Genome-wide association study of cocaine dependence and related traits: FAM53B identified as a risk gene

Associations of childhood adversity and substance use disorder polygenic scores with disorder severity and diagnostic criteria

BACKGROUND

Genetic and environmental factors, including adverse childhood experiences (ACEs), contribute to substance use disorders (SUDs). However, the interactions between these factors are poorly understood.

METHODS

We examined associations between SUD polygenic scores (PGSs), ACEs, and the initiation of use and severity of alcohol (AUD), opioid use disorder (OUD), and cannabis use disorder (CanUD) in 10,275 individuals (43.5% female, 47.2% African-like ancestry [AFR], and 52.8% European-like ancestry [EUR]). ACEs and SUD severity were modeled as latent factors. We conducted logistic and linear regressions within ancestry groups to examine the associations of ACEs, PGS, and their interaction with substance use initiation and SUD severity.

RESULTS

All three SUD PGS were associated with ACEs in EUR individuals, indicating a gene-environment correlation. Among EUR individuals, only the CanUD PGS was associated with initiating use, whereas ACEs were associated with initiating use of all three substances in both ancestry groups. Additionally, a negative gene-by-environment interaction was identified for opioid initiation in EUR individuals. ACEs were associated with all three SUD severity latent factors in EUR individuals and with AUD and CanUD severity in AFR individuals. PGS were associated with AUD severity in both ancestry groups and with CanUD severity in AFR individuals. Gene-by-environment interactions were identified for AUD and CanUD severity among EUR individuals.

CONCLUSIONS

Findings highlight the roles of ACEs and polygenic risk in substance use initiation and SUD severity. Gene-by-environment interactions implicate ACEs as moderators of genetic susceptibility, reinforcing the importance of considering both genetic and environmental influences on SUD risk.

Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 22,668 individuals from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic overlap of psychiatric and psychosocial traits in 7659 individuals of European descent and epigenome-wide changes in 886 individuals of African, European, and Admixed-American descents. The LCA identified four latent classes related to SD comorbidities: AD + TD, CoD + TD, AD + CoD + OD + TD (i.e., polysubstance addiction, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD + TD, AD + TD, and PSU latent classes. AD + TD latent class was also associated with CpG sites located on ARID1B, NOTCH1, SERTAD4, and SIN3B, while additional epigenome-wide significant associations with CoD + TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1. We also observed shared polygenic score (PGS) associations for PSU, AD + TD, and CoD + TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD + TD-latent class (bipolar disorder-PGS). In conclusion, we identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Cell type-specific multi-omics analysis of cocaine use disorder in the human caudate nucleus

Structural and functional alterations in the brain's reward circuitry are present in cocaine use disorder (CocUD), but their molecular underpinnings remain unclear. To investigate these mechanisms, we performed single-nuclei multiome profiling on postmortem caudate nucleus tissue from six individuals with CocUD and eight controls. We profiled 30,030 nuclei, identifying 13 cell types including D1- and D2-medium spiny neurons (MSNs) and glial cells. We observed 1485 differentially regulated genes and 10,342 differentially accessible peaks, with alterations in MSNs and astrocytes related to neurotransmitter activity and synapse organization. Gene regulatory network analysis identified transcription factors including ZEB1 as exhibiting distinct CocUD-specific subclusters, activating downstream expression of ion- and calcium-channels in MSNs. Further, PDE10A emerged as a potential drug target, showing conserved effects in a rat model. This study highlights cell type-specific molecular alterations in CocUD and provides targets for further investigation, demonstrating the value of multi-omics approaches in addiction research.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Predicting Treatment-seeking Status for Alcohol Use Disorder Using Polygenic Scores and Machine Learning in a Deeply-Phenotyped Sample

Background

Few individuals with alcohol use disorder (AUD) receive treatment. Previous studies have shown drinking behavior, psychological problems, and substance dependence to predict treatment seeking. However, to date, no studies have incorporated polygenic scores (PGS), a measure of genetic risk for AUD.

Methods

Using the Yale-Penn sample, we identified 9,103 individuals diagnosed with DSM-IV AUD and indicated treatment-seeking status. We implemented a random forest (RF) model to predict treatment-seeking based on 91 clinically relevant phenotypes. We calculated AUD PGS for those with genetic data (African ancestry [AFR] n=3,192, European ancestry [EUR] n=3,553) and generated RF models for each ancestry group, first without and then with PGS. Lastly, we developed models stratified by age (< and ≥40 years old).

Results

66.6% reported treatment seeking (M age =40.0, 62.4% male). Across models, top predictors included years of alcohol use and related psychological problems, psychiatric diagnoses, and heart disease. In the models without PGS, we found 79.8% accuracy and 0.85 AUC for EUR and 75% and 0.78 for AFR; the addition of PGS did not substantially change these metrics. PGS was the 10 th most important predictor for EUR and 23 rd for AFR. In the age-stratified analysis, PGS ranked 8 th for <40 and 48 th for ≥40 in EUR ancestry, and it ranked 14 th for <40 and 24 th for ≥40 in the AFR sample.

Conclusion

Alcohol use, psychiatric issues, and comorbid medical disorders were predictors of treatment seeking. Incorporating PGS did not substantially alter performance, but was a more important predictor in younger individuals with AUD.

Highlights

While alcohol use problems are common, few individuals seek treatmentWe used machine learning in a deeply-phenotyped sample to predict treatment-seekingWe, for the first time, incorporated polygenic risk for alcohol use as a predictorAlcohol use variables, psychiatric issues, and medical problems were key predictors.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms that underlie the development and progression of AUD remains limited. Here, we investigated AUD-associated DNA methylation changes within and across 2 addiction-relevant brain regions, the nucleus accumbens and dorsolateral prefrontal cortex.

Methods

Illumina HumanMethylation EPIC array data from 119 decedents (61 cases, 58 controls) were analyzed using robust linear regression with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public annotation data and published genetic and epigenetic studies. We also tested for brain region-shared and brain region-specific associations using mixed-effects modeling and assessed implications of these results using public gene expression data from human brain.

Results

At a false discovery rate of ≤.05, we identified 105 unique AUD-associated CpGs (annotated to 120 genes) within and across brain regions. AUD-associated CpGs were enriched in histone marks that tag active promoters, and our strongest signals were specific to a single brain region. Some concordance was found between our results and those of earlier published alcohol use or dependence methylation studies. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors, some of which also overlapped with previous addiction-related methylation studies.

Conclusions

Our findings identify AUD-associated methylation signals and provide evidence of overlap with previous genetic and methylation studies. These signals may constitute predisposing genetic differences or robust methylation changes associated with AUD, although more work is needed to further disentangle the mechanisms that underlie these associations and their implications for AUD.

Epigenetic and Genetic Profiling of Comorbidity Patterns among Substance Dependence Diagnoses

Objective

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity patterns of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD).

Methods

A latent class analysis (LCA) was performed on 31,197 individuals (average age 42±11 years; 49% females) from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic burden of psychiatric and behavioral traits and epigenome-wide changes in three population groups.

Results

An LCA identified four latent classes related to SD comorbidities: AD+TD, CoD+TD, AD+CoD+OD+TD (i.e., polysubstance use, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD+TD, AD+TD, and PSU latent classes. AD+TD latent class was also associated with CpG sites located on ARID1B , NOTCH1 , SERTAD4, and SIN3B , while additional epigenome-wide significant associations with CoD+TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1 . We also observed shared polygenic score (PGS) associations for PSU, AD+TD, and CoD+TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD+TD-latent class (bipolar disorder-PGS).

