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Schizophrenia: A Narrative Review of Etiopathogenetic, Diagnostic and Treatment Aspects. J Clin Med 2022; 11:jcm11175040. [PMID: 36078967 PMCID: PMC9457502 DOI: 10.3390/jcm11175040] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 11/25/2022] Open
Abstract
Although schizophrenia is currently conceptualized as being characterized as a syndrome that includes a collection of signs and symptoms, there is strong evidence of heterogeneous and complex underpinned etiological, etiopathogenetic, and psychopathological mechanisms, which are still under investigation. Therefore, the present viewpoint review is aimed at providing some insights into the recently investigated schizophrenia research fields in order to discuss the potential future research directions in schizophrenia research. The traditional schizophrenia construct and diagnosis were progressively revised and revisited, based on the recently emerging neurobiological, genetic, and epidemiological research. Moreover, innovative diagnostic and therapeutic approaches are pointed to build a new construct, allowing the development of better clinical and treatment outcomes and characterization for schizophrenic individuals, considering a more patient-centered, personalized, and tailored-based dimensional approach. Further translational studies are needed in order to integrate neurobiological, genetic, and environmental studies into clinical practice and to help clinicians and researchers to understand how to redesign a new schizophrenia construct.
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302
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Abu Bakar N, Wan Ibrahim WN, Che Abdullah CA, Ramlan NF, Shaari K, Shohaimi S, Mediani A, Nasruddin NS, Kim CH, Mohd Faudzi SM. Embryonic Arsenic Exposure Triggers Long-Term Behavioral Impairment with Metabolite Alterations in Zebrafish. TOXICS 2022; 10:493. [PMID: 36136458 PMCID: PMC9502072 DOI: 10.3390/toxics10090493] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/19/2022] [Accepted: 08/21/2022] [Indexed: 05/10/2023]
Abstract
Arsenic trioxide (As2O3) is a ubiquitous heavy metal in the environment. Exposure to this toxin at low concentrations is unremarkable in developing organisms. Nevertheless, understanding the underlying mechanism of its long-term adverse effects remains a challenge. In this study, embryos were initially exposed to As2O3 from gastrulation to hatching under semi-static conditions. Results showed dose-dependent increased mortality, with exposure to 30-40 µM As2O3 significantly reducing tail-coiling and heart rate at early larval stages. Surviving larvae after 30 µM As2O3 exposure showed deficits in motor behavior without impairment of anxiety-like responses at 6 dpf and a slight impairment in color preference behavior at 11 dpf, which was later evident in adulthood. As2O3 also altered locomotor function, with a loss of directional and color preference in adult zebrafish, which correlated with changes in transcriptional regulation of adsl, shank3a, and tsc1b genes. During these processes, As2O3 mainly induced metabolic changes in lipids, particularly arachidonic acid, docosahexaenoic acid, prostaglandin, and sphinganine-1-phosphate in the post-hatching period of zebrafish. Overall, this study provides new insight into the potential mechanism of arsenic toxicity leading to long-term learning impairment in zebrafish and may benefit future risk assessments of other environmental toxins of concern.
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Affiliation(s)
- Noraini Abu Bakar
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Wan Norhamidah Wan Ibrahim
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Che Azurahanim Che Abdullah
- Department of Physics, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
- The Institute of Advanced Technology (ITMA), Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Nurul Farhana Ramlan
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Khozirah Shaari
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Shamarina Shohaimi
- Department of Biology, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
| | - Ahmed Mediani
- Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
| | - Nurrul Shaqinah Nasruddin
- Centre for Craniofacial Diagnostics, Faculty of Dentistry, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur 50300, Malaysia
| | - Cheol-Hee Kim
- Department of Biology, Chungnam National University, Daejeon 34134, Korea
| | - Siti Munirah Mohd Faudzi
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang 43400, Malaysia
- Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, Serdang 43400, Malaysia
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303
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Qi S, Sui J, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, Turner JA, Fu Z, Shao W, Jiang R, Yang X, Liu J, Du Y, Chen J, Zhang D, Calhoun VD. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nat Commun 2022; 13:4929. [PMID: 35995794 PMCID: PMC9395379 DOI: 10.1038/s41467-022-32513-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 08/03/2022] [Indexed: 12/23/2022] Open
Abstract
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.
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Affiliation(s)
- Shile Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
| | - Godfrey Pearlson
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Juan Bustillo
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Nora I Perrone-Bizzozero
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Wei Shao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Xiao Yang
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jingyu Liu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Yuhui Du
- School of Computer & Information Technology, Shanxi University, Taiyuan, China
| | - Jiayu Chen
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA.
| | - Daoqiang Zhang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
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304
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Karcher NR, Merchant J, Pine J, Kilciksiz CM. Cognitive Dysfunction as a Risk Factor for Psychosis. Curr Top Behav Neurosci 2022; 63:173-203. [PMID: 35989398 DOI: 10.1007/7854_2022_387] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The current chapter summarizes recent evidence for cognition as a risk factor for the development of psychosis, including the range of cognitive impairments that exist across the spectrum of psychosis risk symptoms. The chapter examines several possible theories linking cognitive deficits with the development of psychotic symptoms, including evidence that cognitive deficits may be an intermediate risk factor linking genetic and/or neural metrics to psychosis spectrum symptoms. Although there is not strong evidence for unique cognitive markers associated specifically with psychosis compared to other forms of psychopathology, psychotic disorders are generally associated with the greatest severity of cognitive deficits. Cognitive deficits precede the development of psychotic symptoms and may be detectable as early as childhood. Across the psychosis spectrum, both the presence and severity of psychotic symptoms are associated with mild to moderate impairments across cognitive domains, perhaps most consistently for language, cognitive control, and working memory domains. Research generally indicates the size of these cognitive impairments worsens as psychosis symptom severity increases. The chapter points out areas of unclarity and unanswered questions in each of these areas, including regarding the mechanisms contributing to the association between cognition and psychosis, the timing of deficits, and whether any cognitive systems can be identified that function as specific predictors of psychosis risk symptoms.
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Affiliation(s)
- Nicole R Karcher
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
| | - Jaisal Merchant
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Jacob Pine
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Can Misel Kilciksiz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
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305
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Yagyu K, Toyomaki A, Hashimoto N, Shiraishi H, Kusumi I, Murohashi H. Approach to impaired corollary discharge in patients with schizophrenia: An analysis of self-induced somatosensory evoked potentials and fields. Front Psychol 2022; 13:904995. [PMID: 36059767 PMCID: PMC9428598 DOI: 10.3389/fpsyg.2022.904995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 07/25/2022] [Indexed: 11/30/2022] Open
Abstract
Background Difficulty in distinguishing between self-generated actions and those generated by others is a core feature of schizophrenia. This is thought to be underpinned by the failure of corollary discharge. However, few studies have investigated these events using somatosensory evoked potentials (SEPs) and somatosensory evoked magnetic fields (SEFs). Methods The study included 15 right-handed patients with schizophrenia and 16 healthy controls. SEP and SEF were elicited by electrical stimuli to the left median nerve at intervals of 1–3 s. In the external condition, stimuli were externally induced by a machine. In the self-condition, stimuli were induced by tapping the participants’ own right index finger. Peak amplitude at C4’ in SEP and root mean square in 10 channels on the right primary somatosensory area in SEF were analyzed. Results Although there was a significant main effect of condition at N20m, and a significant main effect of condition and group at P30m, no significant interactions of condition and group were found in either N20m or P30m. The post-hoc Wilcoxon signed-rank test revealed that the peak value of P30m in the external condition was significantly higher than that in the self-condition in the healthy control group only. In addition, there was a significant positive correlation between the peak value of P30m in the self-condition and a positive symptom score. Conclusion In the current study, we did not find abnormalities of corollary discharge in primary sensory areas in patients with schizophrenia. Further investigations with more cases may reveal the possibility of corollary discharge disturbance in the primary sensory cortex.
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Affiliation(s)
- Kazuyori Yagyu
- Department of Pediatrics, Hokkaido University Hospital, Sapporo, Hokkaidō, Japan
- Department of Child and Adolescent Psychiatry, Hokkaido University Hospital, Sapporo, Hokkaidō, Japan
| | - Atsuhito Toyomaki
- Department of Psychiatry, Hokkaido University, Graduate School of Medicine, Sapporo, Hokkaidō, Japan
| | - Naoki Hashimoto
- Department of Psychiatry, Hokkaido University, Graduate School of Medicine, Sapporo, Hokkaidō, Japan
- *Correspondence: Naoki Hashimoto,
| | - Hideaki Shiraishi
- Department of Pediatrics, Hokkaido University Hospital, Sapporo, Hokkaidō, Japan
| | - Ichiro Kusumi
- Department of Psychiatry, Hokkaido University, Graduate School of Medicine, Sapporo, Hokkaidō, Japan
| | - Harumitsu Murohashi
- Department of Human Development Sciences, Hokkaido University, Graduate School of Education, Sapporo, Hokkaidō, Japan
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306
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Patel Y, Shin J, Abé C, Agartz I, Alloza C, Alnæs D, Ambrogi S, Antonucci LA, Arango C, Arolt V, Auzias G, Ayesa-Arriola R, Banaj N, Banaschewski T, Bandeira C, Başgöze Z, Cupertino RB, Bau CHD, Bauer J, Baumeister S, Bernardoni F, Bertolino A, Bonnin CDM, Brandeis D, Brem S, Bruggemann J, Bülow R, Bustillo JR, Calderoni S, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carmona S, Carr VJ, Catts SV, Chenji S, Chew QH, Coghill D, Connolly CG, Conzelmann A, Craven AR, Crespo-Facorro B, Cullen K, Dahl A, Dannlowski U, Davey CG, Deruelle C, Díaz-Caneja CM, Dohm K, Ehrlich S, Epstein J, Erwin-Grabner T, Eyler LT, Fedor J, Fitzgerald J, Foran W, Ford JM, Fortea L, Fuentes-Claramonte P, Fullerton J, Furlong L, Gallagher L, Gao B, Gao S, Goikolea JM, Gotlib I, Goya-Maldonado R, Grabe HJ, Green M, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Haavik J, Hahn T, Harrison BJ, Heindel W, Henskens F, Heslenfeld DJ, Hilland E, Hoekstra PJ, Hohmann S, Holz N, Howells FM, Ipser JC, Jahanshad N, Jakobi B, Jansen A, Janssen J, Jonassen R, Kaiser A, Kaleda V, Karantonis J, King JA, Kircher T, Kochunov P, Koopowitz SM, Landén M, Landrø NI, Lawrie S, et alPatel Y, Shin J, Abé C, Agartz I, Alloza C, Alnæs D, Ambrogi S, Antonucci LA, Arango C, Arolt V, Auzias G, Ayesa-Arriola R, Banaj N, Banaschewski T, Bandeira C, Başgöze Z, Cupertino RB, Bau CHD, Bauer J, Baumeister S, Bernardoni F, Bertolino A, Bonnin CDM, Brandeis D, Brem S, Bruggemann J, Bülow R, Bustillo JR, Calderoni S, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carmona S, Carr VJ, Catts SV, Chenji S, Chew QH, Coghill D, Connolly CG, Conzelmann A, Craven AR, Crespo-Facorro B, Cullen K, Dahl A, Dannlowski U, Davey CG, Deruelle C, Díaz-Caneja CM, Dohm K, Ehrlich S, Epstein J, Erwin-Grabner T, Eyler LT, Fedor J, Fitzgerald J, Foran W, Ford JM, Fortea L, Fuentes-Claramonte P, Fullerton J, Furlong L, Gallagher L, Gao B, Gao S, Goikolea JM, Gotlib I, Goya-Maldonado R, Grabe HJ, Green M, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Haavik J, Hahn T, Harrison BJ, Heindel W, Henskens F, Heslenfeld DJ, Hilland E, Hoekstra PJ, Hohmann S, Holz N, Howells FM, Ipser JC, Jahanshad N, Jakobi B, Jansen A, Janssen J, Jonassen R, Kaiser A, Kaleda V, Karantonis J, King JA, Kircher T, Kochunov P, Koopowitz SM, Landén M, Landrø NI, Lawrie S, Lebedeva I, Luna B, Lundervold AJ, MacMaster FP, Maglanoc LA, Mathalon DH, McDonald C, McIntosh A, Meinert S, Michie PT, Mitchell P, Moreno-Alcázar A, Mowry B, Muratori F, Nabulsi L, Nenadić I, O'Gorman Tuura R, Oosterlaan J, Overs B, Pantelis C, Parellada M, Pariente JC, Pauli P, Pergola G, Piarulli FM, Picon F, Piras F, Pomarol-Clotet E, Pretus C, Quidé Y, Radua J, Ramos-Quiroga JA, Rasser PE, Reif A, Retico A, Roberts G, Rossell S, Rovaris DL, Rubia K, Sacchet M, Salavert J, Salvador R, Sarró S, Sawa A, Schall U, Scott R, Selvaggi P, Silk T, Sim K, Skoch A, Spalletta G, Spaniel F, Stein DJ, Steinsträter O, Stolicyn A, Takayanagi Y, Tamm L, Tavares M, Teumer A, Thiel K, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, Tosetti M, Uhlmann A, Van Rheenen T, Vazquez-Bourgón J, Vernooij MW, Vieta E, Vilarroya O, Weickert C, Weickert T, Westlye LT, Whalley H, Willinger D, Winter A, Wittfeld K, Yang TT, Yoncheva Y, Zijlmans JL, Hoogman M, Franke B, van Rooij D, Buitelaar J, Ching CRK, Andreassen OA, Pozzi E, Veltman D, Schmaal L, van Erp TGM, Turner J, Castellanos FX, Pausova Z, Thompson P, Paus T. Virtual Ontogeny of Cortical Growth Preceding Mental Illness. Biol Psychiatry 2022; 92:299-313. [PMID: 35489875 PMCID: PMC11080987 DOI: 10.1016/j.biopsych.2022.02.959] [Show More Authors] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 02/02/2022] [Accepted: 02/23/2022] [Indexed: 02/06/2023]
Abstract
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.
