Genetic imaging consortium for addiction medicine: From neuroimaging to genes.
- Mackey, Scott;
- Kan, Kees-Jan;
- Chaarani, Bader;
- Alia-Klein, Nelly;
- Batalla, Albert;
- Brooks, Samantha;
- Cousijn, Janna;
- Dagher, Alain;
- de Ruiter, Michiel;
- Desrivieres, Sylvane;
- Feldstein Ewing, Sarah W;
- Goldstein, Rita Z;
- Goudriaan, Anna E;
- Heitzeg, Mary M;
- Hutchison, Kent;
- Li, Chiang-Shan R;
- London, Edythe D;
- Lorenzetti, Valentina;
- Luijten, Maartje;
- Martin-Santos, Rocio;
- Morales, Angelica M;
- Paulus, Martin P;
- Paus, Tomas;
- Pearlson, Godfrey;
- Schluter, Renée;
- Momenan, Reza;
- Schmaal, Lianne;
- Schumann, Gunter;
- Sinha, Rajita;
- Sjoerds, Zsuzsika;
- Stein, Dan J;
- Stein, Elliot A;
- Solowij, Nadia;
- Tapert, Susan;
- Uhlmann, Anne;
- Veltman, Dick;
- van Holst, Ruth;
- Walter, Henrik;
- Wright, Margaret J;
- Yucel, Murat;
- Yurgelun-Todd, Deborah;
- Hibar, Derrek P;
- Jahanshad, Neda;
- Thompson, Paul M;
- Glahn, David C;
- Garavan, Hugh;
- Conrod, Patricia
- et al.
Published Web Location
https://pubmed.ncbi.nlm.nih.gov/26822360/Abstract
Since the sample size of a typical neuroimaging study lacks sufficient statistical power to explore unknown genomic associations with brain phenotypes, several international genetic imaging consortia have been organized in recent years to pool data across sites. The challenges and achievements of these consortia are considered here with the goal of leveraging these resources to study addiction. The authors of this review have joined together to form an Addiction working group within the framework of the ENIGMA project, a meta-analytic approach to multisite genetic imaging data. Collectively, the Addiction working group possesses neuroimaging and genomic data obtained from over 10,000 subjects. The deadline for contributing data to the first round of analyses occurred at the beginning of May 2015. The studies performed on this data should significantly impact our understanding of the genetic and neurobiological basis of addiction.
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