna1c+/- mice. In Specific Aim 2 we will use this phenotypic data to conduct a GWAS using a statistical model that we developed for this study. Aside from genotype at the Cacna1c allele, genotype data for each F1 will be available from public databases. Our GWAS analysis will reveal markers that are associated with the phenotypic traits themselves, similar to results of a conventional GWAS study, as well as markers that modify the susceptibility or resilience to the effect of Cacna1c observed in some but not other F1s. We will then prioritize and narrow down candidate loci using bioinformatics resources; validate candidates using gene expression assays from brains of F1 mice; and conduct final validation by testing in human genetic datasets to which we will have access by collaboration. This is the first large-scale, efficient approach to mapping modifier loci. Findings of this work will be translated directly to human datasets where they may prove to explain individual risk to psychiatric disorder and generate new biological insights and treatment options for psychiatric disease.