Translational Approach to Studying miRNA functions in sACC and amygdala in patients with BPD

摘要： 双相情感障碍（BPD）是一种严重的精神障碍，对公共卫生造成重大负担。mirna是 在大脑中高度表达，并且已经被我们和其他人证明在BPD的神经病理学中发挥作用 和其他精神疾病。然而，到目前为止，所有已发表的死后脑miRNA表达研究， BPD受到样本量小、检测平台较旧以及缺乏全面数据的阻碍 与其他基因资源的整合。 为了解决这些局限性，我们提出了一种翻译方法，将miRNA测序应用于 杏仁核和膝下扣带前皮质（sAAC）的150例诊断为双相情感障碍， 匹配150个神经典型对照，然后在100个匹配的独立样本中进行重复研究。 病例/对照样本。我们的目标是充分利用这一巨大的和非常好的临床 特征样品。凭借我们的大规模发现和复制样本，我们有能力识别中度至 在神经精神疾病中通常观察到的小效应量。通过利用其他现有的基因组 数据集（即，GWAS数据和RNA-seq），我们将应用一系列最先进的 生物信息学和统计学方法用于这些基因组数据的全面整合。这 整合将导致产生具体和可检验的假设。例如，整合miRNA- BPD的GWAS（来自精神病基因组学联盟）的seq数据将揭示遗传机制 全基因组显著的风险变异体通过其促成双相情感障碍的病因学，例如，变体 影响BPD病例和对照之间的miRNA表达。整合miRNA-Seq和RNA-Seq数据 将确定在双相情感障碍病因学中具有重要功能的miRNA基因靶点。最后，我们将确定 一组BPD的高置信风险miRNA（即，miRNAs与eQTL的发现， 生物信息学和复制分析），并在小鼠模型中递送这些，以描绘疾病特异性 这些miRNA在BPD神经病理学中发挥的功能和作用。 总之，与BPD相关的多态性增加风险的神经生物学机制 双相情感障碍的症状我们假设导致神经病理学的机制之一 BPD风险变异体影响miRNA表达的能力。使用如此大的发现和复制 BPD的大脑样本，我们将鉴定miRNA，其表达与双相情感障碍密切相关， 在BPD风险变异的控制下，通过测试它们对BPD的影响， 小鼠模型中的行为测量。

Abstract: Bipolar disorder (BPD) is a severe mental disorder with a significant burden on public health. MiRNAs are highly expressed in the brain and have been shown by us and others to play a role in the neuropathology of BPD and other psychiatric disorders. However, to date, all published postmortem brain miRNA expression studies of BPD have been hampered by small sample sizes, older detection platforms, and a lack of comprehensive data integration with other genomic resources. To address these limitations, we propose a translational approach that will apply miRNA sequencing in the amygdala and subgenual cingulate anterior cortex (sAAC) in 150 patients diagnosed with bipolar disorder and matched 150 neurotypical controls, followed by a replication study in an independent sample of 100 matched case/control sample. Our aims are designed to take full advantage of this large and exceptionally well clinically characterized sample. With our large discovery and replication samples, we are powered to identify moderate to small effect sizes typically observed in neuropsychiatric disorders. By leveraging other pre-existing genomic datasets (i.e., GWAS data and RNA-seq) generated in our sample, we will apply a state-of-art series of bioinformatic and statistical approaches for the comprehensive integration of these genomic data. This integration will lead to the generation of specific and testable hypotheses. As an example, integrating the miRNA- seq data with GWAS of BPD (from the Psychiatric Genomics Consortium) will reveal the genetic mechanisms by which genome-wide significant risk variants contribute to the etiology of bipolar disorder, e.g., variants affecting miRNA expression between BPD cases and controls. Integrating the miRNA-Seq and RNA-Seq data will identify miRNA gene targets with important functions in the etiology of bipolar disorder. Finally, we will identify a set of high confidence risk miRNA of BPD (i.e., miRNAs with convergent evidence from the discovery, eQTL, bioinformatic, and replication analyses) and deliver these in mice models to delineate the disease-specific functions and roles these miRNA play in BPD neuropathology. In summary, the neurobiological mechanisms by which polymorphisms associated with BPD increase the risk for bipolar disorder are unknown. We hypothesize that one of the mechanisms contributing to the neuropathology of BPD is the ability of risk BPD variants to affect miRNA expression. Using such large discovery and replication brain samples of BPD, we will identify miRNA, whose expression is robustly associated with bipolar disorder and under the control of risk variants for BPD and further validate their disease functions by testing their impact on behavioral measures in mice models.