Opioid receptors: drivers to addiction?

Emmanuel Darcq1 and Brigitte Lina Kieffer 1,2*

Abstract | Drug addiction is a worldwide societal problem and public health burden, and results from recreational drug use that develops into a complex brain disorder. The opioid system, one of the first discovered neuropeptide systems in the history of neuroscience, is central to addiction. Recently, opioid receptors have been propelled back on stage by the rising opioid epidemics, revolutions in G protein-coupled receptor research and fascinating developments in basic neuroscience. This Review discusses rapidly advancing research into the role of opioid receptors in addiction, and addresses the key questions of whether we can kill pain without addiction using mu-opioid-receptor-targeting opiates, how mu- and kappa-opioid receptors operate within

the neurocircuitry of addiction and whether we can bridge human and animal opioid research in the field of drug abuse.



An effect caused by drugs, mimicking symptoms of psychosis, such as agitation, delusions and delirium.

Opium is extracted from the seeds of poppies (Papaver somniferum) and has been used for more than 4,000 years in medicinal and recreational practices to relieve pain and cause euphoria. Morphine was isolated in 1805 as the most active component of opium1 and remains the most potent painkiller in modern medicine, despite severe adverse effects and a strong potential for addiction. Heroin, the diacetylated form of morphine, was origi- nally marketed as the first non-addictive opiate to treat cough and asthma in 1898, yet heroin addiction has represented a major societal problem ever since.

More recently, an ‘opioid epidemic’ has emerged in occidental countries, particularly in North America2. The overprescription of opioids for pain relief in the past 20 years has led to a rapid surge in the non-medical use of prescribed opioids, with deaths by overdose and transition to heroin abuse rising at alarming rates3–6. The increasing availability of low-cost synthetic opioids, such as non-pharmaceutical fentanyls7, further feeds the epidemic. This opioid crisis has fostered novel public policies and much interest in developing better opioids to treat pain. For medical purposes8, the ideal opiate drug would relieve pain with high and sustained efficacy (that is, without tolerance), without the threats of res- piratory depression (the main cause of overdose) and without drug dependence (contributing to addiction).

The early 1970s saw the game-changing discovery that opiate drugs bind to receptors in the brain (see ref- erences cited in ref.1) and hijack a complex endogenous neuromodulatory system. The opioid system comprises three homologous G protein-coupled receptors (GPCRs) known as mu-, delta- and kappa-opioid receptors (MORs, DORs and KORs, respectively). Under physio- logical conditions, opioid receptors are stimulated by endogenous opioid peptides, forming a peptide family that includes β-endorphin, enkephalins and dynorphins.

Distributed throughout the nervous system, opioid pep- tides and receptors reduce responses to painful stimuli and stress, and influence reward processing and mood. The latter influence represents a fundamental role of the opioid system and will be a main focus of this Review. Note that the activity of the endogenous opioid system is extremely broad and covers many other aspects of phys- iology and behaviour (reviewed in ref.9), but these are less related to addiction and will not be discussed here.

In the late 1980s and early 1990s, the isolation of three genes encoding opioid peptide precursors (namely, POMC, PENK and PDYN, which encode proopiomelanocortin, preproenkephalin (also known as proenkephalin) and preprodynorphin (also known as prodynorphin), respectively) and the genes encoding MORs (OPRM1), DORs (OPRD1) and KORs (OPRK1) opened an era of molecular and genetic investigations of the opioid system10,11. Oprm1 deletion in mice simul- taneously eliminated the analgesic, rewarding and dependence-inducing effects of morphine12, demon- strating that the MOR is the sole responsible receptor for both the therapeutic and the adverse actions of morphine. The MOR is also the key molecular target for biological effects of other clinically useful and/or abused opiates (including heroin, fentanyl, oxycodone and methadone). Given the high risk of adverse effects of MOR agonists, the enthusiasm for drug discovery efforts targeting MORs abated in the late 1990s (although new efforts are starting; see Box 1).

On another front, Oprd1-knockout mice revealed that DORs have anxiolytic and antidepressant functions13, decidedly distinguishing this receptor from MORs. Many pharmacological studies have now implicated DORs in mood disorders and chronic pain14–16. By contrast, KOR activation produces both aversive and psychotomimetic effects17. This peculiar profile has strongly limited the

1Douglas Mental Health Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.

2Institut de Génétique et de Biologie Moléculaire et Cellulaire, INSERM, Centre National de la Recherche Scientifique and University of Strasbourg, Strasbourg, France.

*e-mail: brigitte.kieffer@ douglas.mcgill.ca

https://doi.org/10.1038/ s41583-018-0028-x

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Box 1 | can we kill pain without addiction using Mor opiates? Many drug discovery programmes targeting mu-opioid receptors (MOrs)

for analgesia without addiction have had limited success. However, recent advances in G protein-coupled receptor (GPCr) biology have revitalized the field.

Biased signalling

GPCr conformation depends on biological context. the active complex is determined by the drug and neighbouring proteins, including effectors150. thus, different agonists may engage distinct effectors, leading to
biased agonism (see part a of the figure). Biased MOr agonists might reduce pain with minimal adverse effects151–153 (part b of the figure). Mice lacking β-arrestin 2 (β-arr) — one of the two main MOr effectors — showed enhanced morphine analgesia154 and reduced morphine-induced constipation and respiratory depression155. G -biased MOr agonists that

other approaches
Other approaches163 (part c of the figure) include identifying compounds acting at multiple opioid receptors, opioid receptor dimers (MOr–delta-opioid receptor (DOr); see supplementary Box 1) or opioid–non-opioid receptor dimers (for example, MOr–CC-chemokine receptor 5 (CCr5)); compounds with agonist and antagonist activity at MOrs and ‘anti-opioid’ receptors (such as cholecystokinin, neurokinin 1 or the nociceptin peptide receptor), respectively; and compounds targeting effectors besides arrestins (for example, regulator of G protein signalling (rGs) proteins). in addition, a compound binding a truncated MOr isoform (lacking the first transmembrane domain) had an encouraging pharmacological profile, although with unusual properties164,165; the biological importance of this isoform remains unclear166.

in a novel approach (part c of the figure), the active MOr receptor structure167 was used to computationally simulate ligand docking at low pH, with the rationale that binding in an acidic environment might limit effects to injured sites. a pH-sensitive fluorinated fentanyl derivative called NFePP reduced inflammatory pain without central or intestinal effects168.

adverse effects might be limited by mimicking or enhancing endogenous opioid signalling (part d of the figure). endogenous opioid analogues with improved stability and bioavailability have been developed163. recently, MOr positive allosteric modulators were developed to act on allosteric sites (2) to facilitate agonism at the orthosteric site (1), strengthening MOr activity at the optimal times and sites, with fewer adverse effects (part d of the figure)169. BMs-986122 enhances opioid peptide-induced signalling170 and probably binds to the MOr Na+-binding site171. In vivo studies will show whether the concept holds to develop safer opioid analgesics. Part a is adapted with permission from ref.172, elsevier.

c Other approaches for better MOR analgesics

minimally recruit β-arr include trv130 (also known as oliceridine;

identified through cell-based assays)156, which is in a phase iii trial for analgesia157, mitragynine pseudoindoxyl (developed from natural products)158 and PZM21 (identified using computational docking)26. these compounds confer strong analgesia with reduced constipation and respiratory depression in rodents. Novel MOr agonists covering the entire Gi–β-arr bias range were recently designed, with Gi bias correlating with the analgesia–respiratory depression therapeutic window159.

Biased signalling in cells has not often been correlated with

addiction-related behaviours (for example, drug reward), as these in vivo

experiments are less amenable to medicinal chemistry efforts. the three compounds in part b do not induce conditioned place preference at analgesic doses26,158. However, further research should assess the hedonic and motivational properties of Gi-biased drugs; a first study has mixed conclusions160. Moreover, part of the gap between in vitro predictions and in vivo responses depends on location bias161 and systems bias162. studies on receptor signalling in different neuronal compartments and at different brain sites will expand in the future.

a Biased signalling and drug design Drug 1 Drug 2

Drug 3

• Multifunctional opioids • Dimer-specific opioids


d Endogenous signalling and allostery at MOR Endogenous opioid


Clinical and abused opioids



Gi/o-biased opioids

specific to ‘acidic’ receptor

E1 E2 E1

Low efficacy Optimal

b Biased signalling at MOR HO



E3 E2 Adverse effects



β-Arr •Constipation

• Respiratory depression





• Reward?
• Tolerance and/or dependence?

e, effector; r, receptor.

Gi/o Analgesia

Positive allosteric modulator





1 2



Mitragynine pseudoindoxyl

S O Br

O CH3 Cl BMS-986122


Signalling regulator Anti-opioid system



Temporally and spatially controlled enhanced signalling




Endogenous opioid analogue


© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.


Biased agonism

A signalling response determined by the conformation of the drug– receptor–effector complex that engages only a subset of cellular effectors. Some high-throughput screening programmes have aimed to design novel ‘biased’ drugs with improved therapeutic profiles.

Therapeutic window

Dose range for a drug that allows therapeutic efficacy with no (or minimal) side effects.

Location bias

Bias in receptor signalling dictated by the location of the receptor in the cell (for example, at the surface or in endosomes or golgi) and the availability of effectors at this site.

Systems bias

Bias in receptor signalling driven by anatomical localization within brain circuits subserving the behavioural response and the effectors available at those sites.

Precision medicine

Also known as personalized medicine. An innovative approach in medicine in which interindividual variability (in lifestyle, environment and genes) is taken into consideration for disease prevention and/or treatment.

Hedonic balance

The equilibrium between positive and negative affect. A positive hedonic state is considered a state of well- being, whereas a negative hedonic state is unpleasant.

development of KOR agonists for pain control and has given KORs a reputation of being associated with the ‘dark side’ of emotional and perceptual experience18,19 (Box 2). Overall, the very distinct profiles of MORs, DORs and KORs have now been clarified, and opportunities in opioid research are rapidly advancing.

The past decade has witnessed revolutions in GPCR structure and signalling research20,21. In 2012, the first atomic structures of the MOR22, DOR23, KOR24 and the structurally related nociceptin/orphanin FQ receptor25 (Box 3) solved by X-ray crystallography were published (fig. 1a), opening the way to design opioid drugs with entirely novel chemical scaffolds (for example, see ref.26) and perhaps to get closer to the ideal analgesic (Box 1). Many signalling effectors activated by opioid receptor stimulation have been identified (for example, those in fig. 1b). Furthermore, new technologies (such as neural tracing, connectome analysis, optogenetics and chemogenetics) enabled the dissection of neural circuit organization and function at microscale or macroscale levels27–29, and the notion of precision medicine is gradually entering the areas of pain30 and addiction31 treatment. Opioid research strongly benefits from advances in these domains, and this Review addresses three questions that arguably foster the strongest interest in current opioid research. First, can we kill pain without addiction using MOR-targeting opiates (addressed in Box 1)? Second, how do MORs and KORs operate within the neuro- circuitry of addiction? Third, can we bridge human and animal opioid research in the field of drug abuse?

Opioid receptors in addiction circuits

Experimental evidence from animal research has posi- tioned the role of the opioid system at the centre of reward and aversion processing, and has highlighted the notion that the dysregulation of opioid neurotransmission is a main driver to drug abuse (fig. 2).

Opioid system and reward–aversion in physiology.

Searching for reward (such as food, sex and social interactions) and avoiding punishment or discom- fort (for example, pain) are two fundamental forces

that drive decision making. Aminergic neurotrans- mitter systems (such as the dopamine (DA) and serotonin (5-HT) systems) have been extensively studied in this context. Circuit mechanisms encod- ing reward and/or aversion involve the activity and interaction (sometimes bidirectional) of overlapping networks32. The opioid system interacts anatomically and functionally with reward–aversion networks33,34, to maintain hedonic balance, regulate mood states and cope with stress (fig. 2a). Furthermore, the notions that, for example, endogenous opioids contribute to the rewarding effects of pain relief35 and that phys- ical and social pain (such as that associated with social rejection) share common opioid-mediated mechanisms36,37 are gaining interest.

Overall, the opioid system can be considered a central regulator in basic processes of individual and species survival, geared to enhance reward-based learning and reduce aversive experiences. Opioid receptors are therefore critical in the emergence of neuropsychiatric disorders that manifest when reward and aversion processing are dysfunctional. These pathologies primarily include addiction and depres- sion, and opioid receptor targets have therapeutic potential in both of these disease areas. Opioid recep- tor function in mood disorders has been reviewed elsewhere38.

Opioid receptors and the multiple faces of addiction.

Addiction is a complex, relapsing disorder in which drugs of abuse hijack, overstimulate and compromise reward-processing systems and associated networks. The disease develops from an initiation phase, during which the drug produces pleasurable effects and is consumed recreationally. Upon repeated consumption, control over drug taking is gradually lost, leading to compulsive drug seeking and drug taking39,40 (fig. 2b). Whereas recreational drug use is essentially motivated by reward seeking, drug intake in individuals who are addicted is also driven by other factors that arise owing to brain adaptations to chronic drug exposure (fig. 2b). These include reduced self-control41, enhanced incen- tive salience (that is, importance of the context) and habit formation42, altered reward processing and stress reactivity43, and the emergence of a negative affective state upon withdrawal19 or with protracted abstinence (see ref.44 and references therein).

