Xylazine – Another Dangerous Street Drug

Xylazine is the latest veterinary tranquilizer to be sold as a street drug. It has no approved human uses.  It is used as both a light and general anesthetic for horses depending on the extent of the surgery. Xylazine is a presynaptic alpha-2 adrenoceptor agonist inhibiting the release of norepinephrine from synaptic vesicles. This leads to decreased postsynaptic activation of adrenoceptors, inhibited sympathetic activity, leading to analgesia, sedation and anxiolysis.  This mechanism of action is also seen with clonidine and dexmedetomidine.  Xylazine has low potency and affinity for Alpha-2 receptor adrenergic receptors. It has been demonstrated by the use of a knock out genetic mouse model that the clinical effects are mediated through the alpha-2A receptor subtype (5).

Alpha-2 receptor adrenergic receptor (AR) profiles are complicated by the fact that there are 4 subtypes with central, peripheral and behavioral effects but very little seems to be written about the D subtype so I have not included it here.  The general associated mechanisms include a decrease in adenyl cyclase activity, suppressed voltage gated calcium currents, increased potassium currents and increased mitogen-activated protein kinase (MAP kinase) activity. At steady state the α-2A and α-2B receptor types are at the cell surface and the α-2C type is at the cell surface and intracellular.  Some drugs like clonidine and guanfacine promote α-2A internalization. The author (3) of the review suggests that this may account for the unique duration of signaling. α-2AR trafficking and signaling also undergoes complex regulation by a number of factors including protein kinases, G protein coupled receptors (GPCRs), and scaffolding proteins.  A table of receptor affinities for various drugs are listed below. These affinities are primarily from reference 2 and generally represent results for human cloned receptors of the averages of several experiments. Please note the very low affinities for xylazine. I have tried to corroborate these numbers from outside sources and have not been successful. If you have better affinities for xylazine please email me or post them here in the comments section.  

From a pharmacodynamic standpoint there are several relevant Alpha-2 AR polymorphisms that have been tentatively linked disease states like ADHD and hypertension. They have also been studied in heart rate, heart rate variability, blood pressure control, obesity and insulin resistance (4). As expected, these polymorphisms also effect drug response.  

Although Xylazine is approved only for veterinary uses, reports of human use and accidental or inadvertent overdoses began to appear in the 1980s.  A review of initial reports looking at the compound as an adulterant that was done in 2014 (7) and concluded that half of the human overdoses resulted in death.  

Central effects of alpha 2 agonists, results in decreased sympathetic output and resulting imbalances in the peripheral autonomic nervous system.  Decreased sympathetic output leads to the expected effects of bradycardia, hypotension, sedation and decreased level of consciousness. Unopposed vagal parasympathetic effects can lead to increasing heart block and arrhythmias.  

In addition to the central effects of α-2 agonists there are also peripheral effects.  A common α-1 and α-2 agonist used peripherally is oxymetazoline that is used as a topical nasal decongestant. It exhibits very high affinity for both receptors and the following K_is  α-2A (7.24 nM), α-2B (483.5 nM), α-2C (144.07 nM), α-1 (402.75 nM).  Peripheral α-2 adrenergic effects can lead to increased systemic vascular resistance due to effects at the level of arterioles. This is important from a toxicological perspective because it can cause hypertension and is probably the mechanism leading to soft tissue necrosis at injection sites.

The epidemiology of xylazine use is discussed in a few studies at this point (7,12,13). The original paper suggested it may have started in Puerto Rico and spread Philadelphia with the highest prevalence of overdoses in eastern states.  It is well described at this point both in terms of overdoses and as an adulterant when it is added to heroin, fentanyl, cocaine, methamphetamine, alcohol or combinations like heroin + cocaine. There are expected synergies with opioids including a depressed level of consciousness, and decreased respiratory drive. Synergies with stimulants would include increased likelihood of cardiac arrhythmias, hypertension, and tissue necrosis.

The CDC recently published a study of xylazine in Cook County, IL (Chicago area) in MMWR (12).  The study ran from January 2017 to October 2021.  Xylazine associated deaths were defined as positive post-mortem toxicology in any substance related death where the intent was unintentional, undetermined or pending. The authors identified 236 xylazine associated deaths that increased over the study period and are graphed below. The graph on the right is the percentage of fentanyl associated deaths involving xylazine by month. That graph peaks at 11.4% in October. Overall, fentanyl or its metabolites was present in 99.2% of xylazine associated deaths. The authors point out that naloxone does not reverse the effects of xylazine but it should be administered for any suspected opioid use in a polypharmacy toxidrome. They also state that better surveillance for this compound is probably indicated.  

 

The toxidromes from these drug combinations can be complex so that on a clinical basis it will be hard to tell if the patient you are seeing has used xylazine. I was fortunate enough to attend a Hennepin County Medical Center Addiction Medicine Journal Club on 4/5/2022. In that presentation the pharmacology, clinical effects and toxicology of xylazine were discussed. The cases presented all had xylazine combined with other substances and severe necrosis of the lower extremities in two cases and hand and wrist in the other. In one case the patient no longer had venous access and was injecting into the area of necrosis.  All of these patients required skin grafting wanted to leave the hospital after the acute phase of intoxication had passed. In these cases, the transition to detoxification and maintenance medications is complicated because of the possible synergy between opioids and α-2 adrenergic agonists and the question of rebound or withdrawal from preadmission use of xylazine. The question of Takotsubo cardiomyopathy was discussed because some patients the literature were described as using xylazine. Rebound or withdrawal from xylazine and the associated rapid increase in catecholamines was discussed as a potential mechanism. A toxicologist attending the meeting also pointed out that with overdoses the α-2 adrenergic agonists can cause hypertension by peripheral effects and this has caused some acute cardiac problems. That toxicologist was also familiar with local testing for xylazine and it was not currently being done. He pointed out that a half life of 5 hours was determined in humans as contrasted with a few minutes in several animal species.   He suggested that in the case of a patient unresponsive to high dose naloxone, without hypercapnia via arterial blood gases, and normal brain imaging it would be reasonable to request xylazine toxicology.

