This study explores the neurobiological underpinnings of alcohol use disorder (AUD) by integrating bulk and single-cell transcriptomic data from humans, primates, and mice across three brain regions associated with addiction (i.e., prefrontal cortex (PFC), nucleus accumbens (NAc), and central amygdala (CeA)). We compared AUD RNA expression and cell-type abundance from 92 human brain to data from 53 primates and 90 mice engaged in diverse alcohol use paradigms. The findings revealed significant and reproducible correlations between human AUD and mammalian models of alcohol use that vary by tissue, species, and behavioral paradigm. The strongest correlations occurred between primate and mouse models of binge drinking (i.e., high drinking in the dark). Certain primate models demonstrated that the brain RNA correlations with human alcohol use disorder (AUD) were approximately 40% as strong as the correlations observed within human samples themselves. By integrating single-cell transcriptomic data, this study observed decreased oligodendrocyte proportions in the PFC and NAc of human AUD with similar trends in animal models. Gene co-expression network analyses revealed conserved systems associated with human AUD and animal models of heavy/binge alcohol consumption. Gene co-expression networks were enriched for pathways related to inflammation, myelination, and synaptic plasticity and the genes within them accounted for ~20% of the heritability in human alcohol consumption. Identified hub genes were associated with relevant traits (e.g., impulsivity, motivation) in humans and mice. This study sheds light on conserved biological entities underlying AUD and chronic alcohol use, providing insights into the cellular, genetic, and molecular basis across species.

BACKGROUND:Innovation in psychiatric therapeutics has stagnated on known mechanisms. Psychiatric genome-wide association studies (GWAS) have identified hundreds of genome-wide significant (GWS) loci that have rapidly advanced our understanding of disease etiology. However, whether these results can be leveraged to improve clinical treatment for specific psychiatric disorders remains poorly understood. METHODS:In this proof-of-principal evaluation of GWAS clinical utility, we test whether the targets of drugs used to treat Attention Deficit Hyperactivity Disorder (ADHD), Bipolar Disorder (BiP), Generalized Anxiety Disorder (GAD), Major Depressive Disorder (MDD), Post-Traumatic Stress Disorder (PTSD), Schizophrenia (SCZ), Substance Use Disorders (SUDs), and insomnia (INS), are enriched for GWAS meta-analysis findings. RESULTS:The genes coding for treatment targets of medications used to SCZ, BiP, MDD, and SUDs (but not ADHD, PTSD, GAD, or INSOM) are enriched for GWS loci identified in their respective GWAS (ORs: 2.78-27.63; all ps <1.15e-3). Enrichment is largely driven by the presence of a GWS locus or loci within a gene coding for a drug target (i.e., proximity matching). Broadly, additional annotation (i.e., functional: Combined Annotation Dependent Depletion [CADD] scores, regulomeDB scores, eQTL, chromatin loop, and gene region; statistical: effect size of genome-wide significant SNPs; Z-score of SNPs; number of drug targets implicated by GWAS), with the exception of weighting by the largest SNP effect size, does not further improve enrichment across disorders. Evaluation of prior smaller GWAS reveal that more recent larger GWAS improve enrichment. CONCLUSIONS:GWAS results may assist in the prioritization of medications for future psychopharmaceutical research.

