ArticleAddiction biology2023
A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders.
Article in Addiction biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 18 citations in OpenAlex.
- Genome-wide association study of cocaine self-administration behavior in Heterogeneous Stock rats.Nature communications · 2026Article
- Are polygenic scores for psychiatric and substance use outcomes "ready" for clinical application? Current state and next steps.Psychiatric genetics · 2026Review
- Genome-wide association studies of lifetime and frequency of cannabis use in 131,895 individuals.Molecular psychiatry · 2026Article
- Substance use disorders exhibit unique and disorder specific genetic associations with externalizing and internalizing psychopathology.medRxiv : the preprint server for health sciences · 2026Article
- Multivariate genetic analyses of 2.2 million individuals reveal broad and substance-specific pathways of addiction risk.Nature. Mental health · 2026Article
- Youth Correlates of Genetic Liability to Substance Use Disorders.medRxiv : the preprint server for health sciences · 2025Article
- The broad structure of psychopathology in the All of Us Research Program.Psychological medicine · 2025Article
- Multivariate genetic of 2.2 million individuals demonstrate genetic influences on substance use disorders operate via behavioral disinhibition and substance-specific risk.medRxiv : the preprint server for health sciences · 2025Article
- Drinking motives and alcohol sensitivity mediate multidimensional genetic influences on alcohol use behaviors.Alcohol, clinical & experimental research · 2025Article
- Investigating Trivariate Associations Between Risky Sexual Behavior, Internalizing Problems, and Externalizing Problems: A Twin Study.Behavior genetics · 2024Article
- Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling.Behavior genetics · 2024Article
- Executive Function as an Underlying Mechanism of Alcohol Use, Aggression, and ADHD.medRxiv : the preprint server for health sciences · 2024Article
- Generalized genetic liability to substance use disorders.The Journal of clinical investigation · 2024Review
- Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study.Molecular psychiatry · 2024Article
- Genetic and shared environmental factors explain the association between adolescent polysubstance use and high school noncompletion.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2024Article
- The neurobiology of stress: Vulnerability, resilience, and major depression.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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Authors and funding
9 authors at 8 institutions in 1 country.
Funding
Abstract
Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (r
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