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The rat oxycodone and cocaine biobanks contain samples that vary by genotypes by using genetically diverse genotyped HS rats , phenotypes by measuring addiction-like behaviors in an advanced SA model , timepoints samples are collected longitudinally before, during, and after SA, and terminally at three different timepoints in the addiction cycle: intoxication, withdrawal, and abstinence or without exposure to drugs through age-matched naive rats , samples collected organs, cells, biofluids, feces , preservation paraformaldehyde-fixed, snap-frozen, or cryopreserved and application proteomics, transcriptomics, microbiomics, metabolomics, epigenetics, anatomy, circuitry analysis, biomarker discovery, etc. Substance use disorders SUDs are pervasive in our society and have substantial personal and socioeconomical costs. A critical hurdle in identifying biomarkers and novel targets for medication development is the lack of resources for obtaining biological samples with a detailed behavioral characterization of SUD. Moreover, it is nearly impossible to find longitudinal samples. As part of two ongoing large-scale behavioral genetic studies in heterogeneous stock HS rats, we have created two preclinical biobanks using well-validated long access LgA models of intravenous cocaine and oxycodone self-administration SA and comprehensive characterization of addiction-related behaviors. The genetic diversity in HS rats mimics diversity in the human population and includes individuals that are vulnerable or resilient to compulsive-like responding for cocaine or oxycodone. Longitudinal samples are collected throughout the experiment, before exposure to the drug, during intoxication, acute withdrawal, and protracted abstinence, and include naive, age-matched controls. Samples include, but are not limited to, blood plasma, feces and urine, whole brains, brain slices and punches, kidney, liver, spleen, ovary, testis, and adrenal glands. Three preservation methods fixed in formaldehyde, snap-frozen, or cryopreserved are used to facilitate diverse downstream applications such as proteomics, metabolomics, transcriptomics, epigenomics, microbiomics, neuroanatomy, biomarker discovery, and other cellular and molecular approaches. Keywords: biological specimen banks; opioid; outbred strains; psychostimulant; substance-related disorders. Abstract The rat oxycodone and cocaine biobanks contain samples that vary by genotypes by using genetically diverse genotyped HS rats , phenotypes by measuring addiction-like behaviors in an advanced SA model , timepoints samples are collected longitudinally before, during, and after SA, and terminally at three different timepoints in the addiction cycle: intoxication, withdrawal, and abstinence or without exposure to drugs through age-matched naive rats , samples collected organs, cells, biofluids, feces , preservation paraformaldehyde-fixed, snap-frozen, or cryopreserved and application proteomics, transcriptomics, microbiomics, metabolomics, epigenetics, anatomy, circuitry analysis, biomarker discovery, etc. Publication types Review. Substances Oxycodone Cocaine.

Molecular genetics of cocaine use disorders in humans

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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. At the individual level, drugs of abuse produce serious consequences on health and have a negative impact on the family environment and on interpersonal and work relationships. At a wider scale, they have significant socio-economic and public health consequences and they cause delinquency and citizen insecurity. Cocaine, a psychostimulant substance, is one of the most used illicit drugs, especially in America, Western Europe, and Australia. Cocaine use disorders CUD are complex multifactorial conditions driven by both genetic and environmental influences. Importantly, not all people who use cocaine develop CUD, and this is due, at least in part, to biological factors that are encoded in the genome of individuals. Acute and repeated use of cocaine induces epigenetic and gene expression changes responsible for the neuronal adaptations and the remodeling of brain circuits that lead to the transition from use to abuse or dependence. The purpose of this review is to delineate such factors, which should eventually help to understand the inter-individual variability in the susceptibility to cocaine addiction. Heritability estimates for CUD are high and genetic risk factors for cocaine addiction have been investigated by candidate gene association studies CGAS and genome-wide association studies GWAS , reviewed here. Also, the high comorbidity that exists between CUD and several other psychiatric