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      Association between body mass index and subcortical brain volumes in bipolar disorders–ENIGMA study in 2735 individuals

      research-article
      1 , 2 , 1 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 7 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 6 , 7 , 7 , 19 , 7 , 20 , 21 , 2 , 8 , 8 , 22 , 23 , 24 , 25 , 7 , 2 , 11 , 5 , 26 , 10 , 3 , 4 , 10 , 10 , 1 , 7 , 8 , 27 , 3 , 4 , 28 , 10 , 8 , 7 , 29 , 30 , 17 , 8 , 31 , 9 , 2 , 6 , 32 , 7 , 7 , 8 , 28 , 9 , 23 , 33 , 8 , 17 , 18 , 34 , 35 , 20 , 21 , 36 , 8 , 21 , 7 , 37 , 38 , 1 , 11 , 6 , 37 , 7 , 39 , 40 , 12 , 40 , 1 , 41 , , for the ENIGMA Bipolar Disorders Working Group
      Molecular Psychiatry
      Nature Publishing Group UK
      Bipolar disorder, Neuroscience

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          Abstract

          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.

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          Beyond Baron and Kenny: Statistical Mediation Analysis in the New Millennium

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            Effect size, confidence interval and statistical significance: a practical guide for biologists.

            Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
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              Identification of a common neurobiological substrate for mental illness.

              Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness. To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis. PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data. Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach. We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition. Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning. We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.
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                Author and article information

                Contributors
                tomas.hajek@dal.ca
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                16 April 2021
                16 April 2021
                2021
                : 26
                : 11
                : 6806-6819
                Affiliations
                [1 ]GRID grid.55602.34, ISNI 0000 0004 1936 8200, Department of Psychiatry, , Dalhousie University, ; Halifax, NS Canada
                [2 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Clinical Neuroscience, , Karolinska Institutet, ; Stockholm, Sweden
                [3 ]GRID grid.15496.3f, ISNI 0000 0001 0439 0892, Vita-Salute San Raffaele University, ; Milan, Italy
                [4 ]GRID grid.18887.3e, ISNI 0000000417581884, Division of Neuroscience, Psychiatry and Psychobiology Unit, , IRCCS San Raffaele Scientific Institute, ; Milan, Italy
                [5 ]GRID grid.55325.34, ISNI 0000 0004 0389 8485, Unit for Psychosomatics / CL Outpatient Clinic for Adults, Division of Mental Health and Addiction, , Oslo University Hospital, ; Oslo, Norway
                [6 ]GRID grid.5841.8, ISNI 0000 0004 1937 0247, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona Bipolar Disorders and Depressive Unit, Hospital Clinic, Institute of Neurosciences, , University of Barcelona, ; Barcelona, Spain
                [7 ]GRID grid.5949.1, ISNI 0000 0001 2172 9288, Department of Psychiatry, , University of Münster, ; Münster, Germany
                [8 ]GRID grid.10253.35, ISNI 0000 0004 1936 9756, Department of Psychiatry and Psychotherapy, , Philipps-University Marburg, ; Marburg, Germany
                [9 ]GRID grid.466668.c, FIDMAG Germanes Hospitalàries Research Foundation, ; Barcelona, Spain
                [10 ]GRID grid.6142.1, ISNI 0000 0004 0488 0789, Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, , National University of Ireland Galway, ; Galway, Ireland
                [11 ]GRID grid.412881.6, ISNI 0000 0000 8882 5269, Research Group in Psychiatry GIPSI, Department of Psychiatry, Faculty of Medicine, , Universidad de Antioquia, ; Medellín, Colombia
                [12 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Norwegian Centre for Mental Disorders Research (NORMENT), , Institute of Clinical Medicine, University of Oslo, ; Oslo, Norway
                [13 ]GRID grid.55325.34, ISNI 0000 0004 0389 8485, Department of Neurology, Division of Clinical Neuroscience, , Oslo University Hospital, ; Oslo, Norway
                [14 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Institute of Clinical Medicine, , University of Oslo, ; Oslo, Norway
                [15 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Psychiatry, , University of California, San Diego, ; La Jolla, CA USA
                [16 ]GRID grid.410371.0, ISNI 0000 0004 0419 2708, Desert-Pacific MIRECC, , VA San Diego Healthcare, ; San Diego, CA USA
                [17 ]GRID grid.250407.4, ISNI 0000 0000 8900 8842, Neuroscience Research Australia, ; Randwick, NSW Australia
                [18 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Medical Sciences, , University of New South Wales, ; Sydney, NSW Australia
                [19 ]GRID grid.4830.f, ISNI 0000 0004 0407 1981, Department of Psychiatry, University Medical Center Groningen, , University of Groningen, ; Groningen, The Netherlands
                [20 ]GRID grid.7836.a, ISNI 0000 0004 1937 1151, Neuroscience Institute, , University of Cape Town, ; Cape Town, South Africa
                [21 ]GRID grid.7836.a, ISNI 0000 0004 1937 1151, Department of Psychiatry and Mental Health, , University of Cape Town, ; Cape Town, South Africa
                [22 ]GRID grid.10388.32, ISNI 0000 0001 2240 3300, Department of Psychiatry and Psychotherapy, , University of Bonn, ; Bonn, Germany
                [23 ]GRID grid.417423.7, ISNI 0000 0004 0512 8863, Laureate Institute for Brain Research, ; Tulsa, OK USA
                [24 ]GRID grid.8761.8, ISNI 0000 0000 9919 9582, Department of Neuroscience and Physiology, Sahlgrenska Academy at Gothenburg University, ; Gothenburg, Sweden
                [25 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Medical Epidemiology and Biostatistics, , Karolinska Institutet, ; Stockholm, Sweden
                [26 ]GRID grid.5510.1, ISNI 0000 0004 1936 8921, Institute of Clinical Medicine, Department of Neurology, , University of Oslo, ; Oslo, Norway
                [27 ]GRID grid.8664.c, ISNI 0000 0001 2165 8627, Center for Mind, Brain and Behavior (CMBB), , University of Marburg and Justus Liebig University Giessen, ; Marburg, Germany
                [28 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Psychiatry, , University of New South Wales, ; Sydney, NSW Australia
                [29 ]GRID grid.19006.3e, ISNI 0000 0000 9632 6718, UCLA Center for Neurobehavioral Genetics, ; Los Angeles, CA USA
                [30 ]GRID grid.5645.2, ISNI 000000040459992X, Department of Psychiatry, , Erasmus University Medical Center, ; Rotterdam, The Netherlands
                [31 ]Research Group, Instituto de Alta Tecnología Médica, Ayudas diagnósticas SURA, Medellín, Colombia
                [32 ]GRID grid.13097.3c, ISNI 0000 0001 2322 6764, Institute of Psychiartry, , King’s College Londen, ; London, UK
                [33 ]GRID grid.267360.6, ISNI 0000 0001 2160 264X, Oxley College of Health Sciences, , The University of Tulsa, ; Tulsa, OK USA
                [34 ]GRID grid.414752.1, ISNI 0000 0004 0469 9592, West Region, Institute of Mental Health, ; Singapore, Singapore
                [35 ]GRID grid.4280.e, ISNI 0000 0001 2180 6431, Yong Loo Lin School of Medicine, , National University of Singapore, ; Singapore, Singapore
                [36 ]GRID grid.7836.a, ISNI 0000 0004 1937 1151, South African MRC Unit on Risk & Resilience in Mental Disorders, , University of Cape Town, ; Cape Town, South Africa
                [37 ]GRID grid.6906.9, ISNI 0000000092621349, Department of Child and Adolescent Psychiatry and Psychology, , Erasmus University, ; Rotterdam, The Netherlands
                [38 ]GRID grid.5477.1, ISNI 0000000120346234, Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, , Utrecht University, ; Utrecht, The Netherlands
                [39 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, University of British Columbia, ; Vancouver, BC Canada
                [40 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, , University of Southern California, ; Marina del Rey, CA USA
                [41 ]GRID grid.447902.c, National Institute of Mental Health, ; Klecany, Czech Republic
                Author information
                http://orcid.org/0000-0002-1680-8480
                http://orcid.org/0000-0003-4949-856X
                http://orcid.org/0000-0002-9546-2763
                http://orcid.org/0000-0001-6421-2633
                http://orcid.org/0000-0001-7378-3411
                http://orcid.org/0000-0001-9991-1610
                http://orcid.org/0000-0003-4014-4490
                http://orcid.org/0000-0003-3087-1002
                http://orcid.org/0000-0002-0564-2497
                http://orcid.org/0000-0002-9881-2511
                http://orcid.org/0000-0003-1661-5192
                http://orcid.org/0000-0002-7954-5235
                http://orcid.org/0000-0001-9448-7769
                http://orcid.org/0000-0002-8287-6457
                http://orcid.org/0000-0002-7138-5556
                http://orcid.org/0000-0001-8143-182X
                http://orcid.org/0000-0003-2967-9662
                http://orcid.org/0000-0003-3209-9626
                http://orcid.org/0000-0001-7218-7810
                http://orcid.org/0000-0002-2621-2920
                http://orcid.org/0000-0001-7331-0534
                http://orcid.org/0000-0002-4461-3568
                http://orcid.org/0000-0003-0281-8458
                Article
                1098
                10.1038/s41380-021-01098-x
                8760047
                33863996
                ec5c1a2a-5b8a-4375-98dc-920922f5146e
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 August 2020
                : 26 February 2021
                : 1 April 2021
                Funding
                Funded by: This study was supported by funding from the Canadian Institutes of Health Research (103703, 106469 and 142255), Nova Scotia Health Research Foundation, Dalhousie Clinical Research Scholarship to TH, Brain & Behavior Research Foundation (formerly NARSAD); 2007 Young Investigator and 2015 Independent Investigator Awards to TH.
                Funded by: supported by grants from the Swedish Research Council (2018-02653), the Swedish foundation for Strategic Research (KF10-0039), the Swedish Brain foundation, and the Swedish Federal Government under the LUA/ALF agreement (ALF 20170019, ALFGBG-716801).
                Funded by: Supported by the Italian Ministry of Health RF-2011-02350980 project.
                Funded by: Health Research Board (HRA-POR-324)
                Funded by: funded by the German Research Foundation (Deutsche Forschungsgemeinschaft DFG; Forschungsgruppe/Research Unit FOR2107). DA 1151/5-1, DA 1151/5-2,SFB-TRR58.and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD
                Funded by: supported by the Australian National Health and Medical Research Council (NHMRC) Program Grant 1037196, Project Grants 1063960 and 1066177, the Lansdowne Foundation, Good Talk and Keith Pettigrew Family; as well as the Janette Mary O’Neil Research Fellowship to JMF.
                Funded by: supported by the University Research Committee, University of Cape Town and South African funding bodies National Research Foundation and Medical Research Council
                Funded by: DFG grant numbers KI 588/14-1, KI 588/14-2
                Funded by: were supported by the PRISMA UNION TEMPORAL (UNIVERSIDAD DE ANTIOQUIA / HOSPITAL SAN VICENTE FUNDACIÓN), Colciencias-INVITACIÓN 990 de 3 de agosto de 2017, Codigo 99059634.
                Funded by: Funding for the Oslo-Malt cohort was provided by the South Eastern Norway Regional Health Authority (2015-078), the Ebbe Frøland foundation, and a research grant from Mrs. Throne-Holst.
                Funded by: supported by the Health Research Board (HRA_POR/2011/100)
                Funded by: supported by the Irish Research Council (IRC) Postgraduate Scholarship, Ireland awarded to LN and to GM
                Funded by: Supported by DFG, NE 2254/1-1 and NE 2254/2-1
                Funded by: supported by NIMH grant number: R01 MH090553
                Funded by: Funded by CIBERSAM (EPC) and the Instituto de Salud Carlos III (PI18/00877, and PI19/00394)
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: R21MH113871
                Award Recipient :
                Funded by: Funded by the National Institute of General Medical Sciences (P20GM121312)
                Funded by: Funded by the Singapore Bioimaging Consortium (RP C009/2006) research grant
                Funded by: Funded by the Spanish Ministry of Science and Innovation (PI15/00283, PI18/00805) integrated into the Plan Nacional de I+D+I and co-financed by the ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER); the Instituto de Salud Carlos III; the CIBER of Mental Health (CIBERSAM); the Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement (2017 SGR 1365), the CERCA Programme, and the Departament de Salut de la Generalitat de Catalunya for the PERIS grant SLT006/17/00357.
                Funded by: supported by NIH grant U54 EB020403 from the Big Data to Knowledge (BD2K) Program; also funded by NIA T32AG058507.
                Categories
                Article
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                © The Author(s), under exclusive licence to Springer Nature Limited 2021

                Molecular medicine
                bipolar disorder,neuroscience
                Molecular medicine
                bipolar disorder, neuroscience

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