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.

The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease

There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson’s disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain’s neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in de novo PD patients. To this end, we used MRI, SPECT, and clinical data of de novo drug-naïve PD patients (n = 205, mean age 61 ± 10) and age-, sex-matched healthy controls (n = 105, mean age 58 ± 12) acquired at baseline. Moreover, we employed clinical data acquired at 1 year follow-up for PD patients with or without L-Dopa treatment in order to predict the progression symptoms severity. Voxel-based group comparisons and covariance analyses were applied to characterize baseline disease-related alterations for DAT-SPECT, DTI, and sMRI. Cortical and subcortical alterations in de novo PD patients were found in all evaluated imaging modalities, in line with previously reported midbrain-striato-cortical network alterations. The combination of these imaging alterations was reliably linked to clinical severity and disease progression at 1 year follow-up in this patient population, providing evidence for the potential use of these modalities as imaging biomarkers for disease severity and prognosis that can be integrated into clinical trials.

Association of a Noncoding RNA Postmortem With Suicide by Violent Means and In Vivo With Aggressive Phenotypes

BACKGROUND

Previous findings suggest that differences in brain expression of a human-specific long intergenic noncoding RNA (LINC01268; GRCh37/hg19: LOC285758) may be linked to suicide by violent methods. We sought to replicate and extend these findings in a new sample and translate the results to the behavioral level in living healthy subjects.

METHODS

We examined RNA sequencing data in human brains to confirm the prior postmortem association of the long intergenic noncoding RNA specifically with suicide by violent means. In addition, we used a genetic variant associated with LINC01268 expression to detect association in healthy subjects with trait aggression and with in vivo prefrontal physiology related to behavioral control. Finally, we performed weighted gene coexpression network analysis and gene ontology analysis to identify biological processes associated with a LINC01268 coexpression network.

RESULTS

In the replication sample, prefrontal expression of LINC01268 was again higher in suicides by violent means (n = 65) than in both nonsuicides (n = 78; p = 1.29 × 10^-6) and suicides by nonviolent means (n = 46; p = 1.4 × 10^-6). In the living cohort, carriers of the minor allele of a single nucleotide polymorphism associated with increased LINC01268 expression in brain scored higher on a lifetime aggression questionnaire and show diminished engagement of prefrontal cortex (Brodmann area 10) when viewing angry faces during functional magnetic resonance imaging. Weighted gene coexpression network analysis highlighted the immune response.

CONCLUSIONS

These results suggest that LINC01268 influences emotional regulation, aggressive behavior, and suicide by violent means; the underlying biological dynamics may include modulation of genes potentially engaged in the immune response.

Cross-cultural Validation of the 5-Factor Structure of Negative Symptoms in Schizophrenia

OBJECTIVE

Negative symptoms are currently viewed as having a 2-dimensional structure, with factors reflecting diminished expression (EXP) and motivation and pleasure (MAP). However, several factor-analytic studies suggest that the consensus around a 2-dimensional model is premature. The current study investigated and cross-culturally validated the factorial structure of BNSS-rated negative symptoms across a range of cultures and languages.

METHOD

Participants included individuals diagnosed with a psychotic disorder who had been rated on the Brief Negative Symptom Scale (BNSS) from 5 cross-cultural samples, with a total N = 1691. First, exploratory factor analysis was used to extract up to 6 factors from the data. Next, confirmatory factor analysis evaluated the fit of 5 models: (1) a 1-factor model, 2) a 2-factor model with factors of MAP and EXP, 3) a 3-factor model with inner world, external, and alogia factors; 4) a 5-factor model with separate factors for blunted affect, alogia, anhedonia, avolition, and asociality, and 5) a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 aforementioned domains.

RESULTS

Models with 4 factors or less were mediocre fits to the data. The 5-factor, 6-factor, and the hierarchical second-order 5-factor models provided excellent fit with an edge to the 5-factor model. The 5-factor structure demonstrated invariance across study samples.

CONCLUSIONS

Findings support the validity of the 5-factor structure of BNSS-rated negative symptoms across diverse cultures and languages. These findings have important implications for the diagnosis, assessment, and treatment of negative symptoms.

Patients with autism spectrum disorders display reproducible functional connectivity alterations

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

Assessment of de novo copy-number variations in Italian patients with schizophrenia: Detection of putative mutations involving regulatory enhancer elements

OBJECTIVES

Variants appearing de novo in genes regulating key neurodevelopmental processes and/or in non-coding cis-regulatory elements (CREs), as enhancers, may increase the risk for schizophrenia. However, CREs involvement in schizophrenia needs to be explored more deeply.

METHODS

We investigated de novo copy-number variations (CNVs) in the whole-genomic DNA obtained from 46 family trios of schizophrenia probands by using the Enhancer Chip, a customised array CGH able to investigate the whole genome with a 300-kb resolution, specific disease loci at a ten-fold higher resolution, and which was highly enriched in probes in more than 1,250 enhancer elements selected from Vista Enhancer Browser.

RESULTS

In seven patients, we found de novo CNVs, two of which overlapped VISTA enhancer elements. De novo CNVs encompass genes (CNTNAP2, MAGI1, TSPAN7 and MET) involved in brain development, while that involving the enhancer element hs1043, also includes ZIC1, which plays a role in neural development and is responsible of behavioural abnormalities in Zic mutant mice.

CONCLUSIONS

These findings provide further evidence for the involvement of de novo CNVs in the pathogenesis of schizophrenia and suggest that CNVs affecting regulatory enhancer elements could contribute to the genetic vulnerability to the disorder.

Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.

Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

BACKGROUND

The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.

METHODS

The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.

RESULTS

Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.