disorders is well known and includes phenotypes like schizophrenia, aggression, antisocial or risk-taking behaviors. Such comorbidities are associated with a worse lifetime trajectory, and here we report shared genetic factors that may contribute to them. Gene expression changes and epigenetic modifications induced by cocaine use and chronic abuse in humans are addressed by reviewing transcriptomic studies performed on neuronal cells and on postmortem brains. We report some genes which expression is altered by cocaine that also bear genetic risk variants for the disorder. Finally, we have a glance to the pharmacogenetics of CUD treatments, still in early stages. A better understanding of the genetic underpinnings of CUD will foster the search of effective treatments and help to move forward to personalized medicine. The term substance use disorders SUD , including cocaine use disorders CUD , refers to different types of behaviors that range from sporadic use to abuse, dependence or addiction. The main change of DSM-5 with respect to the previous version of the manual is the unification of abuse and dependence into a unidimensional category, SUD, that is qualified on a severity scale i. In addition, DSM-5 drops one of the diagnostic criteria legal problems due to infrequent endorsement and poor discriminant validity \[ 3 \], and adds a new one: craving. Several authors have attempted to establish more homogeneous subgroups of cocaine-related phenotypes that may be useful for subsequent genetic analyses. Thus, five subtypes of cocaine abusers have been defined on the basis of clinical presentation, family history, and response to treatment \[ 4 \]. More recently, cluster analysis was not only used to classify individuals on different groups according to cocaine-related measures but also to demographic features and prevalence rates of comorbid substance use and psychiatric disorders. Interestingly, those clusters characterized by a more severe phenotype yielded higher heritability estimates \[ 5 , 6 \]. From these, over 35 million people suffer from SUD. Cocaine, together with metamphetamines, dominates the psychostimulants share. Some 19 million people used cocaine in 0. In Europe, cocaine is the most used illegal psychostimulant, around 5. From these data, the prevalence of cocaine dependence in the European population can be estimated around 1. Ethnicity is also relevant, for example with rates of cocaine overdose deaths being much higher in African—American AA individuals in the United States \[ 12 \]. For different reasons, research studies, and clinical trials have underrepresented women and ethnic minorities. This may lead to gaps in the discovery of risk factors for addiction, as several factors that influence the origin and development of the disorder differ across gender and ethnic groups. These factors include psychiatric comorbidities, sociodemographic status, frequency and severity of cocaine use, and also biological determinants \[ 13 , 14 \]. At the molecular level, cocaine binds the monoaminergic transporters DAT, NET, and SERT blocking the reuptake of these neurotransmitters by the presynaptic neuron, increasing the levels of dopamine, serotonin, and noradrenaline at the synaptic cleft \[ 15 \]. Cocaine pleasurable and rewarding effects are mediated mainly by the increase of dopamine activity in the limbic system. Chronic cocaine use induces alterations and adaptations in several neurotransmitter systems and affects the function of several circuits and areas such as the mesocorticolimbic system including the nucleus accumbens NAc and ventral tegmental area as well as prefrontal cortex. Serotonin neurotransmission is also key to cocaine addiction since it contributes to relapse by modulating impulsivity and responsivity to cocaine-associated stimuli \[ 16 \]. This vulnerability to relapse, even after a long period of abstinence, involves stable gene expression changes and epigenetic modifications, especially in the corticostriatolimbic circuitry hippocampus, prefrontal cortex, NAc, dorsal striatum, and amygdala \[ 17 \]. Stress plays an important role in relapse since increases drug craving, involving mainly the HPA axis and corticotropin-releasing factor \[ 18 \]. Cocaine-induced changes and adaptations in the brain through repeated use will depend on the genetic background of each individual. Also, these functional modifications are modulated by environmental factors and the interplay between them and genetic risk factors. In this review, we focus on the genetics of CUD. Familial aggregation of alcoholism and addiction to illicit drugs is well described, and relatives of probands with SUD have an eightfold increased risk of drug use disorders, being 