Pathways to Substance Use and Abuse

Neuroscience medicine clinicians encounter patients every day who have both a mental and substance use disorder.

This co-occurrence, or comorbidity, complicates diagnosis, treatment and outcome.

The exact mechanism for this comorbidity issue is unclear.

A recent study out of Washington University in St. Louis and King's College London provides some insight into this comorbidity issue.

They examined participants in the Study of Addiction: Genetics and Environment (SAGE). These subjects provided genetic samples and psychiatric interviews to the research team.

Five psychiatric disorders were studied including attention deficit hyperactivity, autism spectrum disorder, major depression, bipolar disorder and schizophrenia. A initial finding ruled out any link between genetic risk for autism spectrum disorder and any substance use/abuse risk.

The remaining four psychiatric disorders did increase risk for substance use and abuse in a general manner. This means genetic risk for ADHD, bipolar disorder, major depression and schizophrenia all contribute to a general risk for substance use/abuse across all drug categories.

Additionally, the team reported some specific drug use/abuse with individual genetic risk for ADHD, bipolar disorder, major depression and schizophrenia. These specific pathways included:

• Major depression polygenetic risk score and non-problem cannabis use
• Major depression polygenetic risk score and severe cocaine dependence
• Schizophrenia polygenetic risk score and  non-problem cannabis use and severe cannabis dependence
• Schizophrenia polygenetic risk score and severe cocaine dependence

The take-home message from this study is that genetic risk for many psychiatric disorders also contributes to a increased risk for general substance use/abuse. Additionally, some psychiatric disorders appear to increase risk for specific substance use/abuse issues.

Prevention, assessment and treatment services need to address this relationship and the needs for each component of illness in those with comorbidity.

Individuals with more interest in this topic can access the free full-text manuscript by clicking on the link in the citation below.

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Image is an original graphic produced by me based on content in the manuscript.

Carey CE, Agrawal A, Bucholz KK, Hartz SM, Lynskey MT, Nelson EC, Bierut LJ, & Bogdan R (2016). Associations between Polygenic Risk for Psychiatric Disorders and Substance Involvement. Frontiers in genetics, 7 PMID: 27574527

Prenatal Smoking and Offspring Schizophrenia

The topic prevention of brain disorders  is commonly neglected. This is despite increasing evidence for evidence-based support for prevention opportunities.

This issue is highlighted in a recent study out of Finland that examined prenatal nicotine metabolite levels and offspring diagnosis of schizophrenia.

In this study, Solja Niemela and the Finnish research team examined all live births in Finland between 1983 and 1998.

What makes this study powerful is the measurement of maternal serum cotinine levels in maternal serum during the early and mid stages of prenancy. Cotinine is a metabolite and the levels of cotinine reflect the level of nicotine consumption.

The key findings from this study include the following points:

• Measuring cotinine levels as a continuous variable yielded an increased odds ratio for schizophrenia of 3.41 (95% CI 1.86-6.24)
• Mothers in the highest cotinine level group had a 38% increase in offspring schizophrenia rates
• These findings included controlling for potential confounding variables including maternal age and parental history of psychiatric disorders

Interestingly a PubMed search found a second study linking maternal smoking with increased risk of offspring diagnosis of bipolar disorder (odds ratio 2.01, 95% CI 1.48-2.53).

These two studies in combination support a potential non-specific effect of prenatal nicotine exposure on risk for two of the most impairing psychiatric disorders. 

These two studies also support aggressive smoking cessation efforts in young women before pregnancy or at the latest very early after conception.

You can find more information about these two studies by clicking on the citation links below.

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Niemelä, S., Sourander, A., Surcel, H., Hinkka-Yli-Salomäki, S., McKeague, I., Cheslack-Postava, K., & Brown, A. (2016). Prenatal Nicotine Exposure and Risk of Schizophrenia Among Offspring in a National Birth Cohort American Journal of Psychiatry DOI: 10.1176/appi.ajp.2016.15060800

Talati A, Bao Y, Kaufman J, Shen L, Schaefer CA, & Brown AS (2013). Maternal smoking during pregnancy and bipolar disorder in offspring. The American journal of psychiatry, 170 (10), 1178-85 PMID: 24084820

Older Fathers: Epigenetic Factors

 A recent review article published in American Journal of Stem Cells summarized current knowledge of epigenetic factors in fathers.

Epigenetic factors are defined as environmental factors that change the expression of genetics.

We know that as men age, changes in genetic structures have effects on their offspring.

