The Science of Sexual Orientation

(from psychologicalscience.org)
(from psychologicalscience.org)

Happy New Year!

I figure I’ll kick things off with something a little different than my usual science of addiction posts.

My new job deals with supporting LGBT rights in the developing world and there’s a lot of work be done! In fact, as of June 2016, 77 countries or territories criminalize homosexuality and 13 countries or territories penalize homosexual behavior by death. But why is this? Why is someone who is attracted to and has sex with someone of the same sex so controversial in so much of the world? Well..I’m not about to begin to answer that question because I’ll be writing all week (hint, hint: religion is a huge factor).

Instead, I’ll present some of the key findings from a relatively new (April 2016) review article about the science of sexual orientation by JM Bailey and colleagues in the journal Psychological Science in the Public Interest. This is by far one of the most comprehensive and most even handed review articles written on the subject. The authors take an extremely academic approach because let’s face, the science surrounding sexual orientation has been used and abused by both pro- and anti- gay rights folks. (note: this article does not really discuss with transgenderism or gender identity issues)

This article is too long to go into all the details so instead I’m just going to present the main highlights that I prepared for a research report a few months back. Enjoy!

Download the article here. It’s Open Access!

jm-bailey-et-al-2016

Brief Summary:

Political controversies pertaining to the acceptance of non-heterosexual (lesbian, gay, bisexual) orientation often overlap with controversies surrounding the science of sexual orientation. In an attempt to clarify the erroneous use of scientific information from both sides of the debate, this article 1) provides a comprehensive review of the current science of sexual orientation, and 2) considers the relevance of scientific findings to political discussions on sexual orientation.

Top Takeaways from the Review:

  • The scientific evidence strongly supports non-social versus social causes of sexual orientation.
  • The science of sexual orientation is often poorly used in political debates but scientific evidence can be relevant to specific, limited number of issues that may have political consequences.
(wikimedia.org)
(wikimedia.org)

The scientific evidence strongly supports non-social versus social causes of sexual orientation (nature vs nurture).

Prevalence of non-heterosexual orientation (analysis of 9 large studies): 5% of U.S. adults.

Summary of the major, scientifically well-founded findings supporting non-social causes:

  • Gender non-conformity during childhood (before the onset of sexual attraction) strongly correlates with non-heterosexuality as an adult.
  • Occurrence of same-sex behavior has been documented in hundreds of species and regular occurrence of such behavior in a few species (mostly primates, sheep).
  • Reported differences in the structure of a specific brain region (SDN-POA) between heterosexual and homosexual men.
  • Hormone-induced changes in the SDN-POA during development in animal studies and subsequent altered adult sexual behavior (the organizational hypothesis).
  • Reports of males reared as females but who exhibit heterosexual attractions as adults.
  • Twin studies suggest only moderate genetic/heritable influence on sexual orientation.
  • Several reports identify a region on the X chromosome associated with homosexuality.
  • The most consistent finding is that homosexual men tend to have a greater number of biological older brothers than heterosexual men. (fraternal-birth-order effect)

The science of sexual orientation is often poorly used in political debates, but scientific evidence can be relevant to a specific, limited number of issues that may have political consequences.

The question of whether sexual orientation is a “choice” is logically and semantically confusing and cannot be scientifically proven. It should not be included in political discussions.

Examples of scientifically reasonable questions include:

  • Is sexual orientation determined by non-social (genetic/hormonal/etc.) or social causes? (nature vs nurture)
  • Is sexual orientation primarily determined by genetics or environment?

Specific cases in which scientific evidence can be used to inform political decisions:

  • The belief that homosexual people recruit others to homosexuality (recruitment hypothesis). This type of belief was espoused by by President Museveni of Uganda in 2014 and was used to justify Uganda’s notorious anti-homosexuality bill (since repealed).
    • No studies exist that provide any type of evidence in support of this hypothesis.
  • Proponents of conversion/reparative “therapies” argue that sexual orientation can be changed through conditioning and reinforcement.  Gov. and VP-elect Mike Pence  allegedly supported these types of bogus “therapies” in Indiana.
    • Studies reporting successful “conversion” suffer from methodological errors such as selection bias and/or unreliable self-report data and are therefore scientifically unfounded.
    • No evidence exists that a person’s sexual orientation can be changed at will.

 

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Marijuana has Long-term Effects on the Brains of Adolescents

(from wikipedia.org)
(from wikipedia.org)

After alcohol, marijuana is the most widely used illegal drug in the United States (I mean seriously, who hasn’t smoked up at least once? According to Pew Research Center, half of the country) But pot laws are rapidly changing in many parts of the country and soon it may be as ubiquitous as alcohol. Four states in the US have legalized marijuana for recreational use and 23 total states have some form of legal marijuana use (including D.C.). While the health effects of alcohol have been well studied and are significant (some 88,000 deaths/year, the third highest cause of preventable death in the US, according to the CDC and NIAAA), little is known how this shifting trend in marijuana use will affect the country. Another important trend is the amount of THC (Δ-9-tetrohydrocannabinol, the chemical that is primarily responsible for the psychoactive effects of marijuana) in marijuana strains has been steadily increasing over the past few decades [1, 2]. The big question that researchers are asking themselves is if legal marijuana use drastically increases, what are the long-term personal and public health consequences of marijuana use? Of course, this is a huge question with many complexities.

Significantly, Marijuana is the also the most widely used illegal substance amongst youths. Adolescence (ages 12-17) is an extremely critical period for brain development [3, 4] yet the effects of marijuana on the brains of kids have not been thoroughly studied. A recent paper out of Dr. Steven R. Laviolette’s laboratory at the University of Ontario sought to answer this question: what happens to brains of adolescent and adult rats that have been exposed to THC?

Renard et al. 2016 abstract

Why was the research done? What is the hypothesis?

 There have been a number of studies published that suggest there might be an association between prolonged marijuana use (especially of high-potency strains) and schizophrenic-like or psychotic-like symptoms [5, 6] although there is disagreement in the scientific community on the evidence [7, 8] (I may write a blog post discussing this issue in the future). It is has even been suggested that youths that smoke marijuana are more at risk for psychotic symptoms as adults [9, 10]. The author’s sought to test this directly by injecting adolescent and adult rats with THC for a number of days, waiting a period of time after the injections, then measuring the long-term effects on the rats. The team hypothesized THC would have induced long-term changes in the brains of adolescent but not adults rats, and subsequent changes in psychotic-like behavior.

How was it done?