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Affiliation(s)
- Yash Patel
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Jean Shin
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ingrid Agartz
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Dag Alnæs
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Linda A Antonucci
- Departments of Education Science, Psychology, Communication Science, University of Bari Aldo Moro, Bari, Italy
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Volker Arolt
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Guillaume Auzias
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Cibele Bandeira
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Zeynep Başgöze
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | | | - Claiton H D Bau
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Jochen Bauer
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Alessandro Bertolino
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Caterina Del Mar Bonnin
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zürich, Zurich, Switzerland
| | | | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Juan R Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico
| | - Sara Calderoni
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Rosa Calvo
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | | | - Dara M Cannon
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Susanna Carmona
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | | | - Stanley V Catts
- School of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Sneha Chenji
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Qian Hui Chew
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - David Coghill
- Department of Paediatrics, Department of Psychiatry, University of Melbourne, Parkville, Australia; Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Colm G Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee, Florida
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Virgen del Rocio University Hospital, Universidad de Sevilla, Instituto de Biomedicina de Sevilla, CIBERSAM, Sevilla, Spain
| | - Kathryn Cullen
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christopher G Davey
- Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Christine Deruelle
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | | | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Jeffery Epstein
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Tracy Erwin-Grabner
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Jennifer Fedor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacqueline Fitzgerald
- Trinity Institute of Neuroscience, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Judith M Ford
- San Francisco Veterans Affairs Medical Center, San Francisco, California
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | | | | | - Lisa Furlong
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Louise Gallagher
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Bingchen Gao
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jose M Goikolea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Ian Gotlib
- Department of Psychology, Stanford University, Stanford, California
| | - Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | | | - Eugenio H Grevet
- Department of Psychiatry, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nynke A Groenewold
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ben J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Walter Heindel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Frans Henskens
- School of Medicine & Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Dirk J Heslenfeld
- Experimental and Clinical Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva Hilland
- Norwegian Centre for Mental Disorders Research NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pieter J Hoekstra
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Jonathan C Ipser
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Neda Jahanshad
- USC Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Babette Jakobi
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Andreas Jansen
- Core Facility Brain imaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Rune Jonassen
- Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - James Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Tilo Kircher
- Department of Psychiatry, Marburg University, Marburg, Germany
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sheri-Michelle Koopowitz
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Mikael Landén
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | | | - Stephen Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Frank P MacMaster
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Luigi A Maglanoc
- Department for Data Capture and Collections Management, University Center for Information Technology, University of Oslo, Oslo, Norway
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California
| | - Colm McDonald
- Galway Neuroscience Centre, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Patricia T Michie
- School of Psychology, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, New South Wales, Australia
| | | | - Ana Moreno-Alcázar
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Filippo Muratori
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Leila Nabulsi
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | | | - Jaap Oosterlaan
- Clinical Neuropsychology Section, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, Victoria, Australia
| | - Mara Parellada
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Jose C Pariente
- Magnetic Resonance Imaging core facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Paul Pauli
- Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of Würzburg, Würzburg, Germany
| | - Giulio Pergola
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Francesco Maria Piarulli
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Felipe Picon
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | | | - Clara Pretus
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - J Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d'Hebrón, CIBERSAM, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Paul E Rasser
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany
| | | | | | - Susan Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Victoria, Australia
| | - Diego Luiz Rovaris
- Department of Physiology and Biophysics, Instituto de Ciencias Biomédicas Universidade de São Paulo, São Paulo, Brazil
| | - Katya Rubia
- Child & Adolescent Psychiatry, King's College London, London, United Kingdom
| | - Matthew Sacchet
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Josep Salavert
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | | | | | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ulrich Schall
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Rodney Scott
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Pierluigi Selvaggi
- Azienda Ospedaliero-Universitaria Consorziale Policlinico di Bari, Bari, Italy
| | - Tim Silk
- School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Leanne Tamm
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Maria Tavares
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
| | | | - Diana Tordesillas-Gutiérrez
- Department of Radiology, University Hospital Marqués de Valdecilla, Instituto de Investigación Valdecilla, Santander, Spain
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Anne Uhlmann
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany
| | - Tamsyn Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Javier Vazquez-Bourgón
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Eduard Vieta
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | - Oscar Vilarroya
- Department of Psychiatry, Autonomous University of Barcelona, Cerdanyola del Valles, Spain
| | - Cynthia Weickert
- Department of Neuroscience and Physiology, University of New South Wales, Sydney, Australia
| | | | - Lars T Westlye
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Heather Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - David Willinger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital, University of Zürich, Zurich, Switzerland
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases, Site Rostock/Greifswald, Greifswald, Germany
| | - Tony T Yang
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, University of California San Francisco, San Francisco, California
| | | | - Jendé L Zijlmans
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Elena Pozzi
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Dick Veltman
- Department of Psychiatry, Amsterdam UMC, VUMC, Amsterdam, The Netherlands
| | - Lianne Schmaal
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | | | | | - Zdenka Pausova
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Paul Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Tomas Paus
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada; Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montréal, Montreal, Quebec, Canada.
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Levman J, Jennings M, Rouse E, Berger D, Kabaria P, Nangaku M, Gondra I, Takahashi E. A morphological study of schizophrenia with magnetic resonance imaging, advanced analytics, and machine learning. Front Neurosci 2022; 16:926426. [PMID: 36046472 PMCID: PMC9420897 DOI: 10.3389/fnins.2022.926426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 07/05/2022] [Indexed: 11/16/2022] Open
Abstract
We have performed a morphological analysis of patients with schizophrenia and compared them with healthy controls. Our analysis includes the use of publicly available automated extraction tools to assess regional cortical thickness (inclusive of within region cortical thickness variability) from structural magnetic resonance imaging (MRI), to characterize group-wise abnormalities associated with schizophrenia based on a publicly available dataset. We have also performed a correlation analysis between the automatically extracted biomarkers and a variety of patient clinical variables available. Finally, we also present the results of a machine learning analysis. Results demonstrate regional cortical thickness abnormalities in schizophrenia. We observed a correlation (rho = 0.474) between patients' depression and the average cortical thickness of the right medial orbitofrontal cortex. Our leading machine learning technology evaluated was the support vector machine with stepwise feature selection, yielding a sensitivity of 92% and a specificity of 74%, based on regional brain measurements, including from the insula, superior frontal, caudate, calcarine sulcus, gyrus rectus, and rostral middle frontal regions. These results imply that advanced analytic techniques combining MRI with automated biomarker extraction can be helpful in characterizing patients with schizophrenia.
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Affiliation(s)
- Jacob Levman
- Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
- Center for Clinical Research, Nova Scotia Health Authority - Research, Innovation and Discovery, Halifax, NS, Canada
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts Institute of Technology, Boston, MA, United States
| | - Maxwell Jennings
- Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
- Department of Mathematics and Statistics, St. Francis Xavier University, Antigonish, NS, Canada
| | - Ethan Rouse
- Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - Derek Berger
- Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - Priya Kabaria
- Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Masahito Nangaku
- Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Iker Gondra
- Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - Emi Takahashi
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts Institute of Technology, Boston, MA, United States
- Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
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308
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van der Meer D, Shadrin AA, O'Connell K, Bettella F, Djurovic S, Wolfers T, Alnæs D, Agartz I, Smeland OB, Melle I, Sánchez JM, Linden DEJ, Dale AM, Westlye LT, Andreassen OA, Frei O, Kaufmann T. Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology. Biol Psychiatry 2022; 92:291-298. [PMID: 35164939 PMCID: PMC12012303 DOI: 10.1016/j.biopsych.2021.12.007] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/06/2021] [Accepted: 12/09/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. METHODS We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. RESULTS We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. CONCLUSIONS Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue-specific genetic variants and its use in polygenic risk frameworks.
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Affiliation(s)
- Dennis van der Meer
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.
| | - Alexey A Shadrin
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kevin O'Connell
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Francesco Bettella
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway; Norwegian Centre for Mental Disorders Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Thomas Wolfers
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olav B Smeland
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jennifer Monereo Sánchez
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - David E J Linden
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, California
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
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Klaus F, Nguyen TT, Thomas ML, Liou SC, Soontornniyomkij B, Mitchell K, Daly R, Sutherland AN, Jeste DV, Eyler LT. Peripheral inflammation levels associated with degree of advanced brain aging in schizophrenia. Front Psychiatry 2022; 13:966439. [PMID: 36032250 PMCID: PMC9412908 DOI: 10.3389/fpsyt.2022.966439] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 07/26/2022] [Indexed: 11/23/2022] Open
Abstract
Brain structural abnormalities have been demonstrated in schizophrenia (SZ); these resemble those seen in typical aging, but are seen at younger ages. Furthermore, SZ is associated with accelerated global brain aging, as measured by brain structure-based brain predicted age difference (Brain-PAD). High heterogeneity exists in the degree of brain abnormalities in SZ, and individual differences may be related to levels of peripheral inflammation and may relate to cognitive deficits and negative symptoms. The goal of our study was to investigate the relationship between brain aging, peripheral inflammation, and symptoms of SZ. We hypothesized older brain-PAD in SZ vs. healthy comparison (HC) participants, as well as positive relationships of brain-PAD with peripheral inflammation markers and symptoms in SZ. We analyzed data from two cross-sectional studies in SZ (n = 26; M/F: 21/5) and HC (n = 28; 20/8) (22-64 years). Brain-PAD was calculated using a previously validated Gaussian process regression model applied to raw T1-weighted MRI data. Plasma levels of inflammatory biomarkers (CRP, Eotaxin, Fractalkine, IP10, IL6, IL10, ICAM1, IFNγ, MCP1, MIP1β, SAA, TNFα, VEGF, VCAM1) and cognitive and negative symptoms were assessed. We observed a higher brain-PAD in SZ vs. HC, and advanced brain age relative to chronological age was related to higher peripheral levels of TNFα in the overall group and in the SZ group; other inflammatory markers were not related to brain-PAD. Within the SZ group, we observed no association between cognitive or negative symptoms and brain-PAD. These results support our hypothesis of advanced brain aging in SZ. Furthermore, our findings on the relationship of the pro-inflammatory cytokine TNFα with higher brain-PAD of SZ are relevant to explain heterogeneity of brain ages in SZ, but we did not find strong evidence for cognitive or negative symptom relationships with brain-PAD.
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Affiliation(s)
- Federica Klaus
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, La Jolla, CA, United States
| | - Tanya T. Nguyen
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, La Jolla, CA, United States
| | - Michael L. Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, United States
| | - Sharon C. Liou
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
| | | | - Kyle Mitchell
- VA San Diego Healthcare System, La Jolla, CA, United States
| | - Rebecca Daly
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
| | - Ashley N. Sutherland
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, La Jolla, CA, United States
| | - Dilip V. Jeste
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- Sam and Rose Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA, United States
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Lisa T. Eyler
- Department of Psychiatry, UC San Diego, La Jolla, CA, United States
- VA San Diego Healthcare System, La Jolla, CA, United States
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310
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Hansen JY, Shafiei G, Vogel JW, Smart K, Bearden CE, Hoogman M, Franke B, van Rooij D, Buitelaar J, McDonald CR, Sisodiya SM, Schmaal L, Veltman DJ, van den Heuvel OA, Stein DJ, van Erp TGM, Ching CRK, Andreassen OA, Hajek T, Opel N, Modinos G, Aleman A, van der Werf Y, Jahanshad N, Thomopoulos SI, Thompson PM, Carson RE, Dagher A, Misic B. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities. Nat Commun 2022; 13:4682. [PMID: 35948562 PMCID: PMC9365855 DOI: 10.1038/s41467-022-32420-y] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 07/28/2022] [Indexed: 12/21/2022] Open
Abstract
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
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Affiliation(s)
- Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Jacob W Vogel
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kelly Smart
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Martine Hoogman
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Psychiatry and Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Daan van Rooij
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Carrie R McDonald
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Odile A van den Heuvel
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, & Center for the Neurobiology of Leaning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, USA
| | - Christopher R K Ching
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Nils Opel
- Institute of Translational Psychiatry, University of Münster, Münster, Germany & Department of Psychiatry, Jena University Hospital/Friedrich-Schiller-University Jena, Jena, Germany
| | - Gemma Modinos
- Department of Psychosis Studies & MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, University of Groningen, Groningen, The Netherlands
| | - Ysbrand van der Werf
- Department of Anatomy & Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Neda Jahanshad
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Sophia I Thomopoulos
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Keck School of Medicine, Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC, Canada.