Conclusions

We identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Association patterns of antisocial personality disorder across substance use disorders

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1660 individuals with ASPD and 6640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test ASPD with respect to the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs = 1.89 and 1.25), CanUD (ORs = 2.13 and 1.32), and TUD (ORs = 1.50 and 1.21) (ps < 0.003). Of the specific diagnostic criteria, the "hazardous use" criterion showed the strongest association with ASPD across the five SUDs investigated (from ORTUD = 1.88 to ORCanUD = 1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD "hazardous use" and CocUD "attempts to quit". Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR = 0.57, 95% confidence interval = 0.36-0.89) after controlling for interactive effects with sex. The current work provides novel insights into ASPD-SUD comorbidity, supporting the existence of different SUD patterns among individuals affected by ASPD.

Cell type-specific Multi-Omics Analysis of Cocaine Use Disorder in the Human Caudate Nucleus

Structural and functional alterations in the brain's reward circuitry are present in cocaine use disorder (CocUD), but their molecular underpinnings remain unclear. To investigate these mechanisms, we performed single-nuclei multiome profiling on postmortem caudate nucleus tissue from six individuals with CocUD and eight controls. We profiled 31,178 nuclei, identifying 13 cell types including D1- and D2-medium spiny neurons (MSNs) and glial cells. We observed 1,383 differentially regulated genes and 10,235 differentially accessible peaks, with alterations in MSNs and astrocytes related to neurotransmitter activity and synapse organization. Gene regulatory network analysis identified the transcription factor ZEB1 as exhibiting distinct CocUD-specific subclusters, activating downstream expression of ion- and calcium-channels in MSNs. Further, PDE10A emerged as a potential drug target, showing conserved effects in a rat model. This study highlights cell type-specific molecular alterations in CocUD and provides targets for further investigation, demonstrating the value of multi-omics approaches in addiction research.

Generalized genetic liability to substance use disorders

Lifetime and temporal co-occurrence of substance use disorders (SUDs) is common and compared with individual SUDs is characterized by greater severity, additional psychiatric comorbidities, and worse outcomes. Here, we review evidence for the role of generalized genetic liability to various SUDs. Coaggregation of SUDs has familial contributions, with twin studies suggesting a strong contribution of additive genetic influences undergirding use disorders for a variety of substances (including alcohol, nicotine, cannabis, and others). GWAS have documented similarly large genetic correlations between alcohol, cannabis, and opioid use disorders. Extending these findings, recent studies have identified multiple genomic loci that contribute to common risk for these SUDs and problematic tobacco use, implicating dopaminergic regulatory and neuronal development mechanisms in the pathophysiology of generalized SUD genetic liability, with certain signals demonstrating cross-species and translational validity. Overlap with genetic signals for other externalizing behaviors, while substantial, does not explain the entirety of the generalized genetic signal for SUD. Polygenic scores (PGS) derived from the generalized genetic liability to SUDs outperform PGS for individual SUDs in prediction of serious mental health and medical comorbidities. Going forward, it will be important to further elucidate the etiology of generalized SUD genetic liability by incorporating additional SUDs, evaluating clinical presentation across the lifespan, and increasing the granularity of investigation (e.g., specific transdiagnostic criteria) to ultimately improve the nosology, prevention, and treatment of SUDs.

METH exposure alters sperm DNA methylation in F0 mice and mPFC transcriptome in male F1 mice

RATIONALE

Methamphetamine (METH) exposure has toxicity in sperm epigenetic phenotype and increases the risk for developing addiction in their offspring. However, the underlying transgenerational mechanism remains unclear.

OBJECTIVES

The current study aims to investigate the profiles of sperm epigenetic modifications in male METH-exposed mice (F0) and medial prefrontal cortex (mPFC) transcriptome in their male first-generation offspring (F1).

METHODS

METH-related male F0 and F1 mice model was established to investigate the effects of paternal METH exposure on reproductive functions and sperm DNA methylation in F0 and mPFC transcriptomic profile in F1. During adulthood, F1 was subjected to a conditioned place preference (CPP) test to evaluate sensitivity to METH. The gene levels were verified with qPCR.

RESULTS

METH exposure obviously altered F0 sperms DNA methylated profile and male F1 mPFC transcriptomic profile, many of which being related to neuronal system and brain development. In METH-sired male F1, subthreshold dose of METH administration effectively elicited CPP, along with more mPFC activation. After qPCR verification, Sort1 and Shank2 were at higher levels in F0 sperm and F1 mPFC.

CONCLUSIONS

Our findings put new insights into paternal METH exposure-altered profiles of F0 sperm DNA methylation and male F1 mPFC transcriptomics. Several genes, such as Sort1 and Shank2, might be used as potential molecules for further research on the transgenerational vulnerability to drug addiction in offspring by paternal drug exposure.

Voltage-gated potassium channels control extended access cocaine seeking: a role for nucleus accumbens astrocytes

Dopaminergic signaling in the nucleus accumbens shell (NAc) regulates neuronal activity relevant to reward-related learning, including cocaine-associated behaviors. Although astrocytes respond to dopamine and cocaine with structural changes, the impact of dopamine and cocaine on astrocyte functional plasticity has not been widely studied. Specifically, behavioral implications of voltage-gated channel activity in the canonically non-excitable astrocytes are not known. We characterized potassium channel function in NAc astrocytes following exposure to exogenous dopamine or cocaine self-administration training under short (2 h/day) and extended (6 h/day) access schedules. Electrophysiological, Ca2+ imaging, mRNA, and mass spectrometry tools were used for molecular characterization. Behavioral effects were examined after NAc-targeted microinjections of channel antagonists and astroglial toxins. Exogenous dopamine increased activity of currents mediated by voltage-gated (Kv7) channels in NAc astrocytes. This was associated with a ~5-fold increase in expression of Kcnq2 transcript level in homogenized NAc micropunches. Matrix-assisted laser desorption/ionization mass spectrometry revealed increased NAc dopamine levels in extended access, relative to short access, rats. Kv7 inhibition selectively increased frequency and amplitude of astrocyte intracellular Ca2+ transients in NAc of extended access rats. Inhibition of Kv7 channels in the NAc attenuated cocaine-seeking in extended access rats only, an effect that was occluded by microinjection of the astrocyte metabolic poison, fluorocitrate. These results suggest that voltage-gated K+ channel signaling in NAc astrocytes is behaviorally relevant, support Kv7-mediated regulation of astrocyte Ca2+ signals, and propose novel mechanisms of neuroglial interactions relevant to drug use.

Nicotine Motivated Behavior in C. elegans

To maximize the advantages offered by Caenorhabditis elegans as a high-throughput (HTP) model for nicotine dependence studies, utilizing its well-defined neuroconnectome as a robust platform, and to unravel the genetic basis of nicotine-motivated behaviors, we established the nicotine conditioned cue preference (CCP) paradigm. Nicotine CCP enables the assessment of nicotine preference and seeking, revealing a parallel to fundamental aspects of nicotine-dependent behaviors observed in mammals. We demonstrated that nicotine-elicited cue preference in worms is mediated by nicotinic acetylcholine receptors and requires dopamine for CCP development. Subsequently, we pinpointed nAChR subunits associated with nicotine preference and validated human GWAS candidates linked to nicotine dependence involved in nAChRs. Functional validation involves assessing the loss-of-function strain of the CACNA2D3 ortholog and the knock-out (KO) strain of the CACNA2D2 ortholog, closely related to CACNA2D3 and sharing human smoking phenotypes. Our orthogonal approach substantiates the functional conservation of the α2δ subunit of the calcium channel in nicotine-motivated behavior. Nicotine CCP in C. elegans serves as a potent affirmation of the cross-species functional relevance of GWAS candidate genes involved in nicotine seeking associated with tobacco abuse, providing a streamlined yet comprehensive system for investigating intricate behavioral paradigms within a simplified and reliable framework.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and medical traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and medical traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and medical traits were calculated in European-ancestry (EUR; n=5,691) participants and, when discovery datasets were available, for African-ancestry (AFR; n=4,918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGS MDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGS BMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and medical traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC).

