Genotype patterns that contribute to increased risk for or protection from developing heroin addiction

OPRM1 Gene Polymorphism in Women with Alcohol Use Disorder

The main aims of the present study were to explore the relationship of the OPRM1 gene rs1074287 polymorphism in alcohol-dependent women with their personality traits and to try to find out whether any specific features may influence alcohol cravings and be a prognostic for alcohol dependency and treatment in AUD women. Our study found a notable correlation between openness and the interaction of the ORIM1 gene and AUD. The alcohol use disorder subjects with genotype AG showed a higher level of openness compared to the control group with genotypes AG (p = 0.0001) and AA (p = 0.0125). The alcohol use disorder subjects with the AA genotype displayed higher levels of openness than the control group with genotype AG (p = 0.0271). However, the alcohol use disorder subjects with the AA genotype displayed lower levels of openness than the control group with genotype GG (p = 0.0212). Our study indicates that openness as a personality trait is correlated with the OPRM1 gene rs1074287 polymorphism in alcohol-dependent women. These are the first data and results exploring such a relationship between opioid and alcohol pathways and the mental construction of AUD women. Personality traits such as openness to experience and neuroticism might play major roles in the addiction mechanism, especially in genetically predisposed females, independent of the reward system involved in the emotional disturbances that coexist with anxiety and depression.

Mysterious long noncoding RNAs and their relationships to human disease

Increasingly studies have shown that the formation mechanism of many human diseases is very complex, which is determined by environmental factors and genetic factors rather than fully following Mendel's genetic law of inheritance. Long non-coding RNA (lncRNA) is a class of endogenous non-protein coding RNA with a length greater than 200 nt, which has attracted much attention in recent years. Studies have shown that lncRNAs have a wide range of biological functions, such as roles in gene imprinting, cell cycle progression, apoptosis, senescence, cell differentiation, and stress responses, and that they regulate the life processes of mammals at various levels, such as epigenetic transcription, processing, modification, transport, translation and degradation. Analyzing the characteristics of lncRNAs and revealing their internal roles can not only deepen our understanding of human physiological and pathological processes, but also provide new ideas and solutions for the diagnosis, prevention and treatment of some diseases. This article mainly reviews the biological characteristics of lncRNAs and their relationship with some diseases, so as to provide references for the related research of lncRNAs.

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.

Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach

Background

The malaria risk prediction is currently limited to using advanced statistical methods, such as time series and cluster analysis on epidemiological data. Nevertheless, machine learning models have been explored to study the complexity of malaria through blood smear images and environmental data. However, to the best of our knowledge, no study analyses the contribution of Single Nucleotide Polymorphisms (SNPs) to malaria using a machine learning model. More specifically, this study aims to quantify an individual's susceptibility to the development of malaria by using risk scores obtained from the cumulative effects of SNPs, known as weighted genetic risk scores (wGRS).

Results

We proposed an SNP-based feature extraction algorithm that incorporates the susceptibility information of an individual to malaria to generate the feature set. However, it can become computationally expensive for a machine learning model to learn from many SNPs. Therefore, we reduced the feature set by employing the Logistic Regression and Recursive Feature Elimination (LR-RFE) method to select SNPs that improve the efficacy of our model. Next, we calculated the wGRS of the selected feature set, which is used as the model's target variables. Moreover, to compare the performance of the wGRS-only model, we calculated and evaluated the combination of wGRS with genotype frequency (wGRS + GF). Finally, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and Ridge regression algorithms are utilized to establish the machine learning models for malaria risk prediction.

Conclusions

Our proposed approach identified SNP rs334 as the most contributing feature with an importance score of 6.224 compared to the baseline, with an importance score of 1.1314. This is an important result as prior studies have proven that rs334 is a major genetic risk factor for malaria. The analysis and comparison of the three machine learning models demonstrated that LightGBM achieves the highest model performance with a Mean Absolute Error (MAE) score of 0.0373. Furthermore, based on wGRS + GF, all models performed significantly better than wGRS alone, in which LightGBM obtained the best performance (0.0033 MAE score).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04870-0.

Leveraging Mann-Whitney U test on large-scale genetic variation data for analysing malaria genetic markers

Background

The malaria risk analysis of multiple populations is crucial and of great importance whilst compressing limitations. However, the exponential growth in diversity and accumulation of genetic variation data obtained from malaria-infected patients through Genome-Wide Association Studies opens up unprecedented opportunities to explore the significant differences between genetic markers (risk factors), particularly in the resistance or susceptibility of populations to malaria risk. Thus, this study proposes using statistical tests to analyse large-scale genetic variation data, comprising 20,854 samples from 11 populations within three continents: Africa, Oceania, and Asia.

Methods

Even though statistical tests have been utilized to conduct case–control studies since the 1950s to link risk factors to a particular disease, several challenges faced, including the choice of data (ordinal vs. non-ordinal) and test (parametric vs. non-parametric). This study overcomes these challenges by adopting the Mann–Whitney U test to analyse large-scale genetic variation data; to explore the statistical significance of markers between populations; and to further identify the highly differentiated markers.

Results

The findings of this study revealed a significant difference in the genetic markers between populations (p < 0.01) in all the case groups and most control groups. However, for the highly differentiated genetic markers, a significant difference (p < 0.01) was present for most genetic markers with varying p-values between the populations in the case and control groups. Moreover, several genetic markers were observed to have very significant differences (p < 0.001) across all populations, while others exist between certain specific populations. Also, several genetic markers have no significant differences between populations.

Conclusions

These findings further support that the genetic markers contribute differently between populations towards malaria resistance or susceptibility, thus showing differences in the likelihood of malaria infection. In addition, this study demonstrated the robustness of the Mann–Whitney U test in analysing genetic markers in large-scale genetic variation data, thereby indicating an alternative method to explore genetic markers in other complex diseases. The findings hold great promise for genetic markers analysis, and the pipeline emphasized in this study can fully be reproduced to analyse new data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04104-x.

