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 （SUD）。然而，单靠遗传学研究不能解释SNP和SNP之间的分子变化级联， SU和SUD。目前的方法也不能正确地衡量遗传差异的因果影响， 与SU和SUD相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SUD病因学的理解。但他们 未能捕获复杂的基因相互作用，这些基因相互作用是复杂性状的标志，包括SU和SUD，或者 大部分动力不足（尤其是脑组织）。另一个限制是遗传和分子研究 忽略环境混杂。我们知道，父母创造和影响儿童的环境， 某些父母和家庭环境与SU和SUD更相关。不仅遗传风险不同 与环境，但环境本身也是遗传的，因此混淆了父母 遗传学我们和其他人认为，消除父母对后代分子遗传学对SU的影响， 和SUD从父母和家庭环境是遗传学的中心任务。在这里，我们依靠最近的 方法上的进步，以解决这些局限性。首先，我们开发了一种新颖且经过验证的方法， 测量未传递的父母基因组的影响。该方法确定了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基因组的一个重要影响是 遗传培育环境的证据，不受直接的父母到后代遗传学的混淆。 其次，我们现在可以使用现有的GWAS执行基因表达（GE）插补。因此，我们可以 在非常大的样本中估计遗传的、全基因组的个体差异。这 大大增加了我们识别SU和SUD病因的分子途径的能力。总的来说， 我们建议i）使用来自大规模人群家庭样本的现有GWAS数据，ii）应用我们的方法 组装未传播的亲本基因组，iii）估算亲本传播和未传播的GE，iv）应用 网络分析，以识别与SU和SUD相关联的传输和未传输GE网络， 以及v）识别调解这些网络的父母和家庭环境。这将使我们能够识别GE 网络参与SU和SUD，同时确定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被基因“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.