Methods

Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data.

Results

At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations.

Conclusions

Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value

Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.

An approach for prioritizing candidate genes from RNA-seq using preclinical cocaine self-administration datasets as a test case

RNA-sequencing (RNA-seq) technology has led to a surge of neuroscience research using animal models to probe the complex molecular mechanisms underlying brain function and behavior, including substance use disorders. However, findings from rodent studies often fail to be translated into clinical treatments. Here, we developed a novel pipeline for narrowing candidate genes from preclinical studies by translational potential and demonstrated its utility in 2 RNA-seq studies of rodent self-administration. This pipeline uses evolutionary conservation and preferential expression of genes across brain tissues to prioritize candidate genes, increasing the translational utility of RNA-seq in model organisms. Initially, we demonstrate the utility of our prioritization pipeline using an uncorrected P-value. However, we found no differentially expressed genes in either dataset after correcting for multiple testing with false discovery rate (FDR < 0.05 or <0.1). This is likely due to low statistical power that is common across rodent behavioral studies, and, therefore, we additionally illustrate the use of our pipeline on a third dataset with differentially expressed genes corrected for multiple testing (FDR < 0.05). We also advocate for improved RNA-seq data collection, statistical testing, and metadata reporting that will bolster the field's ability to identify reliable candidate genes and improve the translational value of bioinformatics in rodent research.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Association Patterns of Antisocial Personality Disorder across Substance Use Disorders

There is a high prevalence of antisocial personality disorder (ASPD) in individuals affected by substance use disorders (SUD). However, there is limited information on the specific patterns of association of ASPD with SUD severity and specific SUD diagnostic criteria. We investigated the association of alcohol, cannabis, cocaine, opioid, and tobacco use disorders (AUD, CanUD, CocUD, OUD, and TUD, respectively) in 1,660 individuals with ASPD and 6,640 controls matched by sex (24% female), age, and racial/ethnic background in a sample ascertained for addiction-related traits. Generalized linear regressions were used to test the association of ASPD with the five DSM-5 SUD diagnoses, their severity (i.e., mild, moderate, severe), and their individual diagnostic criteria. We found that ASPD is associated with the diagnosis and severity of AUD (Odds Ratio, ORs=1.89 and 1.25), CanUD (ORs=2.13 and 1.32), and TUD (ORs=1.50 and 1.21) ( ps <.003). Of the specific diagnostic criteria, the "hazardous use" criterion showed the strongest association with ASPD across the five SUDs investigated (from OR TUD =1.88 to OR CanUD =1.37). However, when criteria of different SUDs were included in the same model, ASPD was independently associated only with TUD "hazardous use" and CocUD "attempts to quit". Attempting to quit cocaine was inversely related to the presence of ASPD and remained significant (OR=0.57, 95% confidence interval = 0.36-0.89) after controlling for interactive effects with sex. The current work provides novel insights into how different SUDs, their severity, and their diagnostic criteria associate with ASPD, potentially furthering our understanding of the impact of polysubstance addiction on mental health.

Genetic pathways regulating the longitudinal acquisition of cocaine self-administration in a panel of inbred and recombinant inbred mice

To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct. We maximize power to map loci for cocaine intake by using a linear mixed model to account for this longitudinal phenotype while correcting for population structure. A total of 15 unique significant loci are identified in the genome-wide association study. A transcriptome-wide association study highlights the Trpv2 ion channel as a key locus for cocaine self-administration as well as identifying 17 additional genes, including Arhgef26, Slc18b1, and Slco5a1. We find numerous instances where alternate splice site selection or RNA editing altered transcript abundance. Our work emphasizes the importance of Trpv2, an ionotropic cannabinoid receptor, for the response to cocaine.

Polysubstance addiction patterns among 7,989 individuals with cocaine use disorder

To characterize polysubstance addiction (PSA) patterns of cocaine use disorder (CoUD), we performed a latent class analysis (LCA) in 7,989 participants with a lifetime DSM-5 diagnosis of CoUD. This analysis identified three PSA subgroups among CoUD participants (i.e., low, 17%; intermediate, 38%; high, 45%). While these subgroups varied by age, sex, and racial-ethnic distribution (p < 0.001), there was no difference with respect to education or income (p > 0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR = 21.96 vs. 6.39, difference-p = 8.08✕10-6), agoraphobia (OR = 4.58 vs. 2.05, difference-p = 7.04✕10-4), mixed bipolar episode (OR = 10.36 vs. 2.61, difference-p = 7.04✕10-4), posttraumatic stress disorder (OR = 11.54 vs. 5.86, difference-p = 2.67✕10-4), antidepressant medication use (OR = 13.49 vs. 8.02, difference-p = 1.42✕10-4), and sexually transmitted diseases (OR = 5.92 vs. 3.38, difference-p = 1.81✕10-5) than the low-PSA CoUD subgroup. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Phenome-wide Association Analysis of Substance Use Disorders in a Deeply Phenotyped Sample

BACKGROUND

Substance use disorders (SUDs) are associated with a variety of co-occurring psychiatric disorders and other SUDs, which partly reflects genetic pleiotropy. Polygenic risk scores (PRSs) and phenome-wide association studies are useful in evaluating pleiotropic effects. However, the comparatively low prevalence of SUDs in population samples and the lack of detailed information available in electronic health records limit these data sets' informativeness for such analyses.

METHODS

We used the deeply phenotyped Yale-Penn sample (n = 10,610 with genetic data; 46.3% African ancestry, 53.7% European ancestry) to examine pleiotropy for 4 major substance-related traits: alcohol use disorder, opioid use disorder, smoking initiation, and lifetime cannabis use. The sample includes both affected and control subjects interviewed using the Semi-Structured Assessment for Drug Dependence and Alcoholism, a comprehensive psychiatric interview.

RESULTS

In African ancestry individuals, PRS for alcohol use disorder, and in European individuals, PRS for alcohol use disorder, opioid use disorder, and smoking initiation were associated with their respective primary DSM diagnoses. These PRSs were also associated with additional phenotypes involving the same substance. Phenome-wide association study analyses of PRS in European individuals identified associations across multiple phenotypic domains, including phenotypes not commonly assessed in phenome-wide association study analyses, such as family environment and early childhood experiences.

CONCLUSIONS

Smaller, deeply phenotyped samples can complement large biobank genetic studies with limited phenotyping by providing greater phenotypic granularity. These efforts allow associations to be identified between specific features of disorders and genetic liability for SUDs, which help to inform our understanding of the pleiotropic pathways underlying them.

Genotype-by-diagnosis interaction influences self-control in human cocaine addiction

Not everyone who uses drugs loses control over their intake, which is a hallmark of addiction. Although familial risk studies suggest significant addiction heritability, the genetic basis of vulnerability to drug addiction remains largely unknown. In the present study, we investigate the relationship between self-control, cocaine use, and the rs36024 single nucleotide polymorphism of the noradrenaline transporter gene (SLC6A2). We hypothesize that C-allele-carrying adults show impaired self-control, as measured by the stop-signal task and demonstrated previously in adolescents, and further exacerbated by chronic cocaine use. Patients with cocaine use disorder (CUD, n = 79) and healthy unrelated participants with no history of drug abuse (n = 54) completed the stop-signal task. All participants were genotyped for rs36024 allelic variants (CC/TT homozygotes, CT heterozygotes). We measured mean stop-signal reaction time, reflecting the ability to inhibit ongoing motor responses, reaction times to go stimuli, and the proportion of successful stops. CUD patients showed prolonged stop-signal reaction time, however, there was no main effect of rs36024 genotype. Importantly, there was a significant genotype-by-diagnosis interaction such that CUD patients with CC genotype had longer stop-signal reaction time and fewer successful stops compared with CC healthy controls and TT CUD patients. CT CUD patients showed an intermediate performance. Self-control deficits were associated with cocaine use disorder diagnosis, which interacts with the noradrenaline transporter rs36024 polymorphism. Our findings suggest that rs36024 may represent a potential genetic vulnerability marker, which facilitates the transition from first cocaine use to addiction by weakening the inhibitory control over behavior.

