Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIG...
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| Vydané v: | Nature communications Ročník 15; číslo 1; s. 5996 - 15 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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London
Nature Publishing Group UK
17.07.2024
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| Abstract | Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
Machine learning can be used to identify subtypes of psychiatric disease. Here the authors identified two neurostructural subgroups in schizophrenia, each showing reproducibility and generalizability across different collection locations and illness stages, using the SuStain algorithm. |
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| AbstractList | Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. Machine learning can be used to identify subtypes of psychiatric disease. Here the authors identified two neurostructural subgroups in schizophrenia, each showing reproducibility and generalizability across different collection locations and illness stages, using the SuStain algorithm. Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. Machine learning can be used to identify subtypes of psychiatric disease. Here the authors identified two neurostructural subgroups in schizophrenia, each showing reproducibility and generalizability across different collection locations and illness stages, using the SuStain algorithm. Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. Abstract Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. |
| ArticleNumber | 5996 |
| Author | Gonul, Ali Saffet Vecchio, Daniela Rossell, Susan L. Demro, Caroline Calhoun, Vince D. Cheng, Jingliang Xiang, Shitong Sim, Kang Preda, Adrian de Bartolomeis, Andrea Li, Chunbo Glahn, David Iasevoli, Felice Zhou, Enpeng Sponheim, Scott R. Nguyen, Dana D. Turner, Jessica A. Miura, Kenichiro Cocozza, Sirio Yue, Weihua Banaj, Nerisa Rootes-Murdy, Kelly Burhanoglu, Birce Begum Lin, Ching-Po Tsai, Shih-Jen Stein, Frederike Hahn, Tim Green, Melissa Luo, Cheng Gaser, Christian Brunetti, Arturo Thompson, Paul M. Palaniyappan, Lena Pomarol-Clotet, Edith Jiang, Yuchao Westlye, Lars T. Tang, Yingying Dannlowski, Udo Huang, Huan Cecere, Giacomo Thomopoulos, Sophia I. Homan, Stephanie Cui, Long-Biao Barone, Annarita Thomas-Odenthal, Florian Hughes, Matthew Kim, Woo-Sung Fuentes-Claramonte, Paola Yao, Dezhong Kaiser, Stefan Pearlson, Godfrey Chung, Young Chul Tranfa, Mario Meinert, Susanne Georgiadis, Foivos Nenadić, Igor Omlor, Wolfgang Cheng, Wei Woods, William Sumner, Philip Andreassen, Ole A. Rodrigue, Amanda L. Liu, Zhening Wang, Jijun Teutenberg, Lea Lencer |
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M. organization: Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab – sequence: 104 givenname: Wei orcidid: 0000-0003-1118-1743 surname: Cheng fullname: Cheng, Wei organization: Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Department of Neurology, Huashan Hospital, Fudan University, Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University – sequence: 106 givenname: Jianfeng orcidid: 0000-0002-8890-8288 surname: Feng fullname: Feng, Jianfeng email: jffeng@fudan.edu.cn organization: Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Fudan ISTBI—ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, MOE Frontiers Center for Brain Science, Fudan University, Zhangjiang Fudan International Innovation Center, School of Data Science, Fudan University, Department of Computer Science, University of Warwick |
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| Cites_doi | 10.1093/cercor/bhn152 10.1038/mp.2015.90 10.1016/j.neuroimage.2019.116189 10.1016/S0140-6736(03)12323-9 10.1016/j.pnpbp.2018.09.009 10.1093/schbul/sbaa185 10.1016/S2215-0366(15)00540-4 10.1016/S0920-9964(97)00110-2 10.1038/sdata.2016.110 10.1038/s44220-023-00024-0 10.1176/appi.ajp.21070686 10.1093/brain/awaa025 10.1016/j.biopsych.2018.04.023 10.1016/j.neuroimage.2015.05.060 10.1038/s41380-023-02221-w 10.1148/radiol.2018184005 10.1073/pnas.201243998 10.1016/j.biopsych.2015.02.008 10.1192/bjp.bp.113.138099 10.1016/j.brs.2018.11.006 10.1038/s41591-021-01309-6 10.2174/1570159X19666210809101248 10.1016/j.media.2021.102304 10.3389/fnhum.2012.00137 10.1503/jpn.100176 10.1371/journal.pone.0276975 10.1001/jamapsychiatry.2014.2414 10.1192/bjp.188.6.510 10.1038/s41380-023-02043-w 10.1038/s41467-018-05892-0 10.1093/schbul/13.2.261 10.1038/mp.2015.118 10.1093/schbul/sbaa169 10.1093/schbul/sby008 10.1001/jamapsychiatry.2019.0257 10.1038/s41467-024-46629-6 10.1038/s41591-021-01614-0 10.1038/s41380-021-01308-6 10.1097/00005053-199411000-00006 10.1016/j.neuroimage.2018.08.012 10.1038/mp.2014.66 10.1038/s41380-023-02141-9 10.1038/s41380-019-0553-7 10.1002/hbm.24049 10.1016/j.neuroimage.2019.116450 10.1002/wps.20693 10.1001/jamapsychiatry.2015.2324 10.1038/s41380-019-0502-5 10.1038/s41386-022-01426-x 10.1093/schbul/sbt068 10.1038/s41467-021-26703-z 10.1016/j.neuroimage.2015.06.030 10.1073/pnas.1304308110 10.1007/s12021-013-9184-3 10.1016/j.biopsych.2009.11.017 10.1093/schbul/sbaa127 10.1016/S2589-7500(20)30160-6 10.1001/jamapsychiatry.2018.2467 10.1016/0140-6736(93)91707-S 10.1192/bjp.bp.113.138578 10.1016/j.biopsych.2019.07.008 10.1001/archgenpsychiatry.2010.199 10.1001/jamapsychiatry.2017.2663 10.1016/j.neuroimage.2015.04.042 10.1212/WNL.0000000000012410 10.1016/j.neuroimage.2017.04.046 10.1016/S0140-6736(18)31370-9 10.1001/jamapsychiatry.2019.3360 10.1016/j.neuroimage.2015.02.065 10.1038/s41597-021-01004-8 10.1016/j.neuroimage.2006.01.021 10.1016/j.neuron.2019.05.013 10.1016/j.neuroimage.2015.09.003 |