Adolescent and adult rats were injected with THC twice daily for 11 days. The dose of THC administered was increased (escalating dose) to account for any tolerance that may occur. As an important control, separate groups of adolescent and adult rats were injected with vehicle (the solution that THC was dissolved in but minus the THC itself). Following a 30-day abstinence period after the last injection, THC-adolescent, control-adolescent, THC-adult, and control-adult rat groups were subjected to number of behavioral and molecular tests to see what effect the drug had on the animals. I need to point out that the 30-day abstinence period is significant in the rat life-span. This is enough time for the adolescent rats to become adults so what the scientists are primarily studying is the long-term effects of THC on adolescents vs adults in adulthood.

In the behavioral neuroscience field, we have devised another of tests to measure various aspects of animal behavior. Obviously we can’t inject humans with THC and see what happens so we have to use rodents and identify behaviors that approximate a similar behavior in humans. Of course, rodent behavior is no where near as complex as humans but rats are remarkably sophisticated animals (ask anyone living in New York) and scientists have developed a number of ways to measure things from motivation to social behavior to anxiety to depression.

In this experiment, a social test was used, two different types of anxiety tests and a motor activity test. The tests measured effects on motivation, exploratory-behavior (another indicator of how motivated rats are), social interaction, and anxiety.

The scientists also measured the activity of dopamine-releasing neurons in the living animal using a technique called in vivo electrophysiology. Recall from my post I am Neuron! that when activated, brain cells (called neurons) conduct an electrical current that results in the release of neurotransmitters onto another neuron. This electrical current is called an action potential and we can measure this by inserting a special probe into the those neurons in the animals brain (the probe measures electrical currents). Therefore, with in vivo electrophysiology we can measure every time a neuron fires (i.e. an action potential is generated) in a specific part of the brain. Using this technique, the scientists measured dopamine neurons in an important region of the brain called the VTA and how often these neurons fire in THC vs control rats. Check out this video for more details on in vivo electrophysiology.

Finally, brains from animals were dissected and a number of protein molecules were studied using a common technique in molecular biology called a Western blot (or known as an immunoblot). A Western blot takes advantage of antibodies that are able to recognize and stick to one specific type of protein. Therefore, this assay can tell you two main things 1) if your protein of interest is present in your sample and 2) approximately how much of your protein there is compared to other samples. In this paper, tissue from a specific brain region is used and the protein is analyzed by Western blots in order to comparing quantities of proteins between the different experimental groups. Of course, the limitation of a Western blot is if you have a good antibody for your protein of interest. Luckily there are many biotech companies such as Cell Signaling that specialize in making and testing reliable antibodies. The scientists used the Western blots to study many proteins in a region of the brain called the prefrontal cortex (PFC), which is believed to be important in self-control and other high-function brain processes. Check out this video for more details on Western Blots.

What did they find?

THC-adolescent rats exhibited deficits in numerous behavioral experiments compared to controls while THC-adult rats did not appear to have any behavioral changes.

*Recall that these experiments were conducted 30 days after the last THC dose so the author’s show that these are long-term effects of THC on the brain of adolescent rats.

In the social activity test, rats showed little interest in interacting with a stranger rat (normal rats are usually curious about the novel stranger). THC-adolescents also did not walk around or explore a new cage as much. In the two different anxiety tests, THC-rats appeared to have be more anxious (demonstrated more anxiety-like behavior).

In the electrophysiology experiment, VTA DA neurons fired more frequently for some reason in THC-adolescents compared to the other groups.

Finally, numerous protein changes in the PFC were observed in a number of important signaling pathways such as Wnt and mTOR pathways. Interestingly, THC-adolescents vs THC-adults seemed to have opposite effects on this proteins.

Limitations to the study?

  1.  The behavioral changes observed were statistically significant (meaning, most likely a real effect and not some kind of fluke of random chance) but were modest changes in some of the tests performed. Would the changes last beyond the 30 days post injection in this study?
  2. There are impressive arrays of behavioral tests that rats can perform to measure numerous aspects of cognition (for example, memory and learning) but none of these experiments were performed. A far greater range of behavioral experiments would have made this study more compelling.
  3. While the electrophysiology and Western blot data are intriguing, the author’s performed no experiments to determine if these changes are responsible for the difference in behavior (association vs causation). These changes could merely be an incidental change and have nothing to do with the behaviors studies.
  4. The doses that the mice were injected with, while based on a previous study, are somewhat arbitrary. Would the changes be more pronounced or less pronounced with higher/lower doses or a shorter/longer dosing regimen?
  5. Only male rats were studied. Would the same behavioral and molecular changes occur in female rats?

What does it mean?

Based on the behavioral and molecular data presented, this data paper suggests that adolescent rats (but not adults) exposed to THC have long-lasting changes in the brain. The author’s argue that these effects recapitulate schizophrenia-like symptoms but I am not entirely convinced. Also, THC given to rats is not the same thing as marijuana smoked by human teenagers. So it’s important to keep in mind that this is one study. In science, we never draw grand conclusions about anything based on one study. Nevertheless, several other reports have corroborated these findings (see this review paper for a summary of many of them [11]). Indeed, it does seem that marijuana use can cause long-term deficiencies in human and rodent brains. The results of this paper are certainly intriguing and, if true, a whole host of stricter regulations on marijuana use in states that have legalized it may need to put in place to help curb increasing marijuana abuse amongst youths.

References

  1. Cascini F, et al. Increasing delta-9-tetrahydrocannabinol (Delta-9-THC) content in herbal cannabis over time: systematic review and meta-analysis. Current drug abuse reviews. 2012;5(1):32-40.
  1. Mehmedic Z, et al. Potency trends of Delta9-THC and other cannabinoids in confiscated cannabis preparations from 1993 to 2008. Journal of forensic sciences. 2010;55(5):1209-17.
  1. Keshavan MS, et al. Changes in the adolescent brain and the pathophysiology of psychotic disorders. The lancet Psychiatry. 2014;1(7):549-58.
  1. Spear LP. The adolescent brain and age-related behavioral manifestations. Neuroscience and biobehavioral reviews. 2000;24(4):417-63.
  1. Arseneault L, et al. Causal association between cannabis and psychosis: examination of the evidence. The British journal of psychiatry : the journal of mental science. 2004;184:110-7.
  1. Di Forti M, et al. Daily use, especially of high-potency cannabis, drives the earlier onset of psychosis in cannabis users. Schizophrenia bulletin. 2014;40(6):1509-17.
  1. Moore TH, et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet. 2007;370(9584):319-28.
  1. Gage SH, et al. Association Between Cannabis and Psychosis: Epidemiologic Evidence. Biological psychiatry. 2015.
  1. Rubino T, Parolaro D. Long lasting consequences of cannabis exposure in adolescence. Molecular and cellular endocrinology. 2008;286(1-2 Suppl 1):S108-13.
  1. Stefanis NC, et al. Early adolescent cannabis exposure and positive and negative dimensions of psychosis. Addiction. 2004;99(10):1333-41.
  1. Renard J, et al. Long-term consequences of adolescent cannabinoid exposure in adult psychopathology. Frontiers in neuroscience. 2014;8:361.

