PhenoApp: A mobile tool for plant phenotyping to record field and greenhouse observations.

With the ongoing cost decrease of genotyping and sequencing technologies, accurate and fast phenotyping remains the bottleneck in the utilizing of plant genetic resources for breeding and breeding research. Although cost-efficient high-throughput phenotyping platforms are emerging for specific traits and/or species, manual phenotyping is still widely used and is a time- and money-consuming step. Approaches that improve data recording, processing or handling are pivotal steps towards the efficient use of genetic resources and are demanded by the research community. Therefore, we developed PhenoApp, an open-source Android app for tablets and smartphones to facilitate the digital recording of phenotypical data in the field and in greenhouses. It is a versatile tool that offers the possibility to fully customize the descriptors/scales for any possible scenario, also in accordance with international information standards such as MIAPPE (Minimum Information About a Plant Phenotyping Experiment) and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles. Furthermore, PhenoApp enables the use of pre-integrated ready-to-use BBCH (Biologische Bundesanstalt für Land- und Forstwirtschaft, Bundessortenamt und CHemische Industrie) scales for apple, cereals, grapevine, maize, potato, rapeseed and rice. Additional BBCH scales can easily be added. The simple and adaptable structure of input and output files enables an easy data handling by either spreadsheet software or even the integration in the workflow of laboratory information management systems (LIMS). PhenoApp is therefore a decisive contribution to increase efficiency of digital data acquisition in genebank management but also contributes to breeding and breeding research by accelerating the labour intensive and time-consuming acquisition of phenotyping data.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes.

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

Publisher Correction: Common brain disorders are associated with heritable patterns of apparent aging of the brain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Common brain disorders are associated with heritable patterns of apparent aging of the brain.

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

Brain Heterogeneity in Schizophrenia and Its Association With Polygenic Risk.

Importance: Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature. Objectives: To compare brain structural variability between individuals with schizophrenia and healthy controls and to test whether respective variability reflects the polygenic risk score (PRS) for schizophrenia in an independent sample of healthy controls. Design, Setting, and Participants: This case-control and polygenic risk analysis compared MRI-derived cortical thickness and subcortical volumes between healthy controls and patients with schizophrenia across 16 cohorts and tested for associations between PRS and MRI features in a control cohort from the UK Biobank. Data were collected from October 27, 2004, through April 12, 2018, and analyzed from December 3, 2017, through August 1, 2018. Main Outcomes and Measures: Mean and dispersion parameters were estimated using double generalized linear models. Vertex-wise analysis was used to assess cortical thickness, and regions-of-interest analyses were used to assess total cortical volume, total surface area, and white matter, subcortical, and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, test of robustness of the PRS threshold, population covariates, outlier removal, and control for image quality. Results: A comparison of 1151 patients with schizophrenia (mean [SD] age, 33.8 [10.6] years; 68.6% male [n = 790] and 31.4% female [n = 361]) with 2010 healthy controls (mean [SD] age, 32.6 [10.4] years; 56.0% male [n = 1126] and 44.0% female [n = 884]) revealed higher heterogeneity in schizophrenia for cortical thickness and area (t = 3.34), cortical (t = 3.24) and ventricle (t range, 3.15-5.78) volumes, and hippocampal subfields (t range, 2.32-3.55). In the UK Biobank sample of 12 490 participants (mean [SD] age, 55.9 [7.5] years; 48.2% male [n = 6025] and 51.8% female [n = 6465]), higher PRS was associated with thinner frontal and temporal cortices and smaller left CA2/3 (t = -3.00) but was not significantly associated with dispersion. Conclusions and Relevance: This study suggests that schizophrenia is associated with substantial brain structural heterogeneity beyond the mean differences. These findings may reflect higher sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of schizophrenia. A higher PRS was associated with thinner frontotemporal cortices and smaller hippocampal subfield volume, but not heterogeneity. This finding suggests that brain variability in schizophrenia results from interactions between environmental and genetic factors that are not captured by the PRS. Factors contributing to heterogeneity in frontotemporal cortices and hippocampus are key to furthering our understanding of how genetic and environmental factors shape brain biology in schizophrenia.

