Using transmitted and untransmitted gene networks to identify molecular pathways to substance use & misuse in genetically controlled twins

项目摘要 多种遗传风险导致酒精、尼古丁和大麻物质使用(SU)和物质使用障碍 (肥皂水)。然而，单靠遗传研究不能解释SNPs和SNPs之间的级联分子变化。 苏和肥皂水。目前的方法也不能正确地衡量遗传差异对 与SU和SUDS有关的父母和家庭环境。将GWAS结果与基因联系起来的分子研究 通过eQTL发现的表达数据增加了我们对SU和SUDS病因的理解。然而，他们 未能捕捉到复杂的基因相互作用，这些基因是包括SU和SUD在内的复杂特征的标志，或者是 主要是动力不足(尤其是脑组织)。另一个限制是遗传和分子研究 忽视了环境的混杂。我们知道父母创造和影响孩子的环境，而且 某些父母和家庭环境更多地与SU和SUDS有关。不仅遗传风险各不相同 但环境本身也是可遗传的，因此被父母混淆 遗传学。我们和其他人认为，没有混淆的亲子分子遗传学对SU的影响 而来自父母和家庭环境的肥皂水是遗传学的中心任务。在这里，我们依靠最近的 解决这些局限性的方法进步。首先，我们开发了一种新的、经过验证的方法 测量未传播的亲本基因组的影响。此方法确定以下因素的间接影响 未传递的父母基因组对复杂行为的影响。未传播的基因组的一个重要影响是 不受直接亲子遗传影响的遗传培育环境的证据。 其次，我们现在可以使用现有的基因表达(GE)来进行基因表达(GE)推算。因此，我们可以， 在非常大的样本中估计可遗传的、全基因组范围的GE网络中的个体差异。这 极大地增强了我们识别SU和SUD病因的分子途径的能力。总而言之， 我们建议i)使用现有的基于人口的大量家庭样本的Gwas数据，ii)应用我们的方法 组装未传递的亲本基因组，iii)归因于父母传递的和未传递的GE，iv)应用 网络分析以识别与SU和SUD相关联的已传输和未传输GE网络， 以及v)确定调解这些网络的父母和家庭环境。这将使我们能够确定GE 参与SU和SODS的网络，同时识别高风险和保护性的父母和家庭环境 都是在一个统一的理论框架内从基因上“培育”出来的。

Project Summary Multiple genetic risks cause alcohol, nicotine and cannabis substance use (SU) and substance use disorders (SUDs). However, genetic studies alone cannot explain the cascade of molecular changes between SNPs and SU and SUDs. Nor can current approaches correctly measure the causal impact of genetic differences on parental and home environments linked to SU and SUDs. Molecular studies that link GWAS results to gene expression data via eQTL findings have increased our understanding of the etiology of SU and SUDs. Yet, they fail to capture complex gene interactions that are the hallmark of complex traits including SU and SUDs, or are mostly underpowered (especially from brain tissues). Another limitation is that genetic and molecular studies neglect environmental confounding. We know that parents create and influence children’s environments and that certain parental and home environments are more associated with SU and SUDs. Not only do genetic risks vary with environments, but environments themselves are also heritable, and are thus confounded by parental genetics. We and others argue that unconfounding the impact of parent-to-offspring molecular genetics on SU and SUDs from the parental and home environments is the central task of genetics. Here, we rely on recent methodological advances to address these limitations. First, we have developed a novel and proven method of measuring the impact of untransmitted parental genomes. This method identifies the indirect impact of untransmitted parental genomes on complex behaviours. A significant impact of untransmitted genomes is evidence of genetically nurtured environments that are unconfounded by the direct parent-to-offspring genetics. Second, we can now perform gene expression (GE) imputation using existing GWAS. We can, therefore, estimate heritable, genome-wide individual differences in imputed GE networks in very large samples. This substantially increases our power to identify molecular pathways underlying SU and SUD aetiology. In summary, we are proposing to i) use existing GWAS data from large population-based family samples, ii) apply our method of assembling untransmitted parental genomes, iii) impute parentally transmitted and untransmitted GE, iv) apply network analyses to identify transmitted and untransmitted GE networks that are associated with SU and SUDs, and v) identify parental and home environments mediating these networks. This will enable us to identify the GE networks involved in SU and SUDs while identifying risky and protective parental and home environments that are genetically ‘nurtured’ within a unified theoretical framework.