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Background Schizophrenia risk is associated with both genetic and environmental risk factors. Furthermore, cognitive abnormalities are established core characteristics of schizophrenia. We aim to assess whether a classification approach encompassing risk factors, cognition, and their associations can discriminate patients with schizophrenia (SCZs) from healthy control subjects (HCs). We hypothesized that cognition would demonstrate greater HC-SCZ classification accuracy and that combined gene–environment stratification would improve the discrimination performance of cognition. Methods Genome-wide association study–based genetic, environmental, and neurocognitive classifiers were trained to separate 337 HCs from 103 SCZs using support vector classification and repeated nested cross-validation. We validated classifiers on independent datasets using within-diagnostic (SCZ) and cross-diagnostic (clinically isolated syndrome for multiple sclerosis, another condition with cognitive abnormalities) approaches. Then, we tested whether gene–environment multivariate stratification modulated the discrimination performance of the cognitive classifier in iterative subsamples. Results The cognitive classifier discriminated SCZs from HCs with a balanced accuracy (BAC) of 88.7%, followed by environmental (BAC = 65.1%) and genetic (BAC = 55.5%) classifiers. Similar classification performance was measured in the within-diagnosis validation sample (HC-SCZ BACs, cognition = 70.5%; environment = 65.8%; genetics = 49.9%). The cognitive classifier was relatively specific to schizophrenia (HC–clinically isolated syndrome for multiple sclerosis BAC = 56.7%). Combined gene–environment stratification allowed cognitive features to classify HCs from SCZs with 89.4% BAC. Conclusions Consistent with cognitive deficits being core features of the phenotype of SCZs, our results suggest that cognitive features alone bear the greatest amount of information for classification of SCZs. Consistent with genes and environment being risk factors, gene–environment stratification modulates HC-SCZ classification performance of cognition, perhaps providing another target for refining early identification and intervention strategies.

Functional-Magnetic-Imaging (fMRI) is widely adopted to investigate neurophysiological correlates of emotion processing (EP). However, studies have reported that scanning procedures in neuroimaging protocols may increase or cause anxiety and psychological distress related with the scanning, thus inducing peripheral cortisol release. These phenomena may in turn impact on brain EP. Additionally, previous findings have indicated that inter-individual differences in stress-response intensity are mediated by levels of Emotional Stability (ES), a personality trait that has been associated with brain activity during EP, especially in amygdala and prefrontal cortex (PFC). The aim of this study was to investigate the interaction between indices of stress related to anticipation of fMRI scanning and levels of ES on amygdala and PFC activity during EP. With this aim, 55 healthy volunteers were characterized for trait ES. Furthermore, salivary cortisol levels at baseline and soon before fMRI scanning were measured as an index of stress related to scanning anticipation. During fMRI, participants performed an explicit EP task. We found that variation in salivary cortisol (Δc) interacts with ES on left amygdala and PFC activity during EP. More in details, in the context of a higher ES, the greater the Δc, the lower the activity in left amygdala and PFC. In the context of lower ES, the opposite Δc-brain activity relationship was found. Our results suggest that the stressful potential of fMRI interacts with personality traits in modulating brain activity during EP. These findings should be taken into account when interpreting neuroimaging studies especially exploring brain physiology during EP.