In an interesting development, the FDA recently approved a dexmedetomidine sublingual film for the treatment of acute agitation in schizophrenia and bipolar disorder (14).  Dexmedetomidine has been available for intravenous use for 20 years with the indication “sedation of non-intubated patients prior to and/or during surgical and other procedures” (15).  It also has a place in critical care medicine – addressing all three aspects of the ICU triad of pain, agitation, and delirium (16). The film comes in 120 mcg and 180 mcg doses with a schedule in the package insert with dosing for adults and geriatric patients with and without varying degrees of hepatic impairment.  The clinical trials in the package insert describe the medication as effective for this indication. As a psychiatrist who spent most of his career in acute care there are fairly frequent situations where medications that are typically used to treat agitation (antipsychotics and benzodiazepines) do not work – even at high doses. It will be interesting to see if acute care psychiatrists find dexmedetomidine preparation useful. When I ran into that situation it was typically cases of severe mania with agitation or delirious mania with catatonia and the only available option was conscious sedation by anesthesiology. The other unknown at this point is how effective this medication will be over time.  The package insert specifies a maximum of two or three doses.  Clinicians will be on their own after that. It reminds me of how another α-2 adrenergic agonist – clonidine is currently used for anxiety, agitation, and insomnia. Many patients experience it as transiently effective until a more sustained preparation (typically a transdermal patch) is used.  

The appearance and gradual increase in xylazine as a street drug is not good news.  It is clearly used as an adulterant in both opioids and stimulants.  Its use can result in severe complications and death. The surveillance for this compound is not good at this time and clinicians have to have a high index of suspicion to request toxicology for it. People with substance use disorders need to be educated about this compound and its use as an adulterant and that deciding to use it with an opioid or other CNS depressants (including alcohol) is very dangerous and needs to be avoided. Using it with stimulants can also have significant negative effects.  At this point it is also an unknown danger because like fentanyl - it can be sold as anything.

 

George Dawson, MD, DFAPA

 

References:

 

1:  Törneke K, Bergström U, Neil A. Interactions of xylazine and detomidine with alpha2-adrenoceptors in brain tissue from cattle, swine and rats. J Vet Pharmacol Ther. 2003 Jun;26(3):205-11. doi: 10.1046/j.1365-2885.2003.00466.x. PMID: 12755905.

2:  PDSP Ki Database referenced as The Multiplicity of Serotonin Receptors: Uselessly diverse molecules or an embarrassment of riches? BL Roth, WK Kroeze, S Patel and E Lopez: The Neuroscientist, 6:252-262, 2000

3:  Wang Q.  α2-Adrenergic Receptors. In: Primer on the Autonomic Nervous System, Third Edition.  Robertson D, Biaggioni I, Burnstock G, Low PA, Paton JFR. 2012. Elsevier, Amsterdam. 55-58.

4:  Matušková L, Javorka M. Adrenergic receptors gene polymorphisms and autonomic nervous control of heart and vascular tone. Physiol Res. 2021 Dec 30;70(Suppl4):S495-S510. doi: 10.33549/physiolres.934799. PMID: 35199539.

5:  Kitano T, Kobayashi T, Yamaguchi S, Otsuguro K. The α_2A -adrenoceptor subtype plays a key role in the analgesic and sedative effects of xylazine. J Vet Pharmacol Ther. 2019 Mar;42(2):243-247. doi: 10.1111/jvp.12724. Epub 2018 Nov 11. PMID: 30417462.

6:  Weerink MAS, Struys MMRF, Hannivoort LN, Barends CRM, Absalom AR, Colin P. Clinical Pharmacokinetics and Pharmacodynamics of Dexmedetomidine. Clin Pharmacokinet. 2017 Aug;56(8):893-913. doi: 10.1007/s40262-017-0507-7. PMID: 28105598; PMCID: PMC5511603.

7:  Ruiz-Colón K, Chavez-Arias C, Díaz-Alcalá JE, Martínez MA. Xylazine intoxication in humans and its importance as an emerging adulterant in abused drugs: A comprehensive review of the literature. Forensic Sci Int. 2014 Jul;240:1-8. doi: 10.1016/j.forsciint.2014.03.015. Epub 2014 Mar 26. PMID: 24769343.

8:  Sinclair MD. A review of the physiological effects of alpha 2-agonists related to the clinical use of medetomidine in small animal practice. Can Vet J. 2003 Nov;44(11):885-97. PMID: 14664351; PMCID: PMC385445.

9:  Giovannitti JA Jr, Thoms SM, Crawford JJ. Alpha-2 adrenergic receptor agonists: a review of current clinical applications. Anesth Prog. 2015 Spring;62(1):31-9. doi: 10.2344/0003-3006-62.1.31. PMID: 25849473; PMCID: PMC4389556.

10:  Kanagy NL. Alpha(2)-adrenergic receptor signalling in hypertension. Clin Sci (Lond). 2005 Nov;109(5):431-7. doi: 10.1042/CS20050101. PMID: 16232127.

Activation of alpha(2A)-ARs in cardiovascular control centres of the brain lowers blood pressure and decreases plasma noradrenaline (norepinephrine), activation of peripheral alpha(2B)-ARs causes sodium retention and vasoconstriction, whereas activation of peripheral alpha(2C)-ARs causes cold-induced vasoconstriction

11:  Talke P, Lobo E, Brown R. Systemically administered alpha2-agonist-induced peripheral vasoconstriction in humans. Anesthesiology. 2003 Jul;99(1):65-70. doi: 10.1097/00000542-200307000-00014. PMID: 12826844.

12:  Chhabra N, Mir M, Hua MJ, et al. Notes From the Field: Xylazine-Related Deaths — Cook County, Illinois, 2017–2021. MMWR Morb Mortal Wkly Rep 2022;71:503–504. DOI: http://dx.doi.org/10.15585/mmwr.mm7113a3

13:  Friedman J, Montero F, Bourgois P, Wahbi R, Dye D, Goodman-Meza D, Shover C. Xylazine spreads across the US: A growing component of the increasingly synthetic and polysubstance overdose crisis. Drug Alcohol Depend. 2022 Apr 1;233:109380. doi: 10.1016/j.drugalcdep.2022.109380. Epub 2022 Feb 26. PMID: 35247724.

