Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study

The genetic landscape of substance use disorders

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

An emerging multi-omic understanding of the genetics of opioid addiction

Opioid misuse, addiction, and associated overdose deaths remain global public health crises. Despite the tremendous need for pharmacological treatments, current options are limited in number, use, and effectiveness. Fundamental leaps forward in our understanding of the biology driving opioid addiction are needed to guide development of more effective medication-assisted therapies. This Review focuses on the omics-identified biological features associated with opioid addiction. Recent GWAS have begun to identify robust genetic associations, including variants in OPRM1, FURIN, and the gene cluster SCAI/PPP6C/RABEPK. An increasing number of omics studies of postmortem human brain tissue examining biological features (e.g., histone modification and gene expression) across different brain regions have identified broad gene dysregulation associated with overdose death among opioid misusers. Drawn together by meta-analysis and multi-omic systems biology, and informed by model organism studies, key biological pathways enriched for opioid addiction-associated genes are emerging, which include specific receptors (e.g., GABAB receptors, GPCR, and Trk) linked to signaling pathways (e.g., Trk, ERK/MAPK, orexin) that are associated with synaptic plasticity and neuronal signaling. Studies leveraging the agnostic discovery power of omics and placing it within the context of functional neurobiology will propel us toward much-needed, field-changing breakthroughs, including identification of actionable targets for drug development to treat this devastating brain disease.

Genetic Associations of Persistent Opioid Use After Surgery Point to OPRM1 but Not Other Opioid-Related Loci as the Main Driver of Opioid Use Disorder

Persistent opioid use after surgery is a common morbidity outcome associated with subsequent opioid use disorder, overdose, and death. While phenotypic associations have been described, genetic associations remain unidentified. Here, we conducted the largest genetic study of persistent opioid use after surgery, comprising ~40,000 non-Hispanic, European-ancestry Michigan Genomics Initiative participants (3198 cases and 36,321 surgically exposed controls). Our study primarily focused on the reproducibility and reliability of 72 genetic studies of opioid use disorder phenotypes. Nominal associations (p < 0.05) occurred at 12 of 80 unique (r2 < 0.8) signals from these studies. Six occurred in OPRM1 (most significant: rs79704991-T, OR = 1.17, p = 8.7 × 10-5), with two surviving multiple testing correction. Other associations were rs640561-LRRIQ3 (p = 0.015), rs4680-COMT (p = 0.016), rs9478495 (p = 0.017, intergenic), rs10886472-GRK5 (p = 0.028), rs9291211-SLC30A9/BEND4 (p = 0.043), and rs112068658-KCNN1 (p = 0.048). Two highly referenced genes, OPRD1 and DRD2/ANKK1, had no signals in MGI. Associations at previously identified OPRM1 variants suggest common biology between persistent opioid use and opioid use disorder, further demonstrating connections between opioid dependence and addiction phenotypes. Lack of significant associations at other variants challenges previous studies' reliability.

Whole-exome sequencing study of opioid dependence offers novel insights into the contributions of exome variants

Opioid dependence (OD) is epidemic in the United States and it is associated with a variety of adverse health effects. Its estimated heritability is ∼50%, and recent genome-wide association studies have identified more than a dozen common risk variants. However, there are no published studies of rare OD risk variants. In this study, we analyzed whole-exome sequencing data from the Yale-Penn cohort, comprising 2,100 participants of European ancestry (EUR; 1,321 OD cases) and 1,790 of African ancestry (AFR; 864 cases). A novel low-frequency variant (rs746301110) in the RUVBL2 gene was identified in EUR ( p =6.59×10 -10 ). Suggestive associations ( p <1×10 -5 ) were observed in TMCO3 in EUR, in NEIL2 and CFAP44 in AFR, and in FAM210B in the cross-ancestry meta-analysis. Gene-based collapsing tests identified SLC22A10 , TMCO3 , FAM90A1 , DHX58 , CHRND , GLDN , PLAT , H1-4 , COL3A1 , GPHB5 and QPCTL as top genes ( p <1×10 -4 ) with most associations attributable to rare variants and driven by the burden of predicted loss-of-function and missense variants. This study begins to fill the gap in our understanding of the genetic architecture of OD, providing insights into the contribution of rare coding variants and potential targets for future functional studies and drug development.

Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling

Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SUB), substance use disorder (SUD), and other (non-SUB/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits-based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then assessed the partitioning of genetic covariance among the three facets using correlated factors models and Cholesky decomposition. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large correlation (rg = 0.803). BD correlated strongly with the SUD (rg = 0.774) and SUB (rg = 0.778) factors. In our initial decompositions, 33% of total BD variance remained after partialing out SUD and SUB. The majority of covariance between BD and SUB and between BD and SUD was shared across all factors, and, within these models, only a small fraction of the total variation in BD operated via an independent pathway with SUD or SUB outside of the other factor. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their correlation increased to rg = 0.861; in corresponding decompositions, BD-specific variance decreased to 27%. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.