Response to HuffPost Marc Lewis Interview on Addiction

So the Huffington Post runs a sub-blog on Addiction and Recovery and sometimes they present excellent reporting (for example, the piece on opioid addiction by Jason Cherkis who actually interviewed my boss, Dr. Mary Jeanne Kreek, for the article). But more often than not, they present quite variable reporting on addiction.  A recent interview with psychologist Marc Lewis, PhD is one such example.

Based on my own neuroscience of addiction background, I unfortunately find a number of Dr. Lewis’s claims not supported by scientific evidence and I believe the spread of such false statements can have the exact opposite of his intended effect—hurting more addicts rather than helping them. I do not claim to be the consensus voice of the addiction field but present my own arguments based on my own research and work done in the field. I also admit have not read any of Dr. Lewis’s books and am merely responding to the statements made in his interview. I include references at the end of the post.

The original interview between Carolyn Gregoire, Senior Health and Science Writer for Huffington Post and psychologist Marc Lewis, PhD

The questions (Q) by Carolyn Gregoire in the original interview are in bold, Dr. Lewis’s response (L) is italicized, and my response (S) is the un-italicized larger-size text.

Q: What’s wrong with the disease model of addiction? 

L: I know what scientists are looking at when they say addiction is a disease. I don’t dispute the findings, but I dispute the interpretation of them. They see addiction as a chronic brain disease — that’s how they define it in very explicit terms. 

My training is in emotional and personality development. I see addiction as a developmental process. So the brain changes that people talk about and have shown reliably in research can be seen as changes that are due to learning, to recurrent and deep learning experiences. But it’s not an abnormal experience and there’s nothing static or chronic about it, because people continue to change when they recover and come out of addiction. So the chronic label doesn’t make much sense.

S: The brain is a physical organ that operates under defined molecular biological principles. Drugs are physical chemical substances that perturb the molecular function of the brain. It is true that addiction is a process that can take months or even years to develop but the end result is a physical neurobiological change in how the brain functions [1, 2]. And when neuroscientists say chronic brain disease—or what my lab says A disease of the brain with behavioral manifestations—what we mean is that repeated drug use has caused a change is brain function which in turn results in a change in behavior. That doesn’t mean that this change is irreversible but, like other diseases, the first step to treatment is recognizing the underlying biological cause. Defining addiction as a chronic brain disease is not a judgment or interpretation of the development of addiction (which definitely does involve a learning and memory component [3, 4]) but is a statement asserting that drug addiction and drug cravings, compulsive drug use, and relapse are ultimately based on physical changes in the brain. It is important that we recognize this because otherwise we would not be able to treat it with effective and safe medications, in combination with other behavioral and psychological therapies.

Q: What’s problematic about the way we treat addiction, based on the disease model? 

L: Well, lots. The rehab industry is a terrible mess — you either wait on a long list for state-sponsored rehabs that are poorly run or almost entirely 12-Step, or else you pay vast amounts of money for residential rehabs that usually last for 30-90 days and people often go about five to six times. It’s very difficult to maintain your sobriety when you go home and you’re back in your lonely little apartment. 

What I emphasize is that the disease label makes it worse. You have experts saying, “You have a chronic brain disease and you need to get it treated. Why don’t you come here and spend $100,000 and we’ll help you treat it?” There’s a very strong motivation from the family, if not the individual, to go through this process, and then the treatments offered in these places are very seldom evidence-based, and the success rates are low. 

S: I strongly agree with this assessment. The rehab industry and many 12-step programs are ineffective, expensive, and rarely based on scientific evidence. The primary reason is that for decades addiction was thought of a problem of “spiritual weakness” or “lack of will power”. In reality addiction is a medical disorder based on physical neurobiological processes that make it seem like an addict has no “will power”, when in reality that addict’s brain has been hijacked to crave the drug compulsively and practically uncontrollably. However, again, I disagree that calling addiction a disease is what funnels people into rehab clinics. I believe it is the stigmatization of addiction that precludes treatment by doctors (unlike for every other disease), which in turn fuels admission into the rehab industry. Sadly, effective medications exist (such as methadone and buprenorphine for opioid addicts) that can flick a switch off in an addicts brain, satisfying their craving and allow them to live a normal live [5, 6]. Or medications such as naltrexone may be effective at reducing drinking in alcohol addicts but is not widely used [7, 8]. It is only recently that public acknowledgement of the biological basis of addiction and appropriate shifts in public policy are beginning to take place. Importantly, addiction medicine is beginning to become incorporated into medical school education and the first accredited residency programs in addiction medicine have been announced.

Q: There are lots of ways to trigger a humanistic response besides calling something a disease. So you would say that telling people who are in recovery for addiction that they have a “chronic disease” is actually doing them a disservice? 

L: Well, the chronic part is really a yoke that people carry around their necks. [Proponents of the disease model] say that this is important because this is how to prevent the stigmatization of addicts, which has been a standard part of our culture since Victorian times. 

But I think that’s just bullshit. I don’t think it feels good when someone tells you that you have a chronic disease that makes you do bad things. There are ways to reduce stigmatization by recognizing the humanity involved in addiction, the fact that it happens to many people and the fact that people really do try to get better — and most of them do. There are lots of ways to trigger a humanistic response besides calling something a disease.  

S: I agree that stigma is a huge problem with the treatment of drug addiction and mental health. Admitting you are an addict or depressed or know someone who suffers from these disorders is accompanied with unnecessary shame and fear of admission of the problem. I disagree that acknowledgement of medical/neurobiological basis of these disorders (ie calling them diseases) increases stigma but in fact do humanize patients. It helps alleviates shaming–both public and self–and can help an addict to seek evidence-based, medical treatment. Acknowledging the chronic nature of the disorder is not intended to make people feel bad but is merely truthfully stating the nature of the problem in hopes that it can be properly treated; denial can be lead to false and ineffective treatments.

Q: It can be difficult to comprehend the idea that something as severe as a heroin addiction is a developmental process. Can you explain that? 

L: First of all, let’s include the whole bouquet of addictions. So there’s substances — drugs and alcohol — and there’s gambling, sex, porn and some eating disorders. The main brain changes that we see in addiction are common to all of them, so they’re not specific to taking a drug like heroin, which creates a physical dependence. We see similar brain changes in a region called the striatum, which is an area that’s very central to addiction, which is involved in attraction and motivational drive. You see that with gambling as much as you do with cocaine or heroin. So that’s the first step of the argument — it’s not drugs, per se. 