14:  FDA Package Insert. IGALMITM (dexmedetomidine) sublingual film, for sublingual or buccal use.  April 5, 2022.  https://www.igalmihcp.com/igalmi-pi.pdf

15:  FDA Package Insert.  Dexmedetomidine hydrochloride injection. 1999. https://www.accessdata.fda.gov/drugsatfda_docs/label/2015/206628s000lbl.pdf

16:  Reade MC, Finfer S. Sedation and delirium in the intensive care unit. N Engl J Med. 2014 Jan 30;370(5):444-54. doi: 10.1056/NEJMra1208705. PMID: 24476433.

Another Round of Addiction As A Brain Disease

 

A new open access article looking at the issue of addiction as a brain disease was recently published by Neuropsychopharmacology.  The authors point out that since this original claim as made 20 years ago (7) and subsequently reinforced (8) there have been a flurry of critical articles. On this blog I have examined several of these articles in the past. They parallel typical arguments that are used against psychiatric diagnoses, particularly the concept of psychiatric disorders as diseases.  Interestingly, in this paper that entire issue was summarily addressed:

“Few, if any healthcare professionals continue to maintain that schizophrenia, rather than being a disease, is a normal response to societal conditions. Why, then, do people continue to question if addiction is a disease, but not whether schizophrenia, major depressive disorder or posttraumatic stress disorder are diseases?”  (p. 3)

Any casual observer of the constant arguments on this issue will note a constant flux of how psychiatric disorders are described.  Disorders, conditions, and constructs come to mind.  I always like to point out that actual surveys of both the general public and health care professionals finds that both groups typically classify severe mental illnesses and substance use disorders as diseases, but to varying degrees.  The best surveys of this problem have been done in Finland (4,5) with large sample of doctors, nurses, psychiatrists, laypersons, and politicians included.  In two separate studies the authors asked respondents to consider 60 general conditions and 20 psychiatric conditions.  Respondents were asked to rank the disorders according to which were more similar to disease conditions and different cut offs were used for both samples. In the larger survey of 60 medical and psychiatric conditions – schizophrenia and autism met the survey requirements for disease.  In the second survey, 75% of the respondents considered schizophrenia and autism as diseases and 50% considered Depression, Anorexia, Panic disorder, Generalized Anxiety Disorder, Bulimia, Attention deficit hyperactivity disorder, and Personality disorder to be diseases.  There was more disagreement on Alcoholism and Drug Addiction but 64% of physicians and 74% of psychiatrists considered alcoholism to be a disease.  On the issue of drug addiction 50% of physicians and 65% of psychiatrists considered that condition to be a disease. The authors generally discuss the implications of these opinions from a practical and public policy perspective rather than a medical or philosophical one. The common arguments that persist is that disease status confers social legitimacy on a disorder leading to more treatment resources and hopefully decreasing stigma.  In the case of addictions there are longstanding moral defect or choice theories that essentially equate addiction to willful misconduct. Since large corporations have taken over the healthcare systems in the United States many of these biases are less visible since proprietary rules determine who gets treatment resources and how they are treated. A recent court ruling details how these rules are seriously flawed (6).  An important perspective from the discussion and that is personal experience with the illness by the patient, family members, friends, and employers– a subject I will elaborate on further.

The previous posts on this blog addressed a New England Journal of Medicine article suggesting that addiction was a problem in learning rather than a disease in two separate posts.  Before that I addressed a 2015 article that listed 10 reasons why addictions were not a disease. Responding to these articles highlighted their rhetorical aspect.  Many of the arguments against a disease model of addiction have three basic flaws.  First, they consider the concept of disease to be clearly defined and it is not. Second, they use their more precise definitions for comparison and as a way to prove addiction is not a disease.  And third, they suggest that psychosocial variables are relevant only if the condition in question is not a true disease.  They suggest that real diseases are self-contained and self-perpetuating and that interpersonal relationships and environmental factors cannot modify diseases.  By extension only a medication or a surgical intervention can modify or cure a real disease.  There are many examples of diseases that illustrate why that premise is not true.  In my practice over the past 30 years the most common examples have been diabetes mellitus Type 2, hypercholesterolemia, and hypertension. I have seen many people with extreme cholesterol elevations who were “cured” by a simple dietary change and starting to exercise.  My two previous articles discuss these lines of argumentation.

Another disease feature of substance use disorders is that they can occur in discrete epidemics.  Although epidemics are typically thought of as being associated with infectious diseases, the CDC description is careful to point out that they can also occur as a result of non-infectious diseases like obesity and diabetes mellitus. They also describe 5 conditions that lead to epidemics including an increase in exposure in terms of total amount or increased virulence, introduction of a novel agent, enhanced transmission, a change in host response, or increased host exposure that can occur by new portals of entry.  All 5 of these factors are relevant in drug epidemics.  Substance use disorder epidemics have these features as evidenced by the 20-year opioid epidemic that started with excessive availability of prescriptions opioids and transitioned to more potent illicit opioids. The widespread availability of these compounds come from illicit importation and supply chain proliferation often by opioid users selling these compounds in order to assure that they have an adequate supply.  Over the past 25 years there have been a clear pattern of increased geographic availability of multiple drug classes – leading to increased morbidity and mortality from substance use disorders in these areas.  

Does the current paper add anything to the argument for addiction as a brain disease?  The authors review the history of the more public airing of the concept – an original article by Leshner (7) asserting “addiction is a brain disease” and a follow up article by McClellan (8). The fact that both of these declarations are only about 20 years old should not be lost on anyone. The authors get derailed from the basic concept of disease in the very next paragraph by suggesting “To promote patient access to treatments, scientists need to argue that there is a biological basis beneath challenging behaviors of individuals suffering from addiction.”  The social utility of a diagnosis is separate from its medical and scientific utility. All three are conflated at times (even to the point of suggesting that laypersons should have input into what is a diagnosis), but in my opinion without medical and scientific utility – there is not social utility.