Bidirectional influence of heroin and cocaine escalation in persons with dual opioid and cocaine dependence diagnoses

Persons with dual severe opioid and cocaine use disorders are at risk of considerable morbidity, and the bidirectional relationship of escalation of mu-opioid agonists and cocaine use is not well understood. The aim of this study was to examine the bidirectional relationship between escalation of heroin and cocaine use in volunteers dually diagnosed with opioid and cocaine dependence (OD + CD). Volunteers from New York with OD + CD (total n = 295; male = 182, female = 113; age ≥ 18 years) were interviewed with the Structured Clinical Interview for the DSM-IV Axis I Disorders and Kreek-McHugh-Schluger-Kellogg scales for dimensional measures of drug exposure, which also collect ages of 1st use and onset of heaviest use. Time of escalation was defined as age of onset of heaviest use minus age of 1st use in whole years. Times of escalation of heroin and cocaine were positively correlated in both men (Spearman r = .34, 95% confidence interval [CI: .17, .48], p < .0001) and women (Spearman r = .51, [.27, .50], p < .0001) volunteers. After we adjusted for demographic variables, a Cox regression showed that time of cocaine escalation was a predictor of time of heroin escalation (hazard ratio [HR] = 0.97, 95% CI [0.95, 0.99], p = .003). Another Cox regression showed that this relationship is bidirectional, because time of heroin escalation was also a predictor of time of cocaine escalation (HR = 0.98, [0.96-0.99], p = .016). In these adjusted models, gender was not a significant predictor of time of escalation of either heroin or cocaine. Therefore, escalation did not differ robustly by gender when adjusting for demographics and other major variables. Overall, rapid escalation of cocaine use was a predictor of rapid escalation of heroin use, and vice versa, in persons with dual severe opioid and cocaine use disorders. These findings suggest a shared vulnerability to rapid escalation of these 2 drugs in persons with dual severe opioid and cocaine use disorders. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Pharmacogenetics of Addiction Therapy

Drug addiction is a serious relapsing disease that has high costs to society and to the individual addicts. Treatment of these addictions is still in its nascency, with only a few examples of successful therapies. Therapeutic response depends upon genetic, biological, social, and environmental components. A role for genetic makeup in the response to treatment has been shown for several addiction pharmacotherapies with response to treatment based on individual genetic makeup. In this chapter, we will discuss the role of genetics in pharmacotherapies, specifically for cocaine, alcohol, and opioid dependences. The continued elucidation of the role of genetics should aid in the development of new treatments and increase the efficacy of existing treatments.

Epigenetic and Genetic Factors Associated With Opioid Use Disorder: Are These Relevant to African American Populations

In the United States, the number of people suffering from opioid use disorder has skyrocketed in all populations. Nevertheless, observations of racial disparities amongst opioid overdose deaths have recently been described. Opioid use disorder is characterized by compulsive drug consumption followed by periods of withdrawal and recurrent relapses while patients are participating in treatment programs. Similar to other rewarding substances, exposure to opioid drugs is accompanied by epigenetic changes in the brain. In addition, genetic factors that are understudied in some racial groups may also impact the clinical manifestations of opioid use disorder. These studies are important because genetic factors and epigenetic alterations may also influence responses to pharmacological therapeutic approaches. Thus, this mini-review seeks to briefly summarize what is known about the genetic bases of opioid use disorder in African Americans.

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

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

Age of onset of heaviest use of cannabis or alcohol in persons with severe opioid or cocaine use disorders

BACKGROUND

Persons with severe opioid or cocaine use disorders are particularly vulnerable to morbidity and mortality. Heaviest use of mu-opioid receptor agonists and cocaine typically commences in early adulthood and is preceded by substantial adolescent exposure to cannabis and/or alcohol. Little information exists on the age trajectories of exposure to cannabis or alcohol in persons diagnosed with severe opioid or cocaine use disorders, compared to persons diagnosed with other substance use disorders (unrelated to opioids or cocaine).

METHOD

This observational study had n = 854 volunteers (male = 581, female = 273; ≥18 years of age at the time of interview) and examined the ages of onset of heaviest use of cannabis and alcohol in persons diagnosed by DSM-IV criteria with opioid dependence (OD), both opioid and cocaine dependence (OD + CD) and cocaine dependence (CD). These age trajectory measures were compared to persons with other substance use disorders (primarily cannabis and alcohol use disorders, termed "Any Other Diagnoses").

RESULTS

Unadjusted survival analyses showed persons diagnosed with either OD + CD or CD had earlier onset of heaviest use of cannabis (mean ages of 16.2 and 17.8, respectively) compared to the "Any Other Diagnoses" reference group (mean age = 19.5). A multivariate logistic regression showed that later onset of heaviest use of cannabis was associated with lower odds of being in the OD + CD or CD groups, when compared to the reference group.

CONCLUSIONS

Persons diagnosed with severe cocaine use disorders or dual opioid and cocaine use disorders exhibit a pattern of heavy and especially early adolescent exposure to cannabis, compared to persons with other substance use disorders.

Prolonged Withdrawal From Escalated Oxycodone Is Associated With Increased Expression of Glutamate Receptors in the Rat Hippocampus

People suffering from opioid use disorder (OUD) exhibit cognitive dysfunctions. Here, we investigated potential changes in the expression of glutamate receptors in rat hippocampi at 2 h and 31 days after the last session of oxycodone self-administration (SA). RNA extracted from the hippocampus was used in quantitative polymerase chain reaction analyses. Rats, given long-access (9 h per day) to oxycodone (LgA), took significantly more drug than rats exposed to short-access (3 h per day) (ShA). In addition, LgA rats could be further divided into higher oxycodone taking (LgA-H) or lower oxycodone taking (LgA-L) groups, based on a cut-off of 50 infusions per day. LgA rats, but not ShA, rats exhibited incubation of oxycodone craving. In addition, LgA rats showed increased mRNA expression of GluA1-3 and GluN2a-c subunits as well as Grm3, Grm5, Grm6, and Grm8 subtypes of glutamate receptors after 31 days but not after 2 h of stopping the SA experiment. Changes in GluA1-3, Grm6, and Grm8 mRNA levels also correlated with increased lever pressing (incubation) after long periods of withdrawal from oxycodone. More studies are needed to elucidate the molecular mechanisms involved in altering the expression of these receptors during withdrawal from oxycodone and/or incubation of drug seeking.

The molecular neurobiology and neuropathology of opioid use disorder

The number of people diagnosed with opioid use disorder has skyrocketed as a consequence of the opioid epidemic and the increased prescribing of opioid drugs for chronic pain relief. Opioid use disorder is characterized by loss of control of drug taking, continued drug use in the presence of adverse consequences, and repeated relapses to drug taking even after long periods of abstinence. Patients who suffer from opioid use disorder often present with cognitive deficits that are potentially secondary to structural brain abnormalities that vary according to the chemical composition of the abused opioid. This review details the neurobiological effects of oxycodone, morphine, heroin, methadone, and fentanyl on brain neurocircuitries by presenting the acute and chronic effects of these drugs on the human brain. In addition, we review results of neuroimaging in opioid use disorder patients and/or histological studies from brains of patients who had expired after acute intoxication following long-term use of these drugs. Moreover, we include relevant discussions of the neurobiological mechanisms involved in promoting abnormalities in the brains of opioid-exposed patients. Finally, we discuss how novel strategies could be used to provide pharmacological treatment against opioid use disorder.

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Brain abnormalities caused by opioid intoxication.

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Intoxication of opioids leads to defects in brain neurocircuitries.

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Insight into the molecular mechanisms associated with craving in heroin addicts.