From there, it’s important to recognize that certain drugs, like opiates, create physical dependency. There’s a double whammy there. They’re hard to get off because they’re addictive, like sex or porn is, but they also make you uncomfortable when you stop taking them. People try to go off of them and get extremely uncomfortable and then they’re drawn back to it — now for physical as well as psychological reasons. 

S: It is true that all addictions involve the striatum and there are similarities between the different addictions but to say that ALL addictions affect the brain in the exact same way is an absurd simplification. Different drugs absolutely DO affect the brain differently and have differences in addiction potential and relapse potential. To say addiction to heroin is identical to addiction to alcohol is identical to gambling addiction and therefore has nothing to do with the specific drug or behavior is just plain wrong. A wealth of evidence is gathering that addictions to different drugs progress differently and effect different brain systems, despite certain changes common to all [9]. For example, even opioids such as morphine and oxycodone, whose pharmacology are probably the best understood of any drug of abuse (they interact with mu opioid receptors [10]), have different behavioral and neurobiological effects that may affect addictions to the individual drugs (see my blog post). In a paper published by the lab I work for, the Kreek lab, cocaine administration in drug naïve mice (mice that have never had cocaine in their system) results in a rapid release of dopamine [11]. In contrast, some studies show that self-administration of an opioid drug only increases dopamine in rats that have already been exposed to the drug and not naïve animals [10]. The differences in the dopamine profiles between cocaine and opioids obviously means that how these two drugs affect the brain is different and is drug-specific! These are just a few small examples demonstrating the scientific inaccuracy of lumping all addictions into one general category or making the false claim that addiction has “nothing to do with the drug” (just as reducing cancer to a single disease is entirely inaccurate and harmful for its treatment).

Q: In the case of any type of addiction, what’s going on in the brain? 

L: The main region of interest is the striatum, and the nucleus accumbens, which is a part of the striatum. That region is responsible for goal pursuit, and it’s been around since before mammals. When we are attracted to goals, that region becomes activated by cues that tell you that the goal is available, in response to a stimulus. So you feel attraction, excitement and anticipation in response to this stimulus, and then you keep going after it. The more you go after that stimulus, the more you activate the system and the more you build and then refine synaptic pathways within the system. 

The other part of the brain here that’s very important is the prefrontal cortex, which is involved in conscious, deliberate control — reflection, judgment and decision-making. Usually there’s a balance between the prefrontal cortex and the striatum, so that you don’t get carried away by your impulses. With all kinds of addictions — drugs, behavior, people — the prefrontal system becomes less involved in the behavior because the behavior is repeated so many times. It becomes automatic, like riding a bike. 

S: Dr. Lewis’s assessment is basically correct. The core of the reward circuit involves dopamine-releasing neurons of the ventral tegmental area (VTA) projecting to the nucleus accumbens (NAc; a part of the ventral striatum), which primarily drives motivated behavior and is involved in reinforcement of drug taking behavior. Conversely, the prefrontal cortex acts as a “stop” against this system and one model of addiction is the motivated-drive to seek the drug overpowers the “stop” signal from the prefrontal cortex. However, addiction is far more complex beyond just this basic system. Numerous other circuits and systems (hippocampus, amygdala, hypothalamus, just to name a few) are also involved and each individual drug or rewarding stimuli can affect these circuits in disparate ways [12].

Q: What would a scientifically informed approach to addiction look like? 

L: That’s a really hard question because the fact that we know what’s happening in the brain doesn’t mean that we know what to do about it. 

A lot of recent voices have emphasized that addiction tends to be a social problem. Often addicts are isolated; they very often have difficult backgrounds in terms of childhood trauma, stress, abuse or neglect — so they’re struggling with some degree of depression or anxiety — and then they are socially isolated, they don’t know how to make friends and they don’t know how to feel good without their addiction. 

S: As I’ve stated above, a scientifically informed approach to addiction treatment already exists but is not widely used. However, one day an addict will hopefully be able to consult with a medical doctor to receive appropriate medications specific to their addiction, which will be combined with individual counseling by a psychiatrist or psychologist and a specific cognitive behavioral therapy or other psychological/behavioral therapy. The combination of medications and psychological therapy administered by trained medical professionals will be the future of evidence-based addiction medicine. Development of additional medications and/or psychological therapies for future treatment absolutely requires solid scientific evidence supporting their efficacy, which includes use of randomized control trials,  prior to widespread implementation.

But to call addiction primarily a social problem once again ignores all the basic neuroscience research that shows the powerful effects drugs have on the brain. It also ignores the prominent effect of genetics and how, due to a random role of the dice, an individual’s risk of becoming an addict can drastically increase [2, 13]. Plus the opioid epidemic that is currently sweeping the nation effects nearly every strata of society regardless of socioeconomic status, age, gender or race, and therefore cannot be explained simply by the hypothesis that addicts are people that are socially isolated. Why someone starts using drugs in the first place and how exactly they progress from a casual drug user to an addict are incredibly complex questions that scientists all over the world are attempting to answer through rigorous research. Being socially isolated or experiencing childhood trauma may certainly be factors that eschew some people towards the development of addiction but are definitely not the only ones.

Q: So what can we do about that?

L: Other than certain drugs that can reduce withdrawal symptoms, there’s nothing much medicine can offer, so we have to turn to psychology, and psychology actually offers a fair bit. There’s cognitive behavioral therapy, motivational interviewing, dialectic behavioral therapy, and now there are mindfulness-based approaches, which I think are really exciting. 

There’s been good research from Sarah Bowen in Seattle [on Mindfulness-Based Relapse Prevention] showing that mindfulness practices can have a significant impact on people, even on people who are deeply addicted to opiates. 

S: This is a completely false statement: medications for treatment of addictions exist [14]! Once again, comprehensive systematic reviews of methadone and buprenorphine, two medications used for treatment of opioid cravings, have indisputably shown that these medications are effective at keeping addicts off of heroin compared to no medication [5, 6]. Furthermore, a number of other drugs are currently being explored for treatments to alcohol and cocaine addiction [15, 16]. Some people may consider methadone or buprenorphine replacing “one drug with another” but this is naïve view of how powerfully addictive opioid drugs can be and how use of these FDA-approved medications in combination with individual psychological counseling, can lead to gradual dose reduction and amelioration of cravings. Medication-assisted addiction treatment is designed to help addicts fight their craving so that they can live a normal life. With time, dose can be reduced and cravings can become less intense.