They review the definition of disease – starting with Jellinek’s “The Disease Concept of Alcoholism”.  Jellinek made the argument that diseases were not self-contained “entities” but it is more of an agreed upon label “to describe a cluster of substantial deteriorating changes in the structure or function of the human body and the accompanying deterioration in biopsychosocial functioning”.  That definition is very close to the one I came up with reviewing the work of philosophers Munson and Resnick who defined disease as a “failure of normal functioning”. The main difference is that these two philosophers predicated the definition on the premise that biological systems were programmed processes and those processes failing is what causes the disease.  Adaptive reward based learning can certainly be considered a programmed process in brain biology.  

They take a close look at the idea that any definition of addiction should account for spontaneous remission and non-relapsing states. One of the typical arguments against addiction as a disease is that a significant number of heavy drinkers (and probably cannabis smokers) stop after they graduate from college.  In many ways, excessive alcohol and drug use in college is considered a rite of passage by many Americans.  That rite of passage has a considerable mortality and morbidity on its own that is usually not considered by the addiction as disease critics.  The vast majority of these people are not the people seen by addiction specialists later in life. The people seen in their 40s or 50s will typically give a history of knowing that their pattern of drinking was problematic.  As an example: “I knew from the very first time that I drank a lot more and I drank faster than anyone else. I drank more in college and I did not stop after I graduated”.  And they elaborate on the consequences of excessive alcohol use at every life stage.  Binge use or even fairly continuous use of drugs or alcohol in college is not the same as an addiction.  

The authors point out that some of the epidemiological data used to justify the remission argument is dependent on methodology and population.  For example, a population recruited from a residential treatment facility and interviewed with a standardized interview will yield much different results than a community sample. The diagnosis of addiction (or severe alcohol use disorder) will be stable in the former case but not the latter.  They reference NESARC (National Epidemiological Survey on Alcohol and Related Conditions) as the community sample and using that methodology the baseline lifetime prevalence of non-remitting alcohol dependence was 10% (p. 9).  They also point out that opioid use disorder when observed for 10-30 years has a stable abstinence rate of < 30%.  The fact that some people stop using excessive amounts of drugs or alcohol is not an argument that there is not a large population of people who clearly have a chronic relapsing course and incur significant mortality and morbidity along the way.

The authors proceed to the genetic argument and point out that family and adoption studies point to a heritability of ~50% for addictive disorders. They highlight typical misunderstandings of genetics, specifically the concept of polygenic risk and that fact that some polygenic disorders lead to pathological states – addiction being one of them.  An additional argument is that although the first 20 years of human genome study have been very productive for Mendelian disorders, it has been far less productive for more complex disorders (11). Understanding the human genome is far from complete at this point and some research groups are just beginning to understand the relationships between genetics, addiction, and medication effects (12, 13, 14).

The lesion argument is the next disease straw man to fall. It should be obvious to anyone that diseases do not necessarily produce a discrete lesion either on imaging studies or autopsy.  An yet it remains a favorite to anyone who claims that addictions or psychiatric disorders are not diseases.  They review how imaging is currently used clinically.  This is a reality that most of the critics seem to miss.  If I see brain imaging consistent with small vessel ischemic disease – that alone is insufficient to make the diagnosis. It also requires an adequate history and examination of the patient. The critics apparently have not see radiology reports that point out “clinical correlation is necessary”.  The authors briefly review the functional imaging of alcohol and stimulant use disorders that point to problems with frontal-striatal circuitry, structural changes with alcohol, and demonstrable and expected changes in dopamine signaling. Brain imaging in addiction at this point (apart from the necessary clinical imaging) is useful from a heuristic standpoint – looking for relevant mechanism and treatments, but there is no imaging of addictive disorders per se. 

A popular viewpoint these days is that there is not enough of an investment in psychosocial factors in funded research. Many of those critics make the argument that the trade off should be reduced funding for biological research and those funds should be diverted to psychosocial research. The authors here acknowledge the importance of social factors, their incorporation in more complex research designs, and the fact that a view of addiction as a brain disease in no way negates the importance of other environmental factors. 

The authors address the issue of reductionism.  They use the term determinism instead. Over the past two decades molecular biologists have moved firmly away for the idea that all complex biological systems can be reduced to the basic laws of chemistry and physics. The does not mean that with the appropriate tools biological complexity can not be understood and explained.  Many physicists see the brain as deterministic.  In other words because the brain is made up of particles and those particles must follow the laws of physics, the future (or past state) of any brain can be determined by the right differential equation. Deterministic states can be chaotic and in that situation they are not predictable.  If you believe the brain is deterministic based on physical laws – it follows that there is no free will and that free will is an illusion.  The real limiting factors with describing the brain as deterministic include the following problems:

1.  There are known stochastic factors that introduce random events – some of which are relevant for the addiction.

2.  Complexity – as noted above.  There is so much structure and so many particles that must be considered in these complex systems that there is a clear measurement problem and the most difficult problems are solved by computer modeling approximations rather than mathematically.  I have not seen it discussed but whenever I consider the complexity of biological systems, I see them as an almost infinite set of microenvironments - each with their own physical and chemical parameters. If there was an equation to describe all of those microenvironments acting at one - it would be exceedingly complex.

3.  Brain changes occurring during the addiction process (a large number of which are unknown at this time) alter the deterministic nature of the system.  I suppose the response by the physical determinists would be that the new altered system would be determined by the laws of physics and chemistry. That does not alter the fact that it is a new system with different physical and chemical componenets.

The authors contend that the system is indeterministic because of these factors and therefore free will is allowed.  An associated physics and philosophical question is whether it is really deterministic but unpredictable and why.  Overall, these philosophical arguments do not really seem to add much to the debate.  The critical piece is whether either deterministic or reductionist is used in a pejorative manner.  That use is typically coupled with arguments that other social or psychological theories is what is really happening.  Scientists and physicians are generally interested in knowing all of the details and mechanisms of action. The is the real driver of knowing what is happening at the molecular level.  This paper does a good job of explaining why people who use that approach do not exclude everything else that is going on in the environment.