Shared and unique 3D genomic features of substance use disorders across multiple cell types

Recent genome-wide association studies (GWAS) have revealed shared genetic components among alcohol, opioid, tobacco and cannabis use disorders. However, the extent of the underlying shared causal variants and effector genes, along with their cellular context, remain unclear. We leveraged our existing 3D genomic datasets comprising high-resolution promoter-focused Capture-C/Hi-C, ATAC-seq and RNA-seq across >50 diverse human cell types to focus on genomic regions that coincide with GWAS loci. Using stratified LD regression, we determined the proportion of genomewide SNP heritability attributable to the features assayed across our cell types by integrating recent GWAS summary statistics for the relevant traits: alcohol use disorder (AUD), tobacco use disorder (TUD), opioid use disorder (OUD) and cannabis use disorder (CanUD). Statistically significant enrichments (P<0.05) were observed in 14 specific cell types, with heritability reaching 9.2-fold for iPSC-derived cortical neurons and neural progenitors, confirming that they are crucial cell types for further functional exploration. Additionally, several pancreatic cell types, notably pancreatic beta cells, showed enrichment for TUD, with heritability enrichments up to 4.8-fold, suggesting genomic overlap with metabolic processes. Further investigation revealed significant positive genetic correlations between T2D with both TUD and CanUD (FDR<0.05) and a significant negative genetic correlation with AUD. Interestingly, after partitioning the heritability for each cell type's cis-regulatory elements, the correlation between T2D and TUD for pancreatic beta cells was greater (r=0.2) than the global genetic correlation value. Our study provides new genomic insights into substance use disorders and implicates cell types where functional follow-up studies could reveal causal variant-gene mechanisms underpinning these disorders.

Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations

Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.

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.

Genetic and non-genetic predictors of risk for opioid dependence

BACKGROUND

Elucidation of the interaction of biological and psychosocial/environmental factors on opioid dependence (OD) risk can inform our understanding of the etiology of OD. We examined the role of psychosocial/environmental factors in moderating polygenic risk for opioid use disorder (OUD).

METHODS

Data from 1958 European ancestry adults who participated in the Yale-Penn 3 study were analyzed. Polygenic risk scores (PRS) were based on a large-scale multi-trait analysis of genome-wide association studies (MTAG) of OUD.

RESULTS

A total of 420 (21.1%) individuals had a lifetime diagnosis of OD. OUD PRS were positively associated with OD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.21-1.66). Household income and education were the strongest correlates of OD. Among individuals with higher OUD PRS, those with higher education level had lower odds of OD (OR 0.92, 95% CI 0.85-0.98); and those with posttraumatic stress disorder (PTSD) were more likely to have OD relative to those without PTSD (OR 1.56, 95% CI 1.04-2.35).

CONCLUSIONS

Results suggest an interplay between genetics and psychosocial environment in contributing to OD risk. While PRS alone do not yet have useful clinical predictive utility, psychosocial factors may help enhance prediction. These findings could inform more targeted clinical and policy interventions to help address this public health crisis.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Clinical prediction of opioid use disorder in chronic pain patients: a cohort-retrospective study with a pharmacogenetic approach

BACKGROUND

Opioids are widely used in chronic non-cancer pain (CNCP) management. However, they remain controversial due to serious risk of causing opioid use disorder (OUD). Our main aim was to develop a predictive model for future clinical translation that include pharmacogenetic markers.

METHODS

An observational study was conducted in 806 pre-screened Spanish CNCP patients, under long-term use of opioids, to compare cases (with OUD, N.=137) with controls (without OUD, N.=669). Mu-opioid receptor 1 (OPRM1, A118G, rs1799971) and catechol-O-methyltransferase (COMT, G472A, rs4680) genetic variants plus cytochrome P450 2D6 (CYP2D6) liver enzyme phenotypes were analyzed. Socio-demographic, clinical and pharmacological outcomes were also registered. A logistic regression model was performed. The model performance and diagnostic accuracy were calculated.

RESULTS

OPRM1-AA genotype and CYP2D6 poor and ultrarapid metabolizers together with three other potential predictors: 1) age; 2) work disability; 3) oral morphine equivalent daily dose (MEDD), were selected with a satisfactory diagnostic accuracy (sensitivity: 0.82 and specificity: 0.85), goodness of fit (P=0.87) and discrimination (0.89). Cases were ten-year younger with lower incomes, more sleep disturbances, benzodiazepines use, and history of substance use disorder in front of controls.

CONCLUSIONS

Functional polymorphisms related to OPRM1 variant and CYP2D6 phenotypes may predict a higher OUD risk. Established risk factors such as young age, elevated MEDD and lower incomes were identified. A predictive model is expected to be implemented in clinical setting among CNCP patients under long-term opioids use.

The impact of assortative mating, participation bias and socioeconomic status on the polygenic risk of behavioural and psychiatric traits

To investigate assortative mating (AM), participation bias and socioeconomic status (SES) with respect to the genetics of behavioural and psychiatric traits, we estimated AM signatures using gametic phase disequilibrium and within-spouses and within-siblings polygenic risk score correlation analyses, also performing a SES conditional analysis. The cross-method meta-analysis identified AM genetic signatures for multiple alcohol-related phenotypes, bipolar disorder, major depressive disorder, schizophrenia and Tourette syndrome. Here, after SES conditioning, we observed changes in the AM genetic signatures for maximum habitual alcohol intake, frequency of drinking alcohol and Tourette syndrome. We also observed significant gametic phase disequilibrium differences between UK Biobank mental health questionnaire responders versus non-responders for major depressive disorder and alcohol use disorder. These results highlight the impact of AM, participation bias and SES on the polygenic risk of behavioural and psychiatric traits, particularly in alcohol-related traits.

The Potential and Challenges of Genomics Informed Precision Care for Substance Use Disorders

Substance use disorders (SUDs) are complex brain disorders with heritability rooted in the interplay of multiple genetic factors, alongside significant environmental influences. Gaining insights into the genetic mechanisms that heighten SUD risk can guide precision care, specifically in the development of targeted tools for prevention, early intervention, and the discovery of therapeutic targets. Nurses are ideally placed to advance genomics-informed precision care for individuals with SUDs. To fulfill this role, they must be adequately prepared to assess the value and utility of current genomics knowledge, its limitations, and ways to incorporate this understanding into clinical practice, education, research, and health care policy. [Journal of Psychosocial Nursing and Mental Health Services, 62(3), 11-14.].

Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability

BACKGROUND

Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG.

METHODS

We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources.

