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First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d= -0.42,p= 3 x 10(-5)), with weak evidence of IQ reductions among BD-FDRs (d= -0.23,p= .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. in contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment., Australian National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [1037196, 1063960, 1066177, 510135, 1176716]; Canadian Institutes of Health ResearchCanadian Institutes of Health Research (CIHR) [103703, 106469, 142255]; Departament de Salut de la Generalitat de CatalunyaGeneralitat de Catalunya [SLT002/16/00331]; Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [1617]; Development Service Merit Review Award [I01CX000227]; Dokuz Eylul University Department of Scientific Research [2012.KB.SAG.062]; e:Med program [O1ZX1314B, O1ZX1314G]; Ege University School of Medicine Research Foundation [2009-D-00017]; Fundacio Marato TV3 [091630]; Netherlands Organisation for Health Research and DevelopmentNetherlands Organization for Health Research and Development [10-000-1002]; Generalitat de CatalunyaGeneralitat de Catalunya [2017SGR01271]; German Federal Ministry for Education and ResearchFederal Ministry of Education & Research (BMBF); Medical Research CouncilMedical Research Council UK (MRC) [G0901310]; Ministerstvo Zdravotnictvi Ceske Republiky [NR8786, NT13891]; National Alliance for Research on Schizophrenia and DepressionNARSAD [17319, 20244, 26731]; Swiss National Centre of Competence in Research Robotics [51NF40-185897]; National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [1S10OD017974-01, P30 NS076408, R01 MH052857, R01 MH080912, R01 MH113619, U01 MH108150, R01 MH085667]; National Institute on AgingUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Aging (NIA) [T32AG058507]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [P41 EB015922, R01 MH111671, R01 MH116147, R01 MH117601, R01MH121246, R03 MH105808, U54EB020403]; Research Council of NorwayResearch Council of Norway [223273]; Spanish Ministry of Economy and Competitiveness/Instituto de Salud Carlos III [CPII19/00009, PI070066, PI1100683, PI1500467, PI18/00976]; Stanley Medical Research Institute; Swedish Research CouncilSwedish Research Council [K2007-62X-15077-04-1, K2008-62P-20597-01-3, K2010-62X-15078-07-2, K2012-61X-15078-09-3]; Swiss National Science FoundationSwiss National Science Foundation (SNSF) [32003B_156914]; VIDINetherlands Organization for Scientific Research (NWO) [452-11-014, 917-46-370]; Wellcome TrustWellcome Trust [085475/B/08/Z, 085475/Z/08/Z, 064971]; ZonMwNetherlands Organization for Health Research and Development [908-02-123], Australian National Health and Medical Research Council Grants, Grant/Award Numbers: 1037196, 1063960, 1066177, 510135, 1176716; Canadian Institutes of Health Research, Grant/Award Numbers: 103703, 106469, 142255; Departament de Salut de la Generalitat de Catalunya, Grant/Award Number: SLT002/16/00331; Deutsche Forschungsgemeinschaft, Grant/Award Number: 1617; Development Service Merit Review Award, Grant/Award Number: I01CX000227; Dokuz Eylul University Department of Scientific Research Projects Funding, Grant/Award Number: 2012.KB.SAG.062; e:Med program, Grant/Award Numbers: O1ZX1314B, O1ZX1314G; Ege University School of Medicine Research Foundation, Grant/Award Number: 2009-D-00017; Fundacio Marato TV3, Grant/Award Number: 091630; Geestkracht program of the Netherlands Organisation for Health Research and Development, Grant/Award Number: 10-000-1002; Generalitat de Catalunya, Grant/Award Number: 2017SGR01271; German Federal Ministry for Education and Research; Medical Research Council, Grant/Award Number: G0901310; Ministerstvo Zdravotnictvi Ceske Republiky, Grant/Award Numbers: NR8786, NT13891; National Alliance for Research on Schizophrenia and Depression, Grant/Award Numbers: 17319, 20244, 26731; Swiss National Centre of Competence in Research Robotics, Grant/Award Number: 51NF40-185897; National Institute of Mental Health, Grant/Award Numbers: 1S10OD017974-01, P30 NS076408, R01 MH052857, R01 MH080912, R01 MH113619, U01 MH108150, R01 MH085667; National Institute on Aging, Grant/Award Number: T32AG058507; National Institutes of Health, Grant/Award Numbers: P41 EB015922, R01 MH111671, R01 MH116147, R01 MH117601, R01MH121246, R03 MH105808, U54EB020403; Research Council of Norway, Grant/Award Number: 223273; Spanish Ministry of Economy and Competitiveness/Instituto de Salud Carlos III, Grant/Award Numbers: CPII19/00009, PI070066, PI1100683, PI1500467, PI18/00976; Stanley Medical Research Institute; Swedish Research Council, Grant/Award Numbers: K2007-62X-15077-04-1, K2008-62P-20597-01-3, K2010-62X-15078-07-2, K2012-61X-15078-09-3; Swiss National Science Foundation, Grant/Award Number: 32003B_156914; VIDI, Grant/Award Numbers: 452-11-014, 917-46-370; Wellcome Trust, Grant/Award Numbers: 085475/B/08/Z, 085475/Z/08/Z; Wellcome Trust Research Training Fellowship, Grant/Award Number: 064971; ZonMw, Grant/Award Number: 908-02-123

While the biological substrates of brain and behavioural changes in persons with schizophrenia remain unclear, increasing evidence implicates that inflammation is involved. In schizophrenia, including first-episode psychosis and anti-psychotic naive patients, there are numerous reports of increased peripheral inflammation, cognitive deficits and neuropathologies such as cortical thinning. Research defining the relationship between inflammation and schizophrenia symptomatology and neuropathology is needed. Therefore, we analysed the level of C-reactive protein (CRP), a peripheral inflammation marker, and its relationship with cognitive functioning in a cohort of 644 controls and 499 schizophrenia patients. In a subset of individuals who underwent MRI scanning (99 controls and 194 schizophrenia cases), we tested if serum CRP was associated with cortical thickness. CRP was significantly increased in schizophrenia patients compared to controls, co-varying for age, sex, overweight/obesity and diabetes (p

Background: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. Methods: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. Results: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18 < d < 0.22). More (hypo)manic episodes were associated with faster cortical thinning, primarily in the prefrontal cortex. Conclusions: In the hitherto largest longitudinal MRI study on BD, we did not detect accelerated cortical thinning but noted faster ventricular enlargements in BD. However, abnormal frontocortical thinning was observed in association with frequent manic episodes. Our study yields insights into disease progression in BD and highlights the importance of mania prevention in BD treatment.

