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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The Consequences of Childhood Abuse Last Until Adulthood: What are the Implications for Society?

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

One of the great questions in the addiction field is why do some people become full-blown addicts while other people can use drugs occasionally without progressing to anything more serious? One part the answer definitely has to do with the drug itself. For example, heroin causes a more intensely pleasurable high than cocaine and people that try heroin are more likely to become addicted to it than cocaine. But that’s not the whole story.

I’ve written previously about how a negative, stressful environment can have long-lasting negative impacts on the development of a child’s brain (also known as early-life stress of ELS). ELS such as childhood abuse (physical or sexual) and neglect can increase the risk for a whole host of problems as an adult such as depression, bipolar disorder, PTSD, and of course drug and alcohol abuse. There’s even a risk for more physical ailments like obesity, migraines, cardiovascular disease, diabetes, and more.

Childhood abuse/neglect = psychological and physical problems as an adult.

Attitudes towards childhood development have certainly changed! Child coal miners ca. 1911 (wikipedia.org).
Attitudes towards childhood development have certainly changed! Child coal miners ca. 1911 (wikipedia.org).

This idea doesn’t sound too controversial but believe it or not, the idea that a bad or stressful situation as a child would do anything to you as an adult was laughed away as not possible. It’s only within the last decade or so that a wealth of research has supported this idea that ELS can physically change the brain and that these changes can last through the abused child’s entire life.

This recent review paper (published in the journal Neuron) is an excellent, albeit technical, summary of dozens research papers done on this subject and the underlying biology behind their findings.

Paradise lost childhood abuse review 2016 title

I especially love the quotes the author included at the beginning of the article:

Paradise lost childhood abuse review 2016 quotes

And even more recently, yet another research paper has come out that highlights how important childhood is for the development of the brain and how a stressful childhood environment can impact the function of a person as an adult.

Childhood abuse paper 2016

This most recent report, published in the journal Neuropscyhopharmacology concludes that early childhood abuse affects male and females differently. That is to say that the physical changes that occur in the brain are distinct for men and women who were abused as children.

Studies like this one are done by examining the brains of adults who were abused as kids and then comparing the activity or structure of different parts of the brain to the brains of adults who were not abused. The general technique of examining the structure or activity of the brain in a living human being is called neuroimaging and includes a range of techniques such as MRI, PET, fMRI, and others. (I’ve written about some of these techniques before. In fact, the development of better methods to image the brain is a huge are of research in the neuroscience field).

However, this study did not examine behavioral differences in the subjects, but as I said above, a great number of many other studies have looked at the psychological consequences of ELS. But this paper is really primarily interested in the gender differences in the brains of adults that have been abused as kids.

*Note: the following discussion is entirely my own and is not mentioned or alluded to by the author’s of this study at all.

This work—and the many studies that preceded it—has important implications because as a society, we have to realize that part of our personality/intelligence/character/etc. is determined by our genetics while the other part totally depends on the environment we are born into. I don’t want to extrapolate too much but the idea that childhood abuse can increase the risk of psychological problems as an adult also supports the broader notion that a great deal of a person’s success is determined by entirely random circumstances.

The_ACE_Pyramid
The Adverse Consequences Pyramid perfectly illustrates how ELS/abuse/neglect (the bottom of the pyramid) leads to much greater problems in later life. (wikimedia.org).

The science shows that a child born into a household rife with abuse will have more chance of suffering from a psychological problem (such as addiction) as an adult than someone who was born into a more stable life. The psychological problem could hurt that person’s ability to study in school or to hold down a job. And the tragic irony, of course, is that no child gets to choose the conditions under which they are born. A child, born completely without a choice of any kind over whether or not he or she will be abused, can still suffer the consequences of it (and blame for it) as an adult.

As a society, we often always blame a person’s failures as brought on by his or her own personal failings, but what if a person’s childhood plays an important role in why that person might have failed? How, as a society, do we incorporate this information into the idea of ourselves as having complete control over our minds and our destinies, when we very clearly do not? As an adult, how much of a person’s personality is really “their own problem” when research like this clearly show that ELS impacts a person well after the abuse has ended?

If the environment a child is born into has a tangible, physical effect on how the brain functions as an adult, than this problem is more than a social or an economic one: this is a matter of public health. Studies that support findings such as these provide empirical significance for public policy and public services for child care such as universal pre-K, increased availability of daycare, health insurance/medical access for children, increased and equitable funding for all public schools regardless of the economic situation of the district that school happens to be located in, etc.