RESULTS

We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia.

CONCLUSION

We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.

Pharmacogenetics of Biochemically Verified Abstinence in an Opioid Agonist Therapy Randomized Clinical Trial of Methadone and Buprenorphine/Naloxone

Methadone and buprenorphine/naloxone are opioid agonist therapies for opioid use disorder treatment. Genetic factors contribute to individual differences in opioid response; however, little is known regarding genetic associations with clinical outcomes in people receiving opioid agonist therapies. Participants diagnosed with opioid use disorder, principally consisting of prescription opioids (licit or illicit), were randomized to methadone or buprenorphine/naloxone for 24 weeks of daily treatment (NCT03033732). Urine was collected at 12 biweekly study visits and analyzed for non-treatment opioids. Variants in genes involved in methadone metabolism (CYP2B6, CYP2C19, and CYP3A4), buprenorphine metabolism (CYP3A4 and UGT2B7), and μ-opioid receptor function (OPRM1) were genotyped and analyzed for their association with the number of non-treatment opioid-free urine screens. Primary analyses focused on the last 12 weeks (6 study visits, post-titration) of treatment among those reporting White ethnicity. Additional sensitivity and exploratory analyses were performed. Among methadone-treated participants (n = 52), the OPRM1 rs1799971 AA genotype (vs. G-genotypes, i.e., having one or two G alleles) was associated with greater opioid-free urine screens (incidence rate ratio = 5.24, 95% confidence interval (CI) = 2.43-11.26, P = 0.000023); longitudinal analyses showed a significant genotype-by-time interaction over the full 24 weeks (12 study visits, β = -0.28, 95% CI = -0.45 to -0.11, P = 0.0015). Exploratory analyses suggest an OPRM1 rs1799971 genotype effect on retention. No evidence of association was found between other genetic variants, including in metabolic variants, and non-treatment opioid-free urine screens in the methadone or buprenorphine/naloxone arms. Those with the OPRM1 rs1799971 G-genotypes may have a poorer response to methadone maintenance treatment, an effect that persisted through 24 weeks of treatment.

Partitioning the Genomic Components of Behavioral Disinhibition and Substance Use (Disorder) Using Genomic Structural Equation Modeling

Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SU), substance use disorder (SUD), and other (non-SU/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits--based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then applied trivariate Cholesky decomposition to these factors in order to identify BD-specific genomic variation and assess the partitioning of BD's genetic covariance with each of the other facets. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large zero-order correlation (rg=.803). BD correlated strongly with the SUD (rg=.774) and SUB factors (rg=.778). In our initial decompositions, 33% of total BD variance remained after removing variance associated with SUD and SUB. The majority of covariance between BD and SU and between BD and SUD was shared across all factors. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their zero-order correlation increased to rg=.861; in corresponding decompositions, BD-specific variance decreased to 27%. In summary, BD, SU, and SUD were highly genetically correlated at the latent factor level, and a significant minority of genomic BD variation was not shared with SU and/or SUD. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.

Impact of OPRM1 (Mu-opioid Receptor Gene) A112G Polymorphism on Dual Oxycodone and Cocaine Self-administration Behavior in a Mouse Model

The use of mu-opioid receptor (MOP-r) agonists such as oxycodone together with cocaine is prevalent, and deaths attributed to using these combinations have increased.

RATIONALE

It is unknown if functional single nucleotide polymorphisms (SNPs), such as the OPRM1 (MOP-r gene) SNP A118G, can predispose individuals to more dual opioid and psychostimulant intake. The dual self-administration (SA) of MOP-r agonists and cocaine has not been thoroughly examined, especially with regard to neurobiological changes.

OBJECTIVES

We examined oxycodone SA and subsequent dual oxycodone and cocaine SA in male and female A112G (A/G and G/G, heterozygote and homozygote, respectively) mice, models of human A118G carriers, versus wild-type (A/A) mice.

METHODS

Adult male and female A/G, G/G and A/A mice self-administered oxycodone (0.25 mg/kg/infusion, 4hr/session, FR 1.) for 10 consecutive days (sessions 1-10). Mice then self-administered cocaine (2 hr) following oxycodone SA (4 hr, as above) in each session for a further 10 consecutive days (sessions 11-20). Message RNA transcripts of 24 reward-related genes were examined in the dorsal striatum.

RESULTS

Male and female A/G and G/G mice had greater oxycodone SA than A/A mice did in the initial 10 days and in the last 10 sessions. Further, A/G and G/G mice showed greater cocaine intake than A/A mice. Dorsal striatal mRNA levels of Pdyn, Fkbp5, Oprk1, and Oprm1 were altered following oxycodone and cocaine SA.

CONCLUSIONS

These studies demonstrated that this functional genetic variation in Oprm1 affected dual opioid and cocaine SA and altered specific gene expression in the striatum.

Genetic and shared environmental factors explain the association between adolescent polysubstance use and high school noncompletion

OBJECTIVE

Examine the nature of the relationship between adolescent polysubstance use and high school noncompletion.

METHOD

Among a sample of 9,579 adult Australian twins (58.63% female, Mage = 30.59), we examined the association between the number of substances used in adolescence and high school noncompletion within a discordant twin design and bivariate twin analysis.

RESULTS

In individual-level models controlling for parental education, conduct disorder symptoms, childhood major depression, sex, zygosity, and cohort, each additional substance used in adolescence was associated with a 30% increase in the odds of high school noncompletion (OR = 1.30 [1.18, 1.42]). Discordant twin models found that the potentially causal effect of adolescent use on high school noncompletion was nonsignificant (OR = 1.19 [0.96, 1.47]). Follow-up bivariate twin models suggested genetic (35.4%, 95% CI [24.5%, 48.7%]) and shared environmental influences (27.8%, 95% CI [12.7%, 35.1%]) each contributed to the covariation in adolescent polysubstance use and early school dropout.