The study Dr. Lewis cites regarding mindfulness is well designed and intriguing. However, the study did not compare mindfulness-based approaches to medication-based approaches and is therefore incomplete [17]. Nevertheless, it is an interesting approach that may be able to be combined with medication-based treatment but definitely requires more research before its efficacy can be confirmed.

References

  1. Koob GF, Le Moal M. Addiction and the brain antireward system. Annual review of psychology. 2008;59:29-53.
  1. Kreek MJ, et al. Opiate addiction and cocaine addiction: underlying molecular neurobiology and genetics. The Journal of clinical investigation. 2012;122(10):3387-93.
  1. Kelley AE. Memory and addiction: shared neural circuitry and molecular mechanisms. Neuron. 2004;44(1):161-79.
  1. Tronson NC, Taylor JR. Addiction: a drug-induced disorder of memory reconsolidation. Current opinion in neurobiology. 2013;23(4):573-80.
  1. Mattick RP, et al. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. The Cochrane database of systematic reviews. 2009(3):CD002209.
  1. Mattick RP, et al. Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. The Cochrane database of systematic reviews. 2014;2:CD002207.
  1. Anderson P, et al. Effectiveness and cost-effectiveness of policies and programmes to reduce the harm caused by alcohol. Lancet. 2009;373(9682):2234-46.
  1. Hartung DM, et al. Extended-release naltrexone for alcohol and opioid dependence: a meta-analysis of healthcare utilization studies. Journal of substance abuse treatment. 2014;47(2):113-21.
  1. Badiani A, et al. Opiate versus psychostimulant addiction: the differences do matter. Nature reviews Neuroscience. 2011;12(11):685-700.
  1. Fields HL, Margolis EB. Understanding opioid reward. Trends in neurosciences. 2015;38(4):217-25.
  1. Zhang Y, et al. Effect of acute binge cocaine on levels of extracellular dopamine in the caudate putamen and nucleus accumbens in male C57BL/6J and 129/J mice. Brain research. 2001;923(1-2):172-7.
  1. Russo SJ, Nestler EJ. The brain reward circuitry in mood disorders. Nature reviews Neuroscience. 2013;14(9):609-25.
  1. Kreek MJ, et al. Genetic influences on impulsivity, risk taking, stress responsivity and vulnerability to drug abuse and addiction. Nature neuroscience. 2005;8(11):1450-7.
  1. Kreek MJ, et al. Pharmacotherapy of addictions. Nature reviews Drug discovery. 2002;1(9):710-26.
  1. Addolorato G, et al. Novel therapeutic strategies for alcohol and drug addiction: focus on GABA, ion channels and transcranial magnetic stimulation. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. 2012;37(1):163-77.
  1. Bidlack JM. Mixed kappa/mu partial opioid agonists as potential treatments for cocaine dependence. Advances in pharmacology. 2014;69:387-418.
  1. Bowen S, et al. Relative efficacy of mindfulness-based relapse prevention, standard relapse prevention, and treatment as usual for substance use disorders: a randomized clinical trial. JAMA psychiatry. 2014;71(5):547-56.

Personality-targeted Interventions Can Reduce Alcohol and Marijuana Use Among Adolescents

Cover-Photo-for-Conrod-post

Let me state the obvious: alcohol and marijuana are the two most widely used drugs of abuse in the United States. According to the annual National Survey on Drug Use and Health (NSDUH), (the most comprehensive survey of drug use and abuse in the United States conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA)) as of 2013, 86.8% of the population aged 18 or older have reported having consumed alcohol during their lifetime with over 16.6 million adults diagnosed with alcohol abuse disorder.

Of course, we all know the prevalence and extent of underage drinking, and the damage alcohol has on the developing brain has been heavily researched, not to mention all the significant secondary problems associated with alcohol abuse (car crashes, sexual assault on college campuses, falling off of balconies… ).

But here’s some numbers anyways: as of 2013, 8.7 million youths aged 12-20 reported past month alcohol use, a shockingly high number for an age group this is not legally allowed to drink alcohol…

Similarly, marijuana, which is still illegal in the vast majority of the US, is nearly as ubiquitous. According to the NSDUH 2013 survey, 19.8 million adults aged 18 or older reported past month marijuana use.

And with marijuana legalization in Colorado and Washington, a significant concern raised by many is that abuse of the drug among youths will dramatically increase even higher than it is now. The research supporting the damage marijuana can inflict on brain development is also significant.

But what if the risk of use of alcohol and marijuana by youths could be reduced? What if a teacher could be given the tools to not only identify certain risky personality traits in their students but also use that knowledge to help those at-risk students from trying and using drugs such as alcohol and marijuana? A series of studies coming out of the laboratory of Dr. Patricia A Conrod of King’s College London report having done exactly that.

SFN 2015 LogoI had the pleasure of seeing Dr. Conrod speak at the recent Society for Neuroscience Conference as part of a satellite meeting jointly organized by the National Institute on Drug Abuse (NIDA) and National Institute on Alcohol Abuse and Alcoholism (NIAAA). Dr. Conrod presented a compelling story spanning over a decade of her and her colleague’s work, in which certain personality traits amongst high risk youths, can actually be used to predict drug abuse amongst those kids. Dr. Conrod argues that by identifying different risk factors in different adolescents, a specific behavioral intervention can be designed to help reduce alcohol drinking and marijuana use in these youths. And who is best to administer such an intervention? Teachers and counselors, of course: educators that spend a great deal of time interacting with students and are in the best position to help them.

The Teacher-Delivered Personality Targeted Interventions For Substance Misuse Trial, also known as the Adventure Trial, was conducted in London during 2008-2009 and the results were first published in 2010.

This ambitious study recruited 2,643 students (between 13 and 14 years old) from 21 secondary schools in London (20 of the 21 schools were state-funded schools). Importantly, this study was a cluster-randomized control trial, which means the schools were randomly assigned to two groups: one group received the intervention while the other did not. The researchers identified four personality traits in high-risk (HR) youths that increase the risk of engaging in substance abuse. The four traits are:

  1. Anxiety sensitivity,
  2. Hopelessness
  3. Impulsivity
  4. Sensation seeking.

A specific intervention based on cognitive behavioral therapy (CBT) and motivational enhancement therapy (MET) was developed to target each of these personality traits. Teacher, mentors, counselors, and educational specialists in each school that were recruited for the study were trained in the specific interventions. In general, CBT is an approach used in psychotherapy to change negative or harmful thoughts or the patient’s relationship to these thoughts, which in turn can change the patient’s behavior. CBT has been effective in a treating a number of mental disorders such anxiety, personality disorders, and depression. MET is an approach used to augment a patient’s motivation in achieving a goal and has mostly been employed in treating alcohol abuse.

