Genome-wide association analysis of opioid use disorder: A novel approach using clinical data

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.

A genome-wide Association study of the Count of Codeine prescriptions

Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide association analyses were then conducted to identify genomic loci and candidate genes associated with different count patterns of codeine prescriptions. Both low- and high-prescription counts were captured by developing 8 types of phenotypes with selected ranges of prescription numbers to reflect potentially different levels of opioid risk severity. We identified one significant locus associated with low-count codeine prescriptions (1, 2 or 3 prescriptions), while up to 7 loci were identified for higher counts (≥ 4, ≥ 5, ≥6, or ≥ 7 prescriptions), with a strong overlap across different thresholds. We identified 9 significant genomic loci with all-count phenotype. Further, using the polygenic risk approach, we identified a significant correlation (Tau = 0.67, p = 0.01) between an externally derived polygenic risk score for opioid use disorder and numbers of codeine prescriptions. As a proof-of-concept study, our research provides a novel and generalizable phenotyping pipeline for the genomic study of opioid-related risk traits.

Social complexity of a fentanyl vaccine to prevent opioid overdose conference proceedings: Radcliffe Institute for Advanced Study conference proceedings

Despite significant public health attention and investment, hundreds of thousands of individuals have suffered fatal opioid overdose since the onset of the opioid crisis. Risk of opioid overdose has been exacerbated by the influx of fentanyl, a powerful synthetic opioid, into the drug supply. The National Institutes of Health Helping End Addiction Long-term (HEAL) Initiative is supporting the development of vaccines targeting fentanyl to protect against overdose. If successful, a vaccine would induce anti-fentanyl antibodies to sequester fentanyl (but not other opioids) in the blood, preventing fentanyl from crossing into the brain and reaching the central nervous system where it can cause overdose. Introduction of an overdose preventing strategy that relies on a vaccine to confer passive protection may be impactful. However, vaccines are poorly understood by the public and politicized. Moreover, the overdose ecosystem is complex and extends across numerous social, economic, medical, and cultural systems. As such, optimal use of a vaccine strategy to address overdose may benefit from multidisciplinary consideration of the social, ethical, and systemic factors that influence substance use and overdose that may also impact the acceptability of a fentanyl vaccine and related implementation strategies. In March 2022, Dr. Elissa Weitzman convened a two-day conference at the Harvard Radcliffe Institute for Advanced Study on the Social Complexity of a Fentanyl Vaccine to Prevent Opioid Overdose. In all, 19 professionals from diverse disciplines (medicine, psychology, history, ethics, immunology, vaccinology, communications, policy) attended the conference and led discussions that centered on population health and epidemiology, history of medicine and frameworks for understanding substance use, ethics, decision-making and attitudes, and operational issues to the question of a novel immunotherapy targeting fentanyl overdose. Participants also debated the risks and benefits of vaccine administration in response to fictional clinical case vignettes. A summary of the conference presentations and discussions follows.

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.

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.

IUPHAR review - Data-driven computational drug repurposing approaches for opioid use disorder

Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by the misuse of opioid drugs, causing significant morbidity and mortality in the United States. Existing medications for OUD are limited, and there is an immediate need to discover treatments with enhanced safety and efficacy. Drug repurposing aims to find new indications for existing medications, offering a time-saving and cost-efficient alternative strategy to traditional drug discovery. Computational approaches have been developed to further facilitate the drug repurposing process. In this paper, we reviewed state-of-the-art data-driven computational drug repurposing approaches for OUD and discussed their advantages and potential challenges. We also highlighted promising repurposed candidate drugs for OUD that were identified by computational drug repurposing techniques and reviewed studies supporting their potential mechanisms of action in treating OUD.

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.

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.

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond

Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10-9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.

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.