Polysubstance addiction and psychiatric, somatic comorbidities among 7,989 individuals with cocaine use disorder: a latent class analysis

Aims

We performed a latent class analysis (LCA) in a sample ascertained for addiction phenotypes to investigate cocaine use disorder (CoUD) subgroups related to polysubstance addiction (PSA) patterns and characterized their differences with respect to psychiatric and somatic comorbidities.

Design

Cross-sectional study.

Setting

United States.

Participants

Adult participants aged 18-76, 39% female, 47% African American, 36% European American with a lifetime DSM-5 diagnosis of CoUD (N=7,989) enrolled in the Yale-Penn cohort. The control group included 2,952 Yale-Penn participants who did not meet for alcohol, cannabis, cocaine, opioid, or tobacco use disorders.

Measurements

Psychiatric disorders and related traits were assessed via the Semi-structured Assessment for Drug Dependence and Alcoholism. These features included substance use disorders (SUD), family history of substance use, sociodemographic information, traumatic events, suicidal behaviors, psychopathology, and medical history. LCA was conducted using diagnoses and diagnostic criteria of alcohol, cannabis, opioid, and tobacco use disorders.

Findings

Our LCA identified three subgroups of PSA (i.e., low, 17%; intermediate, 38%; high, 45%) among 7,989 CoUD participants. While these subgroups varied by age, sex, and racial-ethnic distribution (p<0.001), there was no difference on education or income (p>0.05). After accounting for sex, age, and race-ethnicity, the CoUD subgroup with high PSA had higher odds of antisocial personality disorder (OR=21.96 vs. 6.39, difference-p=8.08×10 -6 ), agoraphobia (OR=4.58 vs. 2.05, difference-p=7.04×10 -4 ), mixed bipolar episode (OR=10.36 vs. 2.61, difference-p=7.04×10 -4 ), posttraumatic stress disorder (OR=11.54 vs. 5.86, difference-p=2.67×10 -4 ), antidepressant medication use (OR=13.49 vs. 8.02, difference-p=1.42×10 -4 ), and sexually transmitted diseases (OR=5.92 vs. 3.38, difference-p=1.81×10 -5 ) than the low-PSA CoUD subgroup.

Conclusions

We found different patterns of PSA in association with psychiatric and somatic comorbidities among CoUD cases within the Yale-Penn cohort. These findings underscore the importance of modeling PSA severity and comorbidities when examining the clinical, molecular, and neuroimaging correlates of CoUD.

Convergent abnormalities in striatal gene networks in human cocaine use disorder and mouse cocaine administration models

Cocaine use disorder (CUD) is an intractable syndrome, and rising overdose death rates represent a substantial public health crisis that exacts tremendous personal and financial costs on patients and society. Sharp increases in cocaine use drive the urgent need for better mechanistic insight into this chronic relapsing brain disorder that currently lacks effective treatment options. To investigate the transcriptomic changes involved, we conducted RNA sequencing on two striatal brain regions that are heavily implicated in CUD, the nucleus accumbens and caudate nucleus, from men suffering from CUD and matched controls. Weighted gene coexpression analyses identified CUD-specific gene networks enriched in ionotropic receptors and linked to lowered neuroinflammation, contrasting the proinflammatory responses found in opioid use disorder. Integration of comprehensive transcriptomic datasets from mouse cocaine self-administration models revealed evolutionarily conserved gene networks in CUD that implicate especially D1 medium spiny neurons as drivers of cocaine-induced plasticity.

The collaborative cross strains and their founders vary widely in cocaine-induced behavioral sensitization

Cocaine use and overdose deaths attributed to cocaine have increased significantly in the United States in the last 10 years. Despite the prevalence of cocaine use disorder (CUD) and the personal and societal problems it presents, there are currently no approved pharmaceutical treatments. The absence of treatment options is due, in part, to our lack of knowledge about the etiology of CUDs. There is ample evidence that genetics plays a role in increasing CUD risk but thus far, very few risk genes have been identified in human studies. Genetic studies in mice have been extremely useful for identifying genetic loci and genes, but have been limited to very few genetic backgrounds, leaving substantial phenotypic, and genetic diversity unexplored. Herein we report the measurement of cocaine-induced behavioral sensitization using a 19-day protocol that captures baseline locomotor activity, initial locomotor response to an acute exposure to cocaine and locomotor sensitization across 5 exposures to the drug. These behaviors were measured in 51 genetically diverse Collaborative Cross (CC) strains along with their inbred founder strains. The CC was generated by crossing eight genetically diverse inbred strains such that each inbred CC strain has genetic contributions from each of the founder strains. Inbred CC mice are infinitely reproducible and provide a stable, yet diverse genetic platform on which to study the genetic architecture and genetic correlations among phenotypes. We have identified significant differences in cocaine locomotor sensitivity and behavioral sensitization across the panel of CC strains and their founders. We have established relationships among cocaine sensitization behaviors and identified extreme responding strains that can be used in future studies aimed at understanding the genetic, biological, and pharmacological mechanisms that drive addiction-related behaviors. Finally, we have determined that these behaviors exhibit relatively robust heritability making them amenable to future genetic mapping studies to identify addiction risk genes and genetic pathways that can be studied as potential targets for the development of novel therapeutics.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies

BACKGROUND AND AIMS

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs.

METHODS

Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10^-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database.

RESULTS

Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P < 1 × 10^-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value < 0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD.

CONCLUSIONS

This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

Biomarkers of Relapse in Cocaine Use Disorder: A Narrative Review

Introduction: Cocaine use disorder is a chronic disease with severe consequences and a high relapse rate. There is a critical need to explore the factors influencing relapse in order to achieve more efficient treatment outcomes. Furthermore, there is a great need for easy-to-measure, repeatable, and valid biomarkers that can predict treatment response or relapse. Methods: We reviewed the available literature on the Pubmed database concerning the biomarkers associated with relapse in CUD, including central nervous system-derived, genetic, immune, oxidative stress, and “other” biomarkers. Results: Fifty-one articles were included in our analysis. Twenty-five imaging brain anatomic and function assessment studies, mostly using fMRI, examined the role of several structures such as the striatum activity in abstinence prediction. There were fewer studies assessing the use of neuropsychological factors, neurotrophins, or genetic/genomic factors, immune system, or oxidative stress measures to predict abstinence. Conclusion: Several biomarkers have been shown to have predictive value. Prospective studies using combined multimodal assessments are now warranted.

A Systematic Review of Genetic Polymorphisms Associated with Bipolar Disorder Comorbid to Substance Abuse

It is currently unknown which genetic polymorphisms are involved in substance use disorder (SUD) comorbid with bipolar disorder (BD). The research on polymorphisms in BD comorbid with SUD (BD + SUD) is summarized in this systematic review. We looked for case-control studies that genetically compared adults and adolescents with BD and SUD, healthy controls, and BD without SUD. PRISMA was used to create our protocol, which is PROSPERO-registered (identification: CRD4221270818). The following bibliographic databases were searched indefinitely until December 2021 to identify potentially relevant articles: PubMed, PsycINFO, Scopus, and Web of Science. This systematic review, after the qualitative analysis of the study selection, included 17 eligible articles. In the selected studies, 66 polymorphisms in 29 genes were investigated. The present work delivers a group of potentially valuable genetic polymorphisms associated with BD + SUD: rs11600996 (ARNTL), rs228642/rs228682/rs2640909 (PER3), PONQ192R (PON1), rs945032 (BDKRB2), rs1131339 (NR4A3), and rs6971 (TSPO). It is important to note that none of those findings have been confirmed by two or more studies; thus, we believe that all the polymorphisms identified in this review require additional evidence to be confirmed.