BackgroundBipolar disorder (BD) is a familial psychiatric disorder associated with frontotemporal and subcortical brain abnormalities. It is unclear whether such abnormalities are present in relatives without BD, and little is known about structural brain trajectories in those at risk.MethodNeuroimaging was conducted at baseline and at 2-year follow-up interval in 90 high-risk individuals with a first-degree BD relative (HR), and 56 participants with no family history of mental illness who could have non-BD diagnoses. All 146 subjects were aged 12–30 years at baseline. We examined longitudinal change in gray and white matter volume, cortical thickness, and surface area in the frontotemporal cortex and subcortical regions.ResultsCompared to controls, HR participants showed accelerated cortical thinning and volume reduction in right lateralised frontal regions, including the inferior frontal gyrus, lateral orbitofrontal cortex, frontal pole and rostral middle frontal gyrus. Independent of time, the HR group had greater cortical thickness in the left caudal anterior cingulate cortex, larger volume in the right medial orbitofrontal cortex and greater area of right accumbens, compared to controls. This pattern was evident even in those without the new onset of psychopathology during the inter-scan interval.ConclusionsThis study suggests that differences previously observed in BD are developing prior to the onset of the disorder. The pattern of pathological acceleration of cortical thinning is likely consistent with a disturbance of molecular mechanisms responsible for normal cortical thinning. We also demonstrate that neuroanatomical differences in HR individuals may be progressive in some regions and stable in others.

Proton magnetic resonance spectroscopy (1H-MRS) studies have examined glutamatergic abnormalities in schizophrenia, mostly in single voxels. Though the critical brain nodes remain unknown, schizophrenia involves networks with broad abnormalities. Hence, glutamine plus glutamate (Glx) and other metabolites were examined with whole-brain 1H-MRS, in early schizophrenia. Three dimensional 1H-MRS was acquired in young schizophrenia subjects (N = 36, 19 antipsychotic-naive and 17 antipsychotic-treated) and healthy controls (HC, N = 29). Glx (as well as N-acetylaspartate, choline, myo-inositol and creatine) group contrasts from all individual voxels that met spectral quality, were analyzed in common brain space, followed by cluster-corrected level alpha-value (CCLAV ≤ 0.05). Schizophrenia subjects had lower Glx in the left superior (STG) and middle temporal gyri (16 voxels, CCLAV = 0.04) and increased creatine in two clusters involving left temporal, parietal and occipital regions (32, and 18 voxels, CCLAV = 0.02 and 0.04, respectively). Antipsychotic-treated and naive patients (vs HC) had similar Glx reductions (8/16 vs 10/16 voxels respectively, but CCLAV’s > 0.05). However, creatine was higher in antipsychotic-treated vs HC’s in a larger left hemisphere cluster (100 voxels, CCLAV = 0.01). Also in treated patients, choline was increased in left middle frontal gyrus (18 voxels, CCLAV = 0.04). Finally in antipsychotic-naive patients, NAA was reduced in right frontal gyri (19 voxels, CCLAV = 0.05) and myo-inositol was reduced in the left cerebellum (34 voxels, CCLAV = 0.02). We conclude that data-driven spectroscopic brain examination supports that reductions in Glx in the left STG may be critical to the pathophysiology of schizophrenia. Postmortem and neuromodulation schizophrenia studies focusing on left STG, may provide critical mechanistic and therapeutic advancements, respectively.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder.In the largest study of hippocampal subfields in bipolar disorder to date, from 23 sites worldwide, we report widespread reductions in nine of 12 subfields.The lack of differences between lithium users and healthy controls supports a possible protective role of lithium in bipolar disorder.

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

Background There is growing evidence for complement system involvement in the pathophysiology of schizophrenia, although the extent and magnitude of complement factor disturbances has not been fully reported. It also remains unclear whether complement abnormalities are characteristic of all patients with schizophrenia or whether they are representative of a subgroup of patients who show signs of heightened inflammation. The aim of the present study was to quantify and compare the levels of a range of complement factors, receptors and regulators in healthy controls and people with schizophrenia and to determine the extent to which the levels of these peripheral molecules relate to measures of brain structure, particularly cortical thickness. Method Seventy-five healthy controls and 90 patients with schizophrenia or schizoaffective disorder were included in the study. Peripheral blood samples were collected from all participants and mRNA expression was quantified in 20 complement related genes, four complement proteins, as well as for four cytokines. T1-weighted structural MRI scans were acquired and analysed to determine cortical thickness measures. Results There were significant increases in peripheral mRNA encoding receptors (C5ar1, CR1, CR3a), regulators (CD55, C59) and protein concentrations (C3, C3b, C4) in people with schizophrenia relative to healthy controls. C4a expression was significantly increased in a subgroup of patients displaying elevated peripheral cytokine levels. A higher inflammation index score derived from mRNA expression patterns predicted reductions in cortical thickness in the temporal lobe (superior temporal gyrus, transverse temporal gyrus, fusiform gyrus, insula) in patients with schizophrenia and healthy controls. Conclusions Analysis of all three major complement pathways supports increased complement activity in schizophrenia and also shows for the first time that peripheral C4a up-regulation is related to increased peripheral pro-inflammatory cytokines in schizophrenia. Our region-specific, neuroimaging findings linked to an increased peripheral complement mRNA expression pattern suggests a role for complement in cortical thinning. Further studies are required to further clarify clinical and neurobiological consequences of aberrant complement levels in schizophrenia and related psychoses.

The primary objectives of this study were to examine referral sources and demographic, clinical, and socioenvironmental characteristics of Hispanics referred to and enrolled in a program of coordinated specialty care (Early CSC program) for first-episode psychosis, to compare them with characteristics of other referred and enrolled racial-ethnic groups, and to identify factors associated with enrollment in the program.A retrospective review was conducted for all individuals referred to and enrolled in the Early CSC program over a 2-year period. Extracted data included referral sources and demographic and clinical characteristics. Zip code-level data from publicly available sources were cross-referenced with individual records. Nonparametric tests and appropriate secondary analysis were used to determine significant differences across racial-ethnic groups referred to (N=180) or enrolled in (N=75) the Early CSC program. A random forest model was used to determine which factors or interacting factors were associated with enrollment among the eligible referrals (N=114).Hispanic individuals were more likely to be referred from inpatient or outpatient mental health providers and not from other community sources. Among eligible Hispanic referrals, those who lived in areas with a lower percentage of Spanish speaking in the home were more likely to enroll in services, compared with those who lived in areas with a higher percentage of Spanish speaking.Continued exploration of factors associated with referral and enrollment in CSC programs for the growing Hispanic ethnic group in the United States can help determine best steps for developing these programs.

Neurobiological models explain increased risk-taking behaviours in adolescence and young adulthood as arising from staggered development of subcortical reward networks and prefrontal control networks. In this study, we examined whether individual variability in impulsivity and reward-related mechanisms is associated with higher level of engagement in risky behaviours and vulnerability to maladaptive outcomes and whether this relationship is mediated by cognitive control ability. A community sample of adolescents, young adults, and adults (age = 15-35 years) completed self-report measures and behavioural tasks of cognitive control, impulsivity, and reward-related mechanisms, and self-reported level of maladaptive outcomes. Behavioural, event-related potential (ERP), and multivariate pattern analysis (MVPA) measures of proactive control were derived from a task-switching paradigm. Adolescents, but not young adults, reported higher levels of impulsivity, reward-seeking behaviours and maladaptive outcomes than adults. They also had lower cognitive control ability, as measured by both self-report and task-based measures. Consistent with models of risk-taking behaviour, self-reported level of cognitive control mediated the relationship between self-reported levels of impulsivity and psychological distress, but the effect was not moderated by age. In contrast, there was no mediation effect of behavioural or EEG-based measures of cognitive control. These findings suggest that individual variability in cognitive control is more crucial to the relationship between risk-taking/impulsivity and outcomes than age itself. They also highlight large differences in measurement between self-report and task-based measures of cognitive control and decision-making under reward conditions, which should be considered in any studies of cognitive control.

