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Background: Widely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. Methods: The ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6–65) was divided into six successive 6–10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. Results: Compared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6–13 and adults aged 50–65 with OCD taking SRIs (Cohen's d = −0.24 to −0.74). Volumes of putamen, pallidum (d = 0.18–0.40), and ventricles (d = 0.31–0.66) were greater in patients aged 20–29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = −0.27 to −1.31). Conclusions: Results suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20–29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.

Distortions in time processing may be regarded as an endophenotypic marker of neuropsychiatric diseases; however, investigations addressing Bipolar Disorder (BD) are still scarce.The present study compared timing abilities in 30 BD patients and 30 healthy controls (HC), and explored the relationship between time processing and affective-cognitive symptoms in BD, with the aim to determine whether timing difficulties are primary in bipolar patients or due to comorbid cognitive impairment. Four tasks measuring external timing were administered: a temporal and spatial orienting of attention task and a temporal and colour discrimination task, for assessing the ability to evaluate temporal properties of external events; two other tasks assessed the speed of the internal clock (i.e. temporal bisection and temporal production tasks). Attentional, executive and working memory (WM) demands were equated for controlling additional cognitive processes.BD patients did not show differences in external timing accuracy compared to HC; conversely, we found increased variability of the internal clock in BD and this performance was related to Major Depressive Episodes recurrence and WM functioning. Hence, variability of the internal clock is influenced by the progressive course of BD and impacted by variations in WM.Future studies including BD patients stratified by mood episode will further specify timing alterations conditional to the current affective state.Our results shed new light on the clinical phenotypes of BD, suggesting that timing might be used as a model system of the ongoing pathophysiological process.

Contains fulltext : 291574.pdf (Publisher’s version ) (Open Access) Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset d = 0.37), posterior corona radiata (d = 0.32), and superior fronto‐occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status. Using the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male individuals with early-onset schizophrenia and individuals with a shorter duration of illness.

Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.TeaserWe present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.

Objective: A major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behavior. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia. Method: Here, we examine this issue through two approaches: (a) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments and (b) by pooling data (N ∼ 6,000 participants) from cohorts from the Enhancing NeuroImaging Genetics Through Meta-Analysis (ENIGMA) Major Depressive Disorder and ENIGMA–Suicidal Thoughts and Behaviour working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behavior. Results: We observed moderate-to-high correlations between measures, consistent with the wide range (κ range: 0.15–0.97; r range: 0.21–0.94) reported in the literature. Two common multi-item instruments, the Columbia Suicide Severity Rating Scale and the Beck Scale for Suicidal Ideation were highly correlated with each other (r = 0.83). Sensitivity analyses identified sources of heterogeneity such as the time frame of the instrument and whether it relies on self-report or a clinical interview. Finally, construct-specific analyses suggest that suicide ideation items from common psychiatric questionnaires are most concordant with the suicide ideation construct of multi-item instruments. Conclusions: Our findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behavior but share a modest core factor with single suicidal ideation items. Retrospective, multisite collaborations including distinct instruments should be feasible provided they harmonize across instruments or focus on specific constructs of suicidality.

[Background]: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life., [Methods]: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed., [Results]: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth., [Conclusions]: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy., This work was supported by the German Research Foundation (DFG Grant Nos. HA7070/2-2, HA7070/3, HA7070/4 [to TH]) and IZKF of the medical faculty of Münster (Grants No. Dan3/012/17 [to UD] and MzH 3/020/20 [to TH]), and NHMRC projects (Grant No. 1064643 [to BJH] and 1024570 [to CGD]). The CIAM study was supported by the University of Cape Town Research Committee, South African National Research Foundation, and the South African Medical Research Council (principal investigator [PI], Fleur M. Howells) and Grant No. R01MH117601 (to NJ). This work was funded by the German Research Foundation (Grant Nos. FOR2107 JA 1890/7-1 and FOR2107 JA 1890/7-2 [to AJ]) and Swinburne University scholarship/Australian Postgraduate Award (to JK). Collection of the COGSBD cohort was funded by the Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L Cooper Foundation, and the Society of Mental Health Research (to JK). This work was funded by the German Research Foundation (Grant Nos. FOR2107 KI588/14-1 and FOR2107 KI588/14-2 [to TK]). The St. Göran study was supported by grants from the Swedish Research Council (Grant No. 2018-02653 [to ML]), the Swedish foundation for Strategic Research (Grant No. KF10-0039 [to ML]), the Swedish Brain foundation (Grant No. FO2020-0261 [to ML]), and the Swedish Government under the LUA/ALF agreement (Grant Nos. ALF 20170019 and ALFGBG-716801 [to ML]). This work was supported by RFBR (Grant No. 20-013-00748 [to IL, AST]) and funded by the Health Research Board (Grant No. HRA_POR/2011/100 [to CM]). The Australian Schizophrenia Research Bank (ASRB) was supported by the NHMRC (Enabling Grant No. 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation, and the Schizophrenia Research Institute. Chief investigators for ASRB were VC, US, RSc, AJ, BM, PTM, SVC, FH, and CPa. This work was supported by Deutsche Forschungsgemeinschaft (Grant Nos. DFG NE 2254/2-1, NE 2254/3-1, NE2254/4-1 [to IN]), the University Research Priority Program “Integrative Human Physiology” at the University of Zurich (to ROT), an NHMRC Senior Principal Research Fellowship (Grant No. 1105825 [to CPa]), an NHMRC L3 Investigator Grant (Grant No. 1196508 [to CPa]), and NHMRC Program Grant (Grant No. 1150083 [to CPa]). ASRB was supported by the NHMRC (Enabling Grant No. 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation and the Schizophrenia Research Institute. Chief investigators for ASRB were VC, US, RSc, AJ, BM, PTM, SVC, FH, and CPa. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant (Agreement No. 798181 [to GP]). ASRB was supported by the 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 VC, US, RSc, AJ, BM, PTM, SVC, FH, and CPa. The Imaging Genetics in Psychosis study was funded by Project Grants from the NHMRC (Grant Nos. APP630471 and APP1081603 [to YQ]) and the Macquarie University’s Australian Research Council (ARC) Centre of Excellence in Cognition and its Disorders (Grant No. CE110001021 [to YQ]). This work was supported by the Spanish Ministry of Science, Innovation and Universities/Economy and Competitiveness/Instituto de Salud Carlos III (Grant Nos. PI11/01766 and CPII19/00009 [to JR]), co-financed by European Regional Development Fund funds from the European Commission (“A Way of Making Europe”). ASRB was supported by the NHMRC (Enabling Grant No. 386500), the Pratt Foundation, Ramsay Health Care, the Viertel Charitable Foundation, and the Schizophrenia Research Institute. Chief investigators for ASRB were VC, US, RSc, AJ, BM, PTM, SVC, FH, and CPa. SR was supported by an NHMRC Senior Fellowship (Grant No. GNT1154651). Collection of the COGSBD cohort was funded by the Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L Cooper Foundation, and the Society of Mental Health Research (to SR). This work was supported by NIHR; MRC (to KR), NIH (Grant Nos. MH-094268, MH-105660, and MH-107730 [to ASS]). The Neuroimaging of the Children's Attention Project cohort was funded by NHMRC, Australia (Grant No. 1065895). Earlier funding for the cohort as also provided by NHMRC (Grant No. 1008522) and a grant from the Collier Foundation. The ACPU cohort was funded by NHMRC, Australia (Project Grant Nos. 384419 and 569533 [to TS]). This work was supported by research grants from the National Healthcare Group, Singapore (Grant Nos. SIG/05004, SIG/05028, and SIG /1103), and the Singapore Bioimaging Consortium (RP C009/2006 [to KS]), and the Ministry of Health, Czech Republic - conceptual development of research organization (“Institute for Clinical and Experimental Medicine - IKEM, IN 00023001” [to ASk]). This study was supported by the Italian Ministry of Health (Grant No. RC/17-18-19-20-21/A [to GS]) and Ministry of Health of the Czech Republic (Grant No. NU20-04-00393 [to FS]). The Drakenstein Child Health Study (DCHS) cohort is funded by the Bill and Melinda Gates Foundation (Grant No. OPP 1017641) and the South African Medical Research Council. This DCHS contribution was made possible in part by a grant from Carnegie Corporation of New York. The statements made and views expressed are solely the responsibility of the author (DJS). STRADL study was supported and funded by the Wellcome Trust Strategic Award “Stratifying Resilience and Depression Longitudinally” (Grant No. 104036/Z/14/Z), and the Medical Research Council Mental Health Pathfinder Award “Leveraging routinely collected and linked research data to study the causes and consequences of common mental disorders” (MRC, Grant No. MC_PC_17209). Scottish Bipolar Family Study (SBFS) was supported by National Health Service Research Scotland, through the Scottish Mental Health Research Network (www.smhrn.org.uk), who provided assistance with subject recruitment and assessments. SBFS was conducted at the Brain Research Imaging Centre (http://www.bric.ed.ac.uk), which is supported by SINAPSE (Scottish Imaging Network, a Platform for Scientific Excellence, http://www.sinapse.ac.uk). Processing of the datasets used the resources provided by the Edinburgh Compute and Data Facility (http://www.ecdf.ed.ac.uk/) (ASt). TVR was supported by an NHMRC Early Career Fellowship (Grant No. GNT1088785). Collection of the COGSBD cohort was funded by the Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L Cooper Foundation, and the Society of Mental Health Research (to TVR). EV was supported by the Spanish Ministry of Science and Innovation (PI18/00805) integrated into the Plan Nacional de I+D+I and co-financed by the ISCIII-Subdirección General de Evaluación and the FEDER; the Instituto de Salud Carlos III; the CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental); by the CERCA Programme/Generalitat de Catalunya and the Secretaria d’Universitats i Recerca del Departament d’Economia I Coneixement (Grant No. 2017SGR1355). This study was also supported by the Departament de Salut de la Generalitat de Catalunya, Pla Estratègic de Recerca i Innovació en Salut (PERIS) 2016-2020 (Grant No. SLT006/17/00345) and the European Union Horizon 2020 research and innovation program (EU.3.1.1. Understanding health, wellbeing and disease: Grant Nos. 754907 and EU.3.1.3 [to EB]; Treating and managing disease: Grant No. 945151 [to EV]). This study was supported by the National Center for Complementary and Integrative Health (Grant Nos. R21AT009173 and R61AT009864 [to TTY]); by the National Center for Advancing Translational Sciences (CTSI), National Institutes of Health, through UCSF-CTSI (Grant No. UL1TR001872 [to TTY]); by the American Foundation for Suicide Prevention (Grant No. SRG-1-141-18 [to TTY]); by UCSF Research Evaluation and Allocation Committee (REAC) and J. Jacobson Fund (to TTY); by the NIMH (Grant No. R01MH085734 [to TTY]); and by the Brain and Behavior Research Foundation (formerly NARSAD) (to TTY). This work was supported by a personal Veni grant to MH from the Netherlands Organization for Scientific Research (NWO, Grant No. 91619115 [to MH]) and European Community’s Horizon 2020 Programme (H2020/2014 – 2020) (Grant Agreements Nos. 667302 [CoCA], 728018 [Eat2beNICE], and 847879 [PRIME] [to BF]). JBu has been supported by the EU-AIMS (European Autism Interventions) and AIMS-2-TRIALS programmes, which receive support from Innovative Medicines Initiative Joint Undertaking Grant Nos. 115300 and 777394, the resources of which are composed of financial contributions from the European Union’s FP7 and Horizon 2020 Programmes, and from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions, and AUTISM SPEAKS, Autistica and SFARI; and by the Horizon 2020–supported programme CANDY (Grant No. 847818 [to JBu]). This work is supported by Grant No. NIA T32AG058507 and NIH Grant No. U54EB020403 from the Big Data to Knowledge (BD2K) Program (to CRKC). ENIGMA MDD work is supported by NIH (Grant Nos. U54 EB020403 [to PT], R01 MH116147 [to PT], and R01 MH117601 [to NJ and LS]). LS was supported by an NHMRC Career Development Fellowship (Grant No. 1140764). This work was supported by the National Center for Research Resources at the NIH (Grant Nos. NIH 1 U24 RR021992 [Function Biomedical Informatics Research Network], NIH 1 U24 RR025736-01 [Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org]). TGMvE is supported by ENIGMA’s NIH BD2K initiative (Grant No. U54 EB020403), ENIGMA Sex Differences (Grant No. R01MH116147), and ENIGMA-COINSTAC: Advanced Worldwide Transdiagnostic Analysis of Valence System Brain Circuits (Grant No. R01MH121246). This work was supported by the NIH (Grant No. R01MH121246 [to JT, Calhoun, and TGMvE]). This work was supported in part by NIH (Grant No. U54 EB020403 [to PT]).

Patients with deficit schizophrenia (SZD) suffer from primary and enduring negative symptoms. Limited pieces of evidence and neuroimaging studies indicate they differ from patients with non-deficit schizophrenia (SZND) in neurobiological aspects, but the results are far from conclusive. We applied for the first time, graph theory analyses to discriminate local and global indices of brain network topology in SZD and SZND patients compared with healthy controls (HC). High-resolution T1-weighted images were acquired for 21 SZD patients, 21 SZND patients, and 21 HC to measure cortical thickness from 68 brain regions. Graph-based metrics (i.e., centrality, segregation, and integration) were computed and compared among groups, at both global and regional networks. When compared to HC, at the regional level, SZND were characterized by temporoparietal segregation and integration differences, while SZD showed widespread alterations in all network measures. SZD also showed less segregated network topology at the global level in comparison to HC. SZD and SZND differed in terms of centrality and integration measures in nodes belonging to the left temporoparietal cortex and to the limbic system. SZD is characterized by topological features in the network architecture of brain regions involved in negative symptomatology. Such results help to better define the neurobiology of SZD (SZD: Deficit Schizophrenia; SZND: Non-Deficit Schizophrenia; SZ: Schizophrenia; HC: healthy controls; CC: clustering coefficient; L: characteristic path length; E: efficiency; D: degree; CCnode: CC of a node; CCglob: the global CC of the network; Eloc: efficiency of the information transfer flow either within segregated subgraphs or neighborhoods nodes; Eglob: efficiency of the information transfer flow among the global network; FDA: Functional Data Analysis; and Dmin: estimated minimum densities).

BackgroundEmerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset MethodsOur sample included 321 adolescents with EOP (mean age: 16.3 ± 1.4 years, 46.4% females) and 265 adolescent CTR (mean age: 16.0 ± 1.7 years, 57.7% females) pooled from nine sites. All sites extracted mean fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for 25 white matter regions of interest per participant. ComBat harmonization was performed for all DTI measures to adjust for scanner differences. Multiple linear regression models were fitted to investigate case-control differences and associations with clinical variables in regional DTI measures.ResultsWe found widespread lower FA in EOP compared to CTR, with the largest effect sizes in the superior longitudinal fasciculus (Cohen’s d = 0.37), posterior corona radiata (d = 0.32), and superior fronto□occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status.ConclusionUsing the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male patients with early-onset schizophrenia and patients with a shorter duration of illness.

Transcranial direct current stimulation (tDCS) has been implemented in neuropsychiatric disorders characterized by cognitive impairment. However, methodological heterogeneity challenges conclusive remarks. Through a critical analysis of previous conflicting findings and in the light of current neurobiological models of pathophysiology, we qualitatively assessed the effects of tDCS in neuropsychiatric disorders that share neurobiological underpinnings, as to evaluate whether stimulation can improve cognitive deficits in patients’ cohorts. We performed a systematic review of tDCS studies targeting cognitive functions in mental disorders and pathological cognitive aging. Data from 41 studies, comprising patients with diagnosis of mood disorders, schizophrenia-spectrum disorders, Alzheimer’s disease (AD), and mild cognitive impairment (MCI), were included. Results indicate that tDCS has the capacity to enhance processing speed, working memory, and executive functions in patients with mood and schizophrenia-spectrum disorders. The evidence of a positive effect on general cognitive functioning and memory is either inconclusive in AD, or weak in MCI. Future directions are discussed for developing standardized stimulation protocols and for translating the technique therapeutic potential into effective clinical practice.

BackgroundPositive symptoms are a useful predictor of aggression in schizophrenia. Although a similar pattern of abnormal brain structures related to both positive symptoms and aggression has been reported, this observation has not yet been confirmed in a single sample.MethodTo study the association between positive symptoms and aggression in schizophrenia on a neurobiological level, a prospective meta-analytic approach was employed to analyze harmonized structural neuroimaging data from 10 research centers worldwide. We analyzed brain MRI scans from 902 individuals with a primary diagnosis of schizophrenia and 952 healthy controls.ResultsThe result identified a widespread cortical thickness reduction in schizophrenia compared to their controls. Two separate meta-regression analyses revealed that a common pattern of reduced cortical gray matter thickness within the left lateral temporal lobe and right midcingulate cortex was significantly associated with both positive symptoms and aggression.ConclusionThese findings suggested that positive symptoms such as formal thought disorder and auditory misperception, combined with cognitive impairments reflecting difficulties in deploying an adaptive control toward perceived threats, could escalate the likelihood of aggression in schizophrenia.

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.64 years (95% CI: 3.01, 4.26; I2 = 55.28%) compared to controls, after adjusting for age and sex (Cohen’s d = 0.50). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

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.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in rehabilitation research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires significant neuroanatomical expertise. We previously released a large, open-source dataset of stroke T1w MRIs and manually segmented lesion masks (ATLAS v1.2, N=304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N=955), a larger dataset of T1w stroke MRIs and manually segmented lesion masks that includes both training (public) and test (hidden) data. Algorithm development using this larger sample should lead to more robust solutions, and the hidden test data allows for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke rehabilitation research.

Amnestic mild cognitive impairment (aMCI) and sporadic Alzheimer’s disease (AD) are multifactorial conditions resulting from a complex crosstalk among multiple molecular and biological processes. The present study investigates the association of variants localized in genes and miRNAs with aMCI and AD, which may represent susceptibility, prognostic biomarkers or multi-target treatment options for such conditions. We included 371 patients (217 aMCI and 154 AD) and 503 healthy controls, which were genotyped for a panel of 120 single nucleotide polymorphisms (SNPs) and, subsequently, analyzed by statistical, bioinformatics and machine-learning approaches. As a result, 21 SNPs were associated with aMCI and 13 SNPs with sporadic AD. Interestingly, a set of variants shared between aMCI and AD displayed slightly higher Odd Ratios in AD with respect to aMCI, highlighting a specific risk trajectory linking aMCI to AD. Some of the associated genes and miRNAs were shown to interact within the signaling pathways of APP (Amyloid Precursor Protein), ACE2 (Angiotensin Converting Enzyme 2), miR-155 and PPARG (Peroxisome Proliferator Activated Receptor Gamma), which are known to contribute to neuroinflammation and neurodegeneration. Overall, results of this study increase insights concerning the genetic factors contributing to the neuroinflammatory and neurodegenerative mechanisms underlying aMCI and sporadic AD. They have to be exploited to develop personalized approaches based on the individual genetic make-up and multi-target treatments.

Homotaurine is a potential therapeutic compound for treatment of Alzheimer’s disease (AD), but its efficacy is still under investigation. Emerging data have shown that other than neuroprotective, homotaurine is endowed with anti-inflammatory activities, though with still unclear underlying mechanisms. Inflammation plays a critical role in the pathogenesis of AD and we previously suggested that homotaurine supplementation in patients with amnestic mild cognitive impairment (MCI) plays beneficial effects associated to a decrease in the circulating levels of the pro-inflammatory cytokine IL-18. Here we report that MCI patients supplemented with homotaurine for 12 months show elevated serum levels of IL-10 and IL-33, as compared to baseline, in addition to the described IL-18 decrease. Furthermore, we observed a significant positive correlation between IL-10 and IL-33 levels after treatment but not at the baseline, underlining the effectiveness of the compound in modulating both cytokines in an inter-related fashion and in regulating the pro/anti-inflammation balance. Furthermore, the elevation of both IL-10 and IL-33 is significantly associated with an improvement of episodic memory of treated patients, as measured by the Delayed Verbal Ray Test. In conclusion, our results confirm that homotaurine treatment exerts an overall anti-inflammatory action in MCI patients, based not only on the down-regulation of pro-inflammatory IL-18, but also on up-regulation of the anti-inflammatory IL-33 and IL-10 cytokines, which in turn are associated with an amelioration of patient’s cognitive functions. Future studies should be addressed to investigate the molecular mechanisms of homotaurine anti-inflammatory activity and its therapeutic exploitation in early AD.

Although etiological and maintenance cognitive factors have proved effective in predicting the disease course in youths with OCD, their contribution to symptom severity and specific OCD dimensions has been scarcely examined. In a cohort of children and adolescents with OCD (N = 41; mean age = 14; age range = 10–18 yrs.), we investigated whether certain dysfunctional beliefs and cognitive traits could predict symptom severity, and whether they were differentially associated with specific symptom dimensions. We found that self-oriented and socially prescribed perfectionism and intolerance to uncertainty were associated with higher obsession severity, which was not uniquely related to any neuropsychological variable. Greater severity of obsessions and compulsions about harm due to aggression/injury/violence/natural disasters was predicted by excessive concerns with the expectations of other people. Severity in this dimension was additionally predicted by decreasing accuracy in performing a problem-solving, non-verbal reasoning task, which was also a significant predictor of severity of obsessions about symmetry and compulsions to count or order/arrange. Apart from corroborating both the belief-based and neuropsychological models of OCD, our findings substantiate for the first time the specificity of certain dysfunctional beliefs and cognitive traits in two definite symptom dimensions in youth. This bears important clinical implications for developing treatment strategies to deal with unique dysfunctional core beliefs, and possibly for preventing illness chronicity.

ObjectiveIdentifying brain differences associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and generating effective approaches to early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth.MethodsFirst, we examined associations among regional brain structure and STBs, which were assessed in six samples of youth with mood disorders, using the Columbia Suicide Severity Rating Scale (C-SSRS;N=577). Second, we combined this sample with a larger sample (total 21 sites) in which STBs were assessed using various instruments. MRI metrics were compared among healthy controls without STBs (HC;N=688), clinical controls without STBs (CC;N=648), and young people with psychiatric diagnoses and current suicidal ideation (N=406). In separate analyses, MRI metrics were compared among HCs (N=335), CCs (N=768), and suicide attempters (N=254).ResultsIn the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and history of actual suicide attempts (N=163) than those without (N=394; FDR-pd=.334). When expanding to more clinically heterogeneous samples, we also found lower surface area of the frontal pole in those with a history of suicide attempts (Cohen’sd=.22).ConclusionsLower frontal pole surface area may represent a vulnerability for a suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.

ObjectiveA major limitation of current suicide research is the lack of power to identify robust correlates of suicidal thoughts or behaviour. Variation in suicide risk assessment instruments used across cohorts may represent a limitation to pooling data in international consortia.MethodHere, we examine this issue through two approaches: (i) an extensive literature search on the reliability and concurrent validity of the most commonly used instruments; and (ii) by pooling data (N∼6,000 participants) from cohorts from the ENIGMA-Major Depressive Disorder (ENIGMA-MDD) and ENIGMA-Suicidal Thoughts and Behaviour (ENIGMA-STB) working groups, to assess the concurrent validity of instruments currently used for assessing suicidal thoughts or behaviour.ResultsOur results suggested a pattern of moderate-to-high correlations between instruments, consistent with the wide range of correlations, r=0.22-0.97, reported in the literature. Two common complex instruments, the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Scale for Suicidal Ideation (SSI), were highly correlated with each other (r=0.83), as were suicidal ideation items from common depression severity questionnaires.ConclusionsOur findings suggest that multi-item instruments provide valuable information on different aspects of suicidal thoughts or behaviour, but share a core factor with single suicidal ideation items found in depression severity questionnaires. Multi-site collaborations including cohorts that used distinct instruments for suicide risk assessment should be feasible provided that they harmonise across instruments or focus on specific constructs of suicidal thoughts or behaviours.Key pointsQuestion: To inform future suicide research in multi-site international consortia, it is important to examine how different suicide measures relate to each other and whether they can be used interchangeably.Findings: Findings suggest detailed instruments (such as the Columbia Suicide Severity Rating Scale and Beck Scale for Suicidal Ideation) provide valuable information on suicidal thoughts and behaviour, and share a core factor with items on suicidal ideation from depression severity rating scale (such as the Hamilton Depression Rating Scale or the Beck Depression Inventory).Importance: Results from international collaborations can mitigate biases by harmonising distinct suicide risk assessment instruments.Next steps: Pooling data within international suicide research consortia may reveal novel clinical, biological and cognitive correlates of suicidal thoughts and/or behaviour.

Current investigations in pre-symptomatic dementia have suggested that depressive mood, a treatable condition, may play an important role in the development of the disorder. However, whether depression in adulthood constitute a risk factor, or a prodrome of dementia remains unclear. A major implication in such dispute is the analytic framework used to identify putative risk factors. Indeed, if evaluated in the years immediately prior to dementia diagnosis the association between depression and dementia may reflect depressive symptoms as a prodrome of yet-undiagnosed dementia. Unfortunately, long term prospective cohort investigations, reaching back into the preclinical phase of dementia are sparse. Here, we have surveyed high-quality evidence (systematic reviews and meta-analyses) on the association between depressive symptoms and increased odds of dementia. Meta-analytic findings are also presented and discussed regarding depression as a prodromal stage of dementia, or a consequence of underlying neurodegenerative processes. Additionally, the potential confounding effect of several variables on the risk association between depression and dementia, an aspect hardly investigated, is discussed. While early onset late-life depression - defined as starting before 60 years of age - increases the odds of developing dementia in predisposed subjects, late-onset depression appears to be a prodrome and a clear accelerating factor for cognitive deterioration. Since it is increasingly important to consider the potential of preemptive approaches to decrease the impact of dementia, evidence on potentially effective preventive strategies targeting depression as a risk factor, and next steps in further research are presented as concluding remarks.

Objective Defective cerebellar GABAergic inhibitory control may participate to the cognitive impairments seen in SZ. We tested the prediction of a model for the relationship between cerebellar GABA concentration and the associative/executive processes required by verbal fluency in patients with schizophrenia (SZ) and matched healthy controls (HC). Method Magnetic resonance spectroscopy of GABA was performed using a 3 Tesla scanner and verbal fluency assessed by the Controlled Word (WFT) and Semantic (SFT) Fluency tests. Cerebellar GABA measurements were obtained using the MEGA-PRESS acquisition sequence. Linear correlations between cerebellar GABA levels and the WFT, SFT score were performed to test differences between correlation coefficients of SZ and HC. Quantile regressions between GABA levels and the WFT score were performed. Results Higher cerebellar GABA concentration was associated in SZ with lower phonemic fluency and reduced number of switches among subcategories as opposed to what observed in HC (with higher cerebellar GABA associated with higher number of words and phonemic switches). GABA levels explained phonemic fluency in SZ performing above the group mean. Conclusion Studying cerebellar GABA provides a valid heuristic to explore the molecular mechanisms of SZ. This is crucial for developing pharmacological treatments to improve cognition and functional recovery in SZ.