A neurogenetic model for the study of schizophrenia spectrum disorders: The International 22q11.2 Deletion Syndrome Brain Behavior Consortium

Rare copy number variants contribute significantly to the risk for schizophrenia, with the 22q11.2 locus consistently implicated. Individuals with the 22q11.2 deletion syndrome (22q11DS) have an estimated 25-fold increased risk for schizophrenia spectrum disorders, compared to individuals in the general population. The International 22q11DS Brain Behavior Consortium is examining this highly informative neurogenetic syndrome phenotypically and genomically. Here we detail the procedures of the effort to characterize the neuropsychiatric and neurobehavioral phenotypes associated with 22q11DS, focusing on schizophrenia and subthreshold expression of psychosis. The genomic approach includes a combination of whole genome sequencing and genome-wide microarray technologies, allowing the investigation of all possible DNA variation and gene pathways influencing the schizophrenia-relevant phenotypic expression. A phenotypically rich data set provides a psychiatrically well-characterized sample of unprecedented size (n=1,616) that informs the neurobehavioral developmental course of 22q11DS. This combined set of phenotypic and genomic data will enable hypothesis testing to elucidate the mechanisms underlying the pathogenesis of schizophrenia spectrum disorders

Lack of cortico-limbic coupling in bipolar disorder and schizophrenia during emotion regulation

Bipolar disorder (BD) and schizophrenia (Sz) share dysfunction in prefrontal inhibitory brain systems, yet exhibit distinct forms of affective disturbance. We aimed to distinguish these disorders on the basis of differential activation in cortico-limbic pathways during voluntary emotion regulation. Patients with DSM-IV diagnosed Sz (12) or BD-I (13) and 15 healthy control (HC) participants performed a well-established emotion regulation task while undergoing functional magnetic resonance imaging. The task required participants to voluntarily upregulate or downregulate their subjective affect while viewing emotionally negative images or maintain their affective response as a comparison condition. In BD, abnormal overactivity (hyperactivation) occurred in the right ventrolateral prefrontal cortex (VLPFC) during up- and downregulation of negative affect, relative to HC. Among Sz, prefrontal hypoactivation of the right VLPFC occurred during downregulation (opposite to BD), whereas upregulation elicited hyperactivity in the right VLPFC similar to BD. Amygdala activity was significantly related to subjective negative affect in HC and BD, but not Sz. Furthermore, amygdala activity was inversely coupled with the activity in the left PFC during downregulation in HC (r=−0.76), while such coupling did not occur in BD or Sz. These preliminary results indicate that differential cortico-limbic activation can distinguish the clinical groups in line with affective disturbance: BD is characterized by ineffective cortical control over limbic regions during emotion regulation, while Sz is characterized by an apparent failure to engage cortical (hypofrontality) and limbic regions during downregulation

Recognition Profile of Emotions in Natural and Virtual Faces

BACKGROUND: Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. METHODOLOGY/PRINCIPAL FINDINGS: Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. CONCLUSIONS/SIGNIFICANCE: Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications

Comorbid substance abuse and brain morphology in recent-onset psychosis

The aim of the presented study was to compare schizophrenia and schizoaffective patients early in the course of the disease with and without comorbid substance abuse disorder (SUD vs. NSUD) with regard to brain morphology. In a prospective design 41 patients (20 SUD vs. 21 NSUD) diagnosed as recent-onset schizophrenia or schizoaffective disorder consecutively admitted to hospital received standardized psychopathological evaluation (BPRS, SANS, MADRS, CGI, GAF) and MRI scanning with volumetric measurement of superior temporal gyrus (STG), amygdala-hippocampal complex, and cingulum. Patients with SUD (primarily cannabis) were significantly younger, predominantly male and had a lower socioeconomic status. Despite less attentional impairment (SANS subscore) and elevated anxiety/depression (BPRS subscore) in patients with SUD compared to NSUD, no other psychopathological differences could be detected. There were no differences in the assessed temporolimbic brain morphology between the two subgroups. In conclusion, in this study substance abuse in recent-onset psychosis had no effect on brain morphology and the earlier onset of psychosis in patients with comorbid SUD could not be explained by supposed accentuated brain abnormalities in temporolimbic regions

Disordered semantic representation in schizophrenic temporal cortex revealed by neuromagnetic response patterns

BACKGROUND: Loosening of associations and thought disruption are key features of schizophrenic psychopathology. Alterations in neural networks underlying this basic abnormality have not yet been sufficiently identified. Previously, we demonstrated that spatio-temporal clustering of magnetic brain responses to pictorial stimuli map categorical representations in temporal cortex. This result has opened the possibility to quantify associative strength within and across semantic categories in schizophrenic patients. We hypothesized that in contrast to controls, schizophrenic patients exhibit disordered representations of semantic categories. METHODS: The spatio-temporal clusters of brain magnetic activities elicited by object pictures related to super-ordinate (flowers, animals, furniture, clothes) and base-level (e.g. tulip, rose, orchid, sunflower) categories were analysed in the source space for the time epochs 170–210 and 210–450 ms following stimulus onset and were compared between 10 schizophrenic patients and 10 control subjects. RESULTS: Spatio-temporal correlations of responses elicited by base-level concepts and the difference of within vs. across super-ordinate categories were distinctly lower in patients than in controls. Additionally, in contrast to the well-defined categorical representation in control subjects, unsupervised clustering indicated poorly defined representation of semantic categories in patients. Within the patient group, distinctiveness of categorical representation in the temporal cortex was positively related to negative symptoms and tended to be inversely related to positive symptoms. CONCLUSION: Schizophrenic patients show a less organized representation of semantic categories in clusters of magnetic brain responses than healthy adults. This atypical neural network architecture may be a correlate of loosening of associations, promoting positive symptoms