Immunomodulation by adoptive regulatory T-cell transfer improves Coxsackievirus B3-induced myocarditis.

Regulatory T (Treg) cells offer new therapeutic options for controlling undesired systemic and local immune responses. The aim of the current study was to determine the impact of therapeutic Treg administration on systemic and cardiac inflammation and remodeling in coxsackievirus B3 (CVB3) -induced myocarditis. Therefore, syngeneic Treg cells were applied intravenously in CVB3-infected mice 3 d after infection. Compared with CVB3 + PBS mice, CVB3 + Treg mice exhibited lower left ventricular (LV) chemokine expression, accompanied by reduced cardiac presence of proinflammatory Ly6ChighCCR2highCx3Cr1low monocytes and higher retention of proinflammatory Ly6CmidCCR2highCx3Cr1low monocytes in the spleen. In addition, splenic myelopoiesis was reduced in CVB3 + Treg compared with CVB3 + PBS mice. Coculture of Treg cells with splenocytes isolated from mice 3 d post-CVB3 infection further demonstrated the ability of Treg cells to modulate monocyte differentiation in favor of the anti-inflammatory Ly6ClowCCR2lowCx3Cr1high subset. Treg-mediated immunomodulation was paralleled by lower collagen 1 protein expression and decreased levels of soluble and insoluble collagen in LV of CVB3 + Treg compared with CVB3 + PBS mice. In agreement with these findings, LV systolic and diastolic function was improved in CVB3 + Treg mice compared with CVB3 + PBS mice. In summary, adoptive Treg transfer in the inflammatory phase of viral-induced myocarditis protects the heart against inflammatory damage and fibrosis via modulation of monocyte subsets.-Pappritz, K., Savvatis, K., Miteva, K., Kerim, B., Dong, F., Fechner, H., Müller, I., Brandt, C., Lopez, B., González, A., Ravassa, S., Klingel, K., Diez, J., Reinke, P., Volk, H.-D., Van Linthout, S., Tschöpe, C. Immunomodulation by adoptive regulatory T-cell transfer improves Coxsackievirus B3-induced myocarditis.

Thalamo-cortical functional connectivity in schizophrenia and bipolar disorder.

The thalamus is a highly connected subcortical structure that relays and integrates sensory and cortical information, which is critical for coherent and accurate perceptual awareness and cognition. Thalamic dysfunction is a classical finding in schizophrenia (SZ), and resting-state functional MRI has implicated somatomotor and frontal lobe thalamic dysconnectivity. However, it remains unclear whether these findings generalize to different psychotic disorders, are confined to specific thalamic sub-regions, and how they relate to structural thalamic alterations. Within-thalamic and thalamo-cortical functional connectivity was assessed using resting-state functional MRI data obtained from patients with SZ (n = 96), bipolar disorder (BD, n = 57), and healthy controls (HC, n = 280). Further, we used thalamic sub-regions as seeds to investigate specific cortical connectivity patterns, and performed structural analyses of thalamic volume and shape. Results showed reduced within-thalamic connectivity and thalamo-frontoparietal coupling in SZ and increased thalamo-somatomotor connectivity in BD. One thalamic sub-region showed increased sensory connectivity in SZ and eight sub-regions showed reductions with frontal and posterior areas. Reduced gray matter and shape abnormalities were found in frontal-projecting regions in both SZ and BD, but did not seem to explain reduced functional connectivity. Aberrant thalamo-cortical connectivity patterns in SZ and BD supports the notion of the thalamus as a key structure in the functional connectome across the psychosis spectrum, and the frontal and somatomotor anatomical distribution is in line with the characteristic cognitive and perceptual symptoms in psychotic disorders.

Distinct multivariate brain morphological patterns and their added predictive value with cognitive and polygenic risk scores in mental disorders.

The brain underpinnings of schizophrenia and bipolar disorders are multidimensional, reflecting complex pathological processes and causal pathways, requiring multivariate techniques to disentangle. Furthermore, little is known about the complementary clinical value of brain structural phenotypes when combined with data on cognitive performance and genetic risk. Using data-driven fusion of cortical thickness, surface area, and gray matter density maps (GMD), we found six biologically meaningful patterns showing strong group effects, including four statistically independent multimodal patterns reflecting co-occurring alterations in thickness and GMD in patients, over and above two other independent patterns of widespread thickness and area reduction. Case-control classification using cognitive scores alone revealed high accuracy, and adding imaging features or polygenic risk scores increased performance, suggesting their complementary predictive value with cognitive scores being the most sensitive features. Multivariate pattern analyses reveal distinct patterns of brain morphology in mental disorders, provide insights on the relative importance between brain structure, cognitive and polygenetic risk score in classification of patients, and demonstrate the importance of multivariate approaches in studying the pathophysiological substrate of these complex disorders.

Delayed stabilization and individualization in connectome development are related to psychiatric disorders.

The brain functional connectome constitutes a unique fingerprint allowing identification of individuals among a pool of people. Here we establish that the connectome develops into a more stable, individual wiring pattern during adolescence and demonstrate that a delay in this network tuning process is associated with reduced mental health in the formative years of late neurodevelopment.

Task modulations and clinical manifestations in the brain functional connectome in 1615 fMRI datasets.

OBJECTIVE: An abundance of experimental studies have motivated a range of models concerning the cognitive underpinnings of severe mental disorders, yet the conception that cognitive and brain dysfunction is confined to specific cognitive domains and contexts has limited ecological validity. Schizophrenia and bipolar spectrum disorders have been conceptualized as disorders of brain connectivity; yet little is known about the pervasiveness across cognitive tasks. METHODS: To address this outstanding issue of context specificity, we estimated functional network connectivity from fMRI data obtained during five cognitive tasks (0-back, 2-back, go/no-go, recognition of positive faces, negative faces) in 90 patients with schizophrenia spectrum, 97 patients with bipolar spectrum disorder, and 136 healthy controls, including 1615 fMRI datasets in total. We tested for main effects of task and group, and their interactions, and used machine learning to classify task labels and predict cognitive domain scores from brain connectivity. RESULTS: Connectivity profiles were positively correlated across tasks, supporting the existence of a core functional connectivity backbone common to all tasks. However, 76.2% of all network links also showed significant task-related alterations, robust on the single subject level as evidenced by high machine-learning performance when classifying task labels. Independent of such task-specific modulations, 9.5% of all network links showed significant group effects, particularly including sensory (sensorimotor, visual, auditory) and cognitive (frontoparietal, default-mode, dorsal attention) networks. A lack of group by task interactions revealed that the pathophysiological sensitivity remained across tasks. Such pervasiveness across tasks was further supported by significant predictions of cognitive domain scores from the connectivity backbone obtained across tasks. CONCLUSIONS: The high accuracies obtained when classifying cognitive tasks support that brain connectivity indices provide sensitive and specific measures of cognitive states. Importantly, we provide evidence that brain network dysfunction in severe mental disorders is not confined to specific cognitive tasks and show that the connectivity backbone common to all tasks is predictive of cognitive domain traits. Such pervasiveness across tasks may support a generalization of pathophysiological models from different domains, thereby reducing their complexity and increasing their ecological validity. Future research incorporating a wider range of cognitive tasks, involving other sensory modalities (auditory, somatosensory, motor) and requirements (learning, perceptual inference, decision making, etc.), is needed to assess if under certain circumstances, context dependent aberrations may evolve. Our results provide further evidence from a large sample that fMRI based functional network connectivity can be used to reveal both, state and trait effects in the connectome.

Resting-state high-frequency heart rate variability is related to respiratory frequency in individuals with severe mental illness but not healthy controls.