The CBT and MET interventions in this study were designed to target one of the four personality traits (for example, anxiety reduction) and were administered in two 90-minute group sessions. The specific lesson plans for these interventions were not reported in the studies but included workbooks and such activities as goal-setting exercises and CBT therapies to help students to dissect their own personal experiences through identifying and dealing with negative/harmful thoughts and how those thoughts can result in negative behaviors. Interestingly, alcohol and drug use were only a minor focus of the interventions.

The success of the interventions was determined through self-reporting. The student’s completed the Reckless Behavior Questionnaire (RBQ), which is based on a six-point scale (“never” to “daily or almost daily”) to report substance use. Obviously due to the sensitive nature of these questionnaires and need for honesty by the students, measures were taken to ensure accuracy in the self-reporting, such as strong emphasis on the anonymity and confidentiality of the reports and inclusion of several “sham” items designed to gauge accuracy of reporting over time. Surveys were completed every 6-months for 24-months (two years) which is a sufficient time frame to assess the effect of the interventions.

Most importantly, schools were blinded to which group they were placed in and teachers and students not involved in the study were not aware of the trial occurring at the school. The students involved were unaware of the real purpose and scope of the study. These factors are important to consider because it held eliminate secondary effects and helps support the direct efficacy of the interventions themselves.

The results were impressive: reduced frequency and quantity of drinking occurred in the high-risk students that received the intervention compared to the control students that did not. While HR students were overall more likely to report drinking than low-risk (LR) students, the HR students saw a significant effect of the personality-targeted interventions on drinking behavior.

Conrod et al.2013 abstract

A study of this size is incredibly complex and the statistics involved are equally complex. The author’s analyzed the data in a number of ways and published the results in several papers. A recent study modeled the data over time (the 24-months in which the surveys were collected) and used these models to predict the odds that the students would engage in risky drinking behavior. The authors reported a 29% reduction in odds of frequency of drinking by HR students receiving the interventions and a 43% reduction in odds of binge drinking  when compared to HR students not receiving the interventions.

Interestingly, the authors report a mild herd-effect in the LR students. Meaning that they believe the intervention slowed the onset of drinking in the LR students possibly due to the interactions between the HR student’s receiving the interventions and LR students. However, additional studies will need to be done in order to confirm this result.

Recall that the Reckless Behavior Questionnaire (RBQ) was utilized in this study to quantify drug-taking behavior. While the study was specifically designed to measure effects on alcohol, the RBQ also included questions about marijuana. So the authors reanalyzed their data and specifically looked at effects of the interventions on marijuana use.

Mahu et al. 2015

The found that the sensation seeking personality sub-type of HR students that received an intervention had a 75% reduction in marijuana use compared to the sensation seeking HR students that did not receive the intervention. However, unlike the findings found on alcohol use, the study was not able to detect any effect on marijuana use for the HR students in general. Nevertheless, the data suggest that the teacher/counselor administered interventions are effective at reduce marijuana use as well.

While you may be unconvinced by the modest reduction in drinking and marijuana frequency reported in these studies and may be skeptical of the long-term effect on drug use in these kids, keep in mind that the teachers and counselors that administered these interventions received only 2 or 3 days of training and the interventions themselves were very brief, only two 90-minute sessions. What I find remarkable is that such a brief, targeted program can have ANY effects at all. And most importantly, the effects well outlasted the course of the interventions for the full two-years of the follow-up interviews.

These targeted interventions have four main advantages:

  1. Administered in a real-world setting by teachers and counselors
  2. Brief (only two 90-minute group sessions)
  3. Cheap (the cost of training and materials for the group sessions)
  4. Effective!

The scope of this intervention needs to be tested on a much larger cohort of students in a larger variety of neighborhoods but it is extremely promising nonetheless. Also, it would be interesting to breakdown these data by race, socioeconomic status, and gender, all of which may impact the effectiveness of the treatments and was not considered in this analysis. Finally, how would you implement these interventions on a wide scale? I eagerly look forward to additional work on these topics.

Thanks for reading 🙂

See these other articles in Time and on King’s College for less detailed discussions of these studies.

Also see these related studies from Conrod’s group:

Castellanos-Ryan N, Conrod PJ, Vester JBK, Strain E,, Galanter M, Conrod PJ. Personality and substance misuse: evidence for a four-factor model of vulnerability. In: Vester JBK, Strain E, Galanter M, Conrod PJ, eds. Drug Abuse and Addiction in Medical Illness. Vols 1 and 2. New York, NY: Humana/Spring Press; 2012.

Conrod PJ, Pihl RO, Stewart SH, Dongier M. Validation of a system of classifying female substance abusers on the basis of personality and motivational risk factors for substance abuse. Psychol Addict Behav. 2000;14(3):243-256.

Conrod PJ, Stewart SH, Comeau N, Maclean AM. Efficacy of cognitive behavioral interventions targeting personality risk factors for youth alcohol misuse. J Clin Child Adolesc Psychol. 2006;35(4):550-563.

Conrod PJ, Castellanos-Ryan N, Strang J. Brief, personality-targeted coping skills interventions and survival as a non-drug user over a 2-year period during adolescence. Arch Gen Psychiatry. 2010;67(1):85-93.

O’Leary-Barrett M, Mackie CJ, Castellanos-Ryan N, Al-Khudhairy N, Conrod PJ. Personality-targeted interventions delay uptake of drinking and decrease risk of alcohol-related problems when delivered by teachers. J AmAcad Child Adol Psychiatry. 2010;49(9):954-963.

Important Considerations in Optogenetics Behavioral Experiments

Image credit NSF, Inbal Goshen, Karl Deisseroth.
Image credit NSF, Inbal Goshen, Karl Deisseroth.

The third and final part of my three part guest blog series on Optogenetics has been published on the Addgene blog. Addgene is a nonprofit organization dedicated to making it easier for scientists to share plasmids and I’m thrilled to be able to contribute to their blog! This post covers the running behavioral experiments utilizing optogenetics.

Check it out!

http://blog.addgene.org/important-consideration-in-optogenetics-behavioral-experiments

 

The Materials Science of Optogenetics Experiments

(blog.addgene.org)
(blog.addgene.org)

The second part of my three part guest blog series on Optogenetics has been published on the Addgene blog. Addgene is a nonprofit organization dedicated to making it easier for scientists to share plasmids and I’m thrilled to be able to contribute to their blog! This post covers the material science aspects of running optogenetic experiments.

Check it out!

http://blog.addgene.org/the-materials-science-of-optogenetics-experiments

Optogenetics on the Addgene Blog: Part 1

(blog.addgene.org)
(blog.addgene.org)

The first part of my three part guest blog series on Optogenetics has been published on the Addgene blog. Addgene is a nonprofit organization dedicated to making it easier for scientists to share plasmids and I’m thrilled to be able to contribute to their blog!

