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Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction
- Karlsson Linnér, Richard;
- Mallard, Travis T;
- Barr, Peter B;
- Sanchez-Roige, Sandra;
- Madole, James W;
- Driver, Morgan N;
- Poore, Holly E;
- de Vlaming, Ronald;
- Grotzinger, Andrew D;
- Tielbeek, Jorim J;
- Johnson, Emma C;
- Liu, Mengzhen;
- Rosenthal, Sara Brin;
- Ideker, Trey;
- Zhou, Hang;
- Kember, Rachel L;
- Pasman, Joëlle A;
- Verweij, Karin JH;
- Liu, Dajiang J;
- Vrieze, Scott;
- Kranzler, Henry R;
- Gelernter, Joel;
- Harris, Kathleen Mullan;
- Tucker-Drob, Elliot M;
- Waldman, Irwin D;
- Palmer, Abraham A;
- Harden, K Paige;
- Koellinger, Philipp D;
- Dick, Danielle M
- et al.
Published Web Location
https://doi.org/10.1038/s41593-021-00908-3Abstract
Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.
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