Cannabis-based medicinal products (CBMPs) are increasingly being used to treat post-traumatic stress disorder (PTSD), despite limited evidence of their efficacy. PTSD is often comorbid with major depression, and little is known about whether comorbid depression alters the effectiveness of CBMPs.

To document the prevalence of depression among individuals seeking CBMPs to treat PTSD and to examine whether the effectiveness of CBMPs varies by depression status.

Data were available for 238 people with PTSD seeking CBMP treatment (5.9% of the treatment-seeking sample) and 3-month follow-up data were available for 116 of these. Self-reported PTSD symptoms were assessed at treatment entry and at 3-month follow-up using the PTSD Checklist – Civilian Version (PCL-C). The probable presence of comorbid depression at treatment entry was assessed using the nine-item Patient Health Questionnaire (PHQ-9). Additional data included sociodemographic characteristics and self-reported quality of life.

In total, 77% met screening criteria for depression, which was associated with higher levels of PTSD symptomatology (mean 67.8 v. 48.4, F(1,236) = 118.5, P < 0.001) and poorer general health, quality of life and sleep. PTSD symptomatology reduced substantially 3 months after commencing treatment (mean 58.0 v. 47.0, F(1,112) = 14.5, P < 0.001), with a significant interaction (F(1,112) = 6.2, P < 0.05) indicating greater improvement in those with depression (mean difference 15.3) than in those without (mean difference 7).

Depression is common among individuals seeking CBMPs to treat PTSD and is associated with greater symptom severity and poorer quality of life. Effectiveness of CBMPs for treating PTSD does not appear to be impaired in people with comorbid depression.

Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.

A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.

Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.

Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.

Substance use and psychiatric illness, particularly psychotic disorders, contribute to violence in emergency healthcare settings. However, there is limited research regarding the relationship between specific substances, psychotic symptoms and violent behaviour in such settings. We investigated the interaction between recent cannabinoid and stimulant use, and acute psychotic symptoms, in relation to violent behaviour in a British emergency healthcare setting.

We used electronic medical records from detentions of 1089 individuals under Section 136 of the UK Mental Health Act (1983 amended 2007), an emergency police power used to detain people for 24–36 h for psychiatric assessment. The relationship between recent cannabinoids and/or stimulant use, psychotic symptoms, and violent behaviour, was estimated using logistic regression.

There was evidence of recent alcohol or drug use in 64.5% of detentions. Violent incidents occurred in 12.6% of detentions. Psychotic symptoms increased the odds of violence by 4.0 [95% confidence intervals (CI) 2.2–7.4; p < 0.0001]. Cannabinoid use combined with psychotic symptoms increased the odds of violence further [odds ratios (OR) 7.1, 95% CI 3.7–13.6; p < 0.0001]. Recent use of cannabinoids with stimulants but without psychotic symptoms was also associated with increased odds of violence (OR 3.3, 95% CI 1.4–7.9; p < 0.0001).

In the emergency setting, patients who have recently used cannabinoids and exhibit psychotic symptoms are at higher risk of violent behaviour. Those who have used both stimulants and cannabinoids without psychotic symptoms may also be at increased risk. De-escalation protocols in emergency healthcare settings should account explicitly for substance use.

Daily use of high-potency cannabis has been reported to carry a high risk for developing a psychotic disorder. However, the evidence is mixed on whether any pattern of cannabis use is associated with a particular symptomatology in first-episode psychosis (FEP) patients.

We analysed data from 901 FEP patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. We used item response modelling to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use were evaluated using linear mixed-effects models analyses.

In patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high-potency cannabis having the highest score (B = 0.35; 95% CI 0.14–0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B = −0.22; 95% CI −0.37 to −0.07). In controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use. Neither patients nor controls presented differences in depressive dimension related to cannabis use.

Our findings provide the first large-scale evidence that FEP patients with a history of daily use of high-potency cannabis present with more positive and less negative symptoms, compared with those who never used cannabis or used low-potency types.

As new cannabis products and administration methods proliferate, patterns of use are becoming increasingly heterogeneous. However, few studies have explored different profiles of cannabis use and their association with problematic use.