Identifying alcohol misuse biotypes from neural connectivity markers and concurrent genetic associations

Alcohol use behaviors are highly heterogeneous, posing significant challenges to etiologic research of alcohol use disorder (AUD). Magnetic resonance imaging (MRI) provides intermediate endophenotypes in characterizing problem alcohol use and assessing the genetic architecture of addictive behavior. We used connectivity features derived from resting state functional MRI to subtype alcohol misuse (AM) behavior. With a machine learning pipeline of feature selection, dimension reduction, clustering, and classification we identified three AM biotypes-mild, comorbid, and moderate AM biotypes (MIA, COA, and MOA)-from a Human Connectome Project (HCP) discovery sample (194 drinkers). The three groups and controls (397 non-drinkers) demonstrated significant differences in alcohol use frequency during the heaviest 12-month drinking period (MOA > MIA; COA > non-drinkers) and were distinguished by connectivity features involving the frontal, parietal, subcortical and default mode networks. Further, COA relative to MIA, MOA and controls endorsed significantly higher scores in antisocial personality. A genetic association study identified that an alcohol use and antisocial behavior related variant rs16930842 from LINC01414 was significantly associated with COA. Using a replication HCP sample (28 drinkers and 46 non-drinkers), we found that subtyping helped in classifying AM from controls (area under the curve or AUC = 0.70, P < 0.005) in comparison to classifiers without subtyping (AUC = 0.60, not significant) and successfully reproduced the genetic association. Together, the results suggest functional connectivities as important features in classifying AM subgroups and the utility of reducing the heterogeneity in connectivity features among AM subgroups in advancing the research of etiological neural markers of AUD.

Cocaine-Induced Locomotor Activation Differs Across Inbred Mouse Substrains

Cocaine use disorders (CUD) are devastating for affected individuals and impose a significant societal burden, but there are currently no FDA-approved therapies. The development of novel and effective treatments has been hindered by substantial gaps in our knowledge about the etiology of these disorders. The risk for developing a CUD is influenced by genetics, the environment and complex interactions between the two. Identifying specific genes and environmental risk factors that increase CUD risk would provide an avenue for the development of novel treatments. Rodent models of addiction-relevant behaviors have been a valuable tool for studying the genetics of behavioral responses to drugs of abuse. Traditional genetic mapping using genetically and phenotypically divergent inbred mice has been successful in identifying numerous chromosomal regions that influence addiction-relevant behaviors, but these strategies rarely result in identification of the causal gene or genetic variant. To overcome this challenge, reduced complexity crosses (RCC) between closely related inbred mouse strains have been proposed as a method for rapidly identifying and validating functional variants. The RCC approach is dependent on identifying phenotypic differences between substrains. To date, however, the study of addiction-relevant behaviors has been limited to very few sets of substrains, mostly comprising the C57BL/6 lineage. The present study expands upon the current literature to assess cocaine-induced locomotor activation in 20 inbred mouse substrains representing six inbred strain lineages (A/J, BALB/c, FVB/N, C3H/He, DBA/2 and NOD) that were either bred in-house or supplied directly by a commercial vendor. To our knowledge, we are the first to identify significant differences in cocaine-induced locomotor response in several of these inbred substrains. The identification of substrain differences allows for the initiation of RCC populations to more rapidly identify specific genetic variants associated with acute cocaine response. The observation of behavioral profiles that differ between mice generated in-house and those that are vendor-supplied also presents an opportunity to investigate the influence of environmental factors on cocaine-induced locomotor activity.

Extreme phenotypic diversity in operant response to intravenous cocaine or saline infusion in the hybrid mouse diversity panel

Cocaine self-administration is a complexly determined trait, with a substantial proportion of individual differences being determined by genetic variation. However, the relevant genetic variants that drive heritable differences in cocaine use remain undiscovered. Cocaine intravenous self-administration (IVSA) procedures in laboratory animals provide opportunities to prospectively investigate neurogenetic influences on the acquisition of voluntary cocaine use. Here, we provide information on cocaine (or saline-as a control) IVSA in 84 members of the hybrid mouse diversity panel (HMDP), an array of genetically distinct classical or recombinant inbred strains. We found cocaine IVSA to be substantially heritable in this population, with strain-level intake ranging for near 0 to >25 mg/kg/session. Though saline IVSA was also found to be heritable, a modest genetic correlation between cocaine and saline IVSA indicates that operant responding for the cocaine reinforcer was influenced, at least in part, by unique genetic variants. Genome-wide association studies (GWAS) of infusions earned in cocaine and saline groups revealed significant quantitative trait loci (QTL) on Chromosomes 3 and 14 for cocaine, but not saline, IVSA. Positional candidates were further prioritized through use of bulk RNA sequencing data that revealed genes with cis-eQTL and genetic correlation to number of infusions. Additionally, these data identify reference strains with extreme cocaine IVSA phenotypes, revealing them as polygenic models of risk and resilience to cocaine reinforcement. This work is part of an ongoing effort to characterize genetic variation that moderates cocaine IVSA that may, in turn, provide a more comprehensive understanding of cocaine risk genetics and neurobiology.

Development and validation of the Reward Deficiency Syndrome Questionnaire (RDSQ-29)

BACKGROUND

The reward deficiency syndrome (RDS) integrates psychological, neurological, and genetic factors of addictive, impulsive, and compulsive behaviors. However, to date, no instrument has been validated to assess the RDS construct.

AIMS

The present study developed and tested a tool to assess RDS.

METHODS

Data were collected on two college and university samples. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed on Sample 1 (N = 1726), and confirmatory analysis was conducted on an independent sample (N = 253). Impulsivity and sensation-seeking were assessed.

RESULTS

Based on EFAs, a 29-item Reward Deficiency Syndrome Questionnaire (RDSQ-29) was developed, containing four subscales (lack of sexual satisfaction, activity, social concerns, and risk-seeking behavior). CFA indicated good fit (comparative fit index (CFI) = 0.941; Tucker-Lewis index (TLI) = 0.933; root mean square error of approximation (RMSEA) = 0.068). Construct validity analysis showed strong relationship between sensation-seeking and the RDS scale.

CONCLUSION

The RDSQ-29 is an adequate scale assessing psychological and behavioral aspects of RDS. The RDSQ-29 assesses psychological and behavioral characteristics that may contribute to addictions generally.

Using Mendelian randomization to explore the gateway hypothesis: possible causal effects of smoking initiation and alcohol consumption on substance use outcomes

BACKGROUND AND AIMS

Initial use of drugs such as tobacco and alcohol may lead to subsequent more problematic drug use-the 'gateway' hypothesis. However, observed associations may be due to a shared underlying risk factor, such as trait impulsivity. We used bidirectional Mendelian randomization (MR) to test the gateway hypothesis.

DESIGN

Our main method was inverse-variance weighted (IVW) MR, with other methods included as sensitivity analyses (where consistent results across methods would raise confidence in our primary results). MR is a genetic instrumental variable approach used to support stronger causal inference in observational studies.

SETTING AND PARTICIPANTS

Genome-wide association summary data among European ancestry individuals for smoking initiation, alcoholic drinks per week, cannabis use and dependence, cocaine and opioid dependence (n = 1749-1 232 091).

MEASUREMENTS

Genetic variants for exposure.