They end on the issue of compulsivity (or more accurately uncontrolled use) in addiction. It is not the case that this does not happen, but the degree at which it happens.  In the people who I work with practically all of the negative outcomes are associated with uncontrolled use/compulsivity.   That does not mean that people with addictions are automatons. The major treatment modality anywhere is some form of group therapy.  Those groups would not exist if there was an assumptions that people with substance use disorders could not choose to change their thought patterns and behavior.  They continue to have some flexibility, but the probabilities during an active addiction is that the substance use will continue despite negative and in many cases life threatening outcomes. Intact decision making in other areas or even in the focal area of continued substance use with episodes of abstinence does not mean that normal decision making occurs in all areas of life.

In their conclusion, the authors suggest that progress can occur from integrating a number of scientific perspectives including those outside the field of neuroscience.  They advocate for consilience and input from a plurality of disciplines. They also suggest that no single discipline has exclusive ownership of the field.

As a clinician who is used to constant criticism of psychiatry from people who don’t know anything about it – I have a different position.   First, we need to acknowledge the severity of addictions specifically that they kill and disable large numbers of people.  Family members trying to help an afflicted persons know that as well as the difficulty in trying to help them stop.  Second, in rankings of disability compared with other disease states – addictions are consistently in the top 10.  When combined with psychiatric diseases they are ranked second.  There are few other diseases as disabling or lethal.  Third, there have been treatments that are based on the underlying biological factors that are thought to be relevant to addiction that have worked.  Four, it is very clear that individuals with addictions are no longer functioning normally – defined as their normal baseline.  That can start at any point in the life cycle – and at some point most people are aware that they have a severe problem and cannot stop.

All of those factors point to a disease state and it is good to see a paper supporting that opinion.   But even beyond this opinion, consider the people you have known with addictions and make up your own mind based on that experience.  Carefully consider how you interact with people if you consider addiction to be a disease or intentional decision-making.

 

 George Dawson, MD

 

References:

1:  Heilig M, MacKillop J, Martinez D, Rehm J, Leggio L, Vanderschuren LJMJ. Addiction as a brain disease revised: why it still matters, and the need for consilience. Neuropsychopharmacology. 2021 Feb 22. doi: 10.1038/s41386-020-00950-y. Epub ahead of print. PMID: 33619327.

2:  Heilig M, Augier E, Pfarr S, Sommer WH. Developing neuroscience-based treatments for alcohol addiction: A matter of choice? Transl Psychiatry. 2019 Oct 8;9(1):255. doi: 10.1038/s41398-019-0591-6. PMID: 31594920; PMCID: PMC6783461.

3:  Venniro M, Banks ML, Heilig M, Epstein DH, Shaham Y. Improving translation of animal models of addiction and relapse by reverse translation. Nat Rev Neurosci. 2020 Nov;21(11):625-643. doi: 10.1038/s41583-020-0378-z. Epub 2020 Oct 6. PMID: 33024318.

4:  Tikkinen KA, Leinonen JS, Guyatt GH, Ebrahim S, Järvinen TL. What is a disease? Perspectives of the public, health professionals and legislators. BMJ Open. 2012 Dec 2;2(6):e001632. doi: 10.1136/bmjopen-2012-001632. PMID: 23204142; PMCID: PMC3533011.

5:  Tikkinen KAO, Rutanen J, Frances A, Perry BL, Dennis BB, Agarwal A, Maqbool A, Ebrahim S, Leinonen JS, Järvinen TLN, Guyatt GH. Public, health professional and legislator perspectives on the concept of psychiatric disease: a population-based survey. BMJ Open. 2019 Jun 4;9(6):e024265. doi: 10.1136/bmjopen-2018-024265. PMID: 31167856; PMCID: PMC6561450.

6:  Wit v. United Behavioral Health.  Full text of ruling.

7:  Leshner AI. Addiction is a brain disease, and it matters. Science. 1997 Oct 3;278(5335):45-7. doi: 10.1126/science.278.5335.45. PMID: 9311924.

8:  McLellan AT, Lewis DC, O'Brien CP, Kleber HD. Drug dependence, a chronic medical illness: implications for treatment, insurance, and outcomes evaluation. JAMA. 2000 Oct 4;284(13):1689-95. doi: 10.1001/jama.284.13.1689. PMID: 11015800.

9:  Koob GF, Volkow ND. Neurobiology of addiction: a neurocircuitry analysis. Lancet Psychiatry. 2016 Aug;3(8):760-773. doi: 10.1016/S2215-0366(16)00104-8. PMID: 27475769; PMCID: PMC6135092.

10:  Volkow ND, Morales M. The Brain on Drugs: From Reward to Addiction. Cell. 2015 Aug 13;162(4):712-25. doi: 10.1016/j.cell.2015.07.046. PMID: 26276628.

11:  Koob GF, Powell P, White A. Addiction as a Coping Response: Hyperkatifeia, Deaths of Despair, and COVID-19. Am J Psychiatry. 2020 Nov 1;177(11):1031-1037. doi: 10.1176/appi.ajp.2020.20091375. PMID: 33135468.

12.  Miga KH. Breaking through the unknowns of the human reference genome. Nature. 2021 Feb;590(7845):217-218. doi: 10.1038/d41586-021-00293-8. PMID: 33568817.

13:  Ho MF, Zhang C, Zhang L, Wei L, Zhou Y, Moon I, Geske JR, Choi DS, Biernacka J, Frye M, Wen Z, Karpyak VM, Li H, Weinshilboum R. TSPAN5 influences serotonin and kynurenine: pharmacogenomic mechanisms related to alcohol use disorder and acamprosate treatment response. Mol Psychiatry. 2020 Aug 4:10.1038/s41380-020-0855-9. doi: 10.1038/s41380-020-0855-9. Epub ahead of print. PMID: 32753686; PMCID: PMC7858703.