Men who have children after age 40 have higher rates of offspring with:

• schizophrenia
• autism and autism spectrum disorder
• birth defects including heart defects, Down syndrome and other chromosomal anomalies

These effects are not completely understood but do appear to be related to age-dependent methylation of DNA.

Older age is not the only epigenetic influence in fathers. Cigarette smoking, heavy alcohol intake, paternal diet and paternal stress all have some evidence of adversely affecting paternal epigenetic effects.

The effect of advanced paternal age on increased risk in offspring is important as the age at first child is increasing for both men and women. Part of older father effect appears related to the association of older parenthood with increased level of education in the population. (see original chart produced above from U.S. Census Bureau data)

You can read more about this review at MedicalXpress HERE.

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iPad Intervention Boosts Cognition in Schizophrenia

In a previous post, I summarized some of the current thinking on the use of cognitive enhancement drugs in Alzheimer's disease, Parkinson's disease, ADHD and schizophrenia.

This summary was based on a review by Gabe Howard and colleagues. The review also included a summary of a clinical trial using an iPad cognitive training app for the treatment of cognition in schizophrenia.

Here are the key elements of the study and the results.

Study sample: 22 adults with a diagnosis of DSM-5 schizophrenia, schizoaffective disorder or schizophreniform disorder. Most subjects were receiving antipsychotic drug treatment during the course of the study.

Intervention design: Subjects were randomly assigned to two groups. One completed 8 hours of training on an iPad cognitive training app over 4 weeks while the remaining group continued as a treatment as usual control group

iPad app details: A study-designed app that used a paired associative learning task into a narrative game that provided feedback and used visual and music stimulation to keep subjects engage

Outcome measure: Baseline and 4 week neuropsychological testing using the CANTAB PAL task

Results: The CT intervention group showed superior pattern location, fewer errors and improved rating on the Global Assessment of Functioning scale compared to the treatment as usual group

This study has several implications. First, it appears game app design can be effectively used in schizophrenia. Additionally, this type of intervention appears to produce improvement in the types of memory impairment associated with the disorder. The study should stimulate further development and implementation of cognitive training tools in schizophrenia and other neuroscience medicine disorders.

Readers with more interest in this research can access the free full-text manuscript by clicking on the PMID link in the citation below.

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Sahakian BJ, Bruhl AB, Cook J, Killikelly C, Savulich G, Piercy T, Hafizi S, Perez J, Fernandez-Egea E, Suckling J, & Jones PB (2015). The impact of neuroscience on society: cognitive enhancement in neuropsychiatric disorders and in healthy people. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 370 (1677) PMID: 26240429

Cognitive Enhancers in Neuroscience Medicine

Neuropsychiatric disorders cause impairment via multiple pathways. One pathway to impairment is cognitive impairment via attention problems, cognitive slowing and memory disruption.

Barbara Sahakian and colleagues recently published an interesting manuscript examining the issue of cognitive enhancement.

Their review begins by summarizing some of the research related to cognitive enhancement in four neuropsychiatric syndromes. I will summarize their main points by specific disorder.

Alzheimer's Disease (AD)

• Acetylcholinesterase inhibitors such as donepezil have been specifically developed to enhance and slow deterioration of cognitive function in AD
• NMDA receptor agonists such as memantine can also enhance cognitive function and these types of cognitive enhancement agents are typically used in later stages of the disease
• Early identification and early use of cognitive enhancement agents is estimated to decrease the cost of AD by $5000 per individual

Parkinson's Disease (PD)

• Cognitive impairment and dementia are commonly found in PD
• Dopamine agonists such as methylphenidate have been used in PD for treatment of fatigue and cognitive impairment but can worsen impulsivity/compulsive gambling problems
• Atomoxetine may hold promise in PD for psychomotor slowing, global cognition and executive functioning
• Anticholinesterase inhibitors and memantine have shown only marginal improvement in cognition in studies of PD subjects

Attention Deficit Hyperactivity Disorder (ADHD)

• Stimulant treatment of ADHD with drugs such as methylphenidate is effective in 60-70% of children and adults with ADHD
• However, new non-stimulant drug development is needed to address issues of stimulant abuse and non-response
• Methylphenidate improves spatial working memory performance in both individuals with ADHD and healthy volunteers
• Modafinil and atomoxetine may improve response inhibition in ADHD but appear to have limited effects on sustained attention and working memory

Schizophrenia

• Cognitive deficits are a hallmark of schizophrenia and the target of drug and non-drug intervention studies
• Modafanil has shown some early promise in schizophrenia with at least one study showing improvements in working memory, cognitive flexibility, emotion recognition, dorsolateral prefrontal cortex function
• Acetylcholinesterase inhibitors have shown limited effect on cognition in schizophrenia
• Non-drug interventions such as cognitive enhancement techniques (i.e. video games) may hold promise in schizophrenia

The authors go on to describe the results of a computer game study of cognition in schizophrenia using an iPad. I will describe the results of this study in my next post.