Together, alterations of both positive and neg- ative affect contribute to the development and maintenance of addiction, and relevant transmitter and circuit adaptations are being actively studied39. All three opioid receptors are involved in the process, although with very different contributions (fig. 2b). The effects of MORs and KORs in regulating addic- tion networks and, more importantly, the neuronal populations in which these receptors operate, have been well characterized and are discussed below (fig. 2c). DOR-mediated circuit mechanisms contrib- uting to addiction have been less well studied using cell-specific genetic approaches (only one study45); thus, the current knowledge of DOR involvement in addiction is reviewed more briefly.

Box 2 | The intriguing hallucinogenic properties of Kor agonists

Beyond aversion, kappa-opioid receptor (KOr) agonists show hallucinogenic properties — a facet of KOr function that is unique among opioid receptors. salvinorin a is a natural product from the sage Salvia divinorum, or ‘magic mint’, that was long used by the Mazatecs of Oaxaca, Mexico for spiritual rituals and medicinal practice, and was recently discovered to be a specific KOr agonist173,174. salvinorin a is a highly potent hallucinogen for which the psychoactive effect is comparable to that of lysergic acid diethylamide (LsD). the use of salvinorin a, which is much less regulated than, for example, LsD use, is currently gaining popularity among young individuals in a recreational context.

the finding that this KOr agonist has psychoactive effects definitively establishes a specific role for KOrs in higher cognitive and perceptual functions, the dysregulation of which is associated with psychiatric disorders such as psychosis, bipolar disorders and dementia175. this particular KOr function remains poorly understood and adds another aspect to the known role of this receptor in stress responses, mood deficits and drug abuse. the circuits underlying this phenomenon are yet to be characterized. Notably, new analogues of salvinorin a with partial agonism or biased ligand properties are now proposed for the treatment of neuropsychiatric diseases, including addiction176; this research is still at an early stage.



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Reverse pharmacology

An approach in which a receptor or endogenous ligand is discovered first, the physiological function is determined.

Conditioned place preference
(CPP). A behavioural paradigm in rodents that determines the rewarding or aversive effect of a drug on the basis of time spent in a drug-associated context after conditioning.


(THC). The principal psychoactive component of cannabis, which produces central effects by acting at cannabinoid CB1 receptors.


A group of substances (including cocaine and amphetamines) that enhance physical and cognitive performance. Psychostimulants are used to treat attention deficit–hyperactivity disorder.

MORs in reward, motivation and self-control. MORs mediate the pleasurable properties of therapeutic and/or abused opiates in vivo. Importantly, genetic approaches have demonstrated that these receptors are also necessary for the rewarding effects of other drugs of abuse (reviewed elsewhere11,46 and in Supplementary Table 1). Briefly, Oprm1-knockout mice show lower levels of vol- untary alcohol drinking and self-administration (SA) and fail to express conditioned place preference (CPP) in response to tetrahydrocannabinol (THC) or nicotine. The latter molecules primarily activate non-opioid receptor targets (that is, cannabinoid receptors and nicotinic receptors, respectively), and these activated receptors, in turn, trigger opioid release at appropriate MOR- expressing brain sites to produce reward11. The data are less clear for cocaine and amphetamine, as Oprm1– knockout mice show decreased SA for these substances, but no change in CPP (see ref.11), consistent with the notion that psychostimulants hijack reward systems via mechanisms that do not necessarily engage MORs, at least for their rewarding effects47,48.

Genetic approaches have also demonstrated the essential role of MORs in mediating natural rewards. The constitutive Oprm1 deletion reduced maternal attachment in 4–8 day old mutant pups49; furthermore, adult knockout mice showed impaired social interac- tions together with several other signs of autistic-like behaviours50, confirming the essential function of MORs in social bonding that was previously suggested by the pharmacology36,38. Oprm1-null mutants also showed reduced motivation for both food and sucrose in an SA paradigm51. Finally, Oprm1-null mutant mice showed no

naloxone aversion in a conditioned place aversion (CPA) paradigm, indicating that MORs are crucial in mediat- ing the positive hedonic tone elicited by endogenous opioids52. Together, the findings above show that MOR activity both mediates natural rewards and promotes recreational drug use, with the latter in turn favouring the onset of drug abuse.

MORs are expressed throughout the addiction cir- cuitry53 (fig. 2c). Several brain sites for MOR-mediated reward have been identified by local pharmacology, and these mainly belong to mesocorticolimbic networks54. Central to this circuitry is the well-characterized ven- tral tegmental area (VTA)–nucleus accumbens (NAc; also known as the ventral striatum) DA pathway. The prevailing disinhibition hypothesis postulates that activation of MORs expressed by VTA GABAergic interneurons relieves the local inhibitory tone and thus disinhibits DA neurons, which release DA to sig- nal drug reward55,56. This hypothesis is supported by many pharmacology and electrophysiology studies57. However, this is not the only mechanism through which MORs affect DA signalling, as MORs are also abundant in brain areas that receive DA neuron projections and, notably, among NAc neurons that project back to the VTA58,59. Furthermore, DA-independent opioid reward is also documented60–63, but in fact little is known about MOR-expressing cells driving opioid reward outside the VTA.

A few studies using genetic approaches in mice have recently interrogated MOR function outside the VTA. In the striatum, MOR expression is robust in DA D1 receptor (D1R)-expressing medium spiny neurons

Box 3 | The opioid system’s cousin: the opioid-like receptor and nociceptin/orphanin FQ

the cloning of the opioid-receptor-encoding genes led to the identification of homologous G protein-coupled receptor (GPCr)-encoding genes,
some of which were known (such as those encoding somatostatin receptors). However, the closest homologue encoded a GPCr for which the ligand was unknown, thereafter named opioid-like receptor (OrL1). this receptor does not bind opioids with high affinity, and therefore cannot be classified as an opioid receptor. using reverse pharmacology177, two teams discovered its endogenous ligand, a 17-amino-acid peptide named either orphanin FQ178 or nociceptin179 based on its first reported characteristics (its peptide sequence and its effect on pain). this was one of the first GPCr de-orphanizations, and the receptor and peptide are now classically known as the nociceptin opioid peptide receptor (NOP) and N/OFQ, respectively.

strikingly, just as NOP shows the highest homology with the kappa- opioid receptor (KOr), the N/OFQ peptide shows sequence similarity with dynorphin (although lacking the amino-terminal tyrosine typical of opioid peptides), suggesting a common ancestor in evolution. similar to the opioid receptors, NOP is an inhibitory Gi/o-coupled GPCr that reduces neuronal activity and/or neurotransmitter release. Many synthetic NOP ligands developed in academia and industry180, as well as genetic mouse mutants, have been used to study the multiple in vivo functions of the NOP system and its potential interactions with the opioid system (reviewed in ref.181). NOP-regulated physiology and pathology cover areas of pain control, reward processing and drug abuse, stress, anxiety and mood disorders, feeding and obesity, motor control and cognition, and operate broadly in the nervous system (reviewed in refS181,182). to the best of our knowledge, no cell-specific genetic studies have yet addressed NOP function in defined brain networks or neuronal populations.

Much evidence supports a role for the N/OFQ–NOP system in addiction and this has been reviewed extensively180–182. in brief, N/OFQ and NOP

agonists reduce drug reward and basal or drug-induced (mostly cocaine- induced) dopamine release in the nucleus accumbens, alleviate signs of alcohol withdrawal and diminish stress-primed or drug-primed reinstatement of cocaine place preference, possibly by antagonizing corticotropin releasing factor (CrF) stress systems. Furthermore, the fact that N/OFQ blocks morphine-induced supraspinal analgesia and conditioned place preference suggests that the N/OFQ–NOP system acts as an anti-opioid system for some responses. indeed, NOP genetic inactivation or blockade reduces analgesic tolerance to morphine, confirming functional interactions between the two systems. rodent research has therefore positioned the NOP system as a feasible target for the development of addiction treatments.

at this stage, however, translation to non-human primates and the clinic may prove challenging for two reasons. First, the anatomical localization of the N/OFQ–NOP system seems to be different in rodent, non-human primate and human brains. the recent synthesis of positron emission tomography (Pet) tracers for NOP will help to guide clinical trials180. second, the effects of N/OFQ on the drug-abuse-associated aspects of physiology (such as stress and anxiety) have proved to be complex; both agonists and antagonists need be examined for their potential therapeutic utility. the current thinking is that NOP blockade has potential for treating depression and obesity, whereas NOP activation may reduce anxiety and help to treat several aspects of addiction, including a reduction of consumption and the prevention of relapse180,182; however, the best valid strategy remains open. as an illustration, a NOP agonist (cebranopadol; phase iii) and a NOP antagonist (JtC-801; phase ii) have both reached clinical trials to treat pain, and the NOP antagonist LY2940094 was tested in phase ii trials for major depressive disorders and for alcohol dependence180.

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a First solved atomic structure of opioid receptors



2 3










5 4



EC membrane


7 5




G protein- dependent signalling



b The active MOR and signalling effectors ECL2

Ca2+ channel

K+ channel


Helix8 5 6





IC membrane



JNK G protein-

independent signalling

Fig. 1 | opioid receptor structure and signalling. a | First resolved atomic structures of inactive opioid receptors and the nociceptin opioid peptide receptor (NOP); see Box 3). The receptors are bound to their specific antagonists — β-funaltrexamine (β-FNA) for the mu-opioid receptor (MOR)22, naltrindole for the delta-opioid receptor (DOR)23 and JDTic for the kappa-opioid receptor (KOR)24 as well as the peptide mimetic antagonist Compound 24 (C-24) for the NOP receptor25. The receptors each have seven transmembrane domains (numbered). DRY and NPXXY, shown here for the KOR structure, are conserved motifs important for receptor function. b | MOR activation and signalling in cells. The left side of the panel shows a comparison of the seven-helical arrangement of active (green) and inactive (blue)formsofthereceptor167.Themainmodificationisa10Åoutwardshift of the intracellular part of transmembrane domain 6, which typically interacts with cellular effectors and notably the Gα subunit of G proteins. The conformation of the extracellular receptor domains shows minimal changes. The structure also revealed a network of polar amino acid residues, which links the binding site to the cytoplasmic face of the receptor and is involved in G protein-coupled receptor (GPCR) signal propagation167. The switch from inactive to active structures was also probed using solution- state NMR, revealing that the conformational changes of transmembrane domains 5 and 6, the main receptor movements to reach full activation, require engagement of both the ligand and the G protein mimic in the complex183. The right side of the panel illustrates MOR signalling in cells.

All three opioid receptors are inhibitory-type GPCRs, the activation of which reduces postsynaptic neuronal excitability or presynaptic neurotransmitter release151. At the cellular level, opioid receptors activate G protein- dependent pathways involving both Gαi/o and Gβγ subunits, as well as G protein-independent signalling cascades that involve scaffold proteins such as arrestins (Arr). Altogether, many downstream signalling effectors have been identified for each receptor8,72,184,185. The scheme illustrates currently known effectors for MOR and indicates which are G protein-dependent (green) or G protein-independent (red) or whether G protein and/or Arr dependency is unclear (orange). The cell adapts to repeated receptor stimulation, leading to desensitization of receptor signalling (via, for example, receptor trafficking and effector uncoupling) and/or compensatory upregulation of related cellular pathways72. As for most GPCRs, opioid receptor activation is subjected to biased agonism; that is, the cellular and in vivo responses are often agonist-dependent185. AC, adenylyl cyclase; CAMKII, calmodulin-dependent protein kinase II; EC, extracellular; ECL, extracellular loop; ERK, extracellular-signal-regulated kinases; GRK, GPCR kinase; IC, intracellular; ICL, intracellular loop; JNK, Jun N-terminal kinase; MAPK, mitogen-activated protein kinase; PKA, protein kinase A; PKC, protein kinase C; STAT3, signal transducer and activator of transcription 3. Structures in part a adapted from refS22–25, Macmillan Publishers Limited. Structure in part b adapted from ref.167, Macmillan Publishers Limited.

