Prospective progression from high-prevalence disorders to bipolar disorder: exploring characteristics of pre-illness stages

BACKGROUND: Identification of risk factors within precursor syndromes, such as depression, anxiety or substance use disorders (SUD), might help to pinpoint high-risk stages where preventive interventions for Bipolar Disorder (BD) could be evaluated.

METHODS: We examined baseline demographic, clinical, quality of life, and temperament measures along with risk clusters among 52 young people seeking help for depression, anxiety or SUDs without psychosis or BD. The risk clusters included Bipolar At-Risk (BAR) and the Bipolarity Index as measures of bipolarity and the Ultra-High Risk assessment for psychosis. The participants were followed up for 12 months to identify conversion to BD. Those who converted and did not convert to BD were compared using Chi-Square and Mann Whitney U tests.

RESULTS: The sample was predominantly female (85%) and a majority had prior treatment (64%). Four participants converted to BD over the 1-year follow up period. Having an alcohol use disorder at baseline (75% vs 8%, χ(2)=14.1, p<0.001) or a family history of SUD (67% vs 12.5%, χ(2)=6.0, p=0.01) were associated with development of BD. The sub-threshold mania subgroup of BAR criteria was also associated with 12-month BD outcomes. The severity of depressive symptoms and cannabis use had high effects sizes of association with BD outcomes, without statistical significance.

CONCLUSIONS AND LIMITATIONS: The small number of conversions limited the power of the study to identify associations with risk factors that have previously been reported to predict BD. However, subthreshold affective symptoms and SUDs might predict the onset of BD among help-seeking young people with high-prevalence disorders.

Screening of cannabinoids in industrial-grade hemp using two-dimensional liquid chromatography coupled with acidic potassium permanganate chemiluminescence detection

Widely known for its recreational use, the cannabis plant also has the potential to act as an antibacterial agent in the medicinal field. The analysis of cannabis plants/products in both pharmacological and forensic studies often requires the separation of compounds of interest and/or accurate identification of the whole cannabinoid profile. In order to provide a complete separation and detection of cannabinoids, a new two-dimensional liquid chromatography method has been developed using acidic potassium permanganate chemiluminescence detection, which has been shown to be selective for cannabinoids. This was carried out using a Luna 100 Å CN column and a Poroshell 120 EC-C18 column in the first and second dimensions, respectively. The method has utilized a large amount of the available separation space with a spreading angle of 48.4° and a correlation of 0.66 allowing the determination of more than 120 constituents and mass spectral identification of ten cannabinoids in a single analytical run. The method has the potential to improve research involved in the characterization of sensitive, complex matrices.

A longitudinal study of the association of adolescent polydrug use, alcohol use and high school non-completion

AIMS: Failure to complete high school predicts substantial economic and social disadvantage in adult life. The aim of this study was to determine the longitudinal association of mid-adolescent polydrug use and high school non-completion, relative to other drug use profiles. DESIGN: A longitudinal analysis of the relationship between polydrug use in three cohorts at grade 9 (age 14-15 years) and school non-completion (reported post-high school). SETTING: A State-representative sample of students across Victoria, Australia. PARTICIPANTS: A total of 2287 secondary school students from 152 high schools. The retention rate was 85%. MEASUREMENTS: The primary outcome was non-completion of grade 12 (assessed at age 19-23 years). At grade 9, predictors included 30-day use of eight drugs, school commitment, academic failure and peer drug use. Other controls included socio-economic status, family relationship quality, depressive symptoms, gender, age and cohort. FINDINGS: Three distinct classes of drug use were identified-no drug use (31.7%), mainly alcohol use (61.8%) and polydrug use (6.5%). Polydrug users were characterized by high rates of alcohol, tobacco and cannabis use. In the full model, mainly alcohol users and polydrug users were less likely to complete school than non-drug users [odds ratio (OR) = 1.54, 95% confidence interval (CI) = 1.17-2.03) and OR = 2.51, 95% CI = 1.45-4.33), respectively, P < 0.001]. These effects were independent of school commitment, academic failure, peer drug use and other controls. CONCLUSIONS: Mid-adolescent polydrug use in Australia predicts subsequent school non-completion after accounting for a range of potential confounding factors. Adolescents who mainly consume alcohol are also at elevated risk of school non-completion.

Are the profiles of past-year internet gamblers generalizable to regular internet gamblers?