Readers with more interest in this manuscript can access the free full-text version by clicking on the PMID link in the citation below.

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Photo of Roman ruler Marcus Aurelius on horse from author's files.

Sahakian BJ, Bruhl AB, Cook J, Killikelly C, Savulich G, Piercy T, Hafizi S, Perez J, Fernandez-Egea E, Suckling J, & Jones PB (2015). The impact of neuroscience on society: cognitive enhancement in neuropsychiatric disorders and in healthy people. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 370 (1677) PMID: 26240429

Bipolar Disorder Linked to Increased Dementia Risk

A variety of risk factors have been identified in Alzheimer's disease and other types of dementia.

The risk for dementia following major psychiatric syndromes in mid-life is an important research area.

Renate Zilkens and colleagues in Australia recently published an informative study of psychiatric disorders and later dementia risk. This study used a population-based case control methodology.

The key elements in the design of this study included the following:

• Subjects: General population in Western Australia
• Data sources: inpatient, outpatient and emergency medical records along with death records
• Cases: Incident cases of dementia between ages of 65 and 84 years of age
• Controls: Age and sex-matched individuals without incident dementia diagnosis
• Psychiatric diagnoses: medical record diagnoses that were required to be present at least ten years prior to dementia onset
• Statistical analysis: odds ratio using conditional logistic regression

The research group in this study used a variety of models to assess risk based on specific medical and psychiatric disorders.

For simplicity, I have used data from the study to put together the summary graph in this post.

This graph estimates later dementia odds ratios for specific disorders when that disorder is present during the 65-69 year age period.

There is evidence of a strong increase in risk for dementia following bipolar disorder diagnosis (odds ratio 4.71, 95% confidence interval 2.29 to 9.65). Bipolar disorder is the psychiatric disorder with the second highest odds ratio being topped only by schizophrenia with an estimated odds ratio of 12.1. The odds ratio with depression was only slight lower than that associated with a diabetes diagnosis (odds ratio 2.77 vs 3.47). Anxiety disorder had a small but statistically significant increased odds ration for later dementia (odds ratio 1.37, 95% confidence interval 1.14-1.65)

Alcoholism diagnosis by age 65 years of age is also associated with a marked increase in dementia risk (odds ratio 4.14, 95% confidence interval 2.25 to 7.61).

The authors note their findings support the role of psychiatric disorders in contributing to brain vascular abnormalities that can contribute to later cognitive decline. Additionally, they note there is increasing evidence that psychiatric disorders are associated with brain inflammation and immune system dysfunction, areas know to contribute to cognitive decline.

This study is important is suggests at lease five psychiatric disorders need to be considered as potential risk factors for dementia (bipolar disorder plus schizophrenia, depression, anxiety and alcoholism). Adding these risk factors may allow for improvement in detection and prevention efforts.

Additionally, the finding suggest dementia populations may have higher rates of psychiatric disorders. These psychiatric disorders can complicate dementia management and increase the need for psychiatric assessment and consultation in geriatric care settings.

Readers with more interest in this topic can access the free full-text manuscript by clicking on DOI link below.

Follow the author on Twitter @WRY999

Zilkens, R., Bruce, D., Duke, J., Spilsbury, K., & Semmens, J. (2014). Severe Psychiatric Disorders in Mid-Life and Risk of Dementia in Late- Life (Age 65-84 Years): A Population Based Case-Control Study Current Alzheimer Research, 11 (7), 681-693 DOI: 10.2174/1567205011666140812115004

Brain Default Network in Psychotic Bipolar Disorder

In a previous post I reviewed a summary of research related to genetics and improved diagnosis in bipolar disorder.

One key point in this review was a highlight of the promise for integrating genetic with imaging research in bipolar disorder and other neuropsychiatric disorders.

An example of this type of integrated research has been recently published in PNAS by a group of Yale University, the University of New Mexico and the University of Texas Southwestern Medical Center.

