Genetic liability to substance use disorders can be parsed into loci conferring general and substance-specific addiction risk. We report a multivariate genome-wide association study that disaggregates general and substance-specific loci for problematic alcohol use, problematic tobacco use, and cannabis and opioid use disorders in a sample of 1,025,550 individuals of European and 92,630 individuals of African descent. Nineteen loci were genome-wide significant for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries PDE4B was significant (among others), suggesting dopamine regulation as a cross-trait vulnerability. The addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into the genetic architecture of general and substance-specific use disorder risk that may be leveraged as treatment targets.

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 modelling to genomewide 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 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.The MVP summary statistics were obtained via an approved dbGaP application (phs001672.v4.p1). The authors thank Million Veteran Program (MVP) staff, researchers, and volunteers, who have contributed to MVP, and especially participants who previously served their country in the military and now generously agreed to enroll in the study. (For details, see https://www.research.va.gov/mvp/ and Gaziano, J.M. et al. Million Veteran Program: A megabiobank to study genetic influences on health and disease. J Clin Epidemiol 70, 214-23 (2016)). This research is based on data from the Million Veteran Program, Office of Research and Development, Veterans Health Administration, and was supported by the Veterans Administration (VA) Cooperative Studies Program (CSP) award #G002. This study included summary statistics of a genetic study on cannabis use (Pasman et al, 2018 Nature Neuroscience). We would like to acknowledge all participating groups of the International Cannabis Consortium, and in particular the members of the working group including Joelle Pasman, Karin Verweij, Nathan Gillespie, Eske Derks, and Jacqueline Vink. Pasman et al, (2018) included data from the UK Biobank resource under application numbers 9905, 16406 and 25331.

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci from published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent singlenucleotide polymorphisms were genome-wide significant (P < 5 × 10 -8 ) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis and 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.The lives lost, impacts on individuals and families, and socioeconomic costs attributable to substance use reflect a growing public health crisis 1 . For example, in the United States, 13.5% of deaths among young adults 2 are attributable to alcohol, smoking is the leading risk factor for mortality in males 3 , and the odds of dying by opioid overdose are greater than those of dying in a motor vehicle crash 4 . Despite the large impact of substance use and substance use disorders 5 , there is limited knowledge of the molecular genetic underpinnings of addiction broadly.

Suicide-related behaviors are heterogeneous and transdiagnostic, and may demonstrate varying levels of genetic overlap with different substance use disorders (SUDs). We used linkage disequilibrium score regression, genomic structural equation models, and Mendelian randomization to examine the genetic relationships between several SUDs and suicide-related behaviors. Our analyses incorporated summary statistics from the largest genome-wide association studies (GWAS) of problematic alcohol use, the Fagerström test for nicotine dependence, cannabis use disorder, and opioid use disorder (Ns ranging from 46,213-435,563) and GWAS of ever selfharmed, suicide attempt, and suicide death (Ns ranging from 18,223-117,733). We also accounted for genetic liability to depression (N = 500,199) and risk tolerance (N = 315,894). Suicide-related behaviors were significantly genetically correlated with each other and each SUD, but there was little evidence of causal relationships between the traits. Simultaneously correlating a common SUD factor with each specific suicide indicator while controlling for depression and risk tolerance revealed significant, positive genetic correlations between the SUD factor and suicide-related behaviors (r g = 0.26-0.45, SE = 0.08-0.09). In the model, depression's association with suicide death (β = 0.42, SE = 0.06) was weaker compared to ever-self harmed and suicide attempt (β = 0.58, SE = 0.05 and β = 0.50, SE = 0.06, respectively). We identify a general level of genetic overlap between SUDs and suicide-related behaviors, which is independent of depression and risk tolerance. Additionally, our findings suggest that genetic and behavioral contributions to suicide death may somewhat differ from nonlethal suicide-related behaviors.

Background Early identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM‐5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD. Methods We studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM‐5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM‐IV alcohol dependence or DSM‐5 AUD and 1616 were alcohol‐exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first‐degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH−). PRS were derived from a meta‐analysis of a genome‐wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity. Results AUD cases had higher PRS than controls with PRS increasing as the number of DSM‐5 diagnostic criteria increased (p‐values ≤ 1.85E−05) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p‐value = 7.57E−08) and 1.86 (95% CI: 1.35 to 2.56, p‐value = 1.32E−04) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first‐degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM‐5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p‐values ≤6.7E−11). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p‐values ≤6.8E−10). Conclusions Both PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.