CONCLUSIONS

The association between polysubstance use and early school dropout was largely accounted for by genetic and shared environmental factors, with nonsignificant evidence for a potentially causal association. Future research should examine whether underlying shared risk factors reflect a general propensity for addiction, a broader externalizing liability, or a combination of the two. More evidence using finer measurement of substance use is needed to rule out a causal association between adolescent polysubstance use and high school noncompletion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Opioid trail: Tracking contributions to opioid use disorder from host genetics to the gut microbiome

Opioid use disorder (OUD) is a worldwide public health crisis with few effective treatment options. Traditional genetics and neuroscience approaches have provided knowledge about biological mechanisms that contribute to OUD-related phenotypes, but the complexity and magnitude of effects in the brain and body remain poorly understood. The gut-brain axis has emerged as a promising target for future therapeutics for several psychiatric conditions, so characterizing the relationship between host genetics and the gut microbiome in the context of OUD will be essential for development of novel treatments. In this review, we describe evidence that interactions between host genetics, the gut microbiome, and immune signaling likely play a key role in mediating opioid-related phenotypes. Studies in humans and model organisms consistently demonstrated that genetic background is a major determinant of gut microbiome composition. Furthermore, the gut microbiome is susceptible to environmental influences such as opioid exposure. Additional work focused on gene by microbiome interactions will be necessary to gain improved understanding of their effects on OUD-related behaviors.

Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

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.

Identifying genetic loci and phenomic associations of substance use traits: A multi-trait analysis of GWAS (MTAG) study

BACKGROUND AND AIMS

Genome-wide association studies (GWAS) of opioid use disorder (OUD) and cannabis use disorder (CUD) have lagged behind those of alcohol use disorder (AUD) and smoking, where many more loci have been identified. We sought to identify novel loci for substance use traits (SUTs) in both African- (AFR) and European- (EUR) ancestry individuals to enhance our understanding of the traits' genetic architecture.

DESIGN

We used multi-trait analysis of GWAS (MTAG) to analyze four SUTs in EUR subjects (OUD, CUD, AUD and smoking initiation [SMKinitiation]), and three SUTs in AFR subjects (OUD, AUD and smoking trajectory [SMKtrajectory]). We conducted gene-set and protein-protein interaction analyses and calculated polygenic risk scores (PRS) in two independent samples.

SETTING

This study was conducted in the United States.

PARTICIPANTS

A total of 5692 EUR and 4918 AFR individuals in the Yale-Penn sample and 29 054 EUR and 10 265 AFR individuals in the Penn Medicine BioBank sample.

FINDINGS

MTAG identified genome-wide significant (GWS) single nucleotide polymorphisms (SNPs) for all four traits in EUR: 41 SNPs in 36 loci for OUD; 74 SNPs in 60 loci for CUD; 63 SNPs in 52 loci for AUD; and 183 SNPs in 144 loci for SMKinitiation. MTAG also identified GWS SNPs in AFR: 2 SNPs in 2 loci for OUD; 3 SNPs in 3 loci for AUD; and 1 SNP in 1 locus for SMKtrajectory. In the Yale-Penn sample, the MTAG-derived PRS consistently yielded more significant associations with both the corresponding substance use disorder diagnosis and multiple related phenotypes than the GWAS-derived PRS.

CONCLUSIONS

Multi-trait analysis of genome-wide association studies boosted the number of loci found for substance use traits, identifying genes not previously linked to any substance, and increased the power of polygenic risk scores. Multi-trait analysis of genome-wide association studies can be used to identify novel associations for substance use, especially those for which the samples are smaller than those for historically legal substances.

Methylation and expression quantitative trait loci rs1799971 in the OPRM1 gene and rs4654327 in the OPRD1 gene are associated with opioid use disorder

Opioid use disorder (OUD) is a chronic and relapsing brain disease that results in significant mortality worldwide. Genetic factors are estimated to contribute to 40%-60% of the liability, with polymorphisms of opioid receptor genes implicated in this disorder. However, the mechanisms underlying these associations are not yet fully understood. In the present study, we first examined the methylation levels in the promoter region of the OPRM1, OPRD1, and OPRK1 genes in 111 healthy controls (HCs) and 120 patients with OUD, and genotyped three tag SNPs in these genes. Correlations between these SNPs and the methylation levels of the CpG sites and expression levels of the genes were analyzed. After identifying the mQTLs and eQTLs, we determined the associations between the mQTLs/eQTLs and susceptibility to and characteristics of OUD in 930 HCs and 801 patients with OUD. Our results demonstrated that SNPs rs1799971 in the OPRM1 gene and rs4654327 in the OPRD1 gene were both mQTLs and eQTLs. We observed unique correlations between mQTLs and methylation levels of several CpG sites in the OUD group compared to the HC group. Interestingly, both the two mQTLs and eQTLs were associated with the susceptibility to OUD. In conclusion, we suppose that mQTLs and eQTLs in genes may underlie the associations between certain risk genetic polymorphisms and OUD. These mQTLs and eQTLs could potentially serve as promising biomarkers for better management of opioid misuse.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Allele frequency and genotype distribution of the opioid receptor μ-1 (OPRM1) A118G polymorphism in the Western Saudi population

