Mapping genomic loci implicates genes and synaptic biology in schizophrenia.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Changes in patterns of age-related network connectivity are associated with risk for schizophrenia.

Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in first-degree relatives of SCZ patients mostly including unaffected siblings (SIB) with neurotypical controls (NC) at the same age stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Two of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.05). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlates with genetic risk for SCZ and is detectable with MRI in young participants.

Sex dimorphism controls dysbindin-related cognitive dysfunctions in mice and humans with the contribution of COMT.

Cognitive dysfunctions are core-enduring symptoms of schizophrenia, with important sex-related differences. Genetic variants of the DTBPN1 gene associated with reduced dysbindin-1 protein (Dys) expression negatively impact cognitive functions in schizophrenia through a functional epistatic interaction with Catechol-O-methyltransferase (COMT). Dys is involved in the trafficking of dopaminergic receptors, crucial for prefrontal cortex (PFC) signaling regulation. Moreover, dopamine signaling is modulated by estrogens via inhibition of COMT expression. We hypothesized a sex dimorphism in Dys-related cognitive functions dependent on COMT and estrogen levels. Our multidisciplinary approach combined behavioral-molecular findings on genetically modified mice, human postmortem Dys expression data, and in vivo fMRI during a working memory task performance. We found cognitive impairments in male mice related to genetic variants characterized by reduced Dys protein expression (pBonferroni = 0.0001), as well as in male humans through a COMT/Dys functional epistatic interaction involving PFC brain activity during working memory (t(23) = -3.21; pFDR = 0.004). Dorsolateral PFC activity was associated with lower working memory performance in males only (p = 0.04). Also, male humans showed decreased Dys expression in dorsolateral PFC during adulthood (pFDR = 0.05). Female Dys mice showed preserved cognitive performances with deficits only with a lack of estrogen tested in an ovariectomy model (pBonferroni = 0.0001), suggesting that genetic variants reducing Dys protein expression could probably become functional in females when the protective effect of estrogens is attenuated, i.e., during menopause. Overall, our results show the differential impact of functional variants of the DTBPN1 gene interacting with COMT on cognitive functions across sexes in mice and humans, underlying the importance of considering sex as a target for patient stratification and precision medicine in schizophrenia.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants.

BACKGROUND: Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity. METHODS: 169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP. RESULTS: Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP. CONCLUSIONS: These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

The interplay between mentalization, personality traits and burnout in psychiatry training: Results from a large multicenter controlled study.

BACKGROUND: A better characterization of educational processes during psychiatry training is needed, both to foster personal resilience and occupational proficiency. METHODS: An adequate coverage of medical residents at the national level was reached (41.86% of the total reference population, 29 out of 36 training centers-80.55%). Controls were recruited among residents in other medical specialties. All participants were assessed by questionnaires to evaluate early life experiences, attachment style, personality traits, coping strategies, emotional competencies. A Structural Equation Model (SEM) framework was employed to investigate the interplay between individual factors. RESULTS: A total sample of 936 people was recruited (87.9% response-rate; 645 residents in psychiatry, 291 other medical residents). Psychiatry trainees reported a higher prevalence of adverse childhood experiences (emotional abuse, emotional neglect, physical neglect), greater attachment insecurity (anxious or avoidant) in comparison to other medical trainees. Psychiatry residents also reported higher social support-seeking as a coping strategy, lower problem-orientation, and lower transcendence. Lower neuroticism, higher openness to experience, and higher emotional awareness were also observed in psychiatry trainees. Psychiatry training was associated with a redefinition of conflict management skills as a function of seniority. The SEM model provided support for an interplay between early traumatic experiences, mentalization skills (coping strategies, emotion regulation), interpersonal competencies and occupational distress. CONCLUSIONS: The findings of the present study supported a theoretical model based on mentalization theory for the interactions between personal and relational competencies in psychiatry training, thus providing potential target of remodulation and redefinition of this specific process of education.