This study used functional magnetic resonance imaging (fMRI) default mode network (DMN) across a group of subjects with psychotic bipolar disorder, schizophrenia and healthy controls. Additionally, study included imaging a group of unaffected relatives of the psychotic bipolar subjects and schizophrenia.

Subjects also had genetic analyses available for comparison with any imaging results that would emerge in the study.

The research team identified three circuit components in the DMN. The included the networks below (also identified by color as highlighted in group name):
Anterior DMN--Medial prefrontal cortex-anterior cingulate caudate DMN
Inferior posterior DMN--posterior cingulate caudate, inferior parietal lobule, middle temporal gyrus, cuneus/pre-cuneus
Superior posterior DMN--cuneus/pre-cuneus, inferior parietal lobule, cingulate

The key findings from the study include the following:

• Measures of hypoconnectivity in all three networks were identified in the psychotic bipolar and schizophrenia groups compared to controls.
• Unaffected psychotic bipolar disorder relatives had normal DMN measures in the three networks while the unaffected schizophrenic relatives showed hypoconnectivity in on one of the three networks.
• Genetic analysis revealed five genetic links to a brain connectivity sub-DMNs.
• Genes identified in this brain mapping linkage had previously been linked to psychosis and mood disorders

The five genetic clusters identified in this study were related to specific brain developmental and neuronal processes:

• NMDA long-term potentiation
• Protein kinase A regulation
• Immune response signaling
• Guidance of axonal development
• Synaptogenesis

The authors note an important advance in their study is the ability to

"dissect the underlying biological/molecular pathways and processes that might mediate genetic risk of psychosis via a valuable, noninvasive imaging marker."

Default mode network imaging and analysis is advancing as a promising research and clinical tool. It holds the promise of improving diagnostic accuracy and potentially improvement in targeting best treatment interventions for many brain disorders.

Readers with more interest in this topic can access the free full-text manuscript by clicking on the PMID link below.

Image of the cingulate fiber connectivity anatomy is an iPad screen shot from the app Brain Tutor.

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Meda SA, Ruaño G, Windemuth A, O'Neil K, Berwise C, Dunn SM, Boccaccio LE, Narayanan B, Kocherla M, Sprooten E, Keshavan MS, Tamminga CA, Sweeney JA, Clementz BA, Calhoun VD, & Pearlson GD (2014). Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia. Proceedings of the National Academy of Sciences of the United States of America, 111 (19) PMID: 24778245

Genetics Leading to Better Bipolar Disorder Diagnosis

I wanted to alert Brain Posts readers to an important new review of genetics and diagnosis in brain disorders including bipolar disorder.

One hope for the emerging genetics research in mental disorders is a better diagnostic classification system.

The current psychiatric diagnostic system is hampered by use of a primary symptoms and signs approach leading to messy heterogeneous groups of clinical conditions.

Elliot Gerson has been a giant in neuroscience genetics for quite some time and recently published an important manuscript titled: "Genetic and genomic analyses as a basis for new diagnostic nosologies" in the journal Dialogues in Clinical Neuroscience.

Gershon notes current clinical diagnostic categories in psychiatry fail three of five tests for diagnostic validity described by Feigher in 1972:

• family study clustering
• course of illness 
• laboratory tests

There is promise for using genetic and genomic findings to improve diagnostic validity in psychiatric disorders. Gershon goes on to outline what is currently known in psychiatric genetics and how future genetic research can lead to "biologically coherent diagnostic entities".

Here is my summary on what I see as the key points in the review:

• The number of common gene single-neucleotide polymorphisms (SNPs) linked to brain disorders is growing (from 10 to over 100 for schizophrenia an example)
• Summing risk across known schizophrenia SNPs using risk profile scores accounts for 7% of genetic variance in schizophrenia (this increases to up to 23% of variance when broader phenotypic systems are used)
• A similar SNP risk profile approach separates bipolar disorder groups from controls
• Larger sample sizes may increase this SNP genetic variance understanding in schizophrenia and bipolar disorder
• Some SNPs contribute to risk for more than one disorder i.e. schizophrenia, bipolar disorder and major depression showing weakness of current classification system
• Common genome-wide SNP data may be a promising path to defining better diagnostic categories
• Rare variants such as copy number variations (CNVs) may also be promising for improved psychiatric diagnosis
• Chromosome 22q11 deletion (DiGeorge syndrome or velocardiofacial syndrome) occurs in 1/4000 births and has high penetrance for psychiatric diagnosis although nonspecific (23% autism sprectrum, 68% schizophrenia, 26% bipolar disorder)
• Brain molecular network modeling also holds promise as a basis for diagnosis
• Many known risk genes for psychiatric illness have been linked to key brain network nodes
• Genetic variants could be mapped to human molecular networks and this map may lead to predictable "therapeutic targets"
• Brain connectivity networks (fMRI) may be a promising alternate approach to psychiatric diagnosis

