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Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10−6). Novel reciprocal case–control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present. ispartof: Molecular Psychiatry vol:26 issue:8 pages:1-15 ispartof: location:England status: published

The 22q11.2 deletion syndrome (22q11.2DS) results from non-allelic homologous recombination between low-copy repeats termed LCR22. About 60%-70% of individuals with the typical 3 megabase (Mb) deletion from LCR22A-D have congenital heart disease, mostly of the conotruncal type (CTD), whereas others have normal cardiac anatomy. In this study, we tested whether variants in the hemizygous LCR22A-D region are associated with risk for CTDs on the basis of the sequence of the 22q11.2 region from 1,053 22q11.2DS individuals. We found a significant association (FDR p < 0.05) of the CTD subset with 62 common variants in a single linkage disequilibrium (LD) block in a 350 kb interval harboring CRKL. A total of 45 of the 62 variants were associated with increased risk for CTDs (odds ratio [OR) ranges: 1.64-4.75). Associations of four variants were replicated in a meta-analysis of three genome-wide association studies of CTDs in affected individuals without 22q11.2DS. One of the replicated variants, rs178252, is located in an open chromatin region and resides in the double-elite enhancer, GH22J020947, that is predicted to regulate CRKL (CRK-like proto-oncogene, cytoplasmic adaptor) expression. Approximately 23% of patients with nested LCR22C-D deletions have CTDs, and inactivation of Crkl in mice causes CTDs, thus implicating this gene as a modifier. Rs178252 and rs6004160 are expression quantitative trait loci (eQTLs) of CRKL. Furthermore, set-based tests identified an enhancer that is predicted to target CRKL and is significantly associated with CTD risk (GH22J020946, sequence kernal association test (SKAT) p = 7.21 × 10-5) in the 22q11.2DS cohort. These findings suggest that variance in CTD penetrance in the 22q11.2DS population can be explained in part by variants affecting CRKL expression. ispartof: AMERICAN JOURNAL OF HUMAN GENETICS vol:106 issue:1 pages:26-40 ispartof: location:United States status: published

Background22q11.2 deletion syndrome (22q11.2DS) is considered as the genetic model of schizophrenia. However, its polymorphic nature has led researchers to further investigate its neuropsychiatric manifestations.MethodsWe enrolled 56 adults (38 men, 18 women) diagnosed with 22q11.2DS. All subjects were evaluated by a multidisciplinary team. The neuropsychiatric features were investigated by means of clinical and neurophysiological evaluation (video-EEG).ResultsThirty per cent of our patients were left-handed. Fifty-eight per cent had a low IQ, and 22 of 56 subjects had psychotic disorders (13 of 22 with schizophrenia). Eighteen patients reported at least one seizure in their lifetime, and ten were diagnosed with epilepsy; among them, seven had genetic generalised epilepsy (GGE), and five of seven showed features suggestive of juvenile myoclonic epilepsy (JME). Video-EEG recordings revealed generalised epileptiform abnormalities in 24 of 56 cases. Besides, only one patient with epilepsy had a cardiac malformation. Lastly, 31 of 56 subjects presented with parkinsonism, 16 of whom were taking neuroleptics. None of the 15 patients with parkinsonism not related to neuroleptic therapy was diagnosed with epilepsy, compared with 6 of those taking antipsychotics.Conclusions22q11.2DS is characterised by left-handedness and neuropsychiatric features such as cognitive impairment, schizophrenia, epilepsy and parkinsonism. GGE, mostly the JME phenotype, is the predominant epilepsy type. The significant association between 22q11.2DS and parkinsonian features confirms these patients’ genetic susceptibility to parkinsonism. Despite the lack of any conclusive evidence, our study suggests a possible relationship between the analysed clinical variables: (1) an inverse correlation between low IQ/psychosis/epilepsy and major cardiac diseases; (2) a direct association between psychosis and both mental delay and epilepsy; and (3) an inverse correlation between parkinsonism and epilepsy.