Background Recent views posited that negative parenting and attachment insecurity can be considered as general environmental factors of vulnerability for psychosis, specifically for individuals diagnosed with psychosis (PSY). Furthermore, evidence highlighted a tight relationship between attachment style and social cognition abilities, a key PSY behavioral phenotype. The aim of this study is to generate a machine learning algorithm based on the perceived quality of parenting and attachment style-related features to discriminate between PSY and healthy controls (HC) and to investigate its ability to track PSY early stages and risk conditions, as well as its association with social cognition performance. Methods Perceived maternal and paternal parenting, as well as attachment anxiety and avoidance scores, were trained to separate 71 HC from 34 PSY (20 individuals diagnosed with schizophrenia + 14 diagnosed with bipolar disorder with psychotic manifestations) using support vector classification and repeated nested cross-validation. We then validated this model on independent datasets including individuals at the early stages of disease (ESD, i.e. first episode of psychosis or depression, or at-risk mental state for psychosis) and with familial high risk for PSY (FHR, i.e. having a first-degree relative suffering from psychosis). Then, we performed factorial analyses to test the group x classification rate interaction on emotion perception, social inference and managing of emotions abilities. Results The perceived parenting and attachment-based machine learning model discriminated PSY from HC with a Balanced Accuracy (BAC) of 72.2%. Slightly lower classification performance was measured in the ESD sample (HC-ESD BAC = 63.5%), while the model could not discriminate between FHR and HC (BAC = 44.2%). We observed a significant group x classification interaction in PSY and HC from the discovery sample on emotion perception and on the ability to manage emotions (both p = 0.02). The interaction on managing of emotion abilities was replicated in the ESD and HC validation sample (p = 0.03). Conclusion Our results suggest that parenting and attachment-related variables bear significant classification power when applied to both PSY and its early stages and are associated with variability in emotion processing. These variables could therefore be useful in psychosis early recognition programs aimed at softening the psychosis-associated disability.

Background Genome-Wide Association Studies (GWASs) have identified several genes associated with Schizophrenia (SCZ) and exponentially increased knowledge on the genetic basis of the disease. In addition, products of GWAS genes interact with neuronal factors coded by genes lacking association, such that this interaction may confer risk for specific phenotypes of this brain disorder. In this regard, fragile X mental retardation syndrome-related 1 (FXR1) gene has been GWAS associated with SCZ. FXR1 protein is regulated by glycogen synthase kinase-3β (GSK3β), which has been implicated in pathophysiology of SCZ and response to antipsychotics (APs). rs496250 and rs12630592, two eQTLs (Expression Quantitative Trait Loci) of FXR1 and GSK3β, respectively, interact on emotion stability and amygdala/prefrontal cortex activity during emotion processing. These two phenotypes are associated with Negative Symptoms (NSs) of SCZ suggesting that the interaction between these SNPs may also affect NS severity and responsiveness to medication. Methods To test this hypothesis, in two independent samples of patients with SCZ, we investigated rs496250 by rs12630592 interaction on NS severity and response to APs. We also tested a putative link between APs administration and FXR1 expression, as already reported for GSK3β expression. Results We found that rs496250 and rs12630592 interact on NS severity. We also found evidence suggesting interaction of these polymorphisms also on response to APs. This interaction was not present when looking at positive and general psychopathology scores. Furthermore, chronic olanzapine administration led to a reduction of FXR1 expression in mouse frontal cortex. Discussion Our findings suggest that, like GSK3β, FXR1 is affected by APs while shedding new light on the role of the FXR1/GSK3β pathway for NSs of SCZ.

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders., The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

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.

Background Patients with schizophrenia (SCZ) show lower volumetric estimates of gray matter (GM) than healthy controls (HC). Similar results have been reported in healthy siblings of patients (SIB). However, it is unclear whether this phenotype is also present in individuals at clinical high-risk (CHR), characterized by sub-threshold symptoms and loss of functioning. We hypothesized that GM volumetric differences are associated with both familial and clinical risk for schizophrenia Methods We processed the T1-weighted MRI scans acquired at 3 Tesla of 544 HC, 63 SIB, 20 CHR and 120 SCZ using CAT12. We used ANCOVA to assess group differences (HC vs. CHR vs. SIB vs. SCZ), with linear and quadratic age, gender and total intracranial volume as nuisance covariates. We assessed the reproducibility of our case/control findings in an independent sample of 127 HC and 36 SCZ. Group differences were tested post hoc through Fisher’s test. Results We found significant group effects in the bilateral thalamus, bilateral hippocampus and anterior cingulate (FWE Discussion Individuals with familial or clinical risk for schizophrenia have lower GM estimates in the same brain regions. These findings, suggest that these structural features are not only associated with familial risk for schizophrenia but that they are also associated with its sub-threshold symptoms.

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.

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.