CONCLUSIONS

The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Progressive Decline in Gray and White Matter Integrity in de novo Parkinson's Disease: An Analysis of Longitudinal Parkinson Progression Markers Initiative Diffusion Tensor Imaging Data

Background: Progressive neuronal loss in neurodegenerative diseases such as Parkinson's disease (PD) is associated with progressive degeneration of associated white matter tracts as measured by diffusion tensor imaging (DTI). These findings may have diagnostic and functional implications but their value in de novo PD remains unknown. Here we analyzed longitudinal DTI data from Parkinson's Progression Markers Initiative de novo PD patients for changes over time relative to healthy control (HC) participants. Methods: Baseline and 1-year follow-up DTI MRI data from 71 PD patients and 45 HC PPMI participants were included in the analyses. Whole-brain fractional anisotropy (FA) and mean diffusivity (MD) images were compared for baseline group differences and group-by-time interactions. Baseline and 1-year changes in DTI values were correlated with changes in DTI measures and symptom severity, respectively. Results: At baseline, PD patients showed significantly increased FA in brainstem, cerebellar, anterior corpus callosal, inferior frontal and inferior fronto-occipital white matter and increased MD in primary sensorimotor and supplementary motor regions. Over 1 year PD patients showed a significantly stronger decline in FA compared to HC in the optic radiation and corpus callosum and parietal, occipital, posterior temporal, posterior thalamic, and vermis gray matter. Significant increases in MD were observed in white matter of the midbrain, optic radiation and corpus callosum, while gray matter of prefrontal, insular and posterior thalamic regions. Baseline brainstem FA white matter (WM) values predicted 1-year changes in FA white matter and MD gray matter values. White but not gray matter changes in both FA and MD were significantly associated with changes in symptom severity. Conclusion: Significant gray and white matter DTI alterations are observable at the time of PD diagnosis and expand in the first year of de novo PD to other cortical and white matter regions. This pattern of DTI changes is in line with preclinical and neuroanatomical studies suggesting that the increased spatial spread of alpha-synuclein neuropathology is the key mechanism of PD progression. Taken together, these findings suggest that DTI may serve as a sensitive biomarker of disease progression in early-stage PD.

Premorbid academic and social functioning in patients with schizophrenia and its associations with negative symptoms and cognition

OBJECTIVE

The study aimed to explore premorbid academic and social functioning in patients with schizophrenia, and its associations with the severity of negative symptoms and neurocognitive impairment.

METHOD

Premorbid adjustment (PA) in patients with schizophrenia was compared to early adjustment in unaffected first-degree relatives and healthy controls. Its associations with psychopathology, cognition, and real-life functioning were investigated. The associations of PA with primary negative symptoms and their two factors were explored.

RESULTS

We found an impairment of academic and social PA in patients (P ≤ 0.000001) and an impairment of academic aspects of early adjustment in relatives (P ≤ 0.01). Patients with poor PA showed greater severity of negative symptoms (limited to avolition after excluding the effect of depression/parkinsonism), working memory, social cognition, and real-life functioning (P ≤ 0.01 to ≤0.000001). Worse academic and social PA were associated with greater severity of psychopathology, cognitive impairment, and real-life functioning impairment (P ≤ 0.000001). Regression analyses showed that worse PA in the academic domain was mainly associated to the impairment of working memory, whereas worse PA in the social domain to avolition (P ≤ 0.000001).

CONCLUSION

Our findings suggest that poor early adjustment may represent a marker of vulnerability to schizophrenia and highlight the need for preventive/early interventions based on psychosocial and/or cognitive programs.

Familial Risk and a Genome-Wide Supported DRD2 Variant for Schizophrenia Predict Lateral Prefrontal-Amygdala Effective Connectivity During Emotion Processing

The brain functional mechanisms translating genetic risk into emotional symptoms in schizophrenia (SCZ) may include abnormal functional integration between areas key for emotion processing, such as the amygdala and the lateral prefrontal cortex (LPFC). Indeed, investigation of these mechanisms is also complicated by emotion processing comprising different subcomponents and by disease-associated state variables. Here, our aim was to investigate the relationship between risk for SCZ and effective connectivity between the amygdala and the LPFC during different subcomponents of emotion processing. Thus, we first characterized with dynamic causal modeling (DCM) physiological patterns of LPFC-amygdala effective connectivity in healthy controls (HC) during implicit and explicit emotion processing. Then, we compared DCM patterns in a subsample of HC, in patients with SCZ and in healthy siblings of patients (SIB), matched for demographics. Finally, we investigated in HC association of LPFC-amygdala effective connectivity with a genome-wide supported variant increasing genetic risk for SCZ and possibly relevant to emotion processing (DRD2 rs2514218). In HC, we found that a "bottom-up" amygdala-to-LPFC pattern during implicit processing and a "top-down" LPFC-to-amygdala pattern during explicit processing were the most likely directional models of effective connectivity. Differently, implicit emotion processing in SIB, SCZ, and HC homozygous for the SCZ risk rs2514218 C allele was associated with decreased probability for the "bottom-up" as well as with increased probability for the "top-down" model. These findings suggest that task-specific anomaly in the directional flow of information or disconnection between the amygdala and the LPFC is a good candidate endophenotype of SCZ.

Familial aggregation of MATRICS Consensus Cognitive Battery scores in a large sample of outpatients with schizophrenia and their unaffected relatives

BACKGROUND

The 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.

METHODS

Multivariate 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.

RESULTS

SCZ 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.

CONCLUSIONS

In 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.

Interaction of childhood urbanicity and variation in dopamine genes alters adult prefrontal function as measured by functional magnetic resonance imaging (fMRI)

Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.

Interplay Among Psychopathologic Variables, Personal Resources, Context-Related Factors, and Real-life Functioning in Individuals With Schizophrenia: A Network Analysis

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.

Cerebral blood flow predicts differential neurotransmitter activity

Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. In particular, the sensitivity of cerebral blood flow to activity changes in specific neurotransmitter systems remains unclear. We address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action. We use a novel framework aimed at disentangling the observed effects to contribution from underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings suggest that cerebral blood flow is a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans.

The complex relationship between self-reported 'personal recovery' and clinical recovery in schizophrenia

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 clusters. 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 cluster showed positive features of recovery, while the third cluster showed negative features. The second cluster, with the most positive insight, showed a more complex pattern, a somewhat '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.

Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium

BACKGROUND

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.

METHODS

This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).

RESULTS

Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.