Genetic implications in quality palliative care and preventing opioid crisis in cancer-related pain management

The prevalence of cancer-related pain is 64% among patients with metastatic, advanced, or terminal cancer, 59% among patients undergoing anticancer treatment, and 33% among patients who completed curative treatment. According to the World Health Organization cancer pain relief guidelines, opioid analgesics are the mainstay analgesic therapy in addition to conventional first-step analgesics, such as non-steroidal anti-inflammatory drugs and acetaminophen. The indications for strong opioids have recently been expanded to include mild-to-moderate pain in addition to moderate-to-severe pain. The U.S. Centers for Disease Control and Prevention guidelines emphasize that realistic expectations should be weighed against potential serious harm from opioids, rather than relying on the unrealized long-term benefits of these drugs. Therefore, treatment strategies for both cancer-related chronic or acute pain have been unfortunately deviated from opioid analgesics. The barriers hindering adequate cancer-related pain management with opioid analgesics are related to the inadequate knowledge of opioid analgesics (e.g., effective dose, adverse effects, and likelihood of addiction or tolerance). To achieve adequate opioid availability, these barriers should be overcome in a clinically suitable manner. Genetic assessments could play an important role in overcoming challenges in opioid management. To balance the improvement in opioid availability and the prevention of opioid misuse and addiction, the following two considerations concerning opioids and genetic polymorphisms warrant attention: (A) pain severity, opioid sensitivity, and opioid tolerance; and (B) vulnerability to opioid dependence and addiction.

A single nucleotide polymorphism in OPRM1(rs483481) and risk for heroin use disorder

Opioid receptor mu1 (OPRM1) is the target of many opioid drugs, and it is known to have affinity toward both endogenous and exogenous opioids, opiate and opioid analgesic drugs. The present study was undertaken to explore association of single nucleotide polymorphisms (SNPs) in the OPRM1 gene with heroin use disorder. Ten OPRM1 polymorphisms were analyzed in 132 cases and 147 healthy controls. The SNP rs483481 showed significant allelic, genotypic and haplotypic association (Allelic: p-value = 0.003, OR = 1.75, CI = 1.21-2.55) (Genotypic: p-value = 0.003, OR = 1.72, CI = 1.08-2.75) with heroin use disorder. Allelic and genotypic association remained significant even after multiple testing corrections with 1000 permutations. A significant positive correlation between 'Number of times drug abstained' and 'rs483481-AA genotype' (p-value = 0.002; Pearson correlation = 0.265) was also observed. One-way ANOVA analysis demonstrated significant association of rs483481 with 'number of times drug abstained' (F = 4.86, p-value =0.009). 'A' allele and 'AA' genotype of marker rs483481 seem to confer protective effect while 'G' allele and 'GG' genotype potentiates risk for heroin use disorder. OPRM1 is found to be associated with heroin use disorder in the studied Manipuri cohort. The study suggests that individuals with G allele and GG genotypes at rs483481 could be more vulnerable to heroin dependence, and it could be taken into consideration in prevention and intervention programs.

Pharmacogenomics of Pain Management: The Impact of Specific Biological Polymorphisms on Drugs and Metabolism

PURPOSE OF REVIEW

Pain is multifactorial and complex, often with a genetic component. Pharmacogenomics is a relative new field, which allows for the development of a truly unique and personalized therapeutic approach in the treatment of pain.

RECENT FINDINGS

Until recently, drug mechanisms in humans were determined by testing that drug in a population and calculating response averages. However, some patients will inevitably fall outside of those averages, and it is nearly impossible to predict who those outliers might be. Pharmacogenetics considers a patient's unique genetic information and allows for anticipation of that individual's response to medication. Pharmacogenomic testing is steadily making progress in the management of pain by being able to identify individual differences in the perception of pain and susceptibility and sensitivity to drugs based on genetic markers. This has a huge potential to increase efficacy and reduce the incidence of iatrogenic drug dependence and addiction. The streamlining of relevant polymorphisms of genes encoding receptors, transporters, and drug-metabolizing enzymes influencing the pain phenotype can be an important guide to develop safe new strategies and approaches to personalized pain management. Additionally, some challenges still prevail and preclude adoption of pharmacogenomic testing universally. These include lack of knowledge about pharmacogenomic testing, inadequate standardization of the process of data handling, questionable benefits about the clinical and financial aspects of pharmacogenomic testing-guided therapy, discrepancies in clinical evidence supporting these tests, and doubtful reimbursement of the tests by health insurance agencies.

Escalated Oxycodone Self-Administration and Punishment: Differential Expression of Opioid Receptors and Immediate Early Genes in the Rat Dorsal Striatum and Prefrontal Cortex

Opioid use disorder (OUD) is characterized by compulsive drug taking despite adverse life consequences. Here, we sought to identify neurobiological consequences associated with the behavioral effects of contingent footshocks administered after escalation of oxycodone self-administration. To reach these goals, Sprague-Dawley rats were trained to self-administer oxycodone for 4 weeks and were then exposed to contingent electric footshocks. This paradigm helped to dichotomize rats into two distinct behavioral phenotypes: (1) those that reduce lever pressing (shock-sensitive) and (2) others that continue lever pressing (shock-resistant) for oxycodone during contingent punishment. The rats were euthanized at 2-h after the last oxycodone plus footshock session. The dorsal striata and prefrontal cortices were dissected for use in western blot and RT-qPCR analyses. All oxycodone self-administration rats showed significant decreased expression of Mu and Kappa opioid receptor proteins only in the dorsal striatum. However, expression of Delta opioid receptor protein was decreased in both brain regions. RT-qPCR analyses documented significant decreases in the expression of c-fos, fosB, fra2, junB, egr1, and egr2 mRNAs in the dorsal striatum (but not in PFC) of the shock-sensitive rats. In the PFC, junD expression was reduced in both phenotypes. However, egr3 mRNA expression was increased in the PFC of only shock-resistant rats. These results reveal that, similar to psychostimulants and alcohol, footshocks can dichotomize rats that escalated their intake of oxycodone into two distinct behavioral phenotypes. These animals also show significant differences in the mRNA expression of immediate early genes, mainly, in the dorsal striatum. The increases in PFC egr3 expression in the shock-resistant rats suggest that Egr3 might be involved in the persistence of oxycodone-associated memory under aversive conditions. This punishment-driven model may help to identify neurobiological substrates of persistent oxycodone taking and abstinence in the presence of adverse consequences.