BackgroundThe GluN2B subunit ofN-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 howGRIN2Bgenetic variation affects gene expression and prefrontal cognitive processing. Using a composite score, we tested the combined effect ofGRIN2Bvariants on prefrontal activity during WM performance in healthy subjects.MethodWe computed a composite score to combine the effects of single nucleotide polymorphisms on post-mortem prefrontalGRIN2BmRNA 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).ResultsFive polymorphisms were associated withGRIN2Bexpression: rs2160517, rs219931, rs11055792, rs17833967 and rs12814951 (all correctedp< 0.05). The score computed to account for their combined effect reliably indexed gene expression.GRIN2Bcomposite score correlated negatively with intelligence quotient, WM behavioural efficiency and dorsolateral prefrontal cortex activity. Moreover, there was a non-linear association betweenGRIN2Bgenetic 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.ConclusionsMultiple genetic variants inGRIN2Bare jointly associated with gene expression, prefrontal function and behaviour during WM. These results support the role ofGRIN2Bgenetic variants in WM prefrontal activity in human adults.

Rasd2 is a thyroid hormone target gene, which encodes for a GTP-binding protein enriched in the striatum where, among other functions, it modulates dopaminergic neurotransmission. Here we report that human RASD2 mRNA is abundant in putamen, but it also occurs in the cerebral cortex, with a distinctive expression pattern that differs from that present in rodents. Consistent with its localization, we found that a genetic variation in RASD2 (rs6518956) affects postmortem prefrontal mRNA expression in healthy humans and is associated with phenotypes of relevance to schizophrenia, including prefrontal and striatal grey matter volume and physiology during working memory, as measured with magnetic resonance imaging. Interestingly, quantitative real-time PCR analysis indicated that RASD2 mRNA is slightly reduced in postmortem prefrontal cortex of patients with schizophrenia. In the attempt to uncover the neurobiological substrates associated with Rasd2 activity, we used knockout mice to analyze the in vivo influence of this G-protein on the prepulse inhibition of the startle response and psychotomimetic drug-related behavioral response. Data showed that Rasd2 mutants display deficits in basal prepulse inhibition that, in turn, exacerbate gating disruption under psychotomimetic drug challenge. Furthermore, we documented that lack of Rasd2 strikingly enhances the behavioral sensitivity to motor stimulation elicited by amphetamine and phencyclidine. Based on animal model data, along with the finding that RASD2 influences prefronto-striatal phenotypes in healthy humans, we suggest that genetic mutation or reduced levels of this G-protein might have a role in cerebral circuitry dysfunction underpinning exaggerated psychotomimetic drugs responses and development of specific biological phenotypes linked to schizophrenia.

The Nogo receptor (NgR) is implicated in neurodevelopmental processes and it participates in inhibiting axonal growth. Consistent with its high levels of expression in the prefrontal cortex, animal studies indicate that NgR is relevant for prefrontal-related cognitive processing. Given that genetic variation may alter mechanisms of gene expression impacting molecular and systems-level phenotypes, we investigated the association of genetic variation with the expression of the NgR coding gene (RTN4R), as well as with prefrontal correlates at progressively greater biological distance from gene effects. First, we studied the association of single nucleotide polymorphisms (SNPs) with RTN4R mRNA expression in postmortem prefrontal cortex of humans without psychiatric illnesses. Then, we probed in peripheral blood mononuclear cells (PBMCs) the association that we found in prefrontal tissue. Thus, we investigated whether functional genetic variation affecting RTN4R expression is also associated with prefrontal activity during working memory. We found that rs696884 (A/G) predicted these phenotypes. Specifically, the AA genotype was associated with lower RTN4R mRNA expression levels in the prefrontal cortex and PBMCs and inefficient prefrontal activity during working memory compared to the GG genotype. These results suggest that genetic variation associated with RTN4R mRNA expression influences prefrontal physiology in healthy individuals. Furthermore, they highlight the need for further investigations of the role of NgR in the pathophysiology of brain disorders associated with prefrontal dysfunction.

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 DRD2 GG 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.