22q11.2 microdeletion syndrome (22q11DS) is associated with a 25% risk of psychotic onset.The sample consist of 120 subjects: 39 schizophrenics (SCZ); 20 siblings of schizophrenic patients (SIB); 34 22q11DS non-psychotic patients (DEL); 17 22q11DS psychotic patients (DEL_scz); 30 control subjects (CS). Social cognition was evaluated with the awareness of social interference test. Intelligence Quotient (IQ) was calculated with Wechsler Adult Intelligence Scale. TASIT (Awareness of Social Inference Test) performance was analyzed via MANOVA, including IQ as covariate.Group and IQ showed significant effect (p0.001; p = 0.037). The only TASIT variables where IQ showed no effect were paradoxical sarcasm; sincerity; lie. In sincerity, CS group shows a better performance than both 22q11DS groups (p0.05). In paradoxical sarcasm and lie, CS group performed better than each clinical group (p0.05). Regarding lie, DEL group was worst also respect to SCZ group (p = 0.029).Our results show a specific social cognition deficit in 22q11DS and schizophrenia.

Importance Enhanced understanding of factors associated with symptomatic and functional recovery is instrumental to designing personalized treatment plans for people with schizophrenia. To date, this is the first study using network analysis to investigate the associations among cognitive, psychopathologic, and psychosocial variables in a large sample of community-dwelling individuals with schizophrenia. Objective To assess the interplay among psychopathologic variables, cognitive dysfunctions, functional capacity, personal resources, perceived stigma, and real-life functioning in individuals with schizophrenia, using a data-driven approach. Design, Setting, and Participants This multicenter, cross-sectional study involved 26 university psychiatric clinics and/or mental health departments. A total of 921 community-dwelling individuals with a DSM-IV diagnosis of schizophrenia who were stabilized on antipsychotic treatment were recruited from those consecutively presenting to the outpatient units of the sites between March 1, 2012, and September 30, 2013. Statistical analysis was conducted between July 1 and September 30, 2017. Main Outcomes and Measures Measures covered psychopathologic variables, neurocognition, social cognition, functional capacity, real-life functioning, resilience, perceived stigma, incentives, and service engagement. Results Of 740 patients (221 women and 519 men; mean [SD] age, 40.0 [10.9] years) with complete data on the 27 study measures, 163 (22.0%) were remitted (with a score of mild or better on 8 core symptoms). The network analysis showed that functional capacity and everyday life skills were the most central and highly interconnected nodes in the network. Psychopathologic variables split in 2 domains, with positive symptoms being one of the most peripheral and least connected nodes. Functional capacity bridged cognition with everyday life skills; the everyday life skills node was connected to disorganization and expressive deficits. Interpersonal relationships and work skills were connected to avolition; the interpersonal relationships node was also linked to social competence, and the work skills node was linked to social incentives and engagement with mental health services. A case-dropping bootstrap procedure showed centrality indices correlations of 0.75 or greater between the original and randomly defined samples up to 481 of 740 case-dropping (65.0%). No difference in the network structure was found between men and women. Conclusions and Relevance The high centrality of functional capacity and everyday life skills in the network suggests that improving the ability to perform tasks relevant to everyday life is critical for any therapeutic intervention in schizophrenia. The pattern of network node connections supports the implementation of personalized interventions.