Haplotype-Based Association and In Silico Studies of OPRM1 Gene Variants with Susceptibility to Opioid Dependence Among Addicted Iranians Undergoing Methadone Treatment

The associations of OPRM1 gene variants with opioid dependence have been demonstrated. This study investigated the association of rs495491, rs1799971 (A118G), rs589046, and rs10457090 variants of OPRM1 gene with opium dependence and their haplotypes among addicted individuals undergoing methadone treatment. Moreover, we investigated whether any of these variants were associated with libido dysfunction or insomnia among addicted people. A total of 404 individuals were genotyped by amplification refractory mutation system (ARMS) PCR. In silico studies were designed through homology modeling of A118G structures (N40 and D40) and docked with 41 FDA-approved drugs of OPRM1 protein by SWISS-MODEL, COACH, MolProbity, ProSA, Errat, Glide XP, and Autodock 4. Results revealed that rs495491, A118G, rs589046, and rs10457090 were significantly associated with opium dependence under recessive (P = 6.66E-10), dominant (P = 0.017), co-dominant (P = 0.001), and recessive (P = 9.28E-6) models of inheritance, respectively. Further analyses indicated three significant haplotypes including A-A-A-C (P-permutation < 1E-9), G-G-A-C (P-permutation = 0.04), and G-A-G-C (P-permutation = 8.69E-4). Genotype-phenotype associations of OPRM1 variants with insomnia and libido dysfunction showed no significant association. Docking showed the higher binding affinity of N40 rather than D40 model; however, methadone and morphine were bonded with D40 structure more powerful. Consequently, rs495491, A118G, rs589046, and rs10457090 were associated with opioid dependence among Iranians; also, A118G might be the most remarkable marker of OPRM1 owing to its vital structural roles.

VMAT2 gene (SLC18A2) variants associated with a greater risk for developing opioid dependence

Aim: To determine if selected serotonergic and noradrenergic gene variants are associated with heroin addiction. Subjects & methods: A total of 126 variants in 19 genes in subjects with Dutch European ancestry from The Netherlands. Subjects included 281 opioid-dependent volunteers in methadone maintenance or heroin-assisted treatment, 163 opioid-exposed but not opioid-dependent volunteers who have been using illicit opioids but never became opioid-dependent and 153 healthy controls. Results: Nominal associations were indicated for 20 variants in six genes including an experiment-wise significant association from the combined effect of three SLC18A2 SNPs (rs363332, rs363334 and rs363338) with heroin dependence (p_final = 0.047). Conclusion: Further studies are warranted to confirm and elucidate the role of these variants in the vulnerability to opioid addiction.

Regulation of microRNA-29c in the nucleus accumbens modulates methamphetamine -induced locomotor sensitization in mice

Changes in microRNA (miRNA)-mediated gene expression in the nucleus accumbens (NAc) may play important roles in regulating drug addiction. MiR-29c is a highly expressed miRNA in the human and rodent nervous systems where it plays a broad regulatory role. As the first step towards investigating potential functions of miR-29c in methamphetamine (METH) addiction, we used C57BL/6 mice in a model of METH-induced locomotor sensitization. We measured miR-29c expression changes in the NAc of the mice after repeated-intermittent METH exposure and acute METH administration respectively by using quantitative real-time PCR (qPCR). We found that miR-29c expression was significantly down-regulated in the NAc of METH-sensitized mice but not in the acute METH-treated mice. Then, we tested the respective effects of miR-29c over-expression and inhibition in the NAc on METH-induced locomotor sensitization. To reach this goal, we constructed adeno-associated virus (AAV)-expressing miR-29c (AAV-miR-29c) and its corresponding inhibitor - tough decoy (AAV-anti-miR-29c TuD) to over-express and inhibit miR-29c, respectively. We found that AAV-miR-29c over-expression in the NAc enhanced METH-induced locomotor sensitization, whereas AAV inhibition of miR-29c expression in the NAc attenuated the effects of METH. Moreover, we observed the participation of Dnmt3a, Dnmt3b, and Meg3 in the effects of miR-29c on METH sensitization. Our results suggest that miR-29c is an important epigenetic regulator of METH-induced behavioural sensitization and changes in gene expression. These data further suggest a potential role of miR-29c in regulating long-term METH-induced adaptation in the brain.

OPRD1 gene affects disease vulnerability and environmental stress in patients with heroin dependence in Han Chinese

Exposure to stress not only increases the vulnerability to heroin dependence (HD) but also provokes relapse. The etiology of HD and the role of life stress remain unclear, but prior studies suggested that both genetic and environmental factors are important. Opioid related genes, including OPRM1, OPRD1, OPRK1, and POMC, are obvious candidates for HD. Therefore, this study was conducted to explore whether the genetic polymorphisms of the candidates could affect vulnerability to HD and response to life stress in patients with HD. Ten polymorphisms of the opioid related genes were analyzed in 801 patients and 530 controls. The Life Event Questionnaire was used to assess the perspective and response to life stress in the past year. The genotype distribution and allelic frequency analyses showed that the minor C allele of rs2234918 in OPRD1 is over-represented in the HD group (P = .006 and P = .002, respectively). This finding was further confirmed by logistic regression analysis, showing that C allele carriers have a 1.42 times greater risk for HD compared to T/T homozygotes. A subgroup of 421 patients and 135 controls were eligible for life stress assessment. Patients with HD have a higher occurrence of negative events (No), negative events score (Ns), and average negative event score (Na) than those of controls (all P < .001), but there was no difference regarding positive recent events between the two groups. Gene-stress assessment in the HD group showed that T/T homozygotes of OPRD1 rs2236857 have more severe stress than C allele carriers (Ns, P = .004 and Na, P = .047). Our results indicate that the OPRD1 gene may not only play a role in the pathogenesis of HD but also affect the response to life stress among patients with HD in our Han Chinese population. Patients with the risk genotype may need additional psychosocial intervention for relapse prevention.

Genetic Markers in Psychiatry

Psychiatric disorders such as addiction (substance use and addictive disorders), depression, eating disorders, schizophrenia, and post-traumatic stress disorder (PTSD) are severe, complex, multifactorial mental disorders that carry a high social impact, enormous public health costs, and various comorbidities as well as premature morbidity. Their neurobiological foundation is still not clear. Therefore, it is difficult to uncover new set of genes and possible genetic markers of these disorders since the understanding of the molecular imbalance leading to these disorders is not complete. The integrative approach is needed which will combine genomics and epigenomics; evaluate epigenetic influence on genes and their influence on neuropeptides, neurotransmitters, and hormones; examine gene × gene and gene × environment interplay; and identify abnormalities contributing to development of these disorders. Therefore, novel genetic approaches based on systems biology focused on improvement of the identification of the biological underpinnings might offer genetic markers of addiction, depression, eating disorders, schizophrenia, and PTSD. These markers might be used for early prediction, detection of the risk to develop these disorders, novel subtypes of the diseases and tailored, personalized approach to therapy.

Molecular Genetics and New Medication Strategies for Opioid Addiction

The opioid epidemic is at the epicenter of the drug crisis, resulting in an inconceivable number of overdose deaths and exorbitant associated medical costs that have crippled many communities across the socioeconomic spectrum in the United States. Classic medications for the treatment of opioid use disorder predominantly target the opioid system and thus have been underutilized, in part due to their own potential for abuse and heavy regulatory burden for patients and clinicians. Opioid antagonists are now evolving in their use, not only to prevent acute overdoses but as extended-use treatment options. Strategies that target specific genetic and epigenetic factors, along with novel nonopioid medications, hold promise as future therapeutic interventions for opioid abuse. Success in increasing the treatment options in the clinical toolbox will, hopefully, help to end the historical pattern of recurring opioid epidemics. [AJP at 175: Remembering Our Past As We Envision Our Future Drug Addiction in Relation to Problems of Adolescence Zimmering and colleagues wrote in the midst of an opiate epidemic among young people that "only the human being, or rather certain types of human beings, will return to the enslaving, self-destructive habit." (Am J Psychiatry 1952; 109:272-278 )].