Heart rate variability (HRV) has become central to biobehavioral models of self-regulation and interpersonal interaction. While research on healthy populations suggests changes in respiratory frequency do not affect short-term HRV, thus negating the need to include respiratory frequency as a HRV covariate, the nature of the relationship between these two variables in psychiatric illness is poorly understood. Therefore, the aim of this study was to investigate the association between HRV and respiratory frequency in a sample of individuals with severe psychiatric illness (n = 55) and a healthy control comparison group (n = 149). While there was no significant correlation between HF-HRV and respiration in the control group, we observed a significant negative correlation in the psychiatric illness group, with a 94.1% probability that these two relationships are different. Thus, we provide preliminary evidence suggesting that HF-HRV is related to respiratory frequency in severe mental illness, but not in healthy controls, suggesting that HRV research in this population may need to account for respiratory frequency. Future work is required to better understand the complex relationship between respiration and HRV in other clinical samples with psychiatric diseases.

Contribution of oxytocin receptor polymorphisms to amygdala activation in schizophrenia spectrum disorders.

BACKGROUND: Oxytocin has been proposed to mediate amygdala dysfunction associated with altered emotion processing in schizophrenia, but the contribution of oxytocin pathway genes is yet to be investigated. AIMS: To identify potential different contributions of three oxytocin receptor polymorphisms (rs53576, rs237902 and rs2254298) between patients with schizophrenia spectrum disorders (SCZ), affective spectrum disorders (AD) and healthy controls (HC). METHOD: In a total of 346 participants (104 with SCZ, 100 with AD, and 142 HC) underwent genotyping and functional magnetic resonance imaging (fMRI) during an emotional faces matching paradigm. Genetic association analyses were performed to test the possible effects on task-induced BOLD amygdala response to fearful/angry faces. RESULTS: In participants with SCZ, the rs237902 G allele was associated with low amygdala activation (left hemisphere: b=-4.99, Bonferroni corrected P=0.04) and interaction analyses showed that this association was disorder specific (left hemisphere: Bonferroni corrected P=0.003; right hemisphere: Bonferroni corrected P=0.03). There were no associations between oxytocin polymorphisms and amygdala activation in the total sample, among AD patients or HC. CONCLUSIONS: Rs237902 was associated with amygdala activation in response to fearful/angry faces only in patients with SCZ. Our findings indicate that the endogenous oxytocin system could serve as a contributing factor in biological underpinnings of emotion processing and that this contribution is disorder specific. DECLARATION OF INTEREST: O.A.A. received speaker's honoraria from GSK, Otsuka, Lundbeck. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Reduced load-dependent default mode network deactivation across executive tasks in schizophrenia spectrum disorders.

BACKGROUND: Schizophrenia is associated with cognitive impairment and brain network dysconnectivity. Recent efforts have explored brain circuits underlying cognitive dysfunction in schizophrenia and documented altered activation of large-scale brain networks, including the task-positive network (TPN) and the task-negative default mode network (DMN) in response to cognitive demands. However, to what extent TPN and DMN dysfunction reflect overlapping mechanisms and are dependent on cognitive state remain to be determined. METHODS: In the current study, we investigated the recruitment of TPN and DMN using independent component analysis in patients with schizophrenia spectrum disorders (n = 29) and healthy controls (n = 21) during two different executive tasks probing planning/problem-solving and spatial working memory. RESULTS: We found reduced load-dependent DMN deactivation across tasks in patients compared to controls. Furthermore, we observed only moderate associations between the TPN and DMN activation across groups, implying that the two networks reflect partly independent mechanisms. Additionally, whereas TPN activation was associated with task performance in both tasks, no such associations were found for DMN. CONCLUSION: These results support a general load-dependent DMN dysfunction in schizophrenia spectrum disorder across two demanding executive tasks that is not merely an epiphenomenon of cognitive dysfunction.

Assessing brain structural associations with working-memory related brain patterns in schizophrenia and healthy controls using linked independent component analysis.

Schizophrenia (SZ) is a psychotic disorder with significant cognitive dysfunction. Abnormal brain activation during cognitive processing has been reported, both in task-positive and task-negative networks. Further, structural cortical and subcortical brain abnormalities have been documented, but little is known about how task-related brain activation is associated with brain anatomy in SZ compared to healthy controls (HC). Utilizing linked independent component analysis (LICA), a data-driven multimodal analysis approach, we investigated structure-function associations in a large sample of SZ (n = 96) and HC (n = 142). We tested for associations between task-positive (fronto-parietal) and task-negative (default-mode) brain networks derived from fMRI activation during an n-back working memory task, and brain structural measures of surface area, cortical thickness, and gray matter volume, and to what extent these associations differed in SZ compared to HC. A significant association (p < .05, corrected for multiple comparisons) was found between a component reflecting the task-positive fronto-parietal network and another component reflecting cortical thickness in fronto-temporal brain regions in SZ, indicating increased activation with increased thickness. Other structure-function associations across, between and within groups were generally moderate and significant at a nominal p-level only, with more numerous and stronger associations in SZ compared to HC. These results indicate a complex pattern of moderate associations between brain activation during cognitive processing and brain morphometry, and extend previous findings of fronto-temporal brain abnormalities in SZ by suggesting a coupling between cortical thickness of these brain regions and working memory-related brain activation.

Altered Brain Activation during Emotional Face Processing in Relation to Both Diagnosis and Polygenic Risk of Bipolar Disorder.

OBJECTIVES: Bipolar disorder (BD) is a highly heritable disorder with polygenic inheritance. Among the most consistent findings from functional magnetic imaging (fMRI) studies are limbic hyperactivation and dorsal hypoactivation. However, the relation between reported brain functional abnormalities and underlying genetic risk remains elusive. This is the first cross-sectional study applying a whole-brain explorative approach to investigate potential influence of BD case-control status and polygenic risk on brain activation. METHODS: A BD polygenic risk score (PGRS) was estimated from the Psychiatric Genomics Consortium BD case-control study, and assigned to each individual in our independent sample (N=85 BD cases and 121 healthy controls (HC)), all of whom participated in an fMRI emotional faces matching paradigm. Potential differences in BOLD response across diagnostic groups were explored at whole-brain level in addition to amygdala as a region of interest. Putative effects of BD PGRS on brain activation were also investigated. RESULTS: At whole-brain level, BD cases presented with significantly lower cuneus/precuneus activation than HC during negative face processing (Z-threshold=2.3 as cluster-level correction). The PGRS was associated positively with increased right inferior frontal gyrus (rIFG) activation during negative face processing. For amygdala activation, there were no correlations with diagnostic status or PGRS. CONCLUSIONS: These findings are in line with previous reports of reduced precuneus and altered rIFG activation in BD. While these results demonstrate the ability of PGRS to reveal underlying genetic risk of altered brain activation in BD, the lack of convergence of effects at diagnostic and PGRS level suggests that this relation is a complex one.

Cognitive Effort and Schizophrenia Modulate Large-Scale Functional Brain Connectivity.

Schizophrenia (SZ) is characterized by cognitive dysfunction and disorganized thought, in addition to hallucinations and delusions, and is regarded a disorder of brain connectivity. Recent efforts have been made to characterize the underlying brain network organization and interactions. However, to which degree connectivity alterations in SZ vary across different levels of cognitive effort is unknown. Utilizing independent component analysis (ICA) and methods for delineating functional connectivity measures from functional magnetic resonance imaging (fMRI) data, we investigated the effects of cognitive effort, SZ and their interactions on between-network functional connectivity during 2 levels of cognitive load in a large and well-characterized sample of SZ patients (n = 99) and healthy individuals (n = 143). Cognitive load influenced a majority of the functional connections, including but not limited to fronto-parietal and default-mode networks, reflecting both decreases and increases in between-network synchronization. Reduced connectivity in SZ was identified in 2 large-scale functional connections across load conditions, with a particular involvement of an insular network. The results document an important role of interactions between insular, default-mode, and visual networks in SZ pathophysiology. The interplay between brain networks was robustly modulated by cognitive effort, but the reduced functional connectivity in SZ, primarily related to an insular network, was independent of cognitive load, indicating a relatively general brain network-level dysfunction.

Direct angiotensin type 2 receptor (AT2R) stimulation attenuates T-cell and microglia activation and prevents demyelination in experimental autoimmune encephalomyelitis in mice.

In the present study, we evaluated stimulation of the angiotensin type 2 receptor (AT2R) by the selective non-peptide agonist Compound 21 (C21) as a novel therapeutic concept for the treatment of multiple sclerosis using the model of experimental autoimmune encephalomyelitis (EAE) in mice. C57BL-6 mice were immunized with myelin-oligodendrocyte peptide and treated for 4 weeks with C21 (0.3 mg/kg/day i.p.). Potential effects on myelination, microglia and T-cell composition were estimated by immunostaining and FACS analyses of lumbar spinal cords. The in vivo study was complemented by experiments in aggregating brain cell cultures and microglia in vitro. In the EAE model, treatment with C21 ameliorated microglia activation and decreased the number of total T-cells and CD4+ T-cells in the spinal cord. Fluorescent myelin staining of spinal cords further revealed a significant reduction in EAE-induced demyelinated areas in lumbar spinal cord tissue after AT2R stimulation. C21-treated mice had a significantly better neurological score than vehicle-treated controls. In aggregating brain cell cultures challenged with lipopolysaccharide (LPS) plus interferon-γ (IFNγ), AT2R stimulation prevented demyelination, accelerated re-myelination and reduced the number of microglia. Cytokine synthesis and nitric oxide production by microglia in vitro were significantly reduced after C21 treatment. These results suggest that AT2R stimulation protects the myelin sheaths in autoimmune central nervous system inflammation by inhibiting the T-cell response and microglia activation. Our findings identify the AT2R as a potential new pharmacological target for demyelinating diseases such as multiple sclerosis.

Polygenic risk for schizophrenia associated with working memory-related prefrontal brain activation in patients with schizophrenia and healthy controls.

Schizophrenia is a highly heritable and polygenic disease, and identified common genetic variants have shown weak individual effects. Many studies have reported altered working memory (WM)-related brain activation in schizophrenia, preferentially in the frontal lobe. Such differences in brain activations could reflect inherited alterations possibly involved in the disease etiology, or rather secondary disease-related mechanisms. The use of polygenic risk scores (PGRS) based on a large number of risk polymorphisms with small effects is a valuable approach to examine the effect of cumulative genetic risk on brain functioning. This study examined the impact of cumulative genetic risk for schizophrenia on WM-related brain activations, assessed with functional magnetic resonance imaging. For each participant (63 schizophrenia patients and 118 healthy controls), we calculated a PGRS for schizophrenia based on 18 862 single-nucleotide polymorphism in a large multicenter genome-wide association study including 9146 schizophrenia patients and 12 111 controls, performed by the Psychiatric Genomics Consortium. As expected, the PGRS was significantly higher in patients compared with healthy controls. Further, the PGRS was related to differences in frontal lobe brain activation between high and low WM demand. Specifically, even in absence of main effects of diagnosis, increased PGRS was associated with decreased activation difference in the right middle-superior prefrontal cortex (BA 10/11) and the right inferior frontal gyrus (BA 45). This effect was seen in both cases and controls, and was not influenced by sex, age, or task performance. The findings support the notion of dysregulation of frontal lobe functioning as an inherited vulnerability factor in schizophrenia.

Working memory networks and activation patterns in schizophrenia and bipolar disorder: comparison with healthy controls.

BACKGROUND: Schizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits. AIMS: To determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals. METHOD: Patients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations. RESULTS: Similar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder. CONCLUSIONS: The same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.