Addiction-related GWASs are increasingly important in understanding risk for substance use and disorders (SUDs). GWASs have begun to identify loci associated with SUDs and other complex traits, but most associated loci necessitate functional evidence to translate and prioritize. Data depots of functional evidence in tissues, cell types, and experimental paradigms across organisms hold significant promise when integrated with GWAS. Model organisms can provide crucial evidence for gene roles in behaviors; however, public facing resources connecting these data types and allowing for a comprehensive assessment and integration of functional evidence are limited. We address this technological gap by introducing the CONSILIENCE-GWAS analytical webtool that simplifies the aggregation, analysis, and visualization of the enrichment of model organism functional data in human GWAS. We developed CONSILIENCE-GWAS to investigate how GWAS results are enriched by functional evidence within and across model systems. CONSILIENCE-GWAS incorporates enrichment pipelines for LD Score Regression and gene-set based polygenic score creation using user-supplied GWAS results and genotype data. CONSILIENCE-GWAS integrates with GENEWEAVER-GWAS via APIs, allowing end-users to upload, curate, compare, analyze, and share their results. GENEWEAVER integration facilitates the efficient identification of enriched gene sets across species and improves the interpretation of non-coding variants in tissue-specific contexts. We demonstrate features of CONSILIENCE-GWAS using publicly available data from a published enrichment analysis of alcohol consumption in Mus musculus translated to human GWAS of alcohol use and disorder. CONSILIENCE-GWAS is freely available on the web at https://consilience.bgalab.emory.edu .

Genetic mechanisms of alternative mRNA splicing have been shown in the brain for a variety of neuropsychiatric traits, but not substance use disorders. Our study utilized RNA-sequencing data on alcohol use disorder (AUD) in four brain regions (n = 56; ages 40–73; 100% ‘Caucasian’; PFC, NAc, BLA and CEA) and genome-wide association data on AUD (n = 435,563, ages 22–90; 100% European-American). Polygenic scores of AUD were associated with AUD-related alternative mRNA splicing in the brain. We identified 714 differentially spliced genes between AUD vs controls, which included both putative addiction genes and novel gene targets. We found 6463 splicing quantitative trait loci (sQTLs) that linked to the AUD differentially spliced genes. sQTLs were enriched in loose chromatin genomic regions and downstream gene targets. Additionally, the heritability of AUD was enriched for DNA variants in and around differentially spliced genes associated with AUD. Our study also performed splicing transcriptome-wide association studies (TWASs) of AUD and other drug use traits that unveiled specific genes for follow-up and splicing correlations across SUDs. Finally, we showed that differentially spliced genes between AUD vs control were also associated with primate models of chronic alcohol consumption in similar brain regions. Our study found substantial genetic contributions of alternative mRNA splicing in AUD.

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.

Opiate/opioid use disorder (OUD) is a chronic relapsing brain disorder that has increased in prevalence in the last two decades in the United States. Understanding the molecular correlates of OUD may provide key insights into the pathophysiology of this syndrome. Using publicly available RNA-sequencing data, our study investigated the possible role of alternative mRNA splicing in human brain tissue (dorsal–lateral prefrontal cortex (dlPFC), nucleus accumbens (NAc), and midbrain) of 90 individuals with OUD or matched controls. We found a total of 788 differentially spliced genes across brain regions. Alternative mRNA splicing demonstrated mostly tissue-specific effects, but a functionally characterized splicing change in the clathrin and AP-2-binding (CLAP) domain of the Bridging Integrator 1 (BIN1) gene was significantly linked to OUD across all brain regions. We investigated two hypotheses that may underlie differential splicing in OUD. First, we tested whether spliceosome genes were disrupted in the brains of individuals with OUD. Pathway enrichment analyses indicated spliceosome perturbations in OUD across brain regions. Second, we tested whether alternative mRNA splicing regions were linked to genetic predisposition. Using a genome-wide association study (GWAS) of OUD, we found no evidence that DNA variants within or surrounding differentially spliced genes were implicated in the heritability of OUD. Altogether, our study contributes to the understanding of OUD pathophysiology by providing evidence of a possible role of alternative mRNA splicing in OUD.