Reduced magnetic mismatch negativity: a shared deficit in psychosis and related risk.

BACKGROUND: Abnormal auditory processing of deviant stimuli, as reflected by mismatch negativity (MMN), is often reported in schizophrenia (SCZ). At present, it is still under debate whether this dysfunctional response is specific to the full-blown SCZ diagnosis or rather a marker of psychosis in general. The present study tested MMN in patients with SCZ, bipolar disorder (BD), first episode of psychosis (FEP), and in people at clinical high risk for psychosis (CHR). METHODS: Source-based MEG activity evoked during a passive auditory oddball task was recorded from 135 patients grouped according to diagnosis (SCZ, BD, FEP, and CHR) and 135 healthy controls also divided into four subgroups, age- and gender-matched with diagnostic subgroups. The magnetic MMN (mMMN) was analyzed as event-related field (ERF), Theta power, and Theta inter-trial phase coherence (ITPC). RESULTS: The clinical group as a whole showed reduced mMMN ERF amplitude, Theta power, and Theta ITPC, without any statistically significant interaction between diagnosis and mMMN reductions. The mMMN subgroup contrasts showed lower ERF amplitude in all the diagnostic subgroups. In the analysis of Theta frequency, SCZ showed significant power and ITPC reductions, while only indications of diminished ITPC were observed in CHR, but no significant decreases characterized BD and FEP. CONCLUSIONS: Significant mMMN alterations in people experiencing psychosis, also for diagnoses other than SCZ, suggest that this neurophysiological response may be a feature shared across psychotic disorders. Additionally, reduced Theta ITPC may be associated with risk for psychosis.

Heritability of amygdala reactivity to angry faces and its replicable association with the schizophrenia risk locus of miR-137.

BACKGROUND: Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia. METHODS: We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI). RESULTS: We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03). LIMITATIONS: The limited sample size available for GWAS analyses may require further replication of results. CONCLUSION: Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137.

Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression.

BACKGROUND: Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning. AIMS: We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample. METHOD: Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD). RESULTS: Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD. CONCLUSIONS: Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

NURR1 and ERR1 Modulate the Expression of Genes of a DRD2 Coexpression Network Enriched for Schizophrenia Risk.

Multiple schizophrenia (SCZ) risk loci may be involved in gene co-regulation mechanisms, and analysis of coexpressed gene networks may help to clarify SCZ molecular basis. We have previously identified a dopamine D2 receptor (DRD2) coexpression module enriched for SCZ risk genes and associated with cognitive and neuroimaging phenotypes of SCZ, as well as with response to treatment with antipsychotics. Here we aimed to identify regulatory factors modulating this coexpression module and their relevance to SCZ. We performed motif enrichment analysis to identify transcription factor (TF) binding sites in human promoters of genes coexpressed with DRD2. Then, we measured transcript levels of a group of these genes in primary mouse cortical neurons in basal conditions and upon overexpression and knockdown of predicted TFs. Finally, we analyzed expression levels of these TFs in dorsolateral prefrontal cortex (DLPFC) of SCZ patients. Our in silico analysis revealed enrichment for NURR1 and ERR1 binding sites. In neuronal cultures, the expression of genes either relevant to SCZ risk (Drd2, Gatad2a, Slc28a1, Cnr1) or indexing coexpression in our module (Btg4, Chit1, Osr1, Gpld1) was significantly modified by gain and loss of Nurr1 and Err1. Postmortem DLPFC expression data analysis showed decreased expression levels of NURR1 and ERR1 in patients with SCZ. For NURR1 such decreased expression is associated with treatment with antipsychotics. Our results show that NURR1 and ERR1 modulate the transcription of DRD2 coexpression partners and support the hypothesis that NURR1 is involved in the response to SCZ treatment.SIGNIFICANCE STATEMENT In the present study, we provide in silico and experimental evidence for a role of the TFs NURR1 and ERR1 in modulating the expression pattern of genes coexpressed with DRD2 in human DLPFC. Notably, genetic variations in these genes is associated with SCZ risk and behavioral and neuroimaging phenotypes of the disease, as well as with response to treatment. Furthermore, this study presents novel findings on a possible interplay between D2 receptor-mediated dopamine signaling involved in treatment with antipsychotics and the transcriptional regulation mechanisms exerted by NURR1. Our results suggest that coexpression and co-regulation mechanisms may help to explain some of the complex biology of genetic associations with SCZ.