One of our goals as a society (if indeed we believe ourselves to be a functioning society…the success of Donald Trump’s candidacy raises some serious doubts…but I digress) is the improvement of the lives of ALL of our citizens and securing the prosperity of the society for future generations. Reducing childhood poverty and abuse quite literally could help secure the future generations themselves and improve the ability of any child to grow up to become a successful and productive adult.

Public programs are essential because the unfortunate reality for many people born into poverty is that they must work all the time at low paying jobs in order to simply survive and may not be able to give their children all the advantages of a wealthier family. And this is where government and public policy step in, to correct the imbalances and unfairness inherent to the randomness of life and level the playing field for all peoples. Of course, the specific programs and policies to reduce childhood poverty and abuse would need to be evaluated empirically themselves to guarantee an important improvement in development of the brain and health of the child when he/she grows up.

And this is the real power of neuroscience and basic scientific research papers like this one. Research into how our brains operate in real-life situations reveal a side of our minds and our personalities that we never may have considered before and the huge implications this can have for society. The brain is a complex machine and just like other machines it can be broken.

Of course, we shouldn’t extrapolate too much and say that, for example, a drug addict who was abused as a child is not responsible for anything they’ve ever done in between. But is important to recognize all the mitigating factors at play in a person’s success and simply dismiss someone’s problems as “their own personal responsibility.” As a neuroscientist, I might argue that that phrase and the issues behind it are way more nuanced than the how certain politicians like to use it.

Special endnote Due to some recent shifts in my career, Dr. Simon Says Science will be expanding the content that I write about. Addiction and neuroscience will still be prominently featured but I plan to delve into a variety of other topics that I find interesting and sharing opinions that I think are important. I hope you will enjoy the changes! Thanks very much!

 

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.

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.

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.

The Formation of New Memories in the Human Brain

Image of the structure of the mouse Hippocampus (Image courtesy of www.gensat.org).
Image of the structure of the mouse Hippocampus (Image courtesy of http://www.gensat.org).

How are new memories created?

This is a fascinating question in neuroscience and at the very core of what makes us human. After all, our entire concept of ourselves is defined by our memories and without them, are we even ourselves? This is a pretty lofty philosophical discussion… but today we’re only interested in the neuroscience of memory.

In specific, what happens to individual neurons in the human brain when a new memory is created and recalled?

Researchers at the University of California-Los Angeles performed a study in humans that has shed some light on this important question. Published recently in the journal Neuron, the novelty of the study involved recording how many times a neuron would fire during a specially designed memory test. In other words, the scientists were able to monitor what happened to individual neurons in a human being as a new memory was being created!

Title Ison et al. 2015

This article is open access (able to downloaded and distributed for free). The article can be found here or download the pdf.

Before I go into what the researchers found, let’s see how it was done.

The subjects in the study were patients being treated for epilepsy. As part of their clinical diagnosis, they had been implanted with an electrode, a tool used to measure neuronal activity or in other words, the electrode measures how often a neuron fires. The fact these patients already had an electrode inserted into the brain for clinical reasons made it convenient for the researchers to conduct this study.

Left Temporal Lobe (www.wikipedia.org)
Left Temporal Lobe (www.wikipedia.org)

The brain region in which the electrode was implanted is called the medial temporal lobe (MTL). The image to the right is of the left human temporal lobe. The medial region of the temporal lobe is located more towards the center of the brain.

Human Hippocampus (www.wikipedia.org)
Human Hippocampus (www.wikipedia.org)

One specific region of the MTL, the hippocampus, is believed to be the primary brain region where memories are “stored”. Specifically, previous studies in animals and humans have suggested that the MTL and hippocampus are very important to encoding episodic memory. Episodic memory involves memories about specific events or places. In this study, the example of episodic memory being used is remembering seeing a person at a particular place. Another example: the game Simon™ can be considered a test of your brain’s ability to rapidly create and recall short-term episodic memories!

Simon game memory

*Note: Episodic memory is considered one of the main bifurcations of declarative memory, or memories that can be consciously recalled. The other type of declarative memory is semantic memory, which are memories of non-physical/tangible things, like facts.

To test the episodic memory of remembering a person at a particular place, images were presented to the patients while the neurons were being recorded. There were 5 different tasks (all completed within 25-30min). See Figure 1 below from the paper.

Figure 1: Experimental Design
Figure 1: Experimental Design

First, a pre-screening was done in which the patients was shown many random images of people and places. The activity of multiple neurons was recorded and the data was quickly analyzed then 3-8 pairs of images were compiled. In each pair, 1 image was “preferred” or “P” image, meaning the neurons being recorded fired when the “P” image was shown. The second image was “non-preferred” or “NP” image, meaning the neurons did not respond to it when it was shown.