CONCLUSIONS

Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

The Emerging Role of Altered d-Aspartate Metabolism in Schizophrenia: New Insights From Preclinical Models and Human Studies

Besides d-serine, another d-amino acid with endogenous occurrence in the mammalian brain, d-aspartate, has been recently shown to influence NMDA receptor (NMDAR)-mediated transmission. d-aspartate is present in the brain at extracellular level in nanomolar concentrations, binds to the agonist site of NMDARs and activates this subclass of glutamate receptors. Along with its direct effect on NMDARs, d-aspartate can also evoke considerable l-glutamate release in specific brain areas through the presynaptic activation of NMDA, AMPA/kainate and mGlu5 receptors. d-aspartate is enriched in the embryonic brain of rodents and humans and its concentration strongly decreases after birth, due to the post-natal expression of the catabolising enzyme d-aspartate oxidase (DDO). Based on the hypothesis of NMDAR hypofunction in schizophrenia pathogenesis, recent preclinical and clinical studies suggested a relationship between perturbation of d-aspartate metabolism and this psychiatric disorder. Consistently, neurophysiological and behavioral characterization of Ddo knockout (Ddo ^-/-) and d-aspartate-treated mice highlighted that abnormally higher endogenous d-aspartate levels significantly increase NMDAR-mediated synaptic plasticity, neuronal spine density and memory. Remarkably, increased d-aspartate levels influence schizophrenia-like phenotypes in rodents, as indicated by improved fronto-hippocampal connectivity, attenuated prepulse inhibition deficits and reduced activation of neuronal circuitry induced by phencyclidine exposure. In healthy humans, a genetic polymorphism associated with reduced prefrontal DDO gene expression predicts changes in prefrontal phenotypes including greater gray matter volume and enhanced functional activity during working memory. Moreover, neurochemical detections in post-mortem brain of schizophrenia-affected patients have shown significantly reduced d-aspartate content in prefrontal regions, associated with increased DDO mRNA expression or DDO enzymatic activity. Overall, these findings suggest a possible involvement of dysregulated embryonic d-aspartate metabolism in schizophrenia pathophysiology and, in turn, highlight the potential use of free d-aspartate supplementation as a new add-on therapy for treating the cognitive symptoms of this mental illness.

An investigation of regional cerebral blood flow and tissue structure changes after acute administration of antipsychotics in healthy male volunteers

Chronic administration of antipsychotic drugs has been linked to structural brain changes observed in patients with schizophrenia. Recent MRI studies have shown rapid changes in regional brain volume following just a single dose of these drugs. However, it is not clear if these changes represent real volume changes or are artefacts ("apparent" volume changes) due to drug-induced physiological changes, such as increased cerebral blood flow (CBF). To address this, we examined the effects of a single, clinical dose of three commonly prescribed antipsychotics on quantitative measures of T1 and regional blood flow of the healthy human brain. Males (n = 42) were randomly assigned to one of two parallel groups in a double-blind, placebo-controlled, randomized, three-period cross-over study design. One group received a single oral dose of either 0.5 or 2 mg of risperidone or placebo during each visit. The other received olanzapine (7.5 mg), haloperidol (3 mg), or placebo. MR measures of quantitative T1, CBF, and T1-weighted images were acquired at the estimated peak plasma concentration of the drug. All three drugs caused localized increases in striatal blood flow, although drug and region specific effects were also apparent. In contrast, all assessments of T1 and brain volume remained stable across sessions, even in those areas experiencing large changes in CBF. This illustrates that a single clinically relevant oral dose of an antipsychotic has no detectable acute effect on T1 in healthy volunteers. We further provide a methodology for applying quantitative imaging methods to assess the acute effects of other compounds on structural MRI metrics. Hum Brain Mapp 39:319-331, 2018. © 2017 Wiley Periodicals, Inc.

A Polygenic Risk Score of glutamatergic SNPs associated with schizophrenia predicts attentional behavior and related brain activity in healthy humans

Multiple genetic variations impact on risk for schizophrenia. Recent analyses by the Psychiatric Genomics Consortium (PGC2) identified 128 SNPs genome-wide associated with the disorder. Furthermore, attention and working memory deficits are core features of schizophrenia, are heritable and have been associated with variation in glutamatergic neurotransmission. Based on this evidence, in a sample of healthy volunteers, we used SNPs associated with schizophrenia in PGC2 to construct a Polygenic-Risk-Score (PRS) reflecting the cumulative risk for schizophrenia, along with a Polygenic-Risk-Score including only SNPs related to genes implicated in glutamatergic signaling (Glu-PRS). We performed Factor Analysis for dimension reduction of indices of cognitive performance. Furthermore, both PRS and Glu-PRS were used as predictors of cognitive functioning in the domains of Attention, Speed of Processing and Working Memory. The association of the Glu-PRS on brain activity during the Variable Attention Control (VAC) task was also explored. Finally, in a second independent sample of healthy volunteers we sought to confirm the association between the Glu-PRS and both performance in the domain of Attention and brain activity during the VAC.We found that performance in Speed of Processing and Working Memory was not associated with any of the Polygenic-Risk-Scores. The Glu-PRS, but not the PRS was associated with Attention and brain activity during the VAC. The specific effects of Glu-PRS on Attention and brain activity during the VAC were also confirmed in the replication sample.Our results suggest a pathway specificity in the relationship between genetic risk for schizophrenia, the associated cognitive dysfunction and related brain processing.

Translating genome-wide association findings into new therapeutics for psychiatry

Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies, risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC phase 3 findings into new therapeutics.

Distinct Role of Striatal Functional Connectivity and Dopaminergic Loss in Parkinson's Symptoms

Degeneration of dopaminergic neurons is a hallmark of Parkinson's disease. However, its link to Parkinson's disease symptoms remains unclear. Striatal resting state functional connectivity differentiates between Parkinson's disease patients and healthy controls and might be a potential mediator of the effects of striatal dopaminergic degeneration onto Parkinson's disease symptoms. Here, we evaluated the relationship between dopaminergic deficits, striatal functional connectivity (SFC) at rest and different Parkinson's disease clinical symptoms in the largest currently established cohort of de novo Parkinson's disease patients. We show that SFC is an independent predictor of symptom severity in Parkinson's disease in addition to striatal dopaminergic deficits. Furthermore, we find that distinct SFC networks are associated with symptoms reflecting the ability to perform daily routine automatized motor tasks and clinician-rated Parkinson's disease motor symptoms. We find that reduced SFC is a major and independent predictor of Parkinson's disease symptoms going beyond the mere reflection of striatal dopaminergic input loss. These findings indicate the high value of SFC as a clinically relevant biomarker in Parkinson's disease.

Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA Schizophrenia consortium

OBJECTIVE

Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia.

METHOD

This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness.

RESULTS

Positive symptom severity was negatively related to STG thickness in both hemispheres (left: β_std = -0.052; P = 0.021; right: β_std = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness.

