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García-León MÁ, Fuentes-Claramonte P, Soler-Vidal J, Ramiro-Sousa N, Salgado-Pineda P, Salavert J, Torres L, Guerrero-Pedraza A, Tristany J, Karuk A, Barbosa L, Del Olmo-Encabo P, Canut-Altemir P, Munuera J, Sarró S, Salvador R, McKenna PJ, Pomarol-Clotet E. Cortical volume abnormalities in schizophrenia: Correlations with symptoms and cognitive impairment. Schizophr Res 2024; 266:50-57. [PMID: 38368705 DOI: 10.1016/j.schres.2024.01.031] [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: 05/15/2023] [Revised: 01/10/2024] [Accepted: 01/22/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND Schizophrenic symptoms are known to segregate into reality distortion, negative and disorganization syndromes, but the correlates of these syndromes with regional brain structural change are not well established. Cognitive impairment is a further clinical feature of schizophrenia, whose brain structural correlates are the subject of conflicting findings. METHODS 165 patients with schizophrenia were rated for symptoms using the PANSS, and cognitive impairment was indexed by estimated premorbid-current IQ discrepancy. Cortical volume was measured using surface-based morphometry in the patients and in 50 healthy controls. Correlations between clinical and cognitive measures and cortical volume were examined using whole-brain FreeSurfer tools. RESULTS No clusters of volume reduction were seen associated with reality distortion or disorganization. Negative symptom scores showed a significant inverse correlation with volume in a small cluster in the left medial orbitofrontal gyrus. Larger estimated premorbid-current IQ discrepancies were associated with clusters of reduced cortical volume in the left precentral gyrus and the left temporal lobe. The cluster of association with negative symptoms disappeared when estimated premorbid-current IQ discrepancy was controlled for. CONCLUSIONS This study does not provide support for an association between brain structural abnormality and reality distortion or disorganization syndromes in schizophrenia. The cluster of volume reduction found in the left medial orbitofrontal cortex correlated with negative symptoms may have reflected the association between this class of symptoms and cognitive impairment. The study adds to existing findings of an association between cognitive impairment and brain structural changes in the disorder.
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Affiliation(s)
- María Ángeles García-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain.
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain
| | - Joan Soler-Vidal
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain; Benito Menni CASM, Sant Boi de Llobregat, Barcelona, Spain
| | | | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain
| | | | | | | | | | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | - Lucila Barbosa
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain
| | | | | | - Josep Munuera
- Diagnostic Imaging Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain
| | - Peter J McKenna
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain.
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM, ISCIII, Barcelona, Spain
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Joo SW, Jo YT, Kim Y, Lee WH, Chung YC, Lee J. Structural variability of the cerebral cortex in schizophrenia and its association with clinical symptoms. Psychol Med 2024; 54:399-408. [PMID: 37485703 DOI: 10.1017/s0033291723001988] [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: 07/25/2023]
Abstract
BACKGROUND Substantial evidence indicates structural abnormalities in the cerebral cortex of patients with schizophrenia (SCZ), although their clinical implications remain unclear. Previous case-control studies have investigated group-level differences in structural abnormalities, although the study design cannot account for interindividual differences. Recent research has focused on the association between the heterogeneity of the cerebral cortex morphometric features and clinical heterogeneity. METHODS We used neuroimaging data from 420 healthy controls and 695 patients with SCZ from seven studies. Four cerebral cortex measures were obtained: surface area, gray matter volume, thickness, and local gyrification index. We calculated the coefficient of variation (CV) and person-based similarity index (PBSI) scores and performed group comparisons. Associations between the PBSI scores and cognitive functions were evaluated using Spearman's rho test and normative modeling. RESULTS Patients with SCZ had a greater CV of surface area and cortical thickness than those of healthy controls. All PBSI scores across cortical measures were lower in patients with SCZ than in HCs. In the patient group, the PBSI scores for gray matter volume and all cortical measures taken together positively correlated with the full-scale IQ scores. Patients with deviant PBSI scores for gray matter volume and all cortical measures taken together had lower full-scale IQ scores than those of other patients. CONCLUSIONS The cerebral cortex in patients with SCZ showed greater regional and global structural variability than that in healthy controls. Patients with deviant similarity of cortical structural profiles exhibited a lower general intelligence than those exhibited by the other patients.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Yangsik Kim
- Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea
| | - Won Hee Lee
- Department of Software Convergence, Kyung Hee University, Yongin, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Chonbuk National University Medical School, Jeonju, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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3
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Burke T, Holleran L, Mothersill D, Lyons J, O'Rourke N, Gleeson C, Cannon DM, McKernan DP, Morris DW, Kelly JP, Hallahan B, McDonald C, Donohoe G. Bilateral anterior corona radiata microstructure organisation relates to impaired social cognition in schizophrenia. Schizophr Res 2023; 262:87-94. [PMID: 37931564 DOI: 10.1016/j.schres.2023.10.035] [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: 02/20/2023] [Revised: 09/25/2023] [Accepted: 10/28/2023] [Indexed: 11/08/2023]
Abstract
OBJECTIVE The Corona Radiata (CR) is a large white matter tract in the brain comprising of the anterior CR (aCR), superior CR (sCR), and posterior CR (pCR), which have associations with cognition, self-regulation, and, in schizophrenia, positive symptom severity. This study tested the hypothesis that the microstructural organisation of the aCR, as measured by Fractional Anisotropy (FA) using Diffusion Tensor Imaging (DTI), would relate to poorer social cognitive outcomes and higher positive symptom severity for people with schizophrenia, when compared to healthy participants. We further hypothesised that increased positive symptoms would relate to poorer social cognitive outcomes. METHODS Data were derived from n = 178 healthy participants (41 % females; 36.11 ± 12.36 years) and 58 people with schizophrenia (30 % females; 42.4 ± 11.1 years). The Positive and Negative Symptom Severity Scale measured clinical symptom severity. Social Cognition was measured using the Reading the Mind in the Eyes Test (RMET) Total Score, as well as the Positive, Neutral, and Negative stimuli valence. The ENIGMA-DTI protocol tract-based spatial statistics (TBSS) was used. RESULTS There was a significant difference in FA for the CR, in individuals with schizophrenia compared to healthy participants. On stratification, both the aCR and pCR were significantly different between groups, with patients showing reduced white matter tract microstructural organisation. Significant negative correlations were observed between positive symptomatology and reduced microstructural organisation of the aCR. Performance for RMET negative valence items was significantly correlated bilaterally with the aCR, but not the sCR or pCR, and no relationship to positive symptoms was observed. CONCLUSIONS These data highlight specific and significant microstructural white-matter differences for people with schizophrenia, which relates to positive clinical symptomology and poorer performance on social cognition stimuli. While reduced FA is associated with higher positive symptomatology in schizophrenia, this study shows the specific associated with anterior frontal white matter tracts and reduced social cognitive performance. The aCR may have a specific role to play in frontal-disconnection syndromes, psychosis, and social cognitive profile within schizophrenia, though further research requires more sensitive, specific, and detailed consideration of social cognition outcomes.
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Affiliation(s)
- Tom Burke
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - Laurena Holleran
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - David Mothersill
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland; Psychology Department, School of Business, National College of, Ireland
| | - James Lyons
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - Nathan O'Rourke
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - Christina Gleeson
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - Dara M Cannon
- Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland; Clinical Neuroimaging Laboratory, Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, University of Galway, Galway, Ireland
| | - Declan P McKernan
- Pharmacology & Therapeutics and Galway Neuroscience Centre, National University of Ireland Galway, H91 W5P7 Galway, Ireland
| | - Derek W Morris
- Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland
| | - John P Kelly
- Pharmacology & Therapeutics and Galway Neuroscience Centre, National University of Ireland Galway, H91 W5P7 Galway, Ireland
| | - Brian Hallahan
- Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland; Department of Psychiatry, Clinical Science Institute, National University of Ireland Galway, H91 TK33 Galway, Ireland
| | - Colm McDonald
- Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland; Department of Psychiatry, Clinical Science Institute, National University of Ireland Galway, H91 TK33 Galway, Ireland
| | - Gary Donohoe
- School of Psychology, University of Galway, Galway, Ireland; Center for Neuroimaging Cognition and Genomics, University of Galway, Galway, Ireland.