4. Familiar, adoption, and especially twin studies have brought consistent evidence that both environmental and genetic risk factors contribute to initiating the use of drugs of abuse, the transition to abuse, and the development of dependence. Heritability estimates described by different twin studies have shown that the genetic contribution to SUD and addictions is in general high, and also variable depending on the drug of abuse \[ 21 \]. Heritability estimates for CUD are summarized in Table 2. In general, heritability is lower for drug use than for dependence for all drugs of abuse \[ 19 \]. For cocaine abuse, heritability estimates are also highly variable, ranging from 0. Finally, genetic risk factors explaining the variance for cocaine dependence have been estimated to be consistently high across studies 0. Although the contribution of genetic risk factors to cocaine addiction is very high, as described before, identifying the specific factors that underlie addiction is challenging due to the high polygenicity and complexity of this disorder. The contribution of common variants through association studies, as well as rare variants, has been investigated for cocaine dependence. Some relevant variants and genes have been highlighted, but most genetic risk factors are still largely unknown. Candidate gene association studies CGAS have focused on specific sets of genes based on a priori assumptions about their role in the mechanism of action of cocaine and in the development of addiction, including dopamine and serotonin neurotransmission Supplementary Table S1. Although transgenic mice for some of these genes showed alterations in cocaine-seeking behavior, particularly those encoding the monoamine transporters \[ 31 \], no robust associations have been found in CGAS. So far, only one copy number variant CNV has been found associated with cocaine dependence, a large polymorphic CNV that partially spans the NSF gene, involved in synaptic vesicle turnover \[ 38 \]. In this study, individuals with a low number of copies showed a quicker transition from cocaine use to dependence than individuals with a high number of copies. The first genome-wide association study GWAS on cocaine dependence with positive findings was published in \[ 39 \]. The authors developed a model Sympcount adj to remove the effect attributable to other substances alcohol, opioids and nicotine , thus facilitating the identification of genetic risk variants for cocaine addiction. In addition, they used cocaine-exposed controls that did not develop addiction. In the European—American EA discovery sample cases and controls , a genome-wide significant GWS association was found between cocaine dependence and rs Table 3 , located in the NCOR2 gene nuclear receptor corepressor 2 that regulates gene expression by activating histone deacetylase 3, and has been involved in memory \[ 40 \]. However, this finding could not be replicated in two follow-up samples including and subjects, respectively. Although genetic variants in this gene have been related to changes in brain volumes \[ 41 \], very little is known about FAM53B function and, more importantly, about its contribution to cocaine addiction susceptibility. Nevertheless, this association could not be replicated in a Spanish cohort of cocaine dependence cases and controls \[ 42 \]. Recently, a transcriptome-wide association study TWAS was performed using these data in several brain regions, although no significant associations were found in any tissue for cocaine dependence \[ 43 \]. This gene, encoding a signaling protein involved in neurodevelopmental processes, had previously been associated with several psychiatric conditions, including schizophrenia SCZ \[ 45 \]. Two GWAS on CUD have been recently published, one accounting for gene—environment interactions \[ 6 \], and another one evaluating time to develop dependence \[ 47 \] Table 3. In addition, a cluster analysis was performed to divide the sample in five CUD groups. In addition, this study supports the idea that CUD subjects can be decomposed into different subgroups, as previously mentioned, and the study of more homogeneous subgroups may result in more powerful genetic analyses \[ 5 \]. The second one identified two GWS hits associated with time from cocaine use to dependence onset, rs identified in the meta-analysis of EA—AA individuals, and located in the gene FAM78B , and rs in AA individuals \[ 47 \]. This approach highlights the importance of investigating addiction-related phenotypes to uncover genetic risk factors involved in the development of dependence. Today, the most important limitation for the association studies on cocaine addiction is the sample size. Hypothesis-free association studies, in the