The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates

Abstract

Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modeling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance-specific Ns range: 82,707-435,563) while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk-taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk-taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for the genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology.

Fig. 1. Factor structure of 4 SUD GWAS.

A The model, loadings, and fit for a model that allowed all four SUD categories to load on a latent factor. A residual correlation between PAU and OUD was added to account for their assessment using electronic health records in the MVP cohort (models without residual correlations also fit well: Supplemental Fig. 1). Addiction-rf = The Addiction Risk-Factor. B The same model, but accounting for common substance use (ever smoke, ever use marijuana, and drinks per week) as covariates at the indicator level, i.e., the three substance use measures are exogenous to all indicators in this model and the model represents the residual associations after accounting for substance use. Both models provided an excellent fit to the data. Bold* represents significance at p < .05. Note that in panel B, the residual of CUD is zero; this model constraint was necessary, as the model produced a negative residual without the constraint. Note: If you want to recreate the correlation matrix from both panels, the model with residual correlations cannot recover the implied correlation between PAU and OUD without taking the square root of the residual variance, rather than the value of the residual variance itself.

Fig. 2. Genetic associations between The Addiction-Risk-Factor and behavioral traits.

Executive function, neuroticism, and risk-taking. A The model, fit, and regression pathways without accounting for common substance use. B Is the same model, but accounting for common substance use (ever smoke, ever use marijuana, and drinks per week) as covariates at the indicator level (regressed on all measured variables/GWAS). Bold* represents significance at p < .05.

Fig. 3. Genetic associations between The Addiction-Risk-Factor and latent psychopathology factors.

Compulsive disorders (F1; Tourette’s syndrome, obsessive-compulsive disorder, and eating disorders), Psychotic Disorders (F2; Major Depressive Disorder, Schizophrenia, and Bipolar Disorder), and neurodevelopmental dysfunction (F3; ADHD, Autism, and Major Depressive Disorder). A The model, fit, and regression pathways without accounting for common substance use (model was scaled by setting the Opioid Use Disorder loading to 1). B Is the same model, but accounting for common substance use (ever smoke, ever use marijuana, and drinks per week) as covariates at the indicator level (regressed on all measured variables/GWAS), i.e., the three substance use measures are exogenous to all indicators in this model and the model is the residual associations after accounting for substance use. Bold* represents significance at p < .05. Addiction-rf = The Addiction-Risk-Factor.