Pharmacological stimulation of D2 receptors modulates prefrontal neural activity associated with working memory (WM) processing. The T allele of a functional single-nucleotide polymorphism (SNP) within DRD2 (rs1076560 G > T) predicts reduced relative expression of the D2S receptor isoform and less efficient neural cortical responses during WM tasks. We used functional MRI to test the hypothesis that DRD2 rs1076560 genotype interacts with pharmacological stimulation of D2 receptors with bromocriptine on prefrontal responses during different loads of a spatial WM task (N-Back). Fifty-three healthy subjects (38 GG and 15 GT) underwent two 3-T functional MRI scans while performing the 1-, 2- and 3-Back versions of the N-Back WM task. Before the imaging sessions, either bromocriptine or placebo was administered to all subjects in a counterbalanced order. A factorial repeated-measures ANOVA within SPM8 (p

Background Diagnosis of schizophrenia is based on a collection of symptoms which are heterogeneous from one patient to the other. Therefore, improving the reliability of this diagnosis is a currently unmet need. Schizophrenia risk is associated with genetic variation and with environmental factors potentially affecting neurodevelopment. Moreover, among the symptoms, cognitive abnormalities are heritable and predate its clinical onset. Multivariate techniques can leverage the high dimensionality of data in order to study the combined effect of multiple risk factors and symptoms on clinical predictions. The aim of the current study is therefore to assess the predictability of schizophrenia diagnosis applying machine learning techniques to an ensemble of genetic, early environmental and cognitive deficits variables. Methods 442 subjects (339 healthy controls – HC – and 103 patients with schizophrenia – SCZ) were recruited for the study. Participants underwent a full neuropsychological evaluation (Modality 1, assessment of working memory, verbal fluency, intelligence quotient, attention, speed of processing and cognitive control), a broad environmental assessment (Modality 2, investigation of urbanicity, obstetric complications, developmental anomalies, socio-economic parental status and age of parents at birth) and genome-wide genotyping (Modality 3). Following published procedures, we computed individual risk scores for each of the single nucleotide polymorphisms (SNPs) associated with risk for schizophrenia in the Psychiatric Genomics Consortium (PGC) study. Data from Modalities 1, 2 and 3 entered NeuroMiner v0.998 and underwent preprocessing procedures through scaling, pruning of non-informative variables and imputation of missing values through Euclidean distance-based nearest-neighbor search. Then, these three modalities were included in a Support Vector Machine HC vs. SCZ classification algorithm, which applied decision-based data fusion strategies to integrate the individual predictions of the three modalities in a nested cross-validation framework. Results Our cross-validated results revealed that Modality 1 (cognition) predicted schizophrenia diagnosis with the highest Balanced Accuracy (BAC, 87.3%) and that the most selected cognitive indices were intelligence quotient scores and attentional abilities. Modality 2 (environment) classified HC and SCZ with a BAC of 67.2%, and the most predictive environmental features were the parental socio-economic status, the presence of developmental anomalies during the first year of life and the age of father at birth. On the other hand, Modality 3 (genetics) predicted schizophrenia diagnosis with BAC=54,1%. The most informative SNPs were FUT9 rs117074560, TCF4 rs72934570 and STAG1 rs7432375. Decision-based fusion combining individual cognitive, environmental and genetic decision scores predicted the classification of SCZ from HC with a 78.9% BAC. Discussion Our results using a novel machine learning approach suggest that an ensemble of cognitive, early environmental and genetic features can predict schizophrenia with significant accuracy. Our results also give key information on cognitive and environmental factors that can be targeted in early identification programs and offer novel insights about genetic loci that may be prioritized in future investigations of the pathophysiology of the disease. However, the near chance-level predictive ability of the genetic modality alone calls for the implementation and testing of more complex models of interaction between multiple risk factors.