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(so-called D1 MSNs) and is barely detectable in DA D2 receptor (D2R)-expressing MSNs (D2 MSNs)58,59. Rescuing MOR expression in D1 MSNs of Oprm1– knockout mice using a bacterial artificial chromosome Pdyn-MOR transgene restores morphine CPP and

partially restores remifentanil SA58, suggesting that MORs expressed in the striatonigral pathway (that is, by D1 MSNs) are sufficient to mediate opioid reward. However, whether this receptor population is neces- sary for drug reward is less clear. Conditional Oprm1

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p38 MAPK






a Opioid system physiology MOR


Hedonic tone

b Opioid receptors in the disease process Reward

• Adaptions to the drug • Lower reward
• MOR adaption


• Lower self-control
• Maladaptive habits
• Higher context salience






• Increased dysphoria • Lower mood
• Higher anxiety
• Increased stress



Recreational drug use


• Dysphoria stress • Negative affect

• Withdrawal
• Aversive state

• Binge
• Intoxication





c Opioid receptor function in addiction circuits



• Low anxiety
• Positive affect

• Preoccupation • Anticipation



















Fig. 2 | opioid receptors in physiology and addiction. a | Opioid receptors regulate reward and aversion. The opioid system contributes to self and species survival by promoting reward elicited by natural stimuli (such as food, sex and social interaction), regulating mood states and facilitating efficient coping with pain and stress. Mu-opioid receptors (MORs) and kappa-opioid receptors (KORs) oppositely regulate hedonic homeostasis, with MOR agonistsandKORagonistsproducingeuphoriaanddysphoria,respectively. Stress and drug abuse both enhance KOR–dynorphin (Dyn) signalling, contributing to an increase in dysphoric states43,83. By contrast, delta-opioid receptor (DOR) activity reduces anxiety and depressive states, and regulates learning and memory14,105. KOR blockade and DOR activation therefore have the potential to improve emotional responses. Finally, MORs and DORs show contrasting activities on motor impulsivity (see main text). Opioid receptors are therefore prime targets for the treatment of addiction and disorders such as depression38 that are characterized by low-reward or high-aversion states. b | Opioid receptors in the addiction cycle. In highly simplified terms, addiction can be characterized by ‘low-reward, high-aversion’ functioning, as negative affective states progressively overtake positive affect. A well- accepted view from animal research is that drug abuse unfolds as a three- stage cycling process, involving binge or intoxication episodes, followed by withdrawal and a negative affective state when the drug clears, in turn leading to a preoccupation or craving step, during which desire for the drug intensifies (craving) and triggers the next intoxication episode (inspired by refS39,40). Neuroplastic changes occur at all the stages, contributing to reinforce the addiction process in a vicious cycle; opioid receptors contribute to all facets of the disease. Animal data (see Supplementary Table 1 for behavioural models) indicate that MORs drive rewarding properties of opioid drugs (via direct, on-target effects) and other drugs of abuse (via indirect, opioid peptide-mediated effects) in both recreational consumption and binge or intoxication, and that repeated MOR activation leads to reduced drug reward (tolerance) and compensatory adaptations (dependence or withdrawal symptoms). KOR–Dyn activity is important in the negative affect that characterizes withdrawal as well as in short-term or prolonged abstinence, whereas DORs should limit development of this aversive state. All three opioid receptors probably influence the preoccupation– anticipation stage, and are implicated in drug-biased motivation, habit formation and loss of control, but these roles are less well understood. In the latter stage, or relapse to drug taking, evidence supports a role for DORs in

drug cue or context learning103. c | MOR and KOR function in neurocircuits of addiction. This simplified scheme summarizes animal data involving genetic or cell-specific approaches to study opioid receptors in circuits of addiction-related behaviours. Similar studies for the DOR are only just starting45. Brain regions involved in drug abuse are represented (circles) with their known connectivities (light grey lines) and include most regions studied inrodentaddictionresearch.Circlesareoutlinedindifferentcolours depending on whether the brain structure has been associated with binge or intoxication (orange), withdrawal or aversion (blue), or preoccupation or anticipation (red) stages and are based on information in refS39,40, with the addition of the habenula (HB) and dorsal raphe nucleus (DRN), which are the focus of increasing interest in the context of aversive aspects of addiction. Receptor density36,54 (represented in a naive mouse brain) is indicated for each region, and the opioid-receptor-regulated pathways identified in the studies discussed in this Review are shown by black arrows. In brief, MORs in GABAergic interneurons of the ventral tegmental area (VTA) facilitate dopamine release and drug reward57, whereas MORs in the striatum (nucleus accumbens (NAc) and caudate putamen (CP)), expressed mainly in dopamine D1-type neurons58,59, regulate both drug reward (for alcohol and morphine)58,64 and heroin seeking59. MOR adaptations in the DRN drive depressive-like states and social withdrawal in protracted heroin abstinence74. The roles of MOR-expressing cell populations in regions that modulate negative affective states, and in regions where the receptor is abundant (HB, DRN and amygdala (AMY)), remain to be studied. KORs in VTA dopamine neurons oppose MOR-stimulating activity at the level of terminals in the NAc and prefrontal cortex18,89 and disrupt behavioural inhibition94. KORs in NAc medium spiny neurons differentially gate D1 and D2 neuron activities and their AMY inputs to negatively regulate motivational processes91. KORs in DRN serotonin (5-HT) neurons promote stress-induced reinstatement to cocaine seeking96,97; KORs in excitatory basolateral amygdala (BLA) neurons projecting to the bed nucleus of stria terminalis (BNST) promote anxiety98; and KORs in GABAergic interneurons of the central AMY contribute to excessive alcohol drinking, probably through interactions with corticotropin releasing factor systems39,78,83. Finally, MORs and KORs are also expressed in brain regions involved in contextual memory and executive functions (including the hippocampus (HIP) and frontal cortex (FC))78,103, but the potential implication of these receptors in preoccupation or anticipation has not been studied so far.

Preoccupation or anticipation Withdrawal or aversive state Receptor density
Binge or intoxication Low Medium High


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Inhibitory controls

A central component of executive functions, geared to inhibit or delay dominant responses to achieve a goal.

deletion from GABAergic forebrain neurons (mostly from D1 neurons), using a Dlx5/6-Cre driver line in floxed Oprm1 mice, reduced voluntary alcohol drinking and alcohol CPP64, indicating that this receptor popula- tion indeed contributes to alcohol reward. Intriguingly, the latter genetic manipulation did not impair heroin CPP — presumably because VTA MORs were intact in these mice — but did increase seeking behaviour for heroin and palatable food in SA experiments59, dissoci- ating MOR-mediated hedonic effects from motivational regulation. Thus, in addition to driving pleasurable drug effects via VTA GABAergic interneurons and, to some degree, striatal MSNs (depending on the drug and par- adigm), MORs also regulate motivational aspects of behaviour, specifically at the level of striatal projecting neurons. This notion is consistent with sophisticated pharmacological studies that show that MORs not only assign hedonic values to rewards, but also contribute to decision making through coordinated activity in core and shell compartments of the NAc, which integrate reward-related information and guide goal-directed actions65.

MORs may also contribute to another facet of addiction — that is, impaired self-control — although this aspect has been less explored. Impulsivity is a critical susceptibility factor for addiction66, and inhibitory controls decline with disease development39. Strikingly, Oprm1– knockout mice showed remarkably lower motor impulsivity in a signalled nose-poke task67. The notion that MORs may facilitate the ‘loss of control’ that characterizes drug abuse is intriguing. Further studies are required to identify the key MOR-expressing neuron populations responsible for this effect.

An important question is whether, in addition to facilitating drug reward and drug seeking in the tra- ditionally studied mesocorticolimbic circuitry, MORs could also regulate aversion processing in other brain networks. The site of the densest MOR expression in the brain is, in fact, the medial habenula (MHb)68. The MHb and lateral habenula form the habenular com- plex, which is active in the anticipation of aversive outcomes and has garnered increasing interest in both addiction and depression research69,70. As the habenular complex is considered to be a centre for aversive pro- cessing and acts as an anti-reward system — notably, by inhibiting DA neuron activity — the hypothesis that MORs may regulate aversion processing, and perhaps limit aversive responses at the level of MHb neurons, is appealing, and investigations along these lines have just begun71.

Finally, an important consideration is that MORs are chronically activated under repeated drug expo- sure, and even more so under opiates. With chronic activation, receptor signalling adapts throughout the brain, triggering long-term molecular modifications within and outside the opioid system72; such neuroa- daptations to chronic opiates are being intensively studied73. Behavioural consequences of these adapta- tions include the development of tolerance (weakening drug effects with repeated exposure), and dependence (which manifests in the form of withdrawal symptoms when the drug is no longer present). Acute withdrawal

and prolonged abstinence from opiates are both associ- ated with negative emotional states that can be mode- lled in rodents44. In this context, MORs in the dorsal raphe nucleus (DRN), the main serotonergic nucleus, were shown to be crucial for the development of despair-like behaviour and deficits in social interac- tion in heroin-abstinent mice74. This finding indicates that DRN MORs regulate serotonergic transmission and that adaptations of MOR signalling in the DRN in response to chronic opiate exposure may profoundly alter mood during abstinence. This mechanism is parti- cularly interesting in the area of addiction–depression comorbidities75.

KORs in dysphoria, stress and depression. In contrast to MOR agonists, KOR agonists are strongly aversive. In humans, these drugs induce an acute dysphoric state, deteriorate mood and have psychotomimetic effects17,76 (Box 2). These KOR activities may have strong implica- tions for several psychiatric disorders, including drug abuse, affective disorders and, potentially, psychosis18.

Animal model research has established that the KOR and dynorphin, the preferred endogenous KOR ligand, form an ‘anti-reward’ brain system43,77. Notably, in the absence of environmental challenge, the endogenous KOR–dynorphin system has only subtly dysphoric activ- ity; however, this system is highly responsive to stress78, and accumulating evidence has shown that addiction dramatically activates brain stress systems, includ- ing endogenous KOR signalling43,79–81. In turn, these events facilitate the emergence of a negative affective state — which characterizes withdrawal episodes of the addiction cycle as well as protracted abstinence82 — and promote escalation of drug consumption, stress- induced potentiation of drug reward and stress-induced reinstatement of drug seeking83,84.

KORs are expressed at many sites in the addiction neurocircuitry (fig. 2c), and a circuit mechanism for KOR-mediated dysphoria has long been proposed. Behavioural analyses have demonstrated CPP and CPA in response to MOR agonists and KOR agonists, respectively, and microdialysis studies have revealed opposing activities for the two types of drugs on DA release, with MOR agonists disinhibiting VTA DA neurons at the level of the cell bodies and KOR ago- nists inhibiting DA-releasing terminals in the NAc85,86. These seminal findings may explain why MORs and KORs have such contrasting effects (that is, euphoria and dysphoria, respectively), and have established the notion that endogenous activities of the two receptors fine-tune DA tone to regulate hedonic homeostasis. Accordingly, deletion of Oprk1 from DA neurons reduced CPA to KOR agonists87, had anxiolytic effects and enhanced cocaine-stimulated locomotor activity88. Electrophysiology demonstrated that KORs in DA neurons inhibit terminals not only in the NAc, but also in the prefrontal cortex (PFC)89. As in the NAc, KORs reduced DA release locally in the PFC via a presynaptic mechanism and thus contributed considerably to KOR agonist-induced CPA90. Therefore, KORs in DA neurons produce dysphoria via presynaptic inhibition at both NAc and PFC sites.



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Operant photostimulation

instrumental conditioning in which animals learn to self- administer optogenetic stimulation; used to determine whether a neuronal population mediates reward.


in animal research, extended access to the drug leads to a daily increase (or escalation) of drug intake, which is suggested to reflect loss of control.

In the NAc, KORs are expressed by D1 and D2 MSNs and at the terminals of glutamatergic projections from the basolateral amygdala (BLA), and dynorphin is produced by D1 MSNs. A recent optogenetic study examined KOR function throughout the entire NAc microcircuitry and demonstrated that two distinct pre- synaptic KOR-mediated mechanisms regulate D1 and D2 MSN activities: one pathway-specific (affecting BLA inputs to the NAc) and the other local (affecting MSN collaterals)91. This study reveals a mechanism whereby KORs in the NAc dampen excessive MSN activation that is driven by incentive stimuli or stress, thereby limiting reward-seeking behaviour. Thus, in addition to the role of KORs in influencing euphoria–dysphoria balance, the notion that KORs negatively regulate motivation is also gaining support. Another optogenetic manipulation revealed functional heterogeneity among Pdyn-positive neurons (D1 MSNs) in the NAc92. Photostimulation of these neurons in the dorsal or ventral NAc shell pro- duced approach or avoidance behaviour, respectively, in a real-time place-preference assay. These opposing effects were both mediated by KORs and were confirmed by operant photostimulation. These findings add support to the emerging notion that reward and aversion mech- anisms are highly intermingled within the NAc (as was previously shown for the VTA93) and further support the view that dysfunctional KOR–dynorphin activity in the NAc affects motivated behaviours. Another study in mice used an operant test of cognition (in which lower rates of response were differentially reinforced) to show that both stress and KOR activation impair behavioural inhibition, an effect prevented by Oprk1 gene deletion in DA neurons94. Thus, KOR blockade might reduce stress- induced compulsive behaviours that contribute to drug seeking and addiction.

KOR activity modulates other brain regions and transmitter systems (in addition to the DA system) that are crucial for negative mood and aversive responses (reviewed in ref.78). First, KORs in the DRN modulate 5-HT transmission, similar to how they modulate DA release from VTA neurons. Local application of a KOR agonist decreased 5-HT release in the DRN95, suggest- ing that a low DA tone may not be the sole cause for KOR-mediated dysphoria and that reductions in 5-HT may also contribute. Accordingly, a KOR antagonist infused in the DRN abolished the CPA induced by systemic KOR agonist administration, and prevented stress-induced reinstatement of cocaine CPP, through a mechanism that involved p38 mitogen-activated protein kinase (MAPK) in 5-HT neurons and their projections to the NAc96,97. Second, amygdala-based mechanisms contribute to KOR-mediated anxiety. Oprk1 deletion in the BLA was anxiolytic in mice, and the anxiolytic effects produced by photostimulation of the BLA–bed nucleus of stria terminalis (BNST) pathway were blocked by systemic administration of a KOR agonist98. The same study also showed that KORs inhibit excitatory BLA terminals in the BNST, and that dynorphin in the BNST thus regulates the activity of BLA–BNST projections to control the amygdala-centred anxiety circuit. KOR activity in the central amygdala (CeA) was also studied in the context of alcohol dependence. Infusion of a KOR

antagonist into the CeA reduced the increase in alcohol SA elicited by chronic intermittent exposure to alcohol vapours (a procedure designed to trigger escalation of alcohol consumption)99. Slice electrophysiology showed that KORs tonically inhibit local GABAergic transmis- sion in the CeA via a presynaptic mechanism and has thus been proposed to regulate the effects of ethanol there100,101. KORs also interact in a complex manner with the stress hormone corticotropin releasing factor (CRF)102. This KOR–CRF signalling interaction is being increasingly studied for a role in the pro-addictive effects of stress, in anxiety disorders and in related psychiatric conditions (reviewed elsewhere39,78,83).