BackgroundThe increased use of the MATRICS Consensus Cognitive Battery (MCCB) to investigate cognitive dysfunctions in schizophrenia fostered interest in its sensitivity in the context of family studies. As various measures of the same cognitive domains may have different power to distinguish between unaffected relatives of patients and controls, the relative sensitivity of MCCB tests for relative–control differences has to be established. We compared MCCB scores of 852 outpatients with schizophrenia (SCZ) with those of 342 unaffected relatives (REL) and a normative Italian sample of 774 healthy subjects (HCS). We examined familial aggregation of cognitive impairment by investigating within-family prediction of MCCB scores based on probands’ scores.MethodsMultivariate analysis of variance was used to analyze group differences in adjusted MCCB scores. Weighted least-squares analysis was used to investigate whether probands’ MCCB scores predicted REL neurocognitive performance.ResultsSCZ were significantly impaired on all MCCB domains. REL had intermediate scores between SCZ and HCS, showing a similar pattern of impairment, except for social cognition. Proband's scores significantly predicted REL MCCB scores on all domains except for visual learning.ConclusionsIn a large sample of stable patients with schizophrenia, living in the community, and in their unaffected relatives, MCCB demonstrated sensitivity to cognitive deficits in both groups. Our findings of significant within-family prediction of MCCB scores might reflect disease-related genetic or environmental factors.

Self-reported 'personal recovery' and clinical recovery in schizophrenia (SRPR and CR. respectively) reflect different perspectives in schizophrenia outcome, not necessarily concordant with each other and usually representing the consumer's or the therapist's point of view. By means of a cluster analysis on SRPR related variables, we identified three dusters. The first and third cluster included subjects with the best and the poorest clinical outcome respectively. The second cluster was characterized by better insight, higher levels of depression and stigma, lowest self-esteem and personal strength, and highest emotional coping. The first duster showed positive features of recovery, while the third duster showed negative features. The second cluster, with the most positive insight, showed a more complex pattern, a some-what 'paradoxical' mixture of positive and negative personal and clinical features of recovery. The present results suggest the need for a characterization of persons with schizophrenia along SRPR and CR dimensions to design individualized and integrated treatment programs aimed to improve insight and coping strategies, reduce stigma and shape recovery styles. (C) 2017 Elsevier B.V. All rights reserved.

Background 22q11DS is the most common microdeletion with an incidence of 1:4000 live births. It is considered a genetic biological model for psychosis vulnerability: 25–28% of 22q11DS adults is affected by a psychotic disorder. Few data are available regarding functioning in 22q11DS. Our aim was to test the hypothesis that functioning is similar in 22q11DS psychotic and non-psychotic patients, and idiopathic schizophrenic subjects. We expected also a correlation between negative symptoms and functioning. Methods Data come from Italian Network for Research on Psychoses for the Schizophrenic (SCZ, N=252) and Control groups (HC, N=110). 22q11DS psychotic (22q11DS_SCZ, N=21) and non-psychotic patients (22q11DS, N=23) were enrolled at Policlinico Umberto I, in Rome. The SLOF scale (Specific Levels of Functioning) and the Brief Negative Symptom Scale interview (BNSS) were employed. Results The Global Functioning was significantly different between all groups but not between 22q11DS groups and SCZ. The multivariate analysis of variance showed the higher effect size for the Interpersonal Functioning, in which differences resulted significant between all groups, except for the comparison between 22q11DS-SCZ and SCZ. Differences between groups in BNSS were significant except for the post-hoc 22q11DS-SCZ vs SCZ. Global and Interpersonal Functioning showed a significant negative correlation with BNSS scores in the three clinical groups. Discussion 22q11DS-SCZ showed a severe deficit in Interpersonal Functioning, similar to that of idiopathic schizophrenia. 22q11DS showed a deficit in Interpersonal Functioning respect to control group, but less severe than psychotic groups. Our data suggest a common impairment shared among the clinical groups, that may be the functional correlate of an underlying neurobiological mechanism.

