Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder

被引:39
作者
Schwarz, Emanuel [1 ]
Nhat Trung Doan [2 ]
Pergola, Giulio [3 ]
Westlye, Lars T. [2 ,4 ]
Kaufmann, Tobias [2 ]
Wolfers, Thomas [5 ,6 ]
Brecheisen, Ralph [7 ]
Quarto, Tiziana [3 ,8 ]
Ing, Alex J. [9 ,10 ]
Di Carlo, Pasquale [3 ]
Gurholt, Tiril P. [2 ]
Harms, Robbert L. [11 ]
Noirhomme, Quentin [11 ]
Moberget, Torgeir [2 ]
Agartz, Ingrid [2 ,12 ,13 ,14 ]
Andreassen, Ole A. [2 ]
Bellani, Marcella [15 ,16 ]
Bertolino, Alessandro [3 ,17 ]
Blasi, Giuseppe [3 ,18 ]
Brambilla, Paolo [19 ]
Buitelaar, Jan K. [20 ,21 ]
Cervenka, Simon [12 ,13 ]
Flyckt, Lena [12 ,13 ]
Frangou, Sophia [22 ]
Franke, Barbara [20 ,23 ,24 ]
Hall, Jeremy [25 ]
Heslenfeld, Dirk J. [26 ]
Kirsch, Peter [27 ,28 ]
McIntosh, Andrew M. [29 ,30 ]
Noethen, Markus M. [31 ,32 ,33 ]
Papassotiropoulos, Andreas [34 ,35 ,36 ,37 ]
de Quervain, Dominique J-F [35 ,36 ,38 ]
Rietschel, Marcella [39 ]
Schumann, Gunter [9 ,10 ]
Tost, Heike [1 ]
Witt, Stephanie H. [39 ]
Zink, Mathias [1 ,40 ]
Meyer-Lindenberg, Andreas [1 ]
Bettella, Francesco [2 ]
Brandt, Christine L. [2 ]
Clarke, Toni-Kim [29 ]
Coynel, David [35 ,38 ]
Degenhardt, Franziska [33 ]
Djurovic, Srdjan [2 ,41 ]
Eisenacher, Sarah [1 ]
Fastenrath, Matthias [35 ,38 ]
Fatouros-Bergman, Helena [12 ,13 ]
Forstner, Andreas J. [31 ,32 ,33 ,42 ,43 ,44 ]
Frank, Josef [39 ]
Gambi, Francesco [45 ]
机构
[1] Heidelberg Univ, Med Fac Mannheim, Cent Inst Mental Hlth, Dept Psychiat & Psychotherapy, Mannheim, Germany
[2] Univ Oslo, Inst Clin Med, Norwegian Ctr Mental Disorders Res NORMENT, KG Jebsen Ctr Psychosis Res,Div Mental Hlth & Add, Oslo, Norway
[3] Univ Bari Aldo Moro, Dept Basic Med Sci Neurosci & Sense Organs, Bari, Italy
[4] Univ Oslo, Dept Psychol, Oslo, Norway
[5] Radboud Univ Nijmegen, Dept Human Genet, Med Ctr, Nijmegen, Netherlands
[6] Radboud Univ Nijmegen, Donders Ctr Cognit Neuroimaging, Nijmegen, Netherlands
[7] Maastricht Univ, Med Ctr, Maastricht, Netherlands
[8] Univ Helsinki, Dept Psychol & Logoped, Cognit Brain Res Unit, Fac Med, Helsinki, Finland
[9] Kings Coll London, Ctr Populat Neurosci & Stratified Med PONS, London, England
[10] Kings Coll London, MRC SGDP Ctr, Inst Psychiat Psychol & Neurosci, London, England
[11] Brain Innovat BV, Maastricht, Netherlands
[12] Karolinska Inst, Dept Clin Neurosci, Ctr Psychiat Res, Stockholm, Sweden
[13] Stockholm Cty Council, Stockholm, Sweden
[14] Diakonhjemmet Hosp, Dept Psychiat Res, Oslo, Norway
[15] Azienda Osped Univ Integrata Verona, Sect Psychiat, Verona, VR, Italy
[16] Univ Verona, Dept Neurosci Biomed & Movements Sci, Verona, VR, Italy
[17] Azienda Osped Univ Consorziale Policlin Bari, Policlin Bari, Inst Psichiatry, Bari, BA, Italy
[18] Azienda Osped Univ Consorziale Policlin, Bari, Italy
[19] Univ Milan, Fdn IRCCS Ca Granda Osped Maggiore Policlin, Dept Neurosci & Mental Hlth, Milan, Italy
[20] Radboudumc, Donders Inst Brain Cognit & Behav, Nijmegen, Netherlands
[21] Karakter Child & Adolescent Psychiat Univ Ctr, Nijmegen, Netherlands
[22] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA
[23] Radboud Univ Nijmegen, Dept Human Genet, Med Ctr, Nijmegen, Netherlands
[24] Radboud Univ Nijmegen, Dept Psychiat, Med Ctr, Nijmegen, Netherlands
[25] Cardiff Univ, Neurosci & Mental Hlth Res Inst, Maindy Rd, Cardiff CF24 4HQ, S Glam, Wales
[26] Vrije Univ Amsterdam, Dept Cognit Psychol, Amsterdam, Netherlands
[27] Heidelberg Univ, Cent Inst Mental Hlth, Med Fac Mannheim, Dept Clin Psychol, Heidelberg, Germany
[28] Bernstein Ctr Computat Neurosci Heidelberg Mannhe, Mannheim, Germany
[29] Univ Edinburgh, Royal Edinburgh Hosp, Div Psychiat, Edinburgh EH10 5HF, Midlothian, Scotland
[30] Univ Edinburgh, Ctr Cognit Ageing & Cognit Epidemiol, George Sq, Edinburgh EH8 9JZ, Midlothian, Scotland
[31] Univ Bonn, Sch Med, Inst Human Genet, Bonn, Germany
[32] Univ Hosp Bonn, Bonn, Germany
[33] Univ Bonn, Dept Genom, Life & Brain Ctr, Bonn, Germany
[34] Univ Basel, Dept Psychol, Div Mol Neurosci, CH-4055 Basel, Switzerland
[35] Univ Basel, Transfac Res Platform Mol & Cognit Neurosci, Basel, Switzerland
[36] Univ Basel, Psychiat Univ Clin, CH-4055 Basel, Switzerland
[37] Univ Basel, Dept Biozentrum, Life Sci Training Facil, CH-4056 Basel, Switzerland
[38] Univ Basel, Dept Psychol, Div Cognit Neurosci, CH-4055 Basel, Switzerland
[39] Heidelberg Univ, Cent Inst Mental Hlth, Med Fac Mannheim, Dept Genet Epidemiol Psychiat, Heidelberg, Germany
[40] Dist Hosp Mittelfranken, Dept Psychiat Psychotherapy & Psychosomat, Ansbach, Germany
[41] Oslo Univ Hosp, Dept Med Genet, Oslo, Norway
[42] Univ Basel, Dept Biomed, Human Genom Res Grp, Basel, Switzerland
[43] Univ Basel, Dept Psychiat UPK, Basel, Switzerland
[44] Univ Hosp Basel, Inst Med Genet & Pathol, Basel, Switzerland
[45] G DAnnunzio Univ Chieti Pescara, Dept Neurosci Imaging & Clin Sci, Pescara, Italy
[46] Natl Hlth Trust, Dept Mental Hlth, Chieti, Italy
[47] Fdn Casa Sollievo Sofferenza IRCCS San Giovanni R, San Giovanni Rotondo, Italy
[48] Univ Groningen, Univ Med Ctr Groningen, Interdisciplinary Ctr Psychopathol & Emot regulat, Dept Psychiat, Groningen, Netherlands
[49] Univ Basel, Dept Biomed, Basel, Switzerland
[50] Univ Basel, Inst Med Genet & Pathol, Human Genom Res Grp, Basel, Switzerland
基金
瑞典研究理事会; 美国国家卫生研究院; 瑞士国家科学基金会; 英国惠康基金;
关键词
LIKELIHOOD ESTIMATION; MRI SCANS; METAANALYSIS; 1ST-EPISODE; RISK; CLASSIFICATION; SEGMENTATION; DEFICITS; VOLUME;
D O I
10.1038/s41398-018-0225-4
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
引用
收藏
页数:13
相关论文
共 59 条
[1]  
[Anonymous], NAT GENET
[2]  
[Anonymous], 101101048991 BIORXIV
[3]  
[Anonymous], QBIO0503025 ARXIV
[4]  
[Anonymous], 2017, R PACKAGE VERSION
[5]   Voxel-based morphometry - The methods [J].
Ashburner, J ;
Friston, KJ .
NEUROIMAGE, 2000, 11 (06) :805-821
[6]   A fast diffeomorphic image registration algorithm [J].
Ashburner, John .
NEUROIMAGE, 2007, 38 (01) :95-113
[7]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[8]   Neuroanatomical abnormalities in schizophrenia: A multimodal voxelwise meta-analysis and meta-regression analysis [J].
Bora, Emre ;
Fornito, Alex ;
Radua, Joaquim ;
Walterfang, Mark ;
Seal, Marc ;
Wood, Stephen J. ;
Yuecel, Murat ;
Velakoulis, Dennis ;
Pantelis, Christos .
SCHIZOPHRENIA RESEARCH, 2011, 127 (1-3) :46-57
[9]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[10]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32