form of GWAS, have taken over from the old CGAS, allowing identification of new, unexpected associations that would have never been explored in hypothesis-driven studies. Nonetheless, a GWAS involves testing millions of genetic variants, which imposes a highly astringent statistical price. Due to the difficulty in recruiting patients that are dependent only on cocaine, some authors have studied the general genetic liability of several illicit drugs of abuse e. These studies identified several SNPs that show a significant association with the phenotype, with subsequent replication in independent samples. However, the sample size of these studies is still limited and further studies are needed. Another important and controversial consideration in association studies for SUD is the selection of the control sample. Some studies use control individuals that have been exposed to the drug at least once in their life \[ 39 \], hence excluding the genetic risk factors related to impulsivity or risk-taking behavior, which are very important in this disorder, as they facilitate the first contact with the drug. Indeed, genetic correlation analyses have recently shown the existence of shared genetic factors between cocaine addiction and risk-taking behavior \[ 44 \]. For that reason, other studies used screened controls that do not meet the DSM criteria for addiction or unselected controls from the general population \[ 44 , 57 , 60 \]. The last approach could eventually dilute positive findings due to the presence of some cases among the controls; however, based on the prevalence of cocaine dependence in the general population about 1. As previously mentioned, the prevalence of CUD varies among ethnicities. Two of the three GWAS performed on CUD \[ 6 , 39 \] included both AA and EA individuals, and their results, as well as those from other SUD \[ 57 \], suggest that some genetic risk variants can be associated with the phenotype only in a particular population. Although this could be due to limited sample size, further studies in larger samples and considering different ethnicities are warranted. While GWAS have begun to identify genes that underlie several traits relevant to drug abuse, they still explain only a small fraction of the heritability of this disorder. One of the most important limitations of these studies is the intrinsic difficulty in obtaining large and homogeneous human samples. This has fostered the emergence of a new project www. In addition, expression data of several brain regions relevant to the addiction process will be analyzed to identify expression QTLs eQTLs. This approach can help to identify new genes that influence drug abuse-related behaviors in rats, providing potential candidates for the genetic susceptibility to drug addiction in humans. Further studies with larger samples sizes that use methodological approaches other than GWAS are needed to dissect the role of rare genetic risk variants on cocaine dependence. Recognition of co-occurring psychiatric disorders among people with SUD has been growing in recent years. Several studies have shown that SUD is highly comorbid with other psychiatric disorders such as SCZ, major depressive disorder MDD , or ADHD \[ 64 , 65 , 66 , 67 \], and traits like aggressive, antisocial, or risk-taking behaviors \[ 68 , 69 \]. The pattern is similar with cocaine: Such comorbidities determine a worse lifetime trajectory in patients, lower rates of treatment success, and a higher prevalence of suicide. Several studies have started to investigate whether shared genetics is behind these comorbid patterns using different statistical tools, such as the estimation of genetic correlation between phenotypes, polygenic risk score PRS analysis to quantify the fraction of the genetics of a given phenotype that predicts a second condition, and Mendelian Randomization or Latent Causal Variable model to infer causal relationships. However, studies focusing particularly on cocaine are still scarce due to the limited availability of properly sized GWAS. Testing traits from LDHub \[ 44 \] yielded significant findings, including negative correlations with cognitive phenotypes e. This SNP has also been found associated with cocaine addiction in several studies \[ 35 , 36 , 37 \], but the direction of the effect is opposite, with allele A being a risk factor for nicotine addiction but protective for cocaine addiction \[ 35 \]. The molecular basis of this distinction is not clear but seems to be related with the localization of this receptor in the mesolimbic dopamine system both in excitatory dopaminergic and in inhibitory GABAergic neurons and the mechanism of action of nicotine and cocaine \[ 35 \]. Interestingly, antagonists of the receptor decrease the reinforcing effects of cocaine, whereas Chrna5 knock-out mice have an increased intake of nicotine \[ 82 , 83 \]. To summarize, we know that CUD is highly comorbid with other psychiatric disorders and cognitive or personality traits, but the role of shared genetics on these co-occurrences has been poorly studied. Thus, we do not know whether risk alleles are acting independently on CUD and on its comorbid phenotypes i. Using analytical tools that investigate causal relationships is needed to clarify this issue. Another relevant issue is whether the different SUD share genetic risk factors or if substance-specific factors are predominant. In this regard, the fact that heritability estimates for substance-related phenotypes significantly differ depending on the drug of abuse supports the view that at least certain risk factors may be substance-specific \[ 85 \]. However, there is evidence from twin studies that a large proportion of genetic liability is shared across substances \[ 29 , 86 \], and molecular studies show that increased cross-disorder polygenic risk e. Cocaine use induces changes in the structure and function of the brain, such as neuronal connectivity and synaptic plasticity \[ 87 , 88 , 89 , 90 \]. Some of these changes may become stable, contributing to addiction and relapse in cocaine use. Epigenetic and gene expression changes underlie these neuroadaptations induced by the drug and help to explain functional alterations \[ 91 , 92 \]. Several studies have assessed gene expression alterations in postmortem brain samples from cocaine abusers or in neuronal cells in vitro, the vast majority using microarrays Table 4. It should be mentioned that these studies are based on few individuals due to the inherent difficulty in obtaining these samples. Across the different studies, some functions are recurrently identified among the genes that are differentially expressed, such as transcription regulation \[ 93 , 94 , 95 , 96 , 97 , 98 , 99 \] and signal transduction \[ 93 , 94 , 95 , 96 , 99 , , \], but certain functions and pathways have been identified only in some particular studies. Alteration of gene expression in the prefrontal cortex of cocaine abusers was assessed in two studies, using postmortem samples of dorsolateral and anterior prefrontal cortex dlPFC and aPFC, respectively. The first study focused on expression alterations in aPFC shared in cocaine, cannabis, and phencyclidine abuse, highlighting genes related to calmodulin signaling, Golgi and endoplasmic reticulum \[ \]. In dlPFC, expression changes identified in cocaine abusers involved genes implicated in mitochondrial and oligodendrocyte function, among others \[ 93 \]. Interestingly, in the NAc of cocaine abusers, myelin-related genes and genes involved in glial function were also found altered, consistent with a loss of MBP-positive oligodendrocytes \[ 94 \], and alterations in the expression of PLP1 , encoding a major constituent of myelin, were identified \[ 93 , 94 , 95 \]. Furthermore, expression changes in neurotransmission-related genes were identified in dlPFC and NAc \[ 93 , 94 , 95 \], in particular genes involved in synaptic function or cell adhesion \[ 94 , 95 \]. In hippocampus of cocaine abusers, two different studies detected alterations in the expression of genes involved in the regulation of the extracellular matrix \[ 96 , 97 \], and also in cell adhesion, neurogenesis and axon guidance \[ 96 \], or mitochondrial function, oxidative phosphorylation and long-term potentiation \[ 97 \]. Another study using postmortem brain samples assessed the expression in midbrain of dopamine cell-enriched regions identifying alterations in expression related to dopamine metabolic process and neuronal differentiation \[ 98 \] Table 4. Remarkably, the first study also assessed the substance-specific and shared gene expression changes between cocaine and alcohol in hippocampus, observing that cocaine induced many more transcriptomic alterations than alcohol, but also identifying common changes in the same direction for both drugs that were related to neuroadaptations \[ 97 \]. The effects of cocaine on human gene expression have also been evaluated in human cells in vitro. Human neuronal progenitor cells showed alterations in the expression of genes mainly involved in immune and inflammatory processes and cell death when exposed to cocaine \[ \], in line with several studies mentioned above \[ 94 , 95 , 96 , 98 \]. In a dopaminergic neuron-like model, changes in gene expression involved chromatin modification \[ 99 \], also occurring in dopamine cell-enriched regions and hippocampus \[ 97 , 98 \]. Other functions were also identified such as cell cycle, adhesion, cell projection and neuroadaptations \[ 99 \], and epigenetic regulation by several miRNAs could explain, at least partially, the expression changes induced by cocaine \[ \] Table 4. Gene expression changes induced by cocaine have been widely investigated in animal models, adding valuable information to human studies and contributing to the understanding of the molecular changes involved in the development of CUD. It should be mentioned that several of the studies previously performed in humans did not apply multiple testing corrections, a relevant statistical filter when thousands of transcripts are interrogated. Nevertheless, all of them validated expression differences of selected genes by quantitative real-time PCR Table 4. It is important to note that biological samples from cocaine-addict individuals are difficult to obtain and involve a wide range of variables that cannot be controlled and add heterogeneity, such as dose and frequency of use, time of last exposure, use of other drugs or cause of death. In contrast, in vitro experiments evaluating cocaine effect on cell lines allow to control for variables such as cocaine concentration and time of exposure, but they cannot mimic the effect of chronic cocaine use in the brain of an addicted individual and the effect of the crosstalk with other cell types and remodeling of circuits. By the use of novel techniques, such as single-cell RNA-sequencing, postmortem brain regions could be used to dissect which cell types show more relevant expression changes in each area and, then, study in vitro the effect of cocaine in a controlled environment using specific iPSCs-derived models. Moreover, the information that can be obtained from a few human samples is limited, making it difficult to fully understand the changes in gene expression and in the biological processes that occur in the brain of cocaine users. Due to the intrinsic difficulties in obtaining expression data from the brain of patients, several tools have been developed to use transcriptomic imputation to integrate genotype and expression data from large consortia, like GTEx, through machine learning. As mentioned above, cocaine addiction is a maladaptive neural plasticity process that occurs in response to repeated drug exposure in vulnerable individuals, depending on the genetic and environmental risk factors, and their interaction. Several studies have demonstrated cocaine-induced changes in epigenetic mechanisms like histone modifications, DNA methylation, and microRNAs, all of them recently reviewed \[ 92 , , , , , , \]. However, only a few studies have been conducted in human samples. Regarding histone posttranslational modifications, we found only one study that inspected genome-wide changes in H3K4Me3 in postmortem hippocampus of individuals with chronic exposure to cocaine, revealing changes in promoters of genes, although only five of them overcame multiple testing corrections \[ 97 \]. On the other hand, a recent study examined DNA methylation profiles in the peripheral blood of CUD patients and found differentially methylated positions, proposing these regions as potential biomarkers \[ \]. Finally, two studies investigated changes in the expression of microRNAs induced by cocaine in human cultured cells \[ , \] and two others in peripheral blood and in postmortem brains of cocaine abusers \[ , \]. Interestingly, all of them found alterations in the expression of miR, a miRNA that has also been related to cocaine effects in rodents \[ , \]. Further studies are needed to explore the epigenetic mechanisms that underlie cocaine addiction and identify potential biomarkers and therapeutic targets. Genes which expression is altered by cocaine, and that possibly mediate its effects and neuroadaptations induced in the brain, could hold genetic risk variants that contribute to the susceptibility to cocaine addiction. Under this hypothesis, some recent studies have pinpointed genes that show altered expression and bear genetic risk variants. Expression of NFAT5 was found increased in dopaminergic neuron-like cells upon acute exposure to cocaine and, additionally, five SNPs in this gene were associated with cocaine dependence \[ 99 \]. Three miRNAs, miR-9, miR, and miR, were downregulated by cocaine in the above-mentioned dopaminergic model, possibly regulating expression changes observed in the previous study. Interestingly, these miRNAs were found associated with cocaine dependence in a gene-based association study \[ \]. PLCB1 , Phospholipase C beta 1 protein, carry genetic variants associated with both cocaine dependence \[ \] and drug dependence \[ , \]. Increased expression of PLCB1 is found in both the NAc of human cocaine abusers and in cultured dopaminergic-like human neurons treated with cocaine \[ \]. Increased expression has been also found in the NAc of mice self-administering cocaine and during withdrawal \[ \], and a recent study in mice suggests that this gene may play an important role in relapse to cocaine consumption \[ \]. KCTD20 , a regulator of AKT signaling, was identified in a recent study that combined genomic and transcriptomic data to detect candidates for cocaine addiction. This gene was one of the three GWS findings in a GWAS of cocaine dependence \[ 39 \], and altered expression was found in hippocampus of cocaine abusers, being a key node in a gene network associated with human cocaine use \[ 46 \]. This gene is a member of the KCTD family, which is involved in a wide range of processes, including proteasome function, GABA signaling, and regulation of transcription responses. But the number of works is still limited and further studies are needed to investigate the convergence between expression and genetic studies. Research in the field would benefit from large GWAS and transcriptomic studies and the use of integrative analyses e. Currently, there is no government-approved medication available to treat CUD. However, the efficacy of these treatments requires further exploration \[ \]. Pharmacogenetic approaches investigate the genetic factors responsible for the inter-individual medication response variability. This core element of personalized medicine is a reality in the oncology field. The identification of these correlations has been possible thanks to huge consortiums, such as the Pan-Cancer Atlas, studying thousands of samples in depth \[ \]. The influence of genetic variants in treatment response in SUD is still at an early stage. An illustrative example is the study of the interaction genotype-treatment in smokers \[ \]. Although these findings require additional replications, selection of medication based on genotype could lead to higher rates of smoking cessation. Early CUD pharmacogenetic studies focused on mouse models reviewed by \[ \]. The results of these studies are summarized in Table 5. Extensive reviews of cocaine medication pharmacogenetics have been published \[ , , , \]. However, the knowledge in the field is still in its early stages. For instance, individuals with the CC genotype, associated with normal DBH levels, presented significant cocaine-positive urine reduction rates on disulfiram treatment in one study \[ \], although the results were not supported by another study \[ \]. Contrarily, T-allele carriers CT and TT genotypes , associated with lower levels of circulating DBH, seem to respond better to doxazosin, levodopa, or cocaine vaccine medications \[ , , \]. The responses to treatments considering multiple polymorphic variants in different genes at the same time are of particular interest. These interactions were tested in two studies \[ , \]. Pharmacogenetic studies published until now present some limitations. Therefore, replication of the other results in independent samples is needed to confirm the participation of these polymorphisms in differential drug response. However, population stratification has been assessed and taken into consideration in statistical analyses. Larger samples representing the multiple ethnic groups are warranted to extract generalizable conclusions. In addition, in some studies, multiple drugs were given e. Larger and more comprehensive studies are needed to be able to move toward personalized medicine in cocaine use disorder therapy. On the other hand, further transcriptomic studies are warranted to improve the understanding of cocaine effects on the brain and the molecular basis of the neuroadaptations that underlie compulsive drug seeking, even after long periods of abstinence. However, we need more studies that investigate the convergence between altered expression and genetic variation in CUD. We have learned from twin studies and from molecular genetics research that there is a common genetic architecture across different SUDs, but they also reveal some genetic risk factors that are substance-specific. Understanding the weight and nature of each of these components is an important challenge in addiction research. For some drugs of abuse with considerable larger samples sizes, GWAS have started to reveal genetic risk variants in few genes that have been consistently associated and replicated, for instance SNPs in the ADH1B gene for alcohol dependence and CHRNA5 gene for nicotine dependence recently reviewed \[ \]. Despite significant advances in the study of the molecular underpinnings of CUD during the last decade, we are still far from individual genetic prediction to aid prevention, diagnostics or to anticipate disease course and therapeutic response. However, there