Objective Convergent evidence indicates that apathy affects cognitive behavior in different neurological and psychiatric conditions. Studies of clinical populations have also suggested the primary involvement of the prefrontal cortex and the basal ganglia in apathy. These brain regions are interconnected at both the structural and functional levels and are deeply involved in cognitive processes, such as working memory and attention. However, it is unclear how apathy modulates brain processing during cognition and whether such a modulation occurs in healthy young subjects. To address this issue, we investigated the link between apathy and prefrontal and basal ganglia function in healthy young individuals. We hypothesized that apathy may be related to sub-optimal activity and connectivity in these brain regions. Methods Three hundred eleven healthy subjects completed an apathy assessment using the Starkstein’s Apathy Scale and underwent fMRI during working memory and attentional performance tasks. Using an ROI approach, we investigated the association of apathy with activity and connectivity in the DLPFC and the basal ganglia. Results Apathy scores correlated positively with prefrontal activity and negatively with prefrontal-basal ganglia connectivity during both working memory and attention tasks. Furthermore, prefrontal activity was inversely related to attentional behavior. Conclusions These results suggest that in healthy young subjects, apathy is a trait associated with inefficient cognitive-related prefrontal activity, i.e., it increases the need for prefrontal resources to process cognitive stimuli. Furthermore, apathy may alter the functional relationship between the prefrontal cortex and the basal ganglia during cognition.

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 (PDRD2 pathway co-expression in both mRNA data sets (all PN=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 PN=87; PDRD2 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.

Earlier neuroimaging studies of motor function in schizophrenia have demonstrated reduced functional lateralization in the motor network during motor tasks. Here, we used event-related functional magnetic resonance imaging during a visually guided motor task in 18 clinically unaffected siblings of patients with schizophrenia and 24 matched controls to investigate if abnormal functional lateralization is related to genetic risk for this brain disorder. Whereas activity associated with motor task performance was mainly contralateral with only a marginal ipsilateral component in healthy participants, unaffected siblings had strong bilateral activity with significantly greater response in ipsilateral and contralateral premotor areas as well as in contralateral subcortical motor regions relative to controls. Reduced lateralization in siblings was also identified with a measure of laterality quotient. These findings suggest that abnormal functional lateralization of motor circuitry is related to genetic risk of schizophrenia.

IntroductionNeuroimaging 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.ObjectivesWe 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.MethodsWe 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.ResultsWe 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.ConclusionThe 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 interestGiulio Pergola is the academic supervisor of a Hoffmann-La Roche Collaboration grant that partially funds his salary.

Objective Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 ( rs1076560 G > T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [ 123 I] FP-CIT SPECT. Methods Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3 T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [ 123 I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Results Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. Interpretation The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease.

Inhibition of glycogen synthase kinase 3β (GSK3β) 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 GSK3β 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 GSK3β. Phosphorylation of FXR1P by GSK3β is facilitated by prior phosphorylation by ERK2 and leads to its down-regulation. In contrast, behaviorally effective chronic mood stabilizer treatments in mice inhibit GSK3β 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 GSK3β gene expression interact to regulate emotional brain responsiveness and stability in humans. These observations uncovered a GSK3β/FXR1P signaling pathway that contributes to regulating mood and emotion processing. Regulation of FXR1P by GSK3β also provides a mechanistic framework that may explain how inhibition of GSK3β 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.

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.

Earlier studies have demonstrated that emotional stimulation modulates attentional processing during goal-directed behavior and related activity of a brain network including the inferior frontal gyrus and the caudate nucleus. However, it is not clear how emotional interference modulates behavior and brain physiology during variation in attentional control, a relevant question for everyday life situations in which both emotional stimuli and cognitive load vary. The aim of this study was to investigate the impact of negative emotions on behavior and activity in inferior frontal gyrus and caudate nucleus during increasing levels of attentional control. 22 healthy subjects underwent event-related functional magnetic resonance imaging while performing a task in which neutral or fearful facial expressions were displayed before stimuli eliciting increasing levels of attentional control processing. Results indicated slower reaction time and greater right inferior frontal gyrus activity when fearful compared with neutral facial expressions preceded the low level of attentional control. On the other hand, fearful facial expressions preceding the intermediate level of attentional control elicited faster behavioral responses and greater activity in the right and left sides of the caudate. Finally, correlation analysis indicated a relationship between behavioral correlates of attentional control after emotional interference and right inferior frontal gyrus activity. All together, these results suggest that the impact of negative emotions on attentional processing is differentially elicited at the behavioral and physiological levels as a function of cognitive load.

