Gene Variants for Nicotine Withdrawal Deficits in Learning

尼古丁戒断学习障碍的基因变异

• 批准号: 9544198
• 负责人: Thomas J Gould
• 金额: $ 35.37万
• 依托单位: PENNSYLVANIA STATE UNIVERSITY, THE
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9544198
• 关键词: Abstinence; Accounting; Alleles; American; Animal Model; Cerebellum; Cessation of life; Chronic; Cognition; Cognitive; Cognitive deficits; Data; Data Analyses; Databases; Development; Dorsal; Economic Burden; Female; Gene Expression; Genes; Genetic; Genetic Variation; Genotype; Goals; Health; Heritability; Hippocampus (Brain); Homologous Gene; Human; Inbred Mouse; Inbred Strains Mice; Inbreeding; Individual; Intervention; Laboratories; Learning; Maps; Measures; Methods; Molecular; Mus; Nicotine; Nicotine Dependence; Nicotine Withdrawal; Outcome; Patients; Pattern; Phenotype; Pilot Projects; Population; Populations at Risk; Predisposition; Quantitative Trait Loci; Recombinant Inbred Strain; Recombinants; Relapse; Reporting; Rodent Model; Signal Transduction; Site; Smoker; Smoking; Surveys; Symptoms; Taxes; Time; Tissue Banks; United States; Variant; Withdrawal; Withdrawal Symptom; Work; base; cigarette smoking; conditioned fear; drug discovery; effective therapy; genetic variant; genome database; individualized medicine; mRNA Expression; male; next generation sequencing; novel therapeutics; premature; public health relevance; relapse prediction; relating to nervous system; response; self-directed learning; sex; smoking cessation; statistics; therapy development; trait; transcriptome; transcriptome sequencing

 DESCRIPTION (provided by applicant): Nicotine addiction continues to be a major problem in the US with smoking accounting for the loss of 443,000 lives and an estimated $193 billion economic burden each year. These staggering statistics speak to important of identifying factors that contribute to nicotine addiction. Cognitive deficits such as disrupted learning are a major symptom of nicotine withdrawal, yet little is understood about the genetic factors that contribute to nicotine withdrawal-related changes in cognition. Identifying the neural and genetic substrates of nicotine withdrawal deficits in cognition will provide data to facilitate drug discovery and identify markers for at risk populations. Use of genetic data to identify at risk populations could also facilitate development of treatments that could increase the likelihood of maintaining abstinence. Recent data from a study examining nicotine withdrawal-related changes in hippocampus-dependent learning in mice demonstrated that genetics contributes to this cognitive withdrawal phenotype. As the specific genes involved in this withdrawal phenotype are unknown, it is the goal of this application to use next-generation sequencing to identify gene variants related to nicotine withdrawal deficits in learning. Studies in the proposal will use the recombinant inbred (RI) BXD strain to characterize phenotypic differences across BXD lines (Aim 1) and use that data for quantitative trait loci (QTL) analysis to identify genes associated with the nicotine withdrawal learning deficit phenotype (Aim 2). In addition, BXD databases will be examined to identify other phenotypes that are genetically correlated with the cognitive withdrawal phenotype (Aim 2). Finally, RNA-sequencing in BXD lines that show extreme phenotypic variation will be used to identify changes in the transcriptome associated with the nicotine withdrawal deficit in learning phenotype. These studies should significantly advance understanding of and treatment of nicotine addiction. Identifying genes and gene expression changes that are associated with nicotine withdrawal deficits in learning in the mouse will facilitate identifying if homologous genes in humans that are associated with nicotine withdrawal deficits in cognition. This could help practitioners tailor treatments to patients. In addition, identifying specific changes in the transcriptome associated with nicotine withdrawal deficits in learning will provide valuable information on the changes in cell signaling that contribute to nicotine withdrawal deficits in learning and this should aid in identifying potential targets for pharmacotherapeutic development.

 描述（由申请人提供）：尼古丁成瘾仍然是美国的一个主要问题，吸烟每年造成 443,000 人死亡，并造成约 1,930 亿美元的经济负担。这些令人震惊的统计数据说明了识别导致尼古丁产生的因素的重要性。认知缺陷（例如学习障碍）是尼古丁戒断的主要症状，但人们对导致尼古丁戒断相关认知变化的遗传因素知之甚少。尼古丁戒断认知缺陷的遗传底物将为促进药物发现和识别高危人群的标记提供数据，可以利用遗传数据来识别高危人群。 还有助于开发可以增加戒断可能性的治疗方法，最近一项研究的数据显示，小鼠海马依赖性学习中尼古丁戒断相关的变化是遗传导致这种认知戒断表型的特定基因。未知，本申请的目标是使用下一代测序来识别与学习中尼古丁戒断缺陷相关的基因变异。该提案中的研究将使用重组近交（RI）BXD菌株来表征。跨 BXD 品系的表型差异（目标 1），并使用该数据进行数量性状基因座 (QTL) 分析，以确定与尼古丁戒断学习缺陷表型相关的基因（目标 2）。此外，还将检查 BXD 数据库以确定其他表型。与认知戒断表型存在遗传相关性（目标 2），对表现出极端表型变异的 BXD 品系进行 RNA 测序将用于识别与认知戒断表型相关的转录组变化。这些研究将显着促进对尼古丁成瘾的理解和治疗，识别与小鼠学习中的尼古丁戒断缺陷相关的基因和基因表达变化将有助于识别人类中是否存在与尼古丁戒断缺陷相关的同源基因。此外，识别与尼古丁戒断认知缺陷相关的转录组的具体变化将为导致尼古丁戒断缺陷的细胞信号变化提供有价值的信息。学习，这应该有助于确定药物治疗开发的潜在目标。