The validity criteria for psychiatric diagnosis described by Feighner in 1972 continue to be a gold standard. Emerging genetic, genomic and brain connectivity research may be part of the tool set that has been missing. Applying these tools to better diagnosis holds promise for new and better treatment and the reduction in pain and suffering for many brain disorders.

Interested readers can access the free full-text manuscript of the Gerson and Grennan review by clicking on the PMID link in the citation below.

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Gershon ES, & Grennan KS (2015). Genetic and genomic analyses as a basis for new diagnostic nosologies. Dialogues in clinical neuroscience, 17 (1), 69-78 PMID: 25987865

Top Research in Bipolar Disorder: Reading Links

In June I will be looking for some of the top recent research advances in bipolar disorder.

Although less common than unipolar depression, bipolar disorder is a serious disorder with high rates of disability and hospitalization.

I will try to cover the spectrum of important areas in bipolar disorder during the month including: epidemiology, risk factors, biomarkers, genetics, brain imaging, neuropsychology, psychopharmacology and psychological interventions.

Here is a starting group of important studies. Some will be covered in more detail in a future post. Click on the study title to be taken to the full abstract and the free full-text manuscript.

Suicidal behavior in bipolar disorder with antidepressant use

This study examined participants in the Collaborative Depression Study, a naturalistic longitudinal study of bipolar I, bipolar II and unipolar depression. The study found a 54% reduction in suicidal behavior in bipolar I subjects receiving antidepressant therapy and a 35% reduction in bipolar II subjects receiving antidepressants. Of note, use of antidepressants in unipolar depression was not linked to change in suicidal behavior frequency. 

Anti-inflammatory markers in bipolar disorder: Effects of celecoxib (Celebrex)

Mood disorders are commonly linked to elevated markers of inflammation including serum cytokines. In this study, subjects with bipolar disorder receiving electroconvulsive therapy were randomly assigned to the anti-inflammatory drug celecoxib versus placebo. Celecoxib treatment was linked to reduced levels of tumor necrosis factor-alpha but not to reduced levels of two interleukin levels and c reactive protein levels.

Biomarkers in bipolar disorder

This manuscript is a review of the literature in biomarker research for bipolar disorder. The authors found support for several brain structural markers including reduced gray matter volumes in the prefrontal cortex. Serum measures of neutrophic factors, oxidative stress and inflammation also hold promise as biomarkers in bipolar disorder.

Brain connectivity in bipolar disorder vs schizophrenia vs controls

A study of resting state connectivity using functional magnetic resonance imaging targeted a group of subjects with bipolar disorder, schizophrenia and healthy controls. The study found significant differences in connectivity between bipolar subjects and controls although these differences were less pronounced than the differences between a group of schizophrenics and controls.

Genome-wide association studies of schizophrenia, bipolar disorder and unipolar disorder

This study examined results from 60,000 subjects in the Psychiatric Genomics Consortium. The study found evidence for common pathways across the schizophrenia, bipolar and unipolar groups that involve neuronal, immune function and histone methylation.

Follow me on Twitter for updates in neuroscience research. @WRY999

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Nicotine Replacement in Schizophrenia

Inpatient psychiatric hospitals increasingly prohibit smoking by patients, staff and family in their units.  Although the public health benefits of smoking restrictions are undeniable, there may be some situations where smoking restrictions have unintended consequences.  One area is the emergency management of patients with serious psychiatric illnesses such as schizophrenia and bipolar affective disorder.

Rates of smoking have been documented to be higher in both schizophrenia and bipolar affective disorder.  The likelihood is high that acute psychiatric emergencies in schizophrenia and bipolar will be accompanied by nicotine dependence.  Clinicians are left making a decision on how to manage nicotine dependence in the context of psychotic decompensation.

Michael Allen and colleagues recently conducted a small study of nicotine dependence management in forty subjects with schizophrenia admitted to a psychiatric emergency service.  Subjects were required to be smokers at the time of admission.  Severity of smoking dependence was assessed using the Fagerstrom scale.  Subjects received standard antipsychotic therapy without restriction but they were randomized to receive either nicotine replacement therapy (21 mg nicotine patch per day) or placebo patch.