Latent class analysis (LCA) was used to identify subgroups of past-year cannabis users endorsing distinct patterns of use from a large international sample (n = 55 240). Past-12-months use of six different cannabis types (sinsemilla, herbal, hashish, concentrates, kief, edibles) were used as latent class indicators. Participants also reported the frequency and amount of cannabis used, whether they had ever received a mental health disorder diagnosis and their cannabis dependence severity via the Severity of Dependence Scale (SDS).

LCA identified seven distinct classes of cannabis use, characterised by high probabilities of using: sinsemilla & herbal (30.3% of the sample); sinsemilla, herbal & hashish (20.4%); herbal (18.4%); hashish & herbal (18.8%); all types (5.7%); edibles & herbal (4.6%) and concentrates & sinsemilla (1.7%). Relative to the herbal class, classes characterised by sinsemilla and/or hashish use had increased dependence severity. By contrast, the classes characterised by concentrates use did not show strong associations with cannabis dependence but reported greater rates of ever receiving a mental health disorder diagnosis.

The identification of these distinct classes underscores heterogeneity among cannabis use behaviours and provides novel insight into their different associations with addiction and mental health.

Gambling disorder (GD), recognized in Diagnostic and Statistical Manual of Mental Disorders, Version 5 (DSM-5) as a behavioral addiction, is associated with a range of adverse outcomes. However, there has been little research on the genetic and environmental influences on the development of this disorder. This study reports results from the largest twin study of GD conducted to date.

Replication and combined analyses were based on samples of 3292 (mean age 31.8, born 1972–79) and 4764 (mean age 37.7, born 1964–71) male, female, and unlike-sex twin pairs from the Australian Twin Registry. Univariate biometric twin models estimated the proportion of variation in the latent GD liability that could be attributed to genetic, shared environmental, and unique environmental factors, and whether these differed quantitatively or qualitatively for men and women.

In the replication study, when using a lower GD threshold, there was evidence for significant genetic (60%; 95% confidence interval (CI) 45–76%) and unique environmental (40%; 95% CI 24–56%), but not shared environmental contributions (0%; 95% CI 0–0%) to GD liability; this did not significantly differ from the original study. In the combined analysis, higher GD thresholds (such as one consistent with DSM-5 GD) and a multiple threshold definitions of GD yielded similar results. There was no evidence for quantitative or qualitative sex differences in the liability for GD.

Twin studies of GD are few in number but they tell a remarkably similar story: substantial genetic and unique environmental influences, with no evidence for shared environmental contributions or sex differences in GD liability.

Prior research has documented shared heritable contributions to non-suicidal self-injury (NSSI) and suicidal ideation (SI) as well as NSSI and suicide attempt (SA). In addition, trauma exposure has been implicated in risk for NSSI and suicide. Genetically informative studies are needed to determine common sources of liability to all three self-injurious thoughts and behaviors, and to clarify the nature of their associations with traumatic experiences.

Multivariate biometric modeling was conducted using data from 9526 twins [59% female, mean age = 31.7 years (range 24–42)] from two cohorts of the Australian Twin Registry, some of whom also participated in the Childhood Trauma Study and the Nicotine Addiction Genetics Project.

The prevalences of high-risk trauma exposure (HRT), NSSI, SI, and SA were 24.4, 5.6, 27.1, and 4.6%, respectively. All phenotypes were moderately to highly correlated. Genetic influences on self-injurious thoughts and behaviors and HRT were significant and highly correlated among men [rG = 0.59, 95% confidence interval (CI) (0.37–0.81)] and women [rG = 0.56 (0.49–0.63)]. Unique environmental influences were modestly correlated in women [rE = 0.23 (0.01–0.45)], suggesting that high-risk trauma may confer some direct risk for self-injurious thoughts and behaviors among females.

Individuals engaging in NSSI are at increased risk for suicide, and common heritable factors contribute to these associations. Preventing trauma exposure may help to mitigate risk for self-harm and suicide, either directly or indirectly via reductions in liability to psychopathology more broadly. In addition, targeting pre-existing vulnerability factors could significantly reduce risk for life-threatening behaviors among those who have experienced trauma.