Substance use and common contributors to morbidity: A genetics perspective

Excessive substance use and substance use disorders (SUDs) are common, serious and relapsing medical conditions. They frequently co-occur with other diseases that are leading contributors to disability worldwide. While heavy substance use may potentiate the course of some of these illnesses, there is accumulating evidence suggesting common genetic architectures. In this narrative review, we focus on four heritable medical conditions - cardiometabolic disease, chronic pain, depression and COVID-19, which are commonly overlapping with, but not necessarily a direct consequence of, SUDs. We find persuasive evidence of underlying genetic liability that predisposes to both SUDs and chronic pain, depression, and COVID-19. For cardiometabolic disease, there is greater support for a potential causal influence of problematic substance use. Our review encourages de-stigmatization of SUDs and the assessment of substance use in clinical settings. We assert that identifying shared pathways of risk has high translational potential, allowing tailoring of treatments for multiple medical conditions. FUNDING: SSR acknowledges T29KT0526, T32IR5226 and DP1DA054394; RLK acknowledges AA028292; AA acknowledges DA054869 & K02DA032573. The funders had no role in the conceptualization or writing of the paper.

Strong and weak cross-inheritance of substance use disorders in a nationally representative sample

Substance use disorders (SUDs) are moderately to highly heritable and are in part cross-transmitted genetically, as observed in twin and family studies. We performed exome-focused genotyping to examine the cross-transmission of four SUDs: alcohol use disorder (AUD, n = 4487); nicotine use disorder (NUD, n = 4394); cannabis use disorder (CUD, n = 954); and nonmedical prescription opioid use disorder (NMPOUD, n = 346) within a large nationally representative sample (n = 36,309), the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III). All diagnoses were based on in-person structured psychiatric interview (AUDADIS-5). SUD cases were compared alone and together to 3959 "super controls" who had neither a SUD nor a psychiatric disorder using an exome-focused array assaying 363,496 SNPs, yielding a representative view of within-disorder and cross-disorder genetic influences on SUDs. The 29 top susceptibility genes for one or more SUDs overlapped highly with genes previously implicated by GWAS of SUD. Polygenic scores (PGS) were computed within the European ancestry (EA) component of the sample (n = 12,505) using summary statistics from each of four clinically distinct SUDs compared to the 3959 "super controls" but then used for two distinctly different purposes: to predict SUD severity (mild, moderate, or severe) and to predict each of the other 3 SUDs. Our findings based on PGS highlight shared and unshared genetic contributions to the pathogenesis of SUDs, confirming the strong cross-inheritance of AUD and NUD as well as the distinctiveness of inheritance of opioid use disorder.

Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry

The growing prevalence of opioid use disorder (OUD) constitutes an urgent health crisis. Ample evidence indicates that risk for OUD is heritable. As a surrogate (or proxy) for OUD, we explored the genetic basis of using prescription opioids 'not as prescribed'. We hypothesized that misuse of opiates might be a heritable risk factor for OUD. To test this hypothesis, we performed a genome-wide association study (GWAS) of problematic opioid use (POU) in 23andMe research participants of European ancestry (N = 132,113; 21% cases). We identified two genome-wide significant loci (rs3791033, an intronic variant of KDM4A; rs640561, an intergenic variant near LRRIQ3). POU showed positive genetic correlations with the two largest available GWAS of OUD and opioid dependence (r_g = 0.64, 0.80, respectively). We also identified numerous additional genetic correlations with POU, including alcohol dependence (r_g = 0.74), smoking initiation (r_g = 0.63), pain relief medication intake (r_g = 0.49), major depressive disorder (r_g = 0.44), chronic pain (r_g = 0.42), insomnia (r_g = 0.39), and loneliness (r_g = 0.28). Although POU was positively genetically correlated with risk-taking (r_g = 0.38), conditioning POU on risk-taking did not substantially alter the magnitude or direction of these genetic correlations, suggesting that POU does not simply reflect a genetic tendency towards risky behavior. Lastly, we performed phenome- and lab-wide association analyses, which uncovered additional phenotypes that were associated with POU, including respiratory failure, insomnia, ischemic heart disease, and metabolic and blood-related biomarkers. We conclude that opioid misuse can be measured in population-based cohorts and provides a cost-effective complementary strategy for understanding the genetic basis of OUD.