CONCLUSION

Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

Longitudinal characterization of biomarkers for spinal muscular atrophy

Objective

Recent advances in understanding Spinal Muscular Atrophy (SMA) etiopathogenesis prompted development of potent intervention strategies and raised need for sensitive outcome measures capable of assessing disease progression and response to treatment. Several biomarkers have been proposed; nevertheless, no general consensus has been reached on the most feasible ones. We observed a wide range of measures over 1 year to assess their ability to monitor the disease status and progression.

Methods

18 SMA patients and 19 healthy volunteers (HV) were followed in this 52‐weeks observational study. Quantitative‐MRI (qMRI) of both thighs and clinical evaluation of motor function was performed at baseline, 6, 9 and 12 months follow‐up. Blood samples were taken in patients for molecular characterization at screening, 9 and 12 month follow‐up. Progression, responsiveness and reliability of collected indices were quantified. Correlation analysis was performed to test for potential associations.

Results

QMRI indices, clinical scales and molecular measures showed high to excellent reliability. Significant differences were found between qMRI of SMA patients and HV. Significant associations were revealed between multiple qMRI measures and functional clinical scales. None of the qMRI, clinical, or molecular measures was able to detect significant disease progression over 1 year.

Interpretation

We probed a variety of quantitative measures for SMA in a slowly‐progressing disease population over 1 year. The presented measures demonstrated potential to provide a closer link to underlying disease biology as compared to conventional functional scales. The proposed biomarker framework can guide implementation of more sensitive endpoints in future clinical trials and prove their utility in search for novel disease‐modifying therapies.

Olanzapine, but not clozapine, increases glutamate release in the prefrontal cortex of freely moving mice by inhibiting D-aspartate oxidase activity

D-aspartate levels in the brain are regulated by the catabolic enzyme D-aspartate oxidase (DDO). D-aspartate activates NMDA receptors, and influences brain connectivity and behaviors relevant to schizophrenia in animal models. In addition, recent evidence reported a significant reduction of D-aspartate levels in the post-mortem brain of schizophrenia-affected patients, associated to higher DDO activity. In the present work, microdialysis experiments in freely moving mice revealed that exogenously administered D-aspartate efficiently cross the blood brain barrier and stimulates L-glutamate efflux in the prefrontal cortex (PFC). Consistently, D-aspartate was able to evoke L-glutamate release in a preparation of cortical synaptosomes through presynaptic stimulation of NMDA, mGlu5 and AMPA/kainate receptors. In support of a potential therapeutic relevance of D-aspartate metabolism in schizophrenia, in vitro enzymatic assays revealed that the second-generation antipsychotic olanzapine, differently to clozapine, chlorpromazine, haloperidol, bupropion, fluoxetine and amitriptyline, inhibits the human DDO activity. In line with in vitro evidence, chronic systemic administration of olanzapine induces a significant extracellular release of D-aspartate and L-glutamate in the PFC of freely moving mice, which is suppressed in Ddo knockout animals. These results suggest that the second-generation antipsychotic olanzapine, through the inhibition of DDO activity, increases L-glutamate release in the PFC of treated mice.

Grey Matter Volume Patterns in Thalamic Nuclei are Associated with Schizotypy in Healthy Subjects

Introduction

Schizotypy refers to a set of temporally stable traits that are observed in the general population and that resemble, in attenuated form, the symptoms of schizophrenia. In a previous work, we identified volumetric patterns in thalamic subregions which were associated with disease status, and trained a random forests classifier, accounting for such thalamic volumetric patterns, that discriminated healthy controls (HC) from patients with schizophrenia (SCZ) (81% accuracy) [1].

Objectives

i) to assess performance of random forests classifier developed by Pergola and coworkers [1], in an independent sample of healthy subjects; ii) to test whether false positives (FP), i.e. HC classified as SCZ based on such classifier would be associated with greater schizotypy compared with true negatives (TN), i.e. HC classified as such.

Methods

A total of 167 HC participated in the MRI study and filled the Schizotypal Personality Questionnaire (SPQ). We pre-processed MRI data with SPM8 and DARTEL. Then, we used thalamic grey matter volumes (GMV) as features in the random forests prediction of disease status at the single subject level. Finally, we tested SPQ scores differences between FP and TN with Mann-Whitney test.

Results

The classification accuracy was 71%. FP had greater SPQ scores compared to TN (P = 0.007).

Conclusions

Classification accuracy of our classifier in an independent sample suggests that thalamic GMV patterns are reproducible markers of disease status. Furthermore, the present results also suggest that variability of thalamic GMV patterns in HC may have relevance for subclinical phenotypes related to schizophrenia spectrum.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

A thalamo-cortical genetic co-expression network is associated with thalamic functional connectivity linked with familial risk for schizophrenia

Introduction

The genetic architecture of schizophrenia is based on polygenic trajectories. Indeed, genes converge on molecular co-expression pathways, which may be associated with heritable characteristics of patients and their siblings, called intermediate phenotypes, such as prefrontal anomalies and thalamic dysconnectivity during attentional control [2].

Objectives

Here, we investigated in healthy humans association between co-expression of genes with coordinated thalamo-prefrontal (THA-PFC) expression and functional connectivity during attentional control.

Methods

We used Brainspan dataset to characterize a coordinated THA-PFC expression gene list by correlating post-mortem gene expression in both areas (Kendall's Tau>.76, Bonferroni P < .05). Then, we identified a PFC co-expression network1 and tested all gene sets for THA-PFC and PGC loci [3] enrichments (P < .05). SNPs associated with the first principal component of the resulting enriched gene set were combined in a Polygenic Co-Expression Index (PCI) [1]. We conducted Independent Component Analysis (ICA) on attentional control fMRI data (n = 265) and selected Independent Components (ICs) including the thalamus and being highly correlated with an attentional control network2. Multiple regressions were conducted (predictor: PCI) using a thalamic cluster previously associated with familial risk for schizophrenia [2] as ROI (FWE P < .05).

Results

In one of the 8 ICs of interest there was a positive effect of PCI on thalamic connectivity strength in a cluster overlapping with our ROI (Z = 4.3).