The kynurenine pathway (KP) of tryptophan (TRP) catabolism links immune system activation with neurotransmitter signaling. The KP metabolite kynurenic acid (KYNA) is increased in the brains of people with schizophrenia. We tested the extent to which: (1) brain KP enzyme mRNAs, (2) brain KP metabolites, and (3) plasma KP metabolites differed on the basis of elevated cytokines in schizophrenia vs. control groups and the extent to which plasma KP metabolites were associated with cognition and brain volume in patients displaying elevated peripheral cytokines. KP enzyme mRNAs and metabolites were assayed in two independent postmortem brain samples from a total of 71 patients with schizophrenia and 72 controls. Plasma KP metabolites, cognition, and brain volumes were measured in an independent cohort of 96 patients with schizophrenia and 81 healthy controls. Groups were stratified based on elevated vs. normal proinflammatory cytokine mRNA levels. In the prefrontal cortex (PFC), kynurenine (KYN)/TRP ratio, KYNA levels, and mRNA for enzymes, tryptophan dioxygenase (TDO) and kynurenine aminotransferases (KATI/II), were significantly increased in the high cytokine schizophrenia subgroup. KAT mRNAs significantly correlated with mRNA for glial fibrillary acidic protein in patients. In plasma, the high cytokine schizophrenia subgroup displayed an elevated KYN/TRP ratio, which correlated inversely with attention and dorsolateral prefrontal cortex (DLPFC) volume. This study provides further evidence for the role of inflammation in a subgroup of patients with schizophrenia and suggests a molecular mechanism through which inflammation could lead to schizophrenia. Proinflammatory cytokines may elicit conversion of TRP to KYN in the periphery and increase the N-methyl-d-aspartate receptor antagonist KYNA via increased KAT mRNA and possibly more enzyme synthesis activity in brain astrocytes, leading to DLPFC volume loss, and attention impairment in schizophrenia.

Objective Given the increasing research and practice interest in father engagement, this article aimed to develop a clinical narrative integrating the extant research literature to distil key practice recommendations for enhancing father engagement in parenting interventions for child wellbeing. Method A narrative review of research on father engagement in interventions for child wellbeing was conducted, to identify and distil evidence‐based policies and practices to enhance father engagement for practitioners and organisations. Results Six broad policy and practice recommendations are provided that pertain to: engaging the parenting team, avoiding a father deficit model, increasing father awareness of parenting interventions, ensuring father‐inclusive program content and delivery, increasing organisational support for father‐inclusive practice, and increasing professional father engagement training. Conclusion This review provides practitioners with guidelines for enhancing father engagement based on the available research. It also provides recommendations for further research regarding the effectiveness of strategies to enhance father engagement.

Glutamine plus glutamate (Glx), as well as N-acetylaspartate compounds, (NAAc), a marker of neuronal viability, are quantified with proton magnetic resonance spectroscopy (UsedAmongst younger (age ≤40 years-median split) bipolar-I vs HC subjects Glx was increased (p 0.001), while NAAc was reduced in WM (p 0.001). In GM, NAAc (p 0.001) and myo-inositol (p = 0.002) were reduced. Amongst older bipolar-I (vs HC) in WM regions we found reductions in: NAAc (p 0.001), glycerophospho-choline + phospho-choline (p 0.001), creatine + phospho-creatine (p 0.001) and myo-inositol (p 0.001); in GM only Glx was increased (p 0.005). Contrasts between bipolar-I and schizophrenia produced fewer results: amongst younger subjects, reduced NAAc (p 0.001) in WM and lower myo-inositol in GM (p = 0.04) in bipolar-I vs schizophrenia. In the older patients, bipolar-I had lower GM NAAc (p = 0.009) than schizophrenia.First, differential exposure to antipsychotic and mood stabilizing medication across the groups. Second, differences in substance use histories among the groups. Third, neglect of peripheral and ventral cortical and subcortical regions. Finally, limited power to detect bipolar/schizophrenia differences.Chronically-treated bipolar-I have increased Glx and reduced NAAc, suggestive of neuronal dysfunction. The NAAc reductions are more severe in bipolar-I than in schizophrenia patients.

The analysis of time-varying activity and connectivity patterns (i.e., the chronnectome) using resting-state magnetic resonance imaging has become an important part of ongoing neuroscience discussions. The majority of previous work has focused on variations of temporal coupling among fixed spatial nodes or transition of the dominant activity/connectivity pattern over time. Here, we introduce an approach to capture spatial dynamics within functional domains (FDs), as well as temporal dynamics within and between FDs. The approach models the brain as a hierarchical functional architecture with different levels of granularity, where lower levels have higher functional homogeneity and less dynamic behavior and higher levels have less homogeneity and more dynamic behavior. First, a high-order spatial independent component analysis is used to approximate functional units. A functional unit is a pattern of regions with very similar functional activity over time. Next, functional units are used to construct FDs. Finally, functional modules (FMs) are calculated from FDs, providing an overall view of brain dynamics. Results highlight the spatial fluidity within FDs, including a broad spectrum of changes in regional associations, from strong coupling to complete decoupling. Moreover, FMs capture the dynamic interplay between FDs. Patients with schizophrenia show transient reductions in functional activity and state connectivity across several FDs, particularly the subcortical domain. Activity and connectivity differences convey unique information in many cases (e.g., the default mode) highlighting their complementarity information. The proposed hierarchical model to capture FD spatiotemporal variations provides new insight into the macroscale chronnectome and identifies changes hidden from existing approaches.

Genetic and environmental etiologies may contribute to schizophrenia and its associated neurobiological profile. We examined the interaction between dopaminergic polymorphisms, childhood adversity and diagnosis (schizophrenia/schizoaffective disorder) on dopamine-related brain structures. Childhood adversity histories and structural MRI data were obtained from 249 (153 schizophrenia/schizoaffective, 96 controls) participants registered in the Australian Schizophrenia Research Bank. Polymorphisms in DRD2 and COMT were genotyped and a dopaminergic risk allelic load (RAL) was calculated. Regression analysis was used to test the main and interaction effects of RAL, childhood adversity and diagnosis on volumes of dopamine-related brain structures (caudate, putamen, nucleus accumbens, dorsolateral prefrontal cortex and hippocampus). A schizophrenia/schizoaffective diagnosis showed significant main effects on bilateral hippocampus, left dorsolateral prefrontal cortex and bilateral putamen volumes. RAL showed a significant main effect on left putamen volumes. Furthermore, across the whole sample, a significant two-way interaction between dopaminergic RAL and childhood adversity was found for left putamen volumes. No brain structure volumes were predicted by a three-way interaction that included diagnosis. Our finding suggests the left putamen may be particularly sensitive to dopaminergic gene-environment interactions regardless of diagnosis. However, larger studies are needed to assess whether these interactions are more or less pronounced in those with schizophrenia/schizoaffective disorders.

