Disentangling Substance Use and Psychiatric Disorder Comorbidity for Future HuGE

解开未来 HuGE 的药物使用和精神疾病合并症

• 批准号: 7126368
• 负责人: RUMI KATO PRICE
• 金额: $ 22.41万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7126368
• 关键词: Disentangling; Substance; Use; Psychiatric; Disorder

DESCRIPTION (provided by applicant): There is a rapidly increasing need of public health significance to integrate human genetic information into analyses of population epidemiologic data to provide better understanding of biology-environment mechanisms underlying comorbidity of substance use and psychiatric disorders. In response to RFA-DA- 05-005, this R01 application requests support for 5 years to conduct coordinated analyses of NLAES, NESARC, Add Health and NHSDA/NSDUH repeated cross-sectional and/or longitudinal adolescent and adult national survey datafiles (each with different strengths and weaknesses) to provide informative results for future human-genome epidemiology (HuGE) aspects of NESARC. Race/ethnicity, immigration and acculturation, and family history, as well as gender, are conceptualized as key "low-resolution" genetic-behavioral-social (G-B-S) markers (reflecting molecular evolutionary history and recent population dynamics) to capture the interplay of genetic and environmental etiological factors. The main phenotypes are cross-sectional or longitudinal comorbidity of relatively-common substance use and psychiatric disorders or syndromes; the pleiotropy concept is applied to unrelated individuals. Add Health data with limited candidate gene information will be used to guide analyses for NESARC; when genotype information becomes available from NESARC, a portion of the phenotypic variance across race/ethnicity and individuals should be "explained away" by candidate gene main effects, epistasis, gene -environment interactions, in addition to independent environmental effects already measurable from the current NESARC datafiles. Specific analysis aims are to: 1) select phenotypes suitable for multiple-phenotype analyses by examining race/ethnicity differences on the comorbidity of two disorders that identify phenotypes that are likely to be influenced by relatively new polymorphisms or by relatively localized environmental factors or both; 2) corroborate cross-sectional phenotype selection achieved in Aim 1 from a genetic perspective; 3) delineate major gender- and race-/ethnic-specific environmental influences on the phenotypes selected in Aim 1; 4) improve polygenic measures standing-in for candidate genes for use in Aims 6), 7) and 8); 5) develop pleiotropy models of substance use abuse and psychiatric comorbidity (SAPC) to guide Aims 6), 7), and 8); 6) develop and test cross-sectional pleiotropy models for NESARC including environmental measures identified in Aim 3); 7) develop longitudinal pleiotropy models of SAPC for NESARC; 8) replicate the pleiotropy models developed in Aims 6) and 7) by replacing stand-in polygenic measures with candidate genotypes, pending on the availability of genotype data from NESARC.

描述（由申请人提供）： 将人类遗传信息整合到人群流行病学数据分析中，以更好地了解物质使用和精神疾病共病的生物环境机制，对公共卫生的重要性日益增长。为了响应 RFA-DA-05-005，此 R01 申请请求支持 5 年，以对 NLAES、NESARC、Add Health 和 NHSDA/NSDUH 重复横断面和/或纵向青少年和成人国家调查数据文件（每个数据文件都有不同的优点和缺点）进行协调分析，为未来的人类基因组流行病学 (HuGE) 方面提供信息结果。 NESARC。种族/族裔、移民和文化适应、家族史以及性别被概念化为关键的“低分辨率”遗传行为社会（G-B-S）标记（反映分子进化历史和近期种群动态），以捕捉遗传和环境病因因素的相互作用。主要表型是相对常见的物质使用和精神疾病或综合征的横向或纵向合并症；多效性概念适用于不相关的个​​体。添加具有有限候选基因信息的健康数据将用于指导 NESARC 的分析；当NESARC提供基因型信息时，除了可以从当前NESARC数据文件测量的独立环境影响之外，还应该通过候选基因主效应、上位性、基因-环境相互作用来“解释”跨种族/族裔和个体的部分表型差异。具体分析目的是：1）通过检查两种疾病合并症的种族/民族差异来选择适合多表型分析的表型，识别可能受到相对新的多态性或相对局部环境因素或两者影响的表型； 2）从遗传学角度证实目标1中实现的横截面表型选择； 3) 描述对目标 1 中选择的表型的主要性别和种族/族裔特定环境影响； 4) 改进用于目标 6)、7) 和 8) 的候选基因的多基因措施； 5) 开发药物滥用和精神共病 (SAPC) 的多效性模型来指导目标 6)、7) 和 8)； 6) 开发和测试 NEARC 的横截面多效性模型，包括目标 3) 中确定的环境措施； 7）为NESARC开发SAPC的纵向多效性模型； 8) 通过用候选基因型替换替代多基因测量来复制目标 6) 和 7) 中开发的多效性模型，等待 NESARC 基因型数据的可用性。