Cocaine use presents a worldwide public health problem with high socioeconomic cost. No current pharmacologic treatments are available for cocaine use disorder (CUD) or cocaine toxicity. To explore pharmaceutical treatments for tthis disorder and its sequelae we analyzed gene expression data from post-mortem brain tissue of individuals with CUD who died from cocaine-related causes with matched cocaine-free controls (n = 71, Mage = 39.9, 100% male, 49% with CUD, 3 samples/brain regions). To match molecular signatures from brain pathology with potential therapeutics, we leveraged the L1000 database honing in on neuronal mRNA profiles of 825 repurposable compounds (e.g., FDA approved). We identified 16 compounds that were negatively associated with CUD gene expression patterns across all brain regions (padj < 0.05), all of which outperformed current targets undergoing clinical trials for CUD (all padj > 0.05). An additional 43 compounds were positively associated with CUD expression. We performed an in silico follow-up potential therapeutics using independent transcriptome-wide in vitro (neuronal cocaine exposure; n = 18) and in vivo (mouse cocaine self-administration; n = 12-15) datasets to prioritize candidates for experimental validation. Among these medications, ibrutinib was consistently linked with the molecular profiles of both neuronal cocaine exposure and mouse cocaine self-administration. We assessed the therapeutic efficacy of ibrutinib using the Drosophila melanogaster model. Ibrutinib reduced cocaine-induced startle response and cocaine-induced seizures (n = 61-142 per group; sex: 51% female), despite increasing cocaine consumption. Our results suggest that ibrutinib could be used for the treatment of cocaine use disorder.

Cross-species translational approaches to human genomic analyses are lacking. The present study uses an integrative framework to investigate how genes associated with nicotine use in model organisms contribute to the genetic architecture of human tobacco consumption. First, we created a model organism geneset by collecting results from five animal models of nicotine exposure (RNA expression changes in brain) and then tested the relevance of these genes and flanking genetic variation using genetic data from human cigarettes per day (UK BioBank N = 123,844; all European Ancestry). We tested three hypotheses: (1) DNA variation in, or around, the ‘model organism geneset’ will contribute to the heritability to human tobacco consumption, (2) that the model organism genes will be enriched for genes associated with human tobacco consumption, and (3) that a polygenic score based off our model organism geneset will predict tobacco consumption in the AddHealth sample ( N = 1667; all European Ancestry). Our results suggested that: (1) model organism genes accounted for ~5–36% of the observed SNP-heritability in human tobacco consumption (enrichment: 1.60–31.45), (2) model organism genes, but not negative control genes, were enriched for the gene-based associations (MAGMA, H-MAGMA, SMultiXcan) for human cigarettes per day, and (3) polygenic scores based on our model organism geneset predicted cigarettes per day in an independent sample. Altogether, these findings highlight the advantages of using multiple species evidence to isolate genetic factors to better understand the etiological complexity of tobacco and other nicotine consumption.

ABSTRACTBackgroundRodent paradigms and human genome-wide association studies (GWASs) on drug use have the potential to provide biological insight into the pathophysiology of addiction.MethodsUsing GeneWeaver, we created rodent alcohol and nicotine gene-sets derived from 19 gene expression studies on alcohol and nicotine outcomes. We partitioned the SNP-heritability of these gene-sets using four large human GWASs: 1) alcoholic drinks per week, 2) problematic alcohol use, 3) cigarettes per day and 4) smoking cessation. We benchmarked our findings with curated human alcoholism and nicotine addiction gene-sets and performed specificity analyses using other rodent gene-sets (e.g., locomotor behavior) and other human GWASs (e.g., height).ResultsThe rodent alcohol gene-set was enriched for heritability of drinks per week, cigarettes per day, and smoking cessation, but not problematic alcohol use. However, the rodent nicotine gene-set was not significantly associated with any of these traits. Both rodent gene-sets showed enrichment for several non-substance use GWASs, and the extent of this relationship tended to increase as a function of trait heritability. In general, larger gene-sets demonstrated more significant enrichment. Finally, when evaluating human traits with similar heritabilities, both rodent gene-sets showed greater enrichment for substance use traits.ConclusionOur results suggest that rodent gene expression studies can help to identify genes that capture heritability of substance use traits in humans, yet the specificity to human substance use was less than expected due to various factors such as the genetic architecture of a trait. We outline various limitations, interpretations and considerations for future research.