While high levels of glucocorticoids are generally neuro-damaging, a related adrenal steroid, dehydroepiandrosterone (DHEA), has anti-glucocorticoid and neuroprotective properties. Previous work has shown increased circulating levels of DHEA and abnormal cortisol/DHEA ratios in people with schizophrenia, however reports are limited and their relationship to neuropathology is unclear. We performed the largest study to date to compare levels of serum DHEA and cortisol/DHEA ratios in people with schizophrenia and healthy controls, and investigated the extent to which cortisol/DHEA ratios predict brain volume. Serum cortisol and DHEA were assayed in 94 people with schizophrenia and 81 healthy controls. T1-weighted high-resolution anatomical scans were obtained using a 3 T Achieva scanner on a subset of 59 people with schizophrenia and 60 healthy controls. Imaging data were preprocessed and analyzed using SPM12. People with schizophrenia had significantly increased serum DHEA levels (p = 0.002), decreased cortisol/DHEA ratios (p = 0.02) and no difference in cortisol levels compared to healthy controls. Cortisol/DHEA ratios were inversely correlated with hippocampal (r = -0.33 p = 0.01) and dorsolateral prefrontal cortex (r = -0.30, p = 0.02) volumes in patients. Our findings suggest that the cortisol/DHEA ratio may be a molecular blood signature of hippocampal and cortical damage. These results further implicate the role of DHEA and hypothalamic-pituitary-adrenal axis dysfunction in the pathophysiology of schizophrenia.

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multicenter structural magnetic resonance imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male), and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. Increases were observed in different brain regions in males and females, with larger effect sizes in females. BSC correlated with ADOS-2 Calibrated Severity Score in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared with cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.

Adolescence is a transitional period between childhood and adulthood characterized by significant changes in global and regional brain tissue volumes. It is also a period of increasing vulnerability to psychiatric illness. The relationship between these patterns and increased levels of circulating sex steroids during adolescence remains unclear. The objective of the current study was to determine whether gonadectomy, prior to puberty, alters adolescent brain development in male rhesus macaques. Ninety-six structural MRI scans were acquired from 12 male rhesus macaques (8 time points per animal over a two-year period). Six animals underwent gonadectomy and 6 animals underwent a sham operation at 29 months of age. Mixed-effects models were used to determine whether gonadectomy altered developmental trajectories of global and regional brain tissue volumes. We observed a significant effect of gonadectomy on the developmental trajectory of prefrontal gray matter (GM), with intact males showing peak volumes around 3.5 years of age with a subsequent decline. In contrast, prefrontal GM volumes continued to increase in gonadectomized males until the end of the study. We did not observe a significant effect of gonadectomy on prefrontal white matter or on any other global or regional brain tissue volumes, though we cannot rule out that effects might be detected in a larger sample. Results suggest that the prefrontal cortex is more vulnerable to gonadectomy than other brain regions.

Altres ajuts: SRB: The Australian Schizophrenia Research Bank (ASRB) was supported by the National Health and Medical Research Council of Australia (NHMRC) (Enabling Grant, ID 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation and the Schizophrenia Research Institute. Chief Investigators for ASRB were Carr, V., Schall, U., Scott, R., Jablensky, A., Mowry, B., Michie, P., Catts, S., Henskens, F., Pantelis, C. We thank Loughland, C., the ASRB Manager, and acknowledge the help of Jason Bridge for ASRB database queries. CP was supported by NHMRC Senior Principal Research Fellowships (IDs: 628386 & 1105825); GC was supported by the Schizophrenia Research Institute utilizing infrastructure funding from the New South Wales Ministry of Health and New South Wales Ministry of Trade and Investment (Australia); JMF was supported by NHMRC project grant (1063960) and the Janette Mary O'Neil Research Fellowship; MJG was supported by NHMRC as an R.D. Wright Biomedical Career Development Fellow (1061875). MJC was supported by NHMRC Senior Research Fellowship (1121474). CASSI: CSW is funded by the NSW Ministry of Health, Office of Health and Medical Research. CSW is a recipient of a National Health and Medical Research Council (Australia) Principal Research Fellowship (PRF) (#1117079). CIAM: The CIAM study (FMH - PI) was supported by the University Research Committee, University of Cape Town and South African funding bodies National Research Foundation and Medical Research Council. COBRE: The COBRE dataset and investigators were supported by NIH grants R01EB006841 & P20GM103472, as well as NSF grant 1539067. JT (senior author) and VDC are supported by 5R01MH094524. JMS is supported by R01 AA021771 and P50 AA022534. EONCKS: This work was supported by a New Partnership for Africa's Development (NEPAD) grant through the Department of Science and Technology of South Africa, the Medical Research Council of South Africa (grant number 65174). ESO: The ESO study was funded by NPU I - LO1611 and Ministry of Health, Czech Republic - Conceptual Development of Research Organization 00023001 (IKEM). FIDMAG/Project: This work was supported by the Catalan Government and several grants from the Instituto de Salud Carlos III and co-funded by European Union (ERDF/ESF, 'Investing in your future'): Miguel Servet Research Contracts and Research Project Grants. FOR2107 Marburg: The FOR2107 Marburg study was funded by the German Research Foundation (DFG), Tilo Kircher (speaker FOR2107; DFG grant numbers KI588/14-1, KI588/14-2), Axel Krug (KR 3822/5-1, KR 3822/7-2), Igor Nenadic (NE 2254/1-2), Carsten Konrad (KO 4291/3-1). FOR2107 Muenster: The FOR2107 Muenster study was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). TH was supported by grants from the German Research Foundation (DFG grants HA7070/2-2, HA7070/3, HA7070/4). Frankfurt: MRI was performed at the Frankfurt Brain Imaging Center, supported by the German Research Council (DFG) and the German Ministry for Education and Research (BMBF; Brain Imaging Center Frankfurt/Main, DLR 01GO0203). GIPSI: This study was supported by Colciencias PRISMA-U.T. Huilong1 & Huilong2: This study was funded by the National Natural Science Foundation of China (81761128021; 31671145; 81401115; 81401133), Beijing Municipal Science and Technology Commission grant (Z141107002514016) and Beijing Natural Science Foundation(7162087, Beijing Municipal Administration of Hospitals Clinical medicine Development of special funding (XMLX201609; zylx201409). IGP: This study was funded by Project Grants from the Australian National Health and Medical Research Council of Australia (NHMRC; APP630471 and APP1081603), the Macquarie University's Australian Research Council Centre of Excellence in Cognition and its Disorders (CE110001021). Johns Hopkins: Supported by National Institutes of Health Grant Nos. MH-092443, MH-094268 (Silvio O. Conte Center), MH-105660, and MH-107730; foundation grants from Stanley, RUSK/S-R, and NARSAD/Brain and Behavior Research Foundation. Madrid: Supported by the Spanish Ministry of Science, Innovation and Universities, Instituto de Salud Carlos III, co-financed by ERDF Funds from the European Commission, "A way of making Europe", CIBERSAM. Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds and European Union Seventh Framework Program and H2020 Program; Fundación Familia Alonso, Fundación Alicia Koplowitz and Fundación Mutua Madrileña. MPRC1 & MPRC2: Support was received from NIH grants U01MH108148, 2R01EB015611, R01MH112180, R01DA027680, R01MH085646, P50MH103222 and T32MH067533, a State of Maryland contract (M00B6400091) and NSF grant (1620457). OLIN: The Olin study was supported by NIH grants R37MH43375 and R01MH074797. Oxford: The Oxford study MRC G0500092. SLF Rome: Support from the Italian Ministry of Health grants RC-12-13-14-15-16-17-18-19/A. RSCZ: RSCZ data collection was supported by RFBR 15-06-05758 grant. SCORE: This study was supported in part by grant 3232BO_119382 from the Swiss National Science Foundation. We thank the FePsy (Frueherkennung von Psychosen; early detection of psychosis) Study Group from the University of Basel, Department of Psychiatry, Switzerland, for the recruitment of the study participants. The FePsy Study was supported in part by grant No. SNF 3200-057216/1, ext./2, ext./3. Singapore: This study was supported by research grants from the National Healthcare Group, Singapore (SIG/05004; SIG/11003), and the Singapore Bioimaging Consortium (RP C-009/2006) research grants awarded to KS. SNUH: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant no. 2013R1A2A1A03071089 and 2017M3C7A1029610). UCISZ: The UCISZ study was supported by the National Institutes of Mental Health grant number R21MH097196 to TGMvE. UCISZ data were processed by the UCI High Performance Computing cluster supported by Joseph Farran, Harry Mangalam, and Adam Brenner and the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1 TR000153. UNIBA: The UNIBA study was supported by grant funding from the Italian Ministry of Health (PE-2011-02347951). UNIMAAS: The study was supported by Dutch Organization for Health Research and Development (ZonMw 91112002) and a personal grant to Thérèse van Amelsvoort (ZonMw-VIDI: 91712394). The data was collected in a clinical trial registered in the Dutch clinical trial registry under ID: NTR5094 (http://www.trialregister.nl). UPenn: This study was supported by the National Institute of Mental Health grants MH064045, MH 60722, MH019112, MH085096 (DHW), and R01MH112847 (RTS and TDS). Zurich: This study was supported by the Swiss National Science Foundation (105314_140351 to S.K.). Matthias Kirschner acknowledges support from the National Bank Fellowship (McGill University) and the Swiss National Foundation (P2SKP3_178175). Research reported in this publication was also supported by the following National Institutes of Health grants: U54 EB020403 to PMT, R01 MH116147, U24 RR21992, R21MH097196, and TR000153 to TGMvE, S10 OD023696 and R01EB015611 to PK, T32 AG058507and 5T32 MH073526 to CRKC, R01 MH117601 to NJ, ENIGMA's NIH Big Data to Knowledge (BD2K) initiative U54 EB020403, ENIGMA Sex Differences R01MH116147, and ENIGMA-COINSTAC: Advanced World-wide Transdiagnostic Analysis of Valence System Brain Circuits R01MH121246. A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multi-center magnetic resonance structural imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male) and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Increases were observed in different brain regions in males and females, with larger effect sizes in females. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. BSC correlated with ADOS-2 CSS in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared to cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.