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| References | VitaADe PeriLDesteGBarlatiSSacchettiEThe effect of antipsychotic treatment on cortical gray matter changes in schizophrenia: does the class matter? a meta-analysis and meta-regression of longitudinal magnetic resonance imaging studiesBiol. Psychiatry2015784034121:CAS:528:DC%2BC2MXltFelurs%3D2580208110.1016/j.biopsych.2015.02.008 Organization W. H. The Global Burden Of Disease: 2004 Update. (World Health Organization, 2008). PalaniyappanLLiddlePFDoes the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunctionJ. Psychiatry Neurosci.201237172721693094324449510.1503/jpn.100176 KochKFunctional connectivity and grey matter volume of the striatum in schizophreniaBr. J. Psychiatry20142052042132501268310.1192/bjp.bp.113.138099 BanajNCortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analysesMol. Psychiatry20232843634373376441741082766510.1038/s41380-023-02221-w CrowTJIs schizophrenia the price that Homo sapiens pays for language?Schizophr. Res1997281271411:STN:280:DyaK1c7islyltA%3D%3D946834810.1016/S0920-9964(97)00110-2 TheLICD-11: a brave attempt at classifying a new worldLancet2018391247610.1016/S0140-6736(18)31370-9 RepovsGBarchDMWorking memory related brain network connectivity in individuals with schizophrenia and their siblingsFront Hum. Neurosci.2012613722654746335877210.3389/fnhum.2012.00137 LalousisPAHeterogeneity and classification of recent onset psychosis and depression: a multimodal machine learning approachSchizophr. Bull.2021471130114033543752826665410.1093/schbul/sbaa185 HowesODCummingsCChapmanGEShatalinaENeuroimaging in schizophrenia: an overview of findings and their implications for synaptic changesNeuropsychopharmacology2023481511673605610610.1038/s41386-022-01426-x Lewandowski K. E., Bouix S., Ongur D., Shenton M. E. Neuroprogression across the Early Course of Psychosis. J Psychiatr Brain Sci 5, e200002 (2020). VercammenAKnegteringHden BoerJALiemburgEJAlemanAAuditory hallucinations in schizophrenia are associated with reduced functional connectivity of the temporo-parietal areaBiol. Psychiatry2010679129182006010310.1016/j.biopsych.2009.11.017 BaluDTMultiple risk pathways for schizophrenia converge in serine racemase knockout mice, a mouse model of NMDA receptor hypofunctionProc. Natl Acad. Sci. USA2013110E2400E24092013PNAS..110.2407B1:CAS:528:DC%2BC3sXhtFejs7fK23729812369682510.1073/pnas.1304308110 ChandGBTwo distinct neuroanatomical subtypes of schizophrenia revealed using machine learningBrain20201431027103832103250708966510.1093/brain/awaa025 WangJECT-induced brain plasticity correlates with positive symptom improvement in schizophrenia by voxel-based morphometry analysis of grey matterBrain Stimul.2019123193281:CAS:528:DC%2BC1MXitFyhtr7O3047347710.1016/j.brs.2018.11.006 OkadaNSubcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classificationMol. Psychiatry20232852065216375372811104179710.1038/s41380-023-02141-9 Fusar-PoliPHeterogeneity of psychosis risk within individuals at clinical high risk: a meta-analytical stratificationJAMA Psychiatry2016731131202671991110.1001/jamapsychiatry.2015.2324 RajpurkarPChenEBanerjeeOTopolEJAI in health and medicineNat. Med20222831381:CAS:528:DC%2BB38XhslCntr4%3D3505861910.1038/s41591-021-01614-0 van ErpTGMCortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro imaging genetics through meta analysis (ENIGMA) consortiumBiol. Psychiatry20188464465429960671617730410.1016/j.biopsych.2018.04.023 PomponioRHarmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespanNeuroimage20202083182186910.1016/j.neuroimage.2019.116450 McCutcheonRAKrystalJHHowesODDopamine and glutamate in schizophrenia: biology, symptoms and treatmentWorld Psychiatry202019153331922684695355110.1002/wps.20693 JiangYIdentification of four biotypes in temporal lobe epilepsy via machine learning on brain imagesNat. Commun.2024152024NatCo..15.2221J1:CAS:528:DC%2BB2cXntFequ7Y%3D384722521093345010.1038/s41467-024-46629-6 ChaseHWLoriemiPWensingTEickhoffSBNickl-JockschatTMeta-analytic evidence for altered mesolimbic responses to reward in schizophreniaHum. Brain Mapp.2018392917292829573046686658610.1002/hbm.24049 DwyerDBBrain subtyping enhances the neuroanatomical discrimination of schizophreniaSchizophr. Bull.2018441060106929529270610148110.1093/schbul/sby008 Collado-TorresLRegional heterogeneity in gene expression, regulation, and coherence in the frontal cortex and hippocampus across development and schizophreniaNeuron2019103203216 e2081:CAS:528:DC%2BB3cXls1Cmur0%3D31174959700020410.1016/j.neuron.2019.05.013 