Methodological Research on Substance Use

描述（由申请人提供）： 该职业奖将帮助PI在未来五年内通过建立他在统计方法学方面的优势，特别是基于递归分区的技术，以及他分析与药物使用相关的数据的经验，实现以下职业目标： (1)进一步拓宽他的知识，提高他对人类遗传学的理解，特别是与物质使用障碍的遗传病因学和与环境的相互作用有关的知识。 (2)开发在生物医学数据分析中具有广泛应用的统计方法;开发用于遗传分析的基于树的统计方法和软件;建立用于序数性状遗传分析的潜变量模型和软件;并将新方法应用于正在进行的NIDA资助的研究，例如通过考虑一个序数表型定义，更好地了解物质使用障碍的遗传流行病学，更好地反映物质使用障碍是如何定义和记录的;并确定烟草使用的候选基因及其与酒精使用和精神障碍（包括焦虑）的共病性。 (3)建立和维持在统计方法和分析的领导作用，通过讲座，研讨会和会议传播我们的方法和结果，研究物质使用和相关疾病的遗传流行病学。 (4)加强他在耶鲁内外的知识网络，特别是在物质使用的研究方面。了解遗传流行病学和环境对复杂疾病的影响，包括物质使用障碍，仍然是一个巨大的挑战。该奖项使PI能够在相对较长的时间内投入大量精力，开发一些急需的，及时的统计方法和软件，帮助我们提高对物质使用障碍的理解。

DESCRIPTION (provided by applicant): This career award will help the PI achieve the following career goals during the next five years by building on his strength in the statistical methodology, particularly the recursive partitioning based techniques, and on his experience of analyzing data related to substance use, and: (1) To further broaden his knowledge and enhance his understanding of human genetics, particularly related to genetic etiology of substance use disorders and interactions with environment. (2) To develop statistical methods that are of broad applications in analyzing biomedical data; to develop tree-based statistical methods and software for genetic analyses; to establish latent variable models and software for genetic analyses of ordinal traits; and to apply the new methods in on-going NIDA funded studies such as to better understand the genetic epidemiology of substance use disorders by considering an ordinal phenotypic definition that is a better reflection of how the substance use disorders were defined and recorded; and to identify candidate genes for tobacco use, and its comorbidity with alcohol use and psychiatric disorders including anxiety. (3) To establish and sustain a leadership role in statistical methodology and analysis for studying genetic epidemiology of substance use and related disorders by disseminating our methods and results through lectures, seminars, and conferences. (4) To strengthen his intellectual network inside and outside Yale particularly in studies of substance use. Understanding genetic epidemiology and environmental effects for complex diseases including substance use disorders remains a tremendous challenge. This award enables the PI to invest a major effort in a relatively long term to develop some of the critically needed, timely statistical methods and software, which help us advance our understanding of substance use disorders.