The genetic component of Cannabis Use Disorder may overlap with influences acting more generally on early stages of cannabis use. This paper aims to determine the extent to which genetic influences on the development of cannabis abuse/dependence are correlated with those acting on the opportunity to use cannabis and frequency of use.

A cross-sectional study of 3303 Australian twins, measuring age of onset of cannabis use opportunity, lifetime frequency of cannabis use, and lifetime DSM-IV cannabis abuse/dependence. A trivariate Cholesky decomposition estimated additive genetic (A), shared environment (C) and unique environment (E) contributions to the opportunity to use cannabis, the frequency of cannabis use, cannabis abuse/dependence, and the extent of overlap between genetic and environmental factors associated with each phenotype.

Variance components estimates were A = 0.64 [95% confidence interval (CI) 0.58–0.70] and E = 0.36 (95% CI 0.29–0.42) for age of opportunity to use cannabis, A = 0.74 (95% CI 0.66–0.80) and E = 0.26 (95% CI 0.20–0.34) for cannabis use frequency, and A = 0.78 (95% CI 0.65–0.88) and E = 0.22 (95% CI 0.12–0.35) for cannabis abuse/dependence. Opportunity shares 45% of genetic influences with the frequency of use, and only 17% of additive genetic influences are unique to abuse/dependence from those acting on opportunity and frequency.

There are significant genetic contributions to lifetime cannabis abuse/dependence, but a large proportion of this overlaps with influences acting on opportunity and frequency of use. Individuals without drug use opportunity are uninformative, and studies of drug use disorders must incorporate individual exposure to accurately identify aetiology.

The number of people entering specialist drug treatment for cannabis problems has increased considerably in recent years. The reasons for this are unclear, but rising cannabis potency could be a contributing factor.

Cannabis potency data were obtained from an ongoing monitoring programme in the Netherlands. We analysed concentrations of δ-9-tetrahydrocannabinol (THC) from the most popular variety of domestic herbal cannabis sold in each retail outlet (2000–2015). Mixed effects linear regression models examined time-dependent associations between THC and first-time cannabis admissions to specialist drug treatment. Candidate time lags were 0–10 years, based on normative European drug treatment data.

THC increased from a mean (95% CI) of 8.62 (7.97–9.27) to 20.38 (19.09–21.67) from 2000 to 2004 and then decreased to 15.31 (14.24–16.38) in 2015. First-time cannabis admissions (per 100 000 inhabitants) rose from 7.08 to 26.36 from 2000 to 2010, and then decreased to 19.82 in 2015. THC was positively associated with treatment entry at lags of 0–9 years, with the strongest association at 5 years, b = 0.370 (0.317–0.424), p < 0.0001. After adjusting for age, sex and non-cannabis drug treatment admissions, these positive associations were attenuated but remained statistically significant at lags of 5–7 years and were again strongest at 5 years, b = 0.082 (0.052–0.111), p < 0.0001.

In this 16-year observational study, we found positive time-dependent associations between changes in cannabis potency and first-time cannabis admissions to drug treatment. These associations are biologically plausible, but their strength after adjustment suggests that other factors are also important.

We investigated the genetic and environmental contributions to covariation between smoking age-at-onset, cigarette consumption and smoking persistence.

Multivariate biometrical modelling methods were applied to questionnaire data from Australian twins and their siblings (14 472 individuals from 6247 families). The contributions of genetic and environmental factors to covariation between the three traits were estimated, allowing for sex differences in both trait prevalence and the magnitude of genetic and environmental effects.

All traits were moderately heritable in males and females (estimates between 0·40 and 0·62), but there were sex differences in the extent to which additive genetic influences were shared across traits. Twin-specific environmental factors accounted for a substantial proportion of the variance in smoking age-at-onset in females (0·19) and males (0·12), but had little influence (<0·08) on other traits. Unique environmental factors were estimated to have a moderate influence on smoking age-at-onset (0·17 for females, 0·19 for males), but a stronger influence on other traits (between 0·39 and 0·49).

These results provide some insight into observed sex differences in smoking behaviour, and suggest that searching for pleiotropic genes may prove fruitful. However, further work on phenotypic definitions of smoking behaviour, particularly persistence, is warranted.