A review of opioid addiction genetics

Opioid use disorder (OUD) affects millions of people worldwide and the risk of developing the disorder has a significant genetic component according to twin and family studies. Identification of the genetic variants underlying this inherited risk has focused on two different methods: candidate gene studies and genome-wide association studies (GWAS). The most studied candidate genes have included the mu-opioid receptor (OPRM1), the delta-opioid receptor (OPRD1), the dopamine D2 receptor (DRD2), and brain-derived neurotrophic factor (BDNF). Variants in these genes have been associated with relatively small, but reproducible, effects on OUD risk. More recently, GWAS have identified potential associations with variants in KCNG2, KCNC1, CNIH3, APBB2, and RGMA. In total the genetic associations identified so far explain only a small portion of OUD risk. GWAS of OUD is still in the early stages when compared to studies of other psychiatric disorders, such as schizophrenia, which have found many relevant variants with small effect sizes only after large meta-analyses. Substantial increases in cohort sizes will likely be necessary in the OUD field to achieve similar results. In addition, it will be important for future studies of OUD to incorporate rare variants, epigenetics, and gene × environment interactions into models in order to better explain the observed heritability.

Contribution of Genetic Polymorphisms and Haplotypes in DRD2, BDNF, and Opioid Receptors to Heroin Dependence and Endophenotypes Among the Han Chinese

Heroin and drug dependence are major contributors to global health burden worldwide, but their underlying mechanisms remain elusive and may vary from population to population. Reward- and memory-related candidate genes dopamine D2 receptor (DRD2) and brain-derived neurotrophic factor (BDNF), as well as the opioid receptor genes (OPRM1, OPRD1, and OPRK1), have been implicated in drug dependence, but relatively little is known on their contributions to heroin dependence in populations worldwide. Hence, we evaluated the contributions of the above five candidate genes in heroin dependence and several important related endophenotypes (the onset age of heroin use and subjective response to first heroin use), at single single-nucleotide polymorphism as well as haplotype levels, in a Han Chinese population sample. We genotyped 546 unrelated and heroin-dependent subjects for the candidate genes noted, and 228 sex- and age-matched unrelated controls. The G allele of rs4654327 (OPRD1), DRD2 haplotype block CCGCCGTT (rs6277-rs1076560-rs2283265-rs2734833-rs2075652-rs1079596-rs4436578-rs11214607), and OPRD1 haplotypes TACG (rs6669447-rs2236857-rs508448-rs4654327), CG (rs508448-rs4654327), and TG (rs6669447-rs4654327) were significantly associated with heroin dependence phenotype. Homozygotes AA at rs6265 (BDNF), TT at rs16917234 (BDNF), and CC at rs508448 (OPRD1) also appeared as risk factors for the endophenotype earlier age of onset for heroin use. Two OPRM1 haplotypes, AG (rs1799971-rs1381376) and AT (rs1799971-rs3778151), were observed as potential protective factors. These emerging findings contribute to the literature on genetic biomarkers of drug dependence and related endophenotypes, and call for replication in independent population.

Human Genetics of Addiction: New Insights and Future Directions

PURPOSE OF REVIEW

With the advent of the genome-wide association study (GWAS), our understanding of the genetics of addiction has made significant strides forward. Here, we summarize genetic loci containing variants identified at genome-wide statistical significance (P < 5 × 10-8) and independently replicated, review evidence of functional or regulatory effects for GWAS-identified variants, and outline multi-omics approaches to enhance discovery and characterize addiction loci.

RECENT FINDINGS

Replicable GWAS findings span 11 genetic loci for smoking, eight loci for alcohol, and two loci for illicit drugs combined and include missense functional variants and noncoding variants with regulatory effects in human brain tissues traditionally viewed as addiction-relevant (e.g., prefrontal cortex [PFC]) and, more recently, tissues often overlooked (e.g., cerebellum). GWAS analyses have discovered several novel, replicable variants contributing to addiction. Using larger sample sizes from harmonized datasets and new approaches to integrate GWAS with multiple 'omics data across human brain tissues holds great promise to significantly advance our understanding of the biology underlying addiction.

Genetic variation in the exome: Associations with alcohol and tobacco co-use

Shared genetic factors represent one underlying mechanism thought to contribute to high rates of alcohol and tobacco co-use and dependence. Common variants identified by molecular genetic studies tend to confer only small disease risk, and rare protein-coding variants are posited to contribute to disease risk, as well. However, given that genotyping technologies allowing for their inclusion in association studies have only recently become available, the magnitude of their contribution is poorly understood. The current study examined genetic variation in protein-coding regions (i.e., the exome) for associations with measures of lifetime alcohol and tobacco co-use. Participants from the UCSF Family Alcoholism Study (N = 1,862) were genotyped using an exome-focused genotyping array, and assessed for DSM-IV diagnoses of alcohol and tobacco dependence and quantitative consumption measures using a modified version of the Semi-Structured Assessment for the Genetics of Alcoholism. Analyses included single variant, gene-based, and pathway-based tests of association. One EMR3 variant and a pathway related to genes upregulated in mesenchymal stem cells during the late phase of adipogenesis met criteria for statistical significance. Suggestive associations were consistent with previous findings from studies of substance use and dependence, including variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster with cigarettes smoked per day. Further, several variants and genes demonstrated suggestive association across phenotypes, suggesting that shared genetic factors may underlie risk for increased levels of alcohol and tobacco use, as well as psychopathology more broadly, providing insight into our understanding of the genetic architecture underlying these traits. (PsycINFO Database Record

Biochemical Diagnosis in Substance and Non-substance Addiction

An optimal biochemical marker for addiction would be some easily traced molecules in body specimens, which indicates indulgent addictive behaviors, or susceptibility to certain addictive stimuli. In this chapter, we discussed existing literature about possible biomarkers, and classified them into three categories: origin forms and metabolites of substances, markers from biochemical responses to certain addiction, and genetic and epigenetic biomarkers suggesting susceptibility to addiction. In every category, we examined studies concerning certain type of addiction one by one, with focuses mainly on opiates, psychostimulants, and pathological gambling. Several promising molecules were highlighted, including those of neurotrophic factors, inflammatory factors, and indicators of vascular injury, and genetic and epigenetic biomarkers such as serum miRNAs. DNA methylation signatures and signal nucleotide polymorphism of candidate gene underlying the addiction.

