학술논문
Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction
Document Type
article
Author
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
Source
Nature Neuroscience. 24(10)
Subject
Language
Abstract
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.