Background 22q11DS is the most important genetic risk factor for schizophrenia: up to 28% of these subjects develop psychosis in adulthood. At present this syndrome represents the strongest biological model to investigate neurobiological underpinnings of schizophrenia. We expected Theory of Mind impairments in subjects at risk for psychosis (22q11DS) and more severe impairments in subjects with an established psychotic disorder. Furthermore we sought to investigate eventual correlations between social cognition and self-esteem levels, hypothesizing that both would be impaired in psychotic groups. Methods Data come from Italian Network for Research on Psychoses for the Schizophrenic (SCZ, N=260) and Control groups (HC, N=111). 22q11DS psychotic (22q11DS_SCZ, N=17) and non-psychotic patients (22q11DS, N=46) were enrolled at Policlinico Umberto I, in Rome. The Awareness and Social Inference Test (TASIT) and Self-Esteem Rating Scale (SERS) were administered. Results The three main TASIT variables, Emotion Recognition, Minimal Social Inference and Enriched Social Inference, showed no different scores between the three clinical groups, which were significantly lower respect to the control group. The SERS total score showed no significant differences between clinical groups but was for all three significantly lower than control group score. No significant correlation was observed between SERS and TASIT scores for clinical groups. Discussion Social Cognition impairments are present in 22q11DS at the same extent as in idiopathic schizophrenia, and thus they represent an endophenotype of psychosis. A low Self-Esteem, even though associated to psychosis, does not affect neurocognitive process, impaired on a neurobiological basis.

Vertical ionization potentials (IPs) computed using the IP-EOMCCSD method are reported for 53 medium sized molecules (6 – 32 atoms) and compared with average experimental vertical IPs. The calculations are practical on a modest computational cluster and yield good agreement with experimental values using the aug-cc-pVDZ basis set, with an average deviation from the experimental IP of −0.04 eV. The accuracy of IP computations appears to be approaching the point where possible systematic experimental errors can be identified. Although good extrapolations to the complete basis set limit for the IP are achievable using just the aug-cc-pVDZ and aug-cc-pVTZ basis sets, deviations of the extrapolation from experimental values suggest that inclusion of higher order "triples" may make the computational method more broadly applicable. Examination of experimental spectra for ethylene, E-2-butene, 2,5-dihydrofuran and pyrrole reinforces the observations of Davidson and Jarzęcki1 that experimental vertical IPs are usually extracted from experimental data in a manner that does not account for band asymmetries, making direct comparison to computations difficult. Despite the good agreement with experiment when using the aug-cc-pVDZ basis set, for the molecules investigated most of these reported experimental IPs are below the actual value, likely by no more than 0.4 eV. This set of 53 molecules is recommended as a benchmark comparison set for computational and experimental IP results.

Depression in schizophrenia represents a challenge from a diagnostic, psychopathological and therapeutic perspective. The objective of this study is to test the hypothesis that resilience and self-stigma affect depression severity and to evaluate the strength of their relations in 921 patients with schizophrenia. A structural equation model was tested where depression is hypothesized as affected by resilience, internalized stigma, gender and negative symptoms, with the latter two variables used as exogenous covariates and the former two as mediators. The analysis reveals that low resilience, high negative symptoms, female gender were directly associated with depression severity, and internalized stigma acted only as a mediator between avolition and resilience, with similar magnitude. The cross-sectional study design and the variable selection limit the generalizability of the study results. The model supports a complex interaction between personal resources and negative symptoms in predicting depression in schizophrenia. The clinical implication of these findings is that personal resources could be a significant target of psychosocial treatments.