Genome-Wide Association of Heroin Dependence in Han Chinese

Drug addiction is a costly and recurring healthcare problem, necessitating a need to understand risk factors and mechanisms of addiction, and to identify new biomarkers. To date, genome-wide association studies (GWAS) for heroin addiction have been limited; moreover they have been restricted to examining samples of European and African-American origin due to difficulty of recruiting samples from other populations. This is the first study to test a Han Chinese population; we performed a GWAS on a homogeneous sample of 370 Han Chinese subjects diagnosed with heroin dependence using the DSM-IV criteria and 134 ethnically matched controls. Analysis using the diagnostic criteria of heroin dependence yielded suggestive evidence for association between variants in the genes CCDC42 (coiled coil domain 42; p = 2.8x10^-7) and BRSK2 (BR serine/threonine 2; p = 4.110⁻⁶). In addition, we found evidence for risk variants within the ARHGEF10 (Rho guanine nucleotide exchange factor 10) gene on chromosome 8 and variants in a region on chromosome 20q13, which is gene-poor but has a concentration of mRNAs and predicted miRNAs. Gene-based association analysis identified genome-wide significant association between variants in CCDC42 and heroin addiction. Additionally, when we investigated shared risk variants between heroin addiction and risk of other addiction-related and psychiatric phenotypes using polygenic risk scores, we found a suggestive relationship with variants predicting tobacco addiction, and a significant relationship with variants predicting schizophrenia. Our genome wide association study of heroin dependence provides data in a novel sample, with functionally plausible results and evidence of genetic data of value to the field.

Susceptibility loci for heroin and cocaine addiction in the serotonergic and adrenergic pathways in populations of different ancestry

BACKGROUND

Drug addiction is influenced by genetic factors.

AIM

To determine if genetic variants in the serotonergic and adrenergic pathways are associated with heroin and/or cocaine addiction.

SUBJECTS & METHODS

The study examined 140 polymorphisms in 19 genes in 1855 subjects with predominantly European or African ancestries.

RESULTS

A total of 38 polymorphisms (13 genes) showed nominal associations, including novel associations in S100A10 (p11) and SLC18A2 (VMAT2). The association of HTR3B SNP rs11606194 with heroin addiction in the European ancestry subgroup remained significant after correction for multiple testing (p(corrected) = 0.04).

CONCLUSION

The study strengthens our previous findings of association of polymorphisms in HTR3A, HTR3B and ADRA1A. The study suggests partial overlap in genetic susceptibility between populations of different ancestry and between heroin and cocaine addiction.

A review of pharmacogenetic studies of substance-related disorders

BACKGROUND

Substance-related disorders (SRDs) are a major cause of morbidity and mortality worldwide. Family, twin, and adoption studies have demonstrated the substantial heritability of SRDs. To determine the impact of genetic variation on risk for SRD and the response to treatment, researchers have conducted a number of secondary data analyses and quasi-experimental studies that target one or more candidate gene variants.

METHODS

This review examines studies in which candidate polymorphisms were examined as mediator variables to identify pharmacogenetic effects on subjective responses to drug administration or cues or outcomes of medication trials for SRDs. Efforts to use a meta-analytic approach to quantify these effects are premature because the number of available studies using similar methods and outcomes is limited, so the present review is qualitative.

RESULTS

Findings from these studies provide preliminary evidence of clinically relevant pharmacogenetic effects. However, independent replication of these findings has been sparse.

CONCLUSIONS

Although this growing body of literature has produced conflicting results, improved statistical controls may help to clarify the findings. Additionally, the use of empirically derived sub-phenotypes (i.e., which serve to differentiate distinct groups of affected individuals) may also help to identify genetic mediators of pharmacologic response in relation to SRDs. The identification of genetic mediators can inform clinical care both by identifying risk factors for SRDs and predicting adverse events and therapeutic outcomes associated with specific pharmacotherapies.

Genetics of opiate addiction

Addiction to MOP-r agonists such as heroin (and also addiction to prescription opioids) has reemerged as an epidemic in the twenty first century, causing massive morbidity. Understanding the genetics contributing to susceptibility to this disease is crucial for the identification of novel therapeutic targets, and also for discovery of genetic markers which would indicate relative protection or vulnerability from addiction, and relative responsiveness to pharmacotherapy. This information could thus eventually inform clinical practice. In this review, we focus primarily on association studies of heroin and opiate addiction, and further describe the studies which have been replicated in this field, and are thus more likely to be useful for translational efforts.

Pharmacogenetics of addiction therapy

Drug addiction is a serious relapsing disease that has high costs to society and to the individual addicts. Treatment of these addictions is still in its nascency, with only a few examples of successful therapies. Therapeutic response depends upon genetic, biological, social, and environmental components. A role for genetic makeup in the response to treatment has been shown for several addiction pharmacotherapies. For several addiction pharmacotherapies, response to treatment varies based on individual genetic makeup. In this chapter, we discuss the role of genetics in pharmacotherapies, specifically for cocaine, alcohol, and opioid dependences. The elucidation of the role of genetics should aid in the development of new treatments and increase the efficacy of existing treatments.

Nur transcription factors in stress and addiction

The Nur transcription factors Nur77 (NGFI-B, NR4A1), Nurr1 (NR4A2), and Nor-1 (NR4A3) are a sub-family of orphan members of the nuclear receptor superfamily. These transcription factors are products of immediate early genes, whose expression is rapidly and transiently induced in the central nervous system by several types of stimuli. Nur factors are present throughout the hypothalamus-pituitary-adrenal (HPA) axis where are prominently induced in response to stress. Drugs of abuse and stress also induce the expression of Nur factors in nuclei of the motivation/reward circuit of the brain, indicating their participation in the process of drug addiction and in non-hypothalamic responses to stress. Repeated use of addictive drugs and chronic stress induce long-lasting dysregulation of the brain motivation/reward circuit due to reprogramming of gene expression and enduring alterations in neuronal function. Here, we review the data supporting that Nur transcription factors are key players in the molecular basis of the dysregulation of neuronal circuits involved in chronic stress and addiction.

Personalized medicine and opioid analgesic prescribing for chronic pain: opportunities and challenges

Use of opioid analgesics for pain management has increased dramatically over the past decade, with corresponding increases in negative sequelae including overdose and death. There is currently no well-validated objective means of accurately identifying patients likely to experience good analgesia with low side effects and abuse risk prior to initiating opioid therapy. This paper discusses the concept of data-based personalized prescribing of opioid analgesics as a means to achieve this goal. Strengths, weaknesses, and potential synergism of traditional randomized placebo-controlled trial (RCT) and practice-based evidence (PBE) methodologies as means to acquire the clinical data necessary to develop validated personalized analgesic-prescribing algorithms are overviewed. Several predictive factors that might be incorporated into such algorithms are briefly discussed, including genetic factors, differences in brain structure and function, differences in neurotransmitter pathways, and patient phenotypic variables such as negative affect, sex, and pain sensitivity. Currently available research is insufficient to inform development of quantitative analgesic-prescribing algorithms. However, responder subtype analyses made practical by the large numbers of chronic pain patients in proposed collaborative PBE pain registries, in conjunction with follow-up validation RCTs, may eventually permit development of clinically useful analgesic-prescribing algorithms.

