Identifying genetic sources of comorbidity between cannabis and schizophrenia using genome-wide and integrative omics data

使用全基因组和综合组学数据识别大麻和精神分裂症之间共病的遗传来源

• 批准号: 10594423
• 负责人: Emma Covey Johnson
• 金额: $ 15.73万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594423
• 关键词: Accounting; Acute; Address; Animal Model; Antipsychotic Agents; Behavior; Behavioral; Bioinformatics; Biological; Biology; Cannabis; Cannabis policy; Child; Childhood; Chronic; Clinical; Data; Data Analyses; Data Set; Development; Disease; Educational Status; Epigenetic Process; Etiology; Exposure to; Foundations; Funding; Future; Gene Expression; General Population; Genes; Genetic; Genetic Predisposition to Disease; Goals; Heritability; Incidence; Individual; Investigation; Leadership; Maps; Mediating; Mental Depression; Mental disorders; Mentored Research Scientist Development Award; Mentorship; Motivation; Multiomic Data; Neurobiology; Outcome; Pathway interactions; Patients; Persons; Pharmaceutical Preparations; Population; Positioning Attribute; Predisposition; Prefrontal Cortex; Psychoses; Psychotic Disorders; Public Health; REM Sleep; Recording of previous events; Recreation; Relapse; Reporting; Research; Research Personnel; Risk; Rodent; Rodent Model; Role; Sampling; Schizophrenia; Source; Subgroup; Suicide; Testing; Tetrahydrocannabinol; Therapeutic; Time; Tissue Model; Tissues; Training; US State; United States; United States National Institutes of Health; Variant; Vulnerable Populations; Work; actionable mutation; addiction; adverse outcome; career; career development; causal variant; clinical effect; clinical translation; comorbidity; cost; data integration; design; experimental study; first episode psychosis; follow-up; genetic architecture; genetic variant; genome wide association study; genome-wide; high risk; human data; human model; human tissue; insight; longitudinal course; marijuana legalization; marijuana use; marijuana use disorder; marijuana user; multiple omics; novel; pleiotropism; polygenic risk score; population based; psychiatric comorbidity; psychosocial; skill acquisition; substance use treatment; transcriptomics

Project Summary Recreational cannabis use is becoming increasingly common in the United States, even within vulnerable populations. Amidst growing concerns surrounding the possible adverse consequences of chronic cannabis use, there is evidence that cannabis use disorder (CUD) is genetically correlated with susceptibility to several behavioral (e.g., lower educational achievement) and psychiatric (e.g., schizophrenia) outcomes, thus bringing into question prior causal claims. The most aggressively contested discussion surrounds the role of cannabis use and CUD in the etiology of schizophrenia (SCZ) and psychotic illness. While there is now an abundance of evidence supporting shared genetic influences, studies also outline the psychotomimetic effects of especially high potency forms of tetrahydrocannabinol (THC). A systematic search for pleiotropic variants that undergird this comorbidity between CUD and SCZ can not only provide insights into shared biology, but also outline avenues for identifying subgroups of individuals at greatest risk. This Mentored Research Scientist Development Award (K01) proposes a research plan that leverages some of the largest currently available genome-wide association study (GWAS) datasets to (a) conduct a cross-disorder GWAS of CUD with SCZ, and to contrast it with findings from a similar cross-disorder analysis of cannabis use with SCZ, to identify loci of convergent and divergent effect; (b) to test for a causal relationship using a genetically-informed approach and harness curated `omics data from human and rodent models of cannabis exposure and SCZ, to fine-map significant loci and further prioritize causal variants for biological plausibility; and (c) to utilize polygenic risk scores derived from these cross-disorder analyses to identify associations with first-episode psychosis, cannabis-induced psychosis, and childhood psychosis-proneness in independent samples. These research aims are founded on four key training objectives that will enhance the applicant's career goal of becoming an NIH-funded independent investigator who works at the interface of addictions and psychiatric illness. These training objectives include (a) a deep understanding of the clinical effects of acute and chronic exposure to cannabis, (b) integrative bioinformatics approaches for post-GWAS annotation, including cross-species data (c) an appreciation of the neurobiology underlying the comorbidity between cannabis and SCZ, and (d) career development towards leadership and mentorship positions. The applicant builds upon her current funding and training directed at advanced statistical genetics to addressing comorbidity by adding on novel facets relating more broadly to multi- omics data integration and more specifically to the unique yet ubiquitous comorbidity between cannabis and SCZ. Together, this training and research plan will produce some of the first insights into the shared genetic etiology underlying CUD and SCZ and provide opportunities for functionally targeted future studies, with the ultimate objective of producing therapeutic alternatives that can partially mitigate the serious personal costs of chronic cannabis use in SCZ patients.

项目概要 在美国，娱乐性大麻的使用变得越来越普遍，甚至在弱势群体中也是如此 人口。人们越来越担心长期使用大麻可能产生的不利后果， 有证据表明大麻使用障碍 (CUD) 与多种疾病的易感性存在遗传相关性 行为（例如，较低的教育成绩）和精神（例如，精神分裂症）结果，从而带来 对先前的因果主张提出质疑。最激烈的争论围绕着大麻的作用 精神分裂症 (SCZ) 和精神病的病因学中的使用和 CUD。虽然现在有大量的 有证据支持共同的遗传影响，研究还概述了特别是拟心理作用 四氢大麻酚（THC）的高效形式。系统地搜索支撑的多效性变异 CUD 和 SCZ 之间的这种共病不仅可以提供对共享生物学的见解，还可以概述 识别风险最大的个人亚组的途径。这指导了研究科学家的发展 奖（K01）提出了一项研究计划，该计划利用了一些目前可用的最大的全基因组 关联研究 (GWAS) 数据集，以 (a) 进行 CUD 与 SCZ 的跨疾病 GWAS，并进行对比 结合使用大麻和 SCZ 的类似跨疾病分析的结果，以确定收敛和收敛的位点 发散效应； (b) 使用遗传信息方法和利用策划来测试因果关系 “来自人类和啮齿动物大麻暴露和 SCZ 模型的组学数据，以精细绘制重要位点和 进一步优先考虑因果变异的生物学合理性； (c) 利用源自​​的多基因风险评分 这些跨疾病分析旨在确定与首发精神病、大麻引起的精神病、 以及独立样本中的儿童精神病倾向。这些研究目标基于四个关键 培训目标将提高申请人成为 NIH 资助的独立人士的职业目标 研究成瘾和精神疾病的研究者。这些培训目标包括 (a) 深入了解急性和慢性接触大麻的临床影响，(b) 综合 用于后 GWAS 注释的生物信息学方法，包括跨物种数据 (c) 对 大麻和 SCZ 之间共病的神经生物学，以及 (d) 职业发展 领导和指导职位。申请人以目前的资金和培训为基础 先进的统计遗传学通过添加更广泛地与多种相关的新方面来解决合并症 组学数据整合，更具体地说是大麻和大麻之间独特但普遍存在的共病 SCZ。这项培训和研究计划将共同产生对共享遗传的一些初步见解。 CUD 和 SCZ 的病因学，并为未来功能目标研究提供机会， 最终目标是生产可以部分减轻严重个人成本的治疗替代方案 SCZ 患者长期使用大麻。