The single nucleotide polymorphism (SNP) A118G (rs1799971) in the Mu Opioid Receptor 1 (OPRM1) gene is associated with significant variations in analgesic doses and adverse effects of opioids. The A118G OPRM1 allele distributions vary significantly between different populations worldwide. The study aimed to assess the allele frequency and genotype distribution of OPRM1 A118G SNP in Saudis. This cross-sectional study included 124 healthy Saudis (62 males and 62 females) visiting the King Abdulaziz University Hospital in Jeddah, Saudi Arabia. The Oragene®-DISCOVER (OGR-600) kits were used to collect saliva samples from the participants. Polymerase chain reaction-restriction fragment length polymorphism was utilized to assess the SNP. Among the tested population, 79.03% (95% C.I. 70.81-85.82) were homozygous wild-type A118A, 16.13% (95% C.I. 10.14-23.80) were heterozygous A118G, and 4.84% (95% C.I. 1.80-10.23) were homozygous mutant G118G. OPRM1 A118G polymorphism allele frequencies were 87% (95% C.I. 79.89-92.44) and 13% (95% C.I. 7.56-20.11) for the 118A and 118G alleles, respectively. A higher frequency of the OPRM1 118G allele was present in females, 21% (95% C.I. 11.66-33.17) compared to males, 5% (95% C.I. 1.01-13.50). Relative to other Asian countries, the Saudi population showed a low prevalence of the OPRM1 A118G polymorphism, with a higher frequency of the 118G allele in females. Our research will contribute to the existing knowledge on the prevalence of OPRM1 A118G polymorphism, which could be considered for the personalized prescribing of opioid analgesics.

A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders

Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (rg s ≥ 0.87), and between the effect sizes of genetic correlations with external traits (rg  ≥ 0.95). Nevertheless, 21 of the 84 correlations with external criteria showed small, significant differences between externalizing and addiction risk factors. MiXer results showed that approximately 81% of influential externalizing variants were shared with addiction risk, whereas addiction risk shared 56% of its influential variants with externalizing. These results suggest that externalizing and addiction genetic risk are largely shared, though both constructs also retain meaningful unshared genetic variance. These results can inform future efforts to identify specific genetic influences on externalizing and SUDs.

Differences in genetic correlations between posttraumatic stress disorder and alcohol-related problems phenotypes compared to alcohol consumption-related phenotypes

BACKGROUND

Posttraumatic Stress Disorder (PTSD) tends to co-occur with greater alcohol consumption as well as alcohol use disorder (AUD). However, it is unknown whether the same etiologic factors that underlie PTSD-alcohol-related problems comorbidity also contribute to PTSD- alcohol consumption.

METHODS

We used summary statistics from large-scale genome-wide association studies (GWAS) of European-ancestry (EA) and African-ancestry (AA) participants to estimate genetic correlations between PTSD and a range of alcohol consumption-related and alcohol-related problems phenotypes.

RESULTS

In EAs, there were positive genetic correlations between PTSD phenotypes and alcohol-related problems phenotypes (e.g. Alcohol Use Disorders Identification Test (AUDIT) problem score) (rGs: 0.132-0.533, all FDR adjusted p < 0.05). However, the genetic correlations between PTSD phenotypes and alcohol consumption -related phenotypes (e.g. drinks per week) were negatively associated or non-significant (rGs: -0.417 to -0.042, FDR adjusted p: <0.05-NS). For AAs, the direction of correlations was sometimes consistent and sometimes inconsistent with that in EAs, and the ranges were larger (rGs for alcohol-related problems: -0.275 to 0.266, FDR adjusted p: NS, alcohol consumption-related: 0.145-0.699, FDR adjusted p: NS).

CONCLUSIONS

These findings illustrate that the genetic associations between consumption and problem alcohol phenotypes and PTSD differ in both strength and direction. Thus, the genetic factors that may lead someone to develop PTSD and high levels of alcohol consumption are not the same as those that lead someone to develop PTSD and alcohol-related problems. Discussion around needing improved methods to better estimate heritabilities and genetic correlations in diverse and admixed ancestry samples is provided.

The evolution of Big Data in neuroscience and neurology

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-023-00751-2.

Cross-phenotype relationship between opioid use disorder and suicide attempts: new evidence from polygenic association and Mendelian randomization analyses

Clinical epidemiological studies have found high co-occurrence between suicide attempts (SA) and opioid use disorder (OUD). However, the patterns of correlation and causation between them are still not clear due to psychiatric confounding. To investigate their cross-phenotype relationship, we utilized raw phenotypes and genotypes from >150,000 UK Biobank samples, and genome-wide association summary statistics from >600,000 individuals with European ancestry. Pairwise association and a potential bidirectional relationship between OUD and SA were evaluated with and without controlling for major psychiatric disease status (e.g., schizophrenia, major depressive disorder, and alcohol use disorder). Multiple statistical and genetics tools were used to perform epidemiological association, genetic correlation, polygenic risk score prediction, and Mendelian randomizations (MR) analyses. Strong associations between OUD and SA were observed at both the phenotypic level (overall samples [OR = 2.94, P = 1.59 ×10-14]; non-psychiatric subgroup [OR = 2.15, P = 1.07 ×10-3]) and the genetic level (genetic correlation rg = 0.38 and 0.5 with or without conditioning on psychiatric traits, respectively). Consistently, increasing polygenic susceptibility to SA is associated with increasing risk of OUD (OR = 1.08, false discovery rate [FDR] =1.71 ×10-3), and similarly, increasing polygenic susceptibility to OUD is associated with increasing risk of SA (OR = 1.09, FDR = 1.73 ×10-6). However, these polygenic associations were much attenuated after controlling for comorbid psychiatric diseases. A combination of MR analyses suggested a possible causal association from genetic liability for SA to OUD risk (2-sample univariable MR: OR = 1.14, P = 0.001; multivariable MR: OR = 1.08, P = 0.001). This study provided new genetic evidence to explain the observed OUD-SA comorbidity. Future prevention strategies for each phenotype needs to take into consideration of screening for the other one.

