A longitudinal methylome study to detect biomarkers predicting MDD trajectories

纵向甲基化组研究检测预测 MDD 轨迹的生物标志物

• 批准号: 8577286
• 负责人: EDWIN VAN DEN OORD
• 金额: $ 66.55万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8577286
• 关键词: Accounting; Affect; Age of Onset; Algorithms; Anxiety; Autistic Disorder; Bioinformatics; Biological; Biological Markers; Bipolar Disorder; Blood; Blood specimen; Brain; Cell division; Cells; Chronic; Clinic; Clinical; Complement; Cost Measures; DNA; DNA Methylation; DNA Sequence; Data; Development; Diagnosis; Disease; Disease remission; Equation; Etiology; Event; Gene Expression; Gene Expression Profile; Genetic; Goals; Health; Human; Human Genome; Individual Differences; Intervention; Knowledge; Left; Length; Life; Light; Major Depressive Disorder; Measures; Mental Depression; Mental disorders; Methylation; Mitotic; Modeling; Netherlands; Pathway interactions; Pharmacologic Substance; Prevalence; Prevention; Procedures; Reading; Research; Sampling; Schizophrenia; Sex Characteristics; Site; Staging; Stress; Technology; Testing; Time; Tissues; Variant; Work; age related; base; burden of illness; case control; clinical remission; data integration; data reduction; design; disorder subtype; follow-up; genome wide association study; genome-wide; improved; methylome; next generation sequencing; outcome forecast; peripheral blood; pyrosequencing

DESCRIPTION (provided by applicant): Major depressive disorder (MDD) is a leading cause of the global disease burden with a life time prevalence of almost 15%. Genetic studies have not worked as well for MDD as for other psychiatric conditions. DNA methylation studies are a particularly promising complement. First, methylation markers may have better predictive power as methylation is directly related to gene expression. Second, methylation studies may improve disease understanding as they can account for a range of clinical disease features. For example, DNA sequence variants cannot explain the variability in age of onset or the dynamic course of MDD that is typified by exacerbations and remissions. DNA methylation studies potentially can as methylation levels show age-dependent changes and are dynamic in post-mitotic tissues in the brain. Third, the translational potential of methylation studies is profound Methylation sites are excellent modifiable targets for pharmacological interventions and as methylation is stable and can be measured cost-effectively in blood they can potentially be used in clinical settings. Our overarching goal is to identify methylation markers in existing periphera blood samples associated with clinical MDD trajectories over a six year time period. Although methylation marks in blood will not directly impact MDD, factors that affect trajectories (e.g. stress) may also affect methylation signatures in blood. As traces of these methylation changes may be preserved during cell division, indirectly our studies can also shed light on causal mechanisms. Methylation of human (non-stem cell) DNA occurs at CpG sites. As the biological knowledge is lacking to identify good candidate CpG sites, we will use next-generation sequencing to screen the >28 million CpGs in the human genome for their association with the persistence of MDD, and then replicate the top findings in independent samples using a different technology. Specifically, we will sequence 1,500 methylomes using DNA collected from the same subjects at baseline and after six years from three groups from the Netherlands Study of Depression and Anxiety: 1) controls with no MDD, 2) cases with MDD at baseline and then fully remit, and 3) cases with chronic MDD. To improve statistical power and to select the biologically most meaningful methylation markers, we will integrate other data such as genome-wide transcriptome data that is already available for these samples. Using a parallel longitudinal 3 group design, the 50 most promising sites will be replicated in 1,500 independent samples using a different technology. Successful completion of the proposed research will yield replicable methylation signatures of MDD disease trajectories with which we will start generating prediction algorithms that could eventually be used in the clinic to improve prevention, treatment, and diagnosis.

描述(由申请人提供)：严重抑郁障碍(MDD)是全球疾病负担的主要原因，终生患病率几乎为15%。遗传学研究对MDD的效果不如对其他精神疾病的效果好。DNA甲基化研究是一个特别有希望的补充。首先，甲基化标记可能具有更好的预测能力，因为甲基化与基因表达直接相关。其次，甲基化研究可能会提高对疾病的理解，因为它们可以解释一系列临床疾病特征。例如，DNA序列变异不能解释发病年龄的可变性或以病情恶化和缓解为典型的MDD的动态病程。DNA甲基化研究可能会显示甲基化水平随年龄而变化，并且在大脑有丝分裂后组织中是动态的。第三，甲基化研究的翻译潜力是深远的，甲基化位点是药理学干预的极好的可修改靶点，由于甲基化稳定，并且可以在血液中经济有效地测量，它们可能被用于临床环境。我们的首要目标是在六年的时间内识别与临床MDD轨迹相关的现有外周血样中的甲基化标记物。虽然血液中的甲基化标记不会直接影响MDD，但影响运动轨迹的因素(如压力)也可能影响血液中的甲基化标记。由于这些甲基化变化的痕迹可能会在细胞分裂过程中保留下来，因此我们的研究也可以间接地阐明原因机制。人类(非干细胞)DNA的甲基化发生在CpG位点。由于缺乏生物学知识来确定好的候选CpG位点，我们将使用下一代测序来筛选人类基因组中的2800万个CpG，以寻找它们与MDD持久性的关联，然后使用不同的技术在独立样本中复制最新的发现。具体地说，我们将使用从荷兰抑郁症和焦虑研究的三组受试者六年后从相同受试者那里收集的DNA来对1500个甲基基因组进行测序：1)没有MDD的对照组，2)基线有MDD然后完全缓解的病例，以及3)慢性MDD的病例。为了提高统计能力和选择生物学上最有意义的甲基化标记，我们将整合其他数据，例如已经可以用于这些样本的全基因组转录组数据。使用平行的纵向3组设计，最有希望的50个地点将使用不同的技术在1500个独立样本中复制。拟议研究的成功完成将产生MDD疾病轨迹的可复制的甲基化特征，利用这些特征，我们将开始生成预测算法，这些算法最终可能用于临床，以改进预防、治疗和诊断。