FINDINGS

We found evidence of causal effects from smoking initiation to increased drinks per week [(IVW): β = 0.06; 95% confidence interval (CI) = 0.03-0.09; P = 9.44 × 10-06 ], cannabis use [IVW: odds ratio (OR) = 1.34; 95% CI = 1.24-1.44; P = 1.95 × 10-14 ] and cannabis dependence (IVW: OR = 1.68; 95% CI = 1.12-2.51; P = 0.01). We also found evidence of an effect of cannabis use on the increased likelihood of smoking initiation (IVW: OR = 1.39; 95% CI = 1.08-1.80; P = 0.01). We did not find evidence of an effect of drinks per week on other substance use outcomes, except weak evidence of an effect on cannabis use (IVW: OR = 0.55; 95% CI = 0.16-1.93; P-value = 0.35). We found weak evidence of an effect of opioid dependence on increased drinks per week (IVW: β = 0.002; 95% CI = 0.0005-0.003; P = 8.61 × 10-03 ).

CONCLUSIONS

Bidirectional Mendelian randomization testing of the gateway hypothesis reveals that smoking initiation may lead to increased alcohol consumption, cannabis use and cannabis dependence. Cannabis use may also lead to smoking initiation and opioid dependence to alcohol consumption. However, given that tobacco and alcohol use typically begin before other drug use, these results may reflect a shared risk factor or a bidirectional effect for cannabis use and opioid dependence.

Occurrence and severity of cocaine-induced hallucinations: Two distinct phenotypes with shared clinical factors but specific genetic risk factors

Cocaine-induced transient hallucinations (CIH) are a frequent complication following cocaine intake that is associated with addiction severity.

METHODS

Two hundred and forty-two non-psychotic and Caucasian lifetime cocaine users were included in a French multicentric study. Clinical variables and dopamine pathway genotype data were extracted and tested with CIH scores using a zero-inflated binomial model, which allows for the exploration of factors associated with occurrence and severity separately.

RESULTS

Cocaine dependence (p_occurrence= 6.18 × 10^-5, p_severity= 9.25 × 10^-8), number of cocaine dependence DSM IV-Tr criteria (p_occurrence= 1.22 × 10^-7, p_severity= 5.09 × 10^-6), and frequency of intake during the worst period of misuse (p_occurrence= 8.51 × 10^-04, p_severity= 0.04) were associated with greater occurrence and higher severity of CIH. The genetic associations did not yield significant results after correction for multiple tests. However, some nominal associations of SNPs mapped to the VMAT2, DBH, DRD1, and DRD2 genes were significant. In the multivariate model, the significant variables were the number of cocaine dependence criteria, lifetime alcohol dependence, and the nominally associated SNPs.

CONCLUSION

Our study shows that CIH occurrence and severity are two distinct phenotypes, with shared clinical risk factors; however, they likely do not share the same genetic background.

Methylation of the serotonin transporter gene moderates the depressive subjective effect of cocaine

Genetic variation in the serotonin transporter (SLC6A4) has been shown to moderate the acute subjective effects of cocaine. Methylation of the SLC6A4 gene is associated with decreased transcription of the serotonin transporter, leading to increased serotonin in the synapse. In this study, methylation of the SLC6A4 gene was investigated in the moderation of the subjective effects of cocaine. Non-treatment-seeking cocaine-dependent individuals (N = 53) were intravenously administered cocaine (40 mg) and saline in a randomized order. The subjective effects of cocaine were self-reported using a visual analog scale starting prior to the administration of cocaine (-15 min) or saline and up to 20 min after infusion. Participants were evaluated for methylation of the SLC6A4 promoter region and 5-HTTLPR genotype. A series of ANCOVAs for SLC6A4 methylation (high/low) were run for each of ten subjective and three cardiovascular effects controlling for age, sex [utilizing the sex-determining region Y protein (SRY)], and population structure (determined from ancestry informative markers and STRUCTURE software). Participants with SLC6A4 hypermethylation reported greater subjective response to cocaine for 'depressed' relative to participants with SLC6A4 hypomethylation (experiment-wise p = 0.002). These findings indicate that SLC6A4 methylation moderates the 'depressed' subjective effect of cocaine in non-treatment-seeking cocaine-dependent participants.

Molecular genetics of cocaine use disorders in humans

Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. At the individual level, drugs of abuse produce serious consequences on health and have a negative impact on the family environment and on interpersonal and work relationships. At a wider scale, they have significant socio-economic and public health consequences and they cause delinquency and citizen insecurity. Cocaine, a psychostimulant substance, is one of the most used illicit drugs, especially in America, Western Europe, and Australia. Cocaine use disorders (CUD) are complex multifactorial conditions driven by both genetic and environmental influences. Importantly, not all people who use cocaine develop CUD, and this is due, at least in part, to biological factors that are encoded in the genome of individuals. Acute and repeated use of cocaine induces epigenetic and gene expression changes responsible for the neuronal adaptations and the remodeling of brain circuits that lead to the transition from use to abuse or dependence. The purpose of this review is to delineate such factors, which should eventually help to understand the inter-individual variability in the susceptibility to cocaine addiction. Heritability estimates for CUD are high and genetic risk factors for cocaine addiction have been investigated by candidate gene association studies (CGAS) and genome-wide association studies (GWAS), reviewed here. Also, the high comorbidity that exists between CUD and several other psychiatric disorders is well known and includes phenotypes like schizophrenia, aggression, antisocial or risk-taking behaviors. Such comorbidities are associated with a worse lifetime trajectory, and here we report shared genetic factors that may contribute to them. Gene expression changes and epigenetic modifications induced by cocaine use and chronic abuse in humans are addressed by reviewing transcriptomic studies performed on neuronal cells and on postmortem brains. We report some genes which expression is altered by cocaine that also bear genetic risk variants for the disorder. Finally, we have a glance to the pharmacogenetics of CUD treatments, still in early stages. A better understanding of the genetic underpinnings of CUD will foster the search of effective treatments and help to move forward to personalized medicine.

Genomic and Personalized Medicine Approaches for Substance Use Disorders (SUDs) Looking at Genome-Wide Association Studies

Drug addiction, or substance use disorder (SUD), is a chronic, relapsing disorder in which compulsive drug-seeking and drug-taking behaviour persist despite serious negative consequences. Drug abuse represents a problem that deserves great attention from a social point of view, and focuses on the importance of genetic studies to help in understanding the genetic basis of addiction and its medical treatment. Despite the complexity of drug addiction disorders, and the high number of environmental variables playing a role in the onset, recurrence, and duration of the symptoms, several studies have highlighted the non-negligible role of genetics, as demonstrated by heritability and genome-wide association studies. A correlation between the relative risk of addiction to specific substances and heritability has been recently observed, suggesting that neurobiological mechanisms may be, at least in part, inherited. All these observations point towards a scenario where the core neurobiological factors of addiction, involving the reward system, impulsivity, compulsivity, stress, and anxiety response, are transmitted, and therefore, genes and mutations underlying their variation might be detected. In the last few years, the development of new and more efficient sequencing technologies has paved the way for large-scale studies in searching for genetic and epigenetic factors affecting drug addiction disorders and their treatments. These studies have been crucial to pinpoint single nucleotide polymorphisms (SNPs) in genes that affect the reaction to medical treatments. This is critically important to identify pharmacogenomic approaches for substance use disorder, such as OPRM1 SNPs and methadone required doses for maintenance treatment (MMT). Nevertheless, despite the promising results obtained by genome-wide association and pharmacogenomic studies, specific studies related to population genetics diversity are lacking, undermining the overall applicability of the preliminary findings, and thus potentially affecting the portability and the accuracy of the genetic studies. In this review, focusing on cannabis, cocaine and heroin use, we report the state-of-the-art genomics and pharmacogenomics of SUDs, and the possible future perspectives related to medical treatment response in people that ask for assistance in solving drug-related problems.