Conclusion

Decreased co-expression of genes included in PCI predicts thalamic dysconnectivity during attentional control, suggesting a novel co-regulated molecular pathway potentially implicated in genetic risk for schizophrenia.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Association of Inter-individual Differences in Imaging Markers with Schizophrenia Phenotypes

Introduction

Neuroimaging studies have identified several candidate biomarkers of schizophrenia. However, it is unclear whether the considerable variability in these neurobiological correlates between patients can be translated into the clinical setting.

Objectives

We aimed to identify neuroimaging predictors of clinical course in patients with schizophrenia. Combined with the identification of genetically determined markers of schizophrenia risk, our studies aimed to elucidate the biological basis and the clinical relevance of inter-individual variability between patients.

Methods

We included over 150 patients with schizophrenia and 279 healthy volunteers across five neuroimaging centers in the framework of the IMAGEMEND project [1]. We performed multiple studies on MRI scans using random forests and ROC curves to predict clinical course. Data from healthy controls served to normalize the data from the clinical population and to provide a benchmark for the findings.

Results

We identified ensembles of neuroimaging markers and of genetic variants predictive of clinical course. Results highlight that (i) brain imaging carries significant clinical information, (ii) clinical information at baseline can considerably increase prediction accuracy.

Conclusion

The methodological challenges and the results will be discussed in the context of recent findings from other multi-site studies. We conclude that brain imaging data on their own right are relevant to stratify patients in terms of clinical course; however, complementing these data with other modalities such as genetics and clinical information is necessary to further develop the field towards clinical application of the predictions.

Disclosure of interest

Giulio Pergola is the academic supervisor of a Hoffmann-La Roche Collaboration grant that partially funds his salary.

The Impact of Premorbid Functioning on Outcome Indices in a Large Sample of Italian Patients with Schizophrenia

Introduction

An impairment of premorbid adjustment (PA) has been regarded among poor prognostic indicators of schizophrenia. Some discrepancies in the literature suggest the usefulness of further characterizations of its impact on different aspects of the disease.

Aims

The present study aimed to investigate the association of poor PA with psychopathology, neurocognition and real-life functioning in patients with schizophrenia recruited within the multicenter study of the Italian network for research on psychoses. functioning during childhood and adolescence (early adjustment) was assessed also in a group of healthy controls (HC) and one of unaffected relatives of patients (UR).

Methods

Group comparisons were performed between patients with poor and those with good PA. Differences in frequency of poor early adjustment were investigated among patients, HC and UR.

Results

Patients with poor PA, as compared to those with good PA, showed earlier age of onset, more severe negative symptoms and disorganization, greater impairment on all cognitive domains with the exception of attention/vigilance and worse real-life functioning in the considered areas (interpersonal relationships, community activities and work abilities). The pattern of poor early adjustment was more frequent in patients with respect to UR and HC and, to a less degree, in UR with respect to HC.

Conclusions

Our findings confirm that poor PA in schizophrenia is associated with poorer illness outcome, and offer a further characterization of PA impact on different psychopathological and cognitive domains. They also suggest that poor early adjustment is a candidate endophenotype of schizophrenia, occurring in patients and their unaffected relatives.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Grey matter volume patterns in thalamic nuclei are associated with familial risk for schizophrenia

Previous evidence suggests reduced thalamic grey matter volume (GMV) in patients with schizophrenia (SCZ). However, it is not considered an intermediate phenotype for schizophrenia, possibly because previous studies did not assess the contribution of individual thalamic nuclei and employed univariate statistics. Here, we hypothesized that multivariate statistics would reveal an association of GMV in different thalamic nuclei with familial risk for schizophrenia. We also hypothesized that accounting for the heterogeneity of thalamic GMV in healthy controls would improve the detection of subjects at familial risk for the disorder. We acquired MRI scans for 96 clinically stable SCZ, 55 non-affected siblings of patients with schizophrenia (SIB), and 249 HC. The thalamus was parceled into seven regions of interest (ROIs). After a canonical univariate analysis, we used GMV estimates of thalamic ROIs, together with total thalamic GMV and premorbid intelligence, as features in Random Forests to classify HC, SIB, and SCZ. Then, we computed a Misclassification Index for each individual and tested the improvement in SIB detection after excluding a subsample of HC misclassified as patients. Random Forests discriminated SCZ from HC (accuracy=81%) and SIB from HC (accuracy=75%). Left anteromedial thalamic volumes were significantly associated with both multivariate classifications (p<0.05). Excluding HC misclassified as SCZ improved greatly HC vs. SIB classification (Cohen's d=1.39). These findings suggest that multivariate statistics identify a familial background associated with thalamic GMV reduction in SCZ. They also suggest the relevance of inter-individual variability of GMV patterns for the discrimination of individuals at familial risk for the disorder.

DRD2 co-expression network and a related polygenic index predict imaging, behavioral and clinical phenotypes linked to schizophrenia

Genetic risk for schizophrenia (SCZ) is determined by many genetic loci whose compound biological effects are difficult to determine. We hypothesized that co-expression pathways of SCZ risk genes are associated with system-level brain function and clinical phenotypes of SCZ. We examined genetic variants related to the dopamine D2 receptor gene DRD2 co-expression pathway and associated them with working memory (WM) behavior, the related brain activity and treatment response. Using two independent post-mortem prefrontal messenger RNA (mRNA) data sets (total N=249), we identified a DRD2 co-expression pathway enriched for SCZ risk genes. Next, we identified non-coding single-nucleotide polymorphisms (SNPs) associated with co-expression of this pathway. These SNPs were associated with regulatory genetic loci in the dorsolateral prefrontal cortex (P<0.05). We summarized their compound effect on co-expression into a Polygenic Co-expression Index (PCI), which predicted DRD2 pathway co-expression in both mRNA data sets (all P<0.05). We associated the PCI with brain activity during WM performance in two independent samples of healthy individuals (total N=368) and 29 patients with SCZ who performed the n-back task. Greater predicted DRD2 pathway prefrontal co-expression was associated with greater prefrontal activity and longer WM reaction times (all corrected P<0.05), thus indicating inefficient WM processing. Blind prediction of treatment response to antipsychotics in two independent samples of patients with SCZ suggested better clinical course of patientswith greater PCI (total N=87; P<0.05). The findings on this DRD2 co-expression pathway are a proof of concept that gene co-expression can parse SCZ risk genes into biological pathways associated with intermediate phenotypes as well as with clinically meaningful information.