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Omlor W, Rabe F, Fuchs S, Cecere G, Homan S, Surbeck W, Kallen N, Georgiadis F, Spiller T, Seifritz E, Weickert T, Bruggemann J, Weickert C, Potkin S, Hashimoto R, Sim K, Rootes-Murdy K, Quide Y, Houenou J, Banaj N, Vecchio D, Piras F, Piras F, Spalletta G, Salvador R, Karuk A, Pomarol-Clotet E, Rodrigue A, Pearlson G, Glahn D, Tomecek D, Spaniel F, Skoch A, Kirschner M, Kaiser S, Kochunov P, Fan FM, Andreassen OA, Westlye LT, Berthet P, Calhoun VD, Howells F, Uhlmann A, Scheffler F, Stein D, Iasevoli F, Cairns MJ, Carr VJ, Catts SV, Di Biase MA, Jablensky A, Green MJ, Henskens FA, Klauser P, Loughland C, Michie PT, Mowry B, Pantelis C, Rasser PE, Schall U, Scott R, Zalesky A, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Di Giorgio A, Thomopoulos SI, Jahanshad N, Thompson PM, van Erp T, Turner J, Homan P. Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.22.559032. [PMID: 37961617 PMCID: PMC10634976 DOI: 10.1101/2023.09.22.559032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Objective Schizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. Methods This meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. Results We found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. Conclusions Higher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.
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Rodrigue AL, Hayes RA, Waite E, Corcoran M, Glahn DC, Jalbrzikowski M. Multimodal Neuroimaging Summary Scores as Neurobiological Markers of Psychosis. Schizophr Bull 2023:sbad149. [PMID: 37844289 DOI: 10.1093/schbul/sbad149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2023]
Abstract
BACKGROUND AND HYPOTHESIS Structural brain alterations are well-established features of schizophrenia but they do not effectively predict disease/disease risk. Similar to polygenic risk scores in genetics, we integrated multifactorial aspects of brain structure into a summary "Neuroscore" and examined its potential as a marker of disease. STUDY DESIGN We extracted measures from T1-weighted scans and diffusion tensor imaging (DTI) models from three studies with schizophrenia and healthy individuals. We calculated individual-level summary scores (Neuroscores) for T1-weighted and DTI measures and a combined score (Multimodal Neuroscore-MM). We assessed each score's ability to differentiate schizophrenia cases from controls and its relationship to clinical symptomatology, intelligence quotient (IQ), and medication dosage. We assessed Neuroscore specificity by performing all analyses in a more inclusive psychosis sample and by using scores generated from MDD effect sizes. STUDY RESULTS All Neuroscores significantly differentiated schizophrenia cases from controls (T1 d = 0.56, DTI d = 0.29, MM d = 0.64) to a greater degree than individual brain regions. Higher Neuroscores (ie, increased liability) were associated with lower IQ (T1 β = -0.26, DTI β = -0.15, MM β = -0.30). Higher T1-weighted Neuroscores were associated with higher positive and negative symptom severity (Positive β = 0.21, Negative β = 0.16); Higher Multimodal Neuroscores were associated with higher positive symptom severity (β = 0.30). SZ Neuroscores outperformed MDD Neuroscores in predicting IQ (T1: z = 3.5, q = 0.0007; MM: z = 1.8, q = 0.05). CONCLUSIONS Neuroscores are a step toward leveraging widespread structural brain alterations in psychosis to identify robust neurobiological markers of disease. Future studies will assess ways to improve neuroscore calculation, including developing the optimal methods to calculate neuroscores and considering disorder overlap.
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Affiliation(s)
- Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Rebecca A Hayes
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - Emma Waite
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - Mary Corcoran
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry, Boston Children's Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Han Y, Yang Y, Zhou Z, Jin X, Shi H, Shao M, Song M, Su X, Wang Q, Liu Q, Li W, Lv L. Cortical anatomical variations, gene expression profiles, and clinical phenotypes in patients with schizophrenia. Neuroimage Clin 2023; 39:103451. [PMID: 37315484 PMCID: PMC10509526 DOI: 10.1016/j.nicl.2023.103451] [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: 02/12/2023] [Revised: 06/01/2023] [Accepted: 06/05/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) patients display significant structural brain abnormalities; nevertheless, the genetic mechanisms regulating cortical anatomical variations and their correlation with the disease phenotype are still ambiguous. STUDY DESIGN We characterized anatomical variation using a surface-based method derived from structural magnetic resonance imaging of patients with SZ and age- and sex-matched healthy controls (HCs). Partial least-squares regression was performed across cortex regions between anatomical variation and average transcriptional profiles of SZ risk genes and all qualified genes from the Allen Human Brain Atlas. The morphological features of each brain region were correlated to symptomology variables in patients with SZ using partial correlation analysis. STUDY RESULTS A total of 203 SZ and 201 HCs were included in the final analysis. We observed significant variation of 55 regions of cortical thickness, 23 regions of volume, 7 regions of area, and 55 regions of local gyrification index (LGI) between SZ and HC groups. Expression profiles of 4 SZ risk genes and 96 genes from all qualified genes showed a correlation to anatomical variability, however, after multiple comparisons, the correlations were no longer significant. LGI variability in multiple frontal subregions was associated with specific symptoms of SZ, whereas cognitive function involving attention/vigilance was linked to LGI variability across nine brain regions. CONCLUSIONS Cortical anatomical variation of patients with schizophrenia is associated with gene transcriptome profiles as well as clinical phenotypes.
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Affiliation(s)
- Yong Han
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Zhilu Zhou
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xueyan Jin
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Minglong Shao
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Meng Song
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Xi Su
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Qi Wang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Qing Liu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China.
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China; Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, China.
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Ben-Azu B, del Re EC, VanderZwaag J, Carrier M, Keshavan M, Khakpour M, Tremblay MÈ. Emerging epigenetic dynamics in gut-microglia brain axis: experimental and clinical implications for accelerated brain aging in schizophrenia. Front Cell Neurosci 2023; 17:1139357. [PMID: 37256150 PMCID: PMC10225712 DOI: 10.3389/fncel.2023.1139357] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 04/27/2023] [Indexed: 06/01/2023] Open
Abstract
Brain aging, which involves a progressive loss of neuronal functions, has been reported to be premature in probands affected by schizophrenia (SCZ). Evidence shows that SCZ and accelerated aging are linked to changes in epigenetic clocks. Recent cross-sectional magnetic resonance imaging analyses have uncovered reduced brain reserves and connectivity in patients with SCZ compared to typically aging individuals. These data may indicate early abnormalities of neuronal function following cyto-architectural alterations in SCZ. The current mechanistic knowledge on brain aging, epigenetic changes, and their neuropsychiatric disease association remains incomplete. With this review, we explore and summarize evidence that the dynamics of gut-resident bacteria can modulate molecular brain function and contribute to age-related neurodegenerative disorders. It is known that environmental factors such as mode of birth, dietary habits, stress, pollution, and infections can modulate the microbiota system to regulate intrinsic neuronal activity and brain reserves through the vagus nerve and enteric nervous system. Microbiota-derived molecules can trigger continuous activation of the microglial sensome, groups of receptors and proteins that permit microglia to remodel the brain neurochemistry based on complex environmental activities. This remodeling causes aberrant brain plasticity as early as fetal developmental stages, and after the onset of first-episode psychosis. In the central nervous system, microglia, the resident immune surveillance cells, are involved in neurogenesis, phagocytosis of synapses and neurological dysfunction. Here, we review recent emerging experimental and clinical evidence regarding the gut-brain microglia axis involvement in SCZ pathology and etiology, the hypothesis of brain reserve and accelerated aging induced by dietary habits, stress, pollution, infections, and other factors. We also include in our review the possibilities and consequences of gut dysbiosis activities on microglial function and dysfunction, together with the effects of antipsychotics on the gut microbiome: therapeutic and adverse effects, role of fecal microbiota transplant and psychobiotics on microglial sensomes, brain reserves and SCZ-derived accelerated aging. We end the review with suggestions that may be applicable to the clinical setting. For example, we propose that psychobiotics might contribute to antipsychotic-induced therapeutic benefits or adverse effects, as well as reduce the aging process through the gut-brain microglia axis. Overall, we hope that this review will help increase the understanding of SCZ pathogenesis as related to chronobiology and the gut microbiome, as well as reveal new concepts that will serve as novel treatment targets for SCZ.
