from Mackey et al., AJP 2019

The ENIGMA consortium 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.

We created the ENIGMA Addiction working group which now has access to datasets representing over 14,000 participants and we continue to grow in size. Genomic and neuromaging analyses on this unprecedented collection of data will produce important new insights into the neural and genetic basis of addiction. Building on our initial proof of concept funding (R21DA038381) and our recently funded R01 (R01DA047119), we are expanding the Addiction working group. An increased, quality-controlled and curated dataset will enable us 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 are also increasing 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 are also creating 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.

Projects Completed

Mega-analysis of grey matter volume in substance use disorder (Mackey/Garavan)

Sex-differences in grey matter in cocaine use disorder: a voxel-based morphometric study (Goldstein; Rachel Rabin)

Mapping subcortical surface morphometry across substance use: An ENIGMA addiction working group mega-analysis (Mackey/Garavan; Yann Chye)

Meta-analytic comparison substance use disorder with other psychiatric disorders (Conrod; Xavier Navarri)

Sex differences in the neuroanatomy of cannabis and alcohol use: cortical thickness and sub-cortical volume

(Lorenzetti; Gloria Rosetti)

Sex differences in the neuroanatomy of alcohol dependence: a focus on hippocampal subregions and amygdala nuclei  (Lorenzetti; Sally Grace)

Predicting alcohol dependence using brain structural measures (Mackey/Garavan; Sage Hahn)

White microstructure in stimulant dependence (Garavan/Mackey; Anne Uhlmann/Jonatan Ottino)

Substance use disorder related structural brain asymmetries (Mackey/Garavan; Zhipeng Cao)

Graph theoretical summary of structural covariance in substance dependence (Mackey/Garavan; Jonatan Ottino)

Current Projects

Sex differences in cortical thickness of cigarette smokers (London; Dara Ghahremani)

Sex differences in the neuroanatomy of cannabis and alcohol use: cortical thickness and subcortical volumetry 

(Lorenzetti; Eleonora Maggioni)

Combined and sex-specific volumetric variations observed in adults with alcohol and cannabis use disorders

(Conrod; Xavier Navarri)

Effects of substance use disorder on the functional connectivity of the ventral striatum (Sutherland/Laird)

White matter microstructure in substance dependence (Garavan/Mackey; Jonatan Ottino)

Using deep learning classification to highlight general markers of illicit substance use and specific of markers cannabis use (Conrod; Sean Spinney)

Cortical surface morphology across substance use: an ENIGMA addiction working group collaboration (Yucel; Yann Chye)

Cerebellar volumes in substance use disorders (Garza; Jalil Rasgado)

Bayesian adjustment of novel structural imaging datasets based on prior distributions generated from the ENIGMA Addiction consortium (Mackey/Garavan; Zhipeng Cao)

Adolescent neuroimaging phenotypes associated with Polygenic Risks Scores for adult substance use disorder (Mackey?Garavan; Renata Cupertino)

Neural correlates of polygenic risk for cannabis use and cannabis use disorder (Mackey/Garavan; Renata Cupertino)

Machine learning based biotyping in substance use disorder (Mackey/Garavan; Zhipeng Cao)

Network modeling of brain structure in substance use disorder (Kirchner; Foivos Georgiadis)

Investigating the independent and interactive effects of tobacco and cannabis use on brain morphology (Rabin; Zac Yeap)

Structural covariance network changes in alcohol dependence/abstinence (Lingford-Hughes; Leon Fonville)

Brain-age gap in substance dependence (Stein; Freda Scheffler)

Cue reactivity fMRI in substance use disorder (Ehktiari/Zilverstand; Anthony Juliano)

Multi-modal deep learning classifiers for AUD based on structural voxel-based morphometry and resting state fMRI phenotypes (Porjescz; Sivan Kinnreich)

Cocaine related structural differences assessed by COINSTAC (Calhoun; Kelly Rootes-Murdy)

Brain atlas of deep brain coordinates to enable neurostimulation therapy for patients with addictions (Villoslada; Ehsan Dadgar-Kiani)


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