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311
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Boudriot E, Schworm B, Slapakova L, Hanken K, Jäger I, Stephan M, Gabriel V, Ioannou G, Melcher J, Hasanaj G, Campana M, Moussiopoulou J, Löhrs L, Hasan A, Falkai P, Pogarell O, Priglinger S, Keeser D, Kern C, Wagner E, Raabe FJ. Optical coherence tomography reveals retinal thinning in schizophrenia spectrum disorders. Eur Arch Psychiatry Clin Neurosci 2022; 273:575-588. [PMID: 35930031 PMCID: PMC10085905 DOI: 10.1007/s00406-022-01455-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/20/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Schizophrenia spectrum disorders (SSDs) are presumed to be associated with retinal thinning. However, evidence is lacking as to whether these retinal alterations reflect a disease-specific process or are rather a consequence of comorbid diseases or concomitant microvascular impairment. METHODS The study included 126 eyes of 65 patients with SSDs and 143 eyes of 72 healthy controls. We examined macula and optic disc measures by optical coherence tomography (OCT) and OCT angiography (OCT-A). Additive mixed models were used to assess the impact of SSDs on retinal thickness and perfusion and to explore the association of retinal and clinical disease-related parameters by controlling for several ocular and systemic covariates (age, sex, spherical equivalent, intraocular pressure, body mass index, diabetes, hypertension, smoking status, and OCT signal strength). RESULTS OCT revealed significantly lower parafoveal macular, macular ganglion cell-inner plexiform layer (GCIPL), and macular retinal nerve fiber layer (RNFL) thickness and thinner mean and superior peripapillary RNFL in SSDs. In contrast, the applied OCT-A investigations, which included macular and peripapillary perfusion density, macular vessel density, and size of the foveal avascular zone, did not reveal any significant between-group differences. Finally, a longer duration of illness and higher chlorpromazine equivalent doses were associated with lower parafoveal macular and macular RNFL thickness. CONCLUSIONS This study strengthens the evidence for disease-related retinal thinning in SSDs.
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Affiliation(s)
- Emanuel Boudriot
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Benedikt Schworm
- Department of Ophthalmology, University Hospital, LMU Munich, 80336, Munich, Germany
| | - Lenka Slapakova
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany.,International Max Planck Research School for Translational Psychiatry (IMPRS-TP), 80804, Munich, Germany
| | - Katharina Hanken
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Iris Jäger
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Marius Stephan
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany.,International Max Planck Research School for Translational Psychiatry (IMPRS-TP), 80804, Munich, Germany
| | - Vanessa Gabriel
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Georgios Ioannou
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Julian Melcher
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Genc Hasanaj
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Mattia Campana
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Joanna Moussiopoulou
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Lisa Löhrs
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Alkomiet Hasan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, University of Augsburg, 86156, Augsburg, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany.,Max Planck Institute of Psychiatry, 80804, Munich, Germany
| | - Oliver Pogarell
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Siegfried Priglinger
- Department of Ophthalmology, University Hospital, LMU Munich, 80336, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany.,NeuroImaging Core Unit Munich (NICUM), University Hospital, LMU Munich, 80336, Munich, Germany.,Munich Center for Neurosciences (MCN), LMU Munich, 82152, Planegg-Martinsried, Germany
| | - Christoph Kern
- Department of Ophthalmology, University Hospital, LMU Munich, 80336, Munich, Germany
| | - Elias Wagner
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany
| | - Florian J Raabe
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nußbaumstraße 7, 80336, Munich, Germany. .,International Max Planck Research School for Translational Psychiatry (IMPRS-TP), 80804, Munich, Germany.
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312
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Xie Y, Ding H, Du X, Chai C, Wei X, Sun J, Zhuo C, Wang L, Li J, Tian H, Liang M, Zhang S, Yu C, Qin W. Morphometric Integrated Classification Index: A Multisite Model-Based, Interpretable, Shareable and Evolvable Biomarker for Schizophrenia. Schizophr Bull 2022; 48:1217-1227. [PMID: 35925032 PMCID: PMC9673259 DOI: 10.1093/schbul/sbac096] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Multisite massive schizophrenia neuroimaging data sharing is becoming critical in understanding the pathophysiological mechanism and making an objective diagnosis of schizophrenia; it remains challenging to obtain a generalizable and interpretable, shareable, and evolvable neuroimaging biomarker for schizophrenia diagnosis. STUDY DESIGN A Morphometric Integrated Classification Index (MICI) was proposed as a potential biomarker for schizophrenia diagnosis based on structural magnetic resonance imaging data of 1270 subjects from 10 sites (588 schizophrenia patients and 682 normal controls). An optimal XGBoost classifier plus sample-weighted SHapley Additive explanation algorithms were used to construct the MICI measure. STUDY RESULTS The MICI measure achieved comparable performance with the sample-weighted ensembling model and merged model based on raw data (Delong test, P > 0.82) while outperformed the single-site models (Delong test, P < 0.05) in either the independent-sample testing datasets from the 9 sites or the independent-site dataset (generalizable). Besides, when new sites were embedded in, the performance of this measure was gradually increasing (evolvable). Finally, MICI was strongly associated with the severity of schizophrenia brain structural abnormality, with the patients' positive and negative symptoms, and with the brain expression profiles of schizophrenia risk genes (interpretable). CONCLUSIONS In summary, the proposed MICI biomarker may provide a simple and explainable way to support clinicians for objectively diagnosing schizophrenia. Finally, we developed an online model share platform to promote biomarker generalization and provide free individual prediction services (http://micc.tmu.edu.cn/mici/index.html).
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Affiliation(s)
- Yingying Xie
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Xiaotong Du
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chao Chai
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaotong Wei
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jie Sun
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chuanjun Zhuo
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Lina Wang
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | - Jie Li
- Department of Psychiatry Functional Neuroimaging Laboratory, Tianjin Mental Health Center, Tianjin Anding Hospital, Tianjin, China
| | | | - Meng Liang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | | | | | - Wen Qin
- To whom correspondence should be addressed; Department of Radiology, and Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital. Anshan Road No 154, Heping District, Tianjin 300052, China.
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313
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Luckhoff HK, Asmal L, Scheffler F, Phahladira L, Smit R, van den Heuvel L, Fouche JP, Seedat S, Emsley R, du Plessis S. Associations between BMI and brain structures involved in food intake regulation in first-episode schizophrenia spectrum disorders and healthy controls. J Psychiatr Res 2022; 152:250-259. [PMID: 35753245 DOI: 10.1016/j.jpsychires.2022.06.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/04/2022] [Accepted: 06/10/2022] [Indexed: 11/28/2022]
Abstract
Structural brain differences have been described in first-episode schizophrenia spectrum disorders (FES), and often overlap with those evident in the metabolic syndrome (MetS). We examined the associations between body mass index (BMI) and brain structures involved in food intake regulation in minimally treated FES patients (n = 117) compared to healthy controls (n = 117). The effects of FES diagnosis, BMI and their interactions on our selected prefrontal cortical thickness and subcortical gray matter volume regions of interest (ROIs) were investigated with hierarchical multivariate regressions, followed by post-hoc regressions for the individual ROIs. In a secondary analysis, we examined the relationships of other MetS risk factors and psychopathology with the brain ROIs. Both illness and BMI significantly predicted the grouped prefrontal cortical thickness ROIs, whereas only BMI predicted the grouped subcortical volume ROIs. For the individual ROIs, schizophrenia diagnosis predicted thinner left and right frontal pole and right lateral OFC thickness, and increased BMI predicted thinner left and right caudal ACC thickness. There were no significant main or interaction effects for diagnosis and BMI on any of the individual subcortical volume ROIs. Secondary analyses suggest associations between several brain ROIs and individual MetS risk factors, but not with psychopathology. Our findings indicate differential, independent effects for FES diagnosis and BMI on brain structures. Limited evidence suggests that the BMI effects are more prominent in FES. Exploratory analyses suggest associations between other MetS risk factors and some brain ROIs.
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Affiliation(s)
- H K Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa.
| | - L Asmal
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - F Scheffler
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - L Phahladira
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - R Smit
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - L van den Heuvel
- South African Medical Research Council, Stellenbosch University Genomics of Brain Disorders Research Unit, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - J P Fouche
- South African Medical Research Council, Stellenbosch University Genomics of Brain Disorders Research Unit, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - S Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - R Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
| | - S du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, 7550, South Africa
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314
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Kuo SS, Roalf DR, Prasad KM, Musket CW, Rupert PE, Wood J, Gur RC, Almasy L, Gur RE, Nimgaonkar VL, Pogue-Geile MF. Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2022; 131:674-688. [PMID: 35737559 PMCID: PMC9339500 DOI: 10.1037/abn0000765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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315
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Yin Y, Tong J, Huang J, Tian B, Chen S, Tan S, Wang Z, Yang F, Tong Y, Fan F, Kochunov P, Jahanshad N, Li CSR, Hong LE, Tan Y. History of suicide attempts associated with the thinning right superior temporal gyrus among individuals with schizophrenia. Brain Imaging Behav 2022; 16:1893-1901. [PMID: 35545740 PMCID: PMC10025969 DOI: 10.1007/s11682-021-00624-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2021] [Indexed: 11/02/2022]
Abstract
Individuals with schizophrenia have higher rates of suicide attempts than the general population. Specific cortical abnormalities (e.g., the cortical surface area and thickness) may be associated with a history of suicide attempts. We recruited 74 individuals with schizophrenia (37 suicide attempters were individually matched with 37 non-attempters on age, sex, phase of illness, and study center) and 37 healthy volunteers. The cortical surface area and thickness data were extracted from structural MRI and compared between the groups. Suicide attempters showed significantly smaller surface areas in the whole brain (p = .028, Cohen's d = -0.54) than non-attempters. No association was found between the cortical surface area of individual brain regions and a history of suicide attempts. The mean cortical thickness did not differ significantly between the groups; however, suicide attempters demonstrated a thinner cortex in the right superior temporal gyrus (p < .001, q = 0.037, Cohen's d = -0.88). These findings indicate that a history of suicide attempts among individuals with schizophrenia is associated with a reduction in the global cortical surface area and specific cortical thinning of the right superior temporal gyrus. The morphometric alteration of the right superior temporal gyrus may represent a biomarker of suicidal behavior in individuals with schizophrenia.
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Affiliation(s)
- Yi Yin
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Yongsheng Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
- Beijing Suicide Research and Prevention Center, WHO Collaborating Center for Research and Training in Suicide Prevention, Beijing, China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Neda Jahanshad
- Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China.
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316
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Cheung JP, Tubbs JD, Sham PC. Extended gene set analysis of human neuro-psychiatric traits shows enrichment in brain-expressed human accelerated regions across development. Schizophr Res 2022; 246:148-155. [PMID: 35779326 DOI: 10.1016/j.schres.2022.06.023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 04/25/2022] [Accepted: 06/20/2022] [Indexed: 11/18/2022]
Abstract
Human neuropsychiatric disorders are associated with genetic and environmental factors affecting the brain, which has been subjected to strong evolutionary pressures resulting in an enlarged cerebral cortex and improved cognitive performance. Thus, genes involved in human brain evolution may also play a role in neuropsychiatric disorders. We test whether genes associated with 7 neuropsychiatric phenotypes are enriched in genomic regions that have experienced rapid changes in human evolution (HARs) and importantly, whether HAR status interacts with developmental brain expression to predict associated genes. We used the most recent publicly available GWAS and gene expression data to test for enrichment of HARs, brain expression, and their interaction. These revealed significant interactions between HAR status and whole-brain expression across developmental stages, indicating that the relationship between brain expression and association with schizophrenia and intelligence is stronger among HAR than non-HAR genes. Follow-up regional analyses indicated that predicted HAR-expression interaction effects may vary substantially across regions and developmental stages. Although depression indicated significant enrichment of HAR genes, little support was found for HAR enrichment among bipolar, autism, ADHD, or Alzheimer's associated genes. Our results indicate that intelligence, schizophrenia, and depression-associated genes are enriched for those involved in the evolution of the human brain. These findings highlight promising candidates for follow-up study and considerations for novel drug development, but also caution careful assessment of the translational ability of animal models for studying neuropsychiatric traits in the context of HARs, and the importance of using humanized animal models or human-derived tissues when researching these traits.