Background: Dopamine D2 receptors (D2R) contribute to the inverted-U shaped relationship between dopamine dorsolateral prefrontal cortex (DLPFC) and working memory (WM). Genetic variation in DRD2 coding for D2Rs modulates D2 signaling, but other genes in its pathway may be involved. In a previous work, using gene co-expression networks we identified 84 partner genes coregulated with DRD2 and eight single nucleotide polymorphisms (SNPs) predicting coexpression of the whole gene set in the human DLPFC [1]. These SNPs combined into a polygenic coexpression index (PCI) predicted WM performance and DLPFC activity in two independent samples of living healthy humans [1]. Here, we asked whether response to D2R targeting drugs is associated with this PCI. Thus, we investigated the interaction between WM behavioral/brain response to the D2R agonist Bromocriptine (BRO) and the PCI.

Schizotypy is a latent organization of personality related to the genetic risk for schizophrenia. Some evidence suggests that schizophrenia and schizotypy share some biological features, including a link to dopaminergic D2 receptor signaling. A polymorphism in the D2 gene (DRD2 rs1076560, G>T) has been associated with the D2 short/long isoform expression ratio, as well as with striatal dopamine signaling and prefrontal cortical activity during different cognitive operations, which are measures that are altered in patients with schizophrenia. Here, our Our aim is to determine the association of schizotypy scores with the DRD2 rs1076560 genotype in healthy individuals, as well as and their interaction on with prefrontal activity during attention and D2 striatal signaling. A total of 83 healthy subjects were genotyped for DRD2 rs1076560 and completed the Schizotypal Personality Questionnaire (SPQ). Twenty-six 26 participants underwent SPECT with [123I]IBZM D2 receptor radiotracer, while 68 performed an attentional control task during fMRI. We found that rs1076560 GT subjects had greater SPQ scores than GG individuals. Moreover, the interaction between schizotypy and the GT genotype predicted prefrontal activity and related attentional behavior, as well as striatal binding of IBZM. No interaction was found in GG individuals.These individuals. These results suggest that rs1076560 GT healthy individuals are prone to higher levels higher levels of schizotypy, and that the interaction between rs1076560 and schizotypy scores modulates phenotypes related to the pathophysiology of schizophrenia, like such as prefrontal activity and striatal dopamine signaling. These results provide systems-level qualitative evidence for mapping the construct of schizotypy in healthy individuals onto the schizophrenia continuum.

Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1), a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

Background Prefrontal behavior and activity in humans are heritable. Studies in animals demonstrate an interaction between dopamine D2 receptors and nicotinic acetylcholine receptors on prefrontal behavior but evidence in humans is weak. Therefore, we hypothesize that genetic variation regulating dopamine D2 and nicotinic acetylcholine receptor signaling impact prefrontal cortex activity and related cognition. To test this hypothesis in humans, we explored the interaction between functional genetic variants in the D2 receptor gene (DRD2, rs1076560) and in the nicotinic receptor α5 gene (CHRNA5, rs16969968) on both dorsolateral prefrontal cortex mediated behavior and physiology during working memory and on prefrontal gray matter volume. Methods A large sample of healthy subjects was compared for genotypic differences for DRD2 rs1076560 (G>T) and CHNRA5 rs16969968 (G>A) on prefrontal phenotypes, including cognitive performance at the N-Back task, prefrontal physiology with BOLD fMRI during performance of the 2-Back working memory task, and prefrontal morphometry with structural MRI. Results We found that DRD2 rs1076560 and CHNRA5 rs16969968 interact to modulate cognitive function, prefrontal physiology during working memory, and prefrontal gray matter volume. More specifically, CHRNA5-AA/DRD2-GT subjects had greater behavioral performance, more efficient prefrontal cortex activity at 2Back working memory task, and greater prefrontal gray matter volume than the other genotype groups. Conclusions The present data extend previous studies in animals and enhance our understanding of dopamine and acetylcholine signaling in the human prefrontal cortex, demonstrating interactions elicited by working memory that are modulated by genetic variants in DRD2 and CHRNA5.