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Affiliation(s)
- Benneth Ben-Azu
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Department of Pharmacology, Faculty of Basic Medical Sciences, College of Health Sciences, Delta State University, Abraka, Nigeria
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- VA Boston Healthcare System, Brockton, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Jared VanderZwaag
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Micaël Carrier
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
- Beth Israel Deaconess Medical Center, Boston, MA, United States
| | | | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Axe Neurosciences, Centre de Recherche du CHU de Québec, Université Laval, Québec City, QC, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
- Department of Molecular Medicine, Université Laval, Québec City, QC, Canada
- Centre for Advanced Materials and Related Technology (CAMTEC), Institute on Aging and Lifelong Health (IALH), University of Victoria, Victoria, BC, Canada
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Chen Y, Cao H, Liu S, Zhang B, Zhao G, Zhang Z, Li S, Li H, Yu X, Deng H. Brain Structure Measurements Predict Individualized Treatment Outcome of 12-Week Antipsychotic Monotherapies in First-episode Schizophrenia. Schizophr Bull 2023; 49:697-705. [PMID: 37010371 PMCID: PMC10154710 DOI: 10.1093/schbul/sbad043] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
BACKGROUND AND HYPOTHESIS Early prediction of treatment response to antipsychotics in schizophrenia remains a challenge in clinical practice. This study aimed to investigate if brain morphometries including gray matter volume and cortical thickness could serve as potential predictive biomarkers in first-episode schizophrenia. STUDY DESIGN Sixty-eight drug-naïve first-episode patients underwent baseline structural MRI scans and were subsequently randomized to receive a single antipsychotic throughout the first 12 weeks. Assessments for symptoms and social functioning were conducted by eight "core symptoms" selected from the Positive and Negative Syndrome Scale (PANSS-8) and the Personal and Social performance scale (PSP) multiple times during follow-ups. Treatment outcome was evaluated as subject-specific slope coefficients for PANSS-8 and PSP scores using linear mixed model. LASSO regression model were conducted to examine the performance of baseline gray matter volume and cortical thickness in prediction of individualized treatment outcome. STUDY RESULTS The study showed that individual brain morphometries at baseline, especially the orbitofrontal, temporal and parietal cortex, pallidum and amygdala, significantly predicted 12-week treatment outcome of PANSS-8 (r[predicted vs observed] = 0.49, P = .001) and PSP (r[predicted vs observed] = 0.40, P = .003) in first-episode schizophrenia. Moreover, the gray matter volume performed better than cortical thickness in the prediction the symptom changes (P = .034), while cortical thickness outperformed gray matter volume in the prediction of outcome of social functioning (P = .029). CONCLUSIONS These findings provide initial evidence that brain morphometry have potential to be used as prognostic predictors for antipsychotic response in patients, encouraging the future investigation of the translational value of these measures in precision psychiatry.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Center for Psychiatric Neuroscience, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Shanming Liu
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Bo Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | | | - Zhuoqiu Zhang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Shuiying Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Haiming Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Hong Deng
- Hope Recovery and Rehabilitation Center, West China Hospital of Sichuan University, Chengdu, China
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
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9
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Le H, Dimitrakopoulou K, Patel H, Curtis C, Cordero-Grande L, Edwards AD, Hajnal J, Tournier JD, Deprez M, Cullen H. Effect of schizophrenia common variants on infant brain volumes: cross-sectional study in 207 term neonates in developing Human Connectome Project. Transl Psychiatry 2023; 13:121. [PMID: 37037832 PMCID: PMC10085987 DOI: 10.1038/s41398-023-02413-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 03/16/2023] [Accepted: 03/24/2023] [Indexed: 04/12/2023] Open
Abstract
Increasing lines of evidence suggest deviations from the normal early developmental trajectory could give rise to the onset of schizophrenia during adolescence and young adulthood, but few studies have investigated brain imaging changes associated with schizophrenia common variants in neonates. This study compared the brain volumes of both grey and white matter regions with schizophrenia polygenic risk scores (PRS) for 207 healthy term-born infants of European ancestry. Linear regression was used to estimate the relationship between PRS and brain volumes, with gestational age at birth, postmenstrual age at scan, ancestral principal components, sex and intracranial volumes as covariates. The schizophrenia PRS were negatively associated with the grey (β = -0.08, p = 4.2 × 10-3) and white (β = -0.13, p = 9.4 × 10-3) matter superior temporal gyrus volumes, white frontal lobe volume (β = -0.09, p = 1.5 × 10-3) and the total white matter volume (β = -0.062, p = 1.66 × 10-2). This result also remained robust when incorporating individuals of Asian ancestry. Explorative functional analysis of the schizophrenia risk variants associated with the right frontal lobe white matter volume found enrichment in neurodevelopmental pathways. This preliminary result suggests possible involvement of schizophrenia risk genes in early brain growth, and potential early life structural alterations long before the average age of onset of the disease.
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Affiliation(s)
- Hai Le
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK.
| | - Konstantina Dimitrakopoulou
- Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy's and St. Thomas' NHS Foundation Trust and King's College London, London, UK
| | - Hamel Patel
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Charles Curtis
- NIHR Maudsley Biomedical Research Centre, King's College London, London, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, ISCIII, Madrid, Spain
| | - A David Edwards
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Joseph Hajnal
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Maria Deprez
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
| | - Harriet Cullen
- Centre for the Developing Brain, Perinatal Imaging and Health Department, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
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10
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Mao Q, Lin X, Yin Q, Liu P, Zhang Y, Qu S, Xu J, Cheng W, Luo X, Kang L, Taximaimaiti R, Zheng C, Zhang H, Wang X, Ren H, Cao Y, Lin J, Luo X. A significant, functional and replicable risk KTN1 variant block for schizophrenia. Sci Rep 2023; 13:3890. [PMID: 36890161 PMCID: PMC9995530 DOI: 10.1038/s41598-023-27448-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/02/2023] [Indexed: 03/10/2023] Open
Abstract
Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10-5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10-12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10-4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10-3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10-3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10-19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10-19 ≤ p ≤ 1.0 × 10-4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.
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Affiliation(s)
- Qiao Mao
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Xiandong Lin
- Laboratory of Radiation Oncology and Radiobiology, Fujian Provincial Cancer Hospital, the Teaching Hospital of Fujian Medical University, Fuzhou, 350014, Fujian, China
| | - Qin Yin
- Department of Respiratory and Critical Care Medicine, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Wuhan, 430000, Hubei, China
| | - Ping Liu
- Department of Psychosomatic Medicine, People's Hospital of Deyang City, Deyang, 618000, Sichuan, China
| | - Yong Zhang
- Tianjin Mental Health Center, Tianjin, 300222, China
| | - Shihao Qu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Jianying Xu
- Zhuhai Center for Maternal and Child Health Care, Zhuhai, Guangdong, 519001, China
| | - Wenhong Cheng
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xinqun Luo
- Department of Neurosurgery, The First Hospital, Fujian Medical University, Fuzhou, 350004, Fujian, China
| | - Longli Kang
- Key Laboratory for Molecular Genetic Mechanisms and Intervention Research On High Altitude Diseases of Tibet Autonomous Region, Xizang Minzu University School of Medicine, Xiangyang, 712082, Shaanxi, China
| | - Reyisha Taximaimaiti
- Department of Neurology, Shanghai Tongren Hospital, Shanghai Jiao Tong University, Shanghai, 200080, China
| | - Chengchou Zheng
- Minqing Psychiatric Hospital, Minqing, 350800, Fujian, China
| | - Huihao Zhang
- The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350001, China
| | - Xiaoping Wang
- Department of Neurology, The 1st People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 201620, USA
| | - Honggang Ren
- Department of Internal Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuping Cao
- Department of Psychiatry, Second Xiangya Hospital, Central South University, China National Clinical Research Center On Mental Disorders, China National Technology Institute On Mental Disorders, Changsha, 410011, Hunan, China.
| | - Jie Lin
- Fujian Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
- Fujian Institute of Preventive Medicine, Fuzhou, 350012, Fujian, China.
| | - Xingguang Luo
- Beijing Huilongguan Hospital, Peking University Huilongguan School of Clinical Medicine, Beijing, 100096, China.
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11
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Wang Z, Liu C, Dong Q, Xue G, Chen C. Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population. Biol Psychol 2023; 178:108530. [PMID: 36858107 DOI: 10.1016/j.biopsycho.2023.108530] [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: 09/08/2022] [Revised: 02/23/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023]
Abstract
Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.
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Affiliation(s)
- Ziyi Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Experimental School Attached to Haidian Teachers' Training College, Xiangshan Branch, Beijing, China
| | - Chang Liu
- Department of Psychology, Washington State University, Pullman, WA, USA
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chunhui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
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12
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Zhu JD, Tsai SJ, Lin CP, Lee YJ, Yang AC. Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:1. [PMID: 36596800 PMCID: PMC9810255 DOI: 10.1038/s41537-022-00325-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 12/20/2022] [Indexed: 01/05/2023]
Abstract
Brain-age prediction is a novel approach to assessing deviated brain aging trajectories in different diseases. However, most studies have used an average brain age gap (BAG) of individuals with schizophrenia of different illness durations for comparison with healthy participants. Therefore, this study investigated whether declined brain structures as reflected by BAGs may be present in schizophrenia in terms of brain volume, cortical thickness, and fractional anisotropy across different illness durations. We used brain volume, cortical thickness, and fractional anisotropy as features to train three models from the training dataset. Three models were applied to predict brain ages in the hold-out test and schizophrenia datasets and calculate BAGs. We divided the schizophrenia dataset into multiple groups based on the illness duration using a sliding time window approach for ANCOVA analysis. The brain volume and cortical thickness models revealed that, in comparison with healthy controls, individuals with schizophrenia had larger BAGs across different illness durations, whereas the BAG in terms of fractional anisotropy did not differ from that of healthy controls after disease onset. Moreover, the BAG at the initial stage of schizophrenia was the largest in the cortical thickness model. In contrast, the BAG from approximately two decades after disease onset was the largest in the brain volume model. Our findings suggest that schizophrenia differentially affects the decline of different brain structures during the disease course. Moreover, different trends of decline in thickness and volume-based measures suggest a differential decline in dimensions of brain structure throughout the course of schizophrenia.