14:   Nguyen TTL, Liu D, Ho MF, Athreya AP, Weinshilboum R. Selective Serotonin Reuptake Inhibitor Pharmaco-Omics: Mechanisms and Prediction. Front Pharmacol. 2021 Jan 11;11:614048. doi: 10.3389/fphar.2020.614048. PMID: 33510640; PMCID: PMC7836019.

 

 

Sleep and Addiction

One of the major problems that I treat in people with significant substance use disorders is insomnia of all types.  I see people who have had insomnia since childhood.  A significant number have had insomnia and nightmares since childhood.  In that case the insomnia often precedes the development of any associated psychiatric diagnoses – it is a primary problem. In many cases, it is one of the reasons that people develop a substance use problem.  Alcohol, sedative hypnotics (often benzodiazepine type drugs), opioids, and cannabis are commonly taken for sleep and typically lead to many secondary problems.  Alcohol for example, will often lead to faster sleep onset, but as tolerance develops, the person will start to make up at 2 or 3 in the morning.  With increasing tolerance, a decision about taking more drinks at that time or toughing it out until the morning will need to be made. Some people can get to the point that they ingest large enough quantities of alcohol that they sleep the entire night and wake up with elevated blood alcohol levels.  Some do not realize the problem until they are arrested driving into work the next morning for intoxicated driving.

The available medications for treating insomnia in patients with addiction are limited.  We can currently treat a significant number of patients with sleep problems but there are still many that have very difficult to treat insomnia.

Medication	Probable Sleep Mechanism of Action
Trazodone	H-1 antagonist, NE antagonist, 5-HT2 antagonist
Doxepin	H-1 antagonist, NE antagonist, Ach antagonist
Mirtazapine	H-1 antagonist, 5-HT2 antagonist
Hydroxyzine	H-1 inverse agonist, Ach antagonist
Quetiapine	H-1 antagonist, NE antagonist, Ach antagonist, 5-HT2 antagonist, DA antagonist
Ramelteon	MT-1/MT-2 agonist  MT-1> MT-2
Melatonin	MT-1/MT-2 agonist  MT-1>MT-2
Prazosin	α1- adrenergic antagonist
Gabapentin	inhibition of the alpha 2-delta subunit of voltage-gated calcium channels
Benzodiazepines (detox only)	GABAA receptor agonist
Opioids (detox, MAT)	MOR agonist

 

The general strategy of using these medications is apparent from the purported mechanisms. For example, brain histamine (H) and acetylcholine (Ach) are alerting and arousing neurotransmitter systems so that antagonists/inverse agonists would be expected to decrease arousal and facilitate sleep.  Noradrenergic (NE) systems are wake promoting so NE antagonists would be expected to decrease this function.  The compounds in the above table work the best in addictive states when a person is abstinent from intoxicants and chronic use of intoxicants and after they have been detoxed.  Benzodiazepines and opioids are in the table for that purpose.  Although I have seen detox protocols that include many of the medications listed in the table as needed for insomnia and anxiety it is unlikely that they will work until detoxification has occurred.  In many cases, the expected duration of detox is much longer than anticipated and sleep problems are a prominent reason.    

That brings me to the primary focus of this post and that is a recent paper entitled “Drugs, Sleep, and the Addicted brain.” I generally don’t get too excited about research papers these days, but after reading this brief paper by Valentino and Volkow – I was fairly excited.  In this paper the authors main goal is to demonstrate how the biological substrates that regulate sleep interact with the reward system and how they can be direct targets for substance use. 

The first system they look at is the locus ceruleus (LC)-norepinephrine (NE) system that is involved in arousal. LC-NE neurons do not fire during REM sleep.  Activation of the LC results in firing of noradrenergic neurons that activate the cortex. Corticotropin-releasing factor (CRF) leads to LC activation and heightened arousal.  Endogenous opioids lead to damped excitation and decreased arousal.  Tolerance to exogenous opioids would lead to an expected inability to dampen the LC-NE system and increased activation and arousal during opioid withdrawal.

The serotonin (5-HT) dorsal raphe nuclei (DRN) system is also a system implicated in both sleep and arousal.   5-HT neurons are active during waking and do not fire during REM sleep. 

Histaminergic (H) neurons in the tuberomammillary nucleus (TMN) have an arousal function on cortical neurons.  They are active in the awake state.

Midbrain dopaminergic neurons (DA) in the ventral tegmental are (VTA) specifically those projecting to the nucleus accumbens (NAc) increase wakefulness upon activation but activation of the other major set of DA neurons in the substantia nigra has no effect.  This is a critical circuit in substance use because this system determines the value function of stimuli in the environment including addictive compounds and affects arousal.

Cannabinoids promote sleep, sleep onset, slow wave sleep, and sleep duration.  They decrease REM sleep.  CB1 agonists and antagonists respond in the expected manner.  The effects of CB1 agonism may be mediated by adenosine which increases in response to the stimulation of this pathway.  Caffeine is an adenosine antagonist and that may be the reason is promotes wakefulness.  Endocannabinoids also inhibit orexin neurons (arousal promoting) in the lateral hypothalamus and increase the activity of melanin neurons.  These combined effects of cannabinoids on the endogenous cannabinoid system explain the expected insomnia when these compounds are stopped for any reason.

The orexin system in the lateral hypothalamus and dorsal medical hypothalamus/perifornical area is activated during wakening and silent during sleep.  It is the system that is disrupted in narcolepsy.  It is also the system that coordinates the activity of the other arousal centers in the brain including the TMN-HA, LC-NE, DRN-5-HT, VTA-DA, and cholinergic neurons in the Nucleus Basalis of Meynert (NBM-Ach).  This relationship is depicted in the following graphic from the paper and detailed in reference 3.

Orexin A and Orexin B are wake  promoting neuropeptides the general structure of which is given below.  These peptides bind to Ox1R and Ox2R G-protein coupled receptors.  Orexin A has equal binding affinity to both receptor but Orexin B preferentially binds to the Ox2R receptor.  Detailed information is available from PubChem.