A quantitative trait variant in Gabra2 underlies increased methamphetamine stimulant sensitivity

Psychostimulant (methamphetamine, cocaine) use disorders have a genetic component that remains mostly unknown. We conducted genome-wide quantitative trait locus (QTL) analysis of methamphetamine stimulant sensitivity. To facilitate gene identification, we employed a Reduced Complexity Cross between closely related C57BL/6 mouse substrains and examined maximum speed and distance traveled over 30 min following methamphetamine (2 mg/kg, i.p.). For maximum methamphetamine-induced speed following the second and third administration, we identified a single genome-wide significant QTL on chromosome 11 that peaked near the Cyfip2 locus (LOD = 3.5, 4.2; peak = 21 cM [36 Mb]). For methamphetamine-induced distance traveled following the first and second administration, we identified a genome-wide significant QTL on chromosome 5 that peaked near a functional intronic indel in Gabra2 coding for the alpha-2 subunit of the GABA-A receptor (LOD = 3.6-5.2; peak = 34-35 cM [66-67 Mb]). Striatal cis-expression QTL mapping corroborated Gabra2 as a functional candidate gene underlying methamphetamine-induced distance traveled. CRISPR/Cas9-mediated correction of the mutant intronic deletion on the C57BL/6J background to the wild-type C57BL/6NJ allele was sufficient to reduce methamphetamine-induced locomotor activity toward the wild-type C57BL/6NJ-like level, thus validating the quantitative trait variant (QTV). These studies show the power and efficiency of Reduced Complexity Crosses in identifying causal variants underlying complex traits. Functionally restoring Gabra2 expression decreased methamphetamine stimulant sensitivity and supports preclinical and human genetic studies implicating the GABA-A receptor in psychostimulant addiction-relevant traits. Importantly, our findings have major implications for studying psychostimulants in the C57BL/6J strain-the gold standard strain in biomedical research.

Genetics of substance use disorders in the era of big data

Substance use disorders (SUDs) are conditions in which the use of legal or illegal substances, such as nicotine, alcohol or opioids, results in clinical and functional impairment. SUDs and, more generally, substance use are genetically complex traits that are enormously costly on an individual and societal basis. The past few years have seen remarkable progress in our understanding of the genetics, and therefore the biology, of substance use and abuse. Various studies - including of well-defined phenotypes in deeply phenotyped samples, as well as broadly defined phenotypes in meta-analysis and biobank samples - have revealed multiple risk loci for these common traits. A key emerging insight from this work establishes a biological and genetic distinction between quantity and/or frequency measures of substance use (which may involve low levels of use without dependence), versus symptoms related to physical dependence.

Clinical M2 macrophages-related genes to aid therapy in pancreatic ductal adenocarcinoma

Background

Increasing evidence supports that infiltration M2 Macrophages act as pivotal player in tumor progression of pancreatic ductal adenocarcinoma (PDAC). Nonetheless, comprehensive analysis of M2 Macrophage infiltration and biological roles of hub genes (FAM53B) in clinical outcome and immunotherapy was lack.

Method

The multiomic data of PDAC samples were downloaded from distinct datasets. CIBERSORT algorithm was performed to uncover the landscape of TIME. Weighted gene co-expression network analysis (WGCNA) was performed to identify candidate module and significant genes associated with M2 Macrophages. Kaplan-Meier curve and receiver operating characteristic (ROC) curves were applied for prognosis value validation. Mutation data was analyzed by using “maftools” R package. Gene set variation analysis (GSVA) was employed to assign pathway activity estimates to individual sample. Immunophenoscore (IPS) was implemented to estimate immunotherapeutic significance of risk score. The half-maximal inhibitory concentration (IC50) of chemotherapeutic drugs was predicted by using the pRRophetic algorithm. Finally, quantitative real-time polymerase chain reaction was used to determine FAM53B mRNA expression and TIMER database was utilized to uncover its possible role in immune infiltration of PDAC.

Results

Herein, 17,932 genes in 234 samples (214 tumor and 20 normal) were extracted from three platforms. Taking advantage of WGCNA, significant module (royalblue) and 135 candidate genes were considered as M2 Macrophages-related genes. Subsequently, risk signature including 5 hub genes was developed by multiple analysis, which exhibited excellent prognostic performance. Besides, comprehensive prognostic nomogram was constructed to quantitatively estimate risk. Then, intrinsic link between risk score with tumor mutation burden (TMB) was explored. Additionally, risk score significantly correlated with diversity of tumor immune microenvironment (TIME). PDAC samples within different risk presented diverse signaling pathways activity and experienced significantly distinct sensitivity to administering chemotherapeutic or immunotherapeutic agents. Finally, the biological roles of FAM53B were revealed in PDAC.

Conclusions

Taken together, comprehensive analyses of M2 Macrophages profiling will facilitate prognostic prediction, delineating complexity of TIME, and contribute insight into precision therapy for PDAC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02289-w.

Genetics of substance use disorders: a review

Substance use disorders (SUDs) are prevalent and result in an array of negative consequences. They are influenced by genetic factors (h2 = ~50%). Recent years have brought substantial progress in our understanding of the genetic etiology of SUDs and related traits. The present review covers the current state of the field for SUD genetics, including the epidemiology and genetic epidemiology of SUDs, findings from the first-generation of SUD genome-wide association studies (GWAS), cautions about translating GWAS findings to clinical settings, and suggested prioritizations for the next wave of SUD genetics efforts. Recent advances in SUD genetics have been facilitated by the assembly of large GWAS samples, and the development of state-of-the-art methods modeling the aggregate effect of genome-wide variation. These advances have confirmed that SUDs are highly polygenic with many variants across the genome conferring risk, the vast majority of which are of small effect. Downstream analyses have enabled finer resolution of the genetic architecture of SUDs and revealed insights into their genetic relationship with other psychiatric disorders. Recent efforts have also prioritized a closer examination of GWAS findings that have suggested non-uniform genetic influences across measures of substance use (e.g. consumption) and problematic use (e.g. SUD). Additional highlights from recent SUD GWAS include the robust confirmation of loci in alcohol metabolizing genes (e.g. ADH1B and ALDH2) affecting alcohol-related traits, and loci within the CHRNA5-CHRNA3-CHRNB4 gene cluster influencing nicotine-related traits. Similar successes are expected for cannabis, opioid, and cocaine use disorders as sample sizes approach those assembled for alcohol and nicotine.

Spontaneously Hypertensive Rat substrains show differences in model traits for addiction risk and cocaine self-administration: Implications for a novel rat reduced complexity cross

Forward genetic mapping of F2 crosses between closely related substrains of inbred rodents - referred to as a reduced complexity cross (RCC) - is a relatively new strategy for accelerating the pace of gene discovery for complex traits, such as drug addiction. RCCs to date were generated in mice, but rats are thought to be optimal for addiction genetic studies. Based on past literature, one inbred Spontaneously Hypertensive Rat substrain, SHR/NCrl, is predicted to exhibit a distinct behavioral profile as it relates to cocaine self-administration traits relative to another substrain, SHR/NHsd. Direct substrain comparisons are a necessary first step before implementing an RCC. We evaluated model traits for cocaine addiction risk and cocaine self-administration behaviors using a longitudinal within-subjects design. Impulsive-like and compulsive-like traits were greater in SHR/NCrl than SHR/NHsd, as were reactivity to sucrose reward, sensitivity to acute psychostimulant effects of cocaine, and cocaine use studied under fixed-ratio and tandem schedules of cocaine self-administration. Compulsive-like behavior correlated with the acute psychostimulant effects of cocaine, which in turn correlated with cocaine taking under the tandem schedule. Compulsive-like behavior also was the best predictor of cocaine seeking responses. Heritability estimates indicated that 22 %-40 % of the variances for the above phenotypes can be explained by additive genetic factors, providing sufficient genetic variance to conduct genetic mapping in F2 crosses of SHR/NCrl and SHR/NHsd. These results provide compelling support for using an RCC approach in SHR substrains to uncover candidate genes and variants that are of relevance to cocaine use disorders.

