Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction.
Richard Karlsson LinnérTravis T MallardPeter B BarrSandra Sanchez-RoigeJames W MadoleMorgan N DriverHolly E PooreRonald de VlamingAndrew D GrotzingerJorim J TielbeekEmma C JohnsonMengzhen LiuSara Brin RosenthalTrey IdekerHang ZhouRachel L KemberJoëlle A PasmanKarin J H VerweijDajiang J LiuScott I Vriezenull nullHenry R KranzlerJoshua C GrayKathleen Mullan HarrisElliot M Tucker-DrobIrwin D WaldmanAbraham A PalmerKathryn Paige HardenPhilipp D KoellingerDanielle M DickPublished in: Nature neuroscience (2021)
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.
Keyphrases
- genome wide
- dna methylation
- attention deficit hyperactivity disorder
- copy number
- healthcare
- genome wide association
- autism spectrum disorder
- mental health
- gene expression
- public health
- hiv infected
- antiretroviral therapy
- adipose tissue
- wastewater treatment
- electronic health record
- hiv aids
- blood brain barrier
- metabolic syndrome
- machine learning
- working memory
- multiple sclerosis
- health information
- skeletal muscle
- climate change
- genome wide association study
- bioinformatics analysis
- subarachnoid hemorrhage