Here is a summary of the results of the study:

• Nicotine replacement reduced a measure of agitation by 33% in the first four hours and 23% at 24 hours
• This reduction was statistically significantly more than with antipsychotic alone and placebo
• Subjects with lower nicotine dependence scores tended to show the most response compared to placebo
• The size of the effect of nicotine replacement on agitation reduction approached the level seen with standard antipsychotic therapy

So the beneficial effects of replacing nicotine in the short term in this population is pretty dramatic and of signifcant magnitude.  The authors note that it is possible the 21 mg nicotine patch is insufficient to address nicotine withdrawal in schizophrenics with more severe nicotine dependence.  Since the nicotine patch typically takes several hours to provide significant blood levels, the authors suggest a combination of nicotine gum (with rapid onset) and a patch may be the best strategy.

Encouraging patients with psychotic disorders and mood disorders to quit smoking is an important general health strategy.  However, this study suggests that attempting this during an acute psychotic break is probably counter productive and may be inhumane.  Acute nicotinie withdrawal may exacerbate the agitation of psychosis.  Nicotine withdrawal attempts in this population is probably better suited for periods where psychotic symptoms are under control.  It also makes sense to monitor patients with schizophrenia closely during attempts to stop smoking.  This period may be one of increased risk of psychiatric decompensation.

Photo of Nicotine Patch Courtesy of Wikipedia Creative Commons by RegBarc

Allen MH, Debanné M, Lazignac C, Adam E, Dickinson LM, & Damsa C (2011). Effect of nicotine replacement therapy on agitation in smokers with schizophrenia: a double-blind, randomized, placebo-controlled study. The American journal of psychiatry, 168 (4), 395-9 PMID: 21245085

Cannabis Use and Psychosis (Part 2)

I reviewed a research study last fall examining a Dutch study of cannabis use and psychotic symptoms.  That post is linked here.  In summary, the study suggested cannabis probably does not produce psychotic symptoms in the majority of users.  However, if you have a family member with a psychotic disorder (suggesting you may have a genetic risk for psychosis) you may be more likely to experience psychotic symptoms (i.e. hallucinations/delusions) with cannabis use.  This risk may be increased with higher potency cannabis formulations.

Now two additional research publications weigh in on this issue.  Both were published in the February 2011 issue of Archives of General Psychiatry.  Both studies come from the Genetic Risk and Outcome of Psychosis (GROUP) study sample.

The first manuscript summarized the results of study using a sibling-control and cross-sibling comparison.  Eleven hundred twenty subjects with a psychotic disorder were compared to 1057 siblings and 590 controls. In summary the results of this study were:

• You were much more likely to report psychotic symptoms (both positive and negative psychotic symptoms) with cannabis use if you had a sibling with psychosis
• Siblings using cannabis resembled psychotic siblings in their ratings much more than siblings not using cannabis
• The statistical analysis of the relationship pointed to a familial risk increasing cannabis sensitivity, rather than familial risk increasing use of cannabis

So this finding in in line with the original study.  Families may resemble each other in the way they respond to cannabis.  Some families may be particularly more likely to have psychotic symptoms in the context of cannabis use.

The second study takes another step to try to explain this relationship.  Can candidate genes be identified that are linked to this cannabis-linked psychosis effect?  If so, do these genes make biological sense or do they seem to just likely be random associations.

The answers proposed by the GROUP investigators are intriguing.  

• Sixteen single nucleotide proteins (SNPs) showed significant interactions
• The AKT1 gene status (C/C genotype) increased risk of psychosis after cannabis use
• AKT1 gene status explained 19% of the variance of psychotic symptoms in siblings with recent cannabis use
• The AKT1 gene is regulated by endogenous cannabanoid signaling
• This signal is downstream from the dopamine D2 receptor--a receptor known to be involving in psychosis and the target of antipsychotic drugs

The authors note that their proposed mechanism explains two commonly clinical findings:

• antipsychotic drugs do not block the psychotic effect of THC in those that experience psychosis with the drug
• substance abusing patients with schizophrenia respond more poorly to antipsychotic treatment

The explanation would be the endocannabanoid AKT1 effect is downstream from the D2 receptor.  Blocking the D2 receptor would have limited effects downstream from the receptor.