Animal models of drug use have investigated possible mechanisms governing human substance use traits for over 100 years. Most cross-species research on drug use/addiction examines behavioral overlap, but studies assessing neuromolecular (e.g. RNA) correspondence are lacking. Our study utilized transcriptome-wide data from the hippocampus and ventral tegmental area (VTA)/midbrain from a total of 35 human males with cocaine use disorder/controls and 49 male C57BL/6J cocaine/saline administering/exposed mice. We hypothesized differential expressed genes and systems of co-expressed genes (gene networks) would show appreciable overlap across mouse cocaine self-administration and human cocaine use disorder. We found modest, but significant relationships between differentially expressed genes associated with cocaine self-administration (short access) and cocaine use disorder within reward circuitry. Differentially expressed genes underlying models of acute cocaine exposure (cocaine), context re-exposure and cocaine + context re-exposure were not consistently associated with human CUD across brain regions. Investigating systems of co-expressed genes, we found several validated gene networks with weak to moderate conservation between cocaine/saline self-administering mice and disordered cocaine users/controls. The most conserved hippocampal and VTA gene networks demonstrated substantial overlap (2029 common genes) and included both novel and previously implicated targets for cocaine use/addiction. Lastly, we conducted (expression-based) phenome-wide association studies of the ninecommonhub genes across conserved gene networks. Common hub genes were associated with dopamine/serotonin function, cocaine self-administration and other relevant mouse traits. Overall, our study pinpointed and characterized conserved brain-related RNA patterns across mouse cocaine self-administration and human cocaine use disorder. We offer recommendations for future research and add to the dialogue surrounding pre-clinical animal research for human disease.

STUDY OBJECTIVES:Estimate the genetic and environmental influences on the relationship between onset of regular cannabis use and young adult insomnia. METHODS:In a population-based twin cohort of 1882 twins (56% female, mean age = 22.99, SD = 2.97) we explored the genetic/environmental etiology of the relationship between onset of regular cannabis use and insomnia-related outcomes via multivariate twin models. RESULTS:Controlling for sex, current depression symptoms, and prior diagnosis of an anxiety or depression disorder, adult twins who reported early onset for regular cannabis use (age 17 or younger) were more likely to have insomnia (β = 0.07, p = 0.024) and insomnia with short sleep on weekdays (β = 0.08, p = 0.003) as young adults. We found significant genetic contributions for the onset of regular cannabis use (a2 = 76%, p < 0.001), insomnia (a2 = 44%, p < 0.001), and insomnia with short sleep on weekdays (a2 = 37%, p < 0.001). We found significant genetic correlations between onset of regular use and both insomnia (rA = 0.20, p = 0.047) and insomnia with short sleep on weekdays (rA = 0.25, p = 0.008) but no significant environmental associations between these traits. CONCLUSIONS:We found common genetic liabilities for early onset of regular cannabis use and insomnia, implying pleiotropic influences of genes on both traits.

The multitude of gambling activities has given rise to heterogeneous ways of analyzing these behaviors and may partially underlie the lack of replication in gambling research. The current study used complementary analyses to investigate the structure, typology and etiology of gambling behaviors in a discovery sample of 2,116 twins (54.86% female; M-age = 24.90) and a replication sample of 619 siblings (30.37% female; M-age = 28.00). Our approach was twofold. First, we used confirmatory factor analyses to investigate the structure across the frequency of eight gambling activities. Second, we used factor mixture models to identify gambling frequency subtypes. We assessed associations with gambling frequency as well as conducted genetically informed analyses to estimate the role of genetic and environmental influences. Across samples, a two-factor model fit the data best, with a Common Gambling factor influencing all activities and a separate factor for Skill Gambling. Our study identified four gambling frequency subtypes, which resembled the typology from the Pathways Model. We found distinct demographic, psychiatric, behavioral and genetic risk profiles for the different gambling factors and subtypes with robust associations observed for male sex, risk-taking, sensation seeking, alcohol dependence and problem gambling. Controlling for shared genetic and environmental influences (via co-twin control modeling), we found that sensation seeking directly increased Common Gambling frequency. In sum, we illustrated the utility of multi-dimensional statistical techniques for disentangling the structure and typology from complex multivariate gambling data.