The Stage-Based Model of Addiction-Using Drosophila to Investigate Alcohol and Psychostimulant Responses

Addiction is a progressive and complex disease that encompasses a wide range of disorders and symptoms, including substance use disorder (SUD), for which there are few therapeutic treatments. SUD is the uncontrolled and chronic use of substances despite the negative consequences resulting from this use. The progressive nature of addiction is organized into a testable framework, the neurobiological stage-based model, that includes three behavioral stages: (1) binge/intoxication, (2) withdrawal/negative affect, and (3) preoccupation/anticipation. Human studies offer limited opportunities for mechanistic insights into these; therefore, model organisms, like Drosophila melanogaster, are necessary for understanding SUD. Drosophila is a powerful model organism that displays a variety of SUD-like behaviors consistent with human and mammalian substance use, making flies a great candidate to study mechanisms of behavior. Additionally, there are an abundance of genetic tools like the GAL4/UAS and CRISPR/Cas9 systems that can be used to gain insight into the molecular mechanisms underlying the endophenotypes of the three-stage model. This review uses the three-stage framework and discusses how easily testable endophenotypes have been examined with experiments using Drosophila, and it outlines their potential for investigating other endophenotypes.

Genome-wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression

Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, schizophrenia (SCZ), bipolar disorder (BD) and major depression (MD) of European ancestry. Next, we characterized the identified shared loci using biological annotation resources. OUD data were obtained from the Million Veteran Program, Yale-Penn and Study of Addiction: Genetics and Environment (SAGE) (15 756 cases, 99 039 controls). SCZ (53 386 cases, 77 258 controls), BD (41 917 cases, 371 549 controls) and MD (170 756 cases, 329 443 controls) data were provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDR < 0.05 and 7 unique loci shared between OUD and SCZ (n = 2), BD (n = 2) and MD (n = 7) at conjFDR < 0.05 with concordant effect directions, in line with estimated positive genetic correlations. Two loci were novel for OUD, one for BD and one for MD. Three OUD risk loci were shared with more than one psychiatric disorder, at DRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD) and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways.

Specificity in genetic and environmental risk for prescription opioid misuse and heroin use

BACKGROUND

Many studies aggregate prescription opioid misuse (POM) and heroin use into a single phenotype, but emerging evidence suggests that their genetic and environmental influences may be partially distinct.

METHODS

In total, 7164 individual twins (84.12% complete pairs; 59.81% female; mean age = 30.58 years) from the Australian Twin Registry reported their lifetime misuse of prescription opioids, stimulants, and sedatives, and lifetime use of heroin, cannabis, cocaine/crack, illicit stimulants, hallucinogens, inhalants, solvents, and dissociatives via telephone interview. Independent pathway models (IPMs) and common pathway models (CPMs) partitioned the variance of drug use phenotypes into general and drug-specific genetic (a), common environmental (c), and unique environmental factors (e).

RESULTS

An IPM with one general a and one general e factor and a one-factor CPM provided comparable fit to the data. General factors accounted for 55% (a = 14%, e = 41%) and 79% (a = 64%, e = 15%) of the respective variation in POM and heroin use in the IPM, and 25% (a = 12%, c = 8%, e = 5%) and 80% (a = 38%, c = 27%, e = 15%) of the respective variation in POM and heroin use in the CPM. Across both models, POM emerged with substantial drug-specific genetic influence (26-39% of total phenotypic variance; 69-74% of genetic variance); heroin use did not (0% of total phenotypic variance; 0% of genetic variance in both models). Prescription sedative misuse also demonstrated significant drug-specific genetic variance.

CONCLUSIONS

Genetic variation in POM, but not heroin use, is predominantly drug-specific. Misuse of prescription medications that reduce experiences of subjective distress may be partially influenced by sources of genetic variation separate from illicit drug use.

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.

Genome- and transcriptome-wide splicing associations with alcohol use disorder

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.

Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

BACKGROUND

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

METHODS

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

RESULTS

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

CONCLUSIONS

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

A review of the genomics of neonatal abstinence syndrome

Neonatal abstinence syndrome (NAS) is a constellation of signs of withdrawal occurring after birth following in utero exposure to licit or illicit opioids. Despite significant research and public health efforts, NAS remains challenging to diagnose, predict, and manage due to highly variable expression. Biomarker discovery in the field of NAS is crucial for stratifying risk, allocating resources, monitoring longitudinal outcomes, and identifying novel therapeutics. There is considerable interest in identifying important genetic and epigenetic markers of NAS severity and outcome that can guide medical decision making, research efforts, and public policy. A number of recent studies have suggested that genetic and epigenetic changes are associated with NAS severity, including evidence of neurodevelopmental instability. This review will provide an overview of the role of genetics and epigenetics in short and longer-term NAS outcomes. We will also describe novel research efforts using polygenic risk scores for NAS risk stratification and salivary gene expression to understand neurobehavioral modulation. Finally, emerging research focused on neuroinflammation from prenatal opioid exposure may elucidate novel mechanisms that could lead to development of future novel therapeutics.

