ENIGMA- Addiction: Pooling of Existing Datasets to Identify Brain and Genetic Correlates of Addiction

ENIGMA-成瘾：汇集现有数据集以识别成瘾的大脑和遗传相关性

• 批准号: 9615369
• 负责人: Patricia Conrod
• 金额: $ 66.91万
• 依托单位: UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9615369
• 关键词: Abstinence; Address; Adolescent; Adult; Age of Onset; Alcohol or Other Drugs use; Archives; Big Data; Biological Markers; Brain; Brain imaging; Candidate Disease Gene; Chronic; Collaborations; Communities; Comorbidity; Country; Data; Data Analyses; Data Analytics; Data Collection; Data Set; Databases; Dependence; Development; Disease; Ensure; Failure; Funding; Genes; Genetic; Genetic Markers; Genetic Predisposition to Disease; Genomics; Goals; Grant Review; Heritability; Institution; International; Investigation; Light; Link; Longevity; Magnetic Resonance Imaging; Measures; Medical Genetics; Mental Health; Meta-Analysis; Methods; Modality; Modeling; Nature; Neurobiology; Opioid user; Participant; Pattern; Pharmaceutical Preparations; Phenotype; Prefrontal Cortex; Privacy; Publishing; Quality Control; Reporting; Reproducibility; Research; Research Personnel; Rest; Risk; Sample Size; Sampling; Sampling Studies; Series; Sex Characteristics; Site; Smoking; Standardization; Structure; Substance abuse problem; Testing; Thick; United States National Institutes of Health; Validation; Weight; Work; addiction; analytical method; brain behavior; case control; cohort; data sharing; demographics; drug of abuse; genetic association; genome wide association study; imaging study; insight; interactive tool; neuroimaging; novel; pleiotropism; predictive marker; relating to nervous system; sobriety; success; tool; user-friendly; working group

PROJECT SUMMARY The ENIGMA consortium (http://enigma.ini.usc.edu/) was established to investigate brain structure, function, and disease by combining genomic and neuroimaging datasets from multiple sites. Its goal is to maximize statistical power and the yield from existing datasets through very large data pooling efforts. This goal has added importance today in light of concerns over the rigor and reproducibility of many neuroimaging and genomic findings. Since its initial successes (a genome wide association study on subcortical volumes with over 26,000 participants, Stein et al., 2012 Nature Genetics), a number of working groups have been established which use the standardized multi-site ENIGMA preprocessing pipelines and analytic methods to study the neurobiology of specific diseases. This application's PIs created the ENIGMA Addiction working group which now has access to datasets representing over 14000 participants. Genomic and neuromaging analyses on this unprecedented collection of data should produce important new insights into the neural and genetic basis of addiction. Building on our initial proof of concept funding (R21DA038381), we propose to further expand the Addiction working group which currently includes only a fraction of the world's potential relevant datasets, to identify robust brain markers of dependence for genetic association analyses, and to examine genetic and brain markers for the transition between stages of substance use across the lifespan. We will also increase the range of brain measures examined to include structural and functional connectivity (DTI and resting-state data) and will develop morphometric analyses of brain structures. We can use these biomarkers to assess if brain alterations preceded dependence or arose during early or chronic use and if these effects correct with abstinence by exploiting the familial, developmental, longitudinal and abstinence samples in our working group. We will create a data analysis portal that will provide both wide access to the pooled data and optimized analytic methods that maximize rigor and reproducibility (e.g., appropriate covariates, nested variance models, propensity weighting for sociodemographics, cross-validation) thereby guiding others to use these data appropriately and wisely. The analysis portal will archive analyses (e.g., exact subjects and analysis scripts) to ensure best practice and full transparency. We will actively work to expand the consortium to create a uniquely large neuroimaging-genetic addiction dataset and we will make results freely available to the research community through the online interactive tool ENIGMA-Vis (http://enigma.ini.usc.edu/enigma-vis/).

项目总结