Interaction between DRD2 variation and sound environment on mood and emotion-related brain activity

Sounds, like music and noise, are capable of reliably affecting individuals' mood and emotions. However, these effects are highly variable across individuals. A putative source of variability is genetic background. Here we explored the interaction between a functional polymorphism of the dopamine D2 receptor gene (DRD2 rs1076560, G>T, previously associated with the relative expression of D2S/L isoforms) and sound environment on mood and emotion-related brain activity. Thirty-eight healthy subjects were genotyped for DRD2 rs1076560 (G/G=26; G/T=12) and underwent functional magnetic resonance imaging (fMRI) during performance of an implicit emotion-processing task while listening to music or noise. Individual variation in mood induction was assessed before and after the task. Results showed mood improvement after music exposure in DRD2GG subjects and mood deterioration after noise exposure in GT subjects. Moreover, the music, as opposed to noise environment, decreased the striatal activity of GT subjects as well as the prefrontal activity of GG subjects while processing emotional faces. These findings suggest that genetic variability of dopamine receptors affects sound environment modulations of mood and emotion processing.

Accurate Prediction of Conversion to Alzheimer's Disease using Imaging, Genetic, and Neuropsychological Biomarkers

A variety of imaging, neuropsychological, and genetic biomarkers have been suggested as potential biomarkers for the identification of mild cognitive impairment (MCI) in patients who later develop Alzheimer's disease (AD). Here, we systematically evaluated the most promising combinations of these biomarkers regarding discrimination between stable and converter MCI and reflection of disease staging. Alzheimer's Disease Neuroimaging Initiative data of AD (n = 144), controls (n = 112), stable (n = 265) and converter (n = 177) MCI, for which apolipoprotein E status, neuropsychological evaluation, and structural, glucose, and amyloid imaging were available, were included in this study. Naïve Bayes classifiers were built on AD and controls data for all possible combinations of these biomarkers, with and without stratification by amyloid status. All classifiers were then applied to the MCI cohorts. We obtained an accuracy of 76% for discrimination between converter and stable MCI with glucose positron emission tomography as a single biomarker. This accuracy increased to about 87% when including further imaging modalities and genetic information. We also identified several biomarker combinations as strong predictors of time to conversion. Use of amyloid validated training data resulted in increased sensitivities and decreased specificities for differentiation between stable and converter MCI when amyloid was included as a biomarker but not for other classifier combinations. Our results indicate that fully independent classifiers built only on AD and controls data and combining imaging, genetic, and/or neuropsychological biomarkers can more reliably discriminate between stable and converter MCI than single modality classifiers. Several biomarker combinations are identified as strongly predictive for the time to conversion to AD.

Social cognition in people with schizophrenia: a cluster-analytic approach

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 <10), but not in simple sarcasm. Moreover, functioning, neurocognition, disorganization and SC had a linear relationship across the three clusters, while positive symptoms were significantly lower in patients with unimpaired SC as compared with patients with impaired and very impaired SC. On the other hand, negative symptoms were highest in patients with impaired levels of SC.

CONCLUSIONS

If replicated, the identification of such subtypes in clinical practice may help in tailoring rehabilitation efforts to the person's strengths to gain more benefit to the person.

Pathways to functional outcome in subjects with schizophrenia living in the community and their unaffected first-degree relatives

RATIONALE

Variables influencing real-life functioning have repeatedly been modeled in schizophrenia subjects but not systematically investigated in their unaffected first-degree relatives (SRs), in whom milder forms of deficits reported in schizophrenia have been observed, but confounders of clinical cohorts are not in play. Demonstrating that pathways to functional outcome are similar between patients and SRs would validate structural models developed in schizophrenia subjects. The present multicenter study aimed to explore whether variables associated with real-life functioning are similar in schizophrenia patients and their unaffected relatives.

METHODS

The study sample included 921 schizophrenia patients, 379 SRs and 780 healthy controls. Structural Equation Models (SEMs) were used in patients and SRs to test associations of psychopathological dimensions, neurocognition, social cognition, resilience, perceived stigma and functional capacity with real-life functioning domains, impaired in both patients and SRs.

RESULTS

Interpersonal Relationships and Work Skills were the only functional domains impaired in both patients and SRs. For both domains, functional impairment in patients was found to predict impairment in unaffected relatives, suggesting the involvement of similar illness-related vulnerability factors. In both groups variables significantly associated with Interpersonal Relationships included Social Cognition, Neurocognition, Avolition, Resilience, Disorganization, Perceived Stigma and Gender, and those significantly associated with Work Skills included Social Cognition, Neurocognition and Disorganization.

CONCLUSIONS

Pathways to functional outcome for Interpersonal relationships and Work skills are similar between schizophrenia patients and their unaffected first-degree relatives. These findings validate, in the absence of confounders of clinical cohorts, structural models of determinants of functional outcome in people with schizophrenia.

What Impact does An Angry Context have Upon Us? The Effect of Anger on Functional Connectivity of the Right Insula and Superior Temporal Gyri

Being in a social world requires an understanding of other people that is co-determined in its meaning by the situation at hand. Therefore, we investigated the underlying neural activation occurring when we encounter someone acting in angry or joyful situation. We hypothesized a dynamic interplay between the right insula, both involved in mapping visceral states associated with emotional experiences and autonomic control, and the bilateral superior temporal gyri (STG), part of the “social brain”, when facing angry vs. joyful situations. Twenty participants underwent a functional magnetic resonance imaging (fMRI) scanning session while watching video clips of actors grasping objects in joyful and angry situations. The analyses of functional connectivity, psychophysiological interaction (PPI) and dynamic causal modeling (DCM), all revealed changes in functional connectivity associated with the angry situation. Indeed, the DCM model showed that the modulatory effect of anger increased the ipsilateral forward connection from the right insula to the right STG, while it suppressed the contralateral one. Our findings reveal a critical role played by the right insula when we are engaged in angry situations. In addition, they suggest that facing angry people modulates the effective connectivity between these two nodes associated, respectively, with autonomic responses and bodily movements and human-agent motion recognition. Taken together, these results add knowledge to the current understanding of hierarchical brain network for social cognition.

