1
|
Koike S, Tanaka SC, Hayashi T. Beyond case-control study in neuroimaging for psychiatric disorders: Harmonizing and utilizing the brain images from multiple sites. Neurosci Biobehav Rev 2025; 171:106063. [PMID: 40020797 DOI: 10.1016/j.neubiorev.2025.106063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Revised: 01/15/2025] [Accepted: 02/09/2025] [Indexed: 03/03/2025]
Abstract
Recent magnetic resonance imaging (MRI) research has advanced our understanding of brain pathophysiology in psychiatric disorders. This progress necessitates re-evaluation of the diagnostic system for psychiatric disorders based on MRI-based biomarkers, with implications for precise clinical diagnosis and optimal therapeutics. To achieve this goal, large-scale multi-site studies are essential to develop a standardized MRI database, with the analysis of several thousands of images and the incorporation of new data. A critical challenge in these studies is to minimize sampling and measurement biases in MRI studies to accurately capture the diversity of disease-derived biomarkers. Various techniques have been employed to consolidate datasets from multiple sites in case-control studies. Traveling subject harmonization stands out as a powerful tool that can differentiate measurement bias from sample variety and sampling bias. A non-linear statistical model for a normative trajectory across the lifespan also strengthens the database to mitigate sampling bias from known factors such as age and sex. These approaches can enhance the alterations between psychiatric disorders and integrate new data and follow-up scans into existing life-course trajectory, enhancing the reliability of machine learning classification and subtyping. Although this approach has been developed using T1-weighted structural image features, future research may extend this framework to other modalities and measures. The required sample size and methodological establishment are needed for future investigations, leading to novel insights into the brain pathophysiology of psychiatric disorders and the development of optimal therapeutics for bedside clinical applications. Sharing big data and their findings also need to be considered.
Collapse
Affiliation(s)
- Shinsuke Koike
- University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo 153-8902, Japan; Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan; The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), Tokyo 113-8654, Japan.
| | - Saori C Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto 619-0288 Japan; Division of Information Science, Nara Institute of Science and Technology, Nara 630-0192, Japan
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Hyogo 351-0198, Japan; Department of Brain Connectomics, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
| |
Collapse
|
2
|
Sun KY, Schmitt JE, Moore TM, Barzilay R, Almasy L, Schultz LM, Mackey AP, Kafadar E, Sha Z, Seidlitz J, Mallard TT, Cui Z, Li H, Fan Y, Fair DA, Satterthwaite TD, Keller AS, Alexander-Bloch A. Polygenic Risk, Psychopathology, and Personalized Functional Brain Network Topography in Adolescence. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2024.09.20.24314007. [PMID: 39399003 PMCID: PMC11469391 DOI: 10.1101/2024.09.20.24314007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/15/2024]
Abstract
Importance Functional brain networks are associated with both behavior and genetic factors. To uncover biological mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development. Objective To determine the relationships among transdiagnostic polygenic risk scores (PRSs), personalized functional brain networks (PFNs), and overall psychopathology (p-factor) during early adolescence. Design The Adolescent Brain Cognitive Development (ABCD) Study ⍰ is an ongoing longitudinal cohort study of 21 collection sites across the United States. Here, we conduct a cross-sectional analysis of ABCD baseline data, collected 2017-2018. Setting The ABCD Study ® is a multi-site community-based study. Participants The sample is largely recruited through school systems. Exclusion criteria included severe sensory, intellectual, medical, or neurological issues that interfere with protocol and scanner contraindications. Split-half subsets were used for cross-validation, matched on age, ethnicity, family structure, handedness, parental education, site, sex, and anesthesia exposure. Exposures Polygenic risk scores of transdiagnostic genetic factors F1 (PRS-F1) and F2 (PRS-F2) derived from adults in Psychiatric Genomic Consortium and UK Biobanks datasets. PRS-F1 indexes liability for common psychiatric symptoms and disorders related to mood disturbance; PRS-F2 indexes liability for rarer forms of mental illness characterized by mania and psychosis. Main Outcomes and Measures (1) P-factor derived from bifactor models of youth- and parent-reported mental health assessments. (2) Person-specific functional brain network topography derived from functional magnetic resonance imaging (fMRI) scans. Results Total participants included 11,873 youths ages 9-10 years old; 5,678 (47.8%) were female, and the mean (SD) age was 9.92 (0.62) years. PFN topography was found to be heritable ( N =7,459, 57.1% of vertices h 2 p FDR <0.05, mean h 2 =0.35). PRS-F1 was associated with p-factor ( N =5,815, r =0.12, 95% CI [0.09-0.15], p<0.001). Interindividual differences in functional network topography were associated with p-factor ( N =7,459, mean r =0.12), PRS-F1 ( N =3,982, mean r =0.05), and PRS-F2 ( N =3,982, mean r =0.08). Cortical maps of p-factor and PRS-F1 regression coefficients were highly correlated ( r =0.7, p =0.003). Conclusions and Relevance Polygenic risk for transdiagnostic adulthood psychopathology is associated with both p-factor and heritable PFN topography during early adolescence. These results advance our understanding of the developmental drivers of psychopathology. Key Points Question: What are the relationships among transdiagnostic polygenic risk scores (PRSs), personalized functional brain networks (PFNs), and overall psychopathology (p-factor) during early adolescence?Findings: In this cross-sectional analysis of the Adolescent Brain Cognitive Development (ABCD) Study ⍰ ( N =11,873, ages 9-10), we found that a PRS of common mood-related psychopathology in adulthood (PRS-F1) was associated with p-factor during early adolescence. Interindividual differences in p-factor, PRS-F1, and PRS-F2 (capturing more severe psychotic disorders in adulthood) were all robustly associated with PFN topography. Meaning: Polygenic risk for transdiagnostic adulthood psychopathology is associated with both p-factor and PFN topography during early adolescence.
Collapse
|
3
|
Zhang W, Qiu C, Lui S. Imaging Biomarker Studies of Antipsychotic-Naïve First-Episode Schizophrenia in China: Progress and Future Directions. Schizophr Bull 2025; 51:379-391. [PMID: 39841545 PMCID: PMC11908865 DOI: 10.1093/schbul/sbaf002] [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: 01/24/2025]
Abstract
BACKGROUND AND HYPOTHESIS Identifying biomarkers at onset and specifying the progression over the early course of schizophrenia is critical for better understanding of illness pathophysiology and providing novel information relevant to illness prognosis and treatment selection. Studies of antipsychotic-naïve first-episode schizophrenia in China are making contributions to this goal. STUDY DESIGN A review was conducted for how antipsychotic-naïve first-episode patients were identified and studied, the investigated biological measures, with a focus on neuroimaging, and how they extend the understanding of schizophrenia regarding the illness-related brain abnormality, treatment effect characterization and outcome prediction, and subtype discovery and patient stratification, in comparison to findings from western populations. Finally, how biomarker studies should be conducted in the future was also discussed. STUDY RESULTS Gray matter reduction has been most robust within temporo-frontal regions and cerebellum, whereas altered brain function has been most pronounced in cerebello-cortical connections and default mode network, each might be related to long-standing illness alterations and acute physiological alterations at measurement. By studying untreated patients, the progressive alterations in temporal and frontal regions and enlargements in bilateral putamen were found more likely effects of illness, not just treatment. Some of these changes were found with potential to predict clinical outcomes and differentiate biologically patient subgroups. CONCLUSIONS Mostly with data-driven approaches, the studies from China are helping identify candidate imaging biomarkers in schizophrenia that are related to early-stage illness, treatment effects, and biological subgroup differentiation. Future work is needed to translate these biomarkers for clinical application.
Collapse
Affiliation(s)
- Wenjing Zhang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Changjian Qiu
- Mental Health Center, West China Hospital, Sichuan University, Sichuan Clinical Medical Research Center for Mental Disorders, Chengdu 610041, China
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
| |
Collapse
|
4
|
Dudina AN, Tomyshev AS, Ilina EV, Romanov DV, Lebedeva IS. Structural and functional alterations in different types of delusions across schizophrenia spectrum: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2025; 136:111185. [PMID: 39486472 DOI: 10.1016/j.pnpbp.2024.111185] [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] [Received: 06/05/2024] [Revised: 10/22/2024] [Accepted: 10/27/2024] [Indexed: 11/04/2024]
Abstract
BACKGROUND Despite the high clinical role of delusions as a transnosological psychopathological phenomenon, the number of experimental studies on the different types of delusions across schizophrenia spectrum is still relatively small, and their results are somehow inconsistent. We aimed to understand the current state of knowledge regarding the structural and functional brain alterations in delusions to determine whether particular types of delusions are associated with specific brain changes and to identify common alterations underlying the formation and persistence of delusions regardless of their content. METHODS For this systematic review, we followed PRISMA guidelines to search in PubMed for English papers published between 1953 and September 30, 2023. The initial inclusion criteria for screening purposes were articles that investigated delusions or subclinical delusional beliefs in schizophrenia spectrum disorders, high clinical or genetic risk for schizophrenia using fMRI, sMRI or/and dwMRI methods. Exclusion criteria during the screening phase were articles that investigated lesion-induced or substance-induced delusions, delusions in Alzheimer's disease and other neurocognitive disorders, single case studies and non-human studies. The publication metadata were uploaded to the web-tool for working on systematic reviews, Rayyan. For each of the studies, a table was filled out with detailed information. RESULTS We found 1752 records, of which 95 full-text documents were reviewed and included in the current paper. Both nonspecific and particular types of delusions were associated with widespread structural and functional alterations. The most prominent areas affected across all types of delusions were the superior temporal cortex (predominantly left language processing areas), anterior cingulate/medial prefrontal cortex and insula. The most reproducible findings in paranoia may be alterations in the functioning of the amygdala and its interactions with other regions. Somatic delusions and delusional infestation were mostly characterized by alterations in the insula and thalamus. DISCUSSION The data are ambiguous; however, in general the predictive processing framework seems to be the most widely accepted approach to explaining different types of delusions. Aberrant prediction errors signaling during processing of social, self-generated and sensory information may lead to inaccuracies in assessing the intentions of others, self-relevancy of ambiguous stimuli, misattribution of self-generated actions and unusual sensations, which could provoke delusional ideation with persecutory, reference, control and somatic content correspondingly. However, currently available data are still insufficient to draw conclusions about the specific biological mechanisms of predictive coding account of delusions. Thus, further studies exploring more homogeneous groups and interaction of diagnoses by types of delusions are needed. There are also some limitations in this review. Studies that investigate delusions induced by lesions, substance abuse or neurodegeneration and studies using modalities other than fMRI, sMRI or dwMRI were not included in the review. Due to the relatively small number of publications, we systematized them based on a certain type of delusions, while the results could also be affected by the diagnosis of patients, the presence and type of therapy, illness duration etc.
Collapse
Affiliation(s)
- Anastasiia N Dudina
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation.
| | - Alexander S Tomyshev
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation
| | - Ekaterina V Ilina
- I.M. Sechenov First Moscow State Medical University, 8-2 Trubetskaya Str, Moscow 119991, Russian Federation
| | - Dmitriy V Romanov
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation; I.M. Sechenov First Moscow State Medical University, 8-2 Trubetskaya Str, Moscow 119991, Russian Federation
| | - Irina S Lebedeva
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation
| |
Collapse
|
5
|
Chen Y, Wang S, Zhang X, Yang Q, Hua M, Li Y, Qin W, Liu F, Liang M. Functional Connectivity-Based Searchlight Multivariate Pattern Analysis for Discriminating Schizophrenia Patients and Predicting Clinical Variables. Schizophr Bull 2024; 51:108-119. [PMID: 38819252 PMCID: PMC11661961 DOI: 10.1093/schbul/sbae084] [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: 06/01/2024]
Abstract
BACKGROUND Schizophrenia, a multifaceted psychiatric disorder characterized by functional dysconnectivity, poses significant challenges in clinical practice. This study explores the potential of functional connectivity (FC)-based searchlight multivariate pattern analysis (CBS-MVPA) to discriminate between schizophrenia patients and healthy controls while also predicting clinical variables. STUDY DESIGN We enrolled 112 schizophrenia patients and 119 demographically matched healthy controls. Resting-state functional magnetic resonance imaging data were collected, and whole-brain FC subnetworks were constructed. Additionally, clinical assessments and cognitive evaluations yielded a dataset comprising 36 clinical variables. Finally, CBS-MVPA was utilized to identify subnetworks capable of effectively distinguishing between the patient and control groups and predicting clinical scores. STUDY RESULTS The CBS-MVPA approach identified 63 brain subnetworks exhibiting significantly high classification accuracies, ranging from 62.2% to 75.6%, in distinguishing individuals with schizophrenia from healthy controls. Among them, 5 specific subnetworks centered on the dorsolateral superior frontal gyrus, orbital part of inferior frontal gyrus, superior occipital gyrus, hippocampus, and parahippocampal gyrus showed predictive capabilities for clinical variables within the schizophrenia cohort. CONCLUSION This study highlights the potential of CBS-MVPA as a valuable tool for localizing the information related to schizophrenia in terms of brain network abnormalities and capturing the relationship between these abnormalities and clinical variables, and thus, deepens our understanding of the neurological mechanisms of schizophrenia.
Collapse
Affiliation(s)
- Yayuan Chen
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging and Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
- School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging and The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Sijia Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging and Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xi Zhang
- School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging and The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Qingqing Yang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minghui Hua
- Department of Radiology, Chest Hospital, Tianjin University, Tianjin, China
| | - Yifan Li
- School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging and The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging and Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging and Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Key Laboratory of Functional Imaging and The Province and Ministry Cosponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Medical University, Tianjin, China
| |
Collapse
|
6
|
González-Peñas J, Alloza C, Brouwer R, Díaz-Caneja CM, Costas J, González-Lois N, Gallego AG, de Hoyos L, Gurriarán X, Andreu-Bernabeu Á, Romero-García R, Fañanás L, Bobes J, González-Pinto A, Crespo-Facorro B, Martorell L, Arrojo M, Vilella E, Gutiérrez-Zotes A, Perez-Rando M, Moltó MD, Buimer E, van Haren N, Cahn W, O'Donovan M, Kahn RS, Arango C, Pol HH, Janssen J, Schnack H. Accelerated Cortical Thinning in Schizophrenia Is Associated With Rare and Common Predisposing Variation to Schizophrenia and Neurodevelopmental Disorders. Biol Psychiatry 2024; 96:376-389. [PMID: 38521159 DOI: 10.1016/j.biopsych.2024.03.011] [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] [Received: 08/17/2023] [Revised: 02/22/2024] [Accepted: 03/05/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Schizophrenia is a highly heritable disorder characterized by increased cortical thinning throughout the life span. Studies have reported a shared genetic basis between schizophrenia and cortical thickness. However, no genes whose expression is related to abnormal cortical thinning in schizophrenia have been identified. METHODS We conducted linear mixed models to estimate the rates of accelerated cortical thinning across 68 regions from the Desikan-Killiany atlas in individuals with schizophrenia compared with healthy control participants from a large longitudinal sample (ncases = 169 and ncontrols = 298, ages 16-70 years). We studied the correlation between gene expression data from the Allen Human Brain Atlas and accelerated thinning estimates across cortical regions. Finally, we explored the functional and genetic underpinnings of the genes that contribute most to accelerated thinning. RESULTS We found a global pattern of accelerated cortical thinning in individuals with schizophrenia compared with healthy control participants. Genes underexpressed in cortical regions that exhibit this accelerated thinning were downregulated in several psychiatric disorders and were enriched for both common and rare disrupting variation for schizophrenia and neurodevelopmental disorders. In contrast, none of these enrichments were observed for baseline cross-sectional cortical thickness differences. CONCLUSIONS Our findings suggest that accelerated cortical thinning, rather than cortical thickness alone, serves as an informative phenotype for neurodevelopmental disruptions in schizophrenia. We highlight the genetic and transcriptomic correlates of this accelerated cortical thinning, emphasizing the need for future longitudinal studies to elucidate the role of genetic variation and the temporal-spatial dynamics of gene expression in brain development and aging in schizophrenia.
Collapse
Affiliation(s)
- Javier González-Peñas
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain.
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Rachel Brouwer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Javier Costas
- Instituto de Investigación Sanitària de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde, Santiago de Compostela, Galicia, Spain
| | - Noemí González-Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Ana Guil Gallego
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain
| | - Xaquín Gurriarán
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Álvaro Andreu-Bernabeu
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain
| | - Rafael Romero-García
- Department of Medical Physiology and Biophysics, Instituto de Biomedicina de Sevilla, HUVR/CSIC/Universidad de Sevilla/CIBERSAM, Instituto de Salud Carlos III, Sevilla, Spain; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Lourdes Fañanás
- CIBERSAM, Madrid, Spain; Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Julio Bobes
- CIBERSAM, Madrid, Spain; Faculty of Medicine and Health Sciences-Psychiatry, Universidad de Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias, Instituto de Neurociencias del Principado de Asturias, Oviedo, Spain
| | - Ana González-Pinto
- CIBERSAM, Madrid, Spain; BIOARABA Health Research Institute, Organización Sanitaria Integrada Araba, University Hospital, University of the Basque Country, Vitoria, Spain
| | - Benedicto Crespo-Facorro
- CIBERSAM, Madrid, Spain; Hospital Universitario Virgen del Rocío, Department of Psychiatry, Universidad de Sevilla, Sevilla, Spain
| | - Lourdes Martorell
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Manuel Arrojo
- Instituto de Investigación Sanitària de Santiago de Compostela, Complexo Hospitalario Universitario de Santiago de Compostela, Servizo Galego de Saúde, Santiago de Compostela, Galicia, Spain
| | - Elisabet Vilella
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Alfonso Gutiérrez-Zotes
- CIBERSAM, Madrid, Spain; Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili-Centres de Recerca de Catalunya, Universitat Rovira i Virgili, Reus, Spain
| | - Marta Perez-Rando
- Fundación Investigación Hospital Clínico de València, Fundación Investigación Hospital Clínico de Valencia, València, Spain; Unidad de Neurobiología, Instituto de Biotecnología y Biomedicina, Universitat de València, València, Spain
| | - María Dolores Moltó
- CIBERSAM, Madrid, Spain; Unidad de Neurobiología, Instituto de Biotecnología y Biomedicina, Universitat de València, València, Spain; Department of Genetics, Universitat de València, Campus of Burjassot, València, Spain
| | - Elizabeth Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Neeltje van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Rotterdam, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Altrecht Mental Health Institute, Altrecht Science, Utrecht, the Netherlands
| | - Michael O'Donovan
- Medical Research Council for Neuropsychiatric Genetics and Genomics and Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Hilleke Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitària Gregorio Marañón, Madrid, Spain; CIBERSAM, Madrid, Spain; Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hugo Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| |
Collapse
|
7
|
Reinen JM, Polosecki P, Castro E, Corcoran CM, Cecchi GA, Colibazzi T. Multimodal fusion of brain signals for robust prediction of psychosis transition. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:54. [PMID: 38773120 PMCID: PMC11109212 DOI: 10.1038/s41537-024-00464-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 03/15/2024] [Indexed: 05/23/2024]
Abstract
The prospective study of youths at clinical high risk (CHR) for psychosis, including neuroimaging, can identify neural signatures predictive of psychosis outcomes using algorithms that integrate complex information. Here, to identify risk and psychosis conversion, we implemented multiple kernel learning (MKL), a multimodal machine learning approach allowing patterns from each modality to inform each other. Baseline multimodal scans (n = 74, 11 converters) included structural, resting-state functional imaging, and diffusion-weighted data. Multimodal MKL outperformed unimodal models (AUC = 0.73 vs. 0.66 in predicting conversion). Moreover, patterns learned by MKL were robust to training set variations, suggesting it can identify cross-modality redundancies and synergies to stabilize the predictive pattern. We identified many predictors consistent with the literature, including frontal cortices, cingulate, thalamus, and striatum. This highlights the advantage of methods that leverage the complex pathophysiology of psychosis.
Collapse
Affiliation(s)
- Jenna M Reinen
- IBM T.J. Watson Research Center, Yorktown Heights, NY, USA.
| | | | - Eduardo Castro
- IBM T.J. Watson Research Center, Yorktown Heights, NY, USA
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Tiziano Colibazzi
- Department of Psychiatry, The New York State Psychiatric Institute, Columbia College of Physicians and Surgeons, New York, NY, USA
| |
Collapse
|
8
|
Zhu Y, Maikusa N, Radua J, Sämann PG, Fusar-Poli P, Agartz I, Andreassen OA, Bachman P, Baeza I, Chen X, Choi S, Corcoran CM, Ebdrup BH, Fortea A, Garani RR, Glenthøj BY, Glenthøj LB, Haas SS, Hamilton HK, Hayes RA, He Y, Heekeren K, Kasai K, Katagiri N, Kim M, Kristensen TD, Kwon JS, Lawrie SM, Lebedeva I, Lee J, Loewy RL, Mathalon DH, McGuire P, Mizrahi R, Mizuno M, Møller P, Nemoto T, Nordholm D, Omelchenko MA, Raghava JM, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Smigielski L, Sugranyes G, Takahashi T, Tamnes CK, Tang J, Theodoridou A, Tomyshev AS, Uhlhaas PJ, Værnes TG, van Amelsvoort TAMJ, Waltz JA, Westlye LT, Zhou JH, Thompson PM, Hernaus D, Jalbrzikowski M, Koike S. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk. Mol Psychiatry 2024; 29:1465-1477. [PMID: 38332374 PMCID: PMC11189817 DOI: 10.1038/s41380-024-02426-7] [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: 08/16/2023] [Revised: 12/22/2023] [Accepted: 01/08/2024] [Indexed: 02/10/2024]
Abstract
Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.
Collapse
Affiliation(s)
- Yinghan Zhu
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Norihide Maikusa
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Instituto de Salud Carlos III, Universitat de Barcelona, Barcelona, Spain
| | | | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Ingrid Agartz
- 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
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Peter Bachman
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Xiaogang Chen
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Sunah Choi
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
- Mental Illness Research, Education, and Clinical Center, James J Peters VA Medical Center, New York City, NY, USA
| | - Bjørn H Ebdrup
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic Barcelona, Fundació Clínic Recerca Biomèdica, Universitat de Barcelona, Barcelona, Spain
| | - Ranjini Rg Garani
- Douglas Research Center; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Birte Yding Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Louise Birkedal Glenthøj
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Holly K Hamilton
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
| | - Rebecca A Hayes
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
| | - Ying He
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, the Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Karsten Heekeren
- Department of Psychiatry and Psychotherapy I, LVR-Hospital Cologne, Cologne, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence at The University of Tokyo Institutes for Advanced Study (WPI-IRCN), The University of Tokyo, Tokyo, Japan
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyok, Japan
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | - Tina D Kristensen
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
| | | | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russian Federation
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Health Care System, San Francisco, CA, USA
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Romina Mizrahi
- Douglas Research Center; Department of Psychiatry, McGill University, Montreal, QC, Canada
| | | | - Paul Møller
- Department for Mental Health Research and Development, Division of Mental Health and Addiction, Vestre Viken Hospital Trust, Drammen, Norway
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyok, Japan
| | - Dorte Nordholm
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Maria A Omelchenko
- Department of Youth Psychiatry, Mental Health Research Center, Moscow, Russian Federation
| | - Jayachandra M Raghava
- Centre for Neuropsychiatric Schizophrenia Research (CNSR), Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Physiology, Nuclear Medicine and PET, Functional Imaging, University of Copenhagen Copenhagen, Copenhagen, Denmark
| | - Jan I Røssberg
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wulf Rössler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Dean F Salisbury
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Lukasz Smigielski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Christian K Tamnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Zhejiang, China
- Key Laboratory of Medical Neurobiology of Zhejiang Province, School of Medicine, Zhejiang University, Zhejiang, China
| | - Anastasia Theodoridou
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Alexander S Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow, Russian Federation
| | - Peter J Uhlhaas
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin Berlin, Berlin, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Tor G Værnes
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Early Intervention in Psychosis Advisory Unit for South-East Norway, TIPS Sør-Øst, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Therese A M J van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - James A Waltz
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore County, Baltimore, MD, USA
| | - Lars T Westlye
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Juan H Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Cambridge, MA, USA
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo, Japan.
| |
Collapse
|
9
|
Jo YT, Joo SW, Choi W, Joe S, Lee J. White matter tract alterations in schizophrenia identified by DTI-based probabilistic tractography: a multisite harmonisation study. Acta Neuropsychiatr 2024; 37:e47. [PMID: 38348668 DOI: 10.1017/neu.2024.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/25/2025]
Abstract
INTRODUCTION It has been suggested that schizophrenia involves dysconnectivity between functional brain regions and also the white matter structural disorganisation. Thus, diffusion tensor imaging (DTI) has widely been used for studying schizophrenia. However, most previous studies have used the region of interest (ROI) based approach. We, therefore, performed the probabilistic tractography method in this study to reveal the alterations of white matter tracts in the schizophrenia brain. METHODS A total of four different datasets consisted of 189 patients with schizophrenia and 213 healthy controls were investigated. We performed retrospective harmonisation of raw diffusion MRI data by dMRIharmonisation and used the FMRIB Software Library (FSL) for probabilistic tractography. The connectivities between different ROIs were then compared between patients and controls. Furthermore, we evaluated the relationship between the connection probabilities and the symptoms and cognitive measures in patients with schizophrenia. RESULTS After applying Bonferroni correction for multiple comparisons, 11 different tracts showed significant differences between patients with schizophrenia and healthy controls. Many of these tracts were associated with the basal ganglia or cortico-striatal structures, which aligns with the current literature highlighting striatal dysfunction. Moreover, we found that these tracts demonstrated statistically significant relationships with few cognitive measures related to language, executive function, or processing speed. CONCLUSION We performed probabilistic tractography using a large, harmonised dataset of diffusion MRI data, which enhanced the statistical power of our study. It is important to note that most of the tracts identified in this study, particularly callosal and cortico-striatal streamlines, have been previously implicated in schizophrenia within the current literature. Further research with harmonised data focusing specifically on these brain regions could be recommended.
Collapse
Affiliation(s)
- Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea
| | - Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Woohyeok Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Soohyun Joe
- Brain Laboratory in the Department of Psychiatry, School of Medicine, University of California, San Diego, CA, USA
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| |
Collapse
|
10
|
Krcmar M, Wannan CMJ, Lavoie S, Allott K, Davey CG, Yuen HP, Whitford T, Formica M, Youn S, Shetty J, Beedham R, Rayner V, Murray G, Polari A, Gawęda Ł, Koren D, Sass L, Parnas J, Rasmussen AR, McGorry P, Hartmann JA, Nelson B. The self, neuroscience and psychosis study: Testing a neurophenomenological model of the onset of psychosis. Early Interv Psychiatry 2024; 18:153-164. [PMID: 37394278 DOI: 10.1111/eip.13448] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 04/17/2023] [Accepted: 06/07/2023] [Indexed: 07/04/2023]
Abstract
AIM Basic self disturbance is a putative core vulnerability marker of schizophrenia spectrum disorders. The primary aims of the Self, Neuroscience and Psychosis (SNAP) study are to: (1) empirically test a previously described neurophenomenological self-disturbance model of psychosis by examining the relationship between specific clinical, neurocognitive, and neurophysiological variables in UHR patients, and (2) develop a prediction model using these neurophenomenological disturbances for persistence or deterioration of UHR symptoms at 12-month follow-up. METHODS SNAP is a longitudinal observational study. Participants include 400 UHR individuals, 100 clinical controls with no attenuated psychotic symptoms, and 50 healthy controls. All participants complete baseline clinical and neurocognitive assessments and electroencephalography. The UHR sample are followed up for a total of 24 months, with clinical assessment completed every 6 months. RESULTS This paper presents the protocol of the SNAP study, including background rationale, aims and hypotheses, design, and assessment procedures. CONCLUSIONS The SNAP study will test whether neurophenomenological disturbances associated with basic self-disturbance predict persistence or intensification of UHR symptomatology over a 2-year follow up period, and how specific these disturbances are to a clinical population with attenuated psychotic symptoms. This may ultimately inform clinical care and pathoaetiological models of psychosis.
Collapse
Affiliation(s)
- Marija Krcmar
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Cassandra M J Wannan
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Suzie Lavoie
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Kelly Allott
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher G Davey
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
| | - Hok Pan Yuen
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Thomas Whitford
- School of Psychology, University of New South Wales (UNSW), Kensington, New South Wales, Australia
| | - Melanie Formica
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Sarah Youn
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Jashmina Shetty
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Rebecca Beedham
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Victoria Rayner
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Graham Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Andrea Polari
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Łukasz Gawęda
- Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Warsaw, Poland
| | - Dan Koren
- Psychology Department, University of Haifa, Haifa, Israel
| | - Louis Sass
- Department of Clinical Psychology, GSAPP-Rutgers University, Piscataway, New Jersey, USA
| | - Josef Parnas
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Center for Subjectivity Research, University of Copenhagen, Copenhagen, Denmark
| | - Andreas R Rasmussen
- Orygen, Parkville, Parkville, Victoria, Australia
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Patrick McGorry
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Jessica A Hartmann
- Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Barnaby Nelson
- Orygen, Parkville, Parkville, Victoria, Australia
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
11
|
Forsyth JK, Bearden CE. Rethinking the First Episode of Schizophrenia: Identifying Convergent Mechanisms During Development and Moving Toward Prediction. Am J Psychiatry 2023; 180:792-804. [PMID: 37908094 DOI: 10.1176/appi.ajp.20230736] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Affiliation(s)
- Jennifer K Forsyth
- Department of Psychology, University of Washington, Seattle (Forsyth); Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Behavioral Sciences, and Department of Psychology, University of California, Los Angeles (Bearden)
| | - Carrie E Bearden
- Department of Psychology, University of Washington, Seattle (Forsyth); Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Behavioral Sciences, and Department of Psychology, University of California, Los Angeles (Bearden)
| |
Collapse
|
12
|
Ku BS, Collins M, Anglin DM, Diomino AM, Addington J, Bearden CE, Cadenhead KS, Cannon TD, Cornblatt BA, Druss BG, Keshavan M, Mathalon DH, Perkins DO, Stone WS, Tsuang MT, Woods SW, Walker EF. Associations between childhood ethnoracial minority density, cortical thickness, and social engagement among minority youth at clinical high-risk for psychosis. Neuropsychopharmacology 2023; 48:1707-1715. [PMID: 37438421 PMCID: PMC10579230 DOI: 10.1038/s41386-023-01649-6] [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: 04/28/2023] [Revised: 06/16/2023] [Accepted: 06/29/2023] [Indexed: 07/14/2023]
Abstract
An ethnoracial minority density (EMD) effect in studies of psychotic spectrum disorders has been observed, whereby the risk of psychosis in ethnoracial minority group individuals is inversely related to the proportion of minorities in their area of residence. The authors investigated the relationships among area-level EMD during childhood, cortical thickness (CT), and social engagement (SE) in clinical high risk for psychosis (CHR-P) youth. Data were collected as part of the North American Prodrome Longitudinal Study. Participants included 244 ethnoracial minoritized (predominantly Hispanic, Asian and Black) CHR-P youth and ethnoracial minoritized healthy controls. Among youth at CHR-P (n = 164), lower levels of EMD during childhood were associated with reduced CT in the right fusiform gyrus (adjusted β = 0.54; 95% CI 0.17 to 0.91) and right insula (adjusted β = 0.40; 95% CI 0.05 to 0.74). The associations between EMD and CT were significantly moderated by SE: among youth with lower SE (SE at or below the median, n = 122), lower levels of EMD were significantly associated with reduced right fusiform gyrus CT (adjusted β = 0.72; 95% CI 0.29 to 1.14) and reduced right insula CT (adjusted β = 0.57; 95% CI 0.18 to 0.97). However, among those with greater SE (n = 42), the associations between EMD and right insula and fusiform gyrus CT were not significant. We found evidence that lower levels of ethnic density during childhood were associated with reduced cortical thickness in regional brain regions, but this association may be buffered by greater levels of social engagement.
Collapse
Affiliation(s)
- Benson S Ku
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
| | - Meghan Collins
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Deidre M Anglin
- Department of Psychology, The City College of New York, City University of New York, New York, NY, USA
- The Graduate Center, City University of New York, New York, NY, USA
| | - Anthony M Diomino
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
| | - Kristin S Cadenhead
- Department of Psychology, The City College of New York, City University of New York, New York, NY, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Barbara A Cornblatt
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Benjamin G Druss
- Department of Health Policy and Management, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Matcheri Keshavan
- Harvard Medical School, Departments of Psychiatry at Massachusetts Mental Health Center Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Massachusetts General Hospital, Boston, MA, USA
| | - Daniel H Mathalon
- Department of Psychiatry, University of California, and San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - William S Stone
- Harvard Medical School, Departments of Psychiatry at Massachusetts Mental Health Center Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Massachusetts General Hospital, Boston, MA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Scott W Woods
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| |
Collapse
|
13
|
Camprodon-Boadas P, De la Serna E, Plana MT, Flamarique I, Lázaro L, Borràs R, Baeza I, Tasa-Vinyals E, Sugranyes G, Ortiz AE, Castro-Fornieles J. Delusional beliefs in adolescents with anorexia nervosa, obsessive-compulsive disorder, or first-episode psychosis: A comparative study. Psychiatry Res 2023; 328:115490. [PMID: 37748237 DOI: 10.1016/j.psychres.2023.115490] [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] [Received: 05/25/2023] [Revised: 09/13/2023] [Accepted: 09/21/2023] [Indexed: 09/27/2023]
Abstract
Delusional thinking is a key symptom of first-episode psychosis (FEP), but it has also been studied in obsessive-compulsive disorder (OCD) and anorexia nervosa (AN). This study aimed to analyze the psychometric properties of the Brown Assessment of Beliefs Scale (BABS) in a sample of adolescents diagnosed with a FEP, AN, or OCD, and to compare delusional thinking among the three samples. The sample comprised 60 patients in three groups of 20 diagnosed with OCD, AN, or FEP. Participants underwent assessment by diagnostic interview, the BABS scale, and a measure of depressive symptomatology. Specific instruments were also used to assess the main symptomatology of each disorder. The BABS had good internal consistency, and high validity and reliability. The OCD group scored significantly lower than the other two groups in all scale items except for items 4 (fixation of ideas), 6 (insight), and 7 (delusions of reference). A significant difference only existed between the AN and FEP groups for item 7 (delusions of reference). The BABS scale is a valid and reliable tool for assessing delusionality in adolescents diagnosed with OCD, AN, or FEP, with evidence of marked differences between the disorders. Assessing these symptoms could influence management, helping to improve treatment adherence and prognosis.
Collapse
Affiliation(s)
- Patricia Camprodon-Boadas
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain
| | - Elena De la Serna
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain.
| | - Maria Teresa Plana
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Itziar Flamarique
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain
| | - Luisa Lázaro
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Spain
| | - Roger Borràs
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Spain
| | - Elisabet Tasa-Vinyals
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Spain
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain
| | - Ana Encarnación Ortiz
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Josefina Castro-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, 2021SGR01319, Institut Clinic de Neurociències, Hospital Clínic de Barcelona, Barcelona, Spain; Fundació de Recerca Clínic Barcelona-Institut d´Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM - ISCIII, Spain; Department of Medicine, Institute of Neuroscience, University of Barcelona, Spain
| |
Collapse
|
14
|
Ruiz-Torras S, Gudayol-Ferré E, Fernández-Vazquez O, Cañete-Massé C, Peró-Cebollero M, Guàrdia-Olmos J. Hypoconnectivity networks in schizophrenia patients: A voxel-wise meta-analysis of Rs-fMRI. Int J Clin Health Psychol 2023; 23:100395. [PMID: 37533450 PMCID: PMC10392089 DOI: 10.1016/j.ijchp.2023.100395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/05/2023] [Indexed: 08/04/2023] Open
Abstract
In recent years several meta-analyses regarding resting-state functional connectivity in patients with schizophrenia have been published. The authors have used different data analysis techniques: regional homogeneity, seed-based data analysis, independent component analysis, and amplitude of low frequencies. Hence, we aim to perform a meta-analysis to identify connectivity networks with different activation patterns between people diagnosed with schizophrenia and healthy controls using voxel-wise analysis. METHOD We collected primary studies exploring whole brain connectivity by functional magnetic resonance imaging at rest in patients with schizophrenia compared with healthy controls. We identified 25 studies included high-quality studies that included 1285 patients with schizophrenia and 1279 healthy controls. RESULTS The results indicate hypoactivation in the right precentral gyrus and the left superior temporal gyrus of patients with schizophrenia compared with healthy controls. CONCLUSIONS These regions have been linked with some clinical symptoms usually present in Plea with schizophrenia, such as auditory verbal hallucinations, formal thought disorder, and the comprehension and production of gestures.
Collapse
Affiliation(s)
- Silvia Ruiz-Torras
- Clínica Psicològica de la Universitat de Barcelona, Fundació Josep Finestres, Universitat de Barcelona, Spain
| | | | | | - Cristina Cañete-Massé
- Facultat de Psicologia, Secció de Psicologia Quantitativa, Universitat de Barcelona, Spain
- UB Institute of Complex Systems, Universitat de Barcelona, Spain
| | - Maribel Peró-Cebollero
- Facultat de Psicologia, Secció de Psicologia Quantitativa, Universitat de Barcelona, Spain
- UB Institute of Complex Systems, Universitat de Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, Spain
| | - Joan Guàrdia-Olmos
- Facultat de Psicologia, Secció de Psicologia Quantitativa, Universitat de Barcelona, Spain
- UB Institute of Complex Systems, Universitat de Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, Spain
| |
Collapse
|
15
|
Matéos M, Hacein-Bey L, Hanafi R, Mathys L, Amad A, Pruvo JP, Krystal S. Advanced imaging in first episode psychosis: a systematic review. J Neuroradiol 2023; 50:464-469. [PMID: 37028754 DOI: 10.1016/j.neurad.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 03/31/2023] [Accepted: 04/04/2023] [Indexed: 04/09/2023]
Abstract
First-episode psychosis (FEP) is defined as the first occurrence of delusions, hallucinations, or psychic disorganization of significant magnitude, lasting more than 7 days. Evolution is difficult to predict since the first episode remains isolated in one third of cases, while recurrence occurs in another third, and the last third progresses to a schizo-affective disorder. It has been suggested that the longer psychosis goes unnoticed and untreated, the more severe the probability of relapse and recovery. MRI has become the gold standard for imaging psychiatric disorders, especially first episode psychosis. Besides ruling out some neurological conditions that may have psychiatric manifestations, advanced imaging techniques allow for identifying imaging biomarkers of psychiatric disorders. We performed a systematic review of the literature to determine how advanced imaging in FEP may have high diagnostic specificity and predictive value regarding the evolution of disease.
Collapse
Affiliation(s)
- Marjorie Matéos
- Lille University Hospital Center, Department of Neuroradiology, Lille, France.
| | - Lotfi Hacein-Bey
- Neuroradiology, Radiology Department, University of California Davis School of Medicine, Sacramento, CA, 95817, USA
| | - Riyad Hanafi
- Lille University Hospital Center, Department of Neuroradiology, Lille, France; Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France
| | - Luc Mathys
- Lille University Hospital Center, Department of Neuroradiology, Lille, France
| | - Ali Amad
- Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France; Department of neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jean-Pierre Pruvo
- Lille University Hospital Center, Department of Neuroradiology, Lille, France; Univ. Lille, Inserm, CHU Lille, U1172 - LilNCog - Lille Neuroscience & Cognition, F-59000 Lille, France
| | - Sidney Krystal
- Lille University Hospital Center, Department of Neuroradiology, Lille, France; Radiology Department, A. de Rothschild Foundation Hospital, Paris, France; Neurospin, CEA, Université Paris-Saclay, Gif-Sur-Yvette, Paris, France
| |
Collapse
|
16
|
Walia N, Eratne D, Loi SM, Farrand S, Li QX, Malpas CB, Varghese S, Walterfang M, Evans AH, Parker S, Collins SJ, Masters CL, Velakoulis D. Cerebrospinal fluid neurofilament light and cerebral atrophy in younger-onset dementia and primary psychiatric disorders. Intern Med J 2023; 53:1564-1569. [PMID: 36314730 DOI: 10.1111/imj.15956] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 10/03/2022] [Indexed: 09/26/2023]
Abstract
BACKGROUND AND AIMS Neurodegeneration underpins the pathological processes of younger-onset dementia (YOD) and has been implicated in primary psychiatric disorders (PSYs). Cerebrospinal fluid (CSF) neurofilament light (NfL) has been used to investigate neurodegeneration severity through correlation with structural brain changes in various conditions, but has seldom been evaluated in YOD and PSYs. METHODS This retrospective study included patients with YOD or PSYs with magnetic resonance imaging (MRI) of the brain and CSF NfL analysis. Findings from brain MRI were analysed using automated volumetry (volBrain) to measure white matter (WM), grey matter (GM) and whole brain (WB) volumes expressed as percentages of total intracranial volume. Correlations between NfL and brain volume measurements were computed whilst adjusting for age. RESULTS Seventy patients (47 with YOD and 23 with PSY) were identified. YOD types included Alzheimer disease and behavioural variant frontotemporal dementia. PSY included schizophrenia and major depressive disorder. MRI brain sequences were either fast spoiler gradient-echo (FSPGR) or magnetization-prepared rapid acquisition gradient-echo (MPRAGE). In the total cohort, higher NfL was associated with reduced WB in the FSPGR and MPRAGE sequences (r = -0.402 [95% confidence interval (CI), -0.593 to -0.147], P = 0.008 and r = -0.625 [95% CI, -0.828 to -0.395], P < 0.001, respectively). Higher NfL was related to reduced GM in FSPGR (r = 0.385 [95% CI, -0.649 to -0.014], P = 0.017) and reduced WM in MPRAGE (r = -0.650 [95% CI, -0.777 to -0.307], P < 0.001). Similar relationships were seen in YOD, but not in PSY. CONCLUSION Higher CSF NfL is related to brain atrophy in YOD, further supporting its use as a nonspecific marker of neurodegeneration severity.
Collapse
Affiliation(s)
- Nirbaanjot Walia
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre & Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| | - Samantha M Loi
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre & Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sarah Farrand
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre & Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| | - Qiao-Xin Li
- National Dementia and Diagnostics Laboratory, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Neurology, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Shiji Varghese
- National Dementia and Diagnostics Laboratory, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mark Walterfang
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre & Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| | - Andrew H Evans
- Department of Neurology, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Shaun Parker
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Steven J Collins
- National Dementia and Diagnostics Laboratory, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria, Australia
| | - Colin L Masters
- National Dementia and Diagnostics Laboratory, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Melbourne Neuropsychiatry Centre & Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
| |
Collapse
|
17
|
Todd J, Salisbury D, Michie PT. Why mismatch negativity continues to hold potential in probing altered brain function in schizophrenia. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2023; 2:e144. [PMID: 38867817 PMCID: PMC11114358 DOI: 10.1002/pcn5.144] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 08/21/2023] [Accepted: 08/30/2023] [Indexed: 06/14/2024]
Abstract
The brain potential known as mismatch negativity (MMN) is one of the most studied indices of altered brain function in schizophrenia. This review looks at what has been learned about MMN in schizophrenia over the last three decades and why the level of interest and activity in this field of research remains strong. A diligent consideration of available evidence suggests that MMN can serve as a biomarker in schizophrenia, but perhaps not the kind of biomarker that early research supposed. This review concludes that MMN measurement is likely to be most useful as a monitoring and response biomarker enabling tracking of an underlying pathology and efficacy of interventions, respectively. The role of, and challenges presented by, pre-clinical models is discussed as well as the merits of different methodologies that can be brought to bear in pursuing a deeper understanding of pathophysiology that might explain smaller MMN in schizophrenia.
Collapse
Affiliation(s)
- Juanita Todd
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
| | - Dean Salisbury
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Patricia T. Michie
- School of Psychological SciencesUniversity of NewcastleNewcastleNew South WalesAustralia
| |
Collapse
|
18
|
Roach BJ, Hirano Y, Ford JM, Spencer KM, Mathalon DH. Phase Delay of the 40 Hz Auditory Steady-State Response Localizes to Left Auditory Cortex in Schizophrenia. Clin EEG Neurosci 2023; 54:370-378. [PMID: 36213937 PMCID: PMC10311936 DOI: 10.1177/15500594221130896] [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: 01/28/2022] [Revised: 07/11/2022] [Accepted: 09/01/2022] [Indexed: 11/16/2022]
Abstract
Background. The auditory steady state response (ASSR) is generated in bilateral auditory cortex and is the most used electroencephalographic (EEG) or magnetoencephalographic measure of gamma band abnormalities in schizophrenia. While the finding of reduced 40-Hz ASSR power and phase consistency in schizophrenia have been replicated many times, the 40-Hz ASSR phase locking angle (PLA), which assesses oscillation latency or phase delay, has rarely been examined. Furthermore, whether 40-Hz ASSR phase delay in schizophrenia is lateralized or common to left and right auditory cortical generators is unknown. Methods. Previously analyzed EEG data recorded from 24 schizophrenia patients and 24 healthy controls presented with 20-, 30-, and 40-Hz click trains to elicit ASSRs were re-analyzed to assess PLA in source space. Dipole moments in the right and left hemisphere were used to assess both frequency and hemisphere specificity of ASSR phase delay in schizophrenia. Results. Schizophrenia patients exhibited significantly reduced (ie, phase delayed) 40-Hz PLA in the left, but not the right, hemisphere, but their 20- and 30-Hz PLA values were normal. This left-lateralized 40-Hz phase delay was unrelated to symptoms or to previously reported left-lateralized PLF reductions in the schizophrenia patients. Conclusions. Consistent with sensor-based studies, the 40-Hz ASSR source-localized to left, but not right, auditory cortex was phase delayed in schizophrenia. Consistent with prior studies showing left temporal lobe volume deficits in schizophrenia, our findings suggest sluggish entrainment to 40-Hz auditory stimulation specific to left auditory cortex that are distinct from well-established deficits in gamma ASSR power and phase synchrony.
Collapse
Affiliation(s)
- Brian J. Roach
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, USA
- Northern California Institute for Research and Education (NCIRE), San Francisco, USA
| | - Yoji Hirano
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, Boston, USA
- Department of Psychiatry, Harvard Medical School, Boston, USA
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Judith M. Ford
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, USA
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, USA
| | - Kevin M. Spencer
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, Boston, USA
- Department of Psychiatry, Harvard Medical School, Boston, USA
| | - Daniel H. Mathalon
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, USA
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, USA
| |
Collapse
|
19
|
Mamah D. A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2023; 8:e230005. [PMID: 37427077 PMCID: PMC10327607 DOI: 10.20900/jpbs.20230005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.
Collapse
Affiliation(s)
- Daniel Mamah
- Department of Psychiatry, Washington University Medical School, St. Louis, MO, 63110, USA
| |
Collapse
|
20
|
Collins MA, Ji JL, Chung Y, Lympus CA, Afriyie-Agyemang Y, Addington JM, Goodyear BG, Bearden CE, Cadenhead KS, Mirzakhanian H, Tsuang MT, Cornblatt BA, Carrión RE, Keshavan M, Stone WS, Mathalon DH, Perkins DO, Walker EF, Woods SW, Powers AR, Anticevic A, Cannon TD. Accelerated cortical thinning precedes and predicts conversion to psychosis: The NAPLS3 longitudinal study of youth at clinical high-risk. Mol Psychiatry 2023; 28:1182-1189. [PMID: 36434057 PMCID: PMC10005940 DOI: 10.1038/s41380-022-01870-7] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 10/27/2022] [Accepted: 11/02/2022] [Indexed: 11/27/2022]
Abstract
Progressive grey matter loss has been demonstrated among clinical high-risk (CHR) individuals who convert to psychosis, but it is unknown whether these changes occur prior to psychosis onset. Identifying illness-related neurobiological mechanisms that occur prior to conversion is essential for targeted early intervention. Among participants in the third wave of the North American Prodrome Longitudinal Study (NAPLS3), this report investigated if steeper cortical thinning was observable prior to psychosis onset among CHR individuals who ultimately converted (CHR-C) and assessed the shortest possible time interval in which rates of cortical thinning differ between CHR-C, CHR non-converters (CHR-NC), and health controls (HC). 338 CHR-NC, 42 CHR-C, and 62 HC participants (age 19.3±4.2, 44.8% female, 52.5% racial/ethnic minority) completed up to 5 MRI scans across 8 months. Accelerated thinning among CHR-C compared to CHR-NC and HC was observed in multiple prefrontal, temporal, and parietal cortical regions. CHR-NC also exhibited accelerated cortical thinning compared to HC in several of these areas. Greater percent decrease in cortical thickness was observed among CHR-C compared to other groups across 2.9±1.8 months, on average, in several cortical areas. ROC analyses discriminating CHR-C from CHR-NC by percent thickness change in a left hemisphere region of interest, scanner, age, age2, and sex had an AUC of 0.74, with model predictive power driven primarily by percent thickness change. Findings indicate that accelerated cortical thinning precedes psychosis onset and differentiates CHR-C from CHR-NC and HC across short time intervals. Mechanisms underlying cortical thinning may provide novel treatment targets prior to psychosis onset.
Collapse
Affiliation(s)
| | - Jie Lisa Ji
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
| | - Yoonho Chung
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Belmont, MA, USA
- Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, USA
| | - Cole A Lympus
- Department of Psychology, Yale University, New Haven, CT, USA
| | | | - Jean M Addington
- Department of Psychiatry, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Bradley G Goodyear
- Department of Radiology, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
| | | | | | - Ming T Tsuang
- Department of Psychiatry, UCSD, San Diego, CA, USA
- Institute of Genomic Medicine, UCSD, La Jolla, CA, USA
| | | | - Ricardo E Carrión
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY, USA
- Institute of Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA, USA
| | - Wiliam S Stone
- Department of Psychiatry, Harvard Medical School at Beth Israel Deaconess Medical Center and Massachusetts General Hospital, Boston, MA, USA
| | - Daniel H Mathalon
- Department of Psychiatry, UCSF, and SFVA Medical Center, San Francisco, CA, USA
| | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Elaine F Walker
- Departments of Psychology and Psychiatry, Emory University, Atlanta, GA, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Albert R Powers
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Alan Anticevic
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| |
Collapse
|
21
|
Curtis MT, Sklar AL, Coffman BA, Salisbury DF. Functional connectivity and gray matter deficits within the auditory attention circuit in first-episode psychosis. Front Psychiatry 2023; 14:1114703. [PMID: 36860499 PMCID: PMC9968732 DOI: 10.3389/fpsyt.2023.1114703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/24/2023] [Indexed: 02/16/2023] Open
Abstract
Background Selective attention deficits in first episode of psychosis (FEP) can be indexed by impaired attentional modulation of auditory M100. It is unknown if the pathophysiology underlying this deficit is restricted to auditory cortex or involves a distributed attention network. We examined the auditory attention network in FEP. Methods MEG was recorded from 27 FEP and 31 matched healthy controls (HC) while alternately ignoring or attending tones. A whole-brain analysis of MEG source activity during auditory M100 identified non-auditory areas with increased activity. Time-frequency activity and phase-amplitude coupling were examined in auditory cortex to identify the attentional executive carrier frequency. Attention networks were defined by phase-locking at the carrier frequency. Spectral and gray matter deficits in the identified circuits were examined in FEP. Results Attention-related activity was identified in prefrontal and parietal regions, markedly in precuneus. Theta power and phase coupling to gamma amplitude increased with attention in left primary auditory cortex. Two unilateral attention networks were identified with precuneus seeds in HC. Network synchrony was impaired in FEP. Gray matter thickness was reduced within the left hemisphere network in FEP but did not correlate with synchrony. Conclusion Several extra-auditory attention areas with attention-related activity were identified. Theta was the carrier frequency for attentional modulation in auditory cortex. Left and right hemisphere attention networks were identified, with bilateral functional deficits and left hemisphere structural deficits, though FEP showed intact auditory cortex theta phase-gamma amplitude coupling. These novel findings indicate attention-related circuitopathy early in psychosis potentially amenable to future non-invasive interventions.
Collapse
Affiliation(s)
| | | | | | - Dean F. Salisbury
- Clinical Neurophysiology Research Laboratory, Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
| |
Collapse
|
22
|
Saiz-Masvidal C, Contreras F, Soriano-Mas C, Mezquida G, Díaz-Caneja CM, Vieta E, Amoretti S, Lobo A, González-Pinto A, Janssen J, Sagué-Vilavella M, Castro-Fornieles J, Bergé D, Bioque M, Lois NG, Parellada M, Bernardo M. Structural covariance predictors of clinical improvement at 2-year follow-up in first-episode psychosis. Prog Neuropsychopharmacol Biol Psychiatry 2023; 120:110645. [PMID: 36181960 DOI: 10.1016/j.pnpbp.2022.110645] [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: 04/27/2022] [Revised: 09/07/2022] [Accepted: 09/22/2022] [Indexed: 11/30/2022]
Abstract
The relationship between structural brain alterations and prediction of clinical improvement in first-episode psychosis (FEP) has been scarcely studied. We investigated whether structural covariance, a well-established approach to identify abnormal patterns of volumetric correlation across distant brain regions, which allows incorporating network-level information to structural assessments, is associated with longitudinal clinical course. We assessed a sample of 74 individuals from a multicenter study. Magnetic resonance imaging scans were acquired at baseline, and clinical assessments at baseline and at a 2-year follow-up. Participants were split in two groups as a function of their clinical improvement after 2 years (i.e., ≥ < 40% reduction in psychotic symptom severity, (n = 29, n = 45)). We performed a seed-based approach and focused our analyses on 3 cortical and 4 subcortical regions of interest to identify alterations in cortical and cortico-subcortical networks. Improvers presented an increased correlation between the volumes of the right posterior cingulate cortex (PCC) and the left precentral gyrus, and between the left PCC and the left middle occipital gyrus. They also showed an increased correlation between right posterior hippocampus and left angular gyrus volumes. Our study provides a novel mean to identify structural correlates of clinical improvement in FEP, describing clinically-relevant anatomical differences in terms of large-scale brain networks, which is better aligned with prevailing neurobiological models of psychosis. The results involve brain regions considered to participate in the multisensory processing of bodily signals and the construction of bodily self-consciousness, which resonates with recent theoretical accounts in psychosis research.
Collapse
Affiliation(s)
- Cristina Saiz-Masvidal
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, Spain
| | - Fernando Contreras
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Social Psychology and Quantitative Psychology, University of Barcelona, Spain.
| | - Gisela Mezquida
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Eduard Vieta
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Silvia Amoretti
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain; Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Antonio Lobo
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain; Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
| | - Ana González-Pinto
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Instituto de Investigación Sanitaria Bioaraba (BIOARABA), Vitoria, Spain; Department of Psychiatry, Hospital Universitario de Alava, Vitoria, Spain; Universidad del País Vasco/ Euskal Harriko Unibertsitatea (UPV/EHU), País Vasco, Spain
| | - Joost Janssen
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Maria Sagué-Vilavella
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Josefina Castro-Fornieles
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institut Clínic de Neurociències, Hospital Clínic Universitari, Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Daniel Bergé
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institute of Neuropsychiatry and Addiction of the Barcelona MAR Health Park, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Department of Medicine and Life Sciences, Pompeu Fabra University (UPF), Barcelona, Spain
| | - Miquel Bioque
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Noemi G Lois
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Mara Parellada
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Bernardo
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | | |
Collapse
|
23
|
Slapø NB, Nerland S, Nordbø Jørgensen K, Mørch-Johnsen L, Pettersen JH, Roelfs D, Parker N, Valstad M, Pentz A, Timpe CMF, Richard G, Beck D, Werner MCF, Lagerberg TV, Melle I, Agartz I, Westlye LT, Steen NE, Andreassen OA, Moberget T, Elvsåshagen T, Jönsson EG. Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders. SCHIZOPHRENIA BULLETIN OPEN 2023; 4:sgad015. [PMID: 38812720 PMCID: PMC7616042 DOI: 10.1093/schizbullopen/sgad015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Background and Hypothesis The auditory cortex (AC) may play a central role in the pathophysiology of schizophrenia and auditory hallucinations (AH). Previous schizophrenia studies report thinner AC and impaired AC function, as indicated by decreased N100 amplitude of the auditory evoked potential. However, whether these structural and functional alterations link to AH in schizophrenia remain poorly understood. Study Design Patients with a schizophrenia spectrum disorder (SCZspect), including patients with a lifetime experience of AH (AH+), without (AH-), and healthy controls underwent magnetic resonance imaging (39 SCZspect, 22 AH+, 17 AH-, and 146 HC) and electroencephalography (33 SCZspect, 17 AH+, 16 AH-, and 144 HC). Cortical thickness of the primary (AC1, Heschl's gyrus) and secondary (AC2, Heschl's sulcus, and the planum temporale) AC was compared between SCZspect and controls and between AH+, AH-, and controls. To examine if the association between AC thickness and N100 amplitude differed between groups, we used regression models with interaction terms. Study Results N100 amplitude was nominally smaller in SCZspect (P = .03, d = 0.42) and in AH- (P = .020, d = 0.61), while AC2 was nominally thinner in AH+ (P = .02, d = 0.53) compared with controls. AC1 thickness was positively associated with N100 amplitude in SCZspect (t = 2.56, P = .016) and AH- (t = 3.18, P = .008), while AC2 thickness was positively associated with N100 amplitude in SCZspect (t = 2.37, P = .024) and in AH+ (t = 2.68, P = .019). Conclusions The novel findings of positive associations between AC thickness and N100 amplitude in SCZspect, suggest that a common neural substrate may underlie AC thickness and N100 amplitude alterations.
Collapse
Affiliation(s)
- Nora Berz Slapø
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Stener Nerland
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Kjetil Nordbø Jørgensen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Lynn Mørch-Johnsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychiatry, Østfold Hospital, Grålum, Norway
- Department of Clinical Research, Østfold Hospital, Grålum, Norway
| | | | - Daniel Roelfs
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadine Parker
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Mathias Valstad
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Atle Pentz
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Clara M. F. Timpe
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Geneviève Richard
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Maren C. Frogner Werner
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Ingrid Melle
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ingrid Agartz
- Department of Psychiatry, Telemark Hospital, Skien, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Sciences, Stockholm Region, Sweden
| | - Lars T. Westlye
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Nils Eiel Steen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A. Andreassen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Torgeir Moberget
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Behavioral Sciences, Faculty of Health Sciences, Oslo Metropolitan University, OsloMet, Oslo, Norway
| | - Torbjørn Elvsåshagen
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Erik G. Jönsson
- Department of medicine, NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| |
Collapse
|
24
|
Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence. Transl Psychiatry 2022; 12:481. [PMID: 36385133 PMCID: PMC9668814 DOI: 10.1038/s41398-022-02242-z] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 10/21/2022] [Accepted: 10/27/2022] [Indexed: 11/17/2022] Open
Abstract
Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject's clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.
Collapse
|
25
|
Das SC, Hjelm BE, Rollins BL, Sequeira A, Morgan L, Omidsalar AA, Schatzberg AF, Barchas JD, Lee FS, Myers RM, Watson SJ, Akil H, Bunney WE, Vawter MP. Mitochondria DNA copy number, mitochondria DNA total somatic deletions, Complex I activity, synapse number, and synaptic mitochondria number are altered in schizophrenia and bipolar disorder. Transl Psychiatry 2022; 12:353. [PMID: 36042222 PMCID: PMC9427957 DOI: 10.1038/s41398-022-02127-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 08/16/2022] [Accepted: 08/18/2022] [Indexed: 11/15/2022] Open
Abstract
Mitochondrial dysfunction is a neurobiological phenomenon implicated in the pathophysiology of schizophrenia and bipolar disorder that can synergistically affect synaptic neurotransmission. We hypothesized that schizophrenia and bipolar disorder share molecular alterations at the mitochondrial and synaptic levels. Mitochondria DNA (mtDNA) copy number (CN), mtDNA common deletion (CD), mtDNA total deletion, complex I activity, synapse number, and synaptic mitochondria number were studied in the postmortem human dorsolateral prefrontal cortex (DLPFC), superior temporal gyrus (STG), primary visual cortex (V1), and nucleus accumbens (NAc) of controls (CON), and subjects with schizophrenia (SZ), and bipolar disorder (BD). The results showed (i) the mtDNA CN is significantly higher in DLPFC of both SZ and BD, decreased in the STG of BD, and unaltered in V1 and NAc of both SZ and BD; (ii) the mtDNA CD is significantly higher in DLPFC of BD while unaltered in STG, V1, and NAc of both SZ and BD; (iii) The total deletion burden is significantly higher in DLPFC in both SZ and BD while unaltered in STG, V1, and NAc of SZ and BD; (iv) Complex I activity is significantly lower in DLPFC of both SZ and BD, which is driven by the presence of medications, with no alteration in STG, V1, and NAc. In addition, complex I protein concentration, by ELISA, was decreased across three cortical regions of SZ and BD subjects; (v) The number of synapses is decreased in DLPFC of both SZ and BD, while the synaptic mitochondria number was significantly lower in female SZ and female BD compared to female controls. Overall, these findings will pave the way to understand better the pathophysiology of schizophrenia and bipolar disorder for therapeutic interventions.
Collapse
Affiliation(s)
- Sujan C. Das
- grid.266093.80000 0001 0668 7243Functional Genomics Laboratory, Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| | - Brooke E. Hjelm
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Health Sciences Campus, Los Angeles, CA USA
| | - Brandi L. Rollins
- grid.266093.80000 0001 0668 7243Functional Genomics Laboratory, Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| | - Adolfo Sequeira
- grid.266093.80000 0001 0668 7243Functional Genomics Laboratory, Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| | - Ling Morgan
- grid.266093.80000 0001 0668 7243Functional Genomics Laboratory, Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| | - Audrey A. Omidsalar
- grid.42505.360000 0001 2156 6853Department of Translational Genomics, Keck School of Medicine, University of Southern California, Health Sciences Campus, Los Angeles, CA USA
| | - Alan F. Schatzberg
- grid.168010.e0000000419368956Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA USA
| | - Jack D. Barchas
- grid.5386.8000000041936877XDepartment of Psychiatry, Weill Cornell Medical College, Ithaca, NJ USA
| | - Francis S. Lee
- grid.5386.8000000041936877XDepartment of Psychiatry, Weill Cornell Medical College, Ithaca, NJ USA
| | - Richard M. Myers
- grid.417691.c0000 0004 0408 3720HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806 USA
| | - Stanley J. Watson
- grid.214458.e0000000086837370The Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI USA
| | - Huda Akil
- grid.214458.e0000000086837370The Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI USA
| | - William E. Bunney
- grid.266093.80000 0001 0668 7243Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| | - Marquis P. Vawter
- grid.266093.80000 0001 0668 7243Functional Genomics Laboratory, Department of Psychiatry & Human Behavior, University of California, Irvine, CA USA
| |
Collapse
|
26
|
Zhang L, Bai Y, Cui X, Cao G, Dan L, Yin H. Negative emotions and brain: negative emotions mediates the association between structural and functional variations in emotional-related brain regions and sleep quality. Sleep Med 2022; 94:8-16. [DOI: 10.1016/j.sleep.2022.03.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 02/07/2022] [Accepted: 03/26/2022] [Indexed: 10/18/2022]
|
27
|
Zhu Y, Nakatani H, Yassin W, Maikusa N, Okada N, Kunimatsu A, Abe O, Kuwabara H, Yamasue H, Kasai K, Okanoya K, Koike S. Application of a Machine Learning Algorithm for Structural Brain Images in Chronic Schizophrenia to Earlier Clinical Stages of Psychosis and Autism Spectrum Disorder: A Multiprotocol Imaging Dataset Study. Schizophr Bull 2022; 48:563-574. [PMID: 35352811 PMCID: PMC9077435 DOI: 10.1093/schbul/sbac030] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS Machine learning approaches using structural magnetic resonance imaging (MRI) can be informative for disease classification; however, their applicability to earlier clinical stages of psychosis and other disease spectra is unknown. We evaluated whether a model differentiating patients with chronic schizophrenia (ChSZ) from healthy controls (HCs) could be applied to earlier clinical stages such as first-episode psychosis (FEP), ultra-high risk for psychosis (UHR), and autism spectrum disorders (ASDs). STUDY DESIGN Total 359 T1-weighted MRI scans, including 154 individuals with schizophrenia spectrum (UHR, n = 37; FEP, n = 24; and ChSZ, n = 93), 64 with ASD, and 141 HCs, were obtained using three acquisition protocols. Of these, data regarding ChSZ (n = 75) and HC (n = 101) from two protocols were used to build a classifier (training dataset). The remainder was used to evaluate the classifier (test, independent confirmatory, and independent group datasets). Scanner and protocol effects were diminished using ComBat. STUDY RESULTS The accuracy of the classifier for the test and independent confirmatory datasets were 75% and 76%, respectively. The bilateral pallidum and inferior frontal gyrus pars triangularis strongly contributed to classifying ChSZ. Schizophrenia spectrum individuals were more likely to be classified as ChSZ compared to ASD (classification rate to ChSZ: UHR, 41%; FEP, 54%; ChSZ, 70%; ASD, 19%; HC, 21%). CONCLUSION We built a classifier from multiple protocol structural brain images applicable to independent samples from different clinical stages and spectra. The predictive information of the classifier could be useful for applying neuroimaging techniques to clinical differential diagnosis and predicting disease onset earlier.
Collapse
Affiliation(s)
- Yinghan Zhu
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Hironori Nakatani
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
- Department of Information Media Technology, School of Information and Telecommunication Engineering, Tokai University, 2-3-23, Takanawa, Minato-ku, Tokyo 108-8619, Japan
| | - Walid Yassin
- Department of Child Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Norihide Maikusa
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Naohiro Okada
- The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Akira Kunimatsu
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- Department of Radiology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Hitoshi Kuwabara
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu City, Shizuoka 431-3192, Japan
| | - Hidenori Yamasue
- Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-ku, Hamamatsu City, Shizuoka 431-3192, Japan
| | - Kiyoto Kasai
- The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
- University of Tokyo Center for Integrative Science of Human Behavior (CiSHuB), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Kazuo Okanoya
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
- The International Research Center for Neurointelligence (WPI-IRCN), Institutes for Advanced Study (UTIAS), University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan
- University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
- University of Tokyo Center for Integrative Science of Human Behavior (CiSHuB), 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Shinsuke Koike
- To whom correspondence should be addressed; Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan; tel: +81-3-5454-4327, fax: +81-3-5454-4327, e-mail:
| |
Collapse
|
28
|
Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression. Diagnostics (Basel) 2022; 12:diagnostics12020469. [PMID: 35204560 PMCID: PMC8871050 DOI: 10.3390/diagnostics12020469] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/18/2022] [Accepted: 02/08/2022] [Indexed: 01/29/2023] Open
Abstract
We used the Mass Multivariate Method on structural, resting-state, and task-related fMRI data from two groups of patients with schizophrenia and depression in order to define several regions of significant relevance to the differential diagnosis of those conditions. The regions included the left planum polare (PP), the left opercular part of the inferior frontal gyrus (OpIFG), the medial orbital gyrus (MOrG), the posterior insula (PIns), and the parahippocampal gyrus (PHG). This study delivered evidence that a multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnoses. Structural, resting-state, or task-related functional MRI modalities cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity combining clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.
Collapse
|
29
|
Grent-'t-Jong T, Gajwani R, Gross J, Gumley AI, Lawrie SM, Schwannauer M, Schultze-Lutter F, Williams SR, Uhlhaas PJ. MR-Spectroscopy of GABA and Glutamate/Glutamine Concentrations in Auditory Cortex in Clinical High-Risk for Psychosis Individuals. Front Psychiatry 2022; 13:859322. [PMID: 35422722 PMCID: PMC9002006 DOI: 10.3389/fpsyt.2022.859322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 02/21/2022] [Indexed: 11/28/2022] Open
Abstract
Psychosis involves changes in GABAergic and glutamatergic neurotransmission in auditory cortex that could be important for understanding sensory deficits and symptoms of psychosis. However, it is currently unclear whether such deficits are present in participants at clinical high-risk for psychosis (CHR-P) and whether they are associated with clinical outcomes. Magnetic Resonance Spectroscopy (MEGAPRESS, 1H-MRS at 3 Tesla) was used to estimate GABA, glutamate, and glutamate-plus-glutamine (Glx) levels in auditory cortex in a large sample of CHR-P (n = 99), CHR-N (clinical high-risk negative, n = 32), and 45 healthy controls. Examined were group differences in metabolite concentrations as well as relationships with clinical symptoms, general cognition, and 1-year follow-up clinical and general functioning in the CHR-P group. Results showed a marginal (p = 0.039) main group effect only for Glx, but not for GABA and glutamate concentrations, and only in left, not right, auditory cortex. This effect did not survive multiple comparison correction, however. Exploratory post-hoc tests revealed that there were significantly lower Glx levels (p = 0.029, uncorrected) in the CHR-P compared to the CHR-N group, but not relative to healthy controls (p = 0.058, uncorrected). Glx levels correlated with the severity of perceptual abnormalities and disorganized speech scores. However, in the CHR-P group, Glx levels did not predict clinical or functional outcomes. Accordingly, the findings from the present study suggest that MRS-measured GABA, glutamate and Glx levels in auditory cortex of CHR-P individuals are largely intact.
Collapse
Affiliation(s)
- Tineke Grent-'t-Jong
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom.,Department of Child and Adolescent Psychiatry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ruchika Gajwani
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom.,Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Andrew I Gumley
- Mental Health and Wellbeing, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Stephen M Lawrie
- Department of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Schwannauer
- Department of Clinical Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.,Department of Psychology, Faculty of Psychology, Airlangga University, Surabaya, Indonesia.,University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Stephen R Williams
- Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom.,Department of Child and Adolescent Psychiatry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| |
Collapse
|
30
|
Di Biase MA, Cetin-Karayumak S, Lyall AE, Zalesky A, Cho KIK, Zhang F, Kubicki M, Rathi Y, Lyons MG, Bouix S, Billah T, Anticevic A, Schleifer C, Adkinson BD, Ji JL, Tamayo Z, Addington J, Bearden CE, Cornblatt BA, Keshavan MS, Mathalon DH, McGlashan TH, Perkins DO, Cadenhead KS, Tsuang MT, Woods SW, Stone WS, Shenton ME, Cannon TD, Pasternak O. White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis. Mol Psychiatry 2021; 26:6833-6844. [PMID: 34024906 PMCID: PMC8611104 DOI: 10.1038/s41380-021-01128-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 04/14/2021] [Indexed: 02/04/2023]
Abstract
Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1-5 over 1 year) in 286 subjects (aged 12-32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p < 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis-regardless of transition outcome-is characterized by subtle age-related white matter changes that occur in tandem with development.
Collapse
Affiliation(s)
- Maria A Di Biase
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia.
| | - Suheyla Cetin-Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Amanda E Lyall
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Kang Ik Kevin Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yogesh Rathi
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Monica G Lyons
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Alan Anticevic
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | | | - Brendan D Adkinson
- Yale Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA
| | - Jie Lisa Ji
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Zailyn Tamayo
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Jean Addington
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior and Department of Psychology, University of California-Los Angeles, Los Angeles, CA, USA
| | - Barbara A Cornblatt
- Department of Psychiatry and Psychology, The Feinstein Institute for Medical Research, Manhasset, NY, USA
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- The Zucker Hillside Hospital, New York, NY, USA
| | - Matcheri S Keshavan
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Daniel H Mathalon
- University of California, San Francisco, San Francisco, CA, USA
- San Francisco VA Medical Center, San Francisco, CA, USA
| | - Thomas H McGlashan
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Diana O Perkins
- Department of Psychology, Hofstra North Shore-LIJ School of Medicine, Hempstead, NY, USA
- University of North Carolina (UNC), Chapel Hill, NC, USA
| | - Kristen S Cadenhead
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego (UCSD), La Jolla, CA, USA
| | - Scott W Woods
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - William S Stone
- Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyrone D Cannon
- Department of Psychiatry and Psychology, Yale University, New Haven, CT, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
31
|
Takahashi T, Sasabayashi D, Takayanagi Y, Furuichi A, Kido M, Nakamura M, Pham TV, Kobayashi H, Noguchi K, Suzuki M. Altered Heschl's gyrus duplication pattern in first-episode schizophrenia. Schizophr Res 2021; 237:174-181. [PMID: 34536751 DOI: 10.1016/j.schres.2021.09.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 07/21/2021] [Accepted: 09/07/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Reduced gray matter volumes in the superior temporal gyrus and its subregions, such as Heschl's gyrus (HG) and the planum temporale (PT), have been reported in schizophrenia (Sz). However, it remains unclear whether patients exhibit an altered sulcogyral pattern on the superior temporal plane. METHODS This magnetic resonance imaging study examined the distribution of HG duplication patterns [i.e., single HG, common stem duplication (CSD), or complete posterior duplication (CPD)] and their relationships with clinical variables and gray matter volumes in the HG and PT of 64 first-episode (FE) patients with Sz and 64 healthy controls. RESULTS The prevalence of duplicated HG patterns was significantly higher and gray matter volumes in the HG and PT of both hemispheres were smaller in FESz patients than in healthy controls. The right CPD pattern in the FESz group was associated with less severe positive symptoms. In the FESz and control groups, CSD and CPD patterns correlated with larger volumes in the HG and PT, respectively. CONCLUSION The present results revealed an altered HG duplication pattern at the earliest phase of Sz, which may reflect early neurodevelopmental anomalies. However, reduced HG and PT volumes in the FESz were not explained by this sulcogyral pattern only, supporting the complex superior temporal pathology of Sz.
Collapse
Affiliation(s)
- Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan.
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Arisawabashi Hospital, Toyama, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Mikio Kido
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Mihoko Nakamura
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Tien Viet Pham
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Haruko Kobayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan; Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| |
Collapse
|
32
|
Collins MA, Chung Y, Addington J, Bearden CE, Cadenhead KS, Cornblatt BA, Mathalon DH, McGlashan TH, Perkins DO, Seidman LJ, Tsuang MT, Walker EF, Woods SW, Cannon TD. Discriminatory experiences predict neuroanatomical changes and anxiety among healthy individuals and those at clinical high risk for psychosis. Neuroimage Clin 2021; 31:102757. [PMID: 34273790 PMCID: PMC8283423 DOI: 10.1016/j.nicl.2021.102757] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/23/2021] [Accepted: 07/03/2021] [Indexed: 01/14/2023]
Abstract
Individuals face discrimination based on characteristics including race/ethnicity, gender, age, and disability. Discriminatory experiences (DE) are associated with poor psychological health in the general population and with worse outcomes among individuals at clinical high risk for psychosis (CHR). Though the brain is sensitive to stress, and brain structural change is a well-documented precursor to psychosis, potential relationships between DE and brain structure among CHR or healthy individuals are not known. This report assessed whether lifetime DE are associated with cortical thinning and clinical outcomes across time, after controlling for discrimination-related demographic factors among CHR individuals who ultimately do (N = 57) and do not convert to psychosis (N = 451), and healthy comparison (N = 208) participants in the North American Prodrome Longitudinal Study 2. Results indicate that DE are associated with thinner cortex across time in several cortical areas. Thickness in several right hemisphere regions partially mediates associations between DE and subsequent anxiety symptoms, but not attenuated positive symptoms of psychosis. This report provides the first evidence to date of an association between DE and brain structure in both CHR and healthy comparison individuals. Results also suggest that thinner cortex across time in areas linked with DE may partially explain associations between DE and cross-diagnostic indicators of psychological distress.
Collapse
Affiliation(s)
| | - Yoonho Chung
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Belmont, MA, USA
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior & Department of Psychology, University of California, Los Angeles, USA
| | | | | | - Daniel H Mathalon
- Department of Psychiatry, University of California, San Francisco, USA; San Francisco VA Medical Center, San Francisco, CA, USA
| | | | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, USA
| | - Larry J Seidman
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California, San Diego, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA
| |
Collapse
|
33
|
Prakash J, Chatterjee K, Srivastava K, Chauhan VS. First-episode psychosis: How long does it last? A review of evolution and trajectory. Ind Psychiatry J 2021; 30:198-206. [PMID: 35017801 PMCID: PMC8709526 DOI: 10.4103/ipj.ipj_38_21] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/13/2021] [Accepted: 03/16/2021] [Indexed: 11/12/2022] Open
Abstract
Study of first-episode psychosis (FEP), an episode of psychotic nature which manifests for the first time in an individual in the longitudinal continuum of his/her illness, has been study matter of research interest in recent years. A comprehensive review of the literature will help us understand the evolution and trajectory of this concept better. A literature review of available articles addressing the concept, phenomenology, evolution, identification, course, and outcome of FEP was done; the same was subsequently divided into broad topics for better clarity and analyzed. FEP constituted a clinical psychotic phenomenon with underlying significant heterogeneity in diagnosis, stability, course, and outcome. The study has attempted to view FEP both as horizontal spectrum across various diagnoses and longitudinally ranging from asymptomatic individual with unknown risk status to attenuated psychosis to multiple relapses/unremitting illness. Many risk and protective factors have been brought out with varying certainty ranging bio-psycho-social spectrum. Efforts have been made to calculate polygenic risk score based on genes involvement/sharing between various psychotic spectrum disorders; as well as biomarker panels to identify people at risk. FEP may prove to be an important concept to understand psychosis in general; without putting things into the diagnostic rubric. It may help understand multiple risk and protective factors for the course and outcome of psychotic illness and may clear the cloud to sharpen the evidence toward commonality and distinctiveness between various psychotic diagnoses in vogue for more comprehensive concept.
Collapse
Affiliation(s)
- Jyoti Prakash
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Chatterjee
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Srivastava
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - V. S. Chauhan
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| |
Collapse
|
34
|
Jalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, Uhlhaas PJ, Takahashi T, Sugranyes G, Kwak YB, Mathalon DH, Katagiri N, Hooker CI, Smigielski L, Colibazzi T, Via E, Tang J, Koike S, Rasser PE, Michel C, Lebedeva I, Hegelstad WTV, de la Fuente-Sandoval C, Waltz JA, Mizrahi R, Corcoran CM, Resch F, Tamnes CK, Haas SS, Lemmers-Jansen ILJ, Agartz I, Allen P, Amminger GP, Andreassen OA, Atkinson K, Bachman P, Baeza I, Baldwin H, Bartholomeusz CF, Borgwardt S, Catalano S, Chee MWL, Chen X, Cho KIK, Cooper RE, Cropley VL, Dolz M, Ebdrup BH, Fortea A, Glenthøj LB, Glenthøj BY, de Haan L, Hamilton HK, Harris MA, Haut KM, He Y, Heekeren K, Heinz A, Hubl D, Hwang WJ, Kaess M, Kasai K, Kim M, Kindler J, Klaunig MJ, Koppel A, Kristensen TD, Kwon JS, Lawrie SM, Lee J, León-Ortiz P, Lin A, Loewy RL, Ma X, McGorry P, McGuire P, Mizuno M, Møller P, Moncada-Habib T, Muñoz-Samons D, Nelson B, Nemoto T, Nordentoft M, Omelchenko MA, Oppedal K, Ouyang L, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Roach BJ, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Schiffman J, Schlagenhauf F, Schmidt A, Sørensen ME, et alJalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, Uhlhaas PJ, Takahashi T, Sugranyes G, Kwak YB, Mathalon DH, Katagiri N, Hooker CI, Smigielski L, Colibazzi T, Via E, Tang J, Koike S, Rasser PE, Michel C, Lebedeva I, Hegelstad WTV, de la Fuente-Sandoval C, Waltz JA, Mizrahi R, Corcoran CM, Resch F, Tamnes CK, Haas SS, Lemmers-Jansen ILJ, Agartz I, Allen P, Amminger GP, Andreassen OA, Atkinson K, Bachman P, Baeza I, Baldwin H, Bartholomeusz CF, Borgwardt S, Catalano S, Chee MWL, Chen X, Cho KIK, Cooper RE, Cropley VL, Dolz M, Ebdrup BH, Fortea A, Glenthøj LB, Glenthøj BY, de Haan L, Hamilton HK, Harris MA, Haut KM, He Y, Heekeren K, Heinz A, Hubl D, Hwang WJ, Kaess M, Kasai K, Kim M, Kindler J, Klaunig MJ, Koppel A, Kristensen TD, Kwon JS, Lawrie SM, Lee J, León-Ortiz P, Lin A, Loewy RL, Ma X, McGorry P, McGuire P, Mizuno M, Møller P, Moncada-Habib T, Muñoz-Samons D, Nelson B, Nemoto T, Nordentoft M, Omelchenko MA, Oppedal K, Ouyang L, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Roach BJ, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Schiffman J, Schlagenhauf F, Schmidt A, Sørensen ME, Suzuki M, Theodoridou A, Tomyshev AS, Tor J, Værnes TG, Velakoulis D, Venegoni GD, Vinogradov S, Wenneberg C, Westlye LT, Yamasue H, Yuan L, Yung AR, van Amelsvoort TAMJ, Turner JA, van Erp TGM, Thompson PM, Hernaus D. Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group Mega-analysis. JAMA Psychiatry 2021; 78:753-766. [PMID: 33950164 PMCID: PMC8100913 DOI: 10.1001/jamapsychiatry.2021.0638] [Show More Authors] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/04/2021] [Indexed: 01/10/2023]
Abstract
Importance The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. Objective To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). Design, Setting, and Participants In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. Main Outcomes and Measures Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). Results Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001). Conclusions and Relevance This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.
Collapse
Affiliation(s)
- Maria Jalbrzikowski
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Rebecca A Hayes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Stephen J Wood
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Dorte Nordholm
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Juan H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- EPIC Lab, Department of Psychosis Studies, King's College London, London, United Kingdom
| | - Peter J Uhlhaas
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Christine I Hooker
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
| | - Lukasz Smigielski
- Department of Child and Adolescent Psychiatry, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Tiziano Colibazzi
- Department of Psychiatry, Columbia University, New York, New York
- New York State Psychiatric Institute, New York
| | - Esther Via
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Neurobiology of Zhejiang Province, School of Medicine, Zhejiang University Hangzhou, Hangzhou, China
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, Tokyo, Japan
| | - Paul E Rasser
- Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, Australia
- Priority Research Centre for Stroke and Brain Injury, The University of Newcastle, Newcastle, Australia
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Wenche Ten Velden Hegelstad
- Faculty of Social Sciences, University of Stavanger, Stavanger, Norway
- TIPS Centre for Clinical Research in Psychosis, Stavanger University Hospital, Stavanger, Norway
| | | | - James A Waltz
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore
| | - Romina Mizrahi
- Douglas Research Center, Montreal, Quebec, Canada
- McGill University, Department of Psychiatry, Montreal, Quebec, Canada
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, New York, New York
| | - Franz Resch
- Clinic for Child and Adolescent Psychiatry, University Hospital of Heidelberg, Heidelberg, Germany
| | - Christian K Tamnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Imke L J Lemmers-Jansen
- Faculty of Behavioural and Movement Sciences, Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Paul Allen
- Department of Psychology, University of Roehampton, London, United Kingdom
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - G Paul Amminger
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kimberley Atkinson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Helen Baldwin
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom
| | - Cali F Bartholomeusz
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Stefan Borgwardt
- Department of Psychiatry, University of Basel, Basel, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Sabrina Catalano
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michael W L Chee
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Xiaogang Chen
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rebecca E Cooper
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, 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
| | - Montserrat Dolz
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Bjørn H Ebdrup
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic Barcelona, Fundació Clínic Recerca Biomèdica, Universitat de Barcelona, Barcelona, Spain
| | - Louise Birkedal Glenthøj
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Birte Y Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam University Medical Centre, Amsterdam, the Netherlands
- Arkin, Amsterdam, the Netherlands
| | - Holly K Hamilton
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Mathew A Harris
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kristen M Haut
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
| | - Ying He
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Karsten Heekeren
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy I, LVR-Hospital Cologne, Cologne, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Daniela Hubl
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Wu Jeong Hwang
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Department of Child and Adolescent Psychiatry, Center of Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Kiyoto Kasai
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence at The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo, Japan
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Mallory J Klaunig
- Department of Psychology, University of Maryland, Baltimore County, Baltimore
| | - Alex Koppel
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Tina D Kristensen
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Pablo León-Ortiz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Ashleigh Lin
- Telethon Kids Institute, The University of Western Australia, Perth, Australia
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Xiaoqian Ma
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Patrick McGorry
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Masafumi Mizuno
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Paul Møller
- Department for Mental Health Research and Development, Division of Mental Health and Addiction, Vestre Viken Hospital Trust, Lier, Norway
| | - Tomas Moncada-Habib
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Daniel Muñoz-Samons
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Barnaby Nelson
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Merete Nordentoft
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Ketil Oppedal
- Stavanger Medical Imaging Laboratory, Department of Radiology, Stavanger University Hospital, Stavanger, Norway
| | - Lijun Ouyang
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, 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
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Jose C Pariente
- Magnetic Resonance Imaging Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Jayachandra M Raghava
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Physiology, Nuclear Medicine and PET, Functional Imaging Unit, University of Copenhagen, Glostrup, Denmark
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Brian J Roach
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Jan I Røssberg
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wulf Rössler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Dean F Salisbury
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Ulrich Schall
- Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, Australia
- Priority Research Centre Grow Up Well, The University of Newcastle, Newcastle, Australia
| | - Jason Schiffman
- Department of Psychology, University of Maryland, Baltimore County, Baltimore
- Department of Psychological Science, University of California, Irvine
| | - Florian Schlagenhauf
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Andre Schmidt
- Department of Psychiatry, University of Basel, Basel, Switzerland
| | - Mikkel E Sørensen
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Anastasia Theodoridou
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Jordina Tor
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Tor G Værnes
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Early Intervention in Psychosis Advisory Unit for South-East Norway, TIPS Sør-Øst, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Australia
| | - Gloria D Venegoni
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
| | - Christina Wenneberg
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Lars T Westlye
- NORMENT, 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
| | - Hidenori Yamasue
- Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu City, Japan
| | - Liu Yuan
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Alison R Yung
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Thérèse A M J van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | | | - Theo G M van Erp
- Center for the Neurobiology of Learning and Memory, Irvine, California
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| |
Collapse
|
35
|
Tu W, Ma Z, Zhang N. Brain network reorganization after targeted attack at a hub region. Neuroimage 2021; 237:118219. [PMID: 34052466 PMCID: PMC8289586 DOI: 10.1016/j.neuroimage.2021.118219] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 04/14/2021] [Accepted: 05/26/2021] [Indexed: 01/01/2023] Open
Abstract
The architecture of brain networks has been extensively studied in multiple species. However, exactly how the brain network reconfigures when a local region, particularly a hub region, stops functioning remains elusive. By combining chemogenetics and resting-state functional magnetic resonance imaging (rsfMRI) in an awake rodent model, we investigated the causal impact of acutely inactivating a hub region (i.e. the dorsal anterior cingulate cortex) on brain network properties. We found that suppressing neural activity in a hub could have a ripple effect that went beyond the hub-related connections and propagated to other neural connections across multiple brain systems. In addition, hub dysfunction affected the topological architecture of the whole-brain network in terms of the network resilience and segregation. Selectively inhibiting excitatory neurons in the hub further changed network integration. None of these changes were observed in sham rats or when a non-hub region (i.e. the primary visual cortex) was perturbed. This study has established a system that allows for mechanistically dissecting the relationship between local regions and brain network properties. Our data provide direct evidence supporting the hypothesis that acute dysfunction of a brain hub can cause large-scale network changes. These results also provide a comprehensive framework documenting the differential impact of hub versus non-hub nodes on network dynamics.
Collapse
Affiliation(s)
- Wenyu Tu
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA; Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
| |
Collapse
|
36
|
Tateno T, Higuchi Y, Nakajima S, Sasabayashi D, Nakamura M, Ueno M, Mizukami Y, Nishiyama S, Takahashi T, Sumiyoshi T, Suzuki M. Features of Duration Mismatch Negativity Around the Onset of Overt Psychotic Disorders: A Longitudinal Study. Cereb Cortex 2021; 31:2416-2424. [PMID: 33341873 DOI: 10.1093/cercor/bhaa364] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 10/28/2020] [Accepted: 11/02/2020] [Indexed: 01/29/2023] Open
Abstract
Reduced amplitude of duration mismatch negativity (dMMN) has been reported in psychotic disorders and at-risk mental state (ARMS); however, few longitudinal MMN studies have examined the amplitude changes during the course of psychosis. We compared dMMN amplitude between ARMS individuals with later psychosis onset and those without, and we longitudinally examined potential dMMN changes around psychosis onset. Thirty-nine ARMS subjects and 22 healthy controls participated in this study. Of the 39 ARMS subjects, 11 transitioned to psychosis (at-risk mental state with later psychosis onset [ARMS-P]) during follow-up and 28 did not (at-risk mental state without later psychosis onset [ARMS-NP]). dMMN was measured twice using an auditory oddball paradigm with a mean interval of 2 years. Follow-up dMMN data were available for all but four ARMS-P subjects. dMMN amplitude at baseline was smaller in ARMS-P subjects compared with control and ARMS-NP subjects. Additionally, ARMS-P subjects displayed a longitudinal decline in dMMN amplitude, which was not present in control and ARMS-P subjects. We also observed a progressive decline in dMMN amplitude during the transition period, suggesting dynamic brain changes associated with the psychosis onset. Our findings implicate dMMN amplitude as a biological predictor of future psychosis onset in high-risk individuals, which may be used for early detection and intervention of psychosis.
Collapse
Affiliation(s)
- Takahiro Tateno
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Yuko Higuchi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan.,Department of Preventive Intervention for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, 187-8551, Japan
| | - Suguru Nakajima
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Mihoko Nakamura
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Maya Ueno
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Yuko Mizukami
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan
| | - Shimako Nishiyama
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Center for Health Care and Human Sciences, University of Toyama, Toyama, 930-8555, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| | - Tomiki Sumiyoshi
- Department of Preventive Intervention for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, 187-8551, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, 930-0194, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, 930-0194, Japan
| |
Collapse
|
37
|
Hamasaki Y, Nakayama T, Hikida T, Murai T. Combined pattern of childhood psycho-behavioral characteristics in patients with schizophrenia: a retrospective study in Japan. BMC Psychiatry 2021; 21:57. [PMID: 33499818 PMCID: PMC7836163 DOI: 10.1186/s12888-021-03049-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 01/13/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Although epidemiological and genetic studies have provided scientific evidence that places schizophrenia into the framework of early neurodevelopmental disorders, the psycho-behavioral characteristics of children that later go on to develop schizophrenia have not been sufficiently clarified. This study aimed to retrospectively identify characteristics specific to patients with schizophrenia during childhood via their guardians' reporting of these characteristics. METHODS Participants included 54 outpatients with schizophrenia in their twenties who fulfilled DSM-IV-TR criteria. Additionally, 192 normal healthy subjects participated as sex- and age-matched controls. The guardians of all participants were recruited to rate participants' childhood characteristics from 6 to 8 years of age on a modified version of the Child Behavior Checklist (CBCL), which was used as a retrospective assessment questionnaire. Using t-tests, logistic regression, and Receiver Operating Characteristic (ROC) curve analysis, we estimated the psycho-behavioral characteristics specific to schizophrenia during childhood. Using the obtained logistic regression model, we prototyped a risk-predicting algorithm based on the CBCL scores. RESULTS Among the eight CBCL subscale t-scores, "withdrawn" (p = 0.002), "thought problems" (p = 0.001), and "lack of aggressive behavior" (p = 0.002) were each significantly associated with the later diagnosis of schizophrenia, although none of these mean scores were in the clinical range at the time of childhood. The algorithm of the logistic regression model, based on eight CBCL subscales, had an area under the ROC curve of 82.8% (95% CI: 76-89%), which indicated that this algorithm's prediction of late development of schizophrenia has moderate accuracy. CONCLUSIONS The results suggest that according to guardian reports, participants showed psycho-behavioral characteristics during childhood, different to those of healthy controls, which could be predictive of the later development of schizophrenia. Our newly developed algorithm is available to use in future studies to further test its validity.
Collapse
Affiliation(s)
- Yukiko Hamasaki
- Faculty of Contemporary Society, Kyoto Women's University, 35, Kitahiyoshi-cho, Imakumano, Higashiyama-ku, Kyoto, 605-8501, Japan.
- Shigasato Hospital, 1-18-41 Shigasato, Otsu, Shiga, 520-0006, Japan.
| | - Takao Nakayama
- Faculty of Contemporary Society, Kyoto Women's University, 35, Kitahiyoshi-cho, Imakumano, Higashiyama-ku, Kyoto, 605-8501, Japan
| | - Takatoshi Hikida
- Laboratory for Advanced Brain Functions, Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Toshiya Murai
- Department of Psychiatry, Kyoto University Graduate School of Medicine, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| |
Collapse
|
38
|
Takahashi T, Sasabayashi D, Takayanagi Y, Furuichi A, Kido M, Pham TV, Kobayashi H, Noguchi K, Suzuki M. Increased Heschl's Gyrus Duplication in Schizophrenia Spectrum Disorders: A Cross-Sectional MRI Study. J Pers Med 2021; 11:40. [PMID: 33445715 PMCID: PMC7828168 DOI: 10.3390/jpm11010040] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/08/2021] [Accepted: 01/09/2021] [Indexed: 11/17/2022] Open
Abstract
Duplicated Heschl's gyrus (HG) is prevalent in patients with schizophrenia and may reflect early neurodevelopmental anomalies. However, it currently remains unclear whether patients with schizotypal disorder, a prototypic disorder within the schizophrenia spectrum, exhibit a similar HG gyrification pattern. In this magnetic resonance imaging study, HG gyrification patterns were examined in 47 patients with schizotypal disorder, 111 with schizophrenia, and 88 age- and sex-matched healthy subjects. HG gyrification patterns were classified as single, common stem duplication (CSD), or complete posterior duplication (CPD). The prevalence of the duplicated HG patterns (CSD or CPD) bilaterally was higher in the schizophrenia and schizotypal groups than in healthy controls, whereas no significant difference was observed between the schizophrenia and schizotypal groups. Schizophrenia patients with the right CPD pattern had less severe positive symptoms, whereas the right single HG pattern was associated with higher doses of antipsychotic medication in schizotypal patients. The present study demonstrated shared HG gyrification patterns in schizophrenia spectrum disorders, which may reflect a common biological vulnerability factor. HG patterns may also be associated with susceptibility to psychopathology.
Collapse
Affiliation(s)
- Tsutomu Takahashi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Arisawabashi Hospital, Toyama 939-2704, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Mikio Kido
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Tien Viet Pham
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Haruko Kobayashi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| | - Kyo Noguchi
- Department of Radiology, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan;
| | - Michio Suzuki
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (D.S.); (Y.T.); (A.F.); (M.K.); (T.V.P.); (H.K.); (M.S.)
- Research Center for Idling Brain Science, University of Toyama, Toyama 930-0194, Japan
| |
Collapse
|
39
|
Murray RM, David AS, Ajnakina O. Prevention of psychosis: moving on from the at-risk mental state to universal primary prevention. Psychol Med 2021; 51:223-227. [PMID: 32892760 PMCID: PMC7893507 DOI: 10.1017/s003329172000313x] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 04/09/2020] [Accepted: 08/12/2020] [Indexed: 12/14/2022]
Abstract
The value of services for those with the 'At Risk Mental State for Psychosis' (ARMS) continues to be disputed. ARMS services have provided a valuable stimulus to academic research into the transition into psychosis. Furthermore, there is currently a welcome trend to transform such clinics into youth mental health services catering for the broader clientele of young people suffering from anxiety and depression, who already constitute the bulk of those seen at ARMS clinics. However, such services are never likely to make major inroads into preventing psychosis because they only reach a small proportion of those at risk. Evidence from medicine shows that avoiding exposure to factors which increase the risk of disease (e.g. poor nutrition, transmission of infection, tobacco smoking), produces greater public benefit than focussing efforts on individuals with, or about to develop, disease. We consider that the most productive approach for psychosis prevention is avoiding exposure to risk-increasing factors. The best-established risk factors for psychosis are obstetric events, childhood abuse, migration, city living, adverse life events and cannabis use. Some as city living, are likely proxies for an unknown causal factor(s) while preventing others such as childhood abuse is currently beyond our powers. The risk factor for psychosis which is most readily open to this approach is the use of cannabis. Therefore, as an initial step towards a strategy for universal primary prevention, we advocate public health campaigns to educate young people about the harms of regular use of high potency cannabis.
Collapse
Affiliation(s)
- Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry, Experimental Biomedicine and Clinical Neuroscience, University of Palermo, Palermo, Italy
| | - Anthony S. David
- Institute of Mental Health, University College London, London, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, University of London, London, UK
| |
Collapse
|
40
|
Merritt K, Luque Laguna P, Irfan A, David AS. Longitudinal Structural MRI Findings in Individuals at Genetic and Clinical High Risk for Psychosis: A Systematic Review. Front Psychiatry 2021; 12:620401. [PMID: 33603688 PMCID: PMC7884337 DOI: 10.3389/fpsyt.2021.620401] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 01/08/2021] [Indexed: 01/18/2023] Open
Abstract
Background: Several cross-sectional studies report brain structure differences between healthy volunteers and subjects at genetic or clinical high risk of developing schizophrenia. However, longitudinal studies are important to determine whether altered trajectories of brain development precede psychosis onset. Methods: We conducted a systematic review to determine if brain trajectories differ between (i) those with psychotic experiences (PE), genetic (GHR) or clinical high risk (CHR), compared to healthy volunteers, and (ii) those who transition to psychosis compared to those who do not. Results: Thirty-eight studies measured gray matter and 18 studies measured white matter in 2,473 high risk subjects and 990 healthy volunteers. GHR, CHR, and PE subjects show an accelerated decline in gray matter primarily in temporal, and also frontal, cingulate and parietal cortex. In those who remain symptomatic or transition to psychosis, gray matter loss is more pronounced in these brain regions. White matter volume and fractional anisotropy, which typically increase until early adulthood, did not change or reduced in high risk subjects in the cingulum, thalamic radiation, cerebellum, retrolenticular part of internal capsule, and hippocampal-thalamic tracts. In those who transitioned, white matter volume and fractional anisotropy reduced over time in the inferior and superior fronto-occipital fasciculus, corpus callosum, anterior limb of the internal capsule, superior corona radiate, and calcarine cortex. Conclusion: High risk subjects show deficits in white matter maturation and an accelerated decline in gray matter. Gray matter loss is more pronounced in those who transition to psychosis, but may normalize by early adulthood in remitters.
Collapse
Affiliation(s)
- Kate Merritt
- Division of Psychiatry, Institute of Mental Health, University College London, London, United Kingdom
| | - Pedro Luque Laguna
- The Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Ayela Irfan
- Division of Psychiatry, Institute of Mental Health, University College London, London, United Kingdom
| | - Anthony S David
- Division of Psychiatry, Institute of Mental Health, University College London, London, United Kingdom
| |
Collapse
|
41
|
Cao H, Chung Y, McEwen SC, Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Carrión R, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Anticevic A, Woods SW, Cannon TD. Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium. Schizophr Res 2020; 226:30-37. [PMID: 30704864 PMCID: PMC8376298 DOI: 10.1016/j.schres.2019.01.017] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 11/13/2018] [Accepted: 01/19/2019] [Indexed: 01/02/2023]
Abstract
Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, may be implicated in the progression to full psychosis.
Collapse
Affiliation(s)
- Hengyi Cao
- Department of Psychology, Yale University, New Haven, CT, USA.
| | - Yoonho Chung
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Sarah C McEwen
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, Canada
| | - Bradley Goodyear
- Departments of Radiology, Clinical Neuroscience and Psychiatry, University of Calgary, Calgary, Canada
| | - Kristin S Cadenhead
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Heline Mirzakhanian
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Barbara A Cornblatt
- Department of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Ricardo Carrión
- Department of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Daniel H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | | | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - Larry J Seidman
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Heidi Thermenos
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - Theo G M van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Stephan Hamann
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Alan Anticevic
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT, USA; Department of Psychiatry, Yale University, New Haven, CT, USA.
| |
Collapse
|
42
|
Grey-matter abnormalities in clinical high-risk participants for psychosis. Schizophr Res 2020; 226:120-128. [PMID: 31740178 PMCID: PMC7774586 DOI: 10.1016/j.schres.2019.08.034] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 08/28/2019] [Accepted: 08/31/2019] [Indexed: 01/10/2023]
Abstract
The current study examined the presence of abnormalities in cortical grey-matter (GM) in a sample of clinical high-risk (CHR) participants and examined relationships with psychosocial functioning and neurocognition. CHR-participants (n = 114), participants who did not fulfil CHR-criteria (CHR-negative) (n = 39) as well as a group of healthy controls (HC) (n = 49) were recruited. CHR-status was assessed using the Comprehensive Assessment of At-Risk Mental State (CAARMS) and the Schizophrenia Proneness Interview, Adult Version (SPI-A). The Brief Assessment of Cognition in Schizophrenia Battery (BACS) as well as tests for emotion recognition, working memory and attention were administered. In addition, role and social functioning as well as premorbid adjustment were assessed. No significant differences in GM-thickness and intensity were observed in CHR-participants compared to CHR-negative and HC. Circumscribed abnormalities in GM-intensity were found in the visual and frontal cortex of CHR-participants. Moreover, small-to-moderate correlations were observed between GM-intensity and neuropsychological deficits in the CHR-group. The current data suggest that CHR-participants may not show comprehensive abnormalities in GM. We discuss the implications of these findings for the pathophysiological theories of early stage-psychosis as well as methodological issues and the impact of different recruitment strategies.
Collapse
|
43
|
Kogan S, Ospina LH, Mittal VA, Kimhy D. The impact of inflammation on neurocognition and risk for psychosis: a critical review. Eur Arch Psychiatry Clin Neurosci 2020; 270:793-802. [PMID: 31620871 PMCID: PMC7160015 DOI: 10.1007/s00406-019-01073-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 09/24/2019] [Indexed: 12/11/2022]
Abstract
Neurocognitive difficulties are highly prevalent among people with schizophrenia and have been linked to increased inflammation, as well as dysfunction and disability. Poor neurocognitive functioning has also been documented in individuals at clinical high risk for psychosis (CHR) and a burgeoning literature point to alterations in inflammation markers in this population. However, there is limited information regarding the putative link between inflammation and neurocognition in CHR individuals, and the potential role of inflammation in the development of cognitive difficulties and psychosis. As previous reports indicate that early treatment in schizophrenia is associated with better outcomes, there is an urgent need to identify neurobiological mechanisms underlying cognitive deterioration and psychosis in CHR individuals to provide them with care prior to significant cognitive and functional declines. To address this gap in the literature, we review and summarize the relevant literatures on inflammation and neurocognitive dysfunction in schizophrenia and CHR individuals, point to remaining gaps, and suggest directions for future research.
Collapse
Affiliation(s)
- Sophia Kogan
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1230, New York, NY, 10029, USA
| | - Luz H Ospina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1230, New York, NY, 10029, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - David Kimhy
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, 1230, New York, NY, 10029, USA.
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA.
| |
Collapse
|
44
|
Glutamatergic hypo-function in the left superior and middle temporal gyri in early schizophrenia: a data-driven three-dimensional proton spectroscopic imaging study. Neuropsychopharmacology 2020; 45:1851-1859. [PMID: 32403117 PMCID: PMC7608301 DOI: 10.1038/s41386-020-0707-y] [Citation(s) in RCA: 5] [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: 03/06/2020] [Revised: 04/23/2020] [Accepted: 05/06/2020] [Indexed: 12/26/2022]
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) studies have examined glutamatergic abnormalities in schizophrenia, mostly in single voxels. Though the critical brain nodes remain unknown, schizophrenia involves networks with broad abnormalities. Hence, glutamine plus glutamate (Glx) and other metabolites were examined with whole-brain 1H-MRS, in early schizophrenia. Three dimensional 1H-MRS was acquired in young schizophrenia subjects (N = 36, 19 antipsychotic-naïve and 17 antipsychotic-treated) and healthy controls (HC, N = 29). Glx (as well as N-acetylaspartate, choline, myo-inositol and creatine) group contrasts from all individual voxels that met spectral quality, were analyzed in common brain space, followed by cluster-corrected level alpha-value (CCLAV ≤ 0.05). Schizophrenia subjects had lower Glx in the left superior (STG) and middle temporal gyri (16 voxels, CCLAV = 0.04) and increased creatine in two clusters involving left temporal, parietal and occipital regions (32, and 18 voxels, CCLAV = 0.02 and 0.04, respectively). Antipsychotic-treated and naïve patients (vs HC) had similar Glx reductions (8/16 vs 10/16 voxels respectively, but CCLAV's > 0.05). However, creatine was higher in antipsychotic-treated vs HC's in a larger left hemisphere cluster (100 voxels, CCLAV = 0.01). Also in treated patients, choline was increased in left middle frontal gyrus (18 voxels, CCLAV = 0.04). Finally in antipsychotic-naive patients, NAA was reduced in right frontal gyri (19 voxels, CCLAV = 0.05) and myo-inositol was reduced in the left cerebellum (34 voxels, CCLAV = 0.02). We conclude that data-driven spectroscopic brain examination supports that reductions in Glx in the left STG may be critical to the pathophysiology of schizophrenia. Postmortem and neuromodulation schizophrenia studies focusing on left STG, may provide critical mechanistic and therapeutic advancements, respectively.
Collapse
|
45
|
Bellani M, Bontempi P, Zovetti N, Gloria Rossetti M, Perlini C, Dusi N, Squarcina L, Marinelli V, Zoccatelli G, Alessandrini F, Francesca Maria Ciceri E, Sbarbati A, Brambilla P. Resting state networks activity in euthymic bipolar disorder. Bipolar Disord 2020; 22:593-601. [PMID: 32212391 DOI: 10.1111/bdi.12900] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Bipolar disorder (BD) is a psychiatric condition causing shifts in mood, energy and activity levels severely altering the quality of life of the patients even in the euthymic phase. Although widely accepted, the neurobiological bases of the disorder in the euthymic phase remain elusive. This study aims at characterizing resting state functional activity of the BD euthymic phase in order to better understand the pathogenesis of the disease and build future neurobiological models. METHODS Fifteen euthymic BD patients (10 females; mean age 40.2; standard deviation 13.5; range 20-61) and 27 healthy controls (HC) (21 females; mean age 37; standard deviation 10.6; range 22-60) underwent a 3T functional MRI scan at rest. Resting state activity was extracted through independent component analysis (ICA) run with automatic dimensionality estimation. RESULTS ICA identified 22 resting state networks (RSNs). Within-network analysis revealed decreased connectivity in the visual, temporal, motor and cerebellar RSNs of BD patients vs HC. Between-network analysis showed increased connectivity between motor area and the default mode network (DMN) partially overlapping with the fronto-parietal network (FPN) in BD patients. CONCLUSION Within-network analysis confirmed existing evidence of altered cerebellar, temporal, motor and visual networks in BD. Increased connectivity between the DMN and the motor area network suggests the presence of alterations of the fronto-parietal regions, precuneus and cingulate cortex in the euthymic condition. These findings indicate that specific connectivity alterations might persist even in the euthymic state suggesting the importance of examining both within and between-network connectivity to achieve a global understanding of the BD euthymic condition.
Collapse
Affiliation(s)
- Marcella Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Pietro Bontempi
- Department of Computer Science, University of Verona, Verona, Italy
| | - Niccolò Zovetti
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Maria Gloria Rossetti
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy.,Department of Neuroscience and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Cinzia Perlini
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Verona, Italy
| | - Nicola Dusi
- Psychiatry Unit, Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Letizia Squarcina
- Department of Neuroscience and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Veronica Marinelli
- Department of Surgery, Dentistry, Paediatrics and Gynaecology, University of Verona, Verona, Italy
| | - Giada Zoccatelli
- Neuroradiology Department, Azienda Ospedaliera Universitaria Integrata di Verona, Verona, Italy
| | - Franco Alessandrini
- Neuroradiology Department, Azienda Ospedaliera Universitaria Integrata di Verona, Verona, Italy
| | - Elisa Francesca Maria Ciceri
- Neuroradiology Department, Azienda Ospedaliera Universitaria Integrata di Verona, Verona, Italy.,Department of Neurosurgery, IRCCS Fondazione Istituto Neurologico "C.Besta", Milano, Italy
| | - Andrea Sbarbati
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona
| | - Paolo Brambilla
- Department of Neuroscience and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.,Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| |
Collapse
|
46
|
Hirano Y, Oribe N, Onitsuka T, Kanba S, Nestor PG, Hosokawa T, Levin M, Shenton ME, McCarley RW, Spencer KM. Auditory Cortex Volume and Gamma Oscillation Abnormalities in Schizophrenia. Clin EEG Neurosci 2020; 51:244-251. [PMID: 32204613 DOI: 10.1177/1550059420914201] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
We investigated whether the gray matter volume of primary auditory cortex (Heschl's gyrus [HG]) was associated with abnormal patterns of auditory γ activity in schizophrenia, namely impaired γ synchronization in the 40-Hz auditory steady-state response (ASSR) and increased spontaneous broadband γ power. (The γ data were previously reported in Hirano et al, JAMA Psychiatry, 2015;72:813-821). Participants were 24 healthy controls (HC) and 23 individuals with chronic schizophrenia (SZ). The ASSR was obtained from the electroencephalogram to click train stimulation at 20, 30, and 40 Hz rates. Dipole source localization of the ASSR was used to provide a spatial filter of auditory cortex activity, from which ASSR evoked power and phase locking factor (PLF), and induced γ power were computed. HG gray matter volume was derived from structural magnetic resonance imaging at 3 T with manually traced regions of interest. As expected, HG gray matter volume was reduced in SZ compared with HC. In SZ, left hemisphere ASSR PLF and induced γ power during the 40-Hz stimulation condition were positively and negatively correlated with left HG gray matter volume, respectively. These results provide evidence that cortical gray matter structure, possibly resulting from reduced synaptic connectivity at the microcircuit level, is related to impaired γ synchronization and increased spontaneous γ activity in schizophrenia.
Collapse
Affiliation(s)
- Yoji Hirano
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Departments of Psychiatry and Radiology, Veterans Affairs Boston Healthcare System, and Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Naoya Oribe
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Departments of Psychiatry and Radiology, Veterans Affairs Boston Healthcare System, and Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiaki Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shigenobu Kanba
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Paul G Nestor
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Department of Psychology, University of Massachusetts, Boston, MA, USA
| | - Taiga Hosokawa
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA.,Departments of Psychiatry and Radiology, Veterans Affairs Boston Healthcare System, and Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Martha E Shenton
- Departments of Psychiatry and Radiology, Veterans Affairs Boston Healthcare System, and Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert W McCarley
- Laboratory of Neuroscience, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Kevin M Spencer
- Neural Dynamics Laboratory, Research Service, Veterans Affairs Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
47
|
Brain structural correlates of familial risk for mental illness: a meta-analysis of voxel-based morphometry studies in relatives of patients with psychotic or mood disorders. Neuropsychopharmacology 2020; 45:1369-1379. [PMID: 32353861 PMCID: PMC7297956 DOI: 10.1038/s41386-020-0687-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 04/19/2020] [Accepted: 04/22/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.
Collapse
|
48
|
Luza S, Opazo CM, Bousman CA, Pantelis C, Bush AI, Everall IP. The ubiquitin proteasome system and schizophrenia. Lancet Psychiatry 2020; 7:528-537. [PMID: 32061320 DOI: 10.1016/s2215-0366(19)30520-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 11/22/2019] [Accepted: 12/03/2019] [Indexed: 12/12/2022]
Abstract
The ubiquitin-proteasome system is a master regulator of neural development and the maintenance of brain structure and function. It influences neurogenesis, synaptogenesis, and neurotransmission by determining the localisation, interaction, and turnover of scaffolding, presynaptic, and postsynaptic proteins. Moreover, ubiquitin-proteasome system signalling transduces epigenetic changes in neurons independently of protein degradation and, as such, dysfunction of components and substrates of this system has been linked to a broad range of brain conditions. Although links between ubiquitin-proteasome system dysfunction and neurodegenerative disorders have been known for some time, only recently have similar links emerged for neurodevelopmental disorders, such as schizophrenia. Here, we review the components of the ubiquitin-proteasome system that are reported to be dysregulated in schizophrenia, and discuss specific molecular changes to these components that might, in part, explain the complex causes of this mental disorder.
Collapse
Affiliation(s)
- Sandra Luza
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia
| | - Carlos M Opazo
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia
| | - Chad A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; The Cooperative Research Centre for Mental Health, Carlton South, VIC, Australia; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada; University of Calgary, Calgary, AB, Canada
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Centre for Neural Engineering, Department of Electrical and Electronic Engineering, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; The Cooperative Research Centre for Mental Health, Carlton South, VIC, Australia; Alberta Children's Hospital Research Institute, Calgary, AB, Canada; NorthWestern Mental Health, Melbourne, VIC, Australia
| | - Ashley I Bush
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia.
| | - Ian P Everall
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; Centre for Neural Engineering, Department of Electrical and Electronic Engineering, The University of Melbourne & Melbourne Health, Parkville, VIC, Australia; The Cooperative Research Centre for Mental Health, Carlton South, VIC, Australia; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| |
Collapse
|
49
|
Shafiei G, Markello RD, Makowski C, Talpalaru A, Kirschner M, Devenyi GA, Guma E, Hagmann P, Cashman NR, Lepage M, Chakravarty MM, Dagher A, Mišić B. Spatial Patterning of Tissue Volume Loss in Schizophrenia Reflects Brain Network Architecture. Biol Psychiatry 2020; 87:727-735. [PMID: 31837746 DOI: 10.1016/j.biopsych.2019.09.031] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 09/04/2019] [Accepted: 09/30/2019] [Indexed: 12/25/2022]
Abstract
BACKGROUND There is growing recognition that connectome architecture shapes cortical and subcortical gray matter atrophy across a spectrum of neurological and psychiatric diseases. Whether connectivity contributes to tissue volume loss in schizophrenia in the same manner remains unknown. METHODS Here, we relate tissue volume loss in patients with schizophrenia to patterns of structural and functional connectivity. Gray matter deformation was estimated in a sample of 133 individuals with chronic schizophrenia (48 women, mean age 34.7 ± 12.9 years) and 113 control subjects (64 women, mean age 23.5 ± 8.4 years). Deformation-based morphometry was used to estimate cortical and subcortical gray matter deformation from T1-weighted magnetic resonance images. Structural and functional connectivity patterns were derived from an independent sample of 70 healthy participants using diffusion spectrum imaging and resting-state functional magnetic resonance imaging. RESULTS We found that regional deformation is correlated with the deformation of structurally and functionally connected neighbors. Distributed deformation patterns are circumscribed by specific functional systems (the ventral attention network) and cytoarchitectonic classes (limbic class), with an epicenter in the anterior cingulate cortex. CONCLUSIONS Altogether, the present study demonstrates that brain tissue volume loss in schizophrenia is conditioned by structural and functional connectivity, accounting for 25% to 35% of regional variance in deformation.
Collapse
Affiliation(s)
- Golia Shafiei
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Carolina Makowski
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Alexandra Talpalaru
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Matthias Kirschner
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Gabriel A Devenyi
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Elisa Guma
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Neil R Cashman
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Martin Lepage
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - M Mallar Chakravarty
- Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Quebec, Canada.
| |
Collapse
|
50
|
Sepede G, Chiacchiaretta P, Gambi F, Di Iorio G, De Berardis D, Ferretti A, Perrucci MG, Di Giannantonio M. Bipolar disorder with and without a history of psychotic features: fMRI correlates of sustained attention. Prog Neuropsychopharmacol Biol Psychiatry 2020; 98:109817. [PMID: 31756418 DOI: 10.1016/j.pnpbp.2019.109817] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 11/08/2019] [Accepted: 11/09/2019] [Indexed: 01/10/2023]
Affiliation(s)
- Gianna Sepede
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy.
| | - Piero Chiacchiaretta
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy; ITAB - Institute for Advanced Biomedical Technologies, University "G. d'Annunzio", Chieti, Italy
| | - Francesco Gambi
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy
| | | | | | - Antonio Ferretti
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy; ITAB - Institute for Advanced Biomedical Technologies, University "G. d'Annunzio", Chieti, Italy
| | - Mauro Gianni Perrucci
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy; ITAB - Institute for Advanced Biomedical Technologies, University "G. d'Annunzio", Chieti, Italy
| | - Massimo Di Giannantonio
- Department of Neuroscience, Imaging, and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy; Department of Mental Health - Chieti, National Health Trust, Italy
| |
Collapse
|