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Affiliation(s)
- Justin P Cheung
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China
| | - Justin D Tubbs
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China.
| | - Pak C Sham
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong, China.
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317
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Yue W, Huang H, Duan J. Potential diagnostic biomarkers for schizophrenia. MEDICAL REVIEW (BERLIN, GERMANY) 2022; 2:385-416. [PMID: 37724326 PMCID: PMC10388817 DOI: 10.1515/mr-2022-0009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/20/2022] [Indexed: 09/20/2023]
Abstract
Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University Health System, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
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318
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Andreou D, Jørgensen KN, Nerland S, Ueland T, Vaskinn A, Haukvik UK, Yolken RH, Andreassen OA, Agartz I. Herpes simplex virus 1 infection on grey matter and general intelligence in severe mental illness. Transl Psychiatry 2022; 12:276. [PMID: 35821107 PMCID: PMC9276804 DOI: 10.1038/s41398-022-02044-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 06/22/2022] [Accepted: 06/29/2022] [Indexed: 11/09/2022] Open
Abstract
Schizophrenia and bipolar disorder are severe mental illnesses (SMI) linked to both genetic and environmental factors. Herpes simplex virus 1 (HSV1) is a common neurotropic pathogen which after the primary infection establishes latency with periodic reactivations. We hypothesized that the latent HSV1 infection is associated with brain structural abnormalities and cognitive impairment, especially in SMI. We included 420 adult patients with SMI (schizophrenia or bipolar spectrum) and 481 healthy controls. Circulating HSV1 immunoglobulin G concentrations were measured with immunoassays. We measured the total grey matter volume (TGMV), cortical, subcortical, cerebellar and regional cortical volumes based on T1-weighted MRI scans processed in FreeSurfer v6.0.0. Intelligence quotient (IQ) was assessed with the Wechsler Abbreviated Scale of Intelligence. Seropositive patients had significantly smaller TGMV than seronegative patients (642 cm3 and 654 cm3, respectively; p = 0.019) and lower IQ (104 and 107, respectively; p = 0.018). No TGMV or IQ differences were found between seropositive and seronegative healthy controls. Post-hoc analysis showed that (a) in both schizophrenia and bipolar spectrum, seropositive patients had similarly smaller TGMV than seronegative patients, whereas the HSV1-IQ association was driven by the schizophrenia spectrum group, and (b) among all patients, seropositivity was associated with smaller total cortical (p = 0.016), but not subcortical or cerebellar grey matter volumes, and with smaller left caudal middle frontal, precentral, lingual, middle temporal and banks of superior temporal sulcus regional cortical grey matter volumes. The results of this cross-sectional study indicate that HSV1 may be an environmental factor associated with brain structural abnormalities and cognitive impairment in SMI.
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Affiliation(s)
- Dimitrios Andreou
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway. .,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway. .,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden.
| | - Kjetil Nordbø Jørgensen
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Stener Nerland
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Torill Ueland
- grid.55325.340000 0004 0389 8485Psychosis Research Section, Oslo University Hospital, Oslo, Norway ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Anja Vaskinn
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Unn K. Haukvik
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway ,grid.55325.340000 0004 0389 8485Centre for Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Robert H. Yolken
- grid.21107.350000 0001 2171 9311Stanley Division of Developmental Neurovirology, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD USA
| | - Ole A. Andreassen
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- grid.5510.10000 0004 1936 8921Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.413684.c0000 0004 0512 8628Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway ,grid.425979.40000 0001 2326 2191Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
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319
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Almodóvar-Payá C, Guardiola-Ripoll M, Giralt-López M, Gallego C, Salgado-Pineda P, Miret S, Salvador R, Muñoz MJ, Lázaro L, Guerrero-Pedraza A, Parellada M, Carrión MI, Cuesta MJ, Maristany T, Sarró S, Fañanás L, Callado LF, Arias B, Pomarol-Clotet E, Fatjó-Vilas M. NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches. Int J Mol Sci 2022; 23:ijms23137456. [PMID: 35806464 PMCID: PMC9267632 DOI: 10.3390/ijms23137456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022] Open
Abstract
Included in the neurotrophins family, the Neuritin 1 gene (NRN1) has emerged as an attractive candidate gene for schizophrenia (SZ) since it has been associated with the risk for the disorder and general cognitive performance. In this work, we aimed to further investigate the association of NRN1 with SZ by exploring its role on age at onset and its brain activity correlates. First, we developed two genetic association analyses using a family-based sample (80 early-onset (EO) trios (offspring onset ≤ 18 years) and 71 adult-onset (AO) trios) and an independent case–control sample (120 healthy subjects (HS), 87 EO and 138 AO patients). Second, we explored the effect of NRN1 on brain activity during a working memory task (N-back task; 39 HS, 39 EO and 39 AO; matched by age, sex and estimated IQ). Different haplotypes encompassing the same three Single Nucleotide Polymorphisms(SNPs, rs3763180–rs10484320–rs4960155) were associated with EO in the two samples (GCT, TCC and GTT). Besides, the GTT haplotype was associated with worse N-back task performance in EO and was linked to an inefficient dorsolateral prefrontal cortex activity in subjects with EO compared to HS. Our results show convergent evidence on the NRN1 association with EO both from genetic and neuroimaging approaches, highlighting the role of neurotrophins in the pathophysiology of SZ.
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Affiliation(s)
- Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Giralt-López
- Departament de Psiquiatria, Hospital Universitari Germans Trias i Pujol (HUGTP), 08916 Badalona, Barcelona, Spain;
- Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain
| | - Carme Gallego
- Department of Cell Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), 08028 Barcelona, Barcelona, Spain;
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Salvador Miret
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Centre de Salut Mental d’Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida, 25198 Lleida, Lleida, Spain
- Institut de Recerca Biomèdica (IRB), 25198 Lleida, Lleida, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - María J. Muñoz
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Luisa Lázaro
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, 08036 Barcelona, Barcelona, Spain
- Departament de Medicina, Universitat de Barcelona (UB), 08036 Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Barcelona, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Mara Parellada
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Servicio de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM), 28007 Madrid, Madrid, Spain
- Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense, 28040 Madrid, Madrid, Spain
| | | | - Manuel J. Cuesta
- Servicio de Psiquiatría, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain;
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), 31008 Pamplona, Navarra, Spain
| | - Teresa Maristany
- Departament de Diagnòstic per la Imatge, Hospital Sant Joan de Déu Fundació de Recerca, 08950 Esplugues de Llobregat, Barcelona, Spain;
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Lourdes Fañanás
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Luis F. Callado
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Pharmacology, University of the Basque Country, UPV/EHU, 48940 Leioa, Bizkaia, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain
| | - Bárbara Arias
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Correspondence: (E.P.-C.); (M.F.-V.)
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Correspondence: (E.P.-C.); (M.F.-V.)
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320
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Raucher-Chéné D, Lavigne KM, Makowski C, Lepage M. Altered Surface Area Covariance in the Mentalizing Network in Schizophrenia: Insight Into Theory of Mind Processing. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:706-715. [PMID: 32919946 DOI: 10.1016/j.bpsc.2020.06.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Theory of mind (ToM), the cognitive capacity to attribute mental states to self and others, is robustly affected in schizophrenia. The neural substrates of ToM impairment have been largely studied with functional imaging, but little is known about structural abnormalities. We compared structural covariance (between-subjects correlations of brain regional measures) of magnetic resonance imaging-based cortical surface area between patients with schizophrenia and healthy control subjects and between schizophrenia subgroups based on the patients' ToM ability to examine ToM-specific effects on structural covariance in schizophrenia. METHODS T1-weighted structural images were acquired on a 3T magnetic resonance imaging scanner, and ToM was assessed with the Hinting Task for 104 patients with schizophrenia and 69 healthy control subjects. The sum of surface area was computed for 12 regions of interest selected and compared between groups to examine structural covariance within the often reported mentalizing network: rostral and caudal middle frontal gyrus, inferior parietal lobule, precuneus, and middle and superior temporal gyrus. High and low ToM groups were defined using a median split on the Hinting Task. RESULTS Cortical surface contraction was observed in the schizophrenia group, predominantly in temporoparietal regions. Patients with schizophrenia also exhibited significantly stronger covariance between the right rostral middle frontal gyrus and the right superior temporal gyrus than control subjects (r = 4.015; p < .001). Direct comparisons between high and low ToM subgroups revealed stronger contralateral frontotemporal covariances in the low ToM group. CONCLUSIONS Our results provide evidence for structural changes underlying ToM impairments in schizophrenia that need to be confirmed to develop new therapeutic perspectives.
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Affiliation(s)
- Delphine Raucher-Chéné
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Cognition, Health, and Society Laboratory EA 6291, University of Reims Champagne-Ardenne, Reims, France; Academic Department of Psychiatry, University Hospital of Reims, Etablissement Public de Santé Mentale de la Marne, Reims, France
| | - Katie M Lavigne
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Carolina Makowski
- Center for Multimodal Imaging and Genetics, University of California, San Diego School of Medicine, La Jolla, California; Department of Radiology, University of California, San Diego School of Medicine, La Jolla, California
| | - Martin Lepage
- Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
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321
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Su W, Zhao Z, Li G, Tang X, Xu L, Tang Y, Wei Y, Cui H, Zhang T, Zhang J, Liu X, Guo Q, Wang J. Thalamo-hippocampal dysconnectivity is associated with serum cholesterol level in drug-naïve patients with first-episode schizophrenia. J Psychiatr Res 2022; 151:497-506. [PMID: 35623125 DOI: 10.1016/j.jpsychires.2022.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Revised: 03/25/2022] [Accepted: 05/09/2022] [Indexed: 11/30/2022]
Abstract
Hippocampal deficits and metabolic dysregulations such as dyslipidemia have been frequently reported in schizophrenia and are suggested to contribute to the pathophysiology of schizophrenia. Hippocampus is particularly susceptible to environmental challenges including metabolism and inflammation. However, evidence linking hippocampal alterations and metabolic dysregulations are quite sparse in drug-naïve schizophrenia. A total of 166 drug-naïve patients with first-episode schizophrenia (FES) and 78 healthy controls (HC) underwent measures for several serum metabolic markers, structural and resting-state functional magnetic resonance imaging (rs-fMRI), as well as diffusion tensor imaging (DTI). Seed-to-voxel functional connectivity (FC) and probabilistic tractography were performed to assess the functional and microstructural connectivity of the bilateral hippocampi. Clinical symptoms were evaluated with Positive and Negative Syndrome Scale (PANSS). Patients with FES showed significantly decreased total cholesterol (Chol) level. Patients showed elevated FC between the left hippocampus and bilateral thalami while showing decreased microstructural connectivity between the left hippocampus and bilateral thalami. Multiple regression analyses showed that FC from the left hippocampus to the right superior frontal gyrus (SFG), bilateral frontal pole (FP), and right thalamus were negatively associated with the Chol level, while no association was observed in the HC group. Our study validated alterations in both functional and microstructural thalamo-hippocampal connectivities, and abnormal cholesterol level in FES. Moreover, decreased cholesterol level is associated with elevated thalamo-hippocampal functional connectivity in patients with FES, suggesting that dyslipidemia may interact with the hippocampal dysfunction in FES.
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Affiliation(s)
- Wenjun Su
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Zexin Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Guanjun Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xiaochen Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Lihua Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Yingying Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Yanyan Wei
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Huiru Cui
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China
| | - Xiaohua Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
| | - Qian Guo
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; Department of Early Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China; CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, 200031, China; Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, 200240, China.
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322
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Onitsuka T, Hirano Y, Nakazawa T, Ichihashi K, Miura K, Inada K, Mitoma R, Yasui-Furukori N, Hashimoto R. Toward recovery in schizophrenia: Current concepts, findings, and future research directions. Psychiatry Clin Neurosci 2022; 76:282-291. [PMID: 35235256 DOI: 10.1111/pcn.13342] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 02/17/2022] [Accepted: 02/25/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia was initially defined as "dementia praecox" by E. Kraepelin, which implies progressive deterioration. However, recent studies have revealed that early effective intervention may lead to social and functional recovery in schizophrenia. In this review, we provide an overview of current concepts in schizophrenia and pathophysiological hypotheses. In addition, we present recent findings from clinical and basic research on schizophrenia. Recent neuroimaging and neurophysiological studies have consistently revealed specific biological differences in the structure and function of the brain in those with schizophrenia. From a basic research perspective, to determine the essential pathophysiology underlying schizophrenia, it is crucial that findings from all lines of inquiry-induced pluripotent stem cell (iPSC)-derived neural cells from patients, murine models expressing genetic mutations identified in patients, and patient clinical data-be integrated to contextualize the analysis results. However, the findings remain insufficient to serve as a diagnostic tool or a biomarker for predicting schizophrenia-related outcomes. Collaborations to conduct clinical research based on the patients' and their families' values are just beginning, and further development is expected.
