Whole genome profiling to detect schizophrenia methylation markers

描述（由申请人提供）：项目概要精神分裂症是一种经常破坏性的神经精神疾病。遗传因素有很大的影响。然而，精神分裂症的遗传贡献可能是复杂的，并且仅考虑序列变异很难捕获。DNA甲基化研究代表了一个特别有前途的补充，有几个原因。首先，由于甲基化与基因表达直接相关，因此基因甲基化水平的知识可能有助于预测疾病状态。其次，甲基化研究可以提供对发病年龄、精神分裂症的发作性质、基因-环境相互作用、父母效应和性别差异等现象的深入了解。第三，甲基化位点也是很好的新药物靶点，因为它们可以通过药理学干预进行修饰。最后，甲基化标记物在稳定的DNA水平上是可获得的，从翻译的角度来看，这意味着它们也可以潜在地用于临床环境中以改善诊断和治疗。 甲基化研究历来局限于有限数量的候选基因。然而，它最近已成为技术和经济上可行的同时测量数百万个标记的甲基化状态。这类似于全基因组关联研究（GWAS）的最新进展，后者大大加速了疾病变异的发现。为了确定与精神分裂症相关的甲基化位点，我们应用了我们小组开发的统计理论来确定最具成本效益的研究设计。基于这些优化设计计算，我们提出了一个全基因组甲基化分析研究750例精神分裂症患者和750名对照。为了消除由于技术和抽样误差而导致的错误发现，我们将使用焦磷酸测序法对精神分裂症病例和对照的独立样本中最有希望的位点进行随访。我们目前的功效计算表明，我们可能需要对800例病例和800例对照的65个区域进行随访。然而，我们开发的统计方法的一个优点是它可以自适应地使用-也就是说，第二焦磷酸测序复制阶段的最佳样本大小和标记物数量可以根据从第一个基于阵列的发现阶段估计的参数凭经验确定。为了提高我们对疾病机制的理解，将进行二次分析，将甲基化区域与临床信息以及与全基因组范围内已有的SNP标记和拷贝数变异调用相关。 公共卫生相关性：精神分裂症通常是一种毁灭性的神经精神疾病。DNA甲基化研究是对目前遗传学研究的一个特别有前途的补充，为改善对该疾病的理解和治疗提供了巨大的潜力。

DESCRIPTION (provided by applicant): PROJECT SUMMARY Schizophrenia is an often devastating neuropsychiatric illness. Genetic factors have been strongly implicated. The genetic contribution to schizophrenia is, however, likely to be complex and difficult to capture by merely considering sequence variation. DNA methylation studies represent a particularly promising complement for several reasons. First, as methylation is directly related to gene expression, knowledge of gene methylation levels may add to the prediction of disease status. Second, methylation studies can provide insight into phenomena such as age of onset, the episodic nature of schizophrenia, gene-environment interactions, parental effects, and sex differences. Third, methylation sites are also excellent new drug targets as they are modifiable by pharmacological interventions. Finally, methylation markers are accessible at the stable DNA level, which from a translational perspective means that they can potentially also be used in clinical settings to improve diagnosis and treatment. Methylation studies have historically been restricted to a limited number of candidate genes. However, it has recently become technically and economically feasible to measure the methylation status of millions of markers simultaneously. This resembles recent developments in genomewide association studies (GWAS), which have accelerated the discovery of disease variants considerably. To identify methylation sites related to schizophrenia, we have applied statistical theory developed by our group to determine the most cost-effective study design. Based on these optimal design calculations, we propose a whole genome methylation profiling study in 750 schizophrenia cases and 750 controls. To eliminate false discoveries due to technical and sampling errors, we will follow up the most promising sites in an independent sample of schizophrenia cases and controls using pyrosequencing. Our current power calculations suggest that we may need to follow up 65 regions in 800 cases and 800 controls. However, one strength of the statistical method we developed is that it can be used adaptively--that is, the optimal sample size and number of markers for the second pyrosequencing replication stage can be empirically determined based on parameters estimated from the first, array-based discovery stage. In order to improve our understanding of the disease mechanisms, secondary analyses will be performed relating the methylation regions to clinical information as well as to a genome-wide panel of already available SNP markers and copy number variant calls. PUBLIC HEALTH RELEVANCE: Schizophrenia is an often devastating neuropsychiatric illness. DNA methylation studies represent a particularly promising complement to current genetic studies that offer great potential to improve the understanding and treatment of the disease.