The multitude of gambling activities corresponds to heterogeneous ways of analyzing behavioral outcomes and may partially underlie the lack of replication in gambling research. The current study incorporated complementary analyses to provide an approach to investigate associations with multi-dimensional gambling data that we demonstrated in a discovery/community sample of 2,116 twins (54.86% female; Mage=24.90) and a replication/clinical sample of 619 siblings (30.37% female; Mage=28.00). Our proposed approach was twofold. First, we used confirmatory factor analyses (CFAs) to derive a general gambling frequency measure across eight gambling activities and to test the common liability hypothesis. Second, we conducted latent class analyses (LCAs) to derive gambling frequency subtypes and investigated their theoretical correspondence with the Pathways Model. Our study identified robust support for the common liability hypothesis of gambling, suggesting a shared mechanism for multiple gambling behaviors – including activities controversially defined as “gambling.” Using LCAs, we identified four novel gambling frequency subtypes with analogous behavioral profiles and correlates across samples and some resemblance with the Pathways Model. The subtype with the highest rates of problem gambling had a frequent appetite for particular gambling activities and demonstrated externalizing psychopathology comparable to the “antisocial impulsivist” pathway. Using co-twin control models, we determined that risk-taking, sensation seeking and antisocial personality disorder predicted gambling frequency above and beyond shared genetic and environmental factors. In sum, we illustrated the utility of multi-dimensional statistical techniques for disentangling the structure and typology of different gambling behaviors and discussed our results in context of the psychometric, empirical and theoretical implications.

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

Animal models of drug use have been employed for over 100 years to facilitate the identification of mechanisms governing human substance use and addiction. Most cross-species research on drug use/addiction examines behavioral overlap, but studies assessing neuro-molecular correspondence are lacking. Our study utilized transcriptome-wide data from the hippocampus and ventral tegmental area (VTA)/midbrain from a total of 35 human males with cocaine use disorder/controls and 49 male C57BL/6J cocaine/saline administering/exposed mice. We hypothesized that individual genes (differential expression) and systems of co-expressed genes (gene networks) would demonstrate appreciable overlap across mouse cocaine self-administration and human cocaine use disorder. We found modest, but significant associations between differentially expressed genes associated with cocaine self-administration (short access) and cocaine use disorder within meso-limbic circuitry, but non-robust associations with mouse models of acute cocaine exposure, (cocaine) context re-exposure and cocaine + context re-exposure. Investigating systems of co-expressed genes, we also found several validated gene networks with weak to moderate conservation between cocaine/saline self-administering mice and disordered cocaine users/controls. The most conserved hippocampal and VTA gene networks demonstrated substantial overlap (2,029 common genes) and included novel and previously implicated targets of cocaine use/addiction. Lastly, we conducted expression-based phenome-wide association studies of the nine common hub genes across conserved gene networks and found that they were associated with dopamine/serotonin function, cocaine self-administration and other relevant mouse traits. Overall, our study identified and characterized homologous transcriptional effects between mouse models of cocaine self-administration and human cocaine use disorder that may serve as a benchmark for future research.