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Affiliation(s)
- Toshiaki Onitsuka
- Department of Neuroimaging Psychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
| | - Takanobu Nakazawa
- Department of Bioscience, Tokyo University of Agriculture, Tokyo, Japan
| | - Kayo Ichihashi
- Department of Neuropsychiatry, The University of Tokyo Hospital, Tokyo, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Ken Inada
- Department of Psychiatry, Tokyo Women's Medical University, Tokyo, Japan.,Department of Psychiatry, Kitasato University School of Medicine, Kanagawa, Japan
| | - Ryo Mitoma
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Norio Yasui-Furukori
- Department of Psychiatry, Dokkyo Medical University School of Medicine, Tochigi, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
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323
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Cortical changes in patients with schizophrenia across two ethnic backgrounds. Sci Rep 2022; 12:10810. [PMID: 35752706 PMCID: PMC9233668 DOI: 10.1038/s41598-022-14914-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 06/15/2022] [Indexed: 11/24/2022] Open
Abstract
While it is known that cultural background influences the healthy brain, less is known about how it affects cortical changes in schizophrenia. Here, we tested whether schizophrenia differentially affected the brain in Japanese and German patients. In a sample of 155 patients with a diagnosis of schizophrenia and 191 healthy controls from Japan and Germany, we acquired 3 T-MRI of the brain. We subsequently compared cortical thickness and cortical surface area to identify whether differences between healthy controls and patients might be influenced by ethnicity. Additional analyses were performed to account for effects of duration of illness and medication. We found pronounced interactions between schizophrenia and cultural background in the cortical thickness of several areas, including the left inferior and middle temporal gyrus, as well as the right lateral occipital cortex. Regarding cortical surface area, interaction effects appeared in the insula and the occipital cortex, among others. Some of these brain areas are related to the expression of psychotic symptoms, which are known to differ across cultures. Our results indicate that cultural background impacts cortical structures in different ways, probably resulting in varying clinical manifestations, and call for the inclusion of more diverse samples in schizophrenia research.
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324
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Haas SS, Ge R, Sanford N, Modabbernia A, Reichenberg A, Whalley HC, Kahn RS, Frangou S. Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia. Front Psychiatry 2022; 13:913470. [PMID: 35815015 PMCID: PMC9257006 DOI: 10.3389/fpsyt.2022.913470] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/30/2022] [Indexed: 11/22/2022] Open
Abstract
Background Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms. Methods Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T1-weighted structural neuroimaging data from 84 patients (aged 16-35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16-37 years). Multidomain cognitive data from the patient sample were submitted to Heterogeneity through Discriminative Analysis (HYDRA) to identify cognitive clusters. Results HYDRA classified patients into a cognitively impaired cluster (n = 69) and a cognitively spared cluster (n = 15). Compared to healthy individuals, G-brainAGE was significantly higher in the cognitively impaired cluster (+11.08 years) who also showed widespread elevation in L-brainAGE, with the highest deviance observed in frontal and temporal regions. The cognitively spared cluster showed a moderate increase in G-brainAGE (+8.94 years), and higher L-brainAGE localized in the anterior cingulate cortex. Psychotic symptom severity in both clusters showed a positive but non-significant association with G-brainAGE. Discussion Accelerated aging in schizophrenia can be detected at the early disease stages and appears more closely associated with cognitive dysfunction rather than clinical symptoms. Future studies replicating our findings in multi-site cohorts with larger numbers of participants are warranted.
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Affiliation(s)
- Shalaila S. Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Ruiyang Ge
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Nicole Sanford
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Amirhossein Modabbernia
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Abraham Reichenberg
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Heather C. Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - René S. Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, United States
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
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Morese R, Brasso C, Stanziano M, Parola A, Valentini MC, Bosco FM, Rocca P. Efforts for the Correct Comprehension of Deceitful and Ironic Communicative Intentions in Schizophrenia: A Functional Magnetic Resonance Imaging Study on the Role of the Left Middle Temporal Gyrus. Front Psychol 2022; 13:866160. [PMID: 35774960 PMCID: PMC9237627 DOI: 10.3389/fpsyg.2022.866160] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Deficits in social cognition and more specifically in communication have an important impact on the real-life functioning of people with schizophrenia (SZ). In particular, patients have severe problems in communicative-pragmatics, for example, in correctly inferring the speaker's communicative intention in everyday conversational interactions. This limit is associated with morphological and functional alteration of the left middle temporal gyrus (L-MTG), a cerebral area involved in various communicative processes, in particular in the distinction of ironic communicative intention from sincere and deceitful ones. We performed an fMRI study on 20 patients with SZ and 20 matched healthy controls (HCs) while performing a pragmatic task testing the comprehension of sincere, deceitful, and ironic communicative intentions. We considered the L-MTG as the region of interest. SZ patients showed difficulties in the correct comprehension of all types of communicative intentions and, when correctly answering to the task, they exhibited a higher activation of the L-MTG, as compared to HC, under all experimental conditions. This greater involvement of the L-MTG in the group of patients could depend on different factors, such as the increasing inferential effort required in correctly understanding the speaker's communicative intentions, and the higher integrative semantic processes involved in sentence processing. Future studies with a larger sample size and functional connectivity analysis are needed to study deeper the specific role of the L-MTG in pragmatic processes in SZ, also in relation to other brain areas.
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Affiliation(s)
- R. Morese
- Faculty of Communication, Culture and Society, Università della Svizzera italiana, Lugano, Switzerland
- Faculty of Biomedical Sciences, Università della Svizzera italiana, Lugano, Switzerland
| | - C. Brasso
- Department of Neuroscience Rita Levi Montalcini, University of Turin, Turin, Italy
- Struttura Complessa di Psichiatria Universitaria, Dipartimento di Neuroscienze e Salute Mentale, Azienda Ospedaliera Universitaria “Città della Salute e della Scienza di Torino”, Turin, Italy
| | - M. Stanziano
- Department of Neuroscience Rita Levi Montalcini, University of Turin, Turin, Italy
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - A. Parola
- Research Group on Inferential Processes in Social Interaction (GIPSI), Department of Psychology, University of Turin, Turin, Italy
| | - M. C. Valentini
- Struttura Complessa di Neuroradiologia, Dipartimento Diagnostica per Immagini e Radiologia interventistica, Azienda Ospedaliera Universitaria “Città della Salute e della Scienza di Torino”, Turin, Italy
| | - F. M. Bosco
- Research Group on Inferential Processes in Social Interaction (GIPSI), Department of Psychology, University of Turin, Turin, Italy
| | - P. Rocca
- Department of Neuroscience Rita Levi Montalcini, University of Turin, Turin, Italy
- Struttura Complessa di Psichiatria Universitaria, Dipartimento di Neuroscienze e Salute Mentale, Azienda Ospedaliera Universitaria “Città della Salute e della Scienza di Torino”, Turin, Italy
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326
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Ulugut H, Trieu C, Groot C, van 't Hooft JJ, Tijms BM, Scheltens P, Ossenkoppele R, Barkhof F, van den Heuvel OA, Pijnenburg YAL. Overlap of Neuroanatomical Involvement in Frontotemporal Dementia and Primary Psychiatric Disorders: A Meta-analysis. Biol Psychiatry 2022; 93:820-828. [PMID: 35965106 DOI: 10.1016/j.biopsych.2022.05.028] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/05/2022] [Accepted: 05/31/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Despite significant symptomatic overlap between behavioral variant frontotemporal dementia (bvFTD) and primary psychiatric disorders (PPDs), a potential overlap in their structural anatomical changes has not been studied systematically. METHODS In this magnetic resonance imaging-based meta-analysis, we included studies on bvFTD, schizophrenia, bipolar disorder, and autism spectrum disorder that 1) used voxel-based morphometry analysis to assess regional gray matter volumes (GMVs) and 2) reported the coordinates of the regional GMV. Separate analyses were performed comparing clusters of coordinate-based changes in the GMVs (n = 24,183) between patients and control subjects, and overlapping brain regions between bvFTD and each PPD were examined. RESULTS We found that GMV alterations in the prefrontal and anterior cingulate cortices, temporal lobe, amygdala, and insula comprise the transdiagnostic brain alterations in bvFTD and PPD. CONCLUSIONS Our meta-analysis revealed significant anatomical overlap that paves the way for future investigations of shared pathophysiological pathways, and our cross-disorder approach would provide new insights to better understand the relationship between bvFTD and PPD.
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Affiliation(s)
- Hulya Ulugut
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Calvin Trieu
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Colin Groot
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Jochum J van 't Hooft
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Betty M Tijms
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Clinical Memory Research Unit, Lunds Universitet, Lund, Sweden
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; University College London, Institutes of Neurology and Healthcare Engineering, London, United Kingdom
| | - Odile A van den Heuvel
- Department of Psychiatry, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Departments of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Test-retest reliability of FreeSurfer-derived volume, area and cortical thickness from MPRAGE and MP2RAGE brain MRI images. NEUROIMAGE: REPORTS 2022; 2. [PMID: 36032692 PMCID: PMC9409374 DOI: 10.1016/j.ynirp.2022.100086] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background and purpose: Large MRI studies often pool data gathered from widely varying imaging sequences. Pooled data creates a potential source of variation in structural analyses which may cause misinterpretation of findings. The purpose of this study is to determine if data acquired using different scan sequences, head coils and scanners offers consistent structural measurements. Materials and methods: Participants (163 right-handed males: 82 typically developing controls, 81 participants with autism spectrum disorder) were scanned on the same day using an MPRAGE sequence with a 12-channel headcoil on a Siemens 3T Trio scanner and an MP2RAGE sequence with a 64-channel headcoil on a Siemens 3T Prisma scanner. Segmentation was performed using FreeSurfer to identify regions exhibiting variation between sequences on measures of volume, surface area, and cortical thickness. Intraclass correlation coefficient (ICC) and mean percent difference (MPD) were used as test-retest reproducibility measures. Results: ICC for total brain segmented volume yielded a 0.99 intraclass correlation, demonstrating high overall volumetric reproducibility. Comparison of individual regions of interest resulted in greater variation. Volumetric variability, although low overall, was greatest in the entorhinal cortex (ICC = 0.71), frontal (ICC = 0.60) and temporal (ICC = 0.60) poles. Surface area variability was greatest in the insula (ICC = 0.65), temporal (ICC = 0.64) and frontal (ICC = 0.68) poles. Cortical thickness was most variable in the frontal (ICC = 0.41) and temporal (ICC = 0.35) poles. Conclusion: Data collected on different scanners and head coils using MPRAGE and MP2RAGE are generally consistent for surface area and volume estimates. However, regional variability may constrain accuracy in some regions and cortical thickness measurements exhibit higher generalized variability.
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328
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Smigielski L, Stämpfli P, Wotruba D, Buechler R, Sommer S, Gerstenberg M, Theodoridou A, Walitza S, Rössler W, Heekeren K. White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk. Neuroimage Clin 2022; 35:103067. [PMID: 35679786 PMCID: PMC9178487 DOI: 10.1016/j.nicl.2022.103067] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/19/2022] [Accepted: 05/28/2022] [Indexed: 12/29/2022]
Abstract
This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112). The splenium of UHR individuals exhibited differences in fractional anisotropy (FA). Basic symptoms alone were not associated with white matter microstructure changes. Large differences in FA & radial diffusivity were found in converters to psychosis. Regional FA was inversely correlated with the general psychopathology domain.
Background Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis. Methods An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses. Results Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls. Conclusions These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.
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Affiliation(s)
- Lukasz Smigielski
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich, Zurich, Switzerland
| | - Stefan Sommer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany; Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
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329
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Syeda WT, Wannan CMJ, Merritt AH, Raghava JM, Jayaram M, Velakoulis D, Kristensen TD, Soldatos RF, Tonissen S, Thomas N, Ambrosen KS, Sørensen ME, Fagerlund B, Rostrup E, Glenthøj BY, Skafidas E, Bousman CA, Johnston LA, Everall I, Ebdrup BH, Pantelis C. Cortico-cognition coupling in treatment resistant schizophrenia. Neuroimage Clin 2022; 35:103064. [PMID: 35689976 PMCID: PMC9190061 DOI: 10.1016/j.nicl.2022.103064] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/10/2022] [Accepted: 05/26/2022] [Indexed: 11/03/2022]
Abstract
BACKGROUND Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC). METHOD Forty-one TRS patients (age 38.5 ± 9.1, 30 males (M)), and 45 HC (age 40.2 ± 10.6, 29 M) underwent 3T structural MRI. Volumes of 68 brain regions and seven variables from CANTAB covering memory and executive domains were included. Univariate group differences were assessed, followed by the MB-PLS-C analyses to identify group-specific multivariate patterns of cortico-cognitive coupling. Supplementary three-group analyses, which included 23 non-affected first-degree relatives (NAR), were also conducted. RESULTS Univariate tests demonstrated that TRS patients showed impairments in all seven cognitive tasks and volume reductions in 12 cortical regions following Bonferroni correction. The MB-PLS-C analyses revealed two significant latent variables (LVs) explaining > 90% of the sum-of-squares variance. LV1 explained 78.86% of the sum-of-squares variance, describing a shared, widespread structure-cognitive pattern relevant to both TRS patients and HCs. In contrast, LV2 (13.47% of sum-of-squares variance explained) appeared specific to TRS and comprised a differential cortico-cognitive pattern including frontal and temporal lobes as well as paired associates learning (PAL) and intra-extra dimensional set shifting (IED). Three-group analyses also identified two significant LVs, with NARs more closely resembling healthy controls than TRS patients. CONCLUSIONS MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.