DORs in mood and learning. Similar to MORs and KORs, DORs contribute to the development of drug abuse, although very differently from the two other receptors. Oprd1-knockout mice show intact mor- phine SA, intact THC CPP, decreased nicotine SA and increased alcohol SA (reviewed in refS11,38 and see Supplementary Table 1). Therefore, contrary to MORs, DORs are not essential for drug reward. Rather, as pro- posed by pharmacological studies, DORs seem to have a complex regulatory role in motivated behaviours65,103.

Unlike Oprm1-knockout mice and Oprk1-knockout mice, DOR-null mutants show a remarkable anxiogenic and depressive-like phenotype, largely confirmed by pharmacological approaches14,104, suggesting that DOR activity normally helps to alleviate the negative mood associated with acute withdrawal and prolonged absti- nence. In support of this notion, Oprd1-knockout mice undergoing protracted abstinence to heroin show exac- erbated sucrose anhedonia74. Another role of DORs with potential relevance to addiction is the regulation of learning and memory (reviewed elsewhere103,105). DOR-null mice show impaired spatial learning and, consistently, reduced drug–context association in CPP paradigms106. These and other observations suggest that DOR activity in fact enhances drug–context memories and facilitates relapse. These findings would suggest that the DOR is pro-addictive; however, by alleviating the low affect associated with withdrawal, DOR activity may also prevent relapse. In addition, opposing the pheno- type of MOR-null mutants, Oprd1-knockout mice show increased motor impulsivity in a signalled nose-poke task67, suggesting that DOR activity increases inhibitory controls. Thus, altogether, the role of DORs in addiction is complex.

DORs are expressed in all areas subserving reward and motivation, mood control, and learning and memory53,54. The identification of circuit mechanisms underlying addiction-related functions of DORs through cell-specific genetic approaches is just starting. Only one conditional Oprd1-mutant mouse has been produced, demonstrating that DORs in GABAergic forebrain neurons mediate the locomotor-stimulant effect of SNC80 (a prototypic DOR agonist), counteract D1R agonist-induced hyperactivity and exert an anxio- genic effect45. Further cell-targeted genetic studies in the future may address, for example, the intriguing proposed role of DORs in stimulus-based decision-making at the level of the BLA–NAc shell circuit65.

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Table 1 | Genetic mouse mutants to study opioid receptors in addiction


Mouse line

Tool description



Targeting the receptor gene

Knock-in mice with floxed opioid- receptor-encoding alleles crossed with Cre lines to delete receptor genes in specific cell populations

Dlx5/6-Cre-mediated conditional knockout of Oprm1 in forebrain GABAergic neurons

• ↑ Motivation for heroin and food SA • ↓ Voluntary alcohol drinking


Dlx5/6-Cre-mediated conditional knockout of Oprd1 in forebrain GABAergic neurons

• ↓ Anxiety
• Abolished agonist-induced locomotor



Dat-Cre-mediated conditional knockout of Oprk1 in DA neurons

• Abolished CPA to KOR agonists (U69,593 and U50,488)

• ↑ Locomotor sensitization to cocaine


Knock-in reporter mice expressing a functional tagged version of the opioid receptor to allow receptor detection

Oprm1 with carboxy-terminal mCherry fusion

MOR anatomy visualized at brain, neuron and subcellular levels


Oprd1 with carboxy-terminal eGFP fusion

• DOR anatomy visualized at brain, neuron and subcellular levels

• DOR trafficking in primary neurons detected in real time

•Receptor trafficking was linked to tolerance


Oprd1 with amino-terminal HA tag fusion combined with a floxed exon 1 for the conditional deletion of tagged DORs in targeted neuron populations

Mouse line characterized


Overexpressing the receptor gene

Transgenic lines expressing wild-type opioid receptors

Pdyn-MOR transgene on an Oprm1-knockout background to rescue MOR expression in striatopallidal neurons

MOR rescue restored morphine reward and partly restored remifentanil SA


Dat-Cre-dependent viral expression of KORs on an Oprk1-knockout background, to rescue KOR expression in DA neurons

KOR rescue restored KOR agonist (U50,488)-induced CPA


Transgenic lines expressing mutant opioid receptors

Light-activatable opto-MOR virally expressed in GABAergic RMTg and VP neurons

Real-time place preference or avoidance was dependent on the photostimulated area


Viral KOR-DREADD expressed in VTA and SN or subiculum projections to the NAc

• KOR-DREADD activation in the midbrain (VTA and SN) reduced cocaine-induced hyperlocomotion

• KOR-DREADD activation in subiculum projections to NAc reduced context- induced relapse to alcohol seeking


Targeting opioid-receptor-expressing or peptide-expressing neurons


Cre recombinase expressed in Pomc-positive neurons that produce β-endorphin

Not used in addiction-related studies



Cre recombinase expressed in Penk-positive neurons that produce preproenkephalin

Not used in addiction-related studies



Cre recombinase expressed in Pdyn-positive neurons that produce preprodynorphin

Optogenetic activation of Pdyn-expressing cells in the NAc shell produced aversion (ventral) or preference (dorsal) depending on the targeted subregion



Cre recombinase expressed in KOR-positive neurons

Mouse line characterized


CPA, conditioned place aversion; DA, dopamine; Dat, gene encoding DA transporter; Dlx5/6, genes encoding homeobox proteins DLX5 or DLX6; DOR, delta- opioid receptor; DREADD, designer receptor exclusively activated by designer drugs; eGFP, enhanced green fluorescent protein; HA, human influenza haemagglutinin; IRES, internal ribosome entry site, KOR, kappa-opioid receptor; MOR, mu-opioid receptor; NAc, nucleus accumbens, Oprd1, gene encoding DOR; Oprk1, gene encoding KOR; Oprm1, gene encoding MOR; opto-MOR, optically sensitive MOR; Pdyn, gene encoding preprodynorphin; Penk, gene encoding preproenkephalin; Pomc, gene encoding proopiomelanocortin; RMTg, rostromedial tegmental nucleus; SA, self-administration; SN, substantia nigra; VP, ventral pallidum; VTA, ventral tegmental area. aMice generated by the Allen Institute.

The gap between basic knowledge and treatment strategies. As described above, anatomical and phar- macological studies have shown that MORs, KORs and DORs operate at many sites of addiction circuits, and genetic approaches have identified several molecu- lar and neuronal mechanisms underlying MOR and KOR activities at distinct stages of the disease (fig. 2b,c). Genetic

tools to manipulate opioid receptors or the specific neu- rons that express them are developing rapidly107 (TABle 1). More circuit mechanisms subserving MOR-controlled and KOR-controlled behaviours related to drug abuse will undoubtedly be discovered, and the contribution of DORs to this circuitry — particularly in emotion, motivation and learning networks — will also be clarified38,103,105.

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Quantitative trait loci

genomic regions that carry one or more DNA mutations that correlate with phenotypic variations (for example, behaviour, gene expression and protein levels).

Machine learning

A research field in which computers learn to extract patterns from complex data sets without being explicitly programmed for this goal. Helps biologists to build predictions.

In principle, opioid receptors should be ideal targets to treat drug abuse. MOR blockade could reduce drug reward, the motivation to seek drugs and compulsive behaviour. KOR blockade should limit dysphoric states associated with stress and drug withdrawal, and help to prevent stress-induced relapse. Blocking KORs may also reduce compulsivity (although it could promote drug reward). Finally, DOR activation should reduce anxiety and limit compulsivity but may also facilitate drug–context learning. Although circuit analyses will not directly facilitate drug discovery to treat addiction, they should provide a better understanding of drug effects and help target development of therapeutic drugs to specific aspects of this complex disorder, including withdrawal, distinct recovery stages and complete abstinence.

Today, amazingly few opioid drugs are available and used in clinical practice. Naltrexone (a MOR antagonist) is a labelled medication that is used to treat alcohol abuse108 and shows some success for other non-opioid substance or behavioural addictions109 by reducing MOR-mediated reward. Methadone (a partial MOR agonist) and buprenorphine (a partial MOR agonist and KOR antagonist) show good efficacy to treat opioid addiction, essentially as replacement therapies110–112. The KOR antagonist activity of buprenorphine is believed to contribute to its therapeutic success, and pure KOR antagonists are being developed to treat addiction84, anxiety and depression113. One KOR blocker (JDTic) failed a phase I trial owing to some adverse effects includ- ing tachycardia, and another KOR blocker (CERC-501) is currently in trials for smoking cessation, treatment- resistant depression and anxiety disorder (phase II for all)114. The convergence of animal and human research should lead to an expansion of the therapeutic potential of opioids for drug abuse disorders.

Bridging the translational gap

Several lines of research will help to bridge the trans- lational gap between the genetic and pharmacological studies in animal models described above and the development of novel opioid receptor-targeting strat- egies (that is, innovative drugs and/or personalized treatments) to treat addiction in the clinic. Notably, human research includes genetic association studies and neuroimaging research, which unequivocally indicate that opioid receptors — particularly MORs — are associated with the development of addiction.

Gene variability. Drug addiction is partly heritable; therefore, genetic factors contribute to addiction vul- nerability115. Over two decades, association studies have established that all opioid-encoding or opioid- receptor-encoding genes are loci associated with the potential risk of opioid addiction116 or other substance use disorders117. In the case of opioid dependence, for example, risk associations have been found for var- iants of OPRM1, OPRK1, OPRD1 and PDYN116,118 as well as POMC and PENK variants (although the latter two associations require replication)116. Genetic and epigenetic data from studies on the opioid system have been reviewed very recently in the context of addiction biomarker discovery119.

The most common and best-studied variant associ- ated with drug addiction is the A118G single-nucleotide polymorphism (SNP) in the OPRM1 gene (rs1799971, exon 1), which is frequent in non-African popula- tions (16% in Europeans and 38% in Asians) and less frequent among African Americans (3%)120. This non- synonymous substitution creates a new CpG site for DNA methylation and leads to an Asn40Asp substitution in the extracellular amino-terminal domain of the recep- tor protein — two possible reasons for the reduced MOR expression and signalling detected in cell cultures121 and post-mortem human tissues122 expressing this variant. To date, many candidate gene studies have correlated the presence of this particular OPRM1 SNP with opioid dependence, responses to opioid pharmacotherapy, alcoholism and nicotine dependence120 (TABle 2).

This particular coding OPRM1 SNP, however, may not be the sole factor involved in these associations, as other intronic and synonymous coding variants may affect gene function at the level of transcription, mRNA stability and splicing. Recently, a cis-expression quantitative trait loci mapping study identified several other OPRM1 polymorphisms altering OPRM1 expres- sion in PFC samples from the BrainCloud cohort123 and tested their association with risk of heroin addiction124. Four SNPs were associated with the condition, and this association was replicated only when the A118G SNP was in the presence of another SNP in intron 1 (rs3778150), indicating that nearby intronic SNPs may instead underlie the inconsistent associations of the main A118G SNP with heroin addiction124 and alcohol addiction125. In another study, the rs3778150-rs1799971 haplotype was also associated with several alcohol-use phenotypes126. More recently, a genome-wide associ- ation study (GWAS) revealed a significant association between a single SNP (rs73568641) and methadone maintenance therapy in African Americans but not in European Americans; interestingly, the closest gene to this SNP is OPRM1 (ref.127). Future GWAS using novel unbiased machine learning approaches should efficiently address the complexity of allele combination effects.

The A118G SNP was transposed into mice using two knock-in approaches, together representing one of the very few attempts to model a human vulnerability gene for a psychiatric disorder. In one knock-in mouse line, the major Oprm1 allele was replaced by a mouse allele carrying the SNP corresponding to the A118G SNP in humans (A112G)128. The other experimental design cre- ated two humanized mouse models harbouring either the major (A118) or minor (G118) human OPRM1 exon 1 (ref.129). Mutant mouse phenotypes were analysed in depth, but unfortunately the two lines have not been compared in similar paradigms and, as such, phenotype comparison is not straightforward (TABle 2). Of note are the parallel findings of increased heroin and nicotine SA as well as increased heroin-induced and alcohol-induced DA release in A112G knock-in mice and humanized A118G mice, respectively. Importantly, two studies have directly compared human and mouse phenotypes using the humanized mouse model129,130, demonstrat- ing the potential for translation from mouse to human research. Striatal DA release in response to an alcohol

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Table 2 | effects of the OPRM1 A118G polymorphism in humans and mouse models

Population or model

substance or stimulus



Human studies

Polymorphism ID rs1799971, exon 1, A118G


118G allele increased risk of opioid addiction


No association with or protection from opioid addiction was found



118G allele increased risk of alcohol addiction


Only 118G carriers showed a striatal DA response to alcohol



118A allele was associated with increased euphoria and stimulant effect of amphetamine



118G allele was associated with increased pleasurable nicotine effects


Mouse studies

A112G knock-in mice


112GG increased heroin SA and striatal DA release


• 112GG reduced morphine-induced locomotor stimulation

• Female 112GG carriers did not show place conditioning to morphine


112GG reduced buprenorphine-induced locomotor stimulation


Social defeat

112GG mice were resilient to social defeat


Mouse exon 1 replaced by human A118G exon 1


118GG decreased morphine and hydrocodone reward (via intracranial self-stimulation) and DA release in the nucleus accumbens


118GG decreased morphine-induced locomotor stimulation


Place conditioning to morphine was unchanged



118GG increased alcohol-induced DA releasea


118GG increased efficacy of naltrexone and nalmefene in reducing operant alcohol SA



118GG increased nicotine SA in male but not female micea


Receptor bioavailability

Also known as receptor binding. The quantity of radiotracer that binds to its target receptor in positron emission tomography imaging. Depends on receptor levels and occupancy by endogenous ligands.

challenge was enhanced for G-allele carriers in mice and in humans129, and the pleasurable effects of nicotine in humans or nicotine SA in mice were increased in males, but not females, of each species130.