Importance Serotonin (5-hydroxytryptamine) receptor 2a (5-HT2AR) signaling is important for modulation of corticostriatal pathways and prefrontal activity during cognition. Furthermore, newer antipsychotic drugs target 5-HT2AR. A single-nucleotide polymorphism in the 5-HT2AR gene ( HTR2A rs6314, C>T; OMIM 182135) has been weakly associated with differential 5-HT2AR signaling and with physiologic as well as behavioral effects. Objective To use a hierarchical approach to determine the functional effects of this single-nucleotide polymorphism on 5-HT2AR messenger RNA and protein expression, on prefrontal phenotypes linked with genetic risk for schizophrenia, and on treatment with olanzapine. Design In silico predictions, in vitro, and case-control investigations. Setting Academic and clinical facilities. Participants The postmortem study included 112 brains from healthy individuals; the in vivo investigation included a total sample of 371 healthy individuals and patients with schizophrenia. Exposures Patients received olanzapine monotherapy for 8 weeks. Main Outcomes and Measures In silico predictions, messenger RNA, and protein expression in postmortem human prefrontal cortex and HeLa cells, functional magnetic resonance imaging prefrontal activity and behavior during working memory and attention in healthy individuals, and response to an 8-week trial of olanzapine treatment in patients with schizophrenia. Results Bioinformatic analysis predicted that rs6314 alters patterns of splicing, with possible effects on HTR2A expression. Moreover, the T allele was associated with reduced prefrontal messenger RNA expression in postmortem prefrontal cortex, with reduced protein expression in vitro, inefficient prefrontal blood oxygen level–dependent functional magnetic resonance imaging response during working memory and attentional control processing, and impaired working memory and attention behavior, as well as with attenuated improvement in negative symptoms after olanzapine treatment. Conclusions and Relevance Our results suggest that HTR2A rs6314 affects 5-HT2AR expression and functionally contributes to genetic modulation of known endophenotypes of schizophrenia-like higher-level cognitive behaviors and related prefrontal activity, as well as response to treatment with olanzapine.

Objective: Glycogen synthase kinase 3 beta (GSK-3 beta) is an enzyme implicated in neurodevelopmental processes with a broad range of substrates mediating several canonical signaling pathways in the brain. The authors investigated the association of variation in the GSK-3 beta gene with a series of progressively more complex phenotypes of relevance to schizophrenia, a neurodevelopmental disorder with strong genetic risk.Method: Based on computer predictions, the authors investigated in humans the association of GSK-3 beta functional variation with 1) GSK-3 beta mRNA expression from postmortem prefrontal cortex, 2) GSK-3 beta and beta-catenin protein expression from peripheral blood mononuclear cells (PBMCs), 3) prefrontal imaging phenotypes, and 4) diagnosis of schizophrenia.Results: Consistent with predictions, the TT genotype of a single-nucleotide polymorphism in GSK-3 beta (rs12630592) was associated with reduced GSK-3 beta mRNA from postmortem prefrontal cortex. Furthermore, this genotype was associated with GSK-3 beta protein expression and kinase activity, as well as with downstream effects on beta-catenin expression in PBMCs. Finally, the TT genotype was associated with attenuated functional MRI prefrontal activity, reduced prefrontal cortical thickness, and diagnosis of schizophrenia.Conclusions: These results suggest that GSK-3 beta variation is implicated in multiple phenotypes relevant to schizophrenia.

BackgroundAbnormalities in hippocampal–parahippocampal (H-PH) function are prominent features of schizophrenia and have been associated with deficits in episodic memory. However, it remains unclear whether these abnormalities represent a phenotype related to genetic risk for schizophrenia or whether they are related to disease state.MethodWe investigated H-PH-mediated behavior and physiology, using blood oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI), during episodic memory in a sample of patients with schizophrenia, clinically unaffected siblings and healthy subjects.ResultsPatients with schizophrenia and unaffected siblings displayed abnormalities in episodic memory performance. During an fMRI memory encoding task, both patients and siblings demonstrated a similar pattern of reduced H-PH engagement compared with healthy subjects.ConclusionsOur findings suggest that the pathophysiological mechanism underlying the inability of patients with schizophrenia to properly engage the H-PH during episodic memory is related to genetic risk for the disorder. Therefore, H-PH dysfunction can be assumed as a schizophrenia susceptibility-related phenotype.

