Genetic architecture of the human brain and neuropsychiatric disorders

项目摘要 我们的目标是确定基因-大脑-行为关系，包括那些构成神经精神病学基础的关系 精神错乱。这些疾病很常见，而且在全球范围内发病率不断上升。然而，有重要的 当前治疗和客观诊断方面的临床差距。药物开发试验失败率为 由于模型之间遗传基础的很大程度上未知的差异，导致脑部疾病的比例高得不成比例 物种和人类的大脑，这阻碍了翻译的成功。阻碍取得进展的主要挑战 神经精神医学是我们对人类复杂性背后的遗传学的有限理解 大脑的结构和功能。我们目前研究的第一个目标是发现相关的遗传变异 具有脑成像表型(目标1)。我们的第二个目标是测试监管和监管的遗传效应 人类大脑中带有系统发育注释的基因组元件(目标2)。我们的第三个目标是确定 神经精神病学遗传风险及其环境相互作用对大脑的影响(目标3)。先前 我们根据核磁共振成像(MRI)数据制作了第一份人类大脑皮层的遗传图谱 双胞胎使用模糊聚类。这项工作不仅证实了人类大脑的表型是可遗传的，而且 还展示了一种明确的区域特定的遗传模式，这有助于识别遗传变异 与大脑的细分有关。我们最近的工作证明了使用这一图谱来确定 基因组中因影响大脑结构的遗传效应而丰富的片段。在这项提案中，我们 将利用一个十倍扩大的样本，包括核磁共振和单核苷酸多态(SNP)数据，以及 先进的基因和成像方法，大大扩大了我们的工作范围。更大的样本 增加发现与单个大脑结构相关的SNPs的能力，并使我们能够检查 按年龄、性别和遗传祖先划分的遗传异质性。刻画子群是保证精度的关键 医学方法，并利用遗传上更同质的群体来增加统计能力(目标1)。 我们还将通过多模式成像来表征多效性和调节上位性对大脑的影响 (结构成像、扩散成像和功能成像)。这将提供对共同的和不同的基因影响的洞察 在不同的大脑区域之间。我们假设高度扩张的人类皮质中的变异是 与调节遗传效应有关(目标2)。第三，建立在改进的大脑遗传知识的基础上， 我们将确定它与神经精神障碍的遗传关系。我们将评估精神疾病的影响 以及神经遗传风险和环境暴露对MRI表型偏离正常的影响 神经发育和衰老轨迹(目标3)。目前的项目有很强的潜力显著地 增加我们对人脑的遗传基础的了解，并确定遗传和环境 促使大脑在一生中偏离典型轨迹的因素，最终的长期目标是 改进神经精神障碍的诊断、早期干预和治疗发展。

Project Summary Our goal is to determine gene-brain-behavior relationships, including those that underlie neuropsychiatric disorders. These disorders are common and increasing in incidence worldwide. However, there are significant clinical gaps in current treatment and objective diagnosis. Drug development trial failure rates are disproportionately high for brain disorders due to largely unknown differences in genetic bases between model species’ and human’s brains, which prevent translational success. A major challenge hindering progress in neuropsychiatric medicine is our limited understanding of the genetics underlying the complexity of human brain structure and function. Our first objective in the current study is to uncover genetic variants associated with brain imaging phenotypes (Aim 1). Our second objective is to test the genetic effects of regulatory and phylogenically annotated genomic elements on the human brain (Aim 2). Our third objective is to determine the impact of neuropsychiatric genetic risks and their environmental interactions on the brain (Aim 3). Previously we produced the first genetic atlas of the human cortex based on magnetic resonance imaging (MRI) data of twins using fuzzy clustering. This work not only confirmed that human brain phenotypes are heritable traits but also demonstrated a clear region-specific genetic pattern, which facilitates identification of genetic variants associated with brain subdivisions. Our recent work demonstrated the value of using this atlas to determine the segments of the genome that are enriched for genetic effects influencing brain structure. In this proposal, we will leverage a ten-fold enlarged sample with both MRI and single nucleotide polymorphism (SNP) data, and advanced genetic and imaging methods to significantly expand the scope of our work. The larger sample increases power for discovering SNPs associated with individual brain structures and will enable us to examine genetic heterogeneity by age, sex, and genetic ancestries. Characterizing subgroups is critical for precision medicine approaches and to increase statistical power using genetically more homogeneous groups (Aim 1). We will also characterize pleiotropy and regulatory epistasis effects on the brain by multimodal imaging (structural, diffusion and functional imaging). This will provide insight into shared and distinct genetic influences among different brain regions. We hypothesize that variations in the highly expanded human cortex are associated with regulatory genetic effects (Aim 2). Third, building on improved genetic knowledge of the brain, we will determine its genetic relationship with neuropsychiatric disorders. We will estimate effects of psychiatric and neurological genetic risks and environmental exposures on deviations of MRI phenotypes from normal neurodevelopmental and aging trajectories (Aim 3). The current project has strong potential to significantly increase our understanding of genetic basis of the human brain, and to determine genetic and environmental factors that drive brain deviations from typical trajectories across lifespan, with a long-term goal to ultimately improve diagnostics, early intervention and therapeutic development for neuropsychiatric disorders.