PERSPECTIVE

Current research is insufficient to base opioid analgesic prescribing on patient characteristics. Collaborative PBE studies in large, diverse pain patient samples in conjunction with follow-up RCTs may permit development of quantitative analgesic-prescribing algorithms that could optimize opioid analgesic effectiveness and mitigate risks of opioid-related abuse and mortality.

Low frequency genetic variants in the μ-opioid receptor (OPRM1) affect risk for addiction to heroin and cocaine

The μ-opioid receptor (MOR) binds exogenous and endogenous opioids and is known to mediate the rewarding effects of drugs of abuse. Numerous genetic studies have sought to identify common genetic variation in the gene encoding MOR (OPRM1) that affects risk for drug addiction. The purpose of this study was to examine the contribution of rare coding variants in OPRM1 to the risk for addiction. Rare and low frequency variants were selected using the National Heart Lung and Blood Institute - Exome Sequencing Project (NHLBI-ESP) database, which has screened the exomes of over 6500 individuals. Two SNPs (rs62638690 and rs17174794) were selected for genotyping in 1377 European American individuals addicted to heroin and/or cocaine. Two different SNPs (rs1799971 and rs17174801) were genotyped in 1238 African American individuals addicted to heroin and/or cocaine. Using the minor allele frequencies from the NHLBI-ESP dataset as a comparison group, case-control association analyses were performed. Results revealed an association between rs62638690 and cocaine and heroin addiction in European Americans (p=0.02; 95% C.I. 0.47 [0.24-0.92]). This study suggests a potential role for rare OPRM1 variants in addiction disorders and highlights an area worthy of future study.

Challenging false discovery rate: a partition test based on p values in human case-control association studies

BACKGROUND/AIMS

We consider the situation that multiple genetic variants are underlying a heritable trait and assume that each contributes to the trait only to a small degree. The aim is to develop a statistical test for disease association of these multiple variants.

METHODS

We expect that p values resulting from a genome-wide case-control association analysis will fall into two classes: those reflecting true association and those occurring randomly in the interval from 0 to 1. We develop a partition test to find the set of smallest p values deviating most from the number of p values expected under randomness.

RESULTS

Power calculations demonstrate the superiority of our partition test over conventional SNP-by-SNP analyses. Applications of the partition test to six published datasets show that our test is particularly suitable when multiple SNPs appear to contribute to a trait, and furnished more significant results than a well-known procedure to estimate the false discovery rate.

CONCLUSIONS

Our partition test also furnishes an estimate of the number of functional SNPs underlying disease and can be highly significant, while single-locus tests may be far from significant.

Opiate addiction and cocaine addiction: underlying molecular neurobiology and genetics

Addictive diseases, including addiction to heroin, prescription opioids, or cocaine, pose massive personal and public health costs. Addictions are chronic relapsing diseases of the brain caused by drug-induced direct effects and persisting neuroadaptations at the epigenetic, mRNA, neuropeptide, neurotransmitter, or protein levels. These neuroadaptations, which can be specific to drug type, and their resultant behaviors are modified by various internal and external environmental factors, including stress responsivity, addict mindset, and social setting. Specific gene variants, including variants encoding pharmacological target proteins or genes mediating neuroadaptations, also modify vulnerability at particular stages of addiction. Greater understanding of these interacting factors through laboratory-based and translational studies have the potential to optimize early interventions for the therapy of chronic addictive diseases and to reduce the burden of relapse. Here, we review the molecular neurobiology and genetics of opiate addiction, including heroin and prescription opioids, and cocaine addiction.

Therapeutic potential of metabotropic glutamate receptor modulators

Glutamate is the main excitatory neurotransmitter in the central nervous system (CNS) and is a major player in complex brain functions. Glutamatergic transmission is primarily mediated by ionotropic glutamate receptors, which include NMDA, AMPA and kainate receptors. However, glutamate exerts modulatory actions through a family of metabotropic G-protein-coupled glutamate receptors (mGluRs). Dysfunctions of glutamatergic neurotransmission have been implicated in the etiology of several diseases. Therefore, pharmacological modulation of ionotropic glutamate receptors has been widely investigated as a potential therapeutic strategy for the treatment of several disorders associated with glutamatergic dysfunction. However, blockade of ionotropic glutamate receptors might be accompanied by severe side effects due to their vital role in many important physiological functions. A different strategy aimed at pharmacologically interfering with mGluR function has recently gained interest. Many subtype selective agonists and antagonists have been identified and widely used in preclinical studies as an attempt to elucidate the role of specific mGluRs subtypes in glutamatergic transmission. These studies have allowed linkage between specific subtypes and various physiological functions and more importantly to pathological states. This article reviews the currently available knowledge regarding the therapeutic potential of targeting mGluRs in the treatment of several CNS disorders, including schizophrenia, addiction, major depressive disorder and anxiety, Fragile X Syndrome, Parkinson’s disease, Alzheimer’s disease and pain.

Emerging role of non-coding RNA in neural plasticity, cognitive function, and neuropsychiatric disorders

Non-coding RNAs (ncRNAs) have emerged as critical regulators of transcription, epigenetic processes, and gene silencing, which make them ideal candidates for insight into molecular evolution and a better understanding of the molecular pathways of neuropsychiatric disease. Here, we provide an overview of the current state of knowledge regarding various classes of ncRNAs and their role in neural plasticity and cognitive function, and highlight the potential contribution they may make to the development of a variety of neuropsychiatric disorders, including schizophrenia, addiction, and fear-related anxiety disorders.

κ-opioid receptor/dynorphin system: genetic and pharmacotherapeutic implications for addiction

Addictions to cocaine or heroin/prescription opioids [short-acting μ-opioid receptor (MOPr) agonists] involve relapsing cycles, with experimentation/escalating use, withdrawal/abstinence, and relapse/re-escalation. κ-Opioid receptors (KOPr; encoded by OPRK1), and their endogenous agonists, the dynorphins (encoded by PDYN), have counter-modulatory effects on reward caused by cocaine or MOPr agonist exposure, and exhibit plasticity in addictive-like states. KOPr/dynorphin activation is implicated in depression/anxiety, often comorbid with addictions. In this opinion article we propose that particular stages of the addiction cycle are differentially affected by KOPr/dynorphin systems. Vulnerability and resilience can be due to pre-existing (e.g., genetic) factors, or epigenetic modifications of the OPRK1 or PDYN genes during the addiction cycle. Pharmacotherapeutic approaches limiting changes in KOPr/dynorphin tone, especially with KOPr partial agonists, may hold potential for the treatment of specific drug addictions and psychiatric comorbidity.