Human Orexin A

The orexin system may be critical not just in arousal but also in reward.  Patients with narcolepsy have orexin deficiency and generally do not overuse opioids and are less likely to overuse stimulants even though many have been prescribed very high doses.  Opioid users have increased orexin neurons in the lateral hypothalamus.  This increase in orexin signaling may lead to profound insomnia and the associated arousal state after prolonged exposure to opioids and makes this insomnia very difficult to treat.  Orexin can directly potentiate reward in some models.  Orexin is implicated in states where a high level of motivation to acquire the target substance is required or where there are external stimuli like stress, and specific cues for drug use that lead to increased motivational states.  The authors in reference 2 refer to orexin's ability to affect the approach toward a reinforcing stimulus or active withdrawal from an aversive stimulus as motivational activation.

Suvorexant is an interesting compound in that it antagonizes Orexin A and Orexin B wake-promoting neuropeptides and prevents them from binding to Ox1R and OXxR receptors decreasing wakefulness.  It is currently FDA approved as a treatment for insomnia, but the authors propose that it is a compound of interest in that it can potentially counter the arousal and reward potentiation associated with drug seeking states.  If that is the case it could be a useful treatment for both insomnia and the primary addictive disorders.

When I look at possible treatments for insomnia in addiction, a central question is whether or not they will potentially worsen the addictive state.  That is why there are no specific benzodiazepine related sleep compounds in the table at the top of this post.  The benzodiazepines listed there are all basically used on a short term basis for detox and then tapered and discontinued.  In the case of mu-opioid receptors (MOR), medication assisted treatment with both buprenorphine and methadone are possible on an ongoing basis. The package insert for suvorexant suggests possible problems in that subjects with recreational polydrug use rated their "liking" of the drug as being similar to zolpidem 15 and 30 mg doses.  Zolpidem is a standard sedative hypnotic that can be used to treat insomnia.  It definitely has abuse potential and in some cases patients can end up taking very high doses per day until they can be detoxified.  That is not reassuring in terms of safety for persons with substance use problems but I would not take it as proof that it cannot be safely used.  According to the DEA, suvorexant is currently a Schedule IV drug or low potential for abuse or dependence. Some articles on insomnia suggest that despite what appears to be a comprehensive mechanism, the short term efficacy of suvorexant is no greater than zolpidem but at a much greater cost.

I am currently looking at the medicinal chemistry and clinical trials literature to assist me decision making on orexin receptor antagonists and just how much of withdrawal related insomnia is due to orexins. The other important question is whether it will also decrease drug seeking states and withdrawal avoidance.   

George Dawson, MD, DFAPA

References:

All full text and all excellent

1: Valentino RJ, Volkow ND. Drugs, sleep, and the addicted brain. Neuropsychopharmacology. 2020;45(1):3–5. doi:10.1038/s41386-019-0465-x

2: James MH, Mahler SV, Moorman DE, Aston-Jones G. A Decade of Orexin/Hypocretin and Addiction: Where Are We Now?. Curr Top Behav Neurosci. 2017;33:247–281. doi:10.1007/7854_2016_57

3: Peyron C, Tighe DK, van den Pol AN, et al. Neurons containing hypocretin (orexin) project to multiple neuronal systems. J Neurosci. 1998;18(23):9996–10015. doi:10.1523/JNEUROSCI.18-23-09996.1998

Graphics Credit:

The brain graphic is from reference 1 and is used here without modification per the Creative Commons Attribution 4.0 License.

Disclaimer:

This post may change significantly over the next two weeks.  I had to put it up to see what it looks like and plan to elaborate the behavioral pharmacology of orexin and the pharmacology of suvorexant.

Reward Prediction Error At The Gas Pump

A couple of years ago I was driving up to Minnesota resort country when I noticed something happened at gas stations. For decades, gas pump choices were arranged linearly with the lowest octane fuel on the left and the highest on the right.  The only difference was the occasional pump with diesel or racing fuel options and they were typically on the far right.  To illustrate I took this photo of a gas pump display on the way home form work yesterday.  Three years ago the display would have been (left to right) 87-88-91.  In this case, in addition to the octane shuffle there is a price dissociation.  Motorists have been trained for year to expect that 87 octane to be the least expensive and now it is not - 88 octane is the least expensive.  These changes at the pump reminded me of a paper I had read a few years ago by Wolfram Schultz one of the world experts in reward prediction error. 

Reward prediction error is basically the difference between a prediction about the nature of the reward and what really happens. See all of the definitions in the diagram below that are taken directly from Schultz.  Reward is clearly defined as well as predictions to both the positive and negative sides.

In the paper of interest Dr. Schultz introduces it by being confronted with a vending machine where he cannot read the language (Japanese).  There are 6 choices and his expectation is low that he will get his preferred choice so he pushes the second button.  He is surprised that it delivers exactly what he wants - black current juice. He points out that this experience will keep him pressing this second button until the machine is loaded differently and he does not get his expected juice.  He uses this as an example of positive reward prediction error (RPE) or the difference between his low expectation and the ideal outcome that resulted.  RPE systems are set up to optimize positive reward prediction error.  When the eventual negative outcome results in negative prediction error decision making will change in order to return to the positive RPE scenario and then no reward prediction error scenarios.

Getting back to the gas pumps. They appear to have been designed to defeat RPE at two levels.  First, the position of the buttons after everyone was conditioned to push the one at the far left.  The second, is the dissociation of gas price from button position.  There is no longer a linear correlation between octane and price.  I am not sure if both of these trends have been occurring over time or just recently. I do know from studying various gas pumps that the button positions do not necessarily reflect linear price or octane changes, but in some cases they still do. The good news is that they can both be overcome by carefully studying the octane button position and posted per gallon price rather than depending on the old learned patterns.  The other interesting aspect of the gas pump problem is that there don't have to be a lot of predictions.  The prediction error occurs only if the purchaser depends on old patterns without paying close attention to details. 

