Deep sequencing studies for cannabis and stimulant dependence

大麻和兴奋剂依赖的深度测序研究

• 批准号: 8268314
• 负责人: CINDY L EHLERS
• 金额: $ 338.58万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8268314
• 关键词: Affect; African American; Alcohols; American; Blood specimen; Cannabis; Cell Line; Clinical; Cocaine; Cocaine Dependence; Cohort Studies; Comorbidity; Connecticut; DNA; DNA Sequence Analysis; Data; Data Set; Dependence; Development; Diagnosis; Diagnostic and Statistical Manual; Drug Addiction; Economics; European; Event; Exhibits; Family; Family Study; Functional disorder; Gene Amplification; Gene Frequency; Genes; Genetic; Genetic Polymorphism; Genetic Predisposition to Disease; Genetic Variation; Genome; Genomics; Genotype; Goals; Haplotypes; Heritability; Illicit Drugs; Individual; Informatics; Institution; Marijuana Dependence; Methamphetamine; Methodology; Methods; Minor; Mission; Missouri; National Institute of Drug Abuse; Native Americans; Nicotine; Opiate Addiction; Opioid; Other Genetics; Phase; Phenotype; Population; Population Characteristics; Population Study; Predisposition; Prevention strategy; Procedures; Psychostimulant dependence; Public Health; Qualifying; Research; Research Infrastructure; Research Institute; Research Proposals; Rest; Sampling; Sampling Studies; San Francisco; Secure; Sequence Analysis; Site; Source; Structure; Substance of Abuse; Symptoms; Technology; Testing; Universities; Variant; addiction; base; case control; cohort; computer infrastructure; cost; data reduction; data sharing; genetic linkage analysis; genetic risk factor; genome sequencing; genome wide association study; genome-wide; insight; interest; methamphetamine abuse; microdeletion; next generation; public health relevance; response; simulation; theories; trait; treatment strategy

DESCRIPTION (provided by applicant): The goal of this proposal is to identify genes that affect susceptibility to stimulant and cannabis dependence using whole genome sequencing with genotype imputation. The advent of increasingly economical whole genome sequencing provides new opportunities to identify trait-associated sequence variations not detected by linkage or association methods. It is not certain, however, what the most effective analytic method for identifying trait-related loci will be. Thus, we propose to study four distinct analytic approaches to identify sequence variants that affect stimulant and cannabis dependence in three cohorts using a state-of-the-art informatics infrastructure. The three study cohorts were ascertained as part of the Mission Indian Study (PI Cindy Ehlers), the combined Yale-University of Connecticut Addiction Study samples (PI Joel Gelernter) and the San Francisco Family Study (PI Kirk Wilhelmsen). Because we are studying populations with three different continental origins, we will ascertain whether the major genetic risk factors for the traits of interest are shared or population-specific. Two of the three populations that make up our sample (i.e., Native Americans and African Americans) are understudied. Inclusion of these cohorts will allow for analyses within and across populations that differ in ascertainment strategies and ethnic composition, permitting strong tests of replication across populations and enabling direct comparisons of ascertainment and analytic approaches as they apply to genetic studies of addiction. We expect that the approach used for this study will evolve. Currently we plan to use four complementary analytic strategies: 1) a conventional SNP analysis of genotypes detected using >5X sequence coverage for polymorphisms with minor allele frequency (MAF) greater than 0.1%; 2) a gene-based approach to determine whether more cases than controls have rare sequence variants (MAF<1%) likely to affect the function of a given gene; 3) use of a simplified form of affected-only linkage analysis of known and distantly related individuals to identify long chromosomal segments that are likely to be shared identical by descent; and 4) extended analysis of higher-level structural variation. The technology and economics of DNA sequence analysis is rapidly evolving. Based on current costs we plan to complete >5X whole genome sequencing of at least 3000 subjects. Critical to our decision to pursue low-pass genomic sequencing was the development of multipoint imputation methods. Simulation analysis indicates that for the same cost more subjects can undergo >5X whole genome sequencing with imputation than exomic sequencing, thus providing more exomic data as well as rich data for the rest of the genome. The findings from this study may provide insight into the genetics of other substances of abuse which can be confirmed by data sharing with other projects responding to this RFA and to other projects in the NIDA Genetics Consortium. PUBLIC HEALTH RELEVANCE: Cannabis and stimulants (methamphetamine and cocaine) are the most commonly used illicit drugs worldwide, and thus pose significant public health issues. Because cannabis and stimulant dependence have a substantial shared genetic etiology and exhibit significant genetic correlations with other drug dependencies, identifying sequence variants that affect cannabis and stimulant dependence should provide insights into the pathophysiology of dependence and inform prevention and treatment strategies.

描述（由申请人提供）：该提案的目标是使用全基因组测序和基因型插补来识别影响兴奋剂和大麻依赖性易感性的基因。日益经济的全基因组测序的出现为识别连锁或关联方法未检测到的性状相关序列变异提供了新的机会。然而，尚不确定识别性状相关基因座的最有效的分析方法是什么。因此，我们建议研究四种不同的分析方法，以使用最先进的信息学基础设施来识别影响三个队列中兴奋剂和大麻依赖性的序列变异。这三个研究队列被确定为印第安人研究 (PI Cindy Ehlers)、耶鲁大学-康涅狄格大学成瘾研究样本 (PI Joel Gelernter) 和旧金山家庭研究 (PI Kirk Wilhelmsen) 的一部分。因为我们正在研究具有三个不同大陆起源的人群，所以我们将确定感兴趣特征的主要遗传风险因素是共享的还是特定于人群的。构成我们样本的三个人群中的两个（即美洲原住民和非裔美国人）尚未得到充分研究。这些队列的纳入将允许在确定策略和种族构成不同的人群内部和人群之间进行分析，从而允许在人群之间进行强有力的复制测试，并在应用于成瘾遗传研究时能够直接比较确定和分析方法。我们预计本研究使用的方法将会不断发展。目前我们计划使用四种互补的分析策略：1）对次要等位基因频率（MAF）大于0.1％的多态性使用>5X序列覆盖度检测的基因型进行常规SNP分析； 2) 基于基因的方法，以确定是否有比对照更多的病例具有可能影响给定基因功能的罕见序列变异（MAF<1%）； 3) 对已知和远亲个体使用简化形式的仅受影响的连锁分析来识别可能具有相同血统的长染色体片段； 4）高级结构变异的扩展分析。 DNA 序列分析的技术和经济正在迅速发展。根据目前的成本，我们计划对至少 3000 名受试者完成超过 5 倍的全基因组测序。我们决定采用低通基因组测序的关键是多点插补方法的开发。模拟分析表明，在相同的成本下，更多的受试者可以接受比外显子组测序 >5 倍的全基因组测序，从而提供更多的外显子数据以及基因组其余部分的丰富数据。这项研究的结果可能提供对其他滥用药物的遗传学的深入了解，这可以通过与响应本 RFA 的其他项目和 NIDA 遗传学联盟的其他项目共享数据来证实。 公共卫生相关性：大麻和兴奋剂（甲基苯丙胺和可卡因）是全世界最常用的非法药物，因此造成严重的公共卫生问题。由于大麻和兴奋剂依赖具有显着的共同遗传病因，并且与其他药物依赖表现出显着的遗传相关性，因此识别影响大麻和兴奋剂依赖的序列变异应该有助于深入了解依赖的病理生理学，并为预防和治疗策略提供信息。