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: 7498392
• 负责人: RUMI KATO PRICE
• 金额: $ 21.33万
• 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/7498392
• 关键词: Acculturation; Address; Adolescent; Adult; Alcohol or Other Drugs use; Alcohols; Applied Genetics; Asians; Behavioral Genetics; Biology; Candidate Disease Gene; Capital; Clinical; Comorbidity; Condition; Cross-Sectional Studies; Data; Data Collection; Data Set; Databases; Diagnostic and Statistical Manual; Disease; Doctor of Philosophy; Drug abuse; Environment; Environmental Risk Factor; Epidemiology; Ethnic Origin; Extramural Activities; Family history of; Figs - dietary; Future; Gender; General Population; Genes; Genetic; Genetic Epistasis; Genetic Polymorphism; Genome; Genome Scan; Genotype; Goals; Health; Hispanics; Household; Human Genetics; Human Genome; Illicit Drugs; Immigration; Individual; Localized; Longitudinal Studies; Measurable; Measures; Mental disorders; Modeling; Molecular; National Institute on Alcohol Abuse and Alcoholism; Personal Communication; Pharmaceutical Preparations; Phenotype; Population; Population Database; Population Dynamics; Price; Public Domains; Public Health; Race; Recording of previous events; Request for Applications; Research Personnel; Resolution; Sample Size; Sampling; Series; Standards of Weights and Measures; Structure; Subgroup; Surveys; Syndrome; Testing; Variant; base; concept; ethnic difference; gene environment interaction; genetic epidemiology; genetic variant; improved; interest; pleiotropism; response; social

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口流行病学数据的分析中，以更好地了解物质使用和精神障碍共病的生物-环境机制，对公共卫生意义日益增长。作为对RFA-DA-05-005的响应，该R01应用程序请求支持5年，以便对NLAES、NESARC、ADD Health和NHSDA/NSDUH重复的横断面和/或纵向青少年和成人全国调查数据文件(每个文件具有不同的优势和弱点)进行协调分析，以便为NESARC未来的人类基因组流行病学(GHIG)方面提供信息。种族/民族、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(反映分子进化史和最近的种群动态)，以捕捉遗传和环境病因因素的相互作用。主要的表型是相对常见的物质使用和精神障碍或综合征的横断面或纵向共病；多效性概念适用于无关的个人。具有有限候选基因信息的Add Health数据将被用于指导NESARC的分析；当从NESARC获得基因信息时，种族/民族和个人之间的一部分表型差异应该被候选基因主效应、上位性、基因-环境相互作用“解释”，此外还有从当前NESARC数据文件中已经可以测量的独立环境影响。具体分析的目的是：1)通过检查种族/民族差异在两种疾病的共病上的差异来选择适合于多表型分析的表型，该两种疾病识别可能受相对新的多态或相对局部的环境因素影响的表型；2)从遗传角度证实目标1中实现的横截面表型选择；3)描述性别和种族/民族特定的环境对目标1中选择的表型的主要影响；4)改进在目标6)、7)和8)中使用的候选基因的多基因替代措施；5)开发药物滥用和精神共病(SAPC)的多效性模型，以指导AIMS 6)、7)和8)；6)为NESARC开发和测试横断面多效性模型，包括AIMS 3)中确定的环境措施；7)为NESARC开发SAPC的纵向多效性模型；8)复制AIMS 6)和7)中开发的多效性模型，方法是用候选基因替代替代多基因措施，这取决于来自NESARC的基因数据的可用性。