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Affiliation(s)
- Jun-Ding Zhu
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.278247.c0000 0004 0604 5314Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ching-Po Lin
- grid.260539.b0000 0001 2059 7017Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yi-Ju Lee
- grid.28665.3f0000 0001 2287 1366Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Albert C. Yang
- grid.260539.b0000 0001 2059 7017Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.260539.b0000 0001 2059 7017Digital Medicine and Smart Healthcare Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan ,grid.278247.c0000 0004 0604 5314Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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13
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Chang X, Zhao W, Kang J, Xiang S, Xie C, Corona-Hernández H, Palaniyappan L, Feng J. Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:95. [PMID: 36371445 PMCID: PMC9653408 DOI: 10.1038/s41537-022-00308-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.
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Affiliation(s)
- Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Shanghai Center for Mathematical Sciences, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Hugo Corona-Hernández
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
- Lawson Health Research Institute, London, Ontario, Canada.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Shanghai Center for Mathematical Sciences, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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14
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Zhou H, Wang D, Cao B, Zhang X. Association of reduced cortical thickness and psychopathological symptoms in patients with first-episode drug-naïve schizophrenia. Int J Psychiatry Clin Pract 2022; 27:42-50. [PMID: 36193901 DOI: 10.1080/13651501.2022.2129067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/10/2022]
Abstract
OBJECTIVE There is growing evidence that reduced cortical thickness has been considered to be a central abnormality in schizophrenia. Brain imaging studies have demonstrated that the cerebral cortex becomes thinner in patients with first-episode schizophrenia. This study aimed to examine whether cortical thickness is altered in drug-naïve schizophrenia in a Chinese Han population and the relationship between cortical thickness and clinical symptoms. METHODS We compared cortical thickness in 41 schizophrenia patients and 30 healthy controls. Psychopathology of patients with schizophrenia was assessed using the Positive and Negative Syndrome Scale (PANSS). RESULTS The cortical thickness of left banks of superior temporal sulcus, left lateral occipital gyrus, left rostral middle frontal gyrus, right inferior parietal lobule and right lateral occipital gyrus in schizophrenia patients was generally thinner compared with healthy controls. Correlation analysis revealed a negative correlation between cortical thickness of the left banks of superior temporal sulcus and general psychopathology of PANSS. CONCLUSIONS Our results suggest that cortical thickness abnormalities are already present early in the onset of schizophrenia and are associated with psychopathological symptoms, suggesting that it plays an important role in the pathogenesis and symptomatology of schizophrenia.Key points(1) The first-episode drug-naïve schizophrenia had reduced cortical thickness than the controls.(2) Cortical thickness was associated with psychopathological symptoms in patients with schizophrenia.
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Affiliation(s)
- Huixia Zhou
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Dongmei Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.,Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xiangyang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, PR China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
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15
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Cattarinussi G, Kubera KM, Hirjak D, Wolf RC, Sambataro F. Neural Correlates of the Risk for Schizophrenia and Bipolar Disorder: A Meta-analysis of Structural and Functional Neuroimaging Studies. Biol Psychiatry 2022; 92:375-384. [PMID: 35523593 DOI: 10.1016/j.biopsych.2022.02.960] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/28/2022] [Accepted: 02/23/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (RELs), and early recognition biomarkers in ultrahigh risk populations. However, a comprehensive meta-analysis of structural and functional magnetic resonance imaging (MRI) studies examining relatives of patients with SCZ and BD has not been performed yet. METHODS We systematically searched PubMed, Scopus, and Web of Science for structural and functional MRI studies investigating relatives and healthy control subjects. A total of 230 eligible neuroimaging studies (6274 SCZ-RELs, 1900 BD-RELs, 10,789 healthy control subjects) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 structural MRI and 81 functional MRI investigations, including stratification by task type. We also meta-analyzed regional and global volumetric changes. Finally, we performed a meta-analysis of all MRI studies combined. RESULTS Reduced thalamic volume was present in both SCZ and BD RELs. Moreover, SCZ-RELs showed alterations in corticostriatal-thalamic networks, spanning the dorsolateral prefrontal cortex and temporal regions, while BD-RELs showed altered thalamocortical and limbic regions, including the ventrolateral prefrontal, superior parietal, and medial temporal cortices, with frontoparietal alterations in RELs of BD type I. CONCLUSIONS Familiarity for SCZ and BD is associated with alterations in the thalamocortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Fabio Sambataro
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy.
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16
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Qi S, Sui J, Pearlson G, Bustillo J, Perrone-Bizzozero NI, Kochunov P, Turner JA, Fu Z, Shao W, Jiang R, Yang X, Liu J, Du Y, Chen J, Zhang D, Calhoun VD. Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network. Nat Commun 2022; 13:4929. [PMID: 35995794 PMCID: PMC9395379 DOI: 10.1038/s41467-022-32513-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 08/03/2022] [Indexed: 12/23/2022] Open
Abstract
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread functional and structural brain abnormalities. However, previous association studies between MRI and polygenic risk were mostly ROI-based single modality analyses, rather than identifying brain-based multimodal predictive biomarkers. Based on schizophrenia polygenic risk scores (PRS) from healthy white people within the UK Biobank dataset (N = 22,459), we discovered a robust PRS-associated brain pattern with smaller gray matter volume and decreased functional activation in frontotemporal cortex, which distinguished schizophrenia from controls with >83% accuracy, and predicted cognition and symptoms across 4 independent schizophrenia cohorts. Further multi-disease comparisons demonstrated that these identified frontotemporal alterations were most severe in schizophrenia and schizo-affective patients, milder in bipolar disorder, and indistinguishable from controls in autism, depression and attention-deficit hyperactivity disorder. These findings indicate the potential of the identified PRS-associated multimodal frontotemporal network to serve as a trans-diagnostic gene intermediated brain biomarker specific to schizophrenia.
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Affiliation(s)
- Shile Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
| | - Godfrey Pearlson
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Juan Bustillo
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Nora I Perrone-Bizzozero
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Wei Shao
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Xiao Yang
- Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jingyu Liu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | - Yuhui Du
- School of Computer & Information Technology, Shanxi University, Taiyuan, China
| | - Jiayu Chen
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA.
| | - Daoqiang Zhang
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
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17
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Karcher NR, Merchant J, Pine J, Kilciksiz CM. Cognitive Dysfunction as a Risk Factor for Psychosis. Curr Top Behav Neurosci 2022; 63:173-203. [PMID: 35989398 DOI: 10.1007/7854_2022_387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The current chapter summarizes recent evidence for cognition as a risk factor for the development of psychosis, including the range of cognitive impairments that exist across the spectrum of psychosis risk symptoms. The chapter examines several possible theories linking cognitive deficits with the development of psychotic symptoms, including evidence that cognitive deficits may be an intermediate risk factor linking genetic and/or neural metrics to psychosis spectrum symptoms. Although there is not strong evidence for unique cognitive markers associated specifically with psychosis compared to other forms of psychopathology, psychotic disorders are generally associated with the greatest severity of cognitive deficits. Cognitive deficits precede the development of psychotic symptoms and may be detectable as early as childhood. Across the psychosis spectrum, both the presence and severity of psychotic symptoms are associated with mild to moderate impairments across cognitive domains, perhaps most consistently for language, cognitive control, and working memory domains. Research generally indicates the size of these cognitive impairments worsens as psychosis symptom severity increases. The chapter points out areas of unclarity and unanswered questions in each of these areas, including regarding the mechanisms contributing to the association between cognition and psychosis, the timing of deficits, and whether any cognitive systems can be identified that function as specific predictors of psychosis risk symptoms.
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Affiliation(s)
- Nicole R Karcher
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
| | - Jaisal Merchant
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Jacob Pine
- Department of Brain and Psychological Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Can Misel Kilciksiz
- Department of Psychiatry, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
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18
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Yin Y, Tong J, Huang J, Tian B, Chen S, Tan S, Wang Z, Yang F, Tong Y, Fan F, Kochunov P, Jahanshad N, Li CSR, Hong LE, Tan Y. History of suicide attempts associated with the thinning right superior temporal gyrus among individuals with schizophrenia. Brain Imaging Behav 2022; 16:1893-1901. [PMID: 35545740 PMCID: PMC10025969 DOI: 10.1007/s11682-021-00624-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2021] [Indexed: 11/02/2022]
Abstract
Individuals with schizophrenia have higher rates of suicide attempts than the general population. Specific cortical abnormalities (e.g., the cortical surface area and thickness) may be associated with a history of suicide attempts. We recruited 74 individuals with schizophrenia (37 suicide attempters were individually matched with 37 non-attempters on age, sex, phase of illness, and study center) and 37 healthy volunteers. The cortical surface area and thickness data were extracted from structural MRI and compared between the groups. Suicide attempters showed significantly smaller surface areas in the whole brain (p = .028, Cohen's d = -0.54) than non-attempters. No association was found between the cortical surface area of individual brain regions and a history of suicide attempts. The mean cortical thickness did not differ significantly between the groups; however, suicide attempters demonstrated a thinner cortex in the right superior temporal gyrus (p < .001, q = 0.037, Cohen's d = -0.88). These findings indicate that a history of suicide attempts among individuals with schizophrenia is associated with a reduction in the global cortical surface area and specific cortical thinning of the right superior temporal gyrus. The morphometric alteration of the right superior temporal gyrus may represent a biomarker of suicidal behavior in individuals with schizophrenia.