Check it out!

http://blog.addgene.org/a-primer-on-optogenetics-introduction-and-opsin-delivery

The Genetic Link Between Creativity and Psychiatric Disease

(www.wikipedia.org)
(www.wikipedia.org)

The biological sciences are in a golden era: the number of advanced technological tools available coupled with innovations in experimental design has led to an unprecedented and accelerating surge in knowledge (at least as far as the number of papers published is concerned). For the first time in history, we are beginning to ask questions in biology that were previously unanswerable.

No field demonstrates this better than genetics, the study of DNA and our genes. With the advent of high-throughput DNA sequencing, genetic information can be acquired literally from thousands of individuals and even more remarkably, can be analyzed in a meaningful way. Genomics, or the study of the complete set of an organism’s DNA or its genome, directly applies these advances to probe answers to questions that are literally thousands of years old.

A recent study, a collaborative effort from scientists in Iceland, the Netherlands, Sweden, the UK, and the US, is an example of power of genomics and to answer these elusive questions.

Power eet al. Nat. Neursci. 2015. Title

The scientists posed an intriguing question: if you are at risk for a psychiatric disorder, are you more likely to be creative? Is there a link between madness and creativity?

Self-portrait with bandaged ear. Vincent van Gogh, 1889. (wikipedia.org)
Self-portrait with bandaged ear. Vincent van Gogh, 1889. (wikipedia.org)

Aristotle himself once said, “no great genius was without a mixture of insanity” and indeed, the “mad genius” archetype has long pervaded our collective consciousness. But Vincent Van Gogh cutting off his own ear or Beethoven’s erratic fits of rage are compelling stories but can hardly be considered empirical, scientific evidence.

But numerous studies have provided some evidence that suggests a correlation between psychiatric disorders and creativity but never before has an analysis of this magnitude been performed.

Genome-wide association studies (GWAS) take advantage of not only the plethora of human DNA sequencing data but also the computational power to compare it all. Quite literally, the DNA of thousands of individuals is lined up and, using advance computer algorithms, is compared. This comparison helps to reveal if specific changes in DNA, or genetic variants, are more common in individuals with a certain trait. This analysis is especially useful in identifying genetic variants that may be responsible for highly complex diseases that may not be caused by only a single gene or single genetic variant, but are polygenic, or caused by many different genetic variants. Psychiatric diseases are polygenic, thus GWAS is useful in revealing important genetic information about them.

This video features Francis Collins, the former head of the Human Genome Project and current director of the National Institutes of Health (NIH), explaining GWAS studies. The video is 5 years old but the concept is still the same (there’s not many GWAS videos meant for a lay audience).

The authors used data from two huge analyses that previously performed GWAS on individuals with either bipolar disorder or schizophrenia compared to normal controls. Using these prior studies, the author’s generated a polygenic risk score for bipolar disorder and for schizophrenia. This means that based on these enormous data sets, they were able to identify genetic variants that would predict if a normal individual is more likely to develop bipolar disorder or schizophrenia. The author’s then tested their polygenic risk scores on 86,292 individuals from the general population of Iceland and success! The polygenic risk scores did associate with the occurrence of bipolar disorder or schizophrenia.

Next, the scientists tested for an association between the polygenic risk scores and creativity. Of course, creativity is a difficult thing to define scientifically. The authors explain, “a creative person is most often considered one who take novel approaches requiring cognitive processes that are different from prevailing modes of thought.” Translation: they define creativity as someone who often thinks outside the box.

In order to measure creativity, the authors defined creative individuals as “belonging to the national artistic societies of actors, dancers, musicians, and visual artists, and writers.”

The scientists found that the polygenic risk scores for bipolar disorder and schizophrenia each separately associated with creativity while five other types of professions were not associated with the risk scores. An individual at risk for bipolar disorder or schizophrenia is more likely to be in creative profession than someone in a non-creative profession.

 The authors then compared a number of other analyses to see if this effect was due to other factors such as number of years in school or having a university degree but this did not alter the associations with being in a creative field.

Finally, the same type of analysis was done with two other data sets: 18,452 individuals from the Netherlands and 8,893 individuals from Sweden. Creativity was assessed slightly differently. Once again creative profession was used but also data from a Creative Achievement Questionnaire (CAQ), which reported achievements in the creative fields described above, was available for a subset of the individuals.

Once again, the polygenic risk scores associated with being in a creative profession to a similar degree as the Icelandic data set; a similar association was found with the CAQ score.

The authors conclude that the risk for a psychiatric disorder is associated with creativity, which provides concrete scientific evidence for Aristotle’s observation all those years ago.

However, future analyses will have to broaden the definition of creativity beyond just narrowly defined “creative” professions. For example, the design of scientific experiments involves a great deal of creativity but is not considered a creative profession and is therefore not included in these analyses, and a similar argument could be made with other professions. Also, no information about which genetic variants are involved or what their function is was discussed.

Nevertheless, this exciting data is an example of the power that huge genomic data sets can have in answering fascinating questions about the genetic basis of human behavior and complex traits.

For further discussion, read the News and Views article, a scientific discussion of the paper, which talks about potential evolutionary mechanisms to explain these associations.

Methadone Maintenance Therapy Works-End of Story

helping hands (pixbay.com)

I hate to be condescending but how the scientific community perceives a phenomena and how the public at large perceive the exact same thing can be starkly different.

For example, there is still a debate over the scientific legitimacy of global warming and climate change. Of course, this flies in the face of reality. In the scientific community, there is no more doubt over climate change than there is over heliocentricity (the theory that states the Earth revolves around the Sun). Study after study comes to the came conclusion, the scientific evidence is overwhelmingly in favor. But I’m not writing to debate climate change.

The same type of dichotomy exists for replacement/maintenance therapies for addiction. Methadone and the related compound buprenorphine (Suboxone, one of its formulations) are still considered controversial or ineffective or “replacing one drug for another.”

(wikipedia.com)
Methadone pills. (wikipedia.com)

In brief, methadone is a compound that acts on the same target as heroin (the mu opioid receptor) but unlike heroin, it acts for a very long time (24hrs). Dr. Vincent Dole, a doctor at the Rockefeller University in New York, and his colleague, Dr. Marie Nyswander, had the brilliant idea of using this very long-acting opioid compound as a way of treating heroin addiction. Indeed, methadone has the advantage of not producing the intense, pleasurable high that heroin produces but is still effective at curbing cravings for heroin and eliminating withdrawal symptoms. Dole and Nyswander published their first study in 1967 and methadone has been an approved—and effective—treatment for heroin addiction worldwide ever since.