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Affiliation(s)
- Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia.
| | - Cassandra M J Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Antonia H Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Jayachandra M Raghava
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Glostrup, Denmark
| | - Mahesh Jayaram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; MidWest Area Mental Health Service, Sunshine Hospital, St. Albans, Victoria, Australia
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Tina D Kristensen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Rigas Filippos Soldatos
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; First Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece
| | - Shane Tonissen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Naveen Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; MidWest Area Mental Health Service, Sunshine Hospital, St. Albans, Victoria, Australia
| | - Karen S Ambrosen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Mikkel E Sørensen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Birte Y Glenthøj
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Efstratios Skafidas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Canada
| | - Leigh A Johnston
- Department of Biomedical Engineering and Melbourne Brain Centre Imaging Unit, University of Melbourne, Victoria, Australia
| | - Ian Everall
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Bjørn H Ebdrup
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia; Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; MidWest Area Mental Health Service, Sunshine Hospital, St. Albans, Victoria, Australia; The Florey Institute of Neuroscience and Mental Health, Victoria, Australia
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Murray RM, Bora E, Modinos G, Vernon A. Schizophrenia: A developmental disorder with a risk of non-specific but avoidable decline. Schizophr Res 2022; 243:181-186. [PMID: 35390609 DOI: 10.1016/j.schres.2022.03.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/08/2022] [Accepted: 03/11/2022] [Indexed: 12/31/2022]
Abstract
The onset of schizophrenia is determined by biological and social risk factors operating predominantly during development. These result in subtle deviations in brain structure and cognitive function. Striatal dopamine dysregulation follows, causing abnormal salience and resultant psychotic symptoms. Most people diagnosed as having schizophrenia do not progressively deteriorate; many improve or recover. However, poor care can allow a cycle of deterioration to be established, stress increasing dopamine dysregulation, leading to more stress consequent on continuing psychotic experiences, and so further dopamine release. Additionally, long-term antipsychotics can induce dopamine supersensitivity with resultant relapse and eventually treatment resistance. Some patients suffer loss of social and cognitive function, but this is a consequence of the hazards that afflict the person with schizophrenia, not a direct consequence of genetic predisposition. Thus, brain health and cognition can be further impaired by chronic medication effects, cardiovascular and cerebrovascular events, obesity, poor diet, and lack of exercise; drug use, especially of tobacco and cannabis, are likely to contribute. Poverty, homelessness and poor nutrition which become the lot of some people with schizophrenia, can also affect cognition. Regrettably, the model of progressive deterioration provides psychiatry and its funders with an alibi for the effects of poor care.
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Affiliation(s)
- R M Murray
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - E Bora
- Dokuz Eylül Üniversitesi, Izmir, Izmir, Turkey
| | - G Modinos
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - A Vernon
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
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331
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Hu M, Qian X, Liu S, Koh AJ, Sim K, Jiang X, Guan C, Zhou JH. Structural and diffusion MRI based schizophrenia classification using 2D pretrained and 3D naive Convolutional Neural Networks. Schizophr Res 2022; 243:330-341. [PMID: 34210562 DOI: 10.1016/j.schres.2021.06.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 05/11/2021] [Accepted: 06/18/2021] [Indexed: 02/06/2023]
Abstract
The ability of automatic feature learning makes Convolutional Neural Network (CNN) potentially suitable to uncover the complex and widespread brain changes in schizophrenia. Despite that, limited studies have been done on schizophrenia identification using interpretable deep learning approaches on multimodal neuroimaging data. Here, we developed a deep feature approach based on pre-trained 2D CNN and naive 3D CNN models trained from scratch for schizophrenia classification by integrating 3D structural and diffusion magnetic resonance imaging (MRI) data. We found that the naive 3D CNN models outperformed the pretrained 2D CNN models and the handcrafted feature-based machine learning approach using support vector machine during both cross-validation and testing on an independent dataset. Multimodal neuroimaging-based models accomplished performance superior to models based on a single modality. Furthermore, we identified brain grey matter and white matter regions critical for illness classification at the individual- and group-level which supported the salience network and striatal dysfunction hypotheses in schizophrenia. Our findings underscore the potential of CNN not only to automatically uncover and integrate multimodal 3D brain imaging features for schizophrenia identification, but also to provide relevant neurobiological interpretations which are crucial for developing objective and interpretable imaging-based probes for prognosis and diagnosis in psychiatric disorders.
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Affiliation(s)
- Mengjiao Hu
- NTU Institute for Health Technologies, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore, Singapore; Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xing Qian
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Siwei Liu
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Amelia Jialing Koh
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kang Sim
- West Region, Institute of Mental Health (IMH), Singapore, Singapore; Department of Research, Institute of Mental Health (IMH), Singapore, Singapore
| | - Xudong Jiang
- School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Cuntai Guan
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
| | - Juan Helen Zhou
- Center for Sleep and Cognition, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Neuroscience and Behavioural Disorders Program, Duke-NUS Medical School, Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.
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332
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Cheon EJ, Bearden CE, Sun D, Ching CRK, Andreassen OA, Schmaal L, Veltman DJ, Thomopoulos SI, Kochunov P, Jahanshad N, Thompson PM, Turner JA, van Erp TG. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings. Psychiatry Clin Neurosci 2022; 76:140-161. [PMID: 35119167 PMCID: PMC9098675 DOI: 10.1111/pcn.13337] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/29/2021] [Accepted: 01/21/2022] [Indexed: 12/25/2022]
Abstract
This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.
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Affiliation(s)
- Eun-Jin Cheon
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Department of Psychiatry, Yeungnam University College of Medicine, Yeungnam University Medical Center, Daegu, Republic of Korea
| | - Carrie E. Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Daqiang Sun
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, Parkville, Australia
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlant, GA, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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333
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Demro C, Shen C, Hendrickson TJ, Arend JL, Disner SG, Sponheim SR. Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins. Front Aging Neurosci 2022; 14:872867. [PMID: 35527740 PMCID: PMC9074783 DOI: 10.3389/fnagi.2022.872867] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 03/11/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is "older" than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.
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Affiliation(s)
- Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Chen Shen
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | | | - Jessica L. Arend
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Seth G. Disner
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, United States
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334
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Demirci N, Holland MA. Cortical thickness systematically varies with curvature and depth in healthy human brains. Hum Brain Mapp 2022; 43:2064-2084. [PMID: 35098606 PMCID: PMC8933257 DOI: 10.1002/hbm.25776] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 11/30/2021] [Accepted: 01/05/2022] [Indexed: 12/30/2022] Open
Abstract
Cortical thickness varies throughout the cortex in a systematic way. However, it is challenging to investigate the patterns of cortical thickness due to the intricate geometry of the cortex. The cortex has a folded nature both in radial and tangential directions which forms not only gyri and sulci but also tangential folds and intersections. In this article, cortical curvature and depth are used to characterize the spatial distribution of the cortical thickness with much higher resolution than conventional regional atlases. To do this, a computational pipeline was developed that is capable of calculating a variety of quantitative measures such as surface area, cortical thickness, curvature (mean curvature, Gaussian curvature, shape index, intrinsic curvature index, and folding index), and sulcal depth. By analyzing 501 neurotypical adult human subjects from the ABIDE-I dataset, we show that cortex has a very organized structure and cortical thickness is strongly correlated with local shape. Our results indicate that cortical thickness consistently increases along the gyral-sulcal spectrum from concave to convex shape, encompassing the saddle shape along the way. Additionally, tangential folds influence cortical thickness in a similar way as gyral and sulcal folds; outer folds are consistently thicker than inner.
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Affiliation(s)
- Nagehan Demirci
- Bioengineering Graduate ProgramUniversity of Notre DameNotre DameIndianaUSA
| | - Maria A. Holland
- Bioengineering Graduate ProgramUniversity of Notre DameNotre DameIndianaUSA
- Department of Aerospace and Mechanical EngineeringUniversity of Notre DameNotre DameIndianaUSA
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335
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Wu Y, Zhong Y, Liao X, Miao X, Yu J, Lai X, Zhang Y, Ma C, Pan H, Wang S. Transmembrane protein 108 inhibits the proliferation and myelination of oligodendrocyte lineage cells in the corpus callosum. Mol Brain 2022; 15:33. [PMID: 35410424 PMCID: PMC8996597 DOI: 10.1186/s13041-022-00918-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/31/2022] [Indexed: 11/22/2022] Open
Abstract
Background Abnormal white matter is a common neurobiological change in bipolar disorder, and dysregulation of myelination in oligodendrocytes (OLs) is the cause. Transmembrane protein 108 (Tmem108), as a susceptible gene of bipolar disorder, is expressed higher in OL lineage cells than any other lineage cells in the central nervous system. Moreover, Tmem108 mutant mice exhibit mania-like behaviors, belonging to one of the signs of bipolar disorder. However, it is unknown whether Tmem108 regulates the myelination of the OLs. Results Tmem108 expression in the corpus callosum decreased with the development, and OL progenitor cell proliferation and OL myelination were enhanced in the mutant mice. Moreover, the mutant mice exhibited mania-like behavior after acute restraint stress and were susceptible to drug-induced epilepsy. Conclusions Tmem108 inhibited OL progenitor cell proliferation and mitigated OL maturation in the corpus callosum, which may also provide a new role of Tmem108 involving bipolar disorder pathogenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s13041-022-00918-7.
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336
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Iorio-Morin C, Sarica C, Elias GJB, Harmsen I, Hodaie M. Neuroimaging of psychiatric disorders. PROGRESS IN BRAIN RESEARCH 2022; 270:149-169. [PMID: 35396025 DOI: 10.1016/bs.pbr.2021.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Psychiatry remains the only medical specialty where diagnoses are still based on clinical syndromes rather than measurable biological abnormalities. As imaging technology and analytical methods evolve, it is becoming clear that subtle but measurable radiological characteristics exist and can be used to experimentally classify psychiatric disorders, predict response to treatment and, hopefully, develop new, more effective therapies. This review highlights advances in neuroimaging modalities that are now allowing assessment of brain structure, connectivity and neural network function, describes technical aspects of the most promising methods, and summarizes observations made in some frequent psychiatric disorders.
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Affiliation(s)
- Christian Iorio-Morin
- Division of Neurosurgery, Department of Surgery, Université de Sherbrooke, Sherbrooke, QC, Canada; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Can Sarica
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Gavin J B Elias
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Irene Harmsen
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Mojgan Hodaie
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada.
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337
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Feng A, Luo N, Zhao W, Calhoun VD, Jiang R, Zhi D, Shi W, Jiang T, Yu S, Xu Y, Liu S, Sui J. Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage. Hum Brain Mapp 2022; 43:3486-3497. [PMID: 35388581 PMCID: PMC9248316 DOI: 10.1002/hbm.25862] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/10/2022] [Accepted: 03/23/2022] [Indexed: 11/25/2022] Open
Abstract
Incidence of schizophrenia (SZ) has two predominant peaks, in adolescent and young adult. Early‐onset schizophrenia provides an opportunity to explore the neuropathology of SZ early in the disorder and without the confound of antipsychotic mediation. However, it remains unexplored what deficits are shared or differ between adolescent early‐onset (EOS) and adult‐onset schizophrenia (AOS) patients. Here, based on 529 participants recruited from three independent cohorts, we explored AOS and EOS common and unique co‐varying patterns by jointly analyzing three MRI features: fractional amplitude of low‐frequency fluctuations (fALFF), gray matter (GM), and functional network connectivity (FNC). Furthermore, a prediction model was built to evaluate whether the common deficits in drug‐naive SZ could be replicated in chronic patients. Results demonstrated that (1) both EOS and AOS patients showed decreased fALFF and GM in default mode network, increased fALFF and GM in the sub‐cortical network, and aberrant FNC primarily related to middle temporal gyrus; (2) the commonly identified regions in drug‐naive SZ correlate with PANSS positive significantly, which can also predict PANSS positive in chronic SZ with longer duration of illness. Collectively, results suggest that multimodal imaging signatures shared by two types of drug‐naive SZ are also associated with positive symptom severity in chronic SZ and may be vital for understanding the progressive schizophrenic brain structural and functional deficits.