The neurobiology of RPE is more fascinating than the descriptive aspects. We know that the neurobiology of reward in the human brain is heavily dependent on dopaminergic systems in the ventral striatum.  Dopaminergic neurons code reward in the form of prediction error even  in complex tasks.  What is even more interesting  is that the coding is not in terms of quantifiable measures but subjective ones.  Utility functions incorporate subjective measures and can be used to determine the potential values of the reward.  Dopaminergic neurons code the utility of the received reward minus the utility of the predicted reward.  Looking at a computational model of the addictive process, Redish (7) discusses a value function V[s(t)] dependent on the state of the world s(t) and presents it as the calculation of expected future reward discounted by the expected time of reward:

As noted the value of delayed rewards are reduced and the actual discounting applied is based on empirical work on discounting in human and animal models.  The author in this case goes on to develop a computational model of addiction in this case that is based on reward prediction error and the fact that cocaine produces direct phasic increases in dopamine (DA).  The model is termed a temporal-difference reinforcement learning (TDRL) model.  According to RPE increases in DA occur after unexpected natural rewards. Over time DA release decreases, learning stops, and instead is paired with the cues for the reward.  That does not occur with a pharmacological reaction at the level of the dopaminergic neurons.  In that case, a drug like cocaine will release DA independent of the expected reward.  That produces a final state where a unexpected natural reward, a cue for a learned reward, and cocaine will all produce DA.

The Redish paper also looks in detail at a couple of associated issues. The first is rational addiction theory defined as the user maximizing value or utility over time. Long term rewards for quitting are discounted more than the short term penalties and therefore the user remains addicted.  In the author's model "the maximized function entails remaining addicted." (p 1946).  TDRL theory suggests that addiction is always irrational because the pharmacological effects of cocaine (in this case) always outweigh the associated DA surges from the universe of value functions available in the real world. Addictive drugs will produce an increase in DA, so that the user will not be able to encounter and learn a value function that is associated with an equal or greater DA surge than is produced by the drug.  Therefore the user remains addicted.  This has been taught in addiction seminars for years as the Hijacked Brain Hypothesis - meaning that the dopamine signal produced by addictive drugs overwhelms the dopamine signal produced by natural stimuli like eating, drinking water, sexual behavior, and social affiliation.  Both RPE and TDRL theory offer more explanatory power than the Hijacked Brain Hypothesis. 

As I wrap up this post, I pulled down the latest editions of the two major addiction texts to see what they had to say about reward prediction error, computational models of addiction, and some of the authors referenced in this post, especially Wolfram Schultz.  There were no references at all and the sections on the actual function of DA neurons in addiction was surprisingly thin. On the other hand a lot of concepts used in the field like salience are the direct product of these systems. In order to produce a more coherent picture of the neurobiology of addiction it is important to outline these DA systems and how they work normally and in addictive states.

I am hoping that addiction texts for clinicians will contain some of this information in the near future and ideally the chapters will be written by the scientists that have been studying these processes in some cases for decades.


George Dawson, MD, DFAPA

Supplementary 1:

Getting back to the gas pump example, considering the 3 octane ratings and the three prices that may or may not correspond to the octane ratings means that there are 6 possible combinations at any pump that need to be considered.  Any real world actor at the pump needs to consider this carefully when the gas pump has undergone a transition from the expected correlation between increasing octane ratings and price to one where this relationship does not exist. The advantage to the actor in this case is that all of this information is explicit and that behavior is more likely to be affected by negative prediction error when automatic selection behavior results in the wrong octane or fuel cost being selected.  That is unlike Dr. Schultz's example in the Japanese airport when he randomly chose a beverage and was unexpectedly rewarded.


Supplementary 2:

I can't say enough about the writings of Wolfram Schultz.  They are only peripherally mentioned in the addiction literature and yet his theories and experiments are some of the more important that I have read with regard to the neurobiological theories of addiction.

Papers of Wolfram Schultz - Journal of Neurophysiology Page Link

Home Page of Wolfram Schultz Link - contain some of the best PowerPoint slides that I have ever seen.

References:




1: Schultz W. Dopamine reward prediction error coding. Dialogues Clin Neurosci.2016 Mar;18(1):23-32. Review. PubMed PMID: 27069377 full text

2: Schultz W. Reward prediction error. Curr Biol. 2017 May 22;27(10):R369-R371.doi: 10.1016/j.cub.2017.02.064. PubMed PMID: 28535383 full text

3: Stauffer WR. The biological and behavioral computations that influence dopamine responses. Curr Opin Neurobiol. 2018 Apr;49:123-131. doi: 10.1016/j.conb.2018.02.005. Epub 2018 Mar 2. Review. PubMed PMID: 29505948. full text

4: Takahashi YK, Batchelor HM, Liu B, Khanna A, Morales M, Schoenbaum G. DopamineNeurons Respond to Errors in the Prediction of Sensory Features of Expected Rewards. Neuron. 2017 Sep 13;95(6):1395-1405.e3. doi: 10.1016/j.neuron.2017.08.025. PubMed PMID: 28910622. full text

5: Keiflin R, Pribut HJ, Shah NB, Janak PH. Ventral Tegmental Dopamine Neurons Participate in Reward Identity Predictions. Curr Biol. 2019 Jan 7;29(1):93-103.e3. doi: 10.1016/j.cub.2018.11.050. Epub 2018 Dec 20. PubMed PMID: 30581025.

6: Tobler PN, Fiorillo CD, Schultz W. Adaptive coding of reward value by dopamine neurons. Science. 2005 Mar 11;307(5715):1642-5. PubMed PMID: 15761155.

7: Redish AD. Addiction as a computational process gone awry. Science. 2004 Dec10;306(5703):1944-7. PubMed PMID: 15591205.

8: Sweis BM, Thomas MJ, Redish AD. Beyond simple tests of value: measuring addiction as a heterogeneous disease of computation-specific valuation processes. Learn Mem. 2018 Aug 16;25(9):501-512. doi: 10.1101/lm.047795.118. Print 2018 Sep. PubMed PMID: 30115772.