 Research generally classifies internet gamblers as those who have gambled online at least once in the previous year. This classification system has been criticised on the grounds that it fails to consider the frequency of internet gambling. This study aimed to contrast the demographic, gambling, and psychosocial profiles of regular internet gamblers (at least monthly in the previous year) with those of past-year internet gamblers. Computer-assisted telephone interviews were conducted with 4303 adult respondents from Tasmania, Australia. The findings revealed that 3.3% were past-year internet gamblers and 2.1% were regular internet gamblers. Both past-year and regular internet gambling were significantly associated with several variables (younger age, dependent children, paid employment, higher annual income, higher gambling frequency and expenditure, younger age of first gambling, challenge and positive feelings gambling motives, and positive reinforcement gambling triggers). However, several variables were significantly associated only with past-year internet gambling (male gender, living with partner, number of gambling activities, regulate internal state gambling motives, hazardous alcohol use, cannabis use, and other illicit drug use) or regular internet gambling (higher education). Only gambling for positive feelings was a significant independent predictor of both past-year and regular internet gambling. These findings suggest that the classification of past-year internet gambling that is normally employed in research produces profiles that are not fully generalizable to regular internet gamblers.

Prevalence of psychiatric co-morbidity in treatment-seeking problem gamblers: A systematic review and meta-analysis

OBJECTIVE: The aim of this paper was to systematically review and meta-analyse the prevalence of co-morbid psychiatric disorders (DSM-IV Axis I disorders) among treatment-seeking problem gamblers. METHODS: A systematic search was conducted for peer-reviewed studies that provided prevalence estimates of Axis I psychiatric disorders in individuals seeking psychological or pharmacological treatment for problem gambling (including pathological gambling). Meta-analytic techniques were performed to estimate the weighted mean effect size and heterogeneity across studies. RESULTS: Results from 36 studies identified high rates of co-morbid current (74.8%, 95% CI 36.5-93.9) and lifetime (75.5%, 95% CI 46.5-91.8) Axis I disorders. There were high rates of current mood disorders (23.1%, 95% CI 14.9-34.0), alcohol use disorders (21.2%, 95% CI 15.6-28.1), anxiety disorders (17.6%, 95% CI 10.8-27.3) and substance (non-alcohol) use disorders (7.0%, 95% CI 1.7-24.9). Specifically, the highest mean prevalence of current psychiatric disorders was for nicotine dependence (56.4%, 95% CI 35.7-75.2) and major depressive disorder (29.9%, 95% CI 20.5-41.3), with smaller estimates for alcohol abuse (18.2%, 95% CI 13.4-24.2), alcohol dependence (15.2%, 95% CI 10.2-22.0), social phobia (14.9%, 95% CI 2.0-59.8), generalised anxiety disorder (14.4%, 95% CI 3.9-40.8), panic disorder (13.7%, 95% CI 6.7-26.0), post-traumatic stress disorder (12.3%, 95% CI 3.4-35.7), cannabis use disorder (11.5%, 95% CI 4.8-25.0), attention-deficit hyperactivity disorder (9.3%, 95% CI 4.1-19.6), adjustment disorder (9.2%, 95% CI 4.8-17.2), bipolar disorder (8.8%, 95% CI 4.4-17.1) and obsessive-compulsive disorder (8.2%, 95% CI 3.4-18.6). There were no consistent patterns according to gambling problem severity, type of treatment facility and study jurisdiction. Although these estimates were robust to the inclusion of studies with non-representative sampling biases, they should be interpreted with caution as they were highly variable across studies. CONCLUSIONS: The findings highlight the need for gambling treatment services to undertake routine screening and assessment of psychiatric co-morbidity and provide treatment approaches that adequately manage these co-morbid disorders. Further research is required to explore the reasons for the variability observed in the prevalence estimates.

A review of vulnerability and risks for schizophrenia: beyond the two hit hypothesis

Schizophrenia risk has often been conceptualized using a model which requires two hits in order to generate the clinical phenotype-the first as an early priming in a genetically predisposed individual and the second a likely environmental insult. The aim of this paper was to review the literature and reformulate this binary risk-vulnerability model. We sourced the data for this narrative review from the electronic database PUBMED. Our search terms were not limited by language or date of publication. The development of schizophrenia may be driven by genetic vulnerability interacting with multiple vulnerability factors including lowered prenatal vitamin D exposure, viral infections, smoking intelligence quotient, social cognition cannabis use, social defeat, nutrition and childhood trauma. It is likely that these genetic risks, environmental risks and vulnerability factors are cumulative and interactive with each other and with critical periods of neurodevelopmental vulnerability. The development of schizophrenia is likely to be more complex and nuanced than the binary two hit model originally proposed nearly thirty years ago. Risk appears influenced by a more complex process involving genetic risk interfacing with multiple potentially interacting hits and vulnerability factors occurring at key periods of neurodevelopmental activity, which culminate in the expression of disease state. These risks are common across a number of neuropsychiatric and medical disorders, which might inform common preventive and intervention strategies across non-communicable disorders.