IglesiasJEA computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRINeuroimage20151151171372593680710.1016/j.neuroimage.2015.04.042 LindenmayerJPBernstein-HymanRGrochowskiSFive-factor model of schizophrenia. Initial validationJ. Nerv. Ment. Dis.19941826316381:STN:280:DyaK2M%2Fltl2muw%3D%3D796467110.1097/00005053-199411000-00006 MouchlianitisEMcCutcheonRHowesODBrain-imaging studies of treatment-resistant schizophrenia: a systematic reviewLancet Psychiatry2016345146326948188579664010.1016/S2215-0366(15)00540-4 KirschnerMOrbitofrontal-striatal structural alterations linked to negative symptoms at different stages of the schizophrenia spectrumSchizophr. Bull.2021478498633325795410.1093/schbul/sbaa169 DesikanRSAn automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interestNeuroimage2006319689801653043010.1016/j.neuroimage.2006.01.021 JiangYNeuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophreniaNat. Ment. Health2023118619910.1038/s44220-023-00024-0 ThompsonPMMapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophreniaProc. Natl Acad. Sci. USA20019811650116552001PNAS...9811650T1:CAS:528:DC%2BD3MXnt12jsLo%3D115730025878410.1073/pnas.201243998 ThompsonPMTime-lapse mapping of cortical changes in schizophrenia with different treatmentsCereb. Cortex200919110711231884266810.1093/cercor/bhn152 BruggerSPHowesODHeterogeneity and homogeneity of regional brain structure in schizophrenia: a meta-analysisJAMA Psychiatry2017741104111128973084566945610.1001/jamapsychiatry.2017.2663 HowesODOnwordiECThe synaptic hypothesis of schizophrenia version III: a master mechanismMol. Psychiatry20232818431856370414181057578810.1038/s41380-023-02043-w YoungALCharacterizing the clinical features and atrophy patterns of MAPT-related frontotemporal dementia with disease progression modelingNeurology202197e941e9521:CAS:528:DC%2BB3MXhvVKrtLnM34158384840850710.1212/WNL.0000000000012410 KoshiyamaDWhite matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individualsMol. Psychiatry2020258838953178077010.1038/s41380-019-0553-7 HowesODKapurSA neurobiological hypothesis for the classification of schizophrenia: type A (hyperdopaminergic) and type B (normodopaminergic)Br. J. Psychiatry2014205132498638410.1192/bjp.bp.113.138578 SteenRGMullCMcClureRHamerRMLiebermanJABrain volume in first-episode schizophrenia: systematic review and meta-analysis of magnetic resonance imaging studiesBr. J. Psychiatry20061885105181673834010.1192/bjp.188.6.510 HoBCAndreasenNCZiebellSPiersonRMagnottaVLong-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophreniaArch. Gen. Psychiatry20116812813721300943347684010.1001/archgenpsychiatry.2010.199 JiangYDuanMHeHYaoDLuoCStructural and functional MRI brain changes in patients with schizophrenia following electroconvulsive therapy: a systematic reviewCurr. Neuropharmacol.202220124112521:CAS:528:DC%2BB38Xis1ymsrzE34370638988682610.2174/1570159X19666210809101248 AlpertKKoganAParrishTMarcusDWangLThe northwestern university neuroimaging data archive (NUNDA)Neuroimage2016124113111362603288810.1016/j.neuroimage.2015.05.060 YangZA deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structureNat. Commun.2021122021NatCo..12.7065Y1:CAS:528:DC%2BB3MXis1Ort7vI34862382864255410.1038/s41467-021-26703-z TanakaSCA multi-site, multi-disorder resting-state magnetic resonance image databaseSci. Data2021834462444840578210.1038/s41597-021-01004-8 WenJMulti-scale semi-supervised clustering of brain images: deriving disease subtypesMed Image Anal.2022753481861110.1016/j.media.2021.102304 IglesiasJEBayesian segmentation of brainstem structures in MRINeuroimage20151131841952577621410.1016/j.neuroimage.2015.02.065 WolfersTMapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative modelsJAMA Psychiatry2018751146115530304337624811010.1001/jamapsychiatry.2018.2467 KaySRFiszbeinAOplerLAThe positive and negative syndrome scale (PANSS) for schizophreniaSchizophr. Bull.1987132612761:STN:280:DyaL2s3ptF2huw%3D%3D361651810.1093/schbul/13.2.261 RollsETHuangC-CLinC-PFengJJoliotMAutomated anatomical labelling atlas 3Neuroimage20202063152182510.1016/j.neuroimage.2019.116189 GollubRLThe MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophreniaNeuroinformatics2013113673882376081710.1007/s12021-013-9184-3 AlnaesDBrain heterogeneity in schizophrenia and its association with polygenic riskJAMA Psychiatry20197673974830969333658366410.1001/jamapsychiatry.2019.0257 BruggerSPHeterogeneity of Striatal Dopamine Function in Schizophrenia: Meta-analysis of VarianceBiol. Psychiatry2020872152241:CAS:528:DC%2BC1MXhvVCkt7jF3156185810.1016/j.biopsych.2019.07.008 JiangYInsular changes induced by electroconvulsive therapy response to symptom improvements in schizophreniaProg. Neuropsychopharmacol. Biol. Psychiatry2019892542623024837910.1016/j.pnpbp.20 L The (50267_CR10) 2018; 391 PK McGuire (50267_CR38) 1993; 342 JE Iglesias (50267_CR72) 2015; 115 PA Lalousis (50267_CR14) 2021; 47 JE Iglesias (50267_CR75) 2015; 113 O Oren (50267_CR11) 2020; 2 JW Vogel (50267_CR20) 2021; 27 SP Brugger (50267_CR8) 2017; 74 OD Howes (50267_CR28) 2023; 48 TJ Crow (50267_CR36) 1997; 28 GB Chand (50267_CR15) 2020; 143 C Luo (50267_CR18) 2021; 26 D Koshiyama (50267_CR27) 2020; 25 RA McCutcheon (50267_CR3) 2020; 19 Y Jiang (50267_CR54) 2022; 20 P Fusar-Poli (50267_CR5) 2016; 73 Y Jiang (50267_CR22) 2023; 1 D Alnaes (50267_CR29) 2019; 76 J Soler-Vidal (50267_CR66) 2022; 17 K Koch (50267_CR50) 2014; 205 A Vita (50267_CR46) 2015; 78 M Slifstein (50267_CR42) 2015; 72 N Banaj (50267_CR51) 2023; 28 RL Gollub (50267_CR61) 2013; 11 T Wolfers (50267_CR4) 2018; 75 M Kirschner (50267_CR32) 2021; 47 J Wang (50267_CR55) 2019; 12 DT Balu (50267_CR44) 2013; 110 RA McCutcheon (50267_CR47) 2020; 77 ZM Saygin (50267_CR73) 2017; 155 SR Kay (50267_CR67) 1987; 13 RG Steen (50267_CR43) 2006; 188 JP Lindenmayer (50267_CR68) 1994; 182 L Collado-Torres (50267_CR7) 2019; 103 SG Fillman (50267_CR35) 2016; 21 G Repovs (50267_CR65) 2012; 6 N Okada (50267_CR26) 2023; 28 RA Poldrack (50267_CR64) 2016; 3 RS Kahn (50267_CR45) 2015; 20 SC Tanaka (50267_CR59) 2021; 8 PM Thompson (50267_CR34) 2009; 19 K Alpert (50267_CR62) 2016; 124 EC Del Re (50267_CR40) 2021; 47 A Vercammen (50267_CR39) 2010; 67 PM Thompson (50267_CR33) 2001; 98 R Pomponio (50267_CR70) 2020; 208 C Pantelis (50267_CR41) 2003; 361 E Mouchlianitis (50267_CR53) 2016; 3 DL Braff (50267_CR9) 2013; 39 Y Jiang (50267_CR31) 2018; 287 A Kogan (50267_CR63) 2016; 124 HW Chase (50267_CR49) 2018; 39 BC Ho (50267_CR57) 2011; 68 P Rajpurkar (50267_CR12) 2022; 28 OD Howes (50267_CR30) 2014; 205 AL Young (50267_CR21) 2021; 97 SP Brugger (50267_CR48) 2020; 87 Y Jiang (50267_CR23) 2024; 15 50267_CR1 GB Chand (50267_CR52) 2022; 179 JE Iglesias (50267_CR74) 2018; 183 50267_CR58 DB Keator (50267_CR60) 2016; 124 RS Desikan (50267_CR71) 2006; 31 TG van Erp (50267_CR25) 2016; 21 J Wen (50267_CR13) 2022; 75 RA McCutcheon (50267_CR6) 2021; 26 DB Dwyer (50267_CR17) 2018; 44 TGM van Erp (50267_CR24) 2018; 84 OD Howes (50267_CR2) 2023; 28 L Palaniyappan (50267_CR37) 2012; 37 AL Young (50267_CR19) 2018; 9 Z Yang (50267_CR16) 2021; 12 ET Rolls (50267_CR69) 2020; 206 Y Jiang (50267_CR56) 2019; 89 |
| References_xml | – reference: WenJMulti-scale semi-supervised clustering of brain images: deriving disease subtypesMed Image Anal.2022753481861110.1016/j.media.2021.102304 – reference: McGuirePKMurrayRShahGIncreased blood flow in Broca’s area during auditory hallucinations in schizophreniaLancet19933427037061:STN:280:DyaK3szot1Wktg%3D%3D810382110.1016/0140-6736(93)91707-S – reference: BruggerSPHowesODHeterogeneity and homogeneity of regional brain structure in schizophrenia: a meta-analysisJAMA Psychiatry2017741104111128973084566945610.1001/jamapsychiatry.2017.2663 – reference: TheLICD-11: a brave attempt at classifying a new worldLancet2018391247610.1016/S0140-6736(18)31370-9 – reference: Organization W. H. The Global Burden Of Disease: 2004 Update. (World Health Organization, 2008). – reference: LalousisPAHeterogeneity and classification of recent onset psychosis and depression: a multimodal machine learning approachSchizophr. Bull.2021471130114033543752826665410.1093/schbul/sbaa185 – reference: Lewandowski K. E., Bouix S., Ongur D., Shenton M. E. Neuroprogression across the Early Course of Psychosis. J Psychiatr Brain Sci 5, e200002 (2020). – reference: KirschnerMOrbitofrontal-striatal structural alterations linked to negative symptoms at different stages of the schizophrenia spectrumSchizophr. Bull.2021478498633325795410.1093/schbul/sbaa169 – reference: RepovsGBarchDMWorking memory related brain network connectivity in individuals with schizophrenia and their siblingsFront Hum. Neurosci.2012613722654746335877210.3389/fnhum.2012.00137 – reference: ChaseHWLoriemiPWensingTEickhoffSBNickl-JockschatTMeta-analytic evidence for altered mesolimbic responses to reward in schizophreniaHum. Brain Mapp.2018392917292829573046686658610.1002/hbm.24049 – reference: WangJECT-induced brain plasticity correlates with positive symptom improvement in schizophrenia by voxel-based morphometry analysis of grey matterBrain Stimul.2019123193281:CAS:528:DC%2BC1MXitFyhtr7O3047347710.1016/j.brs.2018.11.006 – reference: YangZA deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structureNat. Commun.2021122021NatCo..12.7065Y1:CAS:528:DC%2BB3MXis1Ort7vI34862382864255410.1038/s41467-021-26703-z – reference: VitaADe PeriLDesteGBarlatiSSacchettiEThe effect of antipsychotic treatment on cortical gray matter changes in schizophrenia: does the class matter? a meta-analysis and meta-regression of longitudinal magnetic resonance imaging studiesBiol. Psychiatry2015784034121:CAS:528:DC%2BC2MXltFelurs%3D2580208110.1016/j.biopsych.2015.02.008 – reference: Soler-VidalJBrain correlates of speech perception in schizophrenia patients with and without auditory hallucinationsPLOS ONE202217e02769751:CAS:528:DC%2BB38XjtFyis7%2FO36525414975755610.1371/journal.pone.0276975 – reference: PoldrackRAA phenome-wide examination of neural and cognitive functionSci. Data201631:CAS:528:DC%2BC28XitFaiu7%2FF27922632513967210.1038/sdata.2016.110 – reference: AlpertKKoganAParrishTMarcusDWangLThe northwestern university neuroimaging data archive (NUNDA)Neuroimage2016124113111362603288810.1016/j.neuroimage.2015.05.060 – reference: GollubRLThe MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophreniaNeuroinformatics2013113673882376081710.1007/s12021-013-9184-3 – reference: WolfersTMapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative modelsJAMA Psychiatry2018751146115530304337624811010.1001/jamapsychiatry.2018.2467 – reference: JiangYNeuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophreniaNat. Ment. Health2023118619910.1038/s44220-023-00024-0 – reference: DesikanRSAn automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interestNeuroimage2006319689801653043010.1016/j.neuroimage.2006.01.021 – reference: RollsETHuangC-CLinC-PFengJJoliotMAutomated anatomical labelling atlas 3Neuroimage20202063152182510.1016/j.neuroimage.2019.116189 – reference: PomponioRHarmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespanNeuroimage20202083182186910.1016/j.neuroimage.2019.116450 – reference: McCutcheonRAKrystalJHHowesODDopamine and glutamate in schizophrenia: biology, symptoms and treatmentWorld Psychiatry202019153331922684695355110.1002/wps.20693 – reference: RajpurkarPChenEBanerjeeOTopolEJAI in health and medicineNat. Med20222831381:CAS:528:DC%2BB38XhslCntr4%3D3505861910.1038/s41591-021-01614-0 – reference: van ErpTGSubcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortiumMol. Psychiatry2016215852628364110.1038/mp.2015.118 – reference: DwyerDBBrain subtyping enhances the neuroanatomical discrimination of schizophreniaSchizophr. Bull.2018441060106929529270610148110.1093/schbul/sby008 – reference: VercammenAKnegteringHden BoerJALiemburgEJAlemanAAuditory hallucinations in schizophrenia are associated with reduced functional connectivity of the temporo-parietal areaBiol. Psychiatry2010679129182006010310.1016/j.biopsych.2009.11.017 – reference: HowesODKapurSA neurobiological hypothesis for the classification of schizophrenia: type A (hyperdopaminergic) and type B (normodopaminergic)Br. J. Psychiatry2014205132498638410.1192/bjp.bp.113.138578 – reference: ThompsonPMMapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophreniaProc. Natl Acad. Sci. USA20019811650116552001PNAS...9811650T1:CAS:528:DC%2BD3MXnt12jsLo%3D115730025878410.1073/pnas.201243998 – reference: KoganAAlpertKAmbiteJLMarcusDSWangLNorthwestern University schizophrenia data sharing for SchizConnect: A longitudinal dataset for large-scale integrationNeuroimage2016124119612012608737810.1016/j.neuroimage.2015.06.030 – reference: IglesiasJEA computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRINeuroimage20151151171372593680710.1016/j.neuroimage.2015.04.042 – reference: KeatorDBThe function biomedical informatics research network data repositoryNeuroimage2016124107410792636486310.1016/j.neuroimage.2015.09.003 – reference: PantelisCNeuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparisonLancet20033612812881255986110.1016/S0140-6736(03)12323-9 – reference: OkadaNSubcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classificationMol. Psychiatry20232852065216375372811104179710.1038/s41380-023-02141-9 – reference: SteenRGMullCMcClureRHamerRMLiebermanJABrain volume in first-episode schizophrenia: systematic review and meta-analysis of magnetic resonance imaging studiesBr. J. Psychiatry20061885105181673834010.1192/bjp.188.6.510 – reference: ThompsonPMTime-lapse mapping of cortical changes in schizophrenia with different treatmentsCereb. Cortex200919110711231884266810.1093/cercor/bhn152 – reference: KahnRSSommerIEThe neurobiology and treatment of first-episode schizophreniaMol. Psychiatry20152084971:STN:280:DC%2BC2cbks1eqsw%3D%3D2504800510.1038/mp.2014.66 – reference: HoBCAndreasenNCZiebellSPiersonRMagnottaVLong-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophreniaArch. Gen. Psychiatry20116812813721300943347684010.1001/archgenpsychiatry.2010.199 – reference: KaySRFiszbeinAOplerLAThe positive and negative syndrome scale (PANSS) for schizophreniaSchizophr. Bull.1987132612761:STN:280:DyaL2s3ptF2huw%3D%3D361651810.1093/schbul/13.2.261 – reference: CrowTJIs schizophrenia the price that Homo sapiens pays for language?Schizophr. Res1997281271411:STN:280:DyaK1c7islyltA%3D%3D946834810.1016/S0920-9964(97)00110-2 – reference: AlnaesDBrain heterogeneity in schizophrenia and its association with polygenic riskJAMA Psychiatry20197673974830969333658366410.1001/jamapsychiatry.2019.0257 – reference: JiangYInsular changes induced by electroconvulsive therapy response to symptom improvements in schizophreniaProg. Neuropsychopharmacol. Biol. Psychiatry2019892542623024837910.1016/j.pnpbp.2018.09.009 – reference: MouchlianitisEMcCutcheonRHowesODBrain-imaging studies of treatment-resistant schizophrenia: a systematic reviewLancet Psychiatry2016345146326948188579664010.1016/S2215-0366(15)00540-4 – reference: HowesODCummingsCChapmanGEShatalinaENeuroimaging in schizophrenia: an overview of findings and their implications for synaptic changesNeuropsychopharmacology2023481511673605610610.1038/s41386-022-01426-x – reference: KochKFunctional connectivity and grey matter volume of the striatum in schizophreniaBr. J. Psychiatry20142052042132501268310.1192/bjp.bp.113.138099 – reference: Del ReECBaseline cortical thickness reductions in clinical high risk for psychosis: brain regions associated with conversion to psychosis versus non-conversion as assessed at one-year follow-up in the shanghai-at-risk-for-psychosis (SHARP) studySchizophr. Bull.2021475625743292614110.1093/schbul/sbaa127 – reference: SayginZMHigh-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlasNeuroimage20171553703821:STN:280:DC%2BC1crkvVSrug%3D%3D2847947610.1016/j.neuroimage.2017.04.046 – reference: YoungALCharacterizing the clinical features and atrophy patterns of MAPT-related frontotemporal dementia with disease progression modelingNeurology202197e941e9521:CAS:528:DC%2BB3MXhvVKrtLnM34158384840850710.1212/WNL.0000000000012410 – reference: McCutcheonRAThe efficacy and heterogeneity of antipsychotic response in schizophrenia: A meta-analysisMol. Psychiatry202126131013201:CAS:528:DC%2BC1MXhslajsb7M3147157610.1038/s41380-019-0502-5 – reference: HowesODOnwordiECThe synaptic hypothesis of schizophrenia version III: a master mechanismMol. Psychiatry20232818431856370414181057578810.1038/s41380-023-02043-w – reference: BaluDTMultiple risk pathways for schizophrenia converge in serine racemase knockout mice, a mouse model of NMDA receptor hypofunctionProc. Natl Acad. Sci. USA2013110E2400E24092013PNAS..110.2407B1:CAS:528:DC%2BC3sXhtFejs7fK23729812369682510.1073/pnas.1304308110 – reference: IglesiasJEA probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histologyNeuroimage20181833143263012133710.1016/j.neuroimage.2018.08.012 – reference: TanakaSCA multi-site, multi-disorder resting-state magnetic resonance image databaseSci. Data2021834462444840578210.1038/s41597-021-01004-8 – reference: ChandGBSchizophrenia imaging signatures and their associations with cognition, psychopathology, and genetics in the general populationAm. J. Psychiatry202217965066035410495944488610.1176/appi.ajp.21070686 – reference: JiangYDuanMHeHYaoDLuoCStructural and functional MRI brain changes in patients with schizophrenia following electroconvulsive therapy: a systematic reviewCurr. Neuropharmacol.202220124112521:CAS:528:DC%2BB38Xis1ymsrzE34370638988682610.2174/1570159X19666210809101248 – reference: BraffDLRyanJRisslingAJCarpenterWTLack of use in the literature from the last 20 years supports dropping traditional schizophrenia subtypes from DSM-5 and ICD-11Schizophr. Bull.20133975175323674819368646210.1093/schbul/sbt068 – reference: YoungALUncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage InferenceNat. Commun.201892018NatCo...9.4273Y30323170618917610.1038/s41467-018-05892-0 – reference: KoshiyamaDWhite matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individualsMol. Psychiatry2020258838953178077010.1038/s41380-019-0553-7 – reference: BanajNCortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analysesMol. Psychiatry20232843634373376441741082766510.1038/s41380-023-02221-w – reference: van ErpTGMCortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro imaging genetics through meta analysis (ENIGMA) consortiumBiol. Psychiatry20188464465429960671617730410.1016/j.biopsych.2018.04.023 – reference: Fusar-PoliPHeterogeneity of psychosis risk within individuals at clinical high risk: a meta-analytical stratificationJAMA Psychiatry2016731131202671991110.1001/jamapsychiatry.2015.2324 – reference: Collado-TorresLRegional heterogeneity in gene expression, regulation, and coherence in the frontal cortex and hippocampus across development and schizophreniaNeuron2019103203216 e2081:CAS:528:DC%2BB3cXls1Cmur0%3D31174959700020410.1016/j.neuron.2019.05.013 – reference: ChandGBTwo distinct neuroanatomical subtypes of schizophrenia revealed using machine learningBrain20201431027103832103250708966510.1093/brain/awaa025 – reference: JiangYProgressive reduction in gray matter in patients with schizophrenia assessed with mr imaging by using causal network analysisRadiology20182877292966840910.1148/radiol.2018184005 – reference: SlifsteinMDeficits in prefrontal cortical and extrastriatal dopamine release in schizophrenia: a positron emission tomographic functional magnetic resonance imaging studyJAMA Psychiatry20157231632425651194476874210.1001/jamapsychiatry.2014.2414 – reference: LindenmayerJPBernstein-HymanRGrochowskiSFive-factor model of schizophrenia. Initial validationJ. Nerv. Ment. Dis.19941826316381:STN:280:DyaK2M%2Fltl2muw%3D%3D796467110.1097/00005053-199411000-00006 – reference: McCutcheonRAReis MarquesTHowesODSchizophrenia-an overviewJAMA Psychiatry2020772012103166445310.1001/jamapsychiatry.2019.3360 – reference: OrenOGershBJBhattDLArtificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpointsLancet Digit Health20202e486e4883332811610.1016/S2589-7500(20)30160-6 – reference: PalaniyappanLLiddlePFDoes the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunctionJ. Psychiatry Neurosci.201237172721693094324449510.1503/jpn.100176 – reference: JiangYIdentification of four biotypes in temporal lobe epilepsy via machine learning on brain imagesNat. Commun.2024152024NatCo..15.2221J1:CAS:528:DC%2BB2cXntFequ7Y%3D384722521093345010.1038/s41467-024-46629-6 – reference: BruggerSPHeterogeneity of Striatal Dopamine Function in Schizophrenia: Meta-analysis of VarianceBiol. Psychiatry2020872152241:CAS:528:DC%2BC1MXhvVCkt7jF3156185810.1016/j.biopsych.2019.07.008 – reference: IglesiasJEBayesian segmentation of brainstem structures in MRINeuroimage20151131841952577621410.1016/j.neuroimage.2015.02.065 – reference: VogelJWFour distinct trajectories of tau deposition identified in Alzheimer’s diseaseNat. Med2021278718811:CAS:528:DC%2BB3MXhtVSqsbrJ33927414868668810.1038/s41591-021-01309-6 – reference: FillmanSGElevated peripheral cytokines characterize a subgroup of people with schizophrenia displaying poor verbal fluency and reduced Broca’s area volumeMol. Psychiatry201621109010981:CAS:528:DC%2BC2MXht1Wqt7zM2619418310.1038/mp.2015.90 – reference: LuoCSubtypes of schizophrenia identified by multi-omic measures associated with dysregulated immune functionMol. Psychiatry202126692669361:CAS:528:DC%2BB38XjtV2jsr0%3D3458862210.1038/s41380-021-01308-6 – volume: 19 start-page: 1107 year: 2009 ident: 50267_CR34 publication-title: Cereb. Cortex doi: 10.1093/cercor/bhn152 – volume: 21 start-page: 1090 year: 2016 ident: 50267_CR35 publication-title: Mol. Psychiatry doi: 10.1038/mp.2015.90 – volume: 206 year: 2020 ident: 50267_CR69 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2019.116189 – volume: 361 start-page: 281 year: 2003 ident: 50267_CR41 publication-title: Lancet doi: 10.1016/S0140-6736(03)12323-9 – volume: 89 start-page: 254 year: 2019 ident: 50267_CR56 publication-title: Prog. Neuropsychopharmacol. Biol. Psychiatry doi: 10.1016/j.pnpbp.2018.09.009 – volume: 47 start-page: 1130 year: 2021 ident: 50267_CR14 publication-title: Schizophr. Bull. doi: 10.1093/schbul/sbaa185 – volume: 3 start-page: 451 year: 2016 ident: 50267_CR53 publication-title: Lancet Psychiatry doi: 10.1016/S2215-0366(15)00540-4 – ident: 50267_CR1 – volume: 28 start-page: 127 year: 1997 ident: 50267_CR36 publication-title: Schizophr. Res doi: 10.1016/S0920-9964(97)00110-2 – volume: 3 year: 2016 ident: 50267_CR64 publication-title: Sci. Data doi: 10.1038/sdata.2016.110 – volume: 1 start-page: 186 year: 2023 ident: 50267_CR22 publication-title: Nat. Ment. Health doi: 10.1038/s44220-023-00024-0 – volume: 179 start-page: 650 year: 2022 ident: 50267_CR52 publication-title: Am. J. Psychiatry doi: 10.1176/appi.ajp.21070686 – volume: 143 start-page: 1027 year: 2020 ident: 50267_CR15 publication-title: Brain doi: 10.1093/brain/awaa025 – volume: 84 start-page: 644 year: 2018 ident: 50267_CR24 publication-title: Biol. Psychiatry doi: 10.1016/j.biopsych.2018.04.023 – volume: 124 start-page: 1131 year: 2016 ident: 50267_CR62 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.05.060 – volume: 28 start-page: 4363 year: 2023 ident: 50267_CR51 publication-title: Mol. Psychiatry doi: 10.1038/s41380-023-02221-w – volume: 287 start-page: 729 year: 2018 ident: 50267_CR31 publication-title: Radiology doi: 10.1148/radiol.2018184005 – volume: 98 start-page: 11650 year: 2001 ident: 50267_CR33 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.201243998 – volume: 78 start-page: 403 year: 2015 ident: 50267_CR46 publication-title: Biol. Psychiatry doi: 10.1016/j.biopsych.2015.02.008 – volume: 205 start-page: 204 year: 2014 ident: 50267_CR50 publication-title: Br. J. Psychiatry doi: 10.1192/bjp.bp.113.138099 – volume: 12 start-page: 319 year: 2019 ident: 50267_CR55 publication-title: Brain Stimul. doi: 10.1016/j.brs.2018.11.006 – volume: 27 start-page: 871 year: 2021 ident: 50267_CR20 publication-title: Nat. Med doi: 10.1038/s41591-021-01309-6 – volume: 20 start-page: 1241 year: 2022 ident: 50267_CR54 publication-title: Curr. Neuropharmacol. doi: 10.2174/1570159X19666210809101248 – volume: 75 year: 2022 ident: 50267_CR13 publication-title: Med Image Anal. doi: 10.1016/j.media.2021.102304 – volume: 6 start-page: 137 year: 2012 ident: 50267_CR65 publication-title: Front Hum. Neurosci. doi: 10.3389/fnhum.2012.00137 – volume: 37 start-page: 17 year: 2012 ident: 50267_CR37 publication-title: J. Psychiatry Neurosci. doi: 10.1503/jpn.100176 – volume: 17 start-page: e0276975 year: 2022 ident: 50267_CR66 publication-title: PLOS ONE doi: 10.1371/journal.pone.0276975 – volume: 72 start-page: 316 year: 2015 ident: 50267_CR42 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2014.2414 – volume: 188 start-page: 510 year: 2006 ident: 50267_CR43 publication-title: Br. J. Psychiatry doi: 10.1192/bjp.188.6.510 – volume: 28 start-page: 1843 year: 2023 ident: 50267_CR2 publication-title: Mol. Psychiatry doi: 10.1038/s41380-023-02043-w – volume: 9 year: 2018 ident: 50267_CR19 publication-title: Nat. Commun. doi: 10.1038/s41467-018-05892-0 – volume: 13 start-page: 261 year: 1987 ident: 50267_CR67 publication-title: Schizophr. Bull. doi: 10.1093/schbul/13.2.261 – volume: 21 start-page: 585 year: 2016 ident: 50267_CR25 publication-title: Mol. Psychiatry doi: 10.1038/mp.2015.118 – volume: 47 start-page: 849 year: 2021 ident: 50267_CR32 publication-title: Schizophr. Bull. doi: 10.1093/schbul/sbaa169 – volume: 44 start-page: 1060 year: 2018 ident: 50267_CR17 publication-title: Schizophr. Bull. doi: 10.1093/schbul/sby008 – volume: 76 start-page: 739 year: 2019 ident: 50267_CR29 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2019.0257 – volume: 15 year: 2024 ident: 50267_CR23 publication-title: Nat. Commun. doi: 10.1038/s41467-024-46629-6 – volume: 28 start-page: 31 year: 2022 ident: 50267_CR12 publication-title: Nat. Med doi: 10.1038/s41591-021-01614-0 – volume: 26 start-page: 6926 year: 2021 ident: 50267_CR18 publication-title: Mol. Psychiatry doi: 10.1038/s41380-021-01308-6 – volume: 182 start-page: 631 year: 1994 ident: 50267_CR68 publication-title: J. Nerv. Ment. Dis. doi: 10.1097/00005053-199411000-00006 – volume: 183 start-page: 314 year: 2018 ident: 50267_CR74 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2018.08.012 – volume: 20 start-page: 84 year: 2015 ident: 50267_CR45 publication-title: Mol. Psychiatry doi: 10.1038/mp.2014.66 – volume: 28 start-page: 5206 year: 2023 ident: 50267_CR26 publication-title: Mol. Psychiatry doi: 10.1038/s41380-023-02141-9 – volume: 25 start-page: 883 year: 2020 ident: 50267_CR27 publication-title: Mol. Psychiatry doi: 10.1038/s41380-019-0553-7 – volume: 39 start-page: 2917 year: 2018 ident: 50267_CR49 publication-title: Hum. Brain Mapp. doi: 10.1002/hbm.24049 – volume: 208 year: 2020 ident: 50267_CR70 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2019.116450 – volume: 19 start-page: 15 year: 2020 ident: 50267_CR3 publication-title: World Psychiatry doi: 10.1002/wps.20693 – volume: 73 start-page: 113 year: 2016 ident: 50267_CR5 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2015.2324 – volume: 26 start-page: 1310 year: 2021 ident: 50267_CR6 publication-title: Mol. Psychiatry doi: 10.1038/s41380-019-0502-5 – volume: 48 start-page: 151 year: 2023 ident: 50267_CR28 publication-title: Neuropsychopharmacology doi: 10.1038/s41386-022-01426-x – volume: 39 start-page: 751 year: 2013 ident: 50267_CR9 publication-title: Schizophr. Bull. doi: 10.1093/schbul/sbt068 – volume: 12 year: 2021 ident: 50267_CR16 publication-title: Nat. Commun. doi: 10.1038/s41467-021-26703-z – volume: 124 start-page: 1196 year: 2016 ident: 50267_CR63 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.06.030 – volume: 110 start-page: E2400 year: 2013 ident: 50267_CR44 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.1304308110 – volume: 11 start-page: 367 year: 2013 ident: 50267_CR61 publication-title: Neuroinformatics doi: 10.1007/s12021-013-9184-3 – volume: 67 start-page: 912 year: 2010 ident: 50267_CR39 publication-title: Biol. Psychiatry doi: 10.1016/j.biopsych.2009.11.017 – volume: 47 start-page: 562 year: 2021 ident: 50267_CR40 publication-title: Schizophr. Bull. doi: 10.1093/schbul/sbaa127 – volume: 2 start-page: e486 year: 2020 ident: 50267_CR11 publication-title: Lancet Digit Health doi: 10.1016/S2589-7500(20)30160-6 – volume: 75 start-page: 1146 year: 2018 ident: 50267_CR4 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2018.2467 – volume: 342 start-page: 703 year: 1993 ident: 50267_CR38 publication-title: Lancet doi: 10.1016/0140-6736(93)91707-S – volume: 205 start-page: 1 year: 2014 ident: 50267_CR30 publication-title: Br. J. Psychiatry doi: 10.1192/bjp.bp.113.138578 – volume: 87 start-page: 215 year: 2020 ident: 50267_CR48 publication-title: Biol. Psychiatry doi: 10.1016/j.biopsych.2019.07.008 – volume: 68 start-page: 128 year: 2011 ident: 50267_CR57 publication-title: Arch. Gen. Psychiatry doi: 10.1001/archgenpsychiatry.2010.199 – volume: 74 start-page: 1104 year: 2017 ident: 50267_CR8 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2017.2663 – volume: 115 start-page: 117 year: 2015 ident: 50267_CR72 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.04.042 – volume: 97 start-page: e941 year: 2021 ident: 50267_CR21 publication-title: Neurology doi: 10.1212/WNL.0000000000012410 – volume: 155 start-page: 370 year: 2017 ident: 50267_CR73 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2017.04.046 – volume: 391 start-page: 2476 year: 2018 ident: 50267_CR10 publication-title: Lancet doi: 10.1016/S0140-6736(18)31370-9 – volume: 77 start-page: 201 year: 2020 ident: 50267_CR47 publication-title: JAMA Psychiatry doi: 10.1001/jamapsychiatry.2019.3360 – ident: 50267_CR58 – volume: 113 start-page: 184 year: 2015 ident: 50267_CR75 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.02.065 – volume: 8 year: 2021 ident: 50267_CR59 publication-title: Sci. Data doi: 10.1038/s41597-021-01004-8 – volume: 31 start-page: 968 year: 2006 ident: 50267_CR71 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2006.01.021 – volume: 103 start-page: 203 year: 2019 ident: 50267_CR7 publication-title: Neuron doi: 10.1016/j.neuron.2019.05.013 – volume: 124 start-page: 1074 year: 2016 ident: 50267_CR60 publication-title: Neuroimage doi: 10.1016/j.neuroimage.2015.09.003 |
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| Title | Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm |
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