SUMMARYBackground: A new generation of antipsychotics was introduced over a decade ago for the

Social cognition has become a high priority area for the study of schizophrenia. However, despite developments in this area, progress remains limited by inconsistent terminology and differences in the way social cognition is measured. To address these obstacles, a consensus-building meeting on social cognition in schizophrenia was held at the National Institute of Mental Health in March 2006. Agreement was reached on several points, including definitions of terms, the significance of social cognition for schizophrenia research, and suggestions for future research directions. The importance of translational interdisciplinary research teams was emphasized. The current article presents a summary of these discussions.

Excess mortality in persons with severe mental disorders (SMD) is a major public health challenge that warrants action. The number and scope of truly tested interventions in this area remain limited, and strategies for implementation and scaling up of programmes with a strong evidence base are scarce. Furthermore, the majority of available interventions focus on a single or an otherwise limited number of risk factors. Here we present a multilevel model highlighting risk factors for excess mortality in persons with SMD at the individual, health system and socio-environmental levels. Informed by that model, we describe a comprehensive framework that may be useful for designing, implementing and evaluating interventions and programmes to reduce excess mortality in persons with SMD. This framework includes individual-focused, health system-focused, and community level and policy-focused interventions. Incorporating lessons learned from the multilevel model of risk and the comprehensive intervention framework, we identify priorities for clinical practice, policy and research agendas.

The development of the ICD-11 CDDG over the past decade, based on the principles of clinical utility and global applicability, has been the most broadly international, multilingual, multidisciplinary and participative revision process ever implemented for a classification of mental disorders. Innovations in the ICD-11 include the provision of consistent and systematically characterized information, the adoption of a lifespan approach, and culture-related guidance for each disorder. Dimensional approaches have been incorporated into the classification, particularly for personality disorders and primary psychotic disorders, in ways that are consistent with current evidence, are more compatible with recovery-based approaches, eliminate artificial comorbidity, and more effectively capture changes over time. Here we describe major changes to the structure of the ICD-11 classification of mental disorders as compared to the ICD-10, and the development of two new ICD-11 chapters relevant to mental health practice. We illustrate a set of new categories that have been added to the ICD-11 and present the rationale for their inclusion. Finally, we provide a description of the important changes that have been made in each ICD-11 disorder grouping. This information is intended to be useful for both clinicians and researchers in orienting themselves to the ICD-11 and in preparing for implementation in their own professional contexts.

Context Identification of genes contributing to alcohol dependence will improve our understanding of the mechanisms underlying this disorder. Objective To identify susceptibility genes for alcohol dependence through a genome-wide association study (GWAS) and follow-up study in a population of German male inpatients with an early age at onset. Design The GWAS included 487 male inpatients with DSM-IV alcohol dependence with an age at onset below 28 years and 1,358 population based control individuals. The follow-up study included 1,024 male inpatients and 996 age-matched male controls. All subjects were of German descent. The GWAS tested 524,396 single nucleotide polymorphisms (SNPs). All SNPs with p<10-4 were subjected to the follow-up study. In addition, nominally significant SNPs from those genes that had also shown expression changes in rat brains after chronic alcohol consumption were selected for the follow-up step. Results The GWAS produced 121 SNPs with nominal p<10-4. These, together with 19 additional SNPs from homologs of rat genes showing differential expression, were genotyped in the follow-up sample. Fifteen SNPs showed significant association with the same allele as in the GWAS. In the combined analysis, two closely linked intergenic SNPs met genome-wide significance (rs7590720 p=9.72×10-9; rs1344694 p=1.69×10-8). They are located on chromosome 2q35, a region which has been implicated in linkage studies for alcohol phenotypes. Nine SNPs were located in genes, including CDH13 and ADH1C genes which have been reported to be associated with alcohol dependence. Conclusion This is the first GWAS and follow-up study to identify a genome-wide significant association in alcohol dependence. Further independent studies are required to confirm these findings.

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This paper provides up to date prevalence estimates of mental disorders in Germany derived from a national survey (German Health Interview and Examination Survey for Adults, Mental Health Module [DEGS1-MH]). A nationally representative sample (N = 5318) of the adult (18-79) population was examined by clinically trained interviewers with a modified version of the Composite International Diagnostic Interview (DEGS-CIDI) to assess symptoms, syndromes and diagnoses according to DSM-IV-TR (25 diagnoses covered). Of the participants 27.7% met criteria for at least one mental disorder during the past 12 months, among them 44% with more than one disorder and 22% with three or more diagnoses. Most frequent were anxiety (15.3%), mood (9.3%) and substance use disorders (5.7%). Overall rates for mental disorders were substantially higher in women (33% versus 22% in men), younger age group (18-34: 37% versus 20% in age group 65-79), when living without a partner (37% versus 26% with partnership) or with low (38%) versus high socio-economic status (22%). High degree of urbanization (> 500,000 inhabitants versus < 20,000) was associated with elevated rates of psychotic (5.2% versus 2.5%) and mood disorders (13.9% versus 7.8%). The findings confirm that almost one third of the general population is affected by mental disorders and inform about subsets in the population who are particularly affected.

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