These two studies add to support for a role for cannabis to be a potential risk factor for some forms of psychosis and schizophrenia.  The genetic and molecular correlations in this study a mutually supportive.  So the take home message seems to be the same--there just seems to be more support the message is research based.  Some individuals may have a genetic risk for psychotic symptoms related to cannabis use.  This is not a trivial risk.  If you have a sibling or other relative with psychosis, or if you experience psychotic symptoms with cannabis use, don't use cannabis.

Photo of Back Yard Blue Jay in Tulsa after Snowfall Courtesy of Yates Photography

., Kahn, R., Linszen, D., van Os, J., Wiersma, D., Bruggeman, R., Cahn, W., de Haan, L., Krabbendam, L., & Myin-Germeys, I. (2010). Evidence That Familial Liability for Psychosis Is Expressed as Differential Sensitivity to Cannabis: An Analysis of Patient-Sibling and Sibling-Control Pairs Archives of General Psychiatry DOI: 10.1001/archgenpsychiatry.2010.132

van Winkel, R., , ., Kahn, R., Linszen, D., van Os, J., Wiersma, D., Bruggeman, R., Cahn, W., de Haan, L., Krabbendam, L., & Myin-Germeys, I. (2010). Family-Based Analysis of Genetic Variation Underlying Psychosis-Inducing Effects of Cannabis: Sibling Analysis and Proband Follow-up Archives of General Psychiatry, 68 (2), 148-157 DOI: 10.1001/archgenpsychiatry.2010.152

Economic Effect of Depression-Related Early Retirement

The economic effects of depression and other mental disorders receive limited research attention. One pathway for depression to influence economic status is through early retirement as well as lower rates of employment during the working years.  The effects of early retirement are the focus of a recent Australian study by Schofield et al published in the British Journal of Psychiatry.

This study examined adults between the ages of 45 and 64 participating a large survey of the economic impact of ill health.  Survey respondents who reported they were out of work and attributed their work status as due to depression were the primary case group.  An additional group of respondents who were not working due to another mental disorder (schizophrenia, anxiety disoders, dementia, ADHD or other mental disorder) made up the other mental disorder group.

Based on results from a sub-sample, the authors estimated that Australia has approximately 25,000 older individuals in early retirement or unemployed due to depression and approximately 39,000 in early retirement or unemployed due to another mental disorder.

The key findings from the economic analysis were (depressed group data followed by other mental disorder group in parenthesis)

• Accumulated any wealth: 9% (3%) compared to rates of those employed and not ill
• Among those with any wealth, median wealth: 213,000 (112, 315) compared to control median 255,199 (figures in Australian dollars--multiply by .66 for U.S. dollars)
• Home equity: 75% (56%) compared to 89% of those employed and not ill
• Meets requirements for Australian pension (superannuation): 31% (23%) compared to 93% of those employed and not ill

The findings underscore the significant impact of depression and other mental disorders on wages and accumulation of wealth.  These disorders are commonly chronic in nature reducing income through out the adult life cycle.  Very few middle to older age individuals not working due to depression or other mental illness have any significant life savings.

The authors summarize the implications of their study with the following points:

Because of the limited personal resources for those with depression and other mental disorders as they age, the state will face a significant burden in aiding these individuals

The study supports early identification and treatment as a potential method to reduce the economic effects of depression and other mental illnesses

Photo of male cardinal courtesy of Yates Photography


Schofield DJ, Shrestha RN, Percival R, Kelly SJ, Passey ME, & Callander EJ (2011). Quantifying the effect of early retirement on the wealth of individuals with depression or other mental illness. The British journal of psychiatry : the journal of mental science, 198, 123-8 PMID: 21282782

Mental Disorders: Diseases or Behavioral Conditions?

Clinical neuroscience conditions represent a heterogeneous group of conditions with varying contributions from genetic and environmental influences.  It has been common to view some of these conditions under the disease model presumed to represent a specific pathophysiology, tissue pathology (i.e. Alzheimer’s disease, Huntington’s disease).  Other conditions have been classified as representing primarily a disorder of behavior (i.e. anorexia nevosa, substance use disorders).

The disease model is thought to be something outside of an individual’s control—individuals have the condition and the manifestations of the disease represent the effects of the underlying pathology.   More behavioral disorders are thought to have a volitional component.  Individuals with behavioral disorders are thought to contribute more to their condition and therefore assume some responsibility for having the condition.