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Affiliation(s)
- Aichen Feng
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Wentao Zhao
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Vince D Calhoun
- Tri-Institutional Centre for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA
| | - Rongtao Jiang
- Department of Radiology and Biomedical imaging, Yale University, New Haven, Connecticut, USA
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiyang Shi
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Yong Xu
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jing Sui
- Tri-Institutional Centre for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.,State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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338
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Andreou D, Jørgensen KN, Nerland S, Yolken RH, Haukvik UK, Andreassen OA, Agartz I. Cytomegalovirus Infection Associated with Smaller Total Cortical Surface Area in Schizophrenia Spectrum Disorders. Schizophr Bull 2022; 48:1164-1173. [PMID: 35388401 PMCID: PMC9434442 DOI: 10.1093/schbul/sbac036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVES Cytomegalovirus (CMV) congenital infection and in immunodeficiency can have deleterious effects on human cortex. In immunocompetent adults, the putative association between CMV infection and cortical measures has not been explored. We hypothesized that CMV exposure is associated with smaller cortical surface area or cortical thinning mainly in patients with schizophrenia spectrum disorders. STUDY DESIGN We included 67 adult patients with schizophrenia spectrum disorders and 262 adult healthy controls. We measured circulating CMV IgG antibody concentrations with solid-phase immunoassay techniques. We measured the total cortical surface area, regional cortical surface areas and the overall mean cortical thickness based on T1-weighted MRI scans processed in FreeSurfer v6.0. STUDY RESULTS In the whole sample analysis, we found a significant diagnostic group-by-CMV status interaction on the total surface area (P = .020). Among patients, CMV antibody positivity was significantly associated with smaller total surface area (P = .002, partial eta2 = 0.138) whereas no such association was found in healthy controls (P = .059). Post hoc analysis among patients showed that higher CMV antibody concentrations were also significantly associated with smaller total surface area (P = .038), and that CMV antibody positivity was significantly inversely associated with 14 left and 16 right regional surface areas mainly in the frontal and temporal lobes. CMV infection was not associated with the overall mean cortical thickness. CONCLUSIONS The results are indicative of a cortical surface area vulnerability to CMV infection in patients with schizophrenia spectrum disorders but not in healthy controls. CMV infection may contribute to the established cortical surface area aberrations in schizophrenia.
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Affiliation(s)
- Dimitrios Andreou
- To whom correspondence should be addressed; Diakonhjemmet Hospital, Department of Psychiatric Research, Forskningsveien 7, 0373, Oslo, Norway; tel: +46737678848, fax: +4722029901, e-mail:
| | - Kjetil Nordbø Jørgensen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Stener Nerland
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Robert H Yolken
- Department of Pediatrics, Stanley Division of Developmental Neurovirology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Unn K Haukvik
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway,Department of Forensic Research and Education, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
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339
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Gong J, Cui LB, Zhao YS, Liu ZW, Yang XJ, Xi YB, Liu L, Liu P, Sun JB, Zhao SW, Liu XF, Jia J, Li P, Yin H, Qin W. The correlation between dynamic functional architecture and response to electroconvulsive therapy combined with antipsychotics in schizophrenia. Eur J Neurosci 2022; 55:2024-2036. [PMID: 35388553 DOI: 10.1111/ejn.15664] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 03/29/2022] [Accepted: 03/31/2022] [Indexed: 11/26/2022]
Abstract
Attempts to determine why some patients respond to electroconvulsive therapy (ECT) are valuable in schizophrenia. Schizophrenia is associated with aberrant dynamic functional architecture, which might impact the efficacy of ECT. We aimed to explore the relationship between pre-treatment temporal variability and ECT acute efficacy. Forty-eight patients with schizophrenia and thirty healthy controls underwent functional magnetic resonance imaging to examine whether patterns of temporary variability of functional architecture differ between high responders (HR) and low responders (LR) at baseline. Compared with LR, HR exhibited significantly abnormal temporal variability in right inferior front gyrus (IFGtriang.R), left temporal pole (TPOsup.L) and right middle temporal gyrus (MTG.R). In the pooled patient group, ∆PANSS was correlated with the temporal variability of these regions. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to ECT. Our findings provide not only an understanding of the neural functional architecture patterns that are found in schizophrenia but also the possibility of using these measures as moderators for ECT selection.
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Affiliation(s)
- Jie Gong
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Long-Biao Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Ying-Song Zhao
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Zhao-Wen Liu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Xue-Juan Yang
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xi'an People's Hospital, Xi'an, China
| | - Lin Liu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Peng Liu
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Jin-Bo Sun
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Jie Jia
- Department of Early Intervention, Xi'an Mental Health Center, Xi'an, Shaanxi, China
| | - Ping Li
- Department of Medical Imaging, Xi'an Mental Health Center, Xi'an, Shaanxi, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
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340
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Chen CL, Hwang TJ, Tung YH, Yang LY, Hsu YC, Liu CM, Lin YT, Hsieh MH, Liu CC, Chien YL, Hwu HG, Tseng WYI. Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics. Neuroimage Clin 2022; 34:103003. [PMID: 35413648 PMCID: PMC9018160 DOI: 10.1016/j.nicl.2022.103003] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 03/24/2022] [Accepted: 04/04/2022] [Indexed: 11/28/2022]
Abstract
Conceptualizing mental disorders as deviations from normative functioning provides a statistical perspective for understanding the individual heterogeneity underlying psychiatric disorders. To broaden the understanding of the idiosyncrasy of brain aging in schizophrenia, we introduced an imaging-derived brain age paradigm combined with normative modeling as novel brain age metrics. We constructed brain age models based on GM, WM, and their combination (multimodality) features of 482 normal participants. The normalized predicted age difference (nPAD) was estimated in 147 individuals with schizophrenia and their 130 demographically matched controls through normative models of brain age metrics and compared between the groups. Regression analyses were also performed to investigate the associations of nPAD with illness duration, onset age, symptom severity, and intelligence quotient. Finally, regional contributions to advanced brain aging in schizophrenia were investigated. The results showed that the individuals exhibited significantly higher nPAD (P < 0.001), indicating advanced normative brain age than the normal controls in GM, WM, and multimodality models. The nPAD measure based on WM was positively associated with the negative symptom score (P = 0.009), and negatively associated with the intelligence quotient (P = 0.039) and onset age (P = 0.006). The imaging features that contributed to nPAD mostly involved the prefrontal, temporal, and parietal lobes, especially the precuneus and uncinate fasciculus. This study demonstrates that normative brain age metrics could detect advanced brain aging and associated clinical and neuroanatomical features in schizophrenia. The proposed nPAD measures may be useful to investigate aberrant brain aging in mental disorders and their brain-phenotype relationships.
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Affiliation(s)
- Chang-Le Chen
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yu-Hung Tung
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Li-Ying Yang
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Tin Lin
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Ming-Hsien Hsieh
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Chung Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan; AcroViz Inc., Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Molecular Imaging Center, National Taiwan University, Taipei, Taiwan.
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341
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Wortinger LA, Engen K, Barth C, Andreassen OA, Nordbø Jørgensen K, Agartz I. Asphyxia at birth affects brain structure in patients on the schizophrenia-bipolar disorder spectrum and healthy participants. Psychol Med 2022; 52:1050-1059. [PMID: 32772969 PMCID: PMC9069351 DOI: 10.1017/s0033291720002779] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Revised: 06/05/2020] [Accepted: 07/16/2020] [Indexed: 12/24/2022]
Abstract
BACKGROUND Uncertainty exists about what causes brain structure alterations associated with schizophrenia (SZ) and bipolar disorder (BD). Whether a history of asphyxia-related obstetric complication (ASP) - a common but harmful condition for neural tissue - contributes to variations in adult brain structure is unclear. We investigated ASP and its relationship to intracranial (ICV), global brain volumes and regional cortical and subcortical structures. METHODS A total of 311 patients on the SZ - BD spectrum and 218 healthy control (HC) participants underwent structural magnetic resonance imaging. They were evaluated for ASP using prospective information obtained from the Medical Birth Registry of Norway. RESULTS In all groups, ASP was related to smaller ICV, total brain, white and gray matter volumes and total surface area, but not to cortical thickness. Smaller cortical surface areas were found across frontal, parietal, occipital, temporal and insular regions. Smaller hippocampal, amygdala, thalamus, caudate and putamen volumes were reported for all ASP subgroups. ASP effects did not survive ICV correction, except in the caudate, which remained significantly smaller in both patient ASP subgroups, but not in the HC. CONCLUSIONS Since ASP was associated with smaller brain volumes in all groups, the genetic risk of developing a severe mental illness, alone, cannot easily explain the smaller ICV. Only the smaller caudate volumes of ASP patients specifically suggest that injury from ASP can be related to disease development. Our findings give support for the ICV as a marker of aberrant neurodevelopment and ASP in the etiology of brain development in BD and SZ.
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Affiliation(s)
- Laura Anne Wortinger
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kristine Engen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Claudia Barth
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, NORMENT, Oslo University Hospital, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institute, Stockholm, Sweden
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342
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Owen MJ, Legge SE. The nature of schizophrenia: As broad as it is long. Schizophr Res 2022; 242:109-112. [PMID: 34756599 DOI: 10.1016/j.schres.2021.10.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/18/2021] [Indexed: 11/26/2022]
Affiliation(s)
- Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Sophie E Legge
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
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343
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Barch DM, Karcher N, Moran E. Reinventing schizophrenia - Embracing complexity and complication. Schizophr Res 2022; 242:7-11. [PMID: 34893361 DOI: 10.1016/j.schres.2021.11.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/21/2021] [Accepted: 11/24/2021] [Indexed: 12/28/2022]
Affiliation(s)
- Deanna M Barch
- Department of Psychological & Brain Sciences, Washington University, United States of America; Department of Psychiatry, Washington University, United States of America; Department of Radiology, Washington University, United States of America.
| | - Nicole Karcher
- Department of Psychiatry, Washington University, United States of America
| | - Erin Moran
- Department of Psychological & Brain Sciences, Washington University, United States of America
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344
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Fountoulakis KN, Stahl SM. The effect of first- and second-generation antipsychotics on brain morphology in schizophrenia: A systematic review of longitudinal magnetic resonance studies with a randomized allocation to treatment arms. J Psychopharmacol 2022; 36:428-438. [PMID: 35395911 DOI: 10.1177/02698811221087645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Schizophrenia manifests as loss of brain volume in specific areas in a progressive nature and an important question concerns whether long-term treatment with medications contributes to this. The aim of the current PRISMA systematic review was to search for prospective studies involving randomization to treatment. PROSPERO ID: CRD42020197874. The MEDLINE/PUBMED was searched and it returned 2638 articles; 3 were fulfilling the inclusion criteria. A fourth was published later; they included 359 subjects, of whom 86 were healthy controls, while the rest were first-episode patients, with 91 under olanzapine, 93 under haloperidol, 48 under risperidone, 5 under paliperidone, 6 under ziprasidone, and 30 under placebo. Probably one-third of patients were suffering from a psychotic disorder other than schizophrenia. The consideration of their results suggested that there is no significant difference between these medications concerning their effects on brain structure and also in comparison to healthy subjects. There does not seem to be any strong support to the opinion that medications that treat psychosis cause loss of brain volume in patients with schizophrenia. On the contrary, the data might imply the possible presence of a protective effect for D2, 5-HT2, and NE alpha-2 antagonists (previously called SGAs). However, the literature is limited and focused research in large study samples is essential to clarify the issue, since important numerical differences do exist. The possibility of the results and their heterogeneity to be artifacts secondary to a modification of magnetic resonance imaging (MRI) signal by antipsychotics should not be easily rejected until relevant data are available.
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Affiliation(s)
- Konstantinos N Fountoulakis
- 3rd Department of Psychiatry, Faculty of Medicine, School of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Stephen M Stahl
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.,Department of Psychiatry, Cambridge University, Cambridge, UK
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345
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Guma E, Bordeleau M, González Ibáñez F, Picard K, Snook E, Desrosiers-Grégoire G, Spring S, Lerch JP, Nieman BJ, Devenyi GA, Tremblay ME, Chakravarty MM. Differential effects of early or late exposure to prenatal maternal immune activation on mouse embryonic neurodevelopment. Proc Natl Acad Sci U S A 2022; 119:e2114545119. [PMID: 35286203 PMCID: PMC8944668 DOI: 10.1073/pnas.2114545119] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 02/01/2022] [Indexed: 12/23/2022] Open
Abstract
Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental and psychiatric disorders. MIA-induced deficits in adolescent and adult offspring have been well characterized; however, less is known about the effects of MIA exposure on embryo development. To address this gap, we performed high-resolution ex vivo MRI to investigate the effects of early (gestational day [GD]9) and late (GD17) MIA exposure on embryo (GD18) brain structure. We identify striking neuroanatomical changes in the embryo brain, particularly in the late-exposed offspring. We further examined the putative neuroanatomical underpinnings of MIA timing in the hippocampus using electron microscopy and identified differential effects due to MIA timing. An increase in apoptotic cell density was observed in the GD9-exposed offspring, while an increase in the density of neurons and glia with ultrastructural features reflective of increased neuroinflammation and oxidative stress was observed in GD17-exposed offspring, particularly in females. Overall, our findings integrate imaging techniques across different scales to identify differential impact of MIA timing on the earliest stages of neurodevelopment.