Background: Maternal care (MC) and dopamine modulate brain activity during emotion processing in inferior frontal gyrus (IFG), striatum and amygdala. Reuptake of dopamine from the synapse is performed by the dopamine transporter (DAT), whose abundance is predicted by variation in its gene (DAT 3 0 VNTR; 10 > 9-repeat alleles). Here, we investigated the interaction between perceived MC and DAT 3 0 VNTR genotype on brain activity during processing of aversive facial emotional stimuli. Methods: Sixty-one healthy subjects were genotyped for DAT 3 0 VNTR and categorized in low and high MC individuals. They underwent functional magnetic resonance imaging while performing a task requiring gender discrimination of facial stimuli with angry, fearful or neutral expressions. Results: An interaction between facial expression, DAT genotype and MC was found in left IFG, such that low MC and homozygosity for the 10-repeat allele are associated with greater activity during processing of fearful faces. This greater activity was also inversely correlated with a measure of emotion control as scored with the Big Five Questionnaire. Moreover, MC and DAT genotype described a double dissociation on functional connectivity between IFG and amygdala. Conclusion: These findings suggest that perceived early parental bonding may interact with DAT 3 0 VNTR genotype in modulating brain activity during emotionally relevant inputs.

The default mode network (DMN) comprises a set of brain regions with "increased" activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([(123)I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling.

DNA methylation at CpG dinucleotides is associated with gene silencing, stress, and memory. The catechol-O-methyltransferase (COMT) Val158allele in rs4680 is associated with differential enzyme activity, stress responsivity, and prefrontal activity during working memory (WM), and it creates a CpG dinucleotide. We report that methylation of the Val158allele measured from peripheral blood mononuclear cells (PBMCs) of Val/Val humans is associated negatively with lifetime stress and positively with WM performance; it interacts with stress to modulate prefrontal activity during WM, such that greater stress and lower methylation are related to reduced cortical efficiency; and it is inversely related to mRNA expression and protein levels, potentially explaining thein vivoeffects. Finally, methylation ofCOMTin prefrontal cortex and that in PBMCs of rats are correlated. The relationship of methylation of theCOMTVal158allele with stress, gene expression, WM performance, and related brain activity suggests that stress-related methylation is associated with silencing of the gene, which partially compensates the physiological role of the high-activity Val allele in prefrontal cognition and activity. Moreover, these results demonstrate how stress-related DNA methylation of specific functional alleles impacts directly on human brain physiology beyond sequence variation.

The D2/AKT1/GSK-3β 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-3β 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-3β, 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.

BackgroundCatechol-O-methyltransferase (COMT) Val158Met has been associated with activity of the mesial temporal lobe during episodic memory and it may weakly increase risk for schizophrenia. However, how this variant affects parahippocampal and hippocampal physiology when dopamine transmission is perturbed is unclear. The aim of the present study was to compare the effects of the COMT Val158Met genotype on parahippocampal and hippocampal physiology during encoding of recognition memory in patients with schizophrenia and in healthy subjects.MethodUsing blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI), we studied 28 patients with schizophrenia and 33 healthy subjects matched for a series of sociodemographic and genetic variables while they performed a recognition memory task.ResultsWe found that healthy subjects had greater parahippocampal and hippocampal activity during memory encoding compared to patients with schizophrenia. We also found different activity of the parahippocampal region between healthy subjects and patients with schizophrenia as a function of the COMT genotype, in that the predicted COMT Met allele dose effect had an opposite direction in controls and patients.ConclusionsOur results demonstrate a COMT Val158Met genotype by diagnosis interaction in parahippocampal activity during memory encoding and may suggest that modulation of dopamine signaling interacts with other disease-related processes in determining the phenotype of parahippocampal physiology in schizophrenia.