Bipolar disorder is associated with cognitive deficits and cortical changes for which the developmental dynamics are not well understood. The dopamine D2 receptor (DRD2) gene has been associated with both psychiatric disorders and cognitive variability. Here we examined the mediating role of brain structure in the relationship between DRD2 genomic variation and cognitive performance, with target cortical regions selected based on evidence of association with DRD2, bipolar disorder and/or cognition from prior literature. Participants (n = 143) were aged 12–30 years and comprised 62 first-degree relatives of bipolar patients (deemed ‘at-risk’), 55 controls, and 26 patients with established bipolar disorder; all were unrelated Caucasian individuals with complete data across the three required modalities (structural magnetic resonance imaging, neuropsychological and genetic data). A DRD2 haplotype was derived from three functional polymorphisms (rs1800497, rs1076560, rs2283265) associated with alternative splicing (i.e., D2-short/-long isoforms). Moderated mediation analyses explored group differences in relationships between this DRD2 haplotype, three structural brain networks which subsume the identified cortical regions of interest (frontoparietal, dorsal-attention, and ventral-attention), and three cognitive indices (intelligence, attention, and immediate memory). Controls who were homozygous for the DRD2 major haplotype demonstrated greater cognitive performance as a result of dorsal-attention network mediation. However, this association was absent in the ‘at-risk’ group. This study provides the first evidence of a functional DRD2-brain-cognition pathway. The absence of typical brain-cognition relationships in young ‘at-risk’ individuals may reflect biological differences that precede illness onset. Further insight into early pathogenic processes may facilitate targeted early interventions.

SummaryHuman brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genesGPR139, DACH1andAPOEare associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that has been gaining increasing interest as a method to investigate the brain function of individuals on the autism spectrum. It is a non-invasive, portable and relatively motion-tolerant method of measuring haemodynamic activity in the brain. fNIRS can be particularly effective for quantifying brain function in challenging clinical populations. In light of this, there is a growing body of fNIRS literature focusing on individuals on the autism spectrum. The aim of this review is to evaluate and summarise key studies from the literature and discuss their implications for the field. Potential limitations of the fNIRS approach and resolution of these issues based on emerging fNIRS research are also discussed.

Background: It is well established that people with an intellectual disability have high rates of mental health problems, yet rates of uptake of services do not match need. Aim: To identify the cur...

BackgroundIdentifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention.MethodIn total 287 participants aged 12–30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes.ResultsAt baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of ‘conversion’ to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania.ConclusionsThis study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

Contains fulltext : 191289.pdf (Publisher’s version ) (Open Access) Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 x 10(-21)), left fusiform gyrus (d=-0.288; P=8.25 x 10(-21)) and left rostral middle frontal cortex (d=-0.276; P=2.99 x 10(-19)). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.

Evidence-based parenting interventions have been developed and evaluated largely with mothers. This study examined practitioner reports of rates of father attendance, barriers to engagement, organizational support for father-inclusive practice, participation in training in father engagement, and competencies in working with fathers. It also explored predictors of practitioner competence and rates of father attendance. Practitioners (N = 210) who delivered parenting interventions completed an online survey. Participants reported high levels of confidence in engaging fathers, but only one in three had participated in training and levels of father attendance in parenting interventions were low. Logistic regressions showed that high levels of practitioner competence were predicted by participation in training. Moderate levels of father attendance (vs. low levels) were predicted by greater number of years of experience while high levels of attendance (vs. low levels) were predicted by greater experience, higher levels of competence and higher levels of organizational support. The implications of the findings to informing policy and practice for enhancing father engagement are discussed.