New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications

Psychiatric genetics has made substantial progress in the last decade, providing new insights into the genetic etiology of psychiatric disorders, and paving the way for precision psychiatry, in which individual genetic profiles may be used to personalize risk assessment and inform clinical decision-making. Long recognized to be heritable, recent evidence shows that psychiatric disorders are influenced by thousands of genetic variants acting together. Most of these variants are commonly occurring, meaning that every individual has a genetic risk to each psychiatric disorder, from low to high. A series of large-scale genetic studies have discovered an increasing number of common and rare genetic variants robustly associated with major psychiatric disorders. The most convincing biological interpretation of the genetic findings implicates altered synaptic function in autism spectrum disorder and schizophrenia. However, the mechanistic understanding is still incomplete. In line with their extensive clinical and epidemiological overlap, psychiatric disorders appear to exist on genetic continua and share a large degree of genetic risk with one another. This provides further support to the notion that current psychiatric diagnoses do not represent distinct pathogenic entities, which may inform ongoing attempts to reconceptualize psychiatric nosology. Psychiatric disorders also share genetic influences with a range of behavioral and somatic traits and diseases, including brain structures, cognitive function, immunological phenotypes and cardiovascular disease, suggesting shared genetic etiology of potential clinical importance. Current polygenic risk score tools, which predict individual genetic susceptibility to illness, do not yet provide clinically actionable information. However, their precision is likely to improve in the coming years, and they may eventually become part of clinical practice, stressing the need to educate clinicians and patients about their potential use and misuse. This review discusses key recent insights from psychiatric genetics and their possible clinical applications, and suggests future directions.

Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

CpH methylome analysis in human cortical neurons identifies novel gene pathways and drug targets for opioid use disorder

Introduction

DNA methylation (DNAm), an epigenetic mechanism, has been associated with opioid use disorder (OUD) in preclinical and human studies. However, most of the studies have focused on DNAm at CpG sites. DNAm at non-CpG sites (mCpHs, where H indicates A, T, or C) has been recently shown to have a role in gene regulation and to be highly abundant in neurons. However, its role in OUD is unknown. This work aims to evaluate mCpHs in the human postmortem orbital frontal cortex (OFC) in the context of OUD.

Methods

A total of 38 Postmortem OFC samples were obtained from the VA Brain Bank (OUD = 12; Control = 26). mCpHs were assessed using reduced representation oxidative bisulfite sequencing in neuronal nuclei. Differential analysis was performed using the "methylkit" R package. Age, ancestry, postmortem interval, PTSD, and smoking status were included as covariates. Significant mCpHs were set at q-value < 0.05. Gene Ontology (GO) and KEGG enrichment analyses were performed for the annotated genes of all differential mCpH loci using String, ShinyGO, and amiGO software. Further, all annotated genes were analyzed using the Drug gene interaction database (DGIdb).

Results

A total of 2,352 differentially methylated genome-wide significant mCpHs were identified in OUD, mapping to 2,081 genes. GO analysis of genes with differential mCpH loci showed enrichment for nervous system development (p-value = 2.32E-19). KEGG enrichment analysis identified axon guidance and glutamatergic synapse (FDR 9E-4-2.1E-2). Drug interaction analysis found 3,420 interactions between the annotated genes and drugs, identifying interactions with 15 opioid-related drugs, including lofexidine and tizanidine, both previously used for the treatment of OUD-related symptoms.

Conclusion

Our findings suggest a role of mCpHs for OUD in cortical neurons and reveal important biological pathways and drug targets associated with the disorder.

The Genetically Informed Neurobiology of Addiction (GINA) model

Addictions are heritable and unfold dynamically across the lifespan. One prominent neurobiological theory proposes that substance-induced changes in neural circuitry promote the progression of addiction. Genome-wide association studies have begun to characterize the polygenic architecture undergirding addiction liability and revealed that genetic loci associated with risk can be divided into those associated with a general broad-spectrum liability to addiction and those associated with drug-specific addiction risk. In this Perspective, we integrate these genomic findings with our current understanding of the neurobiology of addiction to propose a new Genetically Informed Neurobiology of Addiction (GINA) model.

Buprenorphine exposure levels to optimize treatment outcomes in opioid use disorder

The severity of the ongoing opioid crisis, recently exacerbated by the COVID-19 pandemic, emphasizes the importance for individuals suffering from opioid use disorder (OUD) to have access to and receive efficacious, evidence-based treatments. Optimal treatment of OUD should aim at blocking the effects of illicit opioids while controlling opioid craving and withdrawal to facilitate abstinence from opioid use and promote recovery. The present work analyses the relationship between buprenorphine plasma exposure and clinical efficacy in participants with moderate to severe OUD using data from two clinical studies (39 and 504 participants). Leveraging data from placebo-controlled measures assessing opioid blockade, craving, withdrawal and abstinence, we found that buprenorphine plasma concentrations sustained at 2-3 ng/ml (corresponding to ≥70% brain mu-opioid receptor occupancy) optimized treatment outcomes in the majority of participants, while some individuals (e.g., injecting opioid users) needed higher concentrations. Our work also included non-linear mixed effects modeling and survival analysis, which identified a number of demographic, genetic and social factors modulating treatment response and retention. Altogether, these findings provide key information on buprenorphine plasma levels that optimize clinical outcomes and increase the likelihood of individual treatment success. NLM identifiers: NCT02044094, NCT02357901.

Why haven't we solved the addiction crisis?

The current addiction crisis has destroyed a multitude of lives, leaving millions of fatalities worldwide in its wake. At the same time, various governmental agencies dedicated to solving this seemingly never-ending dilemma have not yet succeeded or delivered on their promises. We understand that addictive behavioral seeking is a multi-faceted neurobiological and spiritually complicated phenomenon. However, although the substitution replacement approach, especially to treat Opioid Use Disorder (OUD), has importance for harm reduction in the short term, it does not bring about a harm-free recovery or prevention. Instead, we propose a promising novel approach that uses genetic risk testing with induction of dopamine homeostasis and an objective Brain Health Check during youth. Our model involves a six-hit approach known as the "Reward Dysregulation Syndrome Solution System," which can identify addiction risk and target the root cause of addiction, dopamine dysregulation. While we applaud all past sophisticated neurogenetic and neuropharmacological research, our opinion is that in the long term, addiction scientists and clinicians might characterize preaddiction using tests; for example, administering the validated RDSQuestionarre29, genetic risk assessment, a modified brain health check, or diagnostic framing of mild to moderate Substance Use Disorder (SUD). The preaddiction concept could incentivize the development of interventions to prevent addiction from developing in the first place and target and treat neurotransmitter imbalances and other early indications of addiction. WC 222.