A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space.

We propose a novel optimization framework that integrates imaging and genetics data for simultaneous biomarker identification and disease classification. The generative component of our model uses a dictionary learning framework to project the imaging and genetic data into a shared low dimensional space. We have coupled both the data modalities by tying the linear projection coefficients to the same latent space. The discriminative component of our model uses logistic regression on the projection vectors for disease diagnosis. This prediction task implicitly guides our framework to find interpretable biomarkers that are substantially different between a healthy and disease population. We exploit the interconnectedness of different brain regions by incorporating a graph regularization penalty into the joint objective function. We also use a group sparsity penalty to find a representative set of genetic basis vectors that span a low dimensional space where subjects are easily separable between patients and controls. We have evaluated our model on a population study of schizophrenia that includes two task fMRI paradigms and single nucleotide polymorphism (SNP) data. Using ten-fold cross validation, we compare our generative-discriminative framework with canonical correlation analysis (CCA) of imaging and genetics data, parallel independent component analysis (pICA) of imaging and genetics data, random forest (RF) classification, and a linear support vector machine (SVM). We also quantify the reproducibility of the imaging and genetics biomarkers via subsampling. Our framework achieves higher class prediction accuracy and identifies robust biomarkers. Moreover, the implicated brain regions and genetic variants underlie the well documented deficits in schizophrenia.

Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory.

Dopamine D1 receptor (D1R) signaling shapes prefrontal cortex (PFC) activity during working memory (WM). Previous reports found higher WM performance associated with alleles linked to greater expression of the gene coding for D1Rs (DRD1). However, there is no evidence on the relationship between genetic modulation of DRD1 expression in PFC and patterns of prefrontal activity during WM. Furthermore, previous studies have not considered that D1Rs are part of a coregulated molecular environment, which may contribute to D1R-related prefrontal WM processing. Thus, we hypothesized a reciprocal link between a coregulated (i.e., coexpressed) molecular network including DRD1 and PFC activity. To explore this relationship, we used three independent postmortem prefrontal mRNA datasets (total n = 404) to characterize a coexpression network including DRD1 Then, we indexed network coexpression using a measure (polygenic coexpression index-DRD1-PCI) combining the effect of single nucleotide polymorphisms (SNPs) on coexpression. Finally, we associated the DRD1-PCI with WM performance and related brain activity in independent samples of healthy participants (total n = 371). We identified and replicated a coexpression network including DRD1, whose coexpression was correlated with DRD1-PCI. We also found that DRD1-PCI was associated with lower PFC activity and higher WM performance. Behavioral and imaging results were replicated in independent samples. These findings suggest that genetically predicted expression of DRD1 and of its coexpression partners stratifies healthy individuals in terms of WM performance and related prefrontal activity. They also highlight genes and SNPs potentially relevant to pharmacological trials aimed to test cognitive enhancers modulating DRD1 signaling.

Multivariate patterns of gray matter volume in thalamic nuclei are associated with positive schizotypy in healthy individuals.