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Affiliation(s)
- Yi Yin
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Yongsheng Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
- Beijing Suicide Research and Prevention Center, WHO Collaborating Center for Research and Training in Suicide Prevention, Beijing, China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Neda Jahanshad
- Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing, People's Republic of China.
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19
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Yue W, Huang H, Duan J. Potential diagnostic biomarkers for schizophrenia. MEDICAL REVIEW (BERLIN, GERMANY) 2022; 2:385-416. [PMID: 37724326 PMCID: PMC10388817 DOI: 10.1515/mr-2022-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/20/2022] [Indexed: 09/20/2023]
Abstract
Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.
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Affiliation(s)
- Weihua Yue
- Institute of Mental Health, Peking University Sixth Hospital, Beijing, China
- National Clinical Research Center for Mental Disorders & NHC Key Laboratory of Mental Health (Peking University) and Chinese Academy of Medical Sciences Research Unit, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Jubao Duan
- Center for Psychiatric Genetics, NorthShore University Health System, Evanston, IL, USA
- Department of Psychiatry and Behavioral Neurosciences, University of Chicago, Chicago, IL, USA
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20
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Rodrigue AL, Mathias SR, Knowles EEM, Mollon J, Almasy L, Schultz L, Turner J, Calhoun V, Glahn DC. Specificity of Psychiatric Polygenic Risk Scores and their Effects on Associated Risk Phenotypes. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022. [PMID: 37519455 PMCID: PMC10382704 DOI: 10.1016/j.bpsgos.2022.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Polygenic risk scores (PRSs) are indices of genetic liability for illness, but their clinical utility for predicting risk for a specific psychiatric disorder is limited. Genetic overlap among disorders and their effects on allied phenotypes may be a possible explanation, but this has been difficult to quantify given focus on singular disorders and/or allied phenotypes. Methods We constructed PRSs for 5 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder) and 3 nonpsychiatric control traits (height, type II diabetes, irritable bowel disease) in the UK Biobank (N = 31,616) and quantified associations between PRSs and phenotypes allied with mental illness: behavioral (symptoms, cognition, trauma) and brain measures from magnetic resonance imaging. We then evaluated the extent of specificity among PRSs and their effects on these allied phenotypes. Results Correlations among psychiatric PRSs replicated previous work, with overlap between schizophrenia and bipolar disorder, which was distinct from overlap between autism spectrum disorder and attention-deficit/hyperactivity disorder; overlap between psychiatric and control PRSs was minimal. There was, however, substantial overlap of PRS effects on allied phenotypes among psychiatric disorders and among psychiatric disorders and control traits, where the extent and pattern of overlap was phenotype specific. Conclusions Results show that genetic distinctions between psychiatric disorders and between psychiatric disorders and control traits exist, but this does not extend to their effects on allied phenotypes. Although overlap can be informative, work is needed to construct PRSs that will function at the level of specificity needed for clinical application.
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21
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Cheon EJ, Bearden CE, Sun D, Ching CRK, Andreassen OA, Schmaal L, Veltman DJ, Thomopoulos SI, Kochunov P, Jahanshad N, Thompson PM, Turner JA, van Erp TG. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings. Psychiatry Clin Neurosci 2022; 76:140-161. [PMID: 35119167 PMCID: PMC9098675 DOI: 10.1111/pcn.13337] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 11/29/2021] [Accepted: 01/21/2022] [Indexed: 12/25/2022]
Abstract
This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.
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Affiliation(s)
- Eun-Jin Cheon
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Department of Psychiatry, Yeungnam University College of Medicine, Yeungnam University Medical Center, Daegu, Republic of Korea
| | - Carrie E. Bearden
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Daqiang Sun
- Departments of Psychiatry and Biobehavioral Sciences and Psychology, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ole A. Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, Parkville, Australia
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlant, GA, USA
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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22
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Lawrie SM. Do antipsychotic drugs shrink the brain? Probably not. J Psychopharmacol 2022; 36:425-427. [PMID: 35395921 DOI: 10.1177/02698811221092252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Stephen M Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
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23
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Cao X, Li Q, Liu S, Li Z, Wang Y, Cheng L, Yang C, Xu Y. Enhanced Resting-State Functional Connectivity of the Nucleus Accumbens in First-Episode, Medication-Naïve Patients With Early Onset Schizophrenia. Front Neurosci 2022; 16:844519. [PMID: 35401094 PMCID: PMC8990232 DOI: 10.3389/fnins.2022.844519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 02/01/2022] [Indexed: 01/10/2023] Open
Abstract
There is abundant evidence that early onset schizophrenia (EOS) is associated with abnormalities in widespread regions, including the cortical, striatal, and limbic areas. As a main component of the ventral striatum, the nucleus accumbens (NAc) is implicated in the pathology of schizophrenia. However, functional connection patterns of NAc in patients with schizophrenia, especially EOS, are seldom explored. A total of 78 first-episode, medication-naïve patients with EOS and 90 healthy controls were recruited in the present study, and resting-state, seed-based functional connectivity (FC) analyses were performed to investigate temporal correlations between NAc and the rest of the brain in the two groups. Additionally, correlation analyses were done between regions showing group differences in NAc functional integration and clinical features of EOS. Group comparison found enhanced FC of the NAc in the EOS group relative to the HCs with increased FC in the right superior temporal gyrus and left superior parietal gyrus with the left NAc region of interest (ROI) and elevated FC in left middle occipital gyrus with the right NAc ROI. No significant associations were found between FC strength and symptom severity as well as the age of the patients. Our findings reveal abnormally enhanced FC of the NAc with regions located in the temporal, parietal, and occipital areas, which were implicated in auditory/visual processing, sensorimotor integration, and cognitive functions. The results suggest disturbed relationships between regions subserving reward, salience processing, and regions subserving sensory processing as well as cognitive functions, which may deepen our understanding of the role of NAc in the pathology of EOS.
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Affiliation(s)
- Xiaohua Cao
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Qiang Li
- Shanxi Provincial Corps Hospital of Chinese People’s Armed Police Force, Taiyuan, China
| | - Sha Liu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Zexuan Li
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yanfang Wang
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Long Cheng
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
| | - Chengxiang Yang
- Department of Psychiatry, Shanxi Bethune Hospital, Taiyuan, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, China
- Department of Mental Health, Shanxi Medical University, Taiyuan, China
- Shanxi Provincial Key Laboratory of Brain Science and Neuropsychiatric Diseases, Taiyuan, China
- *Correspondence: Yong Xu, ;
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24
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Abstract
Schizophrenia, characterised by psychotic symptoms and in many cases social and occupational decline, remains an aetiological and therapeutic challenge. Contrary to popular belief, the disorder is modestly more common in men than in women. Nor is the outcome uniformly poor. A division of symptoms into positive, negative, and disorganisation syndromes is supported by factor analysis. Catatonic symptoms are not specific to schizophrenia and so-called first rank symptoms are no longer considered diagnostically important. Cognitive impairment is now recognised as a further clinical feature of the disorder. Lateral ventricular enlargement and brain volume reductions of around 2% are established findings. Brain functional changes occur in different subregions of the frontal cortex and might ultimately be understandable in terms of disturbed interaction among large-scale brain networks. Neurochemical disturbance, involving dopamine function and glutamatergic N-methyl-D-aspartate receptor function, is supported by indirect and direct evidence. The genetic contribution to schizophrenia is now recognised to be largely polygenic. Birth and early life factors also have an important aetiological role. The mainstay of treatment remains dopamine receptor-blocking drugs; a psychological intervention, cognitive behavioural therapy, has relatively small effects on symptoms. The idea that schizophrenia is better regarded as the extreme end of a continuum of psychotic symptoms is currently influential. Other areas of debate include cannabis and childhood adversity as causative factors, whether there is progressive brain change after onset, and the long-term success of early intervention initiatives.
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Affiliation(s)
- Sameer Jauhar
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College, London, UK
| | - Mandy Johnstone
- Department of Psychological Medicine, Institute of Psychiatry, Psychology, and Neuroscience, King's College, London, UK; National Psychosis Service, South London and Maudsley NHS Foundation Trust, London, UK
| | - Peter J McKenna
- FIDMAG Hermanas Hospitalarias Research Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Madrid, Spain.