Genetic Basis of Dual Diagnosis: A Review of Genome-Wide Association Studies (GWAS) Focusing on Patients with Mood or Anxiety Disorders and Co-Occurring Alcohol-Use Disorders

(1) Background: Comorbidity between Alcohol Use Disorders (AUD), mood, and anxiety disorders represents a significant health burden, yet its neurobiological underpinnings are elusive. The current paper reviews all genome-wide association studies conducted in the past ten years, sampling patients with AUD and co-occurring mood or anxiety disorder(s). (2) Methods: In keeping with PRISMA guidelines, we searched EMBASE, Medline/PUBMED, and PsycINFO databases (January 2010 to December 2020), including references of enrolled studies. Study selection was based on predefined criteria and data underwent a multistep revision process. (3) Results: 15 studies were included. Some of them explored dual diagnoses phenotypes directly while others employed correlational analysis based on polygenic risk score approach. Their results support the significant overlap of genetic factors involved in AUDs and mood and anxiety disorders. Comorbidity risk seems to be conveyed by genes engaged in neuronal development, connectivity, and signaling although the precise neuronal pathways and mechanisms remain unclear. (4) Conclusion: given that genes associated with complex traits including comorbid clinical presentations are of small effect, and individually responsible for a very low proportion of the total variance, larger samples consisting of multiple refined comorbid combinations and confirmed by re-sequencing approaches will be necessary to disentangle the genetic architecture of dual diagnosis.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): II. Externalizing superspectrum

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical effort to address limitations of traditional mental disorder diagnoses. These include arbitrary boundaries between disorder and normality, disorder co-occurrence in the modal case, heterogeneity of presentation within dis-orders, and instability of diagnosis within patients. This paper reviews the evidence on the validity and utility of the disinhibited externalizing and antagonistic externalizing spectra of HiTOP, which together constitute a broad externalizing superspectrum. These spectra are composed of elements subsumed within a variety of mental disorders described in recent DSM nosologies, including most notably substance use disorders and "Cluster B" personality disorders. The externalizing superspectrum ranges from normative levels of impulse control and self-assertion, to maladaptive disinhibition and antagonism, to extensive polysubstance involvement and personality psychopathology. A rich literature supports the validity of the externalizing superspectrum, and the disinhibited and antagonistic spectra. This evidence encompasses common genetic influences, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, and treatment response. The structure of these validators mirrors the structure of the phenotypic externalizing superspectrum, with some correlates more specific to disinhibited or antagonistic spectra, and others relevant to the entire externalizing superspectrum, underlining the hierarchical structure of the domain. Compared with traditional diagnostic categories, the externalizing superspectrum conceptualization shows improved utility, reliability, explanatory capacity, and clinical applicability. The externalizing superspectrum is one aspect of the general approach to psychopathology offered by HiTOP and can make diagnostic classification more useful in both research and the clinic.

High genes: Genetic underpinnings of cannabis use phenotypes

Cannabis is one of the most widely used substances across the globe and its use has a substantial heritable component. However, the heritability of cannabis use varies according to substance use phenotype, suggesting that a unique profile of gene variants may contribute to the different stages of use, such as age of use onset, lifetime use, cannabis use disorder, and withdrawal and craving during abstinence. Herein, we review a subset of genes identified by candidate gene, family-based linkage, and genome-wide association studies related to these cannabis use phenotypes. We also describe their relationships with other substances, and their functions at the neurobiological, cognitive, and behavioral levels to hypothesize the role of these genes in cannabis use risk. Delineating genetic risk factors in the various stages of cannabis use will provide insight into the biological mechanisms related to cannabis use and highlight points of intervention prior to and following the development of dependence, as well as identify targets to aid drug development for treating problematic cannabis use.

GABAergic polygenic risk for cocaine use disorder is negatively correlated with precuneus activity during cognitive control in African American individuals

Impaired cognitive control has been implicated in cocaine use disorder (CUD). GABAergic treatments have been proposed for CUD. Here we examined relationships between GABAergic genes and neural correlates of cognitive control in CUD. We analyzed two independent African American cohorts: one of >3000 genomewide-genotyped subjects with substance dependence and another of 40 CUD and 22 healthy control (HC) subjects who were exome-array genotyped and completed an fMRI Stroop task. We used five association thresholds to select variants of GABAergic genes in the reference cohort, yielding five polygenic risk scores (i.e., CUD-GABA-PRSs) for the fMRI cohort. At p < 0.005, the CUD-GABA-PRSs, which aggregated relative risks of CUD from 89 variants harboring in 16 genes, differed between CUD and HC individuals in the fMRI sample (p = 0.013). This CUD-GABA-PRS correlated inversely with Stroop-related activity in the left precuneus in CUD (r = -80.58, p_FWE < 0.05) but not HC participants. Post-hoc seed-based connectivity analysis of the left precuneus identified reduced functional connectivity to the posterior cingulate cortex (PCC) in CUD compared to HC subjects (p = 0.0062) and the degree of connectivity correlated with CUD-GABA-PRSs in CUD individuals (r = 0.287, p = 0.036). Our findings suggest that the GABAergic genetic risk of CUD in African Americans relates to precuneus/PCC functional connectivity during cognitive control. Identification of these GABAergic processes may be relevant targets in CUD treatment. The novel identification of 16 GABAergic genes may be investigated further to inform treatment development efforts for this condition that currently has no medication with a formal indication for its treatment.

Genome-wide association study of phenotypes measuring progression from first cocaine or opioid use to dependence reveals novel risk genes

Aim: Substance use disorders (SUD) result in substantial morbidity and mortality worldwide. Opioids, and to a lesser extent cocaine, contribute to a large percentage of this health burden. Despite their high heritability, few genetic risk loci have been identified for either opioid or cocaine dependence (OD or CD, respectively). A genome-wide association study of OD and CD related phenotypes reflecting the time between first self-reported use of these substances and a first DSM-IV dependence diagnosis was conducted. Methods: Cox proportional hazards regression in a discovery sample of 6,188 African-Americans (AAs) and 6,835 European-Americans (EAs) participants in a genetic study of multiple substance dependence phenotypes were used to test for association between genetic variants and these outcomes. The top findings were tested for replication in two independent cohorts. Results: In the discovery sample, three independent regions containing variants associated with time to dependence at P < 5 x 10-8 were identified, one (rs61835088 = 1.03 x 10-8) for cocaine in the combined EA-AA meta-analysis in the gene FAM78B on chromosome 1, and two for opioids in the AA portion of the sample in intergenic regions of chromosomes 4 (rs4860439, P = 1.37 x 10-8) and 9 (rs7032521, P = 3.30 x 10-8). After meta-analysis with data from the replication cohorts, the signal at rs61835088 improved (HR = 0.87, P = 3.71 x 10-9 and an intergenic SNP on chromosome 21 (rs2825295, HR = 1.14, P = 2.57 x 10-8) that missed the significance threshold in the AA discovery sample became genome-wide significant (GWS) for CD. Conclusions: Although the two GWS variants are not in genes with obvious links to SUD biology and have modest effect sizes, they are statistically robust and show evidence for association in independent samples. These results may point to novel pathways contributing to disease progression and highlight the utility of related phenotypes to better understand the genetics of SUDs.