However, controversy over the use of methadone exists. Even the opening of a methadone clinic can incite protests. The persistence of negative attitudes towards methadone and the stigma against treating addiction as a medical disease has prevented addicts from receiving proven medical treatments that are effective at curbing cravings and actually keeping them off of heroin and in treatment programs.

So just for a moment, let’s suspend our preconceived notions about what methadone is or how it works and let’s just ask our selves two simple questions:

 Does methadone work?

Does methadone keep addicts off of heroin and in treatment?

The answer is a resounding YES!

 

Mattick JP et al. Methaodone. 2009 title

Many controlled, clinical studies have examined the effectiveness of methadone. But a comprehensive comparison of methadone versus control, non-medication based treatments has not been considered amongst the various studies.

Researchers at the Cochrane Library performed this type of comprehensive analysis. Data was considered from 14 unique, previous clinical studies conducted over the past 40 years. Researchers compared methadone treatment versus control, non-medication based treatment approaches (placebo medication, withdrawal or detoxification, drug-free rehabilitation clinics, no treatment, or waitlist).

11 studies and 1,969 subjects were included in their final analysis.

 Read the full paper, published in 2009, here.

The results were clear. Methadone was found to keep people off of heroin and in treatment more effectively than control treatments. Urine analysis confirmed methadone-treated addicts were more likely to be heroin-free and regularly seeking treatment.

Of course, as I stated above, this is nothing new. But it’s important to note that abstinence therapies or treatments that encourage addicts to go “cold turkey” don’t really work; inevitably, relapse will occur. A medical treatment exists to help addicts fight their cravings so their brains are not fixated on obtaining heroin and these people are able to regain normal daily functions. And in time, methadone doses can be tapered down as intensity and frequency of cravings decrease.

The debate now should not be on whether methadone works, but on how to use it effectively and how to expand its use so that as many people as possible can benefit from it.

Most importantly, methadone helps an addict to return to normal life. End of story.

Childhood Abuse Has Long-lasting Effects on Brain Function

(© Derek Simon 2015)
(© Derek Simon 2015)

 

Why is it that one person becomes an addict and another does not?

This is a central question in addiction field and one that I’ve touched on in some of my posts (and will continue to explore in the future). Two recent papers may help to shed more light on this difficult and complicated question. Both studies have revealed changes that occur in the brain as a result of childhood trauma that may cause an individual to be more susceptible to risky behavior such as drug abuse.

Both papers are neuroimaging studies meaning they use living human subjects and look at brain activity in response to different scenarios. There are many ways to image a living brain but these studies both use functional magnetic resonance imaging (fMRI). Basically, fMRI measures blood flow into the brain. As neurons turn “on” (that is, when they conduct an electrical signal), they require energy. Neurons use glucose as their primary energy source, which is delivered to them through blood flow. Therefore, the more blood flowing to a region of the brain = the more energy required by neurons = more neurons “firing”.

 The analysis of fMRI data is very complicated and beyond the scope of my knowledge or this discussion. But in essence, when you think or read about something, certain areas of your brain process that information. Using fMRI, you can actually visualize regions of the brain that are turning “on” or “off” when a patient thinks about a particular situation! Watch these YouTube videos for additional explanations on fMRI.

 

fMRI Image (wikipedia.org)
fMRI Image (wikipedia.org)

In both of the studies featured in today’s post, subjects would read different scripts while in the fMRI scanner and the scientists would image the entire brain and identify the regions that were active during the test. Then data from multiple subjects can be compiled and a composite image that represents the averages all the subjects can be produced. The picture to the right is an example of this type of composite image. Finally, you can see which regions of the brain are active for most of the patients during the different experiments. Keep this information in mind as I go over the papers.

Elsey et al. Neuropsychopharm. 2015

The first paper performed fMRI scans on adolescents that had or had not experienced maltreatment or trauma during childhood (less than 18 years old). 67 subjects were recruited from a larger study looking at disadvantaged youth and 64 were eventually used in the study. The adolescents filled out a standard survey that allowed the scientists to learn which of the subjects had experienced maltreatment/trauma during childhood.

The experiment involved having the different subjects read a script about either a stressful moment, their favorite food, or something neutral or relaxing while their brains were being imaged in the fMRI scanner.

Amazingly, for the stressful scenario, a difference in brain activity was detected in multiple regions of the prefrontal cortex only in subjects that had experienced childhood maltreatment! What this means is those youths that were abused as kids responded to stress differently than youths that were not abused. Their brain function has literally been changed later in life as a result of the abuse they suffered as children.

 The prefrontal cortex is a part of the mesocorticolimbic system, a group of brain areas especially involved in addiction. The prefrontal cortex is also involved in decision making, impulsivity, and other functions. It’s not clear what this change in prefrontal cortex activity actually means but it is possible that the altered activity could make the youth more vulnerable to stress or more likely to engage in risky activities, such as drug abuse.

 Elton et al. Addiction Biol. 2014

The second study was also interested in subjects that had experienced maltreatment or trauma during childhood but it instead of adolescents, this study used subjects that are adult men dependent on cocaine. Similarly, the subjects were grouped into those that had been mistreated as kids and those that had not.

In a parallel design to the other study, the subjects read a script describing a situation while being scanned in the fMRI machine. The scripts in this study included stress, cocaine-associated, and neutral. Interestingly, an increase in activity in a specific region of the prefrontal cortex and an area of the brain involved in motor activity were detected in the subjects that had been abused during childhood. And even more important, these changes were correlated to enhanced drug craving. These results suggest that childhood trauma can affect drug craving for addicts, which may be relevant factor in triggering relapse. That is to say, addicts that have been abused as children may be more vulnerable to not only acquiring addiction but also relapse.

 It is important to keep in mind that, like the previous study, the real functional importance of these different changes in unknown. However, clearly there are real changes that occur in the brain as a result of abuse/maltreatment during childhood. Imaging data must be taken with a grain of salt because it is difficult to show real causality. Yet, both studies (and many others) suggest long-lasting changes in brain activity, especially in response to stress, as a result of childhood trauma/maltreatment.

The conclusions we can draw from these studies is that childhood mistreatment, or trauma can have lasting changes on the brain. How these changes affect behavior is a much more difficult question to answer. Nevertheless, the changes that occur may be one of the factors that can contribute to susceptibility to addiction. These studies are supported by a previous post in which animal studies have shown that stress during early age leads to greater drug use as an adult.

And a broader point, these two neuroimaging studies help to put a different perspective on disadvantaged youth and importance of a stable home life, the lack of which can significantly affect you as an adult and may even contribute to susceptibility of become a drug addict.