The ENIGMA consortium http://enigma.ini.usc.edu/) was established to understand brain structure, function, and disease by combining genetic and brain imaging datasets from numerous labs. Its goal is to maximize statistical power and the yield from existing datasets through very large data pooling efforts. Since its initial successes (e.g., a genetic-hippocampal volume association study with over 26,000 participants, Stein et al., 2012 Nature Genetics), a number of specific working groups have been established to use the ENIGMA methods (analysis standardization and meta-analysis) to address the neurobiology of specific diseases. The PI is a co-developer of the ENIGMA Addiction working group and this application proposes to conduct genetic-neuroimaging meta-analyses of over 9,000 datasets in an effort to understand better the biological underpinnings of addiction. We will coordinate the standardized analyses of cortical and subcortical brain structures and GWAS analyses at the participating sites and will take the lead in the combined meta-analyses. The Addiction working group will analyze data relevant to addiction phenotypes including case-control comparisons across a variety of substances. Going beyond this, the group will also examine the influence of comorbidities, gender and stages of disorder. We will aggregate data from case- control and developmental cohorts to examine the relative contribution of various genetic and brain correlates on risk for early onset substance misuse, transition to regular use, susceptibility to dependence, and individual differences in relapse vulnerability. Once established, we anticipate that the Addiction working group will grow considerably enabling ever-more substantial and insightful analyses and the pooled data will become a unique resource for addiction researchers.

Public Health Relevance

The ENIGMA consortium (http://enigma.ini.usc.edu/) was established to understand brain structure, function, and disease by combining genetic and brain imaging datasets. Its goal is to maximize statistical power and also the yield from existing datasets through very large data pooling efforts. This application seeks to establish an ENIGMA working group focused on addiction. We will conduct genetic-neuroimaging meta-analyses of over 9,000 datasets in an effort to understand better the biological underpinnings of addiction.

Agency
National Institute of Health (NIH)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21DA038381-01
Application #
8777779
Study Section
Pathophysiological Basis of Mental Disorders and Addictions Study Section (PMDA)
Program Officer
Grant, Steven J
Project Start
Project End
Budget Start
Budget End
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Vermont & St Agric College
Department
Psychiatry
Type
Schools of Medicine
DUNS #
City
Burlington
State
VT
Country
United States
Zip Code
05405