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25
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Huang Z, Ruan D, Huang B, Zhou T, Shi C, Yu X, Chan RCK, Wang Y, Pu C. Negative symptoms correlate with altered brain structural asymmetry in amygdala and superior temporal region in schizophrenia patients. Front Psychiatry 2022; 13:1000560. [PMID: 36226098 PMCID: PMC9548644 DOI: 10.3389/fpsyt.2022.1000560] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 09/05/2022] [Indexed: 11/18/2022] Open
Abstract
Negative symptoms play an important role in development and treatment of schizophrenia. However, brain changes relevant to negative symptoms are still unclear. This study examined brain structural abnormalities and their asymmetry in schizophrenia patients and the association with negative symptoms. Fifty-nine schizophrenia patients and 66 healthy controls undertook structural brain scans. Schizophrenia patients were further divided into predominant negative symptoms (PNS, n = 18) and non-PNS (n = 34) subgroups. Negative symptoms were assessed by the Negative Symptom Assessment (NSA). T1-weighted images were preprocessed with FreeSurfer to estimate subcortical volumes, cortical thickness and surface areas, asymmetry Index (AI) was then calculated. MANOVA was performed for group differences while partial correlations in patients were analyzed between altered brain structures and negative symptoms. Compared to healthy controls, schizophrenia patients exhibited thinner cortices in frontal and temporal regions, and decreased leftward asymmetry of superior temporal gyrus (STG) in cortical thickness. Patients with PNS exhibited increased rightward asymmetry of amygdala volumes than non-PNS subgroup. In patients, AI of cortical thickness in the STG was negatively correlated with NSA-Emotion scores (r = -0.30, p = 0.035), while AI of amygdala volume was negatively correlated with NSA-Communication (r = -0.30, p = 0.039) and NSA-Total scores (r = -0.30, p = 0.038). Our findings suggested schizophrenia patients exhibited cortical thinning and altered lateralization of brain structures. Emotion and communication dimensions of negative symptoms also correlated with the structural asymmetry of amygdala and superior temporal regions in schizophrenia patients.
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Affiliation(s)
- Zetao Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Dun Ruan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Bingjie Huang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tianhang Zhou
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Chuan Shi
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Xin Yu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chengcheng Pu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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26
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Kirschner M, Hodzic-Santor B, Antoniades M, Nenadic I, Kircher T, Krug A, Meller T, Grotegerd D, Fornito A, Arnatkeviciute A, Bellgrove MA, Tiego J, Dannlowski U, Koch K, Hülsmann C, Kugel H, Enneking V, Klug M, Leehr EJ, Böhnlein J, Gruber M, Mehler D, DeRosse P, Moyett A, Baune BT, Green M, Quidé Y, Pantelis C, Chan R, Wang Y, Ettinger U, Debbané M, Derome M, Gaser C, Besteher B, Diederen K, Spencer TJ, Fletcher P, Rössler W, Smigielski L, Kumari V, Premkumar P, Park HRP, Wiebels K, Lemmers-Jansen I, Gilleen J, Allen P, Kozhuharova P, Marsman JB, Lebedeva I, Tomyshev A, Mukhorina A, Kaiser S, Fett AK, Sommer I, Schuite-Koops S, Paquola C, Larivière S, Bernhardt B, Dagher A, Grant P, van Erp TGM, Turner JA, Thompson PM, Aleman A, Modinos G. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study. Mol Psychiatry 2022; 27:1167-1176. [PMID: 34707236 PMCID: PMC9054674 DOI: 10.1038/s41380-021-01359-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/02/2021] [Accepted: 10/08/2021] [Indexed: 02/04/2023]
Abstract
Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.
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Affiliation(s)
- Matthias Kirschner
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada ,grid.7400.30000 0004 1937 0650Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Benazir Hodzic-Santor
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Mathilde Antoniades
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Igor Nenadic
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Tilo Kircher
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Axel Krug
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany ,grid.10388.320000 0001 2240 3300Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Tina Meller
- grid.10253.350000 0004 1936 9756University of Marburg, Marburg, Germany
| | - Dominik Grotegerd
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Alex Fornito
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Aurina Arnatkeviciute
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Mark A. Bellgrove
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Jeggan Tiego
- grid.1002.30000 0004 1936 7857Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Melbourne, VIC Australia
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Katharina Koch
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Carina Hülsmann
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Harald Kugel
- grid.5949.10000 0001 2172 9288University Clinic for Radiology, University of Münster, Münster, Germany
| | - Verena Enneking
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Melissa Klug
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth J. Leehr
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Joscha Böhnlein
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - David Mehler
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Pamela DeRosse
- grid.416477.70000 0001 2168 3646Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY USA ,grid.250903.d0000 0000 9566 0634The Feinstein Institutes for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY USA ,grid.512756.20000 0004 0370 4759Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY USA
| | - Ashley Moyett
- grid.416477.70000 0001 2168 3646Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY USA
| | - Bernhard T. Baune
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, VIC Australia
| | - Melissa Green
- grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW Australia ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia (NeuRA), Randwick, NSW Australia
| | - Yann Quidé
- grid.1005.40000 0004 4902 0432School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW Australia ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia (NeuRA), Randwick, NSW Australia
| | - Christos Pantelis
- grid.1008.90000 0001 2179 088XMelbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, VIC Australia
| | - Raymond Chan
- grid.9227.e0000000119573309Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Yi Wang
- grid.9227.e0000000119573309Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Ulrich Ettinger
- grid.10388.320000 0001 2240 3300University of Bonn, Bonn, Germany
| | - Martin Debbané
- grid.8591.50000 0001 2322 4988University of Geneva, Geneva, Switzerland
| | - Melodie Derome
- grid.8591.50000 0001 2322 4988University of Geneva, Geneva, Switzerland
| | - Christian Gaser
- grid.275559.90000 0000 8517 6224Jena University Hospital, Jena, Germany
| | - Bianca Besteher
- grid.275559.90000 0000 8517 6224Jena University Hospital, Jena, Germany
| | - Kelly Diederen
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Tom J. Spencer
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK
| | - Paul Fletcher
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Wulf Rössler
- grid.412004.30000 0004 0478 9977Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland ,grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité University Medicine, Berlin, Germany ,grid.11899.380000 0004 1937 0722Institute of Psychiatry, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - Lukasz Smigielski
- grid.412004.30000 0004 0478 9977Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Veena Kumari
- grid.7728.a0000 0001 0724 6933Brunel University London, Uxbridge, UK
| | - Preethi Premkumar
- grid.7728.a0000 0001 0724 6933Brunel University London, Uxbridge, UK
| | - Haeme R. P. Park
- grid.9654.e0000 0004 0372 3343School of Psychology, University of Auckland, Auckland, New Zealand
| | - Kristina Wiebels
- grid.9654.e0000 0004 0372 3343School of Psychology, University of Auckland, Auckland, New Zealand
| | | | - James Gilleen
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK ,grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Paul Allen
- grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Petya Kozhuharova
- grid.35349.380000 0001 0468 7274University of Roehampton, London, UK
| | - Jan-Bernard Marsman
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Irina Lebedeva
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Alexander Tomyshev
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Anna Mukhorina
- grid.466467.10000 0004 0627 319XMental Health Research Center, Moscow, Russian Federation
| | - Stefan Kaiser
- grid.150338.c0000 0001 0721 9812Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - Anne-Kathrin Fett
- grid.13097.3c0000 0001 2322 6764Department of Psychosis Studies, King’s College London, London, UK ,grid.28577.3f0000 0004 1936 8497City, University London, London, UK
| | - Iris Sommer
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sanne Schuite-Koops
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Casey Paquola
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Sara Larivière
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Boris Bernhardt
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Alain Dagher
- grid.14709.3b0000 0004 1936 8649McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, QC Canada
| | - Phillip Grant
- grid.440934.e0000 0004 0593 1824Fresenius University of Applied Sciences, Frankfurt am Main, Germany
| | - Theo G. M. van Erp
- grid.266093.80000 0001 0668 7243Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA USA ,grid.266093.80000 0001 0668 7243Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA USA
| | - Jessica A. Turner
- grid.256304.60000 0004 1936 7400Imaging Genetics and Neuroinformatics Lab, Georgia State University, Atlanta, GA USA
| | - Paul M. Thompson
- grid.42505.360000 0001 2156 6853Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA USA
| | - André Aleman
- grid.4830.f0000 0004 0407 1981Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Gemma Modinos
- Department of Psychosis Studies, King's College London, London, UK. .,MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
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27
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Turner JA, Calhoun VD, Thompson PM, Jahanshad N, Ching CRK, Thomopoulos SI, Verner E, Strauss GP, Ahmed AO, Turner MD, Basodi S, Ford JM, Mathalon DH, Preda A, Belger A, Mueller BA, Lim KO, van Erp TGM. ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability. Neuroinformatics 2022; 20:261-275. [PMID: 34846691 PMCID: PMC9149142 DOI: 10.1007/s12021-021-09559-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2021] [Indexed: 01/07/2023]
Abstract
The FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.