A Genetics-First Approach to Dissecting the Heterogeneity of Autism: Phenotypic Comparison of Autism Risk Copy Number Variants

OBJECTIVE: Certain copy number variants (CNVs) greatly increase the risk of autism. The authors conducted a genetics-first study to investigate whether heterogeneity in the clinical presentation of autism is underpinned by specific genotype-phenotype relationships. METHODS: This international study included 547 individuals (mean age, 12.3 years [SD=4.2], 54% male) who were ascertained on the basis of having a genetic diagnosis of a rare CNV associated with high risk of autism (82 16p11.2 deletion carriers, 50 16p11.2 duplication carriers, 370 22q11.2 deletion carriers, and 45 22q11.2 duplication carriers), as well as 2,027 individuals (mean age, 9.1 years [SD=4.9], 86% male) with autism of heterogeneous etiology. Assessments included the Autism Diagnostic Interview-Revised and IQ testing. RESULTS: The four genetic variant groups differed in autism symptom severity, autism subdomain profile, and IQ profile. However, substantial variability was observed in phenotypic outcome in individual genetic variant groups (74%-97% of the variance, depending on the trait), whereas variability between groups was low (1%-21%, depending on the trait). CNV carriers who met autism criteria were compared with individuals with heterogeneous autism, and a range of profile differences were identified. When clinical cutoff scores were applied, 54% of individuals with one of the four CNVs who did not meet full autism diagnostic criteria had elevated levels of autistic traits. CONCLUSIONS: Many CNV carriers do not meet full diagnostic criteria for autism but nevertheless meet clinical cutoffs for autistic traits. Although profile differences between variants were observed, there is considerable variability in clinical symptoms in the same variant

Treatment Outcome in Patients Receiving Assertive Community Treatment

In an observational study of severely mentally ill patients treated in assertive community treatment (ACT) teams, we investigated how treatment outcome was associated with demographic factors, clinical factors, and motivation for treatment. To determine psychosocial outcome, patients were routinely assessed using the Health of the Nation Outcome Scales (HoNOS). Trends over time were analyzed using a mixed model with repeated measures. The HoNOS total score was modeled as a function of treatment duration and patient-dependent covariates. Data comprised 637 assessments of 139 patients; mean duration of follow-up was 27.4 months (SD = 5.4). Substance abuse, higher age, problems with motivation, and lower educational level were associated with higher HoNOS total scores (i.e., worse outcome). To improve treatment outcome, we recommend better implementation of ACT, and also the implementation of additional programs targeting subgroups which seem to benefit less from ACT

A neurogenetic model for the study of schizophrenia spectrum disorders: The International 22q11.2 Deletion Syndrome Brain Behavior Consortium

Rare copy number variants contribute significantly to the risk for schizophrenia, with the 22q11.2 locus consistently implicated. Individuals with the 22q11.2 deletion syndrome (22q11DS) have an estimated 25-fold increased risk for schizophrenia spectrum disorders, compared to individuals in the general population. The International 22q11DS Brain Behavior Consortium is examining this highly informative neurogenetic syndrome phenotypically and genomically. Here we detail the procedures of the effort to characterize the neuropsychiatric and neurobehavioral phenotypes associated with 22q11DS, focusing on schizophrenia and subthreshold expression of psychosis. The genomic approach includes a combination of whole genome sequencing and genome-wide microarray technologies, allowing the investigation of all possible DNA variation and gene pathways influencing the schizophrenia-relevant phenotypic expression. A phenotypically rich data set provides a psychiatrically well-characterized sample of unprecedented size (n=1,616) that informs the neurobehavioral developmental course of 22q11DS. This combined set of phenotypic and genomic data will enable hypothesis testing to elucidate the mechanisms underlying the pathogenesis of schizophrenia spectrum disorders

The use of Bayesian latent class cluster models to classify patterns of cognitive performance in healthy ageing

The main focus of this study is to illustrate the applicability of latent class analysis in the assessment of cognitive performance profiles during ageing. Principal component analysis (PCA) was used to detect main cognitive dimensions (based on the neurocognitive test variables) and Bayesian latent class analysis (LCA) models (without constraints) were used to explore patterns of cognitive performance among community-dwelling older individuals. Gender, age and number of school years were explored as variables. Three cognitive dimensions were identified: general cognition (MMSE), memory (MEM) and executive (EXEC) function. Based on these, three latent classes of cognitive performance profiles (LC1 to LC3) were identified among the older adults. These classes corresponded to stronger to weaker performance patterns (LC1>LC2>LC3) across all dimensions; each latent class denoted the same hierarchy in the proportion of males, age and number of school years. Bayesian LCA provided a powerful tool to explore cognitive typologies among healthy cognitive agers.The study is integrated in the "Maintaining health in old age through homeostasis (SWITCHBOX)" collaborative project funded by the European Commission FP7 initiative (grant HEALTH-F2-2010-259772). NS and JAP are main team members of the European consortium SWITCHBOX (http://www.switchbox-online.eu/). NCS is supported by a SwitchBox post-doctoral fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript