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Ramduny J, Kelly C. Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction. Neuropsychopharmacology 2024:10.1038/s41386-024-01962-8. [PMID: 39147868 DOI: 10.1038/s41386-024-01962-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 08/02/2024] [Accepted: 08/05/2024] [Indexed: 08/17/2024]
Abstract
Functional magnetic resonance imaging-based functional connectivity enables the non-invasive mapping of individual differences in brain functional organization to individual differences in a vast array of behavioral phenotypes. This flexibility has renewed the search for neuroimaging-based biomarkers that exhibit reproducibility, prediction, and precision. Functional connectivity-based measures that share these three characteristics are key to achieving this goal. Here, we review the functional connectome fingerprinting approach and discuss its value, not only as a simple and intuitive conceptualization of the "functional connectome" that provides new insights into how the connectome is altered in association with psychiatric symptoms, but also as a straightforward and interpretable method for indexing the reproducibility of functional connectivity-based measures. We discuss how these advantages provide new avenues for strengthening reproducibility, precision, and behavioral prediction for functional connectomics and we consider new directions toward discovering better biomarkers for neuropsychiatric conditions.
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Affiliation(s)
- Jivesh Ramduny
- Department of Psychology, Yale University, New Haven, CT, USA.
- Kavli Institute for Neuroscience, Yale University, New Haven, CT, USA.
| | - Clare Kelly
- School of Psychology, Trinity College Dublin, Dublin, Ireland.
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland.
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2
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Cheng Y, Cai H, Liu S, Yang Y, Pan S, Zhang Y, Mo F, Yu Y, Zhu J. Brain Network Localization of Gray Matter Atrophy and Neurocognitive and Social Cognitive Dysfunction in Schizophrenia. Biol Psychiatry 2024:S0006-3223(24)01489-6. [PMID: 39103010 DOI: 10.1016/j.biopsych.2024.07.021] [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: 05/13/2024] [Revised: 07/13/2024] [Accepted: 07/29/2024] [Indexed: 08/07/2024]
Abstract
BACKGROUND Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, relatively few studies have examined brain network localization of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia. METHODS To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 individuals with schizophrenia and 9275 healthy control participants. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia. RESULTS The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks. CONCLUSIONS Our findings suggest shared and unique brain network substrates of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective but may also contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.
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Affiliation(s)
- Yan Cheng
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Huanhuan Cai
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Siyu Liu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yang Yang
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Shan Pan
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yongqi Zhang
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Fan Mo
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China
| | - Yongqiang Yu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
| | - Jiajia Zhu
- Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei, China; Anhui Provincial Institute of Translational Medicine, Hefei, China; Anhui Provincial Key Laboratory for Brain Bank Construction and Resource Utilization, Hefei, China.
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3
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Yang KC, Yang BH, Liu MN, Liou YJ, Chou YH. Cognitive impairment in schizophrenia is associated with prefrontal-striatal functional hypoconnectivity and striatal dopaminergic abnormalities. J Psychopharmacol 2024; 38:515-525. [PMID: 38853592 DOI: 10.1177/02698811241257877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
BACKGROUND A better understanding of the mechanisms underlying cognitive impairment in schizophrenia is imperative, as it causes poor functional outcomes and a lack of effective treatments. AIMS This study aimed to investigate the relationships of two proposed main pathophysiology of schizophrenia, altered prefrontal-striatal connectivity and the dopamine system, with cognitive impairment and their interactions. METHODS Thirty-three patients with schizophrenia and 27 healthy controls (HCs) who are right-handed and matched for age and sex were recruited. We evaluated their cognition, functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC)/middle frontal gyrus (MiFG) and striatum, and the availability of striatal dopamine transporter (DAT) using a cognitive battery investigating attention, memory, and executive function, resting-state functional magnetic resonance imaging with group independent component analysis and single-photon emission computed tomography with 99mTc-TRODAT. RESULTS Patients with schizophrenia exhibited poorer cognitive performance, reduced FC between DLPFC/MiFG and the caudate nucleus (CN) or putamen, decreased DAT availability in the left CN, and decreased right-left DAT asymmetry in the CN compared to HCs. In patients with schizophrenia, altered imaging markers are associated with cognitive impairments, especially the relationship between DLPFC/MiFG-putamen FC and attention and between DAT asymmetry in the CN and executive function. CONCLUSIONS This study is the first to demonstrate how prefrontal-striatal hypoconnectivity and altered striatal DAT markers are associated with different domains of cognitive impairment in schizophrenia. More research is needed to evaluate their complex relationships and potential therapeutic implications.
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Affiliation(s)
- Kai-Chun Yang
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Bang-Hung Yang
- Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Mu-N Liu
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ying-Jay Liou
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yuan-Hwa Chou
- Department of Psychiatry, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan
- The Human Brain Research Center, Taichung Veterans General Hospital, Taichung, Taiwan
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4
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Gu YW, Fan JW, Zhao SW, Liu XF, Yin H, Cui LB. Large-scale mechanism hypothesis and research prospects of cognitive impairment in schizophrenia based on magnetic resonance imaging. Heliyon 2024; 10:e25915. [PMID: 38404811 PMCID: PMC10884805 DOI: 10.1016/j.heliyon.2024.e25915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/09/2024] [Accepted: 02/05/2024] [Indexed: 02/27/2024] Open
Abstract
Cognitive impairments in schizophrenia are pivotal clinical issues that need to be solved urgently. However, the mechanism remains unknown. It has been suggested that cognitive impairments in schizophrenia are associated with connectome damage, and are especially relevant to the disrupted hub nodes in the frontal and parietal lobes. Activating the dorsolateral prefrontal cortex (DLPFC) via repetitive transcranial magnetic stimulation (rTMS) could result in improved cognition. Based on several previous magnetic resonance imaging (MRI) studies on schizophrenia, we found that the first-episode patients showed connectome damage, as well as abnormal activation and connectivity of the DLPFC and inferior parietal lobule (IPL). Accordingly, we proposed that DLPFC-IPL pathway destruction might mediate connectome damage of cognitive impairments in schizophrenia. In the meantime, with the help of multimodal MRI and noninvasive neuromodulation tool, we may not only validate the hypothesis, but also find IPL as the potential intervention target for cognitive impairments in schizophrenia.
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Affiliation(s)
- Yue-Wen Gu
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The General Hospital of Western Theater Command, Chengdu, China
| | - Jing-Wen Fan
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Shu-Wan Zhao
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Hong Yin
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Long-Biao Cui
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
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Lewandowski KE. To lump or to split: cognitive impairment across mood and psychotic disorders. Neuropsychopharmacology 2024; 49:493-494. [PMID: 38017162 PMCID: PMC10789744 DOI: 10.1038/s41386-023-01770-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 11/05/2023] [Indexed: 11/30/2023]
Affiliation(s)
- Kathryn E Lewandowski
- McLean Hospital Schizophrenia and Bipolar Disorder Program, Belmont, MA, USA.
- Harvard Medical School Department of Psychiatry, Boston, MA, USA.
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Wenzel J, Badde L, Haas SS, Bonivento C, Van Rheenen TE, Antonucci LA, Ruef A, Penzel N, Rosen M, Lichtenstein T, Lalousis PA, Paolini M, Stainton A, Dannlowski U, Romer G, Brambilla P, Wood SJ, Upthegrove R, Borgwardt S, Meisenzahl E, Salokangas RKR, Pantelis C, Lencer R, Bertolino A, Kambeitz J, Koutsouleris N, Dwyer DB, Kambeitz-Ilankovic L. Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness. Neuropsychopharmacology 2024; 49:573-583. [PMID: 37737273 PMCID: PMC10789737 DOI: 10.1038/s41386-023-01729-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/03/2023] [Accepted: 08/26/2023] [Indexed: 09/23/2023]
Abstract
Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.
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Affiliation(s)
- Julian Wenzel
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany.
| | - Luzie Badde
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, NY, USA
| | | | - Tamsyn E Van Rheenen
- Centre for Mental Health, School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, VIC, Australia
| | - Linda A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Nora Penzel
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Marlene Rosen
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Theresa Lichtenstein
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Paris Alexandros Lalousis
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, UK
| | - Marco Paolini
- Department of Radiology, University Hospital, Ludwig-Maximilian University, Munich, Germany
| | - Alexandra Stainton
- Orygen, Melbourne, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Muenster, Münster, Germany
| | - Georg Romer
- Department of Child and Adolescent Psychiatry, University of Münster, Münster, Germany
| | - Paolo Brambilla
- Department of Neuosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Mental Health, University of Milan, Milan, Italy
| | - Stephen J Wood
- Orygen, Melbourne, VIC, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
- School of Psychology, University of Birmingham, Birmingham, UK
| | - Rachel Upthegrove
- School of Psychology, University of Birmingham, Birmingham, UK
- Institute of Mental Health and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Stefan Borgwardt
- Translational Psychiatry Unit (TPU), Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, University of Melbourne & Western Health, Melbourne, VIC, Australia
| | - Rebekka Lencer
- Institute for Translational Psychiatry, University of Muenster, Münster, Germany
- Translational Psychiatry Unit (TPU), Department of Psychiatry and Psychotherapy, University of Luebeck, Luebeck, Germany
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience - University of Bari Aldo Moro, Bari, Italy
| | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Institute of Psychiatry, Psychology & Neuroscience, Department of Psychosis Studies, King's College London, London, UK
- Max Planck Institute for Psychiatry, Munich, Germany
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
- Orygen, Melbourne, VIC, Australia
| | - Lana Kambeitz-Ilankovic
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, Cologne, Germany
- Faculty of Psychology and Educational Sciences, Department of Psychology, Ludwig-Maximilian University, Munich, Germany
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Wang L, Ambite JL, Appaji A, Bijsterbosch J, Dockes J, Herrick R, Kogan A, Lander H, Marcus D, Moore SM, Poline JB, Rajasekar A, Sahoo SS, Turner MD, Wang X, Wang Y, Turner JA. NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data. Front Neuroinform 2023; 17:1215261. [PMID: 37720825 PMCID: PMC10500076 DOI: 10.3389/fninf.2023.1215261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 08/01/2023] [Indexed: 09/19/2023] Open
Abstract
Introduction Open science initiatives have enabled sharing of large amounts of already collected data. However, significant gaps remain regarding how to find appropriate data, including underutilized data that exist in the long tail of science. We demonstrate the NeuroBridge prototype and its ability to search PubMed Central full-text papers for information relevant to neuroimaging data collected from schizophrenia and addiction studies. Methods The NeuroBridge architecture contained the following components: (1) Extensible ontology for modeling study metadata: subject population, imaging techniques, and relevant behavioral, cognitive, or clinical data. Details are described in the companion paper in this special issue; (2) A natural-language based document processor that leveraged pre-trained deep-learning models on a small-sample document corpus to establish efficient representations for each article as a collection of machine-recognized ontological terms; (3) Integrated search using ontology-driven similarity to query PubMed Central and NeuroQuery, which provides fMRI activation maps along with PubMed source articles. Results The NeuroBridge prototype contains a corpus of 356 papers from 2018 to 2021 describing schizophrenia and addiction neuroimaging studies, of which 186 were annotated with the NeuroBridge ontology. The search portal on the NeuroBridge website https://neurobridges.org/ provides an interactive Query Builder, where the user builds queries by selecting NeuroBridge ontology terms to preserve the ontology tree structure. For each return entry, links to the PubMed abstract as well as to the PMC full-text article, if available, are presented. For each of the returned articles, we provide a list of clinical assessments described in the Section "Methods" of the article. Articles returned from NeuroQuery based on the same search are also presented. Conclusion The NeuroBridge prototype combines ontology-based search with natural-language text-mining approaches to demonstrate that papers relevant to a user's research question can be identified. The NeuroBridge prototype takes a first step toward identifying potential neuroimaging data described in full-text papers. Toward the overall goal of discovering "enough data of the right kind," ongoing work includes validating the document processor with a larger corpus, extending the ontology to include detailed imaging data, and extracting information regarding data availability from the returned publications and incorporating XNAT-based neuroimaging databases to enhance data accessibility.
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Affiliation(s)
- Lei Wang
- Psychiatry and Behavioral Health Department, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - José Luis Ambite
- Information Sciences Institute and Computer Science, University of Southern California, Los Angeles, CA, United States
| | - Abhishek Appaji
- Department of Medical Electronics Engineering, BMS College of Engineering, Bangalore, India
| | - Janine Bijsterbosch
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Jerome Dockes
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Rick Herrick
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Alex Kogan
- Psychiatry and Behavioral Health Department, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Howard Lander
- Renaissance Computing Institute, Chapel Hill, NC, United States
| | - Daniel Marcus
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Stephen M. Moore
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Jean-Baptiste Poline
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Arcot Rajasekar
- Renaissance Computing Institute, Chapel Hill, NC, United States
- School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Satya S. Sahoo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
| | - Matthew D. Turner
- Psychiatry and Behavioral Health Department, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Xiaochen Wang
- College of Information Sciences and Technology, Pennsylvania State University, State College, PA, United States
| | - Yue Wang
- School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jessica A. Turner
- Psychiatry and Behavioral Health Department, The Ohio State University Wexner Medical Center, Columbus, OH, United States
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8
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Liu XF, Zhao SW, Cui JJ, Gu YW, Fan JW, Fu YF, Zhang YH, Yin H, Chen K, Cui LB. Differential expression of diacylglycerol kinase ζ is involved in inferior parietal lobule-related dysfunction in schizophrenia with cognitive impairments. BMC Psychiatry 2023; 23:526. [PMID: 37479996 PMCID: PMC10362743 DOI: 10.1186/s12888-023-04955-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 06/13/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Cognitive impairment is the main factor in the poor prognosis of schizophrenia, but its mechanism remains unclear. The inferior parietal lobule (IPL) is related to various clinical symptoms and cognitive impairment in schizophrenia. We aimed to explore the relationship between IPL-related functions and cognitive impairment in schizophrenia. METHODS 136 schizophrenia patients and 146 demographically matched healthy controls were enrolled for a cross-sectional study. High-spatial-resolution structural and resting-state functional images were acquired to demonstrate the alternations of brain structure and function. At the same time, the digit span and digit symbol coding tasks of the Chinese Wechsler Adult Intelligence Test Revised (WAIS-RC) were utilized in assessing the subjects' cognitive function. Patients were divided into cognitive impairment and normal cognitive groups according to their cognitive score and then compared whether there were differences between the three groups in fractional amplitude of low-frequency fluctuation (fALFF). In addition, we did a correlation analysis between cognitive function and the fALFF for the left IPL of patients and healthy controls. Based on the Allen Human Brain Atlas, we obtained genes expressed in the left IPL, which were then intersected with the transcriptome-wide association study results and differentially expressed genes in schizophrenia. RESULTS Grouping of patients by the backward digit span task and the digit symbol coding task showed differences in fALFF values between healthy controls and cognitive impairment patients (P < 0.05). We found a negative correlation between the backward digit span task score and fALFF of the left IPL in healthy controls (r = - 0.388, P = 0.003), which was not seen in patients (r = 0.203, P = 0.020). In addition, none of the other analyses were statistically significant (P > 0.017). In addition, we found that diacylglycerol kinase ζ (DGKζ) is differentially expressed in the left IPL and associated with schizophrenia. CONCLUSION Our study demonstrates that the left IPL plays a vital role in cognitive impairment in schizophrenia. DGKζ may act as an essential regulator in the left IPL of schizophrenia patients with cognitive impairment.
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Affiliation(s)
- Xiao-Fan Liu
- Department of Radiology, Xi'an People's Hospital, Xi'an, China
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jin-Jin Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yue-Wen Gu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital, Xi'an, China.
| | - Kun Chen
- Department of Human Anatomy and K. K. Leung Brain Research Centre, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
| | - Long-Biao Cui
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
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Massalha Y, Maggioni E, Callari A, Brambilla P, Delvecchio G. A review of resting-state fMRI correlations with executive functions and social cognition in bipolar disorder. J Affect Disord 2023; 334:337-351. [PMID: 37003435 DOI: 10.1016/j.jad.2023.03.084] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 03/20/2023] [Accepted: 03/25/2023] [Indexed: 04/03/2023]
Abstract
BACKGROUND Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains. METHODS A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria. RESULTS Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients. LIMITATIONS The heterogeneity of the reviewed studies, in terms of cognitive domains explored and neuroimaging acquisitions, limited the comparability of the findings. CONCLUSIONS rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.
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Affiliation(s)
- Yara Massalha
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
| | - Eleonora Maggioni
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20122 Milan, Italy
| | - Antonio Callari
- Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy; Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy
| | - Giuseppe Delvecchio
- Fondazione IRCCS Ca' Granda-Ospedale Maggiore Policlinico, Department of Neurosciences and Mental Health, 20122 Milan, Italy.
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10
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Chen J, Fu Z, Bustillo JR, Perrone-Bizzozero NI, Lin D, Canive J, Pearlson GD, Stephen JM, Mayer AR, Potkin SG, van Erp TGM, Kochunov P, Elliot Hong L, Adhikari BM, Andreassen OA, Agartz I, Westlye LT, Sui J, Du Y, Macciardi F, Hanlon FM, Jung RE, Turner JA, Liu J, Calhoun VD. Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder. Schizophr Bull 2022; 48:1306-1317. [PMID: 35988022 PMCID: PMC9673262 DOI: 10.1093/schbul/sbac088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) and bipolar disorder (BD) share genetic risk factors, yet patients display differential levels of cognitive impairment. We hypothesized a genome-transcriptome-functional connectivity (frontoparietal)-cognition pathway linked to SZ-versus-BD differences, and conducted a multiscale study to delineate this pathway. STUDY DESIGNS Large genome-wide studies provided single nucleotide polymorphisms (SNPs) conferring more risk for SZ than BD, and we identified their regulated genes, namely SZ-biased SNPs and genes. We then (a) computed the polygenic risk score for SZ (PRSSZ) of SZ-biased SNPs and examined its associations with imaging-based frontoparietal functional connectivity (FC) and cognitive performances; (b) examined the spatial correlation between ex vivo postmortem expressions of SZ-biased genes and in vivo, SZ-related FC disruptions across frontoparietal regions; (c) investigated SZ-versus-BD differences in frontoparietal FC; and (d) assessed the associations of frontoparietal FC with cognitive performances. STUDY RESULTS PRSSZ of SZ-biased SNPs was significantly associated with frontoparietal FC and working memory test scores. SZ-biased genes' expressions significantly correlated with SZ-versus-BD differences in FC across frontoparietal regions. SZ patients showed more reductions in frontoparietal FC than BD patients compared to controls. Frontoparietal FC was significantly associated with test scores of multiple cognitive domains including working memory, and with the composite scores of all cognitive domains. CONCLUSIONS Collectively, these multiscale findings support the hypothesis that SZ-biased genetic risk, through transcriptome regulation, is linked to frontoparietal dysconnectivity, which in turn contributes to differential cognitive deficits in SZ-versus BD, suggesting that potential biomarkers for more precise patient stratification and treatment.
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Affiliation(s)
- Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory 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, and Emory University, Atlanta, GA, USA
| | - Juan R Bustillo
- Department of Neurosciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
- Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Nora I Perrone-Bizzozero
- Department of Neurosciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
- Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Dongdong Lin
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Jose Canive
- Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - Godfrey D Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
- Department of Psychiatry and Neuroscience, Yale University, New Haven, CT, USA
| | | | | | - Steven G Potkin
- Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, CA, USA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, Clinical Translational Neuroscience Laboratory, School of Medicine, University of California, Irvine, CA, USA
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Bhim M Adhikari
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Ole A Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Ingrid Agartz
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
| | - Lars T Westlye
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yuhui Du
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, CA, USA
| | | | - Rex E Jung
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| | - Jessica A Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA
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11
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Shao T, Wang W, Hei G, Yang Y, Long Y, Wang X, Xiao J, Huang Y, Song X, Xu X, Gao S, Huang J, Wang Y, Zhao J, Wu R. Identifying and revealing different brain neural activities of cognitive subtypes in early course schizophrenia. Front Mol Neurosci 2022; 15:983995. [PMID: 36267704 PMCID: PMC9577612 DOI: 10.3389/fnmol.2022.983995] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 09/07/2022] [Indexed: 01/10/2023] Open
Abstract
Background Cognitive subtypes of schizophrenia may exhibit different neurobiological characteristics. This study aimed to reveal the underlying neurobiological features between cognitive subtypes in the early course of schizophrenia (ECS). According to prior studies, we hypothesized to identify 2–4 distinct cognitive subtypes. We further hypothesized that the subtype with relatively poorer cognitive function might have lower brain spontaneous neural activity than the subtype with relatively better cognitive function. Method Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). Resting-state functional magnetic resonance imaging scanning was conducted for each individual. There were 155 ECS individuals and 97 healthy controls (HCs) included in the subsequent analysis. Latent profile analysis (LPA) was used to identify the cognitive subtypes in ECS individuals, and amplitude of low-frequency fluctuations (ALFFs) was used to measure brain spontaneous neural activity in ECS individuals and HCs. Results LPA identified two cognitive subtypes in ECS individuals, containing a severely impaired subtype (SI, n = 63) and a moderately impaired subtype (MI, n = 92). Compared to HCs, ECS individuals exhibited significantly increased ALFF in the left caudate and bilateral thalamus and decreased ALFF in the bilateral medial prefrontal cortex and bilateral posterior cingulate cortex/precuneus (PCC/PCu). In ECS cognitive subtypes, SI showed significantly higher ALFF in the left precentral gyrus (PreCG) and lower ALFF in the left PCC/PCu than MI. Furthermore, ALFFs of left PreCG were negatively correlated with several MCCB cognitive domains in ECS individuals, while ALFF of left PCC/PCu presented opposite correlations. Conclusion Our findings suggest that differences in the brain spontaneous neural activity of PreCG and PCC/PCu might be the potential neurobiological features of the cognitive subtypes in ECS, which may deepen our understanding of the role of PreCG and PCC/PCu in the pathogenesis of cognitive impairment in schizophrenia.
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Affiliation(s)
- Tiannan Shao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Weiyan Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Gangrui Hei
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ye Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yujun Long
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiaoyi Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jingmei Xiao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yuyan Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xueqin Song
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Shuzhan Gao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ying Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jingping Zhao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Renrong Wu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- *Correspondence: Renrong Wu
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12
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King VL, Lahti AC, Maximo JO, ver Hoef LW, John S, Kraguljac NV. Contrasting Frontoparietal Network Connectivity in Antipsychotic Medication-Naive First-Episode Psychosis Patients Who Do and Do Not Display Features of the Deficit Syndrome. Schizophr Bull 2022; 48:1344-1353. [PMID: 35869578 PMCID: PMC9673254 DOI: 10.1093/schbul/sbac081] [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: 12/14/2022]
Abstract
BACKGROUND The deficit syndrome is a clinical subtype of schizophrenia that is characterized by enduring negative symptoms. Several lines of evidence point to frontoparietal involvement, but the frontoparietal control network (FPCN) and its subsystems (FPCNA and FPCNB) proposed by Yeo et al. have not been systematically characterized at rest in patients with the deficit syndrome. METHODS We used resting-state fMRI to investigate the FPCN and its subnetworks in 72 healthy controls and 65 antipsychotic medication-naive, first-episode psychosis patients (22 displayed deficit syndrome features, 43 did not). To assess whole-brain FPCN connectivity, we used the right posterior parietal cortex as the seed region. We then performed region of interest analyses in FPCN subsystems. RESULTS We found that patterns of FPCN dysconnectivity to the whole brain differed in patients who displayed deficit syndrome features compared with those who did not. Examining the FPCN on a more granular level revealed reduced within-FPCN(A) connectivity only in patients displaying deficit features. FPCNB connectivity did not differ between patient groups. DISCUSSION Here, we describe a neurobiological signature of aberrant FPCN connectivity in antipsychotic-naive, first-episode patients who display clinical features of the deficit syndrome. Importantly, frontoparietal subnetwork connectivity differentiated subgroups, where the FPCNA is selectively involved in patients with deficit features. Our findings add to the growing body of literature supporting a neurobiological distinction between two clinical subtypes of schizophrenia, which has the potential to be leveraged for patient stratification in clinical trials and the development of novel treatments.
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Affiliation(s)
- Victoria L King
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jose O Maximo
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Lawrence W ver Hoef
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sooraj John
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nina V Kraguljac
- To whom correspondence should be addressed; Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, SC 501, 1720 7th Ave S, Birmingham, AL 35294-0017, USA; tel: 205-996-7171, e-mail:
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13
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Mastrandrea R, Piras F, Gabrielli A, Banaj N, Caldarelli G, Spalletta G, Gili T. The unbalanced reorganization of weaker functional connections induces the altered brain network topology in schizophrenia. Sci Rep 2021; 11:15400. [PMID: 34321538 PMCID: PMC8319172 DOI: 10.1038/s41598-021-94825-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 07/08/2021] [Indexed: 01/10/2023] Open
Abstract
Network neuroscience shed some light on the functional and structural modifications occurring to the brain associated with the phenomenology of schizophrenia. In particular, resting-state functional networks have helped our understanding of the illness by highlighting the global and local alterations within the cerebral organization. We investigated the robustness of the brain functional architecture in 44 medicated schizophrenic patients and 40 healthy comparators through an advanced network analysis of resting-state functional magnetic resonance imaging data. The networks in patients showed more resistance to disconnection than in healthy controls, with an evident discrepancy between the two groups in the node degree distribution computed along a percolation process. Despite a substantial similarity of the basal functional organization between the two groups, the expected hierarchy of healthy brains' modular organization is crumbled in schizophrenia, showing a peculiar arrangement of the functional connections, characterized by several topologically equivalent backbones. Thus, the manifold nature of the functional organization's basal scheme, together with its altered hierarchical modularity, may be crucial in the pathogenesis of schizophrenia. This result fits the disconnection hypothesis that describes schizophrenia as a brain disorder characterized by an abnormal functional integration among brain regions.
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Affiliation(s)
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy
| | - Andrea Gabrielli
- Dipartimento di Ingegneria, Università Roma Tre, 00146, Rome, Italy.,Istituto dei Sistemi Complessi (ISC)-CNR, UoS Sapienza, Dipartimento di Fisica, Università "Sapienza", 00185, Rome, Italy
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy
| | - Guido Caldarelli
- Networks Unit, IMT School for Advanced Studies, 55100, Lucca, Italy.,Istituto dei Sistemi Complessi (ISC)-CNR, UoS Sapienza, Dipartimento di Fisica, Università "Sapienza", 00185, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, 00179, Rome, Italy. .,Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
| | - Tommaso Gili
- Networks Unit, IMT School for Advanced Studies, 55100, Lucca, Italy
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14
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Chen WY, Huang MC, Lee YC, Chang CE, Lin SK, Chiu CC, Liu HC, Kuo CJ, Weng SH, Chen PY, Kuo PH. The Heterogeneity of Longitudinal Cognitive Decline in Euthymic Bipolar I Disorder With Clinical Characteristics and Functional Outcomes. Front Psychiatry 2021; 12:684813. [PMID: 34366918 PMCID: PMC8335543 DOI: 10.3389/fpsyt.2021.684813] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/24/2021] [Indexed: 12/01/2022] Open
Abstract
We characterized the heterogeneity and risk factors of cognitive decline in euthymic bipolar disorder (BD), and their magnitude of associations with subjective daily functions. In this retrospective cohort, BD type I patients (N = 128) were followed for an average of 6.5 years. Intelligence quotient (IQ) at index date was recorded, and premorbid IQ was estimated. We used Brief Assessment of Cognition in Affective Disorders (BAC-A) to assess cognition at follow-up. We evaluated current functions with World Health Organization Disability Assessment Schedule 2.0. Clinical and sociodemographic factors were examined for their independent effects on longitudinal cognitive decline. In addition, we employed multivariate adaptive regression spline to detect inflection points for the nature of slope changes in cognitive decline among BD patients. During follow-up years, 21 BD patients (16.4%) showed longitudinal cognitive decline. In cognitive decline group, all cognitive domains of BAC-A were significantly worsened. We found that density of episodes with psychotic features was an independent risk factor for cognitive decline after adjusted for age, gender and dose of mood stabilizer. After the age of 42 years, a steeper cognitive change was observed in the cognitive decline group. The correlation pattern between cognitive domains and functional outcomes differed between patients with and without cognitive decline. The present study characterized cognitive heterogeneity longitudinally in BD patients. As density of episodes play roles for cognitive decline, our results emphasize the importance of relapse prevention. Our findings provide hints for future personalized interventions and facilitating genetic and biological studies for dissecting the heterogeneity of bipolar illness.
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Affiliation(s)
- Wen-Yin Chen
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Ming-Chyi Huang
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Ya-Chin Lee
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chiao-Erh Chang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Shih-Ku Lin
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Chih Chiang Chiu
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Hsing-Cheng Liu
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Chian-Jue Kuo
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Shih-Han Weng
- Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
| | - Po-Yu Chen
- Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan
- Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Po-Hsiu Kuo
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
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15
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Wang C, Oughourlian T, Tishler TA, Anwar F, Raymond C, Pham AD, Perschon A, Villablanca JP, Ventura J, Subotnik KL, Nuechterlein KH, Ellingson BM. Cortical morphometric correlational networks associated with cognitive deficits in first episode schizophrenia. Schizophr Res 2021; 231:179-188. [PMID: 33872855 DOI: 10.1016/j.schres.2021.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/09/2021] [Accepted: 04/07/2021] [Indexed: 12/14/2022]
Abstract
Schizophrenia (SCZ) is a chronic cognitive and behavioral disorder associated with abnormal cortical activity during information processing. Several brain structures associated with the seven performance domains evaluated using the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery (MCCB) have shown cortical volume loss in first episode schizophrenia (FES) patients. However, the relationship between morphological organization and MCCB performance remains unclear. Therefore, in the current observational study, high-resolution structural MRI scans were collected from 50 FES patients, and the morphometric correlation network (MCN) using cortical volume was established to characterize the cortical pattern associated with poorer MCCB performance. We also investigated topological properties, such as the modularity, the degree and the betweenness centrality. Our findings show structural volume was directly and strongly associated with the cognitive deficits of FES patients in the precuneus, anterior cingulate, and fusiform gyrus, as well as the prefrontal, parietal, and sensorimotor cortices. The medial orbitofrontal, fusiform, and superior frontal gyri were not only identified as the predominant nodes with high degree and betweenness centrality in the MCN, but they were also found to be critical in performance in several of the MCCB domains. Together, these results suggest a widespread cortical network is altered in FES patients and that performance on the MCCB domains is associated with the core pathophysiology of SCZ.
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Affiliation(s)
- Chencai Wang
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Talia Oughourlian
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Todd A Tishler
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Faizan Anwar
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Catalina Raymond
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Alex D Pham
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Abby Perschon
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - J Pablo Villablanca
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Joseph Ventura
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Kenneth L Subotnik
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Keith H Nuechterlein
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States of America
| | - Benjamin M Ellingson
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America; Neuroscience Interdisciplinary Graduate Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States of America.
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16
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Brain morphology does not clearly map to cognition in individuals on the bipolar-schizophrenia-spectrum: a cross-diagnostic study of cognitive subgroups. J Affect Disord 2021; 281:776-785. [PMID: 33246649 DOI: 10.1016/j.jad.2020.11.064] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/08/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Characterisation of brain morphological features common to cognitively similar individuals with bipolar disorder (BD) and schizophrenia spectrum disorders (SSD) may be key to understanding their shared neurobiological deficits. In the current study we examined whether three previously characterised cross-diagnostic cognitive subgroups differed among themselves and in comparison to healthy controls across measures of brain morphology. METHOD T1-weighted structural magnetic resonance imaging scans were obtained for 143 individuals; 65 healthy controls and 78 patients (SSD, n = 40; BD I, n = 38) classified into three cross-diagnostic cognitive subgroups: Globally Impaired (n = 24), Selectively Impaired (n = 32), and Superior/Near-Normal (n = 22). Cognitive subgroups were compared to each other and healthy controls on three separate analyses investigating (1) global, (2) regional, and (3) vertex-wise comparisons of brain volume, thickness, and surface area. RESULTS No significant subgroup differences were evident in global measures of brain morphology. In region of interest analyses, the Selectively Impaired subgroup had greater right accumbens volume than those Superior/Near-Normal subgroup and healthy controls, and the Superior/Near-Normal subgroup had reduced volume of the left entorhinal region compared to all other groups. In vertex-wise comparisons, the Globally Impaired subgroup had greater right precentral volume than the Selectively Impaired subgroup, and thicker cortex in the postcentral region relative to the Superior/Near-Normal subgroup. LIMITATIONS Exploration of medication effects was limited in our data. CONCLUSIONS Although some differences were evident in this sample, generally cross-diagnostic cognitive subgroups of individuals with SSD and BD did not appear to be clearly distinguished by patterns in brain morphology.
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Van Rheenen TE, Cropley V, Fagerlund B, Wannan C, Bruggemann J, Lenroot RK, Sundram S, Weickert CS, Weickert TW, Zalesky A, Bousman CA, Pantelis C. Cognitive reserve attenuates age-related cognitive decline in the context of putatively accelerated brain ageing in schizophrenia-spectrum disorders. Psychol Med 2020; 50:1475-1489. [PMID: 31274065 DOI: 10.1017/s0033291719001417] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND In schizophrenia, relative stability in the magnitude of cognitive deficits across age and illness duration is inconsistent with the evidence of accelerated deterioration in brain regions known to support these functions. These discrepant brain-cognition outcomes may be explained by variability in cognitive reserve (CR), which in neurological disorders has been shown to buffer against brain pathology and minimize its impact on cognitive or clinical indicators of illness. METHODS Age-related change in fluid reasoning, working memory and frontal brain volume, area and thickness were mapped using regression analysis in 214 individuals with schizophrenia or schizoaffective disorder and 168 healthy controls. In patients, these changes were modelled as a function of CR. RESULTS Patients showed exaggerated age-related decline in brain structure, but not fluid reasoning compared to controls. In the patient group, no moderation of age-related brain structural change by CR was evident. However, age-related cognitive change was moderated by CR, such that only patients with low CR showed evidence of exaggerated fluid reasoning decline that paralleled the exaggerated age-related deterioration of underpinning brain structures seen in all patients. CONCLUSIONS In schizophrenia-spectrum illness, CR may negate ageing effects on fluid reasoning by buffering against pathologically exaggerated structural brain deterioration through some form of compensation. CR may represent an important modifier that could explain inconsistencies in brain structure - cognition outcomes in the extant literature.
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Affiliation(s)
- Tamsyn E Van Rheenen
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Center, Glostrup, Denmark
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Cassandra Wannan
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Rhoshel K Lenroot
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Suresh Sundram
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Psychiatry, School of Clinical Sciences, Monash University, Clayton, Australia
- Mental Health Program, Monash Health, Clayton, Victoria, Australia
| | - Cynthia Shannon Weickert
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
- Department of Neuroscience & Physiology, Upstate Medical University, Syracuse, New York13210, USA
| | - Thomas W Weickert
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- School of Psychiatry, University of New South Wales, New South Wales, Australia
- Neuroscience Research Australia, New South Wales, Australia
| | - Andrew Zalesky
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia
| | - Chad A Bousman
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Christos Pantelis
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
- Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia
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Lewandowski KE. Genetically, Developmentally, and Clinically Distinct Cognitive Subtypes in Schizophrenia: A Tale of Three Trajectories. Am J Psychiatry 2020; 177:282-284. [PMID: 32233679 DOI: 10.1176/appi.ajp.2020.20020132] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Kathryn E Lewandowski
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, Mass.; and Department of Psychiatry, Harvard Medical School, Boston
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19
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Neurodevelopmental pathways in bipolar disorder. Neurosci Biobehav Rev 2020; 112:213-226. [PMID: 32035092 DOI: 10.1016/j.neubiorev.2020.02.005] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 01/03/2020] [Accepted: 02/04/2020] [Indexed: 12/14/2022]
Abstract
Aberrations in neurodevelopmental trajectories have been implicated in the neurobiology of several mental disorders and evidence indicates a pathophysiological and genetic overlap of schizophrenia and bipolar disorder (BD). In this narrative review, we summarize findings related to developmental and perinatal factors as well as epidemiological, clinical, neuropsychological, brain imaging, postmortem brain and genomic studies that provide evidence for a putative neurodevelopmental pathogenesis and etiology of BD. Overall, aberrations in neurodevelopmental pathways have been more consistently implicated in the pathophysiology of schizophrenia compared to BD. Nevertheless, an accumulating body of evidence indicates that dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of at least a subset of individuals with BD particularly those with an early age of illness onset and those exhibiting psychotic symptoms. A heuristic neurodevelopmental model for the pathophysiology of BD based on the findings of this review is proposed. Furthermore, we critically discuss clinical and research implications of this model. Finally, further research directions for this emerging field are provided.
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Miskowiak KW, Lewandowski KE. Trajectory of cognitive functions in bipolar disorder: for better or worse? Acta Psychiatr Scand 2020; 141:95-97. [PMID: 31953857 DOI: 10.1111/acps.13144] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 12/27/2019] [Accepted: 12/27/2019] [Indexed: 12/16/2022]
Affiliation(s)
- K W Miskowiak
- Copenhagen Affective Disorder Research Centre, Mental Health Services, Capital Region of Denmark, Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.,Deparment of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - K E Lewandowski
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Psychotic Disorders Division, McLean Hospital, Belmont, MA, USA
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21
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Lewandowski KE. Mapping cognitive trajectories across the course of illness in psychosis. Schizophr Res 2019; 210:48-49. [PMID: 30595442 PMCID: PMC6597326 DOI: 10.1016/j.schres.2018.12.032] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 12/20/2018] [Indexed: 11/19/2022]
Affiliation(s)
- Kathryn E Lewandowski
- Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America.
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Abstract
Historically, most research on the biological origins of psychiatric illness has focused on individual diagnostic categories, studied in isolation. Mounting evidence indicates that nominally distinct psychiatric diagnoses are not separated by clear neurobiological boundaries. Here, we derive functional connectomic signatures in over 1,000 individuals, including patients presenting with different categories of impairment (psychosis), clinical diagnoses, and severity of illness as reflected in treatment seeking. Our analyses reveal features of connectome functioning that are commonly disrupted across distinct forms of pathology, scaling with clinical severity. Conversely, other aspects of network connectivity were preferentially disrupted in patients with psychotic illness. These data have important implications for the establishment of functional connectome fingerprints of severe mental disease. Converging evidence indicates that groups of patients with nominally distinct psychiatric diagnoses are not separated by sharp or discontinuous neurobiological boundaries. In healthy populations, individual differences in behavior are reflected in variability across the collective set of functional brain connections (functional connectome). These data suggest that the spectra of transdiagnostic symptom profiles observed in psychiatric patients may map onto detectable patterns of network function. To examine the manner through which neurobiological variation might underlie clinical presentation, we obtained fMRI data from over 1,000 individuals, including 210 diagnosed with a primary psychotic disorder or affective psychosis (bipolar disorder with psychosis and schizophrenia or schizoaffective disorder), 192 presenting with a primary affective disorder without psychosis (unipolar depression, bipolar disorder without psychosis), and 608 demographically matched healthy comparison participants recruited through a large-scale study of brain imaging and genetics. Here, we examine variation in functional connectomes across psychiatric diagnoses, finding striking evidence for disease connectomic “fingerprints” that are commonly disrupted across distinct forms of pathology and appear to scale as a function of illness severity. The presence of affective and psychotic illnesses was associated with graded disruptions in frontoparietal network connectivity (encompassing aspects of dorsolateral prefrontal, dorsomedial prefrontal, lateral parietal, and posterior temporal cortices). Conversely, other properties of network connectivity, including default network integrity, were preferentially disrupted in patients with psychotic illness, but not patients without psychotic symptoms. This work allows us to establish key biological and clinical features of the functional connectomes of severe mental disease.
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