Common and specific liability to addiction: approaches to association studies of opioid addiction

BACKGROUND

Opioid addiction, whether to opiates such as heroin and morphine, and/or to non-medical use of opioids, is a major problem worldwide. Although drug-induced and environmental factors are essential for the liability to develop opioid addiction, the genetic background of an individual is now known also to play a substantial role.

METHODS

The overall goal of this article is to address the common and specific liabilities to addiction in the context of approaches to studies of one addiction, opioid addiction. Literature on identifying genetic variants that may play a role in the development of opioid addiction was reviewed.

RESULTS

A substantial number of genetic variants have been reported to be associated with opioid addiction. No single variant has been found in any of the reported GWAS studies with a substantial effect size on the liability to develop heroin addiction. It appears that there is a complex interaction of a large number of variants, some rare, some common, which interact with the environment and in response to specific drugs of abuse to increase the liability of developing opioid addiction.

CONCLUSIONS

In spite of the inherent difficulties in obtaining large well-phenotyped cohorts for genetic studies, new findings have been reported that are being used to develop testable hypotheses into the biological basis of opioid addiction.

The genetics of the opioid system and specific drug addictions

Addiction to drugs is a chronic, relapsing brain disease that has major medical, social, and economic complications. It has been established that genetic factors contribute to the vulnerability to develop drug addiction and to the effectiveness of its treatment. Identification of these factors may increase our understanding of the disorders, help in the development of new treatments and advance personalized medicine. In this review, we will describe the genetics of the major genes of the opioid system (opioid receptors and their endogenous ligands) in connection to addiction to opioids, cocaine, alcohol and methamphetamines. Particular emphasis is given to association and functional studies of specific variants. We will provide information on the sample populations and the size of each study, as well as a list of the variants implicated in association with addiction-related phenotypes, and with the effectiveness of pharmacotherapy for addiction.

Possible association between human blood types and opioid addiction

Drug addiction is a complex disorder that has been shown to have a genetic component like several other diseases. Finding any factor that is associated with higher risk of addiction tendency may influence the strategies of prevention and treatment of drug abuse and also provide an avenue of further research in genetics, immunology, and other related fields. This case-control study aimed at finding the frequency rate of ABO blood groups and Rhesus (Rh) factor among opioid dependents. Therefore, 249 opioid dependents referred to the Drug Quit center at Bam, Iran (case group) were compared with 360 blood donors referred to the Blood Transfusion Center (control group) in regard to the frequency of blood groups and Rh factor. The two groups were matched for demographic features. The odds ratio for AB blood group in addicts was 3.98 compared to non-addicts (p < .001) and the odds ratio of negative Rh in addicts compared to non-addicts was 4.27 (p < .001). According to the findings, in this population the frequency of negative Rh and AB blood group were significantly less than the predictive values. The relationship between opioid use and blood group type requires a cohort study eliminating all extraneous factors in order to be proved.

Multilocus association mapping using generalized ridge logistic regression

BACKGROUND

In genome-wide association studies, it is widely accepted that multilocus methods are more powerful than testing single-nucleotide polymorphisms (SNPs) one at a time. Among statistical approaches considering many predictors simultaneously, scan statistics are an effective tool for detecting susceptibility genomic regions and mapping disease genes. In this study, inspired by the idea of scan statistics, we propose a novel sliding window-based method for identifying a parsimonious subset of contiguous SNPs that best predict disease status.

RESULTS

Within each sliding window, we apply a forward model selection procedure using generalized ridge logistic regression for model fitness in each step. In power simulations, we compare the performance of our method with that of five other methods in current use. Averaging power over all the conditions considered, our method dominates the others. We also present two published datasets where our method is useful in causal SNP identification.

CONCLUSIONS

Our method can automatically combine genetic information in local genomic regions and allow for linkage disequilibrium between SNPs. It can overcome some defects of the scan statistics approach and will be very promising in genome-wide case-control association studies.

Genome-wide association studies identify genetic loci related to alcohol consumption in Korean men

BACKGROUND

Genome-wide association (GWA) studies regarding the quantitative trait of alcohol consumption are limited.

OBJECTIVE

The objective of the study was to explore genetic loci associated with the amount of alcohol consumed.

DESIGN

We conducted a GWA study with discovery data on single nucleotide polymorphisms (SNPs) for 1721 Korean male drinkers aged 40-69 y who were included in an urban population-based cohort. Another sample that comprised 1113 male drinkers who were from an independent cohort enrolled in a rural area served as a resource for replication. At baseline (18 June 2001 through 29 January 2003), members of both cohorts provided information on average daily alcohol consumptions, and their DNA samples were collected for genotyping.

RESULTS

We tested 315,914 SNPs of discovery data by using multivariate linear regression analysis adjusted for age and smoking, and 12 SNPs on chromosome 12q24 had genome-wide significant associations with alcohol consumption; adjusted P values by using Bonferroni correction were 1.6 × 10(-5) through 5.8 × 10(-46). We observed most SNPs in intronic regions and showed that the genes that harbor SNPs were C12orf51, CCDC63, MYL2, OAS3, CUX2, and RPH3A. In particular, signals in or near C12orf51, CCDC63, and MYL2 were successfully replicated in the test for 317,951 SNPs; rs2074356 in C12orf51 was in high linkage disequilibrium with SNPs in ALDH2, but other SNPs were not.

CONCLUSIONS

In a GWA study, we identified loci and alleles highly associated with alcohol consumption. The findings suggest the need for further investigations on the genetic propensity for drinking excessive amounts of alcohol.

Replicated association of the NR4A3 gene with smoking behaviour in schizophrenia and in bipolar disorder

Schizophrenia and bipolar disorder are associated with dopamine neurotransmission and show high comorbidity with tobacco dependence. Recent evidence indicates that the family of the NR4A orphan nuclear receptors, which are expressed in dopamine neurons and in dopaminoceptive brain areas, may play a role in dopamine-mediated effects. We have, therefore, analysed the association of six single nucleotide polymorphisms (SNPs) within the three genes belonging to the NR4A orphan nuclear receptor family, NR4A1 (rs2603751, rs2701124), NR4A2 (rs12803, rs834835) and NR4A3 (rs1131339, rs1405209), with the degree of smoking in a sample of 204 unrelated schizophrenia patients, which included 126 smokers and 78 non-smokers. SNPs within the NR4A3 gene (rs1131339 and rs1405209) were significantly associated with heavy smoking in this cohort, using a stepwise analysis of the escalated number of cigarettes smoked per day (P = 0.008 and 0.006, respectively; satisfying the Nyholt significance threshold of 0.009, an adjustment for multiple testing). We then repeated the association analysis of the NR4A3 markers (rs1131339 and rs1405209) in a larger cohort of 319 patients with bipolar disorder, which included 167 smokers and 152 non-smokers. We have replicated the positive association with smoking of the NR4A3 SNP rs1131339 in this group (P = 0.04), providing an important confirmation of the involvement of the NR4A3 gene in nicotine addiction in patients with mental health disease, a population significantly at risk for nicotine addiction.