The first task is the “Screening” test. Each “P” and “NP” image was shown individually and the neurons response to each was recorded. As you would expect, the neuron would fire heavily to the “P” image and not very much to the “NP” image.

The second task was the “learning task” in which a composite image of each of the “P” and “NP” image pairs was made. The person in the “P” image was digitally extracted and placed in front of the landmark in the “NP” image. After the composite images were shown, the individual images were shown again.

For example, in one image pair for one patient, the “P” image was a member of the patient’s family while the “NP” image was the Eiffel Tower (for this example, see Figure 2). The composite image in the “learning” task was the family member in front of the Eiffel Tower. Another example of a “P” image was Clint Eastwood and the “NP” image was the Hollywood sign. The composite image would therefore be Clint Eastwood in front of the Hollywood sign. (However, in some image pairs the “P” image was a place and “NP” image was a person).

The third task was “assessing learning”. The image of just the person in the composite image was shown and the patient had to pick out the correct landmark he/she was paired with. For example, the picture of the family member was shown and the patient would have to pick out the Eiffel Tower image.

The fourth task was the “recall” task. The landmark image was shown and the patient had to remember and say the person it was paired with. For example, the Eiffel Tower was shown and the patient had to say the family member’s name.

Finally, the fifth task was a “re-screening” in which each individual image was shown again so the neuron’s activity could be compared to the Task 1, pre-learning.

The activity of multiple neurons were recorded for each image for each of the tasks. The data was then analyzed in number of different ways and the activity of different neurons was reported.

And what was found?

Figure 2: Response of Neruons in the Hippocampus from One Patient
Figure 2: Response of Neurons in the Hippocampus from a Patient

Let’s go back to the family member/Eiffel tower example. The researchers were able to show that a neuron in the hippocampus responded heavily to the picture of the family member (“P” image) but not to the Eiffel Tower (“NP” image). After showing the composite image, the neuron now responded to the Eiffel Tower too in addition to the family member! (The neuron also fired a comparable amount to the individual family member image as the composite image).

As you can see in Figure 2, each little red or blue line indicates when a neuron fired. For example, in Task 1 you can clearly see more firing (more lines) to the “P” image than the “NP” image. You can see that after Task 2, the neuron responds to either the “P” or “NP” image (especially obvious in the Task 5). The middle graph indicates the firing rate of the neurons to the “NP” image and it clearly shows increased firing rate of the neuron after learning (AL) compared to before learning (BL). It may look small, but the scientists calculated a 230% increase in firing rate of the neuron to “NP” image after the learning/memory task took place!

What does this mean? It means that a new episodic memory has been created and a single neuron is now firing in a new pattern in order to help encode the new memory!

This was confirmed the other way around too. In another patient, the “P” neuron was the White House and the “NP” image was beach volleyball player Kerry Walsh. The neuron that was being recorded fired a lot when the image of the White House was shown but not so much for the Kerri Walsh image. Then the composite image was shown and the learning/recall tasks were performed. The neuron was shown to fire to both the White House image AND the Kerry Walsh image! The neuron was responding to the new association memory that was created!

Keep in mind these are just two examples. The scientists actually recorded from ~600 neurons in several different brain regions besides the hippocampus but they only used about 50 of them that responded to visual presentation of the “P” image, either a person or a landmark (the identification of visually responsive neurons was crucial part of the experiment). Remarkably, when the firing rates of all these neurons was averaged before and after the memory/learning tasks, a similar finding to the above examples was found: the neuron now responded to the “NP” image after the composite was shown!

Many other statistical analyses of the data was done to prove this was not just a fluke of one or two neurons but was consistent observation amongst all the neurons studied but I won’t go into those details now.

But what’s going on here? Are the neurons that respond to the “P” stimulus now directly responding to the “NP” image or is more indirect, some other neuron is responding to the “NP” which in turn signals to the “P” neuron to increase in firing? The authors performed some interesting analyses that both of these mechanisms may apply but for different neurons.

Finally, were all the recorded neurons that were engaged in encoding the new episodic memory located in the hippocampus? The answer is no. Responsive neurons were identified in several brain regions besides the hippocampus including the entorhinal cortex and the amygdala. But most of the responsive cells were located within the parahippocampal cortex, a region of the cortex that surrounds the hippocampus, thus not surprising it is very involved in encoding a new memory.

In conclusion, the scientists were able to observe for the first time the creation of a new memory in the human brain at the level of a single neuron. This is an important development but such a detailed analysis has never before been done in humans and, most importantly, in real time. Meaning, the experiment was able to observe the actual inception of a new memory at the neuronal level.