Clinical, environmental, and genetic risk factors for substance use disorders: characterizing combined effects across multiple cohorts

Substance use disorders (SUDs) incur serious social and personal costs. The risk for SUDs is complex, with risk factors ranging from social conditions to individual genetic variation. We examined whether models that include a clinical/environmental risk index (CERI) and polygenic scores (PGS) are able to identify individuals at increased risk of SUD in young adulthood across four longitudinal cohorts for a combined sample of N = 15,134. Our analyses included participants of European (NEUR = 12,659) and African (NAFR = 2475) ancestries. SUD outcomes included: (1) alcohol dependence, (2) nicotine dependence; (3) drug dependence, and (4) any substance dependence. In the models containing the PGS and CERI, the CERI was associated with all three outcomes (ORs = 01.37-1.67). PGS for problematic alcohol use, externalizing, and smoking quantity were associated with alcohol dependence, drug dependence, and nicotine dependence, respectively (OR = 1.11-1.33). PGS for problematic alcohol use and externalizing were also associated with any substance dependence (ORs = 1.09-1.18). The full model explained 6-13% of the variance in SUDs. Those in the top 10% of CERI and PGS had relative risk ratios of 3.86-8.04 for each SUD relative to the bottom 90%. Overall, the combined measures of clinical, environmental, and genetic risk demonstrated modest ability to distinguish between affected and unaffected individuals in young adulthood. PGS were significant but added little in addition to the clinical/environmental risk index. Results from our analysis demonstrate there is still considerable work to be done before tools such as these are ready for clinical applications.

Association between rs1799971 in the mu opioid receptor gene and methadone maintenance treatment response

OBJECTIVE

Genetic variations can affect individual response to methadone maintenance treatment (MMT) for heroin addiction. The A118G variant (rs1799971) in the mu opioid receptor gene (OPRM1) is a potential candidate single nucleotide polymorphism (SNP) for personalized MMT. This study determined whether rs1799971 is related to MMT response or dose.

METHODS

We recruited 286 MMT patients from a Han Chinese population. The rs1799971 genotype was determined via TaqMan genotyping assay. The genetic effect of this SNP on MMT response or dose was evaluated using logistic regression. A meta-analysis was performed to merge all available data to evaluate the role of rs1799971 in MMT using RevMan 5.3 software.

RESULTS

No statistical significance was observed in the association between the OPRM1 rs1799971 and MMT response or dose in our Chinese cohort. Meta-analysis indicated that the OPRM1 A118G variation was not significantly associated with MMT response or dose requirement.

CONCLUSION

The results suggest that rs1799971 in OPRM1 might not play a critical role alone in influencing MMT response or dose.

Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. Understanding the genetic architecture of this comorbidity could be improved by focusing on intermediate traits that show positive genetic correlation with the disorders. Thus, we aimed to characterize the shared vs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD) -beyond genetic correlation, and boost discovery for jointly-associated loci. Summary statistics for MOOD (a binary measure of the tendency to report frequent mood swings), AC (number of standard drinks over a typical consumption week) and AUD GWASs (Ns > 200,000) were analyzed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD. To do so, we used a newly established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly associated genomic loci, which were mapped to genes and biological functions. MOOD was highly polygenic (10.4k single nucleotide polymorphisms, SNPs, SD = 2k) compared to AC (4.9k SNPs, SD = 0.6k) and AUD (4.3k SNPs, SD = 2k). The polygenic overlap of MOOD and AC was twice that of MOOD and AUD (98% vs. 49%), with opposite genetic correlation (-0.2 vs. 0.23), as confirmed in independent samples. MOOD&AUD associated SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 jointly associated loci, fifteen were novel for MOOD, AC and AUD. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated partly shared biological underpinnings, yet, clearly distinct functional patterns between MOOD&AC and MOOD&AUD, suggesting new mechanisms for the comorbidity of AUD with mood disorders.

Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects in brain regions associated with addiction

Despite an estimated heritability of ~50%, genome-wide association studies of opioid use disorder (OUD) have revealed few genome-wide significant loci. We conducted a cross-ancestry meta-analysis of OUD in the Million Veteran Program (N = 425,944). In addition to known exonic variants in OPRM1 and FURIN, we identified intronic variants in RABEPK, FBXW4, NCAM1 and KCNN1. A meta-analysis including other datasets identified a locus in TSNARE1. In total, we identified 14 loci for OUD, 12 of which are novel. Significant genetic correlations were identified for 127 traits, including psychiatric disorders and other substance use-related traits. The only significantly enriched cell-type group was CNS, with gene expression enrichment in brain regions previously associated with substance use disorders. These findings increase our understanding of the biological basis of OUD and provide further evidence that it is a brain disease, which may help to reduce stigma and inform efforts to address the opioid epidemic.

Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci

Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 (Ncases = 20,686;Neffective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10-8) lead SNPs-one at FURIN (rs11372849; p = 9.54 × 10-10) and two OPRM1 variants (rs1799971, p = 4.92 × 10-09; rs79704991, p = 1.11 × 10-08; r2 = 0.02). Rs1799971 (p = 4.91 × 10-08) and another OPRM1 variant (rs9478500; p = 1.95 × 10-08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10-47) and AUD (rg = 0.77; p = 6.36 × 10-78). The OUD-MTAG resulted in a GWAS Nequivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10-16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10-13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

Are prescription misuse and illicit drug use etiologically distinct? A genetically-informed analysis of opioids and stimulants

BACKGROUND

Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.

METHODS

A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.

RESULTS

Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.

CONCLUSIONS

Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.