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

> **NIH NIH R01** · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · 2021 · $659,264

## Abstract

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/).

## Key facts

- **NIH application ID:** 10205011
- **Project number:** 5R01DA047119-04
- **Recipient organization:** UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
- **Principal Investigator:** Patricia Conrod
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $659,264
- **Award type:** 5
- **Project period:** 2018-09-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10205011

## Citation

> US National Institutes of Health, RePORTER application 10205011, ENIGMA- Addiction: Pooling of Existing Datasets to Identify Brain and Genetic Correlates of Addiction (5R01DA047119-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10205011. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*