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Affiliation(s)
- Jessica A Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA.
| | - Vince D Calhoun
- Psychology Department, Georgia State University, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Eric Verner
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Gregory P Strauss
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Anthony O Ahmed
- Weill Cornell Medicine, Department of Psychiatry, White Plains, NY, 10605, USA
| | - Matthew D Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA
| | - Sunitha Basodi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Judith M Ford
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Daniel H Mathalon
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, University of California Irvine Medical Center, 101 The City Drive S, Orange, CA, 92868, USA
| | - Aysenil Belger
- Department of Psychiatry and Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, 105 Smith Level Road, Chapel Hill, NC, 27599-8180, USA
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Kelvin O Lim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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28
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Wen K, Zhao Y, Gong Q, Zhu Z, Li Q, Pan N, Fu S, Radua J, Vieta E, Kumar P, Kemp GJ, Biswal BB. Cortical thickness abnormalities in patients with first episode psychosis: a meta-analysis of psychoradiologic studies and replication in an independent sample. PSYCHORADIOLOGY 2021; 1:185-198. [PMID: 35156043 PMCID: PMC8826222 DOI: 10.1093/psyrad/kkab015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/14/2021] [Accepted: 11/17/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Abnormalities of cortical thickness (CTh) in patients with their first episode psychosis (FEP) have been frequently reported, but findings are inconsistent. OBJECTIVE To define the most consistent CTh changes in patients with FEP by meta-analysis of published whole-brain studies. METHODS The meta-analysis used seed-based d mapping (SDM) software to obtain the most prominent regional CTh changes in FEP, and meta-regression analyses to explore the effects of demographics and clinical characteristics. The meta-analysis results were verified in an independent sample of 142 FEP patients and 142 age- and sex-matched healthy controls (HCs), using both a vertex-wise and a region of interest analysis, with multiple comparisons correction. RESULTS The meta-analysis identified lower CTh in the right middle temporal cortex (MTC) extending to superior temporal cortex (STC), insula, and anterior cingulate cortex (ACC) in FEP compared with HCs. No significant correlations were identified between CTh alterations and demographic or clinical variables. These results were replicated in the independent dataset analysis. CONCLUSION This study identifies a robust pattern of cortical abnormalities in FEP and extends understanding of gray matter abnormalities and pathological mechanisms in FEP.
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Affiliation(s)
- Keren Wen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu 610041, Sichuan, China
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Qian Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Shiqin Fu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Mental Health Research Networking Center (CIBERSAM), Barcelona 08036, Catalonia, Spain
- Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Solna 171-77, Stockholm, Sweden
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London WC2R 2LS, UK
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Mental Health Research Networking Center (CIBERSAM), Barcelona 08036, Catalonia, Spain
- Barcelona Bipolar Disorders and Depressive Unit, Hospital Clinic, Institute of Neurosciences, University of Barcelona, Barcelona 08036, Catalonia, Spain
| | - Poornima Kumar
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont 02478, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston 02115, MA, USA
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3GE, UK
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark 07102, NJ, USA
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China
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29
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Itahashi T, Noda Y, Iwata Y, Tarumi R, Tsugawa S, Plitman E, Honda S, Caravaggio F, Kim J, Matsushita K, Gerretsen P, Uchida H, Remington G, Mimura M, Aoki YY, Graff-Guerrero A, Nakajima S. Dimensional distribution of cortical abnormality across antipsychotics treatment-resistant and responsive schizophrenia. NEUROIMAGE-CLINICAL 2021; 32:102852. [PMID: 34638035 PMCID: PMC8527893 DOI: 10.1016/j.nicl.2021.102852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/13/2021] [Accepted: 10/04/2021] [Indexed: 11/30/2022]
Abstract
Different etiology is assumed in treatment-resistant
and responsive schizophrenia. Patients with treatment-resistant schizophrenia were
classified from controls. Patients with non-treatment-resistant schizophrenia
were classified from controls. Two classifications reached area under the curve as
high as 0.69 and 0.85. Area under the curve remained as high as 0.69 when
two classifiers were swapped.
Background One-third of patients with schizophrenia are
treatment-resistant to non-clozapine antipsychotics (TRS), while the rest
respond (NTRS). Examining whether TRS and NTRS represent different
pathophysiologies is an important step toward precision
medicine. Methods Focusing on cortical thickness (CT), we analyzed
international multi-site cross-sectional datasets of magnetic resonance imaging
comprising 110 patients with schizophrenia (NTRS = 46, TRS = 64) and 52 healthy
controls (HCs). We utilized a logistic regression with L1-norm regularization to
find brain regions related to either NTRS or TRS. We conducted nested 10-fold
cross-validation and computed the accuracy and area under the curve (AUC). Then,
we applied the NTRS classifier to patients with TRS, and vice
versa. Results Patients with NTRS and TRS were classified from HCs with
65% and 78% accuracies and with the AUC of 0.69 and 0.85
(p = 0.014 and < 0.001, corrected), respectively.
The left planum temporale (PT) and left anterior insula/inferior frontal gyrus
(IFG) contributed to both NTRS and TRS classifiers. The left supramarginal gyrus
only contributed to NTRS and right superior temporal sulcus and right lateral
orbitofrontal cortex only to the TRS. The NTRS classifiers successfully
distinguished those with TRS from HCs with the AUC of 0.78
(p < 0.001), while the TRS classifiers classified
those with NTRS from HCs with the AUC of 0.69
(p = 0.015). Conclusion Both NTRS and TRS could be distinguished from HCs on the
basis of CT. The CT pathological basis of NTRS and TRS has commonalities, and
TRS presents unique CT features.
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Affiliation(s)
- Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Ryosuke Tarumi
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Eric Plitman
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Fernando Caravaggio
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Julia Kim
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Karin Matsushita
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Philip Gerretsen
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Gary Remington
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yuta Y Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan.
| | - Ariel Graff-Guerrero
- Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada.
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30
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Fan YS, Li H, Guo J, Pang Y, Li L, Hu M, Li M, Wang C, Sheng W, Liu H, Gao Q, Chen X, Zong X, Chen H. Tracking positive and negative symptom improvement in first-episode schizophrenia treated with risperidone using individual-level functional connectivity. Brain Connect 2021; 12:454-464. [PMID: 34210149 DOI: 10.1089/brain.2021.0061] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND To improve the treatment outcomes of patients with schizophrenia, research efforts have focused on identifying brain-based markers of treatment response. Personal characteristics regarding disease-related behaviors likely stem from inter-individual variability in the organization of brain functional systems. This study aimed to track dimension-specific changes in psychotic symptoms following risperidone treatment using individual-level functional connectivity (FC). METHODS A reliable cortical parcellation approach that accounts for individual heterogeneity in cortical functional anatomy was used to localize functional regions in a longitudinal cohort, consisting of 42 drug-naive first-episodes schizophrenia (FES) patients at baseline and after 8 weeks of risperidone treatment. FC was calculated in individually specified brain regions and used to predict the baseline severity and improvement of positive and negative symptoms in FES. RESULTS Distinct sets of individual-specific FC were separately associated with the positive and negative symptom burden at baseline, which could be used to track the corresponding symptom resolution in FES patients following risperidone treatment. Between-network connections of the fronto-parietal network (FPN) contributed the most to predicting the positive symptom domain. A combination of between-network connections of the default mode network, FPN, and within-network connections of the FPN contributed markedly to the prediction model of negative symptom. CONCLUSION This novel study, which accounts for individual brain variation, take a step toward establishing individual-specific theranostic biomarkers in schizophrenia.