are promising venues in cocaine research, especially those related to GWAS data: On one hand, we know that PRSs have already been able to identify individuals with risk equivalent to monogenic mutations in several somatic conditions \[ , \] and this is currently being explored also in psychiatric conditions. On the other hand, the relevance of the supporting genetic evidence in the selection of candidates for drug development has been demonstrated across human diseases, increasing by twofold the drug success rate in clinical trials compared to non-genetically selected targets \[ , \]. However, advancing toward more comprehensive pharmacogenetic studies will only be possible once our knowledge on the genetic bases of CUD is wider and more precise. DSM-5 criteria for substance use disorders: recommendations and rationale. Am J Psychiatry. American Psychiatric Association. Diagnostic and statistical manual of mental disorders 4th ed. American Psychiatric Press Inc. Subtypes of cocaine abusers. Psychiatr Clin N Am. The validity of cocaine dependence subtypes. Addict Behav. A genome-wide association study of cocaine use disorder accounting for phenotypic heterogeneity and gene—environment interaction. J Psychiatry Neurosci. Article PubMed Google Scholar. 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Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. Download references. You can also search for this author in PubMed Google Scholar. Reprints and permissions. Molecular genetics of cocaine use disorders in humans. Mol Psychiatry 27 , — Download citation. Received : 19 October Revised : 01 July Accepted : 30 July Published : 27 August Issue Date : January Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content Thank you for visiting nature. Download PDF. Subjects Addiction Genetics. Abstract Drug addiction, one of the major health problems worldwide, is characterized by the loss of control in drug intake, craving, and withdrawal. The addiction risk factor: A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates Article 08 November Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits Article 14 April Divergent gene expression patterns in alcohol and opioid use disorders lead to consistent alterations in functional networks within the dorsolateral prefrontal cortex Article Open access 14 October Clinical definition The term substance use disorders SUD , including cocaine use disorders CUD , refers to different types of behaviors that range from sporadic use to abuse, dependence or addiction. Full size table. Neurobiology At the molecular level, cocaine binds the monoaminergic transporters DAT, NET, and SERT blocking the reuptake of these neurotransmitters by the presynaptic neuron, increasing the levels of dopamine, serotonin, and noradrenaline at the synaptic cleft \[ 15 \]. Table 2 Heritability estimates for cocaine use, abuse and addiction from twin studies. Changes in gene expression induced by cocaine Cocaine use induces changes in the structure and function of the brain, such as neuronal connectivity and synaptic plasticity \[ 87 , 88 , 89 , 90 \]. Transcriptomic studies Several studies have assessed gene expression alterations in postmortem brain samples from cocaine abusers or in neuronal cells in vitro, the vast majority using microarrays Table 4. Table 4 Transcriptomic alterations induced by cocaine in postmortem brain samples of cocaine abusers or cell lines exposed to cocaine in vitro. Convergence of expression and genetic studies Genes which expression is altered by cocaine, and that possibly mediate its effects and neuroadaptations induced in the brain, could hold genetic risk variants that contribute to the susceptibility to cocaine addiction. Treatment and pharmacogenetics Currently, there is no government-approved medication available to treat CUD. Table 5 Studies testing the relationship between genetic variants and pharmacotherapies for cocaine substance abuse treatment adapted from Patriquin et al. View author publications. Ethics declarations Competing interests The authors declare no competing interests. Supplementary information. Supplementary Table S1. About this article. Copy to clipboard. Graczyk Barbara J. Sahakian Karen D. Ersche Translational Psychiatry Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes Ye Lv Lin Wen Zhi-Lin Luan Metabolic Brain Disease Repeated dosing with cocaine produces strain-dependent effects on responding for conditioned reinforcement in Collaborative Cross mice Lauren S. Bailey Jared R. Bagley Lisa M. Tarantino Psychopharmacology Search Search articles by subject, keyword or author. Show results from All journals This journal. Advanced search.

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