Altered Functional Subnetwork During Emotional Face Processing: A Potential Intermediate Phenotype for Schizophrenia

IMPORTANCE

Although deficits in emotional processing are prominent in schizophrenia, it has been difficult to identify neural mechanisms related to the genetic risk for this highly heritable illness. Prior studies have not found consistent regional activation or connectivity alterations in first-degree relatives compared with healthy controls, suggesting that a more comprehensive search for connectomic biomarkers is warranted.

OBJECTIVES

To identify a potential systems-level intermediate phenotype linked to emotion processing in schizophrenia and to examine the psychological association, task specificity, test-retest reliability, and clinical validity of the identified phenotype.

DESIGN, SETTING, AND PARTICIPATIONS

The study was performed in university research hospitals from June 1, 2008, through December 31, 2013. We examined 58 unaffected first-degree relatives of patients with schizophrenia and 94 healthy controls with an emotional face-matching functional magnetic resonance imaging paradigm. Test-retest reliability was analyzed with an independent sample of 26 healthy participants. A clinical association study was performed in 31 patients with schizophrenia and 45 healthy controls. Data analysis was performed from January 1 to September 30, 2014.

MAIN OUTCOMES AND MEASURES

Conventional amygdala activity and seeded connectivity measures, graph-based global and local network connectivity measures, Spearman rank correlation, intraclass correlation, and gray matter volumes.

RESULTS

Among the 152 volunteers included in the relative-control sample, 58 were unaffected first-degree relatives of patients with schizophrenia (mean [SD] age, 33.29 [12.56]; 38 were women), and 94 were healthy controls without a first-degree relative with mental illness (mean [SD] age, 32.69 [10.09] years; 55 were women). A graph-theoretical connectivity approach identified significantly decreased connectivity in a subnetwork that primarily included the limbic cortex, visual cortex, and subcortex during emotional face processing (cluster-level P corrected for familywise error = .006) in relatives compared with controls. The connectivity of the same subnetwork was significantly decreased in patients with schizophrenia (F = 6.29, P = .01). Furthermore, we found that this subnetwork connectivity measure was negatively correlated with trait anxiety scores (P = .04), test-retest reliable (intraclass correlation coefficient = 0.57), specific to emotional face processing (F = 17.97, P < .001), and independent of gray matter volumes of the identified brain areas (F = 1.84, P = .18). Replicating previous results, no significant group differences were found in face-related amygdala activation and amygdala-anterior cingulate cortex connectivity (P corrected for familywise error =.37 and .11, respectively).

CONCLUSIONS AND RELEVANCE

Our results indicate that altered connectivity in a visual-limbic subnetwork during emotional face processing may be a functional connectomic intermediate phenotype for schizophrenia. The phenotype is reliable, task specific, related to trait anxiety, and associated with manifest illness. These data encourage the further investigation of this phenotype in clinical and pharmacologic studies.

Prefrontal activity during working memory is modulated by the interaction of variation in CB1 and COX2 coding genes and correlates with frequency of cannabis use

The CB1 cannabinoid receptor is targeted in the brain by endocannabinoids under physiological conditions as well as by delta9-tetrahydrocannabinol under cannabis use. Furthermore, its signaling appears to affect brain cognitive processing. Recent findings highlight a crucial role of cyclooxygenase-2 (COX-2) in the mechanism of intraneuronal CB1 signaling transduction, while others indicate that two single nucleotide polymorphisms (SNPs) (rs1406977 and rs20417) modulate expression of CB1 (CNR1) and COX-2 (PTGS2) coding genes, respectively. Here, our aim was to use fMRI to investigate in healthy humans whether these SNPs interact in modulating prefrontal activity during working memory processing and if this modulation is linked with cannabis use. We recruited 242 healthy subjects genotyped for CNR1 rs1406977 and PTGS2 rs20417 that performed the N-back working memory task during fMRI and were interviewed using the Cannabis Experience Questionnaire (CEQ). We found that the interaction between CNR1 rs1406977 and PTGS2 rs20417 is associated with dorsolateral prefrontal cortex (DLPFC) activity such that specific genotype configurations (CNR1 C carriers/PTGS2 C carriers and CNR1 TT/PTGS2 GG) predict lower cortical response versus others in spite of similar behavioral accuracy. Furthermore, DLPFC activity in the cluster associated with the CNR1 by PTGS2 interaction was negatively correlated with behavioral efficiency and positively correlated with frequency of cannabis use in cannabis users. These results suggest that a genetically modulated balancing of signaling within the CB1-COX-2 pathway may reflect on more or less efficient patterns of prefrontal activity during working memory. Frequency of cannabis use may be a factor for further modulation of CNR1/PTGS2-mediated cortical processing associated with this cognitive process.

Association of familial risk for schizophrenia with thalamic and medial prefrontal functional connectivity during attentional control

Anomalies in behavioral correlates of attentional processing and related brain activity are crucial correlates of schizophrenia and associated with familial risk for this brain disorder. However, it is not clear how brain functional connectivity during attentional processes is key for schizophrenia and linked with trait vs. state related variables. To address this issue, we investigated patterns of functional connections during attentional control in healthy siblings of patients with schizophrenia, who share with probands genetic features but not variables related to the state of the disorder. 356 controls, 55 patients with schizophrenia on stable treatment with antipsychotics and 40 healthy siblings of patients with this brain disorder underwent the Variable Attentional Control (VAC) task during fMRI. Independent Component Analysis (ICA) is allowed to identify independent components (IC) of BOLD signal recorded during task performance. Results indicated reduced connectivity strength in patients with schizophrenia as well as in their healthy siblings in left thalamus within an attentional control component and greater connectivity in right medial prefrontal cortex (PFC) within the so-called Default Mode Network (DMN) compared to healthy individuals. These results suggest a relationship between familial risk for schizophrenia and brain functional networks during attentional control, such that this biological phenotype may be considered a useful intermediate phenotype in order to link genes effects to aspects of the pathophysiology of this brain disorder.

Combined effect of genetic variants in the GluN2B coding gene (GRIN2B) on prefrontal function during working memory performance

BACKGROUND

The GluN2B subunit of N-methyl-d-aspartate receptors is crucially involved in the physiology of the prefrontal cortex during working memory (WM). Consistently, genetic variants in the GluN2B coding gene (GRIN2B) have been associated with cognitive phenotypes. However, it is unclear how GRIN2B genetic variation affects gene expression and prefrontal cognitive processing. Using a composite score, we tested the combined effect of GRIN2B variants on prefrontal activity during WM performance in healthy subjects.