In people suffering from schizophrenia, major areas of everyday life are impaired, including independent living, productive activities and social relationships. Enhanced understanding of factors that hinder real-life functioning is vital for treatments to translate into more positive outcomes. The goal of the present study was to identify predictors of real-life functioning in people with schizophrenia, and to assess their relative contribution. Based on previous literature and clinical experience, several factors were selected and grouped into three categories: illness-related variables, personal resources and context-related factors. Some of these variables were never investigated before in relationship with real-life functioning. In 921 patients with schizophrenia living in the community, we found that variables relevant to the disease, personal resources and social context explain 53.8% of real-life functioning variance in a structural equation model. Neurocognition exhibited the strongest, though indirect, association with real-life functioning. Positive symptoms and disorganization, as well as avolition, proved to have significant direct and indirect effects, while depression had no significant association and poor emotional expression was only indirectly and weakly related to real-life functioning. Availability of a disability pension and access to social and family incentives also showed a significant direct association with functioning. Social cognition, functional capacity, resilience, internalized stigma and engagement with mental health services served as mediators. The observed complex associations among investigated predictors, mediators and real-life functioning strongly suggest that integrated and personalized programs should be provided as standard treatment to people with schizophrenia. In people suffering from schizophrenia, major areas of everyday life are impaired, including independent living, productive activities and social relationships. Enhanced understanding of factors that hinder real-life functioning is vital for treatments to translate into more positive outcomes. The goal of the present study was to identify predictors of real-life functioning in people with schizophrenia, and to assess their relative contribution. Based on previous literature and clinical experience, several factors were selected and grouped into three categories: illness-related variables, personal resources and context-related factors. Some of these variables were never investigated before in relationship with real-life functioning. In 921 patients with schizophrenia living in the community, we found that variables relevant to the disease, personal resources and social context explain 53.8% of real-life functioning variance in a structural equation model. Neurocognition exhibited the strongest, though indirect, association with real-life functioning. Positive symptoms and disorganization, as well as avolition, proved to have significant direct and indirect effects, while depression had no significant association and poor emotional expression was only indirectly and weakly related to real-life functioning. Availability of a disability pension and access to social and family incentives also showed a significant direct association with functioning. Social cognition, functional capacity, resilience, internalized stigma and engagement with mental health services served as mediators. The observed complex associations among investigated predictors, mediators and real-life functioning strongly suggest that integrated and personalized programs should be provided as standard treatment to people with schizophrenia.

The study of network theory is nothing new, as we may find the first example of a proof of network theory back in the 18th century. However, in recent times, many researchers are using their time to investigate networks, giving new life to an old topic. As we are living in the era of information, networks are everywhere, and their complexity is constantly rising. The field of complex networks attempts to address this complexity with innovative solutions. Complex networks all share a series of common topological features, which revolve around the relationship between nodes, where relationship is intended in the most abstract possible way. Nonetheless, it is important to study these relationships because they can be exploited in several scenarios, like web page searching, recommender systems, e-commerce and so on. This thesis presents studies of sociality in complex networks, ranging from the microscale, which focuses the attention on the point of view of single nodes, to the mesoscale, instead shifts the interest in node groups.

In network science, there is often the need to sort the graph nodes. While the sorting strategy may be different, in general sorting is performed by exploiting the network structure. In particular, the metric PageRank has been used in the past decade in different ways to produce a ranking based on how many neighbors point to a specific node. PageRank is simple, easy to compute and effective in many applications, however it comes with a price: as PageRank is an application of the random walker, the arc weights need to be normalized. This normalization, while necessary, introduces a series of unwanted side-effects. In this paper, we propose a generalization of PageRank named Black Hole Metric which mitigates the problem. We devise a scenario in which the side-effects are particularily impactful on the ranking, test the new metric in both real and synthetic networks, and show the results., 21 pages, 7 figures

22q11.2 deletion syndrome (22q11.2 DS) is widely known as one of the most compelling genetic models of schizophrenia so far, being almost 40% of the carriers affected by psychotic symptoms. Moreover, most of these subjects also show impairment in social cognition, which is a comprehensive array of function that guides social interaction with the others, leading as well to the acquisition of new cognitive and social skills. In the last decade researchers have argued whether social cognition dysfunctions could be underlined by specific genetic alterations, and whether these are linked to specific clinical features. Some valid candidate genes are RTN4R, that encodes a protein which inhibits axonal sprouting, DGCR8, crucial in mRNA processing, or catechol-O-methyltransferase (COMT) and proline oxydase 1 (PRODH), involved in catecholamine metabolism in frontal cortex. This is the first article to address the topic of social cognition in 22q11.2 DS from a wide perspective, with a highlight on its genetic characteristics. We will provide a narrative review of the most recent findings and we will point out new directions on this research path, in order to achieve an effective characterization of the neurobiological system underlying social behavior.