We integrated genomic and bioinformatic analyses, using data from the largest genome-wide association study of cocaine dependence (CD; n = 6546; 82.37% with CD; 57.39% male) and the largest postmortem gene-expression sample of individuals with cocaine use disorder (CUD; n = 36; 51.35% with CUD; 100% male). Our genome-wide analyses identified one novel gene (NDUFB9) associated with the genetic predisposition to CD in African-Americans. The genetic architecture of CD was similar across ancestries. Individual genes associated with CD demonstrated modest overlap across European-Americans and African-Americans, but the genetic liability for CD converged on many similar tissue types (brain, heart, blood, liver) across ancestries. In a separate sample, we investigated the neuronal gene expression associated with CUD by using RNA sequencing of dorsal lateral prefrontal cortex neurons. We identified 133 genes differentially expressed between CUD case patients and cocaine-free control subjects, including previously implicated candidates for cocaine use/addiction (FOSB, ARC, KCNJ9/GIRK3, NR4A2, JUNB, and MECP2). Differential expression analyses significantly correlated across European-Americans and African-Americans. While genes significantly associated with CD via genome-wide methods were not differentially expressed, two of these genes (NDUFB9 and C1qL2) were part of a robust gene coexpression network associated with CUD involved in neurotransmission (GABA, acetylcholine, serotonin, and dopamine) and drug addiction. We then used a "guilt-by-association' approach to unravel the biological relevance of NDUFB9 and ClqL2 in the context of Cl). In sum, our study furthers the understanding of the genetic architecture and molecular neuropathology of human cocaine addiction and provides a framework for translating biological meaning into otherwise obscure genome-wide associations.

Human laboratory studies and twin research investigating relationships between alcohol use/pathology and gambling generally have yielded contradictory results, sometimes suggesting causal relationships and common genetic risk factors. 2860 individuals (mean age: 25.60, s.d = 3.21, 50.62% female) from separate clinical (n = 636) and community based (twin) samples (n = 2224) were used to assess associations between past year alcohol use and frequency of past year gambling behaviors (gambling frequency). After adjustment for demographic and psychiatric covariates, individual-level analyses detected that increased alcohol use was associated with more frequent gambling behaviors in twin and clinical samples. Co-twin control models were then used to test potential causal (direct) relationships between alcohol use and gambling frequency. Controlling for all covariates and shared genetic/environmental factors, we found increased alcohol use directly predicted more frequent gambling behaviors (consistent with causality). Our study also suggests shared genetic and/or environmental risk factors contribute to the association between increased alcohol use and frequent gambling behavior, a finding that may be more pronounced in males. The present study helps bridge the gap between twin research and human laboratory studies on gambling and alcohol use and corroborates findings across community and clinical samples. Overall, our findings support both common risk factors between alcohol use and gambling as well as a direct relationship between alcohol use and gambling frequency. Recognizing these dual processes could prove useful for gambling-related prevention/intervention programs.

BACKGROUND:Research indicates that early tobacco initiation increases risk for dependence, but despite this, early initiation is associated with slower transitions to escalated tobacco use. In contrast to these findings, other studies suggest that rapid escalated tobacco use is associated with increased dependence outcomes.METHODS:Our sample was comprised of 5668 twins (2834 twin-pairs, mean age: 26.89, s.d = 4.42, 53.67% female, 57.69% monozygotic) from Colorado and Minnesota twin cohorts. We assessed the associations between 1) age of tobacco initiation and the speed of transitions (latency) to tobacco problem use and dependence and the associations between 2) age of initiation and latencies to tobacco problem use and dependence with tobacco dependence symptom severity. To further understand the etiological unfolding of these processes, we conducted univariate twin models and causally informative co-twin control models.RESULTS:After adjustment for covariates, we found that early tobacco initiation was associated with a slower transition from initiation to problem use but a faster transition from problem use to dependence. Additionally, we found that earlier initiation and faster transitions to tobacco problem use and dependence predicted greater tobacco dependence severity within twin pairs (consistent with causal influences). The contribution of shared genetic and environmental factors was also evident for these relationships.CONCLUSIONS:Our study further disentangles the role of early initiation with transition times to tobacco problem use and dependence. In addition to common risk factors, we found potential causal roles for early tobacco initiation and rapid escalated tobacco use with increased risk for tobacco dependence severity.