Psychometric and Genetic Assessments of Substance Use

描述（由申请人提供）：该项目旨在开发和应用新的统计方法来解决物质使用，滥用和依赖的病因学中的关键挑战。它们是：高密度数据；环境相互作用的基因型；测量;起跳和偏移；和疾病。基因组学和其他组学技术、神经影像学以及对环境、位置和行为的近连续评估的最新进展，为了解物质使用行为的遗传和环境风险因素之间的相互作用创造了前所未有的机会。该项目将开发新的统计模型和计算效率高的软件和方法，以便对物质使用表型、基因型和环境措施进行数据挖掘。这些模型包括：在测量精度可变的情况下检测GxE相互作用的模型；将遗传标记等高密度数据纳入结构方程模型，区分直接效应和间接效应；基因-环境相互作用模型，特别是生态位选择；合并症混合分布模型；症状共现的可选模型；制度转换是为了更好地描述结果的替代途径。新方法和模型将应用于项目团队成员在美国、荷兰和澳大利亚收集的数据集，包括测量的基因型和环境风险因素。新模型和方法将自由传播，大大增加现有数据集和新技术组装的数据集的价值。

DESCRIPTION (provided by applicant): This project aims to develop and apply novel statistical approaches to address key challenges in the etiology of substance use, abuse and dependence. These are: high-density data; genotype by environment interplay; measurement; onset and offset; and comorbidity. Recent advances in genomic and other -omic technologies, neuroimaging, and near-continuous assessments of environment, location and behavior are creating unprecedented opportunities to understand the interplay between genetic and environmental risk factors for substance use behaviors. The project will develop new statistical models and computationally efficient software and methods to permit data mining of substance use phenotypes, genotypes and environmental measures. These models include those for: detecting GxE interaction in the presence of variable measurement precision; incorporating genetic marker and other high-density data into structural equation models to distinguish direct from indirect effects; models for gene-environment interplay, especially niche-selection; mixture distribution models of comorbidity; alternative models for symptoms co-occurrence; and regime switching to better characterize alternative pathways to outcomes. The new methods and models will be applied to datasets including measured genotypes and environmental risk factors collected in the United States, The Netherlands and Australia by project team members, The new models and methods will be disseminated freely and greatly increase the value of existing datasets and those being assembled with novel technologies.