权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

基本信息

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
项目类别：
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

项目摘要

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.

项目总结