Use of Next-Gen Sequencing to Identify Genetic Variants that Influence compulsive Oxycodone Intake in Outbred Rats

使用下一代测序来识别影响远交大鼠强迫性羟考酮摄入的遗传变异

• 批准号: 10671889
• 负责人: Olivier George
• 金额: $ 92.41万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2028-02-29
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10671889
• 关键词: Absence of pain sensation; Analgesics; Animal Genetics; Animal Model; Animals; Behavior; Behavioral; Biological; Brain; Brain region; Chronic; Collaborations; Communities; Complex; Computer software; Data; Development; Disease; Environment; Epigenetic Process; FDA approved; Family Study; Female; Foundations; Gene Expression; Genes; Genetic; Genomics; Genotype; Goals; Heritability; Human Genome; Hyperalgesia; Individual; Infrastructure; Intake; Intravenous; Investigation; Lead; Machine Learning; Maps; Methodology; Modeling; Molecular; National Institute of Drug Abuse; Nucleotides; Opiate Addiction; Outcome; Oxycodone; Pain; Phenotype; Physiology; Procedures; Quantitative Trait Loci; Rattus; Research; Research Personnel; Resistance; Resources; Risk; Sample Size; Sampling; Self Administration; Sex Differences; Standardization; Substance Addiction; Substance Use Disorder; Substance abuse problem; Tandem Repeat Sequences; Technology; Tissue Banks; Tissues; Twin Studies; United States National Institutes of Health; Variant; Video Recording; Withdrawal; addiction; behavioral phenotyping; biobank; comorbidity; cost; data integration; deep neural network; endophenotype; follow-up; genetic analysis; genetic variant; genome sequencing; genome wide association study; genomic locus; improved; longitudinal analysis; male; multidisciplinary; multiple omics; new therapeutic target; next generation; next generation sequencing; novel; novel strategies; opioid use disorder; pre-clinical; programs; screening; screening program; sex; trait; transfer learning

Abstract The purpose of the NIDA Animal Genetics Program is to identify genetic, genomic, epigenetic variants, physiology and brain functions that contribute to addiction-like behaviors, related behavioral endophenotypes, and behavioral comorbidities to substance use disorder. During the past four years, our multidisciplinary and highly collaborative consortium has been identifying gene variants that are associated with increased vulnerability to compulsive oxycodone use, tolerance to the analgesic effects of oxycodone, and development of withdrawal-induced hyperalgesia by performing the first GWAS using an advanced model of chronic intravenous oxycodone self-administration in N/NIH heterogeneous stock (HS). We have also created the first preclinical oxycodone biobank which enables researchers who do not have the resources to perform chronic intravenous self-administration or next-generation genome sequencing to perform advanced genetic, molecular, and cellular studies to further our understanding of the biological changes underlying addiction-like behaviors. While these efforts have been very successful in achieving the planned milestones, it has become clear that our project would benefit from an even larger sample size. In particular, increasing sample sizes lead to exponential rather than linear increase in the number of loci identified, and would allow us to identify sex- specific gene variants. Moreover, in the past four years there has been tremendous technological advances in behavioral and genetic analysis that can be leveraged to provide unprecedented access to identify the single nucleotide and structural variants that contribute to complex behavioral endophenotypes of high relevance to oxycodone use-disorders. The first goal of this competing renewal is to double the sample size of the current GWAS to increase the number of gene variants identified including sex-specific variants and meet the demands of the Biobank. The second goal is to use high-throughput behavioral phenotyping using markerless pose estimation based on machine learning with deep neural network to identify behavioral endophenotypes that can help predict and identify individuals with a resistant, mild, moderate, or severe phenotype of oxycodone addiction-like behaviors. The third goal is to use methodological improvements of the genetic analysis, including the analysis of structural variants and tandem repeats, as well as enhanced integration with gene expression data. The fourth goal is to strengthen the oxycodone biobank infrastructure. This project is likely to continue having a sustained and powerful impact on the field because it will provide an exponential increase in the number of genetic loci identified, eQTLs and PheWAS analysis related to addiction-like behavior; establish the first high-throughput behavioral motifs analysis of addiction-like behaviors using parallel video-recording and automated machine learning analysis; identify novel behavioral endophenotypes of vulnerability/resistance to addiction-like behaviors; and expand and improve the Oxycodone Biobank offering and infrastructure.

抽象的 NIDA动物遗传学计划的目的是确定遗传，基因组，表观遗传变异， 有助于类似成瘾行为的生理和大脑功能，相关的行为内表型， 和对药物使用障碍的行为合并症。在过去的四年中，我们的多学科和 高度协作的财团一直在识别与增加有关的基因变体 强迫羟考酮使用的脆弱性，对羟考酮的镇痛作用的耐受性以及发育 通过使用高级慢性模型执行第一个GWA的戒断诱导的痛觉过敏 N/NIH异质股（HS）中静脉羟考酮自我给药。我们还创建了第一个 临床前羟考酮生物库，使没有资源的研究人员可以执行慢性 静脉自我给药或下一代基因组测序以执行晚期遗传， 分子和细胞研究，以进一步了解类似成瘾的生物学变化 行为。尽管这些努力在实现计划中的里程碑方面非常成功，但它已经成为 很明显，我们的项目将受益于更大的样本量。特别是，增加样本量的铅 指数级而不是线性增加的基因座数量，并使我们能够识别性别 - 特定基因变体。此外，在过去的四年中，技术进步取得了巨大进步 行为和遗传分析可以利用以提供前所未有的访问来识别单一 核苷酸和结构变体有助于与相关性高相关的复杂行为内表型 羟考酮的使用。这种竞争更新的第一个目标是将电流的样本量增加一倍 GWAS增加了鉴定出包括性别特异性变体的基因变异数量，并满足 生物库的需求。第二个目标是使用无标记的高通量行为表型 基于机器学习的姿势估计，并具有深层神经网络，以识别行为内表型 这可以帮助预测和识别具有抗性，轻度，中度或严重表型的个人 羟考酮成瘾行为。第三个目标是利用遗传的方法论改进 分析，包括分析结构变体和串联重复序列，以及与 基因表达数据。第四个目标是加强羟考酮生物库基础设施。这个项目是 可能会继续对该领域产生持续和强大的影响，因为它将提供指数级 与成瘾相关的遗传基因座，EQTL和PHEWAS分析的数量增加 行为;使用并联建立第一个对成瘾行为的高通量行为图案分析 视频录制和自动化机器学习分析；识别新型的行为内表型 脆弱性/对成瘾行为的抵抗；扩展和改善羟考酮生物库的产品 和基础设施。