none 28 no BACKGROUND: The study aimed to subtype patients with schizophrenia on the basis of social cognition (SC), and to identify cut-offs that best discriminate among subtypes in 809 out-patients recruited in the context of the Italian Network for Research on Psychoses. METHOD: A two-step cluster analysis of The Awareness of Social Inference Test (TASIT), the Facial Emotion Identification Test and Mayer-Salovey-Caruso Emotional Intelligence Test scores was performed. Classification and regression tree analysis was used to identify the cut-offs of variables that best discriminated among clusters. RESULTS: We identified three clusters, characterized by unimpaired (42%), impaired (50.4%) and very impaired (7.5%) SC. Three theory-of-mind domains were more important for the cluster definition as compared with emotion perception and emotional intelligence. Patients more able to understand simple sarcasm (⩾14 for TASIT-SS) were very likely to belong to the unimpaired SC cluster. Compared with patients in the impaired SC cluster, those in the very impaired SC cluster performed significantly worse in lie scenes (TASIT-LI

Ordering nodes by rank is a benchmark used in several contexts, from recommendation-based trust networks to e-commerce, search engines and websites ranking. In these scenarios, the node rank depends on the set of links the node establishes, hence it becomes important to choose appropriately the nodes to connect to. The problem of finding which nodes to connect to in order to achieve the best possible rank is known as the best attachment problem. Since in the general case the best attachment problem is NP-hard, in this work we propose heuristics that produce near-optimal results while being computable in polynomial time; simulations on different networks show that our proposals preserve both effectiveness and feasibility in obtaining the best rank.

Although the problem of partition quality evaluation is well-known in literature, most of the traditional approaches involve the application of a model built upon a theoretical foundation and then applied to real data. Conversely, this work presents a novel approach: it extracts a model from a network which partition in ground-truth communities is known, so that it can be used in other contexts. The extracted model takes the form of a validation function, which is a function that assigns a score to a specific partition of a network: the closer the partition is to the optimal, the better the score. In order to obtain a suitable validation function, we make use of genetic programming, an application of genetic algorithms where the individuals of a population are computer programs. In this paper we present a computationally feasible methodology to set up the genetic programming run, and show our design choices for the terminal set, function set, fitness function and control parameters.

User-Generated Content characterizes the interactions between companyand customers. Comments and contributions provided by customersin social media platforms represent a relevant input for companies'marketing decisions. A firm cannot avoid this interaction with its customerswithin social media. Any firm is already part of spontaneous onlineconversations that cannot be managed by the company. Social mediarepresent an opportunity for Small-Medium Enterprises, which canreach a wide audience of prospects with a small communication budget.This opportunity can be caught if the company is able to measure itscommunication strategy in a social media platform. The article presentsa model to measure and analyze the interactions between a companyand social media users. The model classifies the interaction accordingto some parameters, such as an index of intensity and quality of thediscussion. Starting from these parameters, the management can drawsome hints about the effectiveness of communication in a social mediaplatform. To verify the mentioned model, it has been applied to the interactionsof an entrepreneur in newsgroups and Facebook. The indexesallow to identify some critical points in the communication process andto have suggestions on how to improve it.

In a retrospective investigation performed in the department of Surgical Odontostomatology of Palermo University Polyclinic from 1997-2006, the authors examined 12 cases of cervico-facial actinomycosis, taking into consideration age range, gender distribution, predisposing factors and symptoms. In concordance with reports in literature, they found that the disease was perimandibular in 65%, they also report the diagnostic methods and therapeutic approaches used in the study.

Virtual interaction with strangers often makes use of underlying trust networks. Usually, existing proposals address the evaluation of global (unique) trust for a given node within the network. In this paper we discuss about how to assess the local (direct) trust a node receives from each of his neighbors. Our proposal is social-based and takes into account both positive and negative experiences as well as the history of past feedbacks, ensuring good stability also when a node receives hundreds of positive feedbacks briefly followed by few negative feedbacks. In order to highlight the stability of this approach we performed several simulations with different networks.