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Affiliation(s)
- Elisa Guma
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3A 0G4, Canada
| | - Maude Bordeleau
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3A 0G4, Canada
- Axe Neurosciences, Centre de Recherche du Centre Hospitalier Universitaire de Québec–Université Laval, Quebec City, QC G1V 4G2, Canada
| | - Fernando González Ibáñez
- Axe Neurosciences, Centre de Recherche du Centre Hospitalier Universitaire de Québec–Université Laval, Quebec City, QC G1V 4G2, Canada
- Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, Quebec City, QC G1V 0A6, Canada
- Division of Medical Sciences, University of Victoria, Victoria, BC V8P 5C2, Canada
| | - Katherine Picard
- Axe Neurosciences, Centre de Recherche du Centre Hospitalier Universitaire de Québec–Université Laval, Quebec City, QC G1V 4G2, Canada
- Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, Quebec City, QC G1V 0A6, Canada
- Division of Medical Sciences, University of Victoria, Victoria, BC V8P 5C2, Canada
| | - Emily Snook
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Gabriel Desrosiers-Grégoire
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3A 0G4, Canada
| | - Shoshana Spring
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Jason P. Lerch
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5S 1A1, Canada
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX1 2JD, United Kingdom
| | - Brian J. Nieman
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5S 1A1, Canada
- Translational Medicine, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- Imaging Program, Ontario Institute for Cancer Research, Toronto, ON M5G 0A3, Canada
| | - Gabriel A. Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Department of Psychiatry, McGill University, Montreal, QC H3A 0G4, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC V8P 5C2, Canada
| | - Marie-Eve Tremblay
- Axe Neurosciences, Centre de Recherche du Centre Hospitalier Universitaire de Québec–Université Laval, Quebec City, QC G1V 4G2, Canada
- Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, Quebec City, QC G1V 0A6, Canada
- Division of Medical Sciences, University of Victoria, Victoria, BC V8P 5C2, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC V8P 5C2, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 0G4, Canada
| | - M. Mallar Chakravarty
- Computational Brain Anatomy Laboratory, Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, QC H4H 1R3, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3A 0G4, Canada
- Department of Psychiatry, McGill University, Montreal, QC H3A 0G4, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, QC H3A 0G4, Canada
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346
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Pan S, Zhou Y, Yan L, Xuan F, Tong J, Li Y, Huang J, Feng W, Chen S, Cui Y, Yang F, Tan S, Wang Z, Tian B, Hong LE, Tan YL, Tian L. TGF-β1 is associated with deficits in cognition and cerebral cortical thickness in first-episode schizophrenia. J Psychiatry Neurosci 2022; 47:E86-E98. [PMID: 35301253 PMCID: PMC9259382 DOI: 10.1503/jpn.210121] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 10/04/2021] [Accepted: 11/23/2021] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND Evidence indicates that cytokines are associated with cognitive deficits in schizophrenia; however, the underlying brain-behaviour mechanisms remain unclear. We hypothesized that aberrations in brain structural connectivity mediate the cytokine effect in schizophrenia. METHODS In this study, we recruited patients with first-episode schizophrenia (n = 75, average illness duration 12.3 months, average medication period 0.6 days) and healthy controls (n = 44) of both sexes. We first conducted whole-blood RNA sequencing to detect differentially expressed genes. We also explored transcriptomic data on the dorsal lateral prefrontal cortices (dlPFC) retrieved from the CommonMind Consortium for gene functional clustering; we measured plasma transforming growth factor β1 (TGF-β1) levels by enzyme-linked immunosorbent assay; we acquired high-resolution T 1-weighted MRI data on cortical thickness MRI; and we assessed cognitive function using the validated Chinese version of the MATRICS Consensus Cognitive Battery. We compared these parameters in patients with schizophrenia and controls, and analyzed their associations. RESULTS Patients with schizophrenia had higher TGF-β1 at both the mRNA level (log2 fold change = 0.24; adjusted p = 0.026) and the protein level (12.85 ± 6.01 μg/mL v. 8.46 ± 5.15 μg/mL, adjusted p < 0.001) compared to controls. Genes coexpressed with TGFB1 in the dlPFC were less abundant in patients with schizophrenia compared to healthy controls. In patients with schizophrenia, TGF-β1 protein levels were inversely correlated with cortical thickness, especially of the lateral occipital cortex (r = -0.47, adjusted p = 0.001), and with the MATRICS Consensus Cognitive Battery visual learning and memory domain (r = -0.50, adjusted p < 0.001). We found a complete mediation effect of the thickness of the lateral occipital cortex on the negative relationship between TGF-β1 and visual cognition (p < 0.05). LIMITATIONS We did not explore the effect of other blood cytokines on neurocognitive performance and cortical thickness. Participants from the CommonMind Consortium did not all have first-episode schizophrenia and they were not all antipsychotic-naive, so we could not exclude an effect of antipsychotics on TGF-β1 signalling in the dlPFC. The sample size and cross-sectional design of our study were additional limitations. CONCLUSION These findings highlighted an association between upregulated blood levels of TGF-β1 and impairments in brain structure and function in schizophrenia.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Yun-Long Tan
- From the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Pan, Zhou, Tong, Li, Huang, Feng, Chen, Yang, S. Tan, Wang, B. Tian, Y. Tan, L. Tian); the Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia (Yan, Xuan, L. Tian); the Department of Pharmacy, Peking University First Hospital, Beijing, China (Cui); and the Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, USA (Hong)
| | - Li Tian
- From the Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, China (Pan, Zhou, Tong, Li, Huang, Feng, Chen, Yang, S. Tan, Wang, B. Tian, Y. Tan, L. Tian); the Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia (Yan, Xuan, L. Tian); the Department of Pharmacy, Peking University First Hospital, Beijing, China (Cui); and the Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, USA (Hong)
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347
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The Limits between Schizophrenia and Bipolar Disorder: What Do Magnetic Resonance Findings Tell Us? Behav Sci (Basel) 2022; 12:bs12030078. [PMID: 35323397 PMCID: PMC8944966 DOI: 10.3390/bs12030078] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/10/2022] [Accepted: 03/10/2022] [Indexed: 02/01/2023] Open
Abstract
Schizophrenia and bipolar disorder, two of the most severe psychiatric illnesses, have historically been regarded as dichotomous entities but share many features of the premorbid course, clinical profile, genetic factors and treatment approaches. Studies focusing on neuroimaging findings have received considerable attention, as they plead for an improved understanding of the brain regions involved in the pathophysiology of schizophrenia and bipolar disorder. In this review, we summarize the main magnetic resonance imaging findings in both disorders, aiming at exploring the neuroanatomical and functional similarities and differences between the two. The findings show that gray and white matter structural changes and functional dysconnectivity predominate in the frontal and limbic areas and the frontotemporal circuitry of the brain areas involved in the integration of executive, cognitive and affective functions, commonly affected in both disorders. Available evidence points to a considerable overlap in the affected regions between the two conditions, therefore possibly placing them at opposite ends of a psychosis continuum.
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348
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Krajner F, Hadaya L, McQueen G, Sendt KV, Gillespie A, Avila A, Lally J, Hedges EP, Diederen K, Howes OD, Barker GJ, Lythgoe DJ, Kempton MJ, McGuire P, MacCabe JH, Egerton A. Subcortical volume reduction and cortical thinning 3 months after switching to clozapine in treatment resistant schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:13. [PMID: 35236831 PMCID: PMC8891256 DOI: 10.1038/s41537-022-00230-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/06/2021] [Indexed: 11/29/2022]
Abstract
The neurobiological effects of clozapine are under characterised. We examined the effects clozapine treatment on subcortical volume and cortical thickness and investigated whether macrostructural changes were linked to alterations in glutamate or N-acetylaspartate (NAA). Data were acquired in 24 patients with treatment-resistant schizophrenia before and 12 weeks after switching to clozapine. During clozapine treatment we observed reductions in caudate and putamen volume, lateral ventricle enlargement (P < 0.001), and reductions in thickness of the left inferior temporal cortex, left caudal middle frontal cortex, and the right temporal pole. Reductions in right caudate volume were associated with local reductions in NAA (P = 0.002). None of the morphometric changes were associated with changes in glutamate levels. These results indicate that clozapine treatment is associated with subcortical volume loss and cortical thinning and that at least some of these effects are linked to changes in neuronal or metabolic integrity.
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Affiliation(s)
- Fanni Krajner
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Laila Hadaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Grant McQueen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Kyra-Verena Sendt
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Amy Gillespie
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
| | - Alessia Avila
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - John Lally
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Emily P Hedges
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Kelly Diederen
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - Gareth J Barker
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - David J Lythgoe
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
- South London and Maudsley NHS Trust, London, UK
| | - Alice Egerton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK.
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349
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Oomen PP, Gangadin SS, Begemann MJH, Visser E, Mandl RCW, Sommer IEC. The neurobiological characterization of distinct cognitive subtypes in early-phase schizophrenia-spectrum disorders. Schizophr Res 2022; 241:228-237. [PMID: 35176721 DOI: 10.1016/j.schres.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/28/2022] [Accepted: 02/04/2022] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures. METHODS Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA. RESULTS Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume. DISCUSSION Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.
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Affiliation(s)
- P P Oomen
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands.
| | - S S Gangadin
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - M J H Begemann
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
| | - E Visser
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - R C W Mandl
- Department of Psychiatry, University Medical Center, Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - I E C Sommer
- Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neurosciences, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
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350
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Ji E, Boerrigter D, Cai HQ, Lloyd D, Bruggemann J, O'Donnell M, Galletly C, Lloyd A, Liu D, Lenroot R, Weickert TW, Shannon Weickert C. Peripheral complement is increased in schizophrenia and inversely related to cortical thickness. Brain Behav Immun 2022; 101:423-434. [PMID: 34808287 DOI: 10.1016/j.bbi.2021.11.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/23/2021] [Accepted: 11/15/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND There is growing evidence for complement system involvement in the pathophysiology of schizophrenia, although the extent and magnitude of complement factor disturbances has not been fully reported. It also remains unclear whether complement abnormalities are characteristic of all patients with schizophrenia or whether they are representative of a subgroup of patients who show signs of heightened inflammation. The aim of the present study was to quantify and compare the levels of a range of complement factors, receptors and regulators in healthy controls and people with schizophrenia and to determine the extent to which the levels of these peripheral molecules relate to measures of brain structure, particularly cortical thickness. METHOD Seventy-five healthy controls and 90 patients with schizophrenia or schizoaffective disorder were included in the study. Peripheral blood samples were collected from all participants and mRNA expression was quantified in 20 complement related genes, four complement proteins, as well as for four cytokines. T1-weighted structural MRI scans were acquired and analysed to determine cortical thickness measures. RESULTS There were significant increases in peripheral mRNA encoding receptors (C5ar1, CR1, CR3a), regulators (CD55, C59) and protein concentrations (C3, C3b, C4) in people with schizophrenia relative to healthy controls. C4a expression was significantly increased in a subgroup of patients displaying elevated peripheral cytokine levels. A higher inflammation index score derived from mRNA expression patterns predicted reductions in cortical thickness in the temporal lobe (superior temporal gyrus, transverse temporal gyrus, fusiform gyrus, insula) in patients with schizophrenia and healthy controls. CONCLUSIONS Analysis of all three major complement pathways supports increased complement activity in schizophrenia and also shows that peripheral C4a up-regulation is related to increased peripheral pro-inflammatory cytokines in healthy controls. Our region-specific, neuroimaging findings linked to an increased peripheral complement mRNA expression pattern suggests a role for complement in cortical thinning. Further studies are required to further clarify clinical and neurobiological consequences of aberrant complement levels in schizophrenia and related psychoses.
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Affiliation(s)
- Ellen Ji
- Psychiatric University Hospital Zurich, Zurich, Switzerland; Neuroscience Research Australia, Sydney, NSW, Australia
| | | | - Helen Q Cai
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - David Lloyd
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Jason Bruggemann
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; Edith Collins Centre (Translational Research in Alcohol Drugs & Toxicology), Sydney Local Health District, Australia; Speciality of Addiction Medicine, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Australia
| | - Maryanne O'Donnell
- School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Cherrie Galletly
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, South Australia, Australia; Northern Adelaide Local Health Network, Adelaide, South Australia, Australia; Ramsay Health Care (SA) Mental Health Services, Adelaide, South Australia, Australia
| | - Andrew Lloyd
- Inflammation and Infection Research Centre, University of New South Wales, Sydney, Australia
| | - Dennis Liu
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, South Australia, Australia; Northern Adelaide Local Health Network, Adelaide, South Australia, Australia
| | - Rhoshel Lenroot
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
| | - Thomas W Weickert
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY, USA
| | - Cynthia Shannon Weickert
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia; Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY, USA.
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