The mouse data are certainly complex and do not exactly match the human findings. Nevertheless, the hypothesized reductions in MOR availability and function, in cells and throughout the brain of A118G carriers, seem to modify the neurobiology of drug reward. Altered reward processing may be one of the mechanisms underlying the reported higher risk of addiction in these individuals.

Neuroimaging. Non-invasive neuroimaging techniques, including positron emission tomography (PET) and MRI, have been used for decades to explore neurotrans- mitter system activities and whole-brain functioning in humans and are used to evaluate, for example, the efficacy of addiction treatments131. Rodent neuroimaging using similar approaches has lagged behind owing to limited resolution but is gaining interest as methods improve.

PET imaging seeks to map and quantify receptor occupancy throughout the brain using radiolabelled tracers. receptor bioavailability, also known as binding potential (BP), varies depending on receptor expres- sion and localization, levels of endogenous ligand and the binding of exogenous drugs. For opioid receptors, most reports describe MOR BP using 11C-carfentanil, a highly selective, high-affinity MOR agonist, whereas DORs or KORs remain difficult to study owing to the paucity of suitable tracers132. Overall, MOR bioavailabil- ity is modified by exposure to drugs of abuse (including opiates, cocaine, alcohol and nicotine), drug craving and dependence, opioid pharmacotherapy, affective experiences and pain states (reviewed in refS119,132).

Recently, 11C-carfentanil PET imaging revealed that MOR BP is reduced in the frontal cortex of people who smoke cigarettes and correlates with cigarette liking and wanting, suggesting a MOR-mediated activation mechanism for nicotine reward and dependence133. In a separate study, a short overnight abstinence period was sufficient to decrease MOR BP in smokers compared

DA, dopamine; SA, self-administration. aThese studies directly compared the human and mouse phenotypes.

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Effective connectivity

in functional Mri, a measure of the influence of one brain region on the activity of another brain region.

with non-smokers, and the reduction of MOR availabil- ity in the basal ganglia was correlated with craving and the severity of nicotine dependence134. Moreover, the A118G SNP was associated with lower baseline MOR BP in the NAc and amygdala of smokers134. Another autoradiographic study showed a reduction of MOR binding sites in post-mortem striatal tissue from individ- uals with alcoholism, paralleling low MOR BP in patients with alcoholism. PET imaging also revealed that a reduc- tion in MOR availability in detoxified alcohol-dependent patients may be associated with a higher risk of relapse135.

Intriguingly, recent PET studies have also revealed the role of MORs in natural rewards and behavioural addic- tions. Lower MOR BP has been consistently reported among individuals showing pathological gambling or binge eating136,137, and even in obese individuals who self-report food addiction138. High-intensity training, but not moderate exercise, decreased MOR BP in fronto- limbic regions related to reward and emotional process- ing and correlated with euphoria, consistent in this case with the notion that endogenous opioid peptide release may reduce MOR availability139. Along these lines, social interactions such as social touch140 and social laughter141 modulate MOR availability. Although the interpretation of these two studies seems complex, the link between social behaviour and opioidergic activity has been well established in humans. More generally, PET-based evi- dence suggests that MOR-mediated endogenous opioid activity facilitates approach-oriented emotions (such as anger and pleasure), inhibits avoidance-oriented emo- tions (such as fear or sadness) and modulates affiliative behaviours in humans142. Human studies therefore con- verge well with animal research to demonstrate that the MOR is important in reward–aversion processing and promotes sociability and resilience to stress and that changes in MOR-mediated opioidergic activity may therefore contribute considerably to the development and maintenance of addiction.

Functional MRI (fMRI) is being increasingly used to assess brain activation patterns and functional connectivity, and a variant of fMRI known as phar- macological MRI (phMRI)143 has allowed the mapping of the acute effects of opioids in the human brain. In healthy, opioid-naive individuals, a morphine challenge increased and decreased blood-oxygen-level-dependent (BOLD) signals in the NAc (the key reward centre) and the periaqueductal grey (which processes pain), respectively144. In a subsequent study, buprenorphine dose-dependently increased BOLD signals in several brain structures (anterior cingulate, frontal cortex, cau- date putamen, insula and periaqueductal grey), and the pattern was similar in healthy human participants and in awake, naive rats, demonstrating the translatability of the phMRI approach145. In the future, refined drug phMRI ‘signatures’ should guide dose selection for therapeutic development and clinical trials and provide brain-level mechanistic insights into the incompletely understood and variable in vivo effects of biased MOR agonists that are currently being developed (Box 1) or MOR agonists already used in the clinic.

Resting-state fMRI (rs-fMRI) has also been used to investigate brain network activities at rest and

to characterize long-term modifications of brain states with chronic drug exposure. A set of 21 studies assessing individuals with a history of heroin use was recently meta-analysed. All of these studies pointed to alterations in connectivity that converge to pro- mote dysfunctional decision-making and indicated that network modifications increase with the surveyed duration of heroin exposure and last for a long time after becoming abstinent146. Heroin-abstinent individuals also all showed differences in the strength of functional connectivity in brain systems involved in reward pro- cessing, stress responses and impulsivity147. A recent study analysed changes in connectivity in individuals who were formerly addicted to heroin and were under methadone maintenance therapy. effective connectivity was measured for four networks (reward, motivation, memory and cognitive control). Whereas reward and cognitive control centres were more weakly connected with the rest of the brain, learning-related and memory- related centres were more strongly connected than in heroin-naive individuals148. These findings are particu- larly interesting with regards to bridging human and animal research as similar processes are modelled in preclinical research (fig. 2b).

Finally, fMRI is now being developed in mice to study MOR activation and function, with the unique advantage of including Oprm1-knockout groups in the experimental design to isolate on-target MOR-mediated effects. phMRI analysis of oxycodone effects in awake mice identified an activation pattern149 with anatomi- cal similarities to the effects of morphine in humans145. Furthermore, an unbiased rs-fMRI analysis comparing whole-brain activity in anaesthetized mice revealed that Oprm1-knockout mice show perturbed resting-state functional connectivity, with predominant alteration of the connectivity of reward and aversion centres34. These recent studies indicate that fMRI is now feasible in mouse genetic mutants with a resolution comparable to that in human imaging and open exciting new perspec- tives for connectome genetics29, therapeutic design143 and the search for biomarkers119 in opioid research.


Research in humans and animal models has firmly established that opioid receptors are central to reward and aversion processing in the normal brain and con- tribute to the development of addiction. The supporting literature is huge, and this Review focuses on recent pro- gress and promises for innovative therapeutic discovery and therapeutic strategies as well as the translational potential of opioid research in addiction.

In summary, MORs, DORs and KORs contribute to distinct and specific aspects of the disease: MORs promote recreational drug use (including opioids and others) and adapt to chronic activation (leading to tol- erance and dependence); KORs enable and sustain aver- sive states of withdrawal and abstinence; DORs improve mood states and facilitate context learning; and all three receptors modulate motivation. That both MOR and KOR activities drive the onset, progression and main- tenance of addiction is well recognized, whereas the contribution of DORs remains less straightforward.

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1. Brownstein, M. J. A brief history of opiates, opioid peptides, and opioid receptors. Proc. Natl Acad. Sci. USA 90, 5391–5393 (1993).

2. World Health Organization. Curbing prescription opioid dependency. WHO http://www.who.int/bulletin/ volumes/95/5/17-020517/en/ (2017).

3. Kolodny, A. et al. The prescription opioid and heroin crisis: a public health approach to an epidemic of addiction. Annu. Rev. Publ. Health 36, 559–574 (2015).

4. Volkow, N. D. & McLellan, A. T. Opioid abuse in chronic pain — misconceptions and mitigation strategies. N. Engl. J. Med. 374, 1253–1263 (2016).

5. Voon, P., Karamouzian, M. & Kerr, T. Chronic pain and opioid misuse: a review of reviews. Subst. Abuse Treat. Prev. Policy 12, 36 (2017).

6. Compton, W. M., Jones, C. M. & Baldwin, G. T. Relationship between nonmedical prescription-opioid use and heroin use. N. Engl. J. Med. 374, 154–163 (2016).

7. Suzuki, J. & El-Haddad, S. A review: fentanyl and non-pharmaceutical fentanyls. Drug Alcohol Depend. 171, 107–116 (2017).

8. Al-Hasani, R. & Bruchas, M. R. Molecular mechanisms of opioid receptor-dependent signaling and behavior. Anesthesiology 115, 1363–1381 (2011).

9. Bodnar, R. J. Endogenous opiates and behavior: 2015. Peptides 88, 126–188 (2017).

10. Kieffer, B. L. & Gaveriaux-Ruff, C. Exploring the opioid system by gene knockout. Prog. Neurobiol. 66, 285–306 (2002).

11. Charbogne, P., Kieffer, B. L. & Befort, K. 15 years of genetic approaches in vivo for addiction research: opioid receptor and peptide gene knockout in mouse models of drug abuse. Neuropharmacology 76, 204–217 (2014).

12. Matthes, H. W. et al. Loss of morphine-induced analgesia, reward effect and withdrawal symptoms in mice lacking the mu-opioid-receptor gene. Nature 383, 819–823 (1996).
This is a genetic demonstration that both therapeutic and unwanted morphine effects are mediated by a single receptor protein (MOR).

13. Filliol, D. et al. Mice deficient for delta- and mu-opioid receptors exhibit opposing alterations of emotional responses. Nat. Genet. 25, 195–200 (2000).

14. Pradhan, A. A., Befort, K., Nozaki, C., Gaveriaux-Ruff, C. & Kieffer, B. L. The delta opioid receptor: an evolving target for the treatment of brain disorders. Trends Pharmacol. Sci. 32, 581–590 (2011).

15. Chu Sin Chung, P. & Kieffer, B. L. Delta opioid receptors in brain function and diseases. Pharmacol. Ther. 140, 112–120 (2013).

16. Spahn, V. & Stein, C. Targeting delta opioid receptors for pain treatment: drugs in phase I and II clinical development. Expert Opin. Investig. Drugs 26, 155–160 (2017).

17. Pfeiffer, A., Brantl, V., Herz, A. & Emrich, H. M. Psychotomimesis mediated by kappa opiate receptors. Science 233, 774–776 (1986).

18. Tejeda, H. A., Shippenberg, T. S. & Henriksson, R. The dynorphin/kappa-opioid receptor system and its role in psychiatric disorders. Cell. Mol. Life Sci. 69, 857–896 (2012).

19. Koob, G. F. The dark side of emotion: the addiction perspective. Eur. J. Pharmacol. 753, 73–87 (2015). 20. Kobilka, B. The structural basis of G-protein-coupled

receptor signaling (Nobel Lecture). Angew. Chem. Int.

Ed Engl. 52, 6380–6388 (2013).
21. Audet, M. & Bouvier, M. Restructuring G-protein-

coupled receptor activation. Cell 151, 14–23 (2012). 22. Manglik, A. et al. Crystal structure of the micro-opioid

receptor bound to a morphinan antagonist. Nature 485, 321–326 (2012).
This study reports the atomic structure of the MOR solved by X-ray crystallography and is published back to back with the first atomic structures of the three other opioid and opioid-like receptors, all bound to antagonists.

23. Granier, S. et al. Structure of the delta-opioid
receptor bound to naltrindole. Nature 485,
400–404 (2012).
This study reports the atomic structure of the DOR solved by X-ray crystallography and is published back to back with the first atomic structures of the three other opioid and opioid-like receptors, all bound to antagonists.

24. Wu, H. et al. Structure of the human kappa-opioid receptor in complex with JDTic. Nature 485, 327–332 (2012).
This study reports the atomic structure of the KOR solved by X-ray crystallography and is published back to back with the first atomic structures of the three other opioid and opioid-like receptors, all bound to antagonists.

25. Thompson, A. A. et al. Structure of the nociceptin/ orphanin FQ receptor in complex with a peptide mimetic. Nature 485, 395–399 (2012).
This study reports the atomic structure of the NOR solved by X-ray crystallography and is published back to back with the first atomic structures of the three other opioid and opioid-like receptors, all bound to antagonists.

