Violent behaviour in early psychosis patients: Can we identify clinical risk profiles?

The objective of this study is to explore, within a sample of early psychosis patients (EPP), if subgroups regarding rate of violent behaviour (VB) against others can be identified on the basis of dynamic risk factors (treatment modifiable characteristics). In a sample of 265 EPP, treated at the Treatment and Early Intervention in Psychosis Program in Lausanne, we conducted a latent-class analysis on the basis of the main dynamic VB risk factors (substance use disorder [SUD], positive symptoms, insight, and impulsivity). VB were restricted to "serious violence" and were assessed through patients self-report, interview with relatives or forensic services and with a standardized instrument. The analysis confirmed the heterogeneity of the sample regarding rate of VB. Patients could be stratified within 4 subgroups, 3 of which were at increased risk of VB. The two groups with the highest rates of VB displayed specific clinical profiles. The first one was characterized by high levels of impulsivity, hostility, positive symptoms and SUD, and the second, by low level of insight and low social functioning. These patterns suggest that significant difficulties in social interaction may contribute to the emergence of aggressive reactions against others. Identification of EPP at increased risk of VB seems possible on the basis of dynamic risk factors. If confirmed prospectively, this could pave the way to the development of preventive strategies and specific interventions

Genetics of self-reported risk-taking behaviour, trans-ethnic consistency and relevance to brain gene expression

Risk-taking behaviour is an important component of several psychiatric disorders, including attention-deficit hyperactivity disorder, schizophrenia and bipolar disorder. Previously, two genetic loci have been associated with self-reported risk taking and significant genetic overlap with psychiatric disorders was identified within a subsample of UK Biobank. Using the white British participants of the full UK Biobank cohort (n = 83,677 risk takers versus 244,662 controls) for our primary analysis, we conducted a genome-wide association study of self-reported risk-taking behaviour. In secondary analyses, we assessed sex-specific effects, trans-ethnic heterogeneity and genetic overlap with psychiatric traits. We also investigated the impact of risk-taking-associated SNPs on both gene expression and structural brain imaging. We identified 10 independent loci for risk-taking behaviour, of which eight were novel and two replicated previous findings. In addition, we found two further sex-specific risk-taking loci. There were strong positive genetic correlations between risk-taking and attention-deficit hyperactivity disorder, bipolar disorder and schizophrenia. Index genetic variants demonstrated effects generally consistent with the discovery analysis in individuals of non-British White, South Asian, African-Caribbean or mixed ethnicity. Polygenic risk scores comprising alleles associated with increased risk taking were associated with lower white matter integrity. Genotype-specific expression pattern analyses highlighted DPYSL5, CGREF1 and C15orf59 as plausible candidate genes. Overall, our findings substantially advance our understanding of the biology of risk-taking behaviour, including the possibility of sex-specific contributions, and reveal consistency across ethnicities. We further highlight several putative novel candidate genes, which may mediate these genetic effects

Structured assessment of violence risk in schizophrenia and other psychiatric disorders: a systematic review of the validity, reliability, and item content of 10 available instruments.

OBJECTIVES: To undertake a systematic review on structured violence risk assessment tools in individuals with schizophrenia. METHODS: A systematic search was conducted from 1990 to 2011 to identify violence risk assessment tools and studies examining their predictive validity. Item content of the identified instruments was analyzed, and areas under the curve (AUC) from the studies were extracted. In addition, an 11-item checklist was developed to assess the utility and psychometric properties of these tools. RESULTS: Ten risk assessment tools designed to predict community violence in psychiatric patients were identified, but only 2 studies reporting predictive validity estimates in patients with schizophrenia were found (median AUC = 0.69; interquartile range = 0.60-0.77). When inclusion criteria was broadened to include studies measuring accuracy for any diagnostic group, mixed evidence of predictive validity was found, with median AUCs ranging from 0.62 to 0.85 depending on the population. Item content included mostly clinical, sociodemographic, and criminal history factors. As only 1 tool included a neurobiological item, a structured review of brain-based and cognitive risk factors for violence was included, and 3 clusters (neurocognitive ability, neurocognitive awareness, and attitudinal cognition) were identified. CONCLUSIONS: While a number of violence risk assessment tools exist that can be used to predict the likelihood of community violence in psychiatric patients, there is currently little direct evidence for their utility in individuals with schizophrenia. In addition, there is large variation in item content between instruments, and further research is necessary to determine whether the inclusion of alternative factors could improve risk assessment