Bienvenu, Davydow and Kendler recently published an examination of the validity of this type of classification approach.  They noted that diseases with involuntary symptoms would typically have a stronger genetic contribution that behavioral disorders where personal choices contribute to the condition.   One method to examine the genetic contribution to a particular disorder is the twin study.  Using identical and fraternal twin, examination of the concordance rates for a particular illness will provide an estimate of the relative contribution of genetic factors in the illness.  Heritability ranges between zero (no genetic contribution) to 1 (purely genetic condition). 

The authors reviewed high-quality twin studies in six clinical neuroscience conditions felt to be diseases and six clinical neuroscience conditions with a strong behavioral contribution.   The heritability estimates for the 12 conditions are shown in the graph adapted from data in the manuscript:

The authors note that the review fails to support the disease versus behavior distinction.  Behavioral disorders appear to have as significant of a genetic contribution as a group as do those more typically classified as diseases.  They note that some may argue that the diseases with lower heritabilities (major depression and generalized anxiety) are really not diseases.  If you take away major depression, panic disorder and generalized anxiety disorder from the analysis, you do get the three remaining diseases as having the highest heritability.

Nevertheless, the authors correctly point out that many behavioral disorders carry significant genetic contributions to risk.   This finding should reduce some of the stigmatization of these behavioral disorders.  They note “we humans do not seem to be equally free in our decisions”. 

The study also underscores that mental disorders considered the most disease-like, bipolar disorder and schizophrenia, have heritabilities as high as Alzheimer’s disease.  Few would argue that Alzheimer’s disease is just a behavioral disorder without a brain-based pathological contribution.  Increasing evidence supports incorporating bipolar disorder and schizophrenia in the brain disease model category. 

Bienvenu OJ, Davydow DS, & Kendler KS (2011). Psychiatric 'diseases' versus behavioral disorders and degree of genetic influence. Psychological medicine, 41 (1), 33-40 PMID: 20459884

GABA Neurons and Rett Syndrome

Rett Syndrome is a rare (1 in every 10,000 to 15,000 live female births) neurodevelopmental disorder that occurs almost exclusively in young girls. This syndrome shares features with autism.  The disorder is caused by a mutation of the MECP2 (methyl-CpG-binding protein 2) gene (MECP2 translation protein diagram noted on the right).  This gene is found on the X chromosome. Infant boys born with the mutation typically die shortly after birth as they have no reserve X chromosome that may compensate to a degree with the mutation.


Rett Syndrome is typically diagnosed in early childhood when the following essential diagnostic criteria are met:

• Normal development until 6 to 18 months of age
• Normal head circumference at birth followed by a slowing of the rate of head growth between 3 months and 4 years of age
• Severe impairment in expressive language
• Repetitive and stereotypic hand movements
• Gait abnormalities--toe walking or wide-based, stiff-legged walk

A recent study published in Nature examined a potential mechanism to explain some of the stereotypical behaviors found in Rett Syndrome.  Using a mouse model, mice were produced that lacked MeCP2 in the brain gamma amino butryic acid (GABA) neurons.  These mice demonstrated a series of neurobehavioral abnormalities similar to Rett syndrome including: repetitive behavior, impaired motor coordination, social interaction abnormalites and reduced startle response.  These mice showed evidence of significant reduction in  GABA content in the brain cortex and striatum regions.


The authors note their study "demonstrate(s) that GABAergic dysfunction is a critical mediator of Rett syndrome phenotypes".  They note that MeCP2 mutations are found in a relatively rare number of humans with bipolar disorder, schizophrenia and autism.  They note that GABAergic dysregulation through a variety of mechanisms may be central to these neuropsychiatric disorders.


If you are interested in learning more about the features of Rett Sydrome, I embedded theYouTube video below that documents the developmental history of Chelsea--an 11 year old girl with Rett Syndrome.





Further information on Rett Syndrome at the International Rett Syndrome Association website as well as from a Fact Sheet on Rett Syndrome from the National Institute of Neurological Disorders and Stroke.


Diagram of MECP2 protein is licensed under the Creative Commons Attribution Share Alike 3.0 unported license with author Emw.


Chao, H., Chen, H., Samaco, R., Xue, M., Chahrour, M., Yoo, J., Neul, J., Gong, S., Lu, H., Heintz, N., Ekker, M., Rubenstein, J., Noebels, J., Rosenmund, C., & Zoghbi, H. (2010). Dysfunction in GABA signalling mediates autism-like stereotypies and Rett syndrome phenotypes Nature, 468 (7321), 263-269 DOI: 10.1038/nature09582