26. Manglik, A. et al. Structure-based discovery of opioid analgesics with reduced side effects. Nature 537, 185–190 (2016).
This study reports computational screening based on the MOR structure, allowing the discovery of novel agonist chemotypes unrelated to known opioids and leading to a Gi-biased drug with unusual and promising biological properties towards safer analgesics.

27. Bradley, S. J. & Tobin, A. B. Design of next-generation G protein-coupled receptor drugs: linking novel pharmacology and in vivo animal models. Annu. Rev. Pharmacol. Toxicol. 56, 535–559 (2016).

28. Kim, C. K., Adhikari, A. & Deisseroth, K. Integration of optogenetics with complementary methodologies in systems neuroscience. Nat. Rev. Neurosci. 18, 222–235 (2017).

29. Van Essen, D. C. Cartography and connectomes. Neuron 80, 775–790 (2013).

30. Bruehl, S. et al. Personalized medicine and opioid analgesic prescribing for chronic pain: opportunities and challenges. J. Pain 14, 103–113 (2013).

31. Luo, S. X. & Levin, F. R. Towards precision addiction treatment: new findings in co-morbid substance use and attention-deficit hyperactivity disorders. Curr. Psychiatry Rep. 19, 14 (2017).

32. Hu, H. Reward and aversion. Annu. Rev. Neurosci. 39, 297–324 (2016).

33. Borsook, D. et al. Reward-aversion circuitry in analgesia and pain: implications for psychiatric disorders. Eur. J. Pain 11, 7–20 (2007).

34. Mechling, A. E. et al. Deletion of the mu opioid receptor gene in mice reshapes the reward–aversion connectome. Proc. Natl Acad. Sci. USA 113, 11603–11608 (2016).

This study analyses functional connectivity by non-invasive MRI in live mutant mice and reveals a fingerprint of Oprm1 activity over the whole brain, opening the way to connectome genetics in animal research.

35. Navratilova, E., Atcherley, C. W. & Porreca, F. Brain circuits encoding reward from pain relief. Trends Neurosci. 38, 741–750 (2015).

36. Lutz, P. E. & Kieffer, B. L. The multiple facets of opioid receptor function: implications for addiction. Curr. Opin. Neurobiol. 23, 473–479 (2013).

37. Eisenberger, N. I. The pain of social disconnection: examining the shared neural underpinnings of physical and social pain. Nat. Rev. Neurosci. 13, 421–434 (2012).

38. Lutz, P. E. & Kieffer, B. L. Opioid receptors: distinct roles in mood disorders. Trends Neurosci. 36, 195–206 (2013).

39. Koob, G. F. & Volkow, N. D. Neurobiology of addiction: a neurocircuitry analysis. Lancet Psychiatry 3, 760–773 (2016).
This seminal review summarizes current knowledge on animal addiction research, including conceptual frameworks, behavioural models, brain circuitry and neurobiology.

40. Koob, G. F. & Volkow, N. D. Neurocircuitry of addiction. Neuropsychopharmacology 35, 217–238 (2010).

41. Baler, R. D. & Volkow, N. D. Drug addiction: the neurobiology of disrupted self-control. Trends Mol. Med. 12, 559–566 (2006).

42. Belin, D., Belin-Rauscent, A., Murray, J. E. & Everitt, B. J. Addiction: failure of control over maladaptive incentive habits. Curr. Opin. Neurobiol. 23, 564–572 (2013).

43. Koob, G. F. et al. Addiction as a stress surfeit disorder. Neuropharmacology 76, 370–382 (2014).

44. Goeldner, C. et al. Impaired emotional-like behavior and serotonergic function during protracted abstinence from chronic morphine. Biol. Psychiatry 69, 236–244 (2011).

45. Chu Sin Chung, P. et al. A novel anxiogenic role for the delta opioid receptor expressed in GABAergic forebrain neurons. Biol. Psychiatry 77, 404–415 (2015).

46. Contet, C., Kieffer, B. L. & Befort, K. Mu opioid receptor: a gateway to drug addiction. Curr. Opin. Neurobiol. 14, 370–378 (2004).

47. Badiani, A., Belin, D., Epstein, D., Calu, D. & Shaham, Y. Opiate versus psychostimulant addiction: the differences do matter. Nat. Rev. Neurosci. 12, 685–700 (2011).

48. Becker, J. A. J., Kieffer, B. L. & Le Merrer, J. Differential behavioral and molecular alterations upon protracted abstinence from cocaine versus morphine, nicotine, THC and alcohol. Addict. Biol. 22, 1205–1217 (2017).

In this Review, we have tentatively addressed three questions. First, can we kill pain without addiction using MOR-targeting opiates? Structural and signalling receptor biology have brought fascinating answers to this long-standing question and have guided the creation of entirely novel chemical entities, and system-level animal studies and clinical trials will ultimately reveal the poten- tial of these novel compounds. Second, how do opioid receptors operate with the neurocircuitry of addiction? The identification of neurons and circuits subserving these activities is rapidly progressing as more genetic tools become available. Whether recent basic research efforts in this field will improve treatment strategies in the future is not clear. However, preclinical circuitry research has revealed less well-known roles for opioid

receptors that may help the interpretation of the effects of compounds in humans and expand the breadth of indications for the very few therapies that exist as well as future opioid-targeting agents for treating addiction. Third, can we bridge opioid research in the field of drug abuse in animal models with that in humans? Most of such research (genetic, epigenetic and neuroimag- ing) in humans has been focused on MORs, although research into KORs is increasing. The advent of human- ized mouse genetic models and rodent neuroimaging is expected to integrate molecular and circuit mechanisms into clinical knowledge and to enhance the potential for personalized addiction treatment.

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Nature reviews | NeuroscieNce

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49. Moles, A., Kieffer, B. L. & D’Amato, F. R. Deficit in attachment behavior in mice lacking the mu-opioid receptor gene. Science 304, 1983–1986 (2004). This study demonstrates, using a genetic approach, that the MOR is essential for social bonding very early on (in 4–8 day old pups), providing key evidence for a MOR contribution to process natural rewards and a strong premise to the rising interest in MOR function in the social brain.

50. Becker, J. A. et al. Autistic-like syndrome in mu opioid receptor null mice is relieved by facilitated mGluR4 activity. Neuropsychopharmacology 39, 2049–2060 (2014).

51. Papaleo, F., Kieffer, B. L., Tabarin, A. & Contarino, A. Decreased motivation to eat in mu-opioid receptor-deficient mice. Eur. J. Neurosci. 25, 3398–3405 (2007).

52. Skoubis, P. D., Matthes, H. W., Walwyn, W. M., Kieffer, B. L. & Maidment, N. T. Naloxone fails to produce conditioned place aversion in mu-opioid receptor knock-out mice. Neuroscience 106, 757–763 (2001).

53. Erbs, E. et al. A mu-delta opioid receptor brain atlas reveals neuronal co-occurrence in subcortical networks. Brain Struct. Funct. 220, 677–702 (2015).

54. Le Merrer, J., Becker, J. A., Befort, K. & Kieffer, B. L. Reward processing by the opioid system in the brain. Physiol. Rev. 89, 1379–1412 (2009).

55. Johnson, S. W. & North, R. A. Opioids excite dopamine neurons by hyperpolarization of local interneurons. J. Neurosci. 12, 483–488 (1992).

56. Wise, R. A. & Rompre, P. P. Brain dopamine and reward. Annu. Rev. Psychol. 40, 191–225 (1989).

57. Fields, H. L. & Margolis, E. B. Understanding opioid
reward. Trends Neurosci. 38, 217–225 (2015).

58. Cui, Y. et al. Targeted expression of mu-opioid receptors
in a subset of striatal direct-pathway neurons restores
opiate reward. Nat. Neurosci. 17, 254–261 (2014).

59. Charbogne, P. et al. Mu opioid receptors in gamma- aminobutyric acidergic forebrain neurons moderate
motivation for heroin and palatable food. Biol.
Psychiatry 81, 778–788 (2017).

60. Ettenberg, A., Pettit, H. O., Bloom, F. E. & Koob, G. F.
Heroin and cocaine intravenous self-administration in rats: mediation by separate neural systems. Psychopharmacology 78, 204–209 (1982).

61. Hnasko, T. S., Sotak, B. N. & Palmiter, R. D. Morphine reward in dopamine-deficient mice. Nature 438, 854–857 (2005).

62. Laviolette, S. R. & van der Kooy, D. GABAA receptors signal bidirectional reward transmission from the ventral tegmental area to the tegmental pedunculopontine nucleus as a function of opiate state. Eur. J. Neurosci. 20, 2179–2187 (2004).

63. Narayanan, S. et al. Endogenous opioids mediate basal hedonic tone independent of dopamine
D-1 or D-2 receptor activation. Neuroscience 124, 241–246 (2004).

64. Ben Hamida, S., Boulos, L. J., McNicholas, M., Charbogne, P. & Kieffer, B. L. Mu opioid receptors in GABAergic neurons of the forebrain promote alcohol reward and drinking. Addict. Biol. https://doi.org/ 10.1111/adb.12576 (2017).

65. Laurent, V., Morse, A. K. & Balleine, B. W. The role of opioid processes in reward and decision-making. Br. J. Pharmacol. 172, 449–459 (2015).

66. Dalley, J. W. & Robbins, T. W. Fractionating impulsivity: neuropsychiatric implications. Nat. Rev. Neurosci. 18, 158–171 (2017).

67. Olmstead, M. C., Ouagazzal, A. M. & Kieffer, B. L. Mu and delta opioid receptors oppositely regulate motor impulsivity in the signaled nose poke task. PLoS ONE 4, e4410 (2009).

68. Gardon, O. et al. Expression of mu opioid receptor in dorsal diencephalic conduction system: new insights for the medial habenula. Neuroscience 277, 595–609 (2014).

69. Hikosaka, O. The habenula: from stress evasion to value-based decision-making. Nat. Rev. Neurosci. 11, 503–513 (2010).

70. Boulos, L. J., Darcq, E. & Kieffer, B. L. Translating the habenula-from rodents to humans. Biol. Psychiatry 81, 296–305 (2017).

71. Boulos, L. J. Mu opioid receptors in the habenula: dissecting reward and aversion in addiction. Program No. 78.11. 2016 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2016.

72. Williams, J. T. et al. Regulation of mu-opioid receptors: desensitization, phosphorylation, internalization, and tolerance. Pharmacol. Rev. 65, 223–254 (2013).

73. Cahill, C. M., Walwyn, W., Taylor, A. M. W.,
Pradhan, A. A. A. & Evans, C. J. Allostatic mechanisms

of opioid tolerance beyond desensitization and downregulation. Trends Pharmacol. Sci. 37, 963–976 (2016).

74. Lutz, P. E. et al. Distinct mu, delta, and kappa opioid receptor mechanisms underlie low sociability and depressive-like behaviors during heroin abstinence. Neuropsychopharmacology 39, 2694–2705 (2014).

75. Ng, E., Browne, C. J., Samsom, J. N. & Wong, A. H. C. Depression and substance use comorbidity: what we have learned from animal studies. Am. J. Drug Alcohol Abuse 43, 456–474 (2017).

76. Ranganathan, M. et al. Dose-related behavioral, subjective, endocrine, and psychophysiological effects of the kappa opioid agonist Salvinorin A in humans. Biol. Psychiatry 72, 871–879 (2012).

77. Koob, G. F. & Le Moal, M. Addiction and the brain antireward system. Annu. Rev. Psychol. 59, 29–53 (2008).

78. Crowley, N. A. & Kash, T. L. Kappa opioid receptor signaling in the brain: circuitry and implications for treatment. Prog. Neuropsychopharmacol. Biol. Psychiatry 62, 51–60 (2015).

79. Land, B. B. et al. The dysphoric component of stress is encoded by activation of the dynorphin kappa-opioid system. J. Neurosci. 28, 407–414 (2008).

80. Zhou, Y. & Kreek, M. J. Alcohol: a stimulant activating brain stress responsive systems with persistent neuro- adaptation. Neuropharmacology 87, 51–58 (2014).

81. Massaly, N., Moron, J. A. & Al-Hasani, R. A. Trigger for opioid misuse: chronic pain and stress dysregulate the mesolimbic pathway and kappa opioid system. Front. Neurosci. 10, 480 (2016).

82. Lalanne, L. et al. Kappa opioid receptor antagonism and chronic antidepressant treatment have beneficial activities on social interactions and grooming deficits during heroin abstinence. Addict. Biol. 22, 1010–1021 (2017).

83. Bruchas, M. R., Land, B. B. & Chavkin, C. The dynorphin/kappa opioid system as a modulator of stress-induced and pro-addictive behaviors. Brain Res. 1314, 44–55 (2010).

84. Chavkin, C. & Koob, G. F. Dynorphin, dysphoria, and dependence: the stress of addiction. Neuropsychopharmacology 41, 373–374 (2016).

85. Spanagel, R., Herz, A. & Shippenberg, T. S. Opposing tonically active endogenous opioid systems modulate the mesolimbic dopaminergic pathway. Proc. Natl Acad. Sci. USA 89, 2046–2050 (1992).

86. Bals-Kubik, R., Ableitner, A., Herz, A. & Shippenberg, T. S. Neuroanatomical sites mediating the motivational effects of opioids as mapped by the conditioned place preference paradigm in rats. J. Pharmacol. Exp. Ther. 264, 489–495 (1993).

87. Chefer, V. I., Backman, C. M., Gigante, E. D. & Shippenberg, T. S. Kappa opioid receptors on dopaminergic neurons are necessary for kappa-mediated place aversion. Neuropsychopharmacology 38, 2623–2631 (2013).

88. Van’t Veer, A. et al. Ablation of kappa-opioid receptors from brain dopamine neurons has anxiolytic-like effects and enhances cocaine-induced plasticity. Neuropsychopharmacology 38, 1585–1597 (2013). 89. Margolis, E. B. et al. Kappa opioids selectively control dopaminergic neurons projecting to the prefrontal cortex. Proc. Natl Acad. Sci. USA 103, 2938–2942 (2006).

90. Tejeda, H. A. et al. Prefrontal cortical kappa-opioid receptor modulation of local neurotransmission and conditioned place aversion. Neuropsychopharmacology 38, 1770–1779 (2013).

91. Tejeda, H. A. et al. Pathway- and cell-specific kappa- opioid receptor modulation of excitation-inhibition balance differentially gates D1 and D2 accumbens neuron activity. Neuron 93, 147–163 (2017).

92. Al-Hasani, R. et al. Distinct subpopulations of nucleus accumbens dynorphin neurons drive aversion and reward. Neuron 87, 1063–1077 (2015).
This report reveals regional heterogeneity within a well-known opioid peptide-expressing brain area for the first time, as dynorphin-expressing cells in either the dorsal or ventral part of the NAc shell drive opposing behaviours (that is, reward or aversion, respectively).

93. Lammel, S. et al. Input-specific control of reward and aversion in the ventral tegmental area. Nature 491, 212–217 (2012).

94. Abraham, A. D. et al. Kappa-opioid receptor activation in dopamine neurons disrupts behavioral inhibition. Neuropsychopharmacology 43, 362–372 (2018).

95. Tao, R. & Auerbach, S. B. Mu-opioids disinhibit and kappa-opioids inhibit serotonin efflux in the dorsal raphe nucleus. Brain Res. 1049, 70–79 (2005).

96. Land, B. B. et al. Activation of the kappa opioid receptor in the dorsal raphe nucleus mediates the aversive effects of stress and reinstates drug seeking. Proc. Natl Acad. Sci. USA 106, 19168–19173 (2009).

97. Bruchas, M. R. et al. Selective p38α MAPK deletion in serotonergic neurons produces stress resilience in models of depression and addiction. Neuron 71, 498–511 (2011).

98. Crowley, N. A. et al. Dynorphin controls the gain of an amygdalar anxiety circuit. Cell Rep. 14, 2774–2783 (2016).

99. Kissler, J. L. & Walker, B. M. Dissociating motivational from physiological withdrawal in alcohol dependence: role of central amygdala kappa-opioid receptors. Neuropsychopharmacology 41, 560–567 (2016).

100. Kang-Park, M., Kieffer, B. L., Roberts, A. J., Siggins, G. R. & Moore, S. D. Kappa-opioid receptors in the central amygdala regulate ethanol actions at presynaptic GABAergic sites. J. Pharmacol. Exp. Ther. 346, 130–137 (2013).

101. Gilpin, N. W., Roberto, M., Koob, G. F. & Schweitzer, P. Kappa opioid receptor activation decreases inhibitory transmission and antagonizes alcohol effects in rat central amygdala. Neuropharmacology 77, 294–302 (2014).

102. Kang-Park, M., Kieffer, B. L., Roberts, A. J., Siggins, G. R. & Moore, S. D. Interaction of CRF and kappa opioid systems on GABAergic neurotransmission in the mouse central amygdala. J. Pharmacol. Exp. Ther. 355, 206–211 (2015).

103. Klenowski, P., Morgan, M. & Bartlett, S. E. The role of delta-opioid receptors in learning and memory underlying the development of addiction. Br. J. Pharmacol. 172, 297–310 (2015).

104. Gendron, L., Cahill, C. M., von Zastrow, M., Schiller, P. W. & Pineyro, G. Molecular pharmacology of delta-opioid receptors. Pharmacol. Rev. 68, 631–700 (2016).

105. Pellissier, L. P., Pujol, C. N., Becker, J. A. &
Le Merrer, J. Delta opioid receptors: learning and motivation. Handb Exp. Pharmacol. https://doi.org/ 10.1007/164_2016_89 (2016).

106. Le Merrer, J. et al. Deletion of the delta opioid receptor gene impairs place conditioning but preserves morphine reinforcement. Biol. Psychiatry 69, 700–703 (2011).

107. Bruchas, M. R. & Roth, B. L. New technologies for elucidating opioid receptor function. Trends Pharmacol. Sci. 37, 279–289 (2016).

108. Koob, G. F. & Mason, B. J. Existing and future drugs for the treatment of the dark side of addiction. Annu. Rev. Pharmacol. Toxicol. 56, 299–322 (2016).

109. Aboujaoude, E. & Salame, W. O. Naltrexone: a pan- addiction treatment? CNS Drugs 30, 719–733 (2016).

110. Schuckit, M. A. Treatment of opioid-use disorders. N. Engl. J. Med. 375, 357–368 (2016).

111. Volkow, N. D. & Skolnick, P. New medications for substance use disorders: challenges and opportunities. Neuropsychopharmacology 37, 290–292 (2012).

112. Ayanga, D., Shorter, D. & Kosten, T. R. Update on pharmacotherapy for treatment of opioid use disorder. Expert Opin. Pharmacother. 17, 2307–2318 (2016).

113. Carlezon, W. A. Jr & Krystal, A. D. Kappa-opioid antagonists for psychiatric disorders: from bench to clinical trials. Depress Anxiety 33, 895–906 (2016).

114. Helal, M. A., Habib, E. S. & Chittiboyina, A. G. Selective kappa opioid antagonists for treatment of addiction, are we there yet? Eur. J. Med. Chem. 141, 632–647 (2017).

115. Goldman, D., Oroszi, G. & Ducci, F. The genetics of addictions: uncovering the genes. Nat. Rev. Genet. 6, 521–532 (2005).

116. Reed, B., Butelman, E. R., Yuferov, V., Randesi, M. & Kreek, M. J. Genetics of opiate addiction. Curr. Psychiatry Rep. 16, 504 (2014).

117. Levran, O., Yuferov, V. & Kreek, M. J. The genetics of the opioid system and specific drug addictions. Hum. Genet. 131, 823–842 (2012).

118. Butelman, E. R., Yuferov, V. & Kreek, M. J. Kappa- opioid receptor/dynorphin system: genetic and pharmacotherapeutic implications for addiction. Trends Neurosci. 35, 587–596 (2012).

119. Belzeaux, R., Lalanne, L., Kieffer, B. L. & Lutz, P. E. Focusing on the opioid system for addiction biomarker discovery. Trends Mol. Med. 24, 206–220 (2018).

120. Crist, R. C. & Berrettini, W. H. Pharmacogenetics of OPRM1. Pharmacol. Biochem. Behav. 123, 25–33 (2014).

121. Kroslak, T. et al. The single nucleotide polymorphism A118G alters functional properties of the human
mu opioid receptor. J. Neurochem. 103, 77–87 (2007).

© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.


122. Oertel, B. G. et al. A common human μ-opioid receptor genetic variant diminishes the receptor signaling efficacy in brain regions processing the sensory information of pain. J. Biol. Chem. 284, 6530–6535 (2009).

123. Colantuoni, C. et al. Temporal dynamics and genetic control of transcription in the human prefrontal cortex. Nature 478, 519–523 (2011).

124. Hancock, D. B. et al. Cis-expression quantitative trait loci mapping reveals replicable associations with heroin addiction in OPRM1. Biol. Psychiatry 78, 474–484 (2015).

125. Kong, X. et al. Lack of associations of the opioid receptor mu 1 (OPRM1) A118G polymorphism (rs1799971) with alcohol dependence: review and meta-analysis of retrospective controlled studies. BMC Med. Genet. 18, 120 (2017).

126. Otto, J. M., Gizer, I. R., Deak, J. D., Fleming, K. A. & Bartholow, B. D. A cis-eQTL in OPRM1 is associated with subjective response to alcohol and alcohol use. Alcohol Clin. Exp. Res. 41, 929–938 (2017).

127. Smith, A. H. et al. Genome-wide association study of therapeutic opioid dosing identifies a novel locus upstream of OPRM1. Mol. Psychiatry 22, 346–352 (2017).

128. Mague, S. D. et al. Mouse model of OPRM1 (A118G) polymorphism has sex-specific effects on drug- mediated behavior. Proc. Natl Acad. Sci. USA 106, 10847–10852 (2009).

129. Ramchandani, V. A. et al. A genetic determinant of the striatal dopamine response to alcohol in men. Mol. Psychiatry 16, 809–817 (2011).
This is a translational study to elucidate the role of the MOR A118G SNP in response to alcohol, and data show that 118G carriers in both humans and a humanized A118G genetic mouse mutant release higher levels of DA following alcohol exposure.

130. Bernardi, R. E. et al. A gene-by-sex interaction for nicotine reward: evidence from humanized mice and epidemiology. Transl Psychiatry 6, e861 (2016).

131. Cabrera, E. A. et al. Neuroimaging the effectiveness of substance use disorder treatments. J. Neuroimmune Pharmacol. 11, 408–433 (2016).

132. Henriksen, G. & Willoch, F. Imaging of opioid receptors in the central nervous system. Brain 131, 1171–1196 (2008).

133. Kuwabara, H. et al. Mu opioid receptor binding correlates with nicotine dependence and reward in smokers. PLoS ONE 9, e113694 (2014).

134. Nuechterlein, E. B., Ni, L., Domino, E. F. & Zubieta, J. K. Nicotine-specific and non-specific effects of cigarette smoking on endogenous opioid mechanisms. Prog. Neuropsychopharmacol. Biol. Psychiatry 69, 69–77 (2016).

135. Hermann, D. et al. Low mu-opioid receptor status in alcohol dependence identified by combined positron emission tomography and post-mortem brain analysis. Neuropsychopharmacology 42, 606–614 (2017).

136. Mick, I. et al. Blunted endogenous opioid release following an oral amphetamine challenge in pathological gamblers. Neuropsychopharmacology 41, 1742–1750 (2016).

137. Majuri, J. et al. Dopamine and opioid neurotransmission in behavioral addictions: a comparative PET study in pathological gambling and binge eating. Neuropsychopharmacology 42, 1169–1177 (2017).

138. Karlsson, H. K. et al. Obesity is associated with decreased μ-opioid but unaltered dopamine D2 receptor availability in the brain. J. Neurosci. 35, 3959–3965 (2015).

139. Saanijoki, T. et al. Opioid release after high-intensity interval training in healthy human subjects. Neuropsychopharmacology 43, 246–254 (2018).

140. Nummenmaa, L. et al. Social touch modulates endogenous mu-opioid system activity in humans. Neuroimage 138, 242–247 (2016).

141. Manninen, S. et al. Social laughter triggers endogenous opioid release in humans. J. Neurosci. 37, 6125–6131 (2017).

142. Nummenmaa, L. & Tuominen, L. Opioid system and human emotions. Br. J. Pharmacol. https://doi.org/ 10.1111/bph.13812 (2017).

143. Borsook, D., Becerra, L. & Hargreaves, R. A role for fMRI in optimizing CNS drug development. Nat. Rev. Drug Discov. 5, 411–424 (2006).

144. Becerra, L., Harter, K., Gonzalez, R. G. & Borsook, D. Functional magnetic resonance imaging measures of the effects of morphine on central nervous system circuitry in opioid-naive healthy volunteers. Anesth. Analg. 103, 208–216 (2006).

145. Becerra, L. et al. Parallel buprenorphine phMRI responses in conscious rodents and healthy human subjects. J. Pharmacol. Exp. Ther. 345, 41–51 (2013).

This is a study using phMRI to compare the effect of buprenorphine on the BOLD signal in both humans and rats and reveals a similar activity pattern across pain-related regions in the two species.

146. Fareed, A. et al. Effect of heroin use on changes of brain functions as measured by functional magnetic resonance imaging, a systematic review. J. Addict. Dis. 36, 105–116 (2017).

147. Ieong, H. F. & Yuan, Z. Resting-state neuroimaging and neuropsychological findings in opioid use disorder during abstinence: a review. Front. Hum. Neurosci. 11, 169 (2017).

148. Zhang, Y. et al. Granger causality reveals a dominant role of memory circuit in chronic opioid dependence. Addict. Biol. 22, 1068–1080 (2017).

149. Moore, K. et al. BOLD imaging in awake wild-type and mu-opioid receptor knock-out mice reveals on-target activation maps in response to oxycodone. Front. Neurosci. 10, 471 (2016).

150. Kenakin, T. The effective application of biased signaling to new drug discovery. Mol. Pharmacol. 88, 1055–1061 (2015).

151. Madariaga-Mazon, A. et al. Mu-opioid receptor biased ligands: a safer and painless discovery of analgesics? Drug Discov. Today 22, 1719–1729 (2017).

152. Spangler, S. & Bruchas, M. R. Tuning biased GPCR signaling for physiological gain. Cell 171, 989–991 (2017).

153. Kieffer, B. L. Drug discovery: designing the ideal opioid. Nature 537, 170–171 (2016).

154. Bohn, L. M. et al. Enhanced morphine analgesia in mice lacking β-arrestin 2. Science 286, 2495–2498 (1999).

155. Raehal, K. M., Walker, J. K. & Bohn, L. M. Morphine side effects in β-arrestin 2 knockout mice. J. Pharmacol. Exp. Ther. 314, 1195–1201 (2005).