However, one major limitation is that the activity of these neurons were not studied in the long term so it’s unknown if the rapid change in activity is a short-term response to the association of the two images or if it really represents a long-term memory. The authors acknowledge this limitation but the problem is really in the difficulty of doing such studies in humans. It’s not really ethical to leave an electrode in someone’s brain just so that you can test them every week!

But what does all of this mean? The authors do suggest that the work may help to resolve a debate that has been going in on the psychology field since the 40s. Do associations form gradually or rapidly? These results strongly suggest new neurons rapidly respond to encode the new memory formation.

But how will these results shape the neuroscience of memory? The answer is I don’t know and no one does. Thus is the rich tapestry of neuroscience, another thread weaved by the continuing work of scientists all over the world  in order to understand what it is that makes us human: our brains.

Morphine and Oxycodone Affect the Brain Differently

(Neurons. Image from Ana Milosevic, Rockefeller University)
(Neurons. Image from Ana Milosevic, Rockefeller University)

Why are some drugs of abuse more addictive than others?

 This is a central question to the addiction field yet it remains largely a mystery. All drugs of abuse have a similar effect on the brain: they all result in increased amounts of the neurotransmitter dopamine (DA) in an important brain region called the mesolimbic pathway (also known as the reward pathway). One of the core components of this pathway is the ventral tegmental area (VTA), which contains many neurons that make and release DA. VTA neurons communicate with neurons in the nucleus accumbens (NAc). This means that the axons of VTA neurons project to and synapse on NAc neurons. When VTA neurons are stimulated, they release DA onto the NAc, and this is a core component of how the brain perceives that something is pleasurable or “feels good.” Many types of pleasurable stimuli (food, sex, drugs, etc.) cause DA to be released from the VTA onto the NAc (See the yellow box in the diagram below). In fact, all drugs of abuse cause this release of DA from VTA neurons onto NAc neurons.

*Important note: many other brain regions are involved in how the brain perceives the pleasurable feelings of drugs besides the VTA and NAc, but these regions represent the core of the pathway.

"Dopamineseratonin". Licensed under Public Domain via Wikipedia.
“Dopamineseratonin”. Licensed under Public Domain via Wikipedia.

Check out these videos for a more detailed discussion of the mesolimbic pathway.

But if all drugs of abuse cause DA release, then why do different drugs make you feel differently? This is a very complicated question but one component of the answer is that different drugs have different mechanisms and dynamics of DA release.

For the opioid drugs like heroin, morphine, and oxycodone, they are able to bind to a special molecule called the Mu Opioid Receptor (MOPR). This action on the MOPR results in an indirect activation of DA neurons in the VTA and a release of DA in the NAc. While all opioid drugs reduce the feeling of pain and induce a pleasurable feeling, they have slightly different properties at the MOPR.

The different properties of the opioids may be a reason why some are more abused than others. For example, a number of studies have suggested that oxycodone may have greater abuse potential than morphine. This means that oxycodone is more likely to be abused morphine.

But do the different properties of morphine and oxycodone on the MOPR affect DA release and is this important to why oxycodone is more likely to be abused than morphine?

Vander Weele et al. 2015 titleThis is the question that scientists at the University of Michigan sought to address. Using several different sophisticated techniques, the scientists looked at differences in DA release in the NAc caused by morphine and oxycodone, two common opioid drugs.

Rats were injected with either morphine or oxycodone and then DA release was measured using either fast-scan cyclic voltammetry or microdialysis. I’ve discussed microdialysis in a previous post but in brief, it involves drawing fluid from a particular brain region at different time points in an experiment and then measuring the neurotransmitters present (using advanced chemistry tools that I won’t explain here).

Voltammetry is a more technically complicated technique. In brief, it uses electrodes to measure sensitive voltage changes. Since a molecule has specific electrochemical properties, these voltage changes can be related back to a specific molecule, such as the neurotransmitter DA as in this study. Voltammetry may even allow greater temporal resolution (easier to detect very precise changes at very short time frames, like seconds), which may make it more accurate than microdialysis (which can only measure neurotransmitter release on the scale of minutes).

Because each technology has its own limitations and potential problems, the authors used both of these techniques to show that they are observing the same changes regardless of the technology being used. Showing the same observation multiple times but in different ways is a common practice in scientific papers: it increases your confidence that your experiment is actually working and what you are observing is real and not just some random fluke.

The authors administered a single dose of either morphine or oxycodone to rats and then measured the DA release in the NAc as described above. What they found were very different patterns!