BACKGROUND: Previous models suggest biological and behavioral continua among healthy individuals (HC), at-risk condition, and full-blown schizophrenia (SCZ). Part of these continua may be captured by schizotypy, which shares subclinical traits and biological phenotypes with SCZ, including thalamic structural abnormalities. In this regard, previous findings have suggested that multivariate volumetric patterns of individual thalamic nuclei discriminate HC from SCZ. These results were obtained using machine learning, which allows case-control classification at the single-subject level. However, machine learning accuracy is usually unsatisfactory possibly due to phenotype heterogeneity. Indeed, a source of misclassification may be related to thalamic structural characteristics of those HC with high schizotypy, which may resemble structural abnormalities of SCZ. We hypothesized that thalamic structural heterogeneity is related to schizotypy, such that high schizotypal burden would implicate misclassification of those HC whose thalamic patterns resemble SCZ abnormalities. METHODS: Following a previous report, we used Random Forests to predict diagnosis in a case-control sample (SCZ = 131, HC = 255) based on thalamic nuclei gray matter volumes estimates. Then, we investigated whether the likelihood to be classified as SCZ (π-SCZ) was associated with schizotypy in 174 HC, evaluated with the Schizotypal Personality Questionnaire. RESULTS: Prediction accuracy was 72.5%. Misclassified HC had higher positive schizotypy scores, which were correlated with π-SCZ. Results were specific to thalamic rather than whole-brain structural features. CONCLUSIONS: These findings strengthen the relevance of thalamic structural abnormalities to SCZ and suggest that multivariate thalamic patterns are correlates of the continuum between schizotypy in HC and the full-blown disease.

The interaction between OXTR rs2268493 and perceived maternal care is associated with amygdala-dorsolateral prefrontal effective connectivity during explicit emotion processing.

Previous studies have indicated a link between socio-emotional processing and the oxytocin receptor. In this regard, a single nucleotide polymorphism in the oxytocin receptor coding gene (OXTR rs2268493) has been linked with lower social functioning, increased risk for autism spectrum disorders (ASDs) and with post-mortem OXTR mRNA expression levels. Indeed, the levels of expression of OXTR in brain regions involved in emotion processing are also associated with maternal care. Furthermore, maternal care has been associated with emotional correlates. Taken together, these previous findings suggest a possible combined effect of rs2268493 and maternal care on emotion-related brain phenotypes. A crucial biological mechanism subtending emotional processing is the amygdala-dorsolateral prefrontal cortex (DLPFC) functional connection. On this basis, our aim was to investigate the interaction between rs2268493 and maternal care on amygdala-DLPFC effective connectivity during emotional evaluation. We characterized through dynamic causal modeling (DCM) patterns of amygdala-DLPFC effective connectivity during explicit emotion processing in healthy controls (HC), profiled based on maternal care and rs2268493 genotype. In the whole sample, right top-down DLPFC-to-amygdala pattern was the most likely directional model of effective connectivity. This pattern of connectivity was the most likely for all rs2268493/maternal care subgroups, except for thymine homozygous (TT)/low maternal care individuals. Here, a right bottom-up amygdala-to-DLPFC was the most likely directional model. These results suggest a gene by environment interaction mediated by the oxytocin receptor on biological phenotypes relevant to emotion processing.

Genetic Variation of a DRD2 Co-expression Network is Associated with Changes in Prefrontal Function After D2 Receptors Stimulation.

Dopamine D2 receptors (D2Rs) contribute to the inverted U-shaped relationship between dopamine signaling and prefrontal function. Genetic networks from post-mortem human brain revealed 84 partner genes co-expressed with DRD2. Moreover, eight functional single nucleotide polymorphisms combined into a polygenic co-expression index (PCI) predicted co-expression of this DRD2 network and were associated with prefrontal function in humans. Here, we investigated the non-linear association of the PCI with behavioral and Working Memory (WM) related brain response to pharmacological D2Rs stimulation. Fifty healthy volunteers took part in a double-blind, placebo-controlled, functional MRI (fMRI) study with bromocriptine and performed the N-Back task. The PCI by drug interaction was significant on both WM behavioral scores (P = 0.046) and related prefrontal activity (all corrected P < 0.05) using a polynomial PCI model. Non-linear responses under placebo were reversed by bromocriptine administration. fMRI results on placebo were replicated in an independent sample of 50 participants who did not receive drug administration (P = 0.034). These results match earlier evidence in non-human primates and confirm the physiological relevance of this DRD2 co-expression network. Results show that in healthy subjects, different alleles evaluated as an ensemble are associated with non-linear prefrontal responses. Therefore, brain response to a dopaminergic drug may depend on a complex system of allelic patterns associated with DRD2 co-expression.