Bipolar disorder (BD) is characterized by a dysregulation of affect and impaired integration of emotion with cognition. These traits are also expressed in probands at high genetic risk of BD. The inferior frontal gyrus (IFG) is a key cortical hub in the circuits of emotion and cognitive control, and it has been frequently associated with BD. Here, we studied resting-state functional connectivity of the left IFG in participants with BD and in those at increased genetic risk.Using resting-state functional magnetic resonance imaging we compared 49 young BD participants, 71 individuals with at least one first-degree relative with BD (at-risk), and 80 control subjects. We performed between-group analyses of the functional connectivity of the left IFG and used graph theory to study its local functional network topology. We also used machine learning to study classification based solely on the functional connectivity of the IFG.In BD, the left IFG was functionally dysconnected from a network of regions, including bilateral insulae, ventrolateral prefrontal gyri, superior temporal gyri, and the putamen (p.001). A small network incorporating neighboring insular regions and the anterior cingulate cortex showed weaker functional connectivity in at-risk than control participants (p.006). These constellations of regions overlapped with frontolimbic regions that a machine learning classifier selected as predicting group membership with an accuracy significantly greater than chance.Functional dysconnectivity of the IFG from regions involved in emotional regulation may represent a trait abnormality for BD and could potentially aid clinical diagnosis.

Although brain changes in schizophrenia have been proposed to mirror those found with advancing age, the trajectory of gray matter and white matter changes during the disease course remains unclear. The authors sought to measure whether these changes in individuals with schizophrenia remain stable, are accelerated, or are diminished with age.Gray matter volume and fractional anisotropy were mapped in 326 individuals diagnosed with schizophrenia or schizoaffective disorder and in 197 healthy comparison subjects aged 20-65 years. Polynomial regression was used to model the influence of age on gray matter volume and fractional anisotropy at a whole-brain and voxel level. Between-group differences in gray matter volume and fractional anisotropy were regionally localized across the lifespan using permutation testing and cluster-based inference.Significant loss of gray matter volume was evident in schizophrenia, progressively worsening with age to a maximal loss of 8% in the seventh decade of life. The inferred rate of gray matter volume loss was significantly accelerated in schizophrenia up to middle age and plateaued thereafter. In contrast, significant reductions in fractional anisotropy emerged in schizophrenia only after age 35, and the rate of fractional anisotropy deterioration with age was constant and best modeled with a straight line. The slope of this line was 60% steeper in schizophrenia relative to comparison subjects, indicating a significantly faster rate of white matter deterioration with age. The rates of reduction of gray matter volume and fractional anisotropy were significantly faster in males than in females, but an interaction between sex and diagnosis was not evident.The findings suggest that schizophrenia is characterized by an initial, rapid rate of gray matter loss that slows in middle life, followed by the emergence of a deficit in white matter that progressively worsens with age at a constant rate.

Background Higher inflammation has been identified in a substantial subset of both high-risk and chronically ill patients with schizophrenia and related psychoses and this may account for some of the heterogeneity of the schizophrenia. There is also much heterogeneity in cognitive deficits related to schizophrenia with some patients showing a marked decline from premorbid intellectual levels while others show little change from either normal or low intellect. However, the relationship between intellectual change with the illness onset and inflammation in schizophrenia has not been established. Methods Here, we report the assessment of two common markers of inflammation from two independent samples of generally chronically ill patients with schizophrenia and related psychoses (one sample of 73 patients versus 70 healthy controls from Sydney, NSW, Australia and one sample of 297 patients from Syracuse, NY, USA). Peripheral venous blood samples were collected from all patients and blood markers of inflammation (C-Reactive Protein, CRP, and Neutrophil to Lymphocyte Ratio, NLR) were assayed using standard procedures. Assessment of premorbid and current intellectual abilities were obtained from the Sydney cohort of patients. Results Grouping the patients and controls from the Sydney sample into those with elevated (> 3 mg/L) versus normal (< 3 mg/L) CRP levels revealed 42% of the patients versus 20% of the healthy controls had elevated CRP (Chi Square = 9.16, p = .002) and further evidence of inflammation with an elevated mean NLR of 2.5. The frequency of peripheral inflammation was confirmed by the independent sample from Syracuse in which 39% of the patients (n= 115) had an elevated NLR above a cutoff score for normal of 2.2 which was consistent with the Sydney sample. Patients from the Sydney sample who had an elevated CRP also had a significant mean 15-point IQ decline from premorbid IQ levels, whereas the patients with CRP levels within normal limits did not show a statistically significant drop in IQ from premorbid levels (mean IQ decline 7.6 points). Healthy controls with normal CRP had no IQ change (0.0 points) and healthy controls with elevated CRP has a slight, non-significant IQ decline (mean 2.3 points). Discussion Thus, our study showed supportive evidence of elevated peripheral inflammation markers in subgroups of chronically ill patients with schizophrenia from two independent samples and a link between marked intellectual decline from premorbid levels and current peripheral inflammation in one chronically ill subgroup of patients with schizophrenia suggesting a role for inflammation in the cognitive impairment of a substantial proportion (40%) of patients with schizophrenia.

Emerging evidence suggests that psychiatric disorders are associated with disturbances in structural brain networks. Little is known, however, about brain networks in those at high risk (HR) of bipolar disorder (BD), with such disturbances carrying substantial predictive and etiological value. Whole-brain tractography was performed on diffusion-weighted images acquired from 84 unaffected HR individuals with at least one first-degree relative with BD, 38 young patients with BD and 96 matched controls (CNs) with no family history of mental illness. We studied structural connectivity differences between these groups, with a focus on highly connected hubs and networks involving emotional centres. HR participants showed lower structural connectivity in two lateralised sub-networks centred on bilateral inferior frontal gyri and left insular cortex, as well as increased connectivity in a right lateralised limbic sub-network compared with CN subjects. BD was associated with weaker connectivity in a small right-sided sub-network involving connections between fronto-temporal and temporal areas. Although these sub-networks preferentially involved structural hubs, the integrity of the highly connected structural backbone was preserved in both groups. Weaker structural brain networks involving key emotional centres occur in young people at genetic risk of BD and those with established BD. In contrast to other psychiatric disorders such as schizophrenia, the structural core of the brain remains intact, despite the local involvement of network hubs. These results add to our understanding of the neurobiological correlates of BD and provide predictions for outcomes in young people at high genetic risk for BD.

People with schizophrenia show decreased prefrontal cortex (PFC) activity during emotional response inhibition, a cognitive process sensitive to hormonal influences. Raloxifene, a selective estrogen receptor modulator, binds estrogen receptor alpha (ESR-α), improves memory, attention and normalizes cortical and hippocampal activity during learning and emotional face recognition in schizophrenia. Here, we tested the extent to which raloxifene restores neuronal activity during emotional response inhibition in schizophrenia. Since genetic variation in estrogen receptor alpha (ESR-1) determines cortical ESR-α production and correlates with cognition, we also predicted that genetic ESR-1 variation would differentially relate to increased cortical activity by raloxifene administration. Thirty people with schizophrenia participated in a thirteen-week randomized, double-blind, placebo-controlled, cross-over adjunctive treatment trial of raloxifene administered at 120mg/day. Effects of raloxifene on brain activation were assessed based on ESR-1 genotype using functional magnetic resonance imaging during emotional word inhibition. Raloxifene increased PFC activity during inhibition of response to negative words and the raloxifene related increased PFC activity was greater in patients homozygous for ESR-1 rs9340799 AA relative to G carriers. Comparison to 23 healthy controls demonstrated that PFC activity of people with schizophrenia receiving raloxifene was more similar to controls than to their own brain activity during placebo. Estrogen receptor modulation by raloxifene restores PFC activity during emotional response inhibition in schizophrenia and ESR-1 genotype predicts degree of increased neural activity in response to raloxifene. While these preliminary results require replication, they suggest the potential for personalized pharmacotherapy using ESR-1 and estrogen receptor targeting compounds in schizophrenia.

Task-switching performance relies on a broadly distributed frontoparietal network and declines in older adults. In this study, they investigated whether this age-related decline in task switching performance was mediated by variability in global or regional white matter microstructural health. Seventy cognitively intact adults (43-87 years) completed a cued-trials task switching paradigm. Microstructural white matter measures were derived using diffusion tensor imaging (DTI) analyses on the diffusion-weighted imaging (DWI) sequence. Task switching performance decreased with increasing age and radial diffusivity (RaD), a measure of white matter microstructure that is sensitive to myelin structure. RaD mediated the relationship between age and task switching performance. However, the relationship between RaD and task switching performance remained significant when controlling for age and was stronger in the presence of cardiovascular risk factors. Variability in error and RT mixing cost were associated with RaD in global white matter and in frontoparietal white matter tracts, respectively. These findings suggest that age-related increase in mixing cost may result from both global and tract-specific disruption of cerebral white matter linked to the increased incidence of cardiovascular risks in older adults. Hum Brain Mapp 38:1588-1603, 2017. © 2016 Wiley Periodicals, Inc.

Individuals with schizophrenia who are homozygous at the c.267C>A single nucleotide polymorphism (rs2067477) within the cholinergic muscarinic M1 receptor gene have been reported to perform less well on the Wisconsin Card Sorting Test and demonstrate reduced grey matter volume in the right precentral gyrus. We investigated if rs2067477 genotype variation influenced cortical thickness and cortical surface area in a sample of 176 schizophrenia/schizoaffective disorder patients using FreeSurfer. We were unable to detect any significant changes to either surface-based measure of brain structure across genotype. Future studies should expand the focus and include SNPs that are in linkage disequilibrium with rs2067477.

Evidence-based parenting interventions are effective in reducing conduct problems, yet these interventions have limited reach, and few involve the participation of fathers. This paper describes the outcomes of an open trial of ParentWorks, a universal, online, father-inclusive parenting intervention aiming to decrease childhood behavioural problems and promote positive parenting in mothers and fathers. A total of 388 families (456 individual parents; 36.6% fathers) were included in the study. Mixed model analyses showed significant decreases in child emotional/behavioural problems, dysfunctional parenting, interparental conflict, and parental mental health problems. The baseline severity of child behavioural problems significantly moderated the effects on child outcomes so that children with higher levels of problems benefitted more from the program. Participation of both caregivers in two-parent families, as well as parent sex, did not significantly affect the program outcomes. Results provide initial empirical support for the universal, self-directed, online parenting intervention, in addressing both child behavioural problems and parenting outcomes. Trial registration: ACTRN12616001223426, registered 05/09/2016. Electronic supplementary material The online version of this article (10.1007/s10578-019-00934-0) contains supplementary material, which is available to authorized users.

WOS: 000485217300010, PubMed ID: 31443932, BACKGROUND: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. METHODS: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. RESULTS: FDRs-BD had significantly larger ICV (d = +10.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. CONCLUSIONS: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct., Research Council of NorwayResearch Council of Norway [223273]; National Institutes of Health (NIH)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01 MH117601, R01 MH116147, R01 MH111671, P41 EB015922, 5T32MH073526, U54EB020403, R03 MH105808]; National Institute on Aging (NIA)United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute on Aging (NIA) [T32AG058507]; Canadian Institutes of Health ResearchCanadian Institutes of Health Research (CIHR) [103703, 106469, 341717]; National Centre for Mental Health; 2010 National Alliance for Research on Schizophrenia and Depression (NARSAD) Young Investigator Award [17319]; Dokuz Eylul University Department of Scientific Research Projects FundingDokuz Eylul University [2012.KB.SAG.062]; National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London; Ege University School of Medicine Research Foundation [2009-D-00017]; Medical Research CouncilMedical Research Council UK (MRC) [G0901310]; Geestkracht program of the Netherlands Organisation for Health Research and Development [10-000-1002]; National Institute of Mental HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH 085667]; Nova Scotia Health Research Foundation; Dalhousie Clinical Research Scholarship; 2007 Brain and Behavior Research Foundation Young Investigator Award; Ministry of Health of the Czech RepublicMinistry of Health, Czech Republic [NR8786, NT13891]; Swedish Research CouncilSwedish Research Council [K2007-62X-15077-04-1, K2008-62P-20597-01-3, K2010-62X-15078-07-2, K2012-61X-15078-09-3]; Stockholm County CouncilStockholm County Council; Karolinska InstitutetKarolinska Institutet; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation; HUBIN project; Spanish Ministry of Economy and Competitiveness/Instituto de Salud Carlos III [PI070066, PI1100683, PI1500467]; Fundacio Marato TV3 [091630]; ERDF Funds from the European Commission A Way of Making Europe"); Brain and Behaviour Research Foundation (NARSAD Young Investigator Award); Alicia Koplowitz Foundation; Stanley Medical Research Institute; NARSADNARSAD [20244]; Wellcome TrustWellcome Trust [064971, 085475/B/08/Z, 085475/Z/08/Z]; NARSAD Young Investigator AwardNARSAD; European CommunityEuropean Community (EC); NIMH Intramural Research ProgramUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH); NIHR Biomedical Research Centre at University College London Hospital; British Medical Association Margaret Temple Fellowship 2016; German Federal Ministry for Education and ResearchFederal Ministry of Education & Research (BMBF) [O1ZX1314B, O1ZX1314G]; Deutsche ForschungsgemeinschaftGerman Research Foundation (DFG) [1617]; NIMHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Mental Health (NIMH) [R01 MH116147, R01 MH113619]; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [U01 MH097435, R01 MH084803, R01 EB020062, R01 MH080912, R01 MH052857]; National Science FoundationNational Science Foundation (NSF) [1636893, 1734853]; Australian National Health and Medical Research CouncilNational Health and Medical Research Council of Australia [510135, 1037196, 1063960, 1066177]; ZonMwNetherlands Organization for Health Research and Development [908-02-123]; VIDINetherlands Organization for Scientific Research (NWO) [452-11-014, 917-46-370]; Janssen PharmaceuticaJohnson & Johnson USAJanssen Biotech Inc; Otsuka PharmaceuticalOtsuka Pharmaceutical; Bipolar Disorder Research Network, The researchers and studies included in this article were supported by the Research Council of Norway (Grant No. 223273), National Institutes of Health (NIH) (Grant No. R01 MH117601 [to NJ], Grant Nos. R01 MH116147, R01 MH111671, and P41 EB015922 [to PMT], Grant Nos. 5T32MH073526 and U54EB020403 [to CRKC], and Grant No. R03 MH105808 [to CEB and SCF]) and National Institute on Aging (NIA) (Grant No. T32AG058507 [to CRKC]).; C-SFS: This work was supported by Canadian Institutes of Health Research.; Cardiff: This work was supported by the National Centre for Mental Health, Bipolar Disorder Research Network, 2010 National Alliance for Research on Schizophrenia and Depression (NARSAD) Young Investigator Award (Grant No. 17319).; DEU: This work was supported by Dokuz Eylul University Department of Scientific Research Projects Funding (Grant No. 2012. KB. SAG. 062). This report represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the National Health Service, NIHR, or Department of Health.; EGEU: This work was supported by the Ege University School of Medicine Research Foundation (Grant No. 2009-D-00017).; EHRS: The Edinburgh High Risk Study was supported by the Medical Research Council.; GROUP: The infrastructure for the GROUP study was supported by the Geestkracht program of the Netherlands Organisation for Health Research and Development (Grant No. 10-000-1002).; ENBD_UT/BPO_FLB: This work was supported by the National Institute of Mental Health (Grant No. R01 MH 085667).; HHR/PHHR: This work was supported by the Canadian Institutes of Health Research (Grant Nos. 103703, 106469, and 341717), Nova Scotia Health Research Foundation, Dalhousie Clinical Research Scholarship (to TH), 2007 Brain and Behavior Research Foundation Young Investigator Award (to TH), and Ministry of Health of the Czech Republic (Grant Nos. NR8786 and NT13891).; HUBIN: This work was supported by the Swedish Research Council (Grant Nos. K2007-62X-15077-04-1, K2008-62P-20597-01-3, K2010-62X-15078-07-2, K2012-61X-15078-09-3), regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet, Knut and Alice Wallenberg Foundation, and HUBIN project.; IDIBAPS: This work was supported by the Spanish Ministry of Economy and Competitiveness/Instituto de Salud Carlos III (Grant Nos. PI070066, PI1100683, and PI1500467) and Fundacio Marato TV3 (Grant No. 091630), co-financed by ERDF Funds from the European Commission A Way of Making Europe"), Brain and Behaviour Research Foundation (NARSAD Young Investigator Award), and Alicia Koplowitz Foundation.; IoP-BD: The Maudsley Bipolar Twin Study was supported by the Stanley Medical Research Institute and NARSAD.; IoP-SZ: This work was supported by a Wellcome Trust Research Training Fellowship (Grant No. 064971 to MMP), NARSAD Young Investigator Award (to TT), and European Community's Sixth Framework Programme through a Marie Curie Training Network called the European Twin Study Network on Schizophrenia.; Lieber Institute for Brain Development (LIBD): This work was supported by the NIMH Intramural Research Program (to DRW's laboratory). LIBD is a nonprofit research institute located in Baltimore, MD. The work performed at LIBD was performed in accordance with an NIMH material transfer agreement with LIBD.; MFS: The Maudsley Family Study cohort collection was supported by the Wellcome Trust (Grant Nos. 085475/B/08/Z and 085475/Z/08/Z), NIHR Biomedical Research Centre at University College London Hospital, Medical Research Council (Grant No. G0901310), and British Medical Association Margaret Temple Fellowship 2016.; MooDS: This work was supported by the German Federal Ministry for Education and Research grants NGFNplus MooDS (Systematic Investigation of the Molecular Causes of Major Mood Disorders and Schizophrenia) and Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e: Med program (Grant Nos. O1ZX1314B and O1ZX1314G) and Deutsche Forschungsgemeinschaft (Grant No. 1617 [to AH]).; MSSM: This work was supported by NIMH (Grant Nos. R01 MH116147 and R01 MH113619).; NU: This work was supported by NIH (Grant Nos. U01 MH097435, R01 MH084803, and R01 EB020062) and National Science Foundation (Grant Nos. 1636893 and 1734853).; OLIN: This work was supported by NIH (Grant No. R01 MH080912).; STAR: This work was supported by NIH (Grant No. R01 MH052857).; SydneyBipolarGroup: The Australian cohort collection was supported by the Australian National Health and Medical Research Council Program Grants (Grant No. 510135 [to PBM] and Grant No. 1037196 [to PBM and PRS]) and Project Grants (Grant No. 1063960 [to JMF and PRS] and Grant No. 1066177 [to JMF]).; UMCU: This work was supported by NARSAD (Grant No. 20244 [to MHJH]), ZonMw (Grant No. 908-02-123 [to HEHP]), VIDI (Grant No. 452-11-014 [to NEMvH] and Grant No. 917-46-370 [to HEHP]), and Stanley Medical Research Institute.; CliNG: We thank Anna Fanelli, Kathrin Jakob, and Maria Keil for help with data acquisition.; All authors have contributed to and approved the contents of this manuscript.; GS has received research and travel support from Janssen Pharmaceutica and Otsuka Pharmaceutical and honoraria from Adamed Pharma. NY has been an investigator in clinical studies conducted together with Janssen-Cilag, Corcept Therapeutics, and COMPASS Pathways in the last 3 years. AM-L has received consultant fees from Boehringer Ingelheim, BrainsWay, Elsevier, Lundbeck International Neuroscience Foundation, and Science Advances. CRKC has received partial research support from Biogen, Inc. (Boston, MA) for work unrelated to the topic of this manuscript. The remaining authors report no biomedical financial interests or potential conflicts of interest.

Background Internationally, from 12.2–23.4% of youth (aged 16–24 years) are not in employment, education or training (NEET). These disengaged youth are more likely to experience social exclusion, increased psychological distress and poor quality of life. Youth at risk of disengagement are less likely to access traditional support services, requiring development of innovative interventions. Methods The trial is a single blind, three arm, randomised controlled trial evaluating the effectiveness of a telephone delivered psychological intervention for disengaged youth (12–25 years). Participants will be randomised to receive either (i) SWEL, (ii) Befriending, or (iii) Single Session Psycho-Education. Therapy will be over an 8 week period with a minimum of four and maximum of eight sessions for the SWEL or Befriending conditions, or a single session for the Psycho-Education condition. Outcomes will be assessed at baseline and at 2, 8 and 14-month follow-up with the primary outcome being re-engagement in education, training or employment. Discussion This large, multi-site, randomised controlled trial will inform the delivery of services for young people at risk of disengaging from education or training. The provision of psychological therapy by telephone increases access by youth – especially those in rural and remote areas - both to the trial and the treatment, if adopted by services. The outcomes of this trial could have meaningful societal impact for a vulnerable population. It is expected that recruitment, intervention and retention will present challenges for the trial given the focus on disengaged youth. Trial registration ANZCTR, ACTRN12614001212640, Registered 18 Nov 2014. Retrospectively registered. Ethics and dissemination Ethics approval has been obtained from the participating institutions. Results of the trial will be submitted for publication in peer reviewed journals and findings presented at scientific conferences and to key service providers and policy makers.