METHOD

We computed a composite score to combine the effects of single nucleotide polymorphisms on post-mortem prefrontal GRIN2B mRNA expression. We then computed the composite score in independent samples of healthy participants in a peripheral blood expression study (n = 46), in a WM behavioural study (n = 116) and in a WM functional magnetic resonance imaging study (n = 122).

RESULTS

Five polymorphisms were associated with GRIN2B expression: rs2160517, rs219931, rs11055792, rs17833967 and rs12814951 (all corrected p < 0.05). The score computed to account for their combined effect reliably indexed gene expression. GRIN2B composite score correlated negatively with intelligence quotient, WM behavioural efficiency and dorsolateral prefrontal cortex activity. Moreover, there was a non-linear association between GRIN2B genetic score and prefrontal activity, i.e. both high and low putative genetic score levels were associated with high blood oxygen level-dependent signals in the prefrontal cortex.

CONCLUSIONS

Multiple genetic variants in GRIN2B are jointly associated with gene expression, prefrontal function and behaviour during WM. These results support the role of GRIN2B genetic variants in WM prefrontal activity in human adults.

A multicentric study on cognitive functions in a large sample of patients with schizophrenia and their unaffected first-degree relatives

Introduction

Neurocognition may represent an indicator of genetic risk and poor outcome in schizophrenia patients (SCZ) predicting real life functioning.

Objectives

As cognitive performance of unaffected first-degree relatives (UR) is intermediate between SCZ and healthy controls (HC), neurocognitive impairment may represent a marker of vulnerability to schizophrenia.

Aims

To investigate social and neurocognition in all subjects and their impact on functional capacity of patients as markers of vulnerability.

Methods

Sample: 922 SCZ, 379 UR and 780 HC. Assessment: MATRICS Consensus Cognitive Battery (neurocognition), Facial Emotion Identification Test and Awareness of Social Inference Test (social cognition) and Specific Level of Functioning Scale (social functioning). Analyses: Structural Equation Model (SEM) analyses to model the impact of all variables on functional outcome.

Results

SCZ scored worse in all domains than UR and HC. UR had significant impairments in all cognitive domains with respect to HC. Cognitive functioning had direct and indirect impacts on functional outcome mainly through social cognition and functional capacity. Social cognition had a direct impact on outcome, independent of neurocognition.

Conclusion

SCZ and UR display similar patterns of social and neurocognition deficits. Our results confirm a strong impact of neurocogniton on functional outcome. Social cognition has become an interesting object of study and its conceptualization as trait variable and the existence of a continuum between SCZ and UR are hypotheses for further research.

Acknowledgements

The study was carried out within the project “Multicenter study on factors influencing real-life social functioning of people with a diagnosis of schizophrenia” of the Italian Network for Research on Psychoses.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Relationships between neurocognition, social cognition and functional outcome in schizophrenia

Introduction

The inter-relationships of neurocognition, social cognition, residual psychopathology and real-life functioning are poorly understood. A large multicenter study was carried out by the Italian Network for Research on Psychoses to model relationships between neurocognitive deficits, psychopathology and real-life functioning, taking into account the role of functional capacity and social cognition.

Methods

A structural equation model was used to investigate direct and indirect effects of neurocognition and psychopathology on real-life functioning. Social cognition and functional capacity were modeled as mediators.

Results

In 921 patients with schizophrenia, neurocognition had both direct and indirect effects, through functional capacity and social cognition, on real-life functioning. Neurocognition predicted to a large extent social cognition on which depression and disorganization had a modest effect. Social cognition showed a significant direct impact on real-life functioning.

Conclusion

Our results support a strong link between neurocognition and functional outcome, independent of psychopathology. Social cognition accounted for unique incremental variance in real-life functioning.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

BDNF rs6265 methylation and genotype interact on risk for schizophrenia

Epigenetic mechanisms can mediate gene-environment interactions relevant for complex disorders. The BDNF gene is crucial for development and brain plasticity, is sensitive to environmental stressors, such as hypoxia, and harbors the functional SNP rs6265 (Val(66)Met), which creates or abolishes a CpG dinucleotide for DNA methylation. We found that methylation at the BDNF rs6265 Val allele in peripheral blood of healthy subjects is associated with hypoxia-related early life events (hOCs) and intermediate phenotypes for schizophrenia in a distinctive manner, depending on rs6265 genotype: in ValVal individuals increased methylation is associated with exposure to hOCs and impaired working memory (WM) accuracy, while the opposite is true for ValMet subjects. Also, rs6265 methylation and hOCs interact in modulating WM-related prefrontal activity, another intermediate phenotype for schizophrenia, with an analogous opposite direction in the 2 genotypes. Consistently, rs6265 methylation has a different association with schizophrenia risk in ValVals and ValMets. The relationships of methylation with BDNF levels and of genotype with BHLHB2 binding likely contribute to these opposite effects of methylation. We conclude that BDNF rs6265 methylation interacts with genotype to bridge early environmental exposures to adult phenotypes, relevant for schizophrenia. The study of epigenetic changes in regions containing genetic variation relevant for human diseases may have beneficial implications for the understanding of how genes are actually translated into phenotypes.

Association between Ability Emotional Intelligence and Left Insula during Social Judgment of Facial Emotions

The human ability of identifying, processing and regulating emotions from social stimuli is generally referred as Emotional Intelligence (EI). Within EI, Ability EI identifies a performance measure assessing individual skills at perceiving, using, understanding and managing emotions. Previous models suggest that a brain "somatic marker circuitry" (SMC) sustains emotional sub-processes included in EI. Three primary brain regions are included: the amygdala, the insula and the ventromedial prefrontal cortex (vmPFC). Here, our aim was to investigate the relationship between Ability EI scores and SMC activity during social judgment of emotional faces. Sixty-three healthy subjects completed a test measuring Ability EI and underwent fMRI during a social decision task (i.e. approach or avoid) about emotional faces with different facial expressions. Imaging data revealed that EI scores are associated with left insula activity during social judgment of emotional faces as a function of facial expression. Specifically, higher EI scores are associated with greater left insula activity during social judgment of fearful faces but also with lower activity of this region during social judgment of angry faces. These findings indicate that the association between Ability EI and the SMC activity during social behavior is region- and emotion-specific.