Modelling cognitive loads in schizophrenia by means of new functional dynamic indexes.

Functional connectivity analysis techniques have broadly applied to capture phenomenological aspects of the brain, e.g., by identifying characteristic network topologies for healthy and disease-affected populations, by highlighting several areas important for the global efficiency of the brain during some cognitive processing and at rest. However, most of the known methods for quantifying functional coupling between fMRI time series are focused on linear correlation metrics. In this work, we propose a multidimensional framework to extract multiple descriptors of the dynamic interaction among BOLD signals in their phase space. A set of metrics is extracted from the cross recurrence plots of each couple of signals to form a multilayer connectivity matrix in which each layer is related to a specific complex dynamic phenomenon. The proposed framework is used to characterize functional abnormalities during a working memory task in patients with schizophrenia. Some topological descriptors are then extracted from both multilayer connectivity matrices and the most used Pearson-based connectivity networks to perform a binary classification task of normal controls and patients. The results show that the proposed connectivity model outperforms the statistical correlation-based connectivity in accuracy, sensitivity and specificity. Moreover, the statistical analysis of the selected features highlights that several dynamic metrics could better identify disease-related dynamic states in brain activity than the statistical correlation among physiological signals.

Schizophrenia polygenic risk score predicts mnemonic hippocampal activity.

The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.

FXR1P is a GSK3ß substrate regulating mood and emotion processing.

Inhibition of glycogen synthase kinase 3ß (GSK3ß) is a shared action believed to be involved in the regulation of behavior by psychoactive drugs such as antipsychotics and mood stabilizers. However, little is known about the identity of the substrates through which GSK3ß affects behavior. We identified fragile X mental retardation-related protein 1 (FXR1P), a RNA binding protein associated to genetic risk for schizophrenia, as a substrate for GSK3ß. Phosphorylation of FXR1P by GSK3ß is facilitated by prior phosphorylation by ERK2 and leads to its down-regulation. In contrast, behaviorally effective chronic mood stabilizer treatments in mice inhibit GSK3ß and increase FXR1P levels. In line with this, overexpression of FXR1P in the mouse prefrontal cortex also leads to comparable mood-related responses. Furthermore, functional genetic polymorphisms affecting either FXR1P or GSK3ß gene expression interact to regulate emotional brain responsiveness and stability in humans. These observations uncovered a GSK3ß/FXR1P signaling pathway that contributes to regulating mood and emotion processing. Regulation of FXR1P by GSK3ß also provides a mechanistic framework that may explain how inhibition of GSK3ß can contribute to the regulation of mood by psychoactive drugs in mental illnesses such as bipolar disorder. Moreover, this pathway could potentially be implicated in other biological functions, such as inflammation and cell proliferation, in which FXR1P and GSK3 are known to play a role.

DRD2/AKT1 interaction on D2 c-AMP independent signaling, attentional processing, and response to olanzapine treatment in schizophrenia.

The D2/AKT1/GSK-3ß signaling pathway has been involved in the downstream intracellular effects of dopamine, in the pathophysiology of cognitive deficits and related brain activity in schizophrenia, as well as in response to treatment with antipsychotics. Polymorphisms in the D2 (DRD2 rs1076560) and AKT1 (AKT1 rs1130233) genes have been associated with their respective protein expression and with higher-order cognition and brain function, including attention. Given the strong potential for their relationship, we investigated the interaction of these polymorphisms on multiple molecular and in vivo phenotypes associated with this signaling pathway. We measured AKT1 and GSK-3ß proteins and phosphorylation in human peripheral blood mononuclear cells, functional MRI cingulate response during attentional control, behavioral accuracy during sustained attention, and response to 8 wk of treatment with olanzapine in a total of 190 healthy subjects and 66 patients with schizophrenia. In healthy subjects, we found that the interaction between the T allele of DRD2 rs1076560 and the A allele of AKT1 rs1130233 was associated with reduced AKT1 protein levels and reduced phosphorylation of GSK-3ß, as well as with altered cingulate response and reduced behavioral accuracy during attentional processing. On the other hand, interaction of these two alleles was associated with greater improvement of Positive and Negative Syndrome Scale scores in patients with schizophrenia after treatment with olanzapine. The present results indicate that these functional polymorphisms are epistatically associated with multiple phenotypes of relevance to schizophrenia. Our results also lend support to further investigation of this downstream molecular pathway in the etiology and treatment of this disorder.

The relationship between the resting state functional connectivity and social cognition in schizophrenia: Results from the Italian Network for Research on Psychoses.

Deficits in social cognition (SC) interfere with recovery in schizophrenia (SZ) and may be related to resting state brain connectivity. This study aimed at assessing the alterations in the relationship between resting state functional connectivity and the social-cognitive abilities of patients with SZ compared to healthy subjects. We divided the brain into 246 regions of interest (ROI) following the Human Healthy Volunteers Brainnetome Atlas. For each participant, we calculated the resting-state functional connectivity (rsFC) in terms of degree centrality (DC), which evaluates the total strength of the most powerful coactivations of every ROI with all other ROIs during rest. The rs-DC of the ROIs was correlated with five measures of SC assessing emotion processing and mentalizing in 45 healthy volunteers (HVs) chosen as a normative sample. Then, controlling for symptoms severity, we verified whether these significant associations were altered, i.e., absent or of opposite sign, in 55 patients with SZ. We found five significant differences between SZ patients and HVs: in the patients' group, the correlations between emotion recognition tasks and rsFC of the right entorhinal cortex (R-EC), left superior parietal lobule (L-SPL), right caudal hippocampus (R-c-Hipp), and the right caudal (R-c) and left rostral (L-r) middle temporal gyri (MTG) were lost. An altered resting state functional connectivity of the L-SPL, R-EC, R-c-Hipp, and bilateral MTG in patients with SZ may be associated with impaired emotion recognition. If confirmed, these results may enhance the development of non-invasive brain stimulation interventions targeting those cerebral regions to reduce SC deficit in SZ.

Illness-related variables and abnormalities of resting-state brain activity in schizophrenia.

Background: The development of neuroimaging biomarkers in patients with schizophrenia (SCZ) requires a refined clinical characterization. A limitation of the neuroimaging literature is the partial uptake of progress in characterizing disease-related features, particularly negative symptoms (NS) and cognitive impairment (CI). In the present study, we assessed NS and CI using up-to-date instruments and investigated the associations of abnormalities in brain resting-state (rs)-activity with disease-related features. Methods: Sixty-two community-dwelling SCZ subjects participated in the study. Multiple regression analyses were performed with the rs-activity of nine regions of interest as dependent variables and disease-related features as explanatory variables. Results: Attention/vigilance deficits were negatively associated with dorsal anterior cingulate rs-activity and, together with depression, were positively associated with right dorsolateral prefrontal cortex rs-activity. These deficits and impairment of Reasoning/problem-solving, together with conceptual disorganization, were associated with right inferior parietal lobule and temporal parietal junction rs-activity. Independent of other features, the NS Expressive Deficit domain was associated with the left ventral caudate, while the Motivational Deficit was associated with the dorsal caudate rs-activity. Conclusion: Neurocognitive deficits and the two negative symptom domains are associated with different neural markers. Replications of these findings could foster the identification of clinically actionable biomarkers of poor functional outcomes.