Morphine resulted in a rapid increase in DA (less than 30 seconds) but by 60 seconds had returned to normal. In contrast, oxycodone took longer to rise (about 20-30 sec before a significant increase was detected) but remained high for the entire 2 minutes that it was measured. The difference in DA release caused by morphine and oxycodone is striking!

Many other changes were observed such as differences in DA release in different sub-regions of the NAc, different effects on phasic release of DA (DA is often released in bursts), and differences in the other neurotransmitters such as GABA (morphine caused an increase in GABA release too while oxycodone did not). I won’t discuss these details here but check out the paper for more details.

Of course, do these differences in DA release explain why oxycodone is more often abused than morphine? Unfortunately no, there are many other factors (for example, oxycodone is more widely available than morphine) to consider. Nevertheless, this is some intriguing neuroscientific evidence that adds one more piece to the addiction puzzle.

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.

New Study-Treatment of Opioid Addicts in Prison and Effect on Relapse After Release

JD Lee et al. 2015. Title

There are many stigmas about addiction that are prevalent in society but the underlying cause of them all is that addiction is moral failing, even though we know addiction is a biological disease of the brain (with behavioral symptoms). In addition to being scientifically unfounded, stigmas about addiction can actually affect policy and public health decisions that have a real impact on people’s lives. In the perfect world, every decision we made would be based on concrete evidence and controlled, experimental studies. Unfortunately, this seems to be the exact opposite case for our attitudes as a society and our public policy towards drugs—ignorance, assumptions, and misconceptions seem to dominate. Nevertheless, as scientists, all we can do is the best work we can, explain and communicate the science to as many people as possible, and help to promote and support the work of others. Which brings me to today’s paper: a small pilot study that may have a wide impact on the treatment of addicts in the criminal justice system.

The paper, released in the journal Addiction, looks at how treatment for opioid addiction while in prison can affect the rate of relapse to opioid abuse once inmates are released. The study recruited opioid-dependent male inmates incarcerated in New York City jails that were not interested in maintenance therapy (methadone or buprenorphine). The treatment tested is a new medication, an extended-release naltrexone (XR-NTX), a compound that blocks opioid receptors.

Note on pharmacology: naltrexone is what’s known as a mu opioid receptor (MOPR) antagonist, meaning it blocks activity at MOPR (the molecular target of opioid drugs). It also has a weaker antagonist effect on kappa opioid receptors (KOPR). The KOPR plays a more complicated role in addiction, but several studies have suggested blockade of KOPR may reduce relapse. Extended release means that these receptors remain blocked for a sustained period of time after receiving the initial dose.

While 152 inmates were initially interviewed, only 34 fit the criteria for the study. Many subjects were excluded from the study for a variety of reasons that would have made the study difficult to perform or the data difficult to interpret. For example, no interest, currently on methadone or buprenorphine, tested positive for opioid prior to treatment, and other reasons.

The 34 subjects were randomly assigned to either the group that would receive the XR-NTX or standard behavioral therapy (i.e. no medication given to the patient). 15 (2 of the 17 refused) patients received a single injection of XR-NTX prior to release (average of 5 days before release) and 17 received no medication. Patients that received the XR-NTX were offered a second injection 4-weeks post release and 12 accepted this second injection.

6 of the 16 (1 remained incarcerated so was excluded) that received the first dose of XR-NTX had relapsed to opioid use at 1-4 weeks post-release while 15 of 17 relapsed for the control group. Urine analysis confirmed whether or a not a subject was on opioids.

Granted that these are very small numbers (the authors described the study as a proof-of-principle pilot study) but the data are statistically significant. This means that the effect the experimenters are observing is most likely real and not due to random chance. The results suggest that inmates that receive the XR-NTX medication are less likely to relapse after being released from prison.

 These results are important because one of the problems of the US criminal justice system is that addicts are not treated while in prison. While they are abstinent while incarcerated, the underlying neurobiology of their addiction is not being treated which results in almost immediate relapse following release from prison. This of course can result in being thrown back into jail 1) if arrested while using the drug or  2) due to criminal activity to support the addiction. This cycle of addiction-arrest-incarceration-relapse-arrest-incarceration is harmful for the criminal justice system, for the addicts themselves, and for society at large (after all, we are paying for it). This study suggests addicts in prisons that are treated with medication are less likely to relapse.

However, this study is extremely limited and needs to be expanded to a much larger group of inmates before any type of changes can be implemented on a large scale. Furthermore, once released, subjects need to be monitored more closely and for a longer period of time to determine if relapse rate remains low. Other medications prior to release, besides XR-NTX, should also be considered in future analyses.

Most importantly, this study is an example of how treating addiction as a medical disease that requires medical treatments can actually help addicts to stay off of drugs, and hopefully, out of prison.