156. DeWire, S. M. et al. A G protein-biased ligand at the mu-opioid receptor is potently analgesic with reduced gastrointestinal and respiratory dysfunction compared with morphine. J. Pharmacol. Exp. Ther. 344, 708–717 (2013).

157. Siuda, E. R., Carr, R. 3rd, Rominger, D. H. & Violin, J. D. Biased mu-opioid receptor ligands: a promising new generation of pain therapeutics. Curr. Opin. Pharmacol. 32, 77–84 (2017).

158. Varadi, A. et al. Mitragynine/corynantheidine pseudoindoxyls as opioid analgesics with mu agonism and delta antagonism, which do not recruit β-arrestin-2. J. Med. Chem. 59, 8381–8397 (2016).

159. Schmid, C. L. et al. Bias factor and therapeutic window correlate to predict safer opioid analgesics. Cell 171, 1165–1175 (2017).
This work provides compelling evidence for the physiological relevance of MOR biased signalling, as comparing biased signalling with behavioural effects of a range of MOR agonists reveals strong correlation between Gi/β-arrestin bias factors and the analgesia–respiratory depression therapeutic window.

160. Altarifi, A. A. et al. Effects of acute and repeated treatment with the biased mu opioid receptor agonist TRV130 (oliceridine) on measures of antinociception, gastrointestinal function, and abuse liability in rodents. J. Psychopharmacol 31, 730–739 (2017).

161. Irannejad, R. et al. Functional selectivity of GPCR- directed drug action through location bias. Nat. Chem. Biol. 13, 799–806 (2017).

162. Urs, N. M. et al. Distinct cortical and striatal actions of a β-arrestin-biased dopamine D2 receptor ligand reveal unique antipsychotic-like properties. Proc. Natl Acad. Sci. USA 113, E8178–E8186 (2016).

163. Olson, K. M., Lei, W., Keresztes, A., LaVigne, J. & Streicher, J. M. Novel molecular strategies and targets for opioid drug discovery for the treatment of chronic pain. Yale J. Biol. Med. 90, 97–110 (2017).

164. Pasternak, G. W. Opioids and their receptors: are we there yet? Neuropharmacology 76, 198–203 (2014).

165. Majumdar, S. et al. Truncated G protein-coupled mu opioid receptor MOR-1 splice variants are targets for highly potent opioid analgesics lacking side effects. Proc. Natl Acad. Sci. USA 108, 19778–19783 (2011).

166. Convertino, M. et al. Mu-opioid receptor 6-transmembrane isoform: a potential therapeutic target for new effective opioids. Prog. Neuropsychopharmacol. Biol. Psychiatry 62, 61–67 (2015).

167. Huang, W. et al. Structural insights into micro-opioid receptor activation. Nature 524, 315–321 (2015).

168. Spahn, V. et al. A nontoxic pain killer designed by modeling of pathological receptor conformations. Science 355, 966–969 (2017).

This article reports a highly innovative approach to design safer opioid pain killers, in which ligand docking to a ‘pathological’ (acidic) receptor structure identifies a MOR agonist acting at the receptor only under conditions of inflammation, leaving other receptors at rest.

169. Livingston, K. E. & Traynor, J. R. Allostery at opioid receptors: modulation with small molecule ligands. Br. J. Pharmacol. https://doi.org/10.1111/bph.13823 (2017).

170. Burford, N. T. et al. Discovery of positive allosteric modulators and silent allosteric modulators of the mu-opioid receptor. Proc. Natl Acad. Sci. USA 110, 10830–10835 (2013).

171. Livingston, K. E. & Traynor, J. R. Disruption of the Na+ ion binding site as a mechanism for positive allosteric modulation of the mu-opioid receptor. Proc. Natl Acad. Sci. USA 111, 18369–18374 (2014).

172. Galadrin, S. et al. The evasive nature of drug efficacy: implications for drug discovery. Trends Pharm. Sci. 28, 423–430 (2007).

173. Roth, B. L. et al. Salvinorin A: a potent naturally occurring nonnitrogenous kappa opioid selective agonist. Proc. Natl Acad. Sci. USA 99, 11934–11939 (2002).

174. Sheffler, D. J. & Roth, B. L. Salvinorin A: the “magic mint” hallucinogen finds a molecular target in the kappa opioid receptor. Trends Pharmacol. Sci. 24, 107–109 (2003).

175. Cruz, A., Domingos, S., Gallardo, E. & Martinho, A. A unique natural selective kappa-opioid receptor agonist, salvinorin A, and its roles in human therapeutics. Phytochemistry 137, 9–14 (2017).

176. Butelman, E. R. & Kreek, M. J. Salvinorin A, a kappa- opioid receptor agonist hallucinogen: pharmacology and potential template for novel pharmacotherapeutic agents in neuropsychiatric disorders. Front. Pharmacol. 6, 190 (2015).

177. Civelli, O. et al. G protein-coupled receptor deorphanizations. Annu. Rev. Pharmacol. Toxicol. 53, 127–146 (2013).

178. Reinscheid, R. K. et al. Orphanin FQ: a neuropeptide that activates an opioidlike G protein-coupled receptor. Science 270, 792–794 (1995).

179. Meunier, J. C. et al. Isolation and structure of the endogenous agonist of opioid receptor-like ORL1 receptor. Nature 377, 532–535 (1995).

180. Zaveri, N. T. Nociceptin opioid receptor (NOP) as a therapeutic target: progress in translation from preclinical research to clinical utility. J. Med. Chem. 59, 7011–7028 (2016).

181. Toll, L., Bruchas, M. R., Calo, G., Cox, B. M. &
Zaveri, N. T. Nociceptin/orphanin FQ receptor structure, signaling, ligands, functions, and interactions with opioid systems. Pharmacol. Rev. 68, 419–457 (2016).

182. Witkin, J. M. et al. The biology of nociceptin/orphanin FQ (N/OFQ) related to obesity, stress, anxiety, mood, and drug dependence. Pharmacol. Ther. 141, 283–299 (2014).

183. Sounier, R. et al. Propagation of conformational changes during mu-opioid receptor activation. Nature 524, 375–378 (2015).

184. Raehal, K. M., Schmid, C. L., Groer, C. E. & Bohn, L. M. Functional selectivity at the mu-opioid receptor: implications for understanding opioid analgesia and tolerance. Pharmacol. Rev. 63, 1001–1019 (2011).

185. Pradhan, A. A., Smith, M. L., Kieffer, B. L. & Evans, C. J. Ligand-directed signalling within the opioid receptor family. Br. J. Pharmacol. 167, 960–969 (2012).

186. Ehrich, J. M. et al. Kappa opioid receptor-induced aversion requires p38 MAPK activation in VTA dopamine neurons. J. Neurosci. 35, 12917–12931 (2015).

187. Scherrer, G. et al. Knockin mice expressing fluorescent delta-opioid receptors uncover G protein-coupled receptor dynamics in vivo. Proc. Natl Acad. Sci. USA 103, 9691–9696 (2006).

This study provides a unique knock-in mouse mutant line, and is the first of a series to visualize a GPCR in vivo; it shows DOR subcellular localization and trafficking, opening the way to understand tolerance mechanisms.

188. Pradhan, A. A. et al. Ligand-directed trafficking of the delta-opioid receptor in vivo: two paths toward analgesic tolerance. J. Neurosci. 30, 16459–16468 (2010).

189. Su, D. et al. One-step generation of mice carrying a conditional allele together with an HA-tag insertion for the delta opioid receptor. Sci. Rep. 7, 44476 (2017).

190. Siuda, E. R. et al. Spatiotemporal control of opioid signaling and behavior. Neuron 86, 923–935 (2015).


Nature reviews | NeuroscieNce

© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.


191. Marchant, N. J. et al. Behavioral and physiological effects of a novel kappa-opioid receptor-based DREADD in rats. Neuropsychopharmacology 41, 402–409 (2016).

192. Marchant, N. J. et al. Role of ventral subiculum in context-induced relapse to alcohol seeking after punishment-imposed abstinence. J. Neurosci. 36, 3281–3294 (2016).

193. Harris, J. A. et al. Anatomical characterization of Cre driver mice for neural circuit mapping and manipulation. Front. Neural Circuits 8, 76 (2014).

194. Cai, X. et al. Generation of a KORCre knockin mouse strain to study cells involved in kappa opioid signaling. Genesis 54, 29–37 (2016).

195. Kumar, D., Chakraborty, J. & Das, S. Epistatic effects between variants of kappa-opioid receptor gene and A118G of mu-opioid receptor gene increase susceptibility to addiction in Indian population. Prog. Neuropsychopharmacol. Biol. Psychiatry 36, 225–230 (2012).

196. Deb, I., Chakraborty, J., Gangopadhyay, P. K., Choudhury, S. R. & Das, S. Single-nucleotide polymorphism (A118G) in exon 1 of OPRM1 gene causes alteration in downstream signaling by mu- opioid receptor and may contribute to the genetic risk for addiction. J. Neurochem. 112, 486–496 (2010).

197. Kapur, S., Sharad, S., Singh, R. A. & Gupta, A. K. A118G polymorphism in mu opioid receptor gene (OPRM1): association with opiate addiction in subjects of Indian origin. J. Integr. Neurosci. 6, 511–522 (2007).

198. Bart, G. et al. Substantial attributable risk related to a functional mu-opioid receptor gene polymorphism in association with heroin addiction in central Sweden. Mol. Psychiatry 9, 547–549 (2004).

199. Szeto, C. Y., Tang, N. L., Lee, D. T. & Stadlin, A. Association between mu opioid receptor gene polymorphisms and Chinese heroin addicts. Neuroreport 12, 1103–1106 (2001).

200. Li, T. et al. Association analysis of polymorphisms in the mu opioid gene and heroin abuse in Chinese subjects. Addict. Biol. 5, 181–186 (2000).

201. Hendershot, C. S., Claus, E. D. & Ramchandani, V. A. Associations of OPRM1 A118G and alcohol sensitivity with intravenous alcohol self-administration in young adults. Addict. Biol. 21, 125–135 (2016).

202. Bart, G. et al. Increased attributable risk related to a functional mu-opioid receptor gene polymorphism in association with alcohol dependence in central Sweden. Neuropsychopharmacology 30, 417–422 (2005).

203. Schinka, J. A. et al. A functional polymorphism within the mu-opioid receptor gene and risk for abuse of alcohol and other substances. Mol. Psychiatry 7, 224–228 (2002).

204. Town, T. et al. Association of a functional mu-opioid receptor allele (+118A) with alcohol dependency. Am. J. Med. Genet. 88, 458–461 (1999).

205. Dlugos, A. M. et al. OPRM1 gene variants modulate amphetamine-induced euphoria in humans. Genes Brain Behav. 10, 199–209 (2011).

206. Schuck, K., Otten, R., Engels, R. C. & Kleinjan, M. Initial responses to the first dose of nicotine in novel smokers: the role of exposure to environmental smoking and genetic predisposition. Psychol. Health 29, 698–716 (2014).

207. Zhang, Y. et al. Mouse model of the OPRM1 (A118G) polymorphism: differential heroin self-administration behavior compared with wild-type mice. Neuropsychopharmacology 40, 1091–1100 (2015).

208. Browne, C. A., Erickson, R. L., Blendy, J. A. & Lucki, I. Genetic variation in the behavioral effects of buprenorphine in female mice derived from a murine model of the OPRM1 A118G polymorphism. Neuropharmacology 117, 401–407 (2017).

209. Briand, L. A. et al. Mouse model of OPRM1 (A118G) polymorphism increases sociability and dominance and confers resilience to social defeat. J. Neurosci. 35, 3582–3590 (2015).

210. Robinson, J. E. et al. Receptor reserve moderates mesolimbic responses to opioids in a humanized mouse model of the OPRM1 A118G polymorphism. Neuropsychopharmacology 40, 2614–2622 (2015).



Henderson-Redmond, A. N. et al. Morphine-induced antinociception and reward in “humanized” mice expressing the mu opioid receptor A118G polymorphism. Brain Res. Bull. 123, 5–12

Bilbao, A. et al. A pharmacogenetic determinant of mu-opioid receptor antagonist effects on alcohol reward and consumption: evidence from humanized mice. Biol. Psychiatry 77, 850–858 (2015).

© 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.


The authors deeply thank the CNRS/INSERM/University of Strasbourg (France), the US National Institutes of Health (National Institute of Drug Abuse Grant 05010 and National Institute on Alcohol Abuse and Alcoholism Grant 16658 to B.L.K.), the Canada Fund for Innovation and the Canada Research Chairs (to B.L.K and E.D.), and the Bourgeois family (B.L.K. is the Bourgeois Chair for Pervasive Developmental Disorders) for continuous support.

Author contributions

E.D. and B.L.K. researched data for the article, made substan- tial contributions to the discussion of content, wrote the arti- cle and reviewed and edited the manuscript before submission.

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Reviewer information

Nature Reviews Neuroscience thanks E. J. Nestler and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Supplementary information

Supplementary information is available for this paper at https://doi.org/10.1038/s41583-018-0028-x.


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