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Affiliation(s)
- Yun-Shuang Fan
- University of Electronic Science and Technology of China, 12599, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Chengdu, Sichuan, China;
| | - Haoru Li
- University of Electronic Science and Technology of China, 12599, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Chengdu, Sichuan, China;
| | - Jing Guo
- University of Electronic Science and Technology of China, 12599, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Chengdu, Sichuan, China;
| | - Yajing Pang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China;
| | - Liang Li
- University of Electronic Science and Technology of China, 12599, The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Chengdu, Sichuan, China;
| | - Maolin Hu
- Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, PR China, Changsha, China;
| | - Meiling Li
- University of Electronic Science and Technology of China, 610054, China, School of Life Science & Technology,, Chengdu, Sichuan, China.,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA, Charlestown, United States;
| | - Chong Wang
- University of Electronic Science and Technology of China, 12599, The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, Chengdu, China.,University of Electronic Science and Technology of China, 12599, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Chengdu, China;
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR China, chengdu, China;
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA, Charlestown, MA, United States;
| | - Qing Gao
- University of Electronic Science and Technology of China, 12599, No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, China, 610054;
| | - Xiaogang Chen
- Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, PR China, Changsha, China;
| | - Xiaofen Zong
- Department of Psychiatry, the Second Xiangya Hospital, Central South University, Changsha, PR China, Changsha, China;
| | - Huafu Chen
- University of Electronic Science and Technology of China,, School of Life Science and Technology, University of Electronic Science and Technology of China, Sichuan,Chengdu 610054, China, chengdu, China, 610054;
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31
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Nitta A, Izuo N, Hamatani K, Inagaki R, Kusui Y, Fu K, Asano T, Torii Y, Habuchi C, Sekiguchi H, Iritani S, Muramatsu SI, Ozaki N, Miyamoto Y. Schizophrenia-Like Behavioral Impairments in Mice with Suppressed Expression of Piccolo in the Medial Prefrontal Cortex. J Pers Med 2021; 11:jpm11070607. [PMID: 34206873 PMCID: PMC8304324 DOI: 10.3390/jpm11070607] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/12/2021] [Accepted: 06/18/2021] [Indexed: 11/22/2022] Open
Abstract
Piccolo, a presynaptic cytomatrix protein, plays a role in synaptic vesicle trafficking in the presynaptic active zone. Certain single-nucleotide polymorphisms of the Piccolo-encoding gene PCLO are reported to be associated with mental disorders. However, a few studies have evaluated the relationship between Piccolo dysfunction and psychotic symptoms. Therefore, we investigated the neurophysiological and behavioral phenotypes in mice with Piccolo suppression in the medial prefrontal cortex (mPFC). Downregulation of Piccolo in the mPFC reduced regional synaptic proteins, accompanied with electrophysiological impairments. The Piccolo-suppressed mice showed an enhanced locomotor activity, impaired auditory prepulse inhibition, and cognitive dysfunction. These abnormal behaviors were partially ameliorated by the antipsychotic drug risperidone. Piccolo-suppressed mice received mild social defeat stress showed additional behavioral despair. Furthermore, the responses of these mice to extracellular glutamate and dopamine levels induced by the optical activation of mPFC projection in the dorsal striatum (dSTR) were inhibited. Similarly, the Piccolo-suppressed mice showed decreased depolarization-evoked glutamate and -aminobutyric acid elevations and increased depolarization-evoked dopamine elevation in the dSTR. These suggest that Piccolo regulates neurotransmission at the synaptic terminal of the projection site. Reduced neuronal connectivity in the mPFC-dSTR pathway via suppression of Piccolo in the mPFC may induce behavioral impairments observed in schizophrenia.
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Affiliation(s)
- Atsumi Nitta
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
- Correspondence: ; Tel.: +81-76-415-8822 (ext. 8823); Fax: +81-76-415-8826
| | - Naotaka Izuo
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
| | - Kohei Hamatani
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
| | - Ryo Inagaki
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
| | - Yuka Kusui
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
| | - Kequan Fu
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou 221004, China
| | - Takashi Asano
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
| | - Youta Torii
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 466-8550, Japan; (Y.T.); (C.H.); (H.S.); (S.I.); (N.O.)
| | - Chikako Habuchi
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 466-8550, Japan; (Y.T.); (C.H.); (H.S.); (S.I.); (N.O.)
| | - Hirotaka Sekiguchi
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 466-8550, Japan; (Y.T.); (C.H.); (H.S.); (S.I.); (N.O.)
| | - Shuji Iritani
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 466-8550, Japan; (Y.T.); (C.H.); (H.S.); (S.I.); (N.O.)
| | - Shin-ichi Muramatsu
- Open Innovation Center, Division of Neurological Gene Therapy, Jichi Medical University, Shimotsuke 329-0498, Japan;
- Center for Gene and Cell Therapy, The Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan
| | - Norio Ozaki
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Nagoya 466-8550, Japan; (Y.T.); (C.H.); (H.S.); (S.I.); (N.O.)
| | - Yoshiaki Miyamoto
- Department of Pharmaceutical Therapy and Neuropharmacology, Faculty of Pharmaceutical Sciences, Graduate School of Pharmaceutical Sciences, University of Toyama, Toyama 930-0194, Japan; (N.I.); (K.H.); (R.I.); (Y.K.); (K.F.); (T.A.); (Y.M.)
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Rodriguez-Perez N, Ayesa-Arriola R, Ortiz-García de la Foz V, Setien-Suero E, Tordesillas-Gutierrez D, Crespo-Facorro B. Long term cortical thickness changes after a first episode of non- affective psychosis: The 10 year follow-up of the PAFIP cohort. Prog Neuropsychopharmacol Biol Psychiatry 2021; 108:110180. [PMID: 33212193 DOI: 10.1016/j.pnpbp.2020.110180] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 10/28/2020] [Accepted: 11/12/2020] [Indexed: 12/25/2022]
Abstract
Cortical thickness has been widely studied in individuals with schizophrenia and, in particular, first-episode psychosis. Abnormalities have been described, although there is, to date, a lack of consensus regarding changes across time and correlations with clinical and functional outcomes of the illness. One hundred and twenty-three first-episode psychosis patients and 74 healthy volunteers were subjected to magnetic resonance imaging scans and clinical and functional assessments by different scales at four consecutive visits during a 10 year follow-up period. Linear mixed effects models were applied to our data to compute cortical thickness changes over time in (1) schizophrenia patients versus healthy controls and (2) in patients with good versus poor functional outcome. The associations between cortical thickness percentage changes and clinical and functional status at 10 years were also assessed. The patients presented a thinner cortex than the controls at baseline (b's = -0.06; q ≤ 0.00023) with non-significant coefficients for the interaction term (follow-up time x group) (b's = -0.001; q ≥ 0.681). Poor functioning patients presented statistically significant coefficients for the interaction term (follow-up time x functionality) (left: b = -0.005, q = 0.019; right: b = -0.005, q = 0.022). In contrast, no correlations were found between cortical thickness measurements and clinical variables at 10 years. Overall, there were widespread thickness anomalies in first-episode psychosis patients across cortical regions that remained stable across time. Progressive thickness changes were related to patient functional outcomes, with progressive and steeper cortical thinning in patients with worse functional outcomes and a stabilization in those with better outcomes.
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Affiliation(s)
- Noelia Rodriguez-Perez
- Hospital Universitario Virgen del Rocío, Department of Psychiatry, Instituto de Investigación Sanitaria de Sevilla, IBiS, Sevilla, Spain; CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain.
| | - Rosa Ayesa-Arriola
- University Hospital Marqués de Valdecilla, IDIVAL, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Victor Ortiz-García de la Foz
- University Hospital Marqués de Valdecilla, IDIVAL, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Esther Setien-Suero
- University Hospital Marqués de Valdecilla, IDIVAL, Department of Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Diana Tordesillas-Gutierrez
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain; Neuroimaging Unit, Technological Facilities, IDIVAL, Santander, Spain
| | - Benedicto Crespo-Facorro
- Hospital Universitario Virgen del Rocío, Department of Psychiatry, Instituto de Investigación Sanitaria de Sevilla, IBiS, Sevilla, Spain; CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Madrid, Spain; University of Sevilla, Sevilla, Spain.
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Fortea A, Batalla A, Radua J, van Eijndhoven P, Baeza I, Albajes-Eizagirre A, Fusar-Poli P, Castro-Fornieles J, De la Serna E, Luna LP, Carvalho AF, Vieta E, Sugranyes G. Cortical gray matter reduction precedes transition to psychosis in individuals at clinical high-risk for psychosis: A voxel-based meta-analysis. Schizophr Res 2021; 232:98-106. [PMID: 34029948 DOI: 10.1016/j.schres.2021.05.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/27/2021] [Accepted: 05/02/2021] [Indexed: 01/10/2023]
Abstract
Gray matter and cortical thickness reductions have been documented in individuals at clinical high-risk for psychosis and may be more pronounced in those who transition to psychosis. However, these findings rely on small samples and are inconsistent across studies. In this review and meta-analysis we aimed to investigate neuroanatomical correlates of clinical high-risk for psychosis and potential predictors of transition, using a novel meta-analytic method (Seed-based d Mapping with Permutation of Subject Images) and cortical mask, combining data from surface-based and voxel-based morphometry studies. Individuals at clinical high-risk for psychosis who later transitioned to psychosis were compared to those who did not and to controls, and included three statistical maps. Overall, individuals at clinical high-risk for psychosis did not differ from controls, however, within the clinical high-risk for psychosis group, transition to psychosis was associated with less cortical gray matter in the right temporal lobe (Hedges' g = -0.377), anterior cingulate and paracingulate (Hedges' g = -0.391). These findings have the potential to help refine prognostic and etiopathological research in early psychosis.
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Affiliation(s)
- Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neuroscience, Hospital Clínic, Villarroel 170, 08036 Barcelona, Spain; Fundació Clínic per a la Recerca Biomèdica (FCRB), Esther Koplowitz Centre, Rosselló 153, 08036 Barcelona, Spain; Medicina i Recerca Traslacional, University of Barcelona, Casanova 143, 08036 Barcelona, Spain.
| | - Albert Batalla
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain; Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Center for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| | - Philip van Eijndhoven
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands; Donders Institute for Brain Cognition and Behavior, Center for Cognitive Neuroimaging, Nijmegen, the Netherlands.
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neuroscