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Contains fulltext : 248376.pdf (Publisher’s version ) (Open Access) For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Special Issue: The ENIGMA Consortium: the first 10 years., Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., European Community's Seventh Framework Programme, Grant/Award Numbers: 278948, 602450, 603016, 602805; US National Institute of Child Health and Human Development, Grant/Award Numbers: RO1HD050735, 1009064, 496682; QIMR Berghofer Medical Research Institute and the Centre for Advanced Imaging, University of Queensland; ICTSI NIH/NCRR, Grant/Award Number: RR025761; European Community's Horizon 2020 Programme, Grant/Award Numbers: 667302, 643051; Vici Innovation Program, Grant/Award Numbers: #91619115, 016-130-669; NWO Brain & Cognition Excellence Program, Grant/Award Number: 433-09-229; Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL); Spinozapremie, Grant/Award Number: NWO-56-464-14192; Biobanking and Biomolecular Resources Research Infrastructure, Grant/Award Numbers: 184.033.111, 184.021.007; Netherlands Organization for Health Research and Development (ZonMW), Grant/Award Numbers: 480-15-001/674, 024.001.003, 911-09-032, 056-32-010, 481-08-011, 016-115-035, 31160008, 400-07-080, 400-05-717, 451-04-034, 463-06-001, 480-04-004, 904-61-193, 912-10-020, 985-10-002, 904-61-090; NIMH, Grant/Award Number: R01 MH090553; Geestkracht programme of the Dutch Health Research Council, Grant/Award Number: 10-000-1001; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Numbers: NWO/SPI 56-464-14192, NWO-MagW 480-04-004, 433-09-220, NWO 51.02.062, NWO 51.02.061; National Center for Advancing Translational Sciences, National Institutes of Health, Grant/Award Number: UL1 TR000153; National Center for Research Resources; National Center for Research Resources at the National Institutes of Health, Grant/Award Numbers: NIH 1U24 RR025736-01, NIH 1U24 RR021992; NIH Institutes contributing to the Big Data to Knowledge; U.S. National Institutes of Health, Grant/Award Numbers: R01 CA101318, P30 AG10133, R01 AG19771; Medical Research Council, Grant/Award Numbers: U54EB020403, G0500092; National Institute of Mental Health, Grant/Award Numbers: R01MH117014, R01MH042191; Fundación Instituto de Investigación Marqués de Valdecilla, Grant/Award Numbers: API07/011, NCT02534363, NCT0235832; Instituto de Salud Carlos III, Grant/Award Numbers: PI14/00918, PI14/00639, PI060507, PI050427, PI020499; Swedish Research Council, Grant/Award Numbers: 523-2014-3467, 2017-00949, 521-2014-3487; South-Eastern Norway Health Authority; the Research Council of Norway, Grant/Award Number: 223273; South Eastern Norway Regional Health Authority, Grant/Award Numbers: 2017-112, 2019107; Icahn School of Medicine at Mount Sinai; Seventh Framework Programme (FP7/2007-2013), Grant/Award Number: 602450; National Institutes of Health, Grant/Award Numbers: R01 MH116147, R01 MH113619, R01 MH104284; South London and Maudsley NHS Foundation Trust; the National Institute for Health Research (NIHR)

MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.

Neuroimaging evidence implicates structural network-level abnormalities in bipolar disorder (BD); however, there remain conflicting results in the current literature hampered by sample size limitations and clinical heterogeneity. Here, we set out to perform a multisite graph theory analysis to assess the extent of neuroanatomical dysconnectivity in a large representative study of individuals with BD. This cross-sectional multicenter international study assessed structural and diffusion-weighted magnetic resonance imaging data obtained from 109 subjects with BD type 1 and 103 psychiatrically healthy volunteers. Whole-brain metrics, permutation-based statistics, and connectivity of highly connected nodes were used to compare network-level connectivity patterns in individuals with BD compared with controls. The BD group displayed longer characteristic path length, a weakly connected left frontotemporal network, and increased rich-club dysconnectivity compared with healthy controls. Our multisite findings implicate emotion and reward networks dysconnectivity in bipolar illness and may guide larger scale global efforts in understanding how human brain architecture impacts mood regulation in BD.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset.MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain predicted age difference (brain-PAD).FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohen’s d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004).InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates.FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.

Childhood trauma (CT) has been repeatedly linked to earlier onset and greater severity of bipolar disorder (BD) in adulthood. However, such knowledge is mostly based on retrospective and cross-sectional studies in adults with BD. The first objective of this selective review is to characterize the short-term effects of CT in the development of BD by focusing on studies in young people. The second objective is to describe the longer-term consequences of CT by considering studies with adult participants. This review first outlines the most prominent hypotheses linking CT exposure and the onset of BD. Then, it summarizes the psychological and biological risk factors implicated in the development of BD, followed by a discussion of original studies that investigated the role of CT in young people with early-onset BD, youths at increased risk of developing BD, or young people with BD with a focus on subclinical and clinical outcome measures. The review considers additional biological and psychological factors associated with a negative impact of CT on the long-term course of BD in later adulthood. Finally, we discuss how the integration of information of CT can improve ongoing early identification of BD and mitigate severe clinical expression in later adulthood.

The location, extent and progression of longitudinal morphometric changes after first-episode of psychosis (FEP) remains unclear. We investigated ventricular and cortico-subcortical regions over a 3-year period in FEP patients compared with healthy controls. High resolution 1.5T T1-weighted MR images were obtained at baseline from 28 FEP patients at presentation and 28 controls, and again after 3-years. The longitudinal FreeSurfer pipeline (v.5.3.0) was used for regional volumetric and cortical reconstruction image analyses. Repeated-measures ANCOVA and vertex-wise linear regression analyses compared progressive changes between groups in subcortical structures and cortical thickness respectively. Compared with controls, patients displayed progressively reduced volume of the caudate [F (1,51)=5.86, p=0.02, Hedges’ g=0.66], putamen [F (1,51)=6.06, p=0.02, g=0.67], thalamus [F (1,51)=6.99, p=0.01, g=0.72] and increased right lateral ventricular volume [F (1, 51)=4.03, p=0.05], and significantly increased rate of cortical thinning [F (1,52)=5.11, p=0.028)] at a mean difference of 0.84% [95% CI (0.10, 1.59)] in the left lateral orbitofrontal region over the 3-year period. In patients, greater reduction in putamen volume over time was associated with lower cumulative antipsychotic medication dose (r=0.49, p=0.01), and increasing lateral ventricular volume over time was associated with worsening negative symptoms (r=0.41, p=0.04) and poorer global functioning (r= −0.41, p=0.04). This study demonstrates localised progressive structural abnormalities in the cortico-striato-thalamo-cortical circuit after the onset of psychosis, with increasing ventricular volume noted as a neuroanatomical marker of poorer clinical and functional outcome.

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.

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.

Special Issue: The ENIGMA Consortium: the first 10 years., Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia., Center for Integrated Healthcare, U.S. Department of Veterans Affairs, Grant/Award Number: I01 CX000497; Commonwealth Health Research Board, Grant/Award Number: HRA_POR/2011/100; Conselho Nacional de Desenvolvimento Científico e Tecnológico, Grant/Award Numbers: 478466/2009, 480370/2009; Department of Energy, Labor and Economic Growth, Grant/Award Number: DE-FG02-99ER62764; Forskningsrådet om Hälsa, Arbetsliv och Välfärd, Grant/Award Numbers: K2009-62X-15077-06-3, K2012-61X-15077-09-3, 523-2014-3467, 2009-7053, 2013-2838; Fundação Amazônia Paraense de Amparo à Pesquisa, Grant/Award Numbers: 2009/14891-9, 2010/18672-7, 2012/23796-2, 2013/039; Instituto de Salud Carlos III, Grant/Award Numbers: FIS 00/3095, 01/3129, PI020499, PI060507, PI10/001; National Health and Medical Research Council, Grant/Award Numbers: 1009064, 496682; National Institutes of Health, Grant/Award Numbers: 1RC1MH089257, MH 60722, MH019112, MH064045, MH085096, MH098130, MO1 RR025758, P41RR14075, P50 MH071616, R01 DA053028, R01 EB020062, R01 HD050735, R01 MH056584, R01 MH084803, R01 MH116147, R01 MH117601, R01EB005846, R01EB015611, R01MH074797, R21 MH097196, R21MH097196, R37MH43375, S10 OD023696, T32 AG058507, T32 MH073526, TR000153, U01 MH097435, U24 RR021382A, U24 RR021992, U24 RR025736, U24 RR21992, U24RR021992, U54 EB020403, U54EB020403, UL1 TR000153; National Science Foundation, Grant/Award Numbers: 1636893, 1734853; Norges Forskningsråd, Grant/Award Numbers: 213837, 217776, 223273; Science Foundation Ireland, Grant/Award Numbers: 08/IN.1/B1916, 12/IP/1359; Wellcome Trust, Grant/Award Number: 072894/2/03/Z.

Background: Increasing evidence has implicated the cholinergic system as a modulator of mood episodes, with possible involvement of nicotinic and/or muscarinic receptors. A number of randomized controlled trials (RCTs) have demonstrated a putative rapid antidepressant effect of the muscarinic antagonist scopolamine. Here, we review the clinical evidence regarding the three principal muscarinic-modulating agents administered in studies involving mood disorders: scopolamine, biperiden and physostigmine. We conduct a meta-analysis on RCTs where these agents were administered to participants experiencing a depressive episode. Methods: A systematic bibliographic search of Medline, EMBASE and the Cochrane Central Register of Controlled Trials (CENTRAL) for studies utilizing the above agents was conducted between January 1970 and December 2020. A meta-analysis was subsequently performed on 9 studies which satisfied inclusion criteria, including 322 participants. Results: Administration of scopolamine significantly reduced depressive symptoms compared to placebo, as measured by objective mood rating scales with SMD of -0.95 (95% CI -1.49, -0.42, p = 0.0005). This effect increased to -1.13 (95% CI -1.61, -0.66, p

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.

This study investigates changes on white matter microstructure and neural networks after 6 months of switching to clozapine in schizophrenia patients compared to controls, and whether any changes are related to clinical variables. T1 and diffusion-weighted MRI images were acquired at baseline before commencing clozapine and after 6 months of treatment for 22 patients with treatment-resistant schizophrenia and 23 controls. The Tract-based spatial statistics approach was used to compare changes over time between groups in fractional anisotropy (FA). Changes in structural network organisation weighted by FA and number of streamlines were assessed using graph theory. Patients displayed a significant reduction of FA over time (p

Synchronous and anti-synchronous activity between neural elements at rest reflects the physiological processes underlying complex cognitive ability. Regional and pairwise-connectivity investigations suggest perturbations in these activity patterns may relate to widespread cognitive impairments seen in bipolar disorder (BD). Here we take a network-based perspective to more meaningfully capture interactions among distributed brain regions compared to focal measurements and examine network-cognition relationships across a range of commonly affected cognitive domains in BD in relation to healthy controls. Resting-state networks were constructed as matrices of correlation coefficients between regionally averaged resting-state time series from 86 cortical/subcortical brain regions (FreeSurferv5.3.0). Cognitive performance measured using Weschler Adult Intelligence Scale, Cambridge Automated Neuropsychological Test Battery (CANTAB) and Reading the Mind in the Eyes tests was examined in relation to whole-brain connectivity measures and patterns of connectivity using a permutation-based statistical approach. Faster response times in controls (n=49) related to synchronous activity between frontal, parietal, cingulate, temporal and occipital regions while similar response times in BD (n=35) related to anti-synchronous activity between regions of this subnetwork. Across all subjects, anti-synchronous activity between frontal, parietal, temporal, occipital, cingulate, insula and amygdala regions related to improved memory performance. No resting-state subnetworks related to intelligence, executive function, short-term memory or social cognition performance in the overall sample or in a manner that would explain deficits in these facets in BD. Our results demonstrate alterations in the intrinsic connectivity patterns underlying response timing in BD that are not specific to performance or errors on the same tasks. Across all individuals, no strong effects of resting-state global topology on cognition are found, while distinct functional networks supporting episodic and spatial memory highlight intrinsic inhibitory influences present in the resting-state that facilitate memory processing.

OBJECTIVESchizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants.METHODSThe meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition.RESULTSMeta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44).CONCLUSIONSThis study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

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.

The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. This study investigated subcortical morphometric changes 6 months after switching treatment to clozapine in patients with treatment-resistant schizophrenia compared with healthy volunteers, and the relationships between longitudinal volume changes and clinical variables. In total, 1.5T MRI images were acquired at baseline before commencing clozapine and again after 6 months of treatment for 33 patients with treatment-resistant schizophrenia and 31 controls, and processed using the longitudinal pipeline of Freesurfer v.5.3.0. Two-way repeated MANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Whereas no significant subcortical volume differences were found between patients and controls at baseline (F(8,52) = 1.79; p = 0.101), there was a significant interaction between time, group and structure (F(7,143) = 52.54; p

Manual tracing of magnetic resonance imaging (MRI) represents the gold standard for segmentation in clinical neuropsychiatric research studies, however automated approaches are increasingly used due to its time limitations. The accuracy of segmentation techniques for subcortical structures has not been systematically investigated in large samples. We compared the accuracy of fully automated [(i) model-based: FSL-FIRST; (ii) patch-based: volBrain], semi-automated (FreeSurfer) and stereological (Measure®) segmentation techniques with manual tracing (ITK-SNAP) for delineating volumes of the caudate (easy-to-segment) and the hippocampus (difficult-to-segment). High resolution 1.5 T T1-weighted MR images were obtained from 177 patients with major psychiatric disorders and 104 healthy participants. The relative consistency (partial correlation), absolute agreement (intraclass correlation coefficient, ICC) and potential technique bias (Bland-Altman plots) of each technique was compared with manual segmentation. Each technique yielded high correlations (0.77-0.87, p

Correction to: Neuropsychopharmacology https://doi.org/10.1038/s41386-020-0665-4\ud Linked to BURO article https://eprints.bournemouth.ac.uk/34082/

BackgroundVerbal learning (VL) and fluency (VF) are prominent cognitive deficits in psychosis, of which the precise neuroanatomical contributions are not fully understood. We investigated the arcuate fasciculus (AF) and its associated cortical regions to identify structural abnormalities contributing to these verbal impairments in early stages of psychotic illness.MethodsTwenty-six individuals with recent-onset psychosis and 27 healthy controls underwent cognitive testing (MATRICS Consensus Cognitive Battery) and structural/diffusion-weighted MRI. Bilaterally, AF anisotropy and cortical thickness, surface area and volume of seven cortical regions were investigated in relation to VL and VF performance in both groups.ResultsReduced right superior temporal gyrus surface area and volume related to better VF in controls. In psychosis, greater right pars opercularis volume and reduced left lateralization of this region related to better VL, while greater right long AF fractional anisotropy and right pars orbitalis volume related to better VF, these findings not present in controls. Psychosis had reduced right pars orbitalis thickness compared to controls.ConclusionAnatomical substrates for normal processing of VL and VF appear altered in recent-onset psychosis. A possible aberrant role of the right hemisphere arcuate fasciculus and fronto-temporal cortical regions in psychosis may contribute to deficits in VL and VF.

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.

Background The dysconnectivity hypothesis suggests that psychotic illnesses arise not from regionally specific focal pathophysiology, but rather from impaired neuroanatomical integration across networks of brain regions. Decreased white matter organization has been hypothesized to be a feature of psychotic illnesses in general, which is supported by meta-analyses of DTI studies in bipolar disorder and schizophrenia. Although many diffusion MRI studies investigate bipolar disorder and schizophrenia alone, relatively few studies directly compare structural features in these psychotic illnesses. Recently, the application of graph theory analyses to DTI data has supported the dysconnectivity hypothesis in bipolar disorder and schizophrenia, employing topological properties to assess neuroanatomical dysconnectivity. Methods This selective review evaluates white matter alterations using Diffusion Tensor Imaging (DTI) in bipolar disorder and schizophrenia, with a focus upon direct comparison DTI studies in both psychotic illnesses. We then expand in more detail on the development of network analyses and the application of these techniques in bipolar disorder and schizophrenia. Results Converging evidence indicates that frontal connectivity alterations are common to both disorders, with prominent fronto-temporal deficits identified in schizophrenia and inter-hemispheric and limbic alterations reported in bipolar disorder. Limitations In bipolar disorder, most connectome reports use cortical maps alone, which given the importance of the limbic system in emotional regulation may limit the scope of network approaches in mood disorders. Conclusions Further direct connectivity comparisons between these psychotic illnesses may assist in unravelling the neuroanatomical deviations underpinning the overlapping features of psychosis and cognitive impairment, and the more diagnostically distinctive features of affective disturbance in bipolar disorder and deficit syndrome in schizophrenia.

Background The extent and location of longitudinal morphometric changes after first-episode of psychosis (FEP) remains unclear. We investigated the progressive profile of ventricular and cortico-subcortical regions over a 3-year period in FEP patients compared with healthy controls (HC), and whether any progressive neuroanatomical changes were related to clinical factors. Methods High resolution 1.5T T1-weighted MR images were obtained from 28 FEP patients and 28 HCs shortly after presentation to services and again after 3-year follow-up. The longitudinal FreeSurfer pipeline (v.5.3.0) was used for regional volumetric and cortical reconstruction image analyses. Repeated-measures ANCOVA and vertex-wise linear regression analyses were used to compare progressive changes in relation to subcortical structures/ventricles and thickness across the cortical mantle, respectively, between groups. Partial correlations were used to determine associations of progressive neuroanatomical change with clinical and functional characteristics. Results Compared with controls, patients displayed progressively reduced volume of the caudate [F(1,51)=5.86, p=0.02, Hedges’ g=0.66], putamen [F(1,51)=6.06, p=0.02, g=0.67] and thalamus [F(1,51)=6.99, p=0.01, g=0.72], with a trend for increased lateral ventricular volume [F(1,51)=3.37, p=0.07, g=0.50] more prominent on the right [F(1, 51)=4.03, p=0.05], and significantly increased rate of cortical thinning [F(1,52)=5.11, p=0.028)] at a mean difference of 0.844% [95% CI (0.095, 1.593)] in the left lateral orbitofrontal region (LLOFR) over the 3-year period. In FEP individuals, greater reduction in putamen volume over time was associated with low cumulative antipsychotic medication dose (r=0.49, p=0.01), and increasing lateral ventricular volume over time was associated with worsening negative symptoms (r=0.41, p=0.04) and poorer global assessment of functioning (r=-0.41, p=0.04). Discussion Our results demonstrate existence of localised progressive structural disturbance in the subnetwork of the cortico-striato-thalamo-cortical circuitry after the onset of psychosis. Furthermore, increasing ventricular volume is a neuroanatomical marker of poorer clinical and functional outcome. These findings lend weight to the evidence of early progressive brain changes in psychotic disorders and thus, this knowledge could potentially contribute to the identification of imaging biomarkers for timely intervention.

Background The association of antipsychotic medication with abnormal brain morphometry in schizophrenia remains uncertain. Early studies investigating a switch from first generation antipsychotic to clozapine have steadily shown a decrease of caudate volume over time; however nowadays most patients are already on second generation antipsychotic medications prior to clozapine commencement and it remains unclear whether switching to clozapine in such circumstances would have any such effect on the basal ganglia. In this study we aimed to comprehensively investigate whether after 6 months of switching to clozapine, subcortical structures demonstrate any progressively neuroanatomical changes in patients with treatment-resistant schizophrenia compared to healthy controls, and whether any such changes are related to clinical variables including treatment response and amount of clozapine taken. Methods MRI images were acquired for all participants at baseline and after 6 months at University Hospital Galway in a 1.5 T scanner. The longitudinal pipeline of Freesurfer v.5.3.0, based on an unbiased within-subject anatomical template, was employed to segment eight subcortical regions-of-interest: lateral ventricle, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala and nucleus accumbens. Subcortical volumes were bilaterally extracted following quality check of raw data and segmentation. Clinical assessments included the Positive and Negative Syndrome Scale (PANSS), The Scale for the Assessment of Positive Symptoms (SAPS), The Scale for the Assessment of Negative Symptoms (SANS) and Global Assessment Functioning Score (GAF). Two-way repeated ANCOVA was used to assess group differences in subcortical volumes over time and partial correlations to determine association with clinical variables. Change in volume was expressed using the following formula: (Follow Up -Baseline)/Baseline x 100. Results 33 patients with treatment-resistant schizophrenia (TRS) and 31 healthy volunteers (HC) matched for sex and age were successfully recruited at both baseline prior to clozapine treatment and after 6 months. There was a significant effect of time on subcortical brain volumes between TRS and controls (F(7,143)= 52.54, p Discussion This study demonstrates that, despite the clinical and functional improvement of most patients with schizophrenia who are switched to clozapine, there is a counterintuitive progressive volume reduction in several subcortical structures over time. Furthermore, patients who have the greatest symptomatic improvement display the largest thalamo-putaminal reductions, indicating that volume reduction reflects an adaptive response associated with symptom improvement rather than a harmful or neurotoxic process in these patients.

Well-established structural abnormalities, mostly involving the limbic system, have been associated with disorders of emotion regulation. Understanding the arrangement and connections of these regions with other functionally specialized cortico-subcortical subnetworks is key to understanding how the human brain's architecture underpins abnormalities of mood and emotion. We investigated topological patterns in bipolar disorder (BD) with the anatomically improved precision conferred by combining subject-specific parcellation/segmentation with nontensor-based tractograms derived using a high-angular resolution diffusion-weighted approach. Connectivity matrices were constructed using 34 cortical and 9 subcortical bilateral nodes (Desikan-Killiany), and edges that were weighted by fractional anisotropy and streamline count derived from deterministic tractography using constrained spherical deconvolution. Whole-brain and rich-club connectivity alongside a permutation-based statistical approach was used to investigate topological variance in predominantly euthymic BD relative to healthy volunteers. BP patients (n=40) demonstrated impairments across whole-brain topological arrangements (density, degree, and efficiency), and a dysconnected subnetwork involving limbic and basal ganglia relative to controls (n=45). Increased rich-club connectivity was most evident in females with BD, with frontolimbic and parieto-occipital nodes not members of BD rich-club. Increased centrality in females relative to males was driven by basal ganglia and fronto-temporo-limbic nodes. Our subject-specific cortico-subcortical nontensor-based connectome map presents a neuroanatomical model of BD dysconnectivity that differentially involves communication within and between emotion-regulatory and reward-related subsystems. Moreover, the female brain positions more dependence on nodes belonging to these two differently specialized subsystems for communication relative to males, which may confer increased susceptibility to processes dependent on integration of emotion and reward-related information. This research is supported by the Irish Research Council (IRC) Postgraduate Scholarship, Ireland awarded to Leila Nabulsi, and by the Health Research Board (HRA-POR-324) awarded to Dr Dara M. Cannon. We gratefully acknowledge the participants and the support of the Wellcome-Trust HRB Clinical Research Facility and the Centre for Advanced Medical Imaging, St. James Hospital; Andrew Hoopes, Research Technician I, MGH/HST Martinos Center for Biomedical Imaging, for Freesurfer software support, Christopher Grogan, MSc, for his contribution to data processing, Jenna Pittman, BSc, and Fiona Martyn, BSc, for their contribution to data handling. peer-reviewed 2020-12-16

BACKGROUND: Functional abnormalities, mostly involving functionally specialized subsystems, have been associated with disorders of emotion regulation such as bipolar disorder (BD). Understanding how independent functional subsystems integrate globally and how they relate with anatomical cortical and subcortical networks is key to understanding how the human brain's architecture constrains functional interactions and underpins abnormalities of mood and emotion, particularly in BD.METHODS: Resting-state functional magnetic resonance time series were averaged to obtain individual functional connectivity matrices (using AFNI software); individual structural connectivity matrices were derived using deterministic non-tensor-based tractography (using ExploreDTI, version 4.8.6), weighted by streamline count and fractional anisotropy. Structural and functional nodes were defined using a subject-specific cortico-subcortical mapping (using Desikan-Killiany Atlas, FreeSurfer, version 5.3). Whole-brain connectivity alongside a permutation-based statistical approach and structure-function coupling were employed to investigate topological variance in individuals with predominantly euthymic BD relative to psychiatrically healthy control subjects.RESULTS: Patients with BD (n = 41) exhibited decreased (synchronous) connectivity in a subnetwork encompassing frontolimbic and posterior-occipital functional connections (T > 3, p = .048), alongside increased (antisynchronous) connectivity within a frontotemporal subnetwork (T > 3, p = .014); all relative to control subjects (n = 56). Preserved whole-brain functional connectivity and comparable structure-function coupling among whole-brain and edge-class connections were observed in patients with BD relative to control subjects.CONCLUSIONS: This study presents a functional map of BD dysconnectivity that differentially involves communication within nodes belonging to functionally specialized subsystems-default mode, frontoparietal, and frontolimbic systems; these changes do not extend to be detected globally and may be necessary to maintain a remitted clinical state of BD. Preserved structure-function coupling in BD despite evidence of regional anatomical and functional deficits suggests a dynamic interplay between structural and functional subnetworks. This research is supported by the Irish Research Council (IRC) Postgraduate Scholarship, Ireland awarded to Dr Leila Nabulsi, PhD and by the Health Research Board (HRA-POR324) awarded to Dr Dara M. Cannon, PhD. We gratefully acknowledge the participants and the support of the Wellcome-Trust HRB Clinical Research Facility and the Centre for Advanced Medical Imaging, St. James Hospital, Dublin, Ireland. peer-reviewed 2020-11-11

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: Graph theory applied to brain networks is an emerging approach to understanding the brain's topological associations with human cognitive ability. Despite well-documented cognitive impairments in bipolar disorder (BD) and recent reports of altered anatomical network organization, the association between connectivity and cognitive impairments in BD remains unclear.METHODS: We examined the role of anatomical network connectivity derived from Ti - and diffusion-weighted magnetic resonance imaging in impaired cognitive performance in individuals with BD (n = 32) compared with healthy control individuals (n = 38). Fractional anisotropy- and number of streamlines-weighted anatomical brain networks were generated by mapping constrained spherical deconvolution-reconstructed white matter among 86 cortical/subcortical bilateral brain regions delineated in the individual's own coordinate space. Intelligence and executive function were investigated as distributed functions using measures of global, rich-club, and interhemispheric connectivity, while memory and social cognition were examined in relation to subnetwork connectivity.RESULTS: Lower executive functioning related to higher global clustering coefficient in participants with BD, and lower IQ performance may present with a differential relationship between global and interhemispheric efficiency in individuals with BD relative to control individuals. Spatial recognition memory accuracy and response times were similar between diagnostic groups and associated with basal ganglia and thalamus interconnectivity and connectivity within extended anatomical subnetworks in all participants. No anatomical subnetworks related to episodic memory, short-term memory, or social cognition generally or differently in BD.CONCLUSIONS: Results demonstrate selective influence of subnetwork patterns of connectivity in underlying cognitive performance generally and abnormal global topology underlying discrete cognitive impairments in BD. We gratefully acknowledge the participants, the support of the Welcome-Trust HRB Clinical Research Facility, the Centre for Advanced Medical Imaging at St. James Hospital Dublin and funding support from the Irish Research Council Government of Ireland Postgraduate Scholarship. We would also like to thank Andrew Hoopes, Research Technician I, MGH/HST Martinos Center for Biomedical Imaging for Freesurfer software support, Christopher Grogan, MSc, for his contribution to data processing and Jenna Pittman, BSc and Fiona Martyn, BA for their contribution to data handling. This research was funded by the Health Research Board (HRA-POR324) awarded to Dara M. Cannon, PhD. peer-reviewed 2020-09-18

The association of neuroanatomical progression with cognitive and clinical deterioration after first-episode of psychosis remains uncertain. This longitudinal study aims to assess whether i)impaired executive functioning and emotional intelligence at first presentation are associated with progressive prefrontal and orbitofrontal cortical thinning ii)negative symptom severity is linked to progressive prefrontal cortical thinning. 1.5T MRI images were acquired at baseline and after 3.5 years for 20 individuals with first-episode psychosis and 18 controls. The longitudinal pipeline of Freesurfer was employed to parcellate prefrontal cortex at two time points. Baseline cognitive performance was compared between diagnostic groups using MANCOVA. Partial correlations investigated relationships between cognition and negative symptoms at baseline and cortical thickness change over time. Patients displayed poorer performance than controls at baseline in working memory, reasoning/problem solving and emotional intelligence. In patients, loss of prefrontal and orbitofrontal thickness over time was predicted by impaired working memory and emotional intelligence respectively at baseline. Moreover, exploratory analyses revealed that the worsening of negative symptoms over time was significantly related to prefrontal cortical thinning. Results indicate that specific cognitive deficits at the onset of psychotic illness are markers of progressive neuroanatomical deficits and that worsening of negative symptoms occurs with prefrontal thickness reduction as the illness progresses.

The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Background: The brain-derived neurotrophic factor (BDNF) val66met polymorphism is associated with altered activity dependent secretion of BDNF and a variable influence on brain morphology and cognition. Although a met-dose effect is generally assumed, to date the paucity of met-homozygotes have limited our understanding of the role of the met-allele on brain structure. Methods: To investigate this phenomenon, we recruited sixty normal healthy subjects, twenty in each genotypic group (val/val, val/met and met/met). Global and local morphology were assessed using voxel based morphometry and surface reconstruction methods. White matter organisation was also investigated using tract-based spatial statistics and constrained spherical deconvolution tractography. Results: Morphological analysis revealed an "inverted-U" shaped profile of cortical changes, with val/met heterozygotes most different relative to the two homozygous groups. These results were evident at a global and local level as well as in tractography analysis of white matter fibre bundles. Conclusion: In contrast to our expectations, we found no evidence of a linear met-dose effect on brain structure, rather our results support the view that the heterozygotic BDNF val66met genotype is associated with cortical morphology that is more distinct from the BDNF val66met homozygotes. These results may prove significant in furthering our understanding of the role of the BDNF met-allele in disorders such as Alzheimer's disease and depression. (C) 2014 The Authors. Published by Elsevier Inc All rights reserved.

BackgroundOur understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.MethodsThis study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).ResultsMeta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (βstd = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.ConclusionsUsing an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Background: Neuroticism is a major risk factor for affective disorders. This personality trait has been hypothesized to associate with synaptic availability of the serotonin transporter, which critically controls serotonergic tone in the brain. However, earlier studies linking neuroticism and serotonin transporter have failed to produce converging findings. Because sex affects both the serotonergic system and the risk that neuroticism poses to the individual, sex may modify the association between neuroticism and serotonin transporter, but this question has not been investigated by previous studies.Methods: Here, we combined data from 4 different positron emission tomography imaging centers to address whether neuroticism is related to serotonin transporter binding in vivo. The data set included serotonin transporter binding potential values from the thalamus and striatum and personality scores from 91 healthy males and 56 healthy females. We specifically tested if the association between neuroticism and serotonin transporter is different in females and males.Results: We found that neuroticism and thalamic serotonin transporter binding potentials were associated in both males and females, but with opposite directionality. Higher neuroticism associated with higher serotonin transporter binding potential in males (standardized beta 0.292, P=.008), whereas in females, higher neuroticism associated with lower serotonin transporter binding potential (standardized beta -0.288, P=.014).Conclusions: The finding is in agreement with recent studies showing that the serotonergic system is involved in affective disorders differently in males and females and suggests that contribution of thalamic serotonin transporter to the risk of affective disorders depends on sex.

Current hypotheses stipulate core symptoms of schizophrenia (SZ) result from the brain's incapacity to integrate neural processes. Converging diffusion magnetic resonance imaging and graph theory studies provide evidence of macrostructural alterations in SZ. However, age-related topological changes within and between white matter (WM) networks and its relationship to gene expression with disease progression remain incompletely understood. This cross-sectional study uses network modeling to investigate changes in WM network organization with disease progression in chronic SZ as well its relationship with gene expression in healthy brains. First, we replicate prior findings demonstrating altered global WM network topology in SZ. Novel results show significantly altered age-related network degradation patterns in patients compared with controls. Specifically, controls show stereotyped, linear global network decline with age. In contrast, patients show nonlinear network decline with age. Further analysis reveals lack of significant topological decline in younger adult patients, which is subsequently followed by stereotyped linear decline in older adult patients. Node-specific analyses show significant topological differences in frontal and limbic regions of younger adult patients compared with age-matched controls, which become less pronounced with age in older adult patients compared with age-matched controls. Lastly, we show several gene expression profiles, including DISC1, are associated with age-related changes in WM disconnectivity. Together, these findings provide novel WM topological and genetic evidence supporting neurodevelopmental models of SZ, suggesting that network remodeling continues throughout the third decade of life before stabilizing.

Journal article First episode psychosis (FEP) has been associated with structural brain changes, largely identified by volumetric analyses. Advances in neuroimaging processing have made it possible to measure geometric properties that may identify subtle structural changes not appreciated by a measure of volume alone. In this study we adopt complementary methods of assessing the structural integrity of grey matter in FEP patients and assess whether these relate to patient clinical and functional outcome at 3year follow-up. 1.5Tesla T1-weighted Magnetic Resonance (MR) images were acquired for 46 patients experiencing their first episode of psychosis and 46 healthy controls. Cerebral cortical thickness and local gyrification index (LGI) were investigated using FreeSurfer software. Volume and shape of the hippocampus, caudate and lateral ventricles were assessed using manual tracing and spherical harmonics applied for shape description. A cluster of cortical thinning was identified in FEP compared to controls; this was located in the right superior temporal gyrus, sulcus, extended into the middle temporal gyrus (lateral temporal cortex - LTC). Bilateral caudate volumes were significantly lower in FEP relative to controls and the right caudate also displayed regions of shape deflation in the FEP group. No significant structural abnormalities were identified in cortical LGI or hippocampal or lateral ventricle volume/shape. Neither LTC nor caudate abnormalities were related to change in symptom severity or global functioning 3years later. LTC and caudate abnormalities are present at the first episode of psychosis but do not appear to directly affect clinical or functional outcome. peer-reviewed

The micro RNA 137 (miR-137) variant rs1625579 has been identified as a genome-wide significant risk variant for schizophrenia. miR-137 has an established role in neurodevelopment and may mediate cognitive dysfunction in schizophrenia. This role of miR-137 may be related to changes in brain morphology for risk-related genotypes; however this has not yet been delineated. Here we considered whether rs1625579 genotype was predictive of indices of brain structure in patients with schizophrenia and healthy controls. Structural magnetic resonance imaging (sMRI) data (i.e. 3T T1-TFE or 1.5T T1-MPRAGE) were acquired from 150 healthy controls and 163 schizophrenic patients. Two volumetric analyses that considered the impact of miR-137/rs1625579 genotype were carried out on sMRI data. In the first analysis, voxel based morphometry was employed to consider genotype-related variability in local grey and white matter across the entire brain volume. Our secondary analysis utilized the FIRST protocol in FSL to consider the volume of subcortical structures (i.e. bilateral accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus). Several brain regions in both analyses demonstrated the expected main effect of participant group (i.e. schizophrenics

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness., published version, peerReviewed

Contains fulltext : 193179.pdf (Publisher’s version ) (Open Access) The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10(-7)) and thalamus (d=-0.148; P=4.27 × 10(-3)) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10(-5)) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.Molecular Psychiatry advance online publication, 9 February 2016; doi:10.1038/mp.2015.227. ispartof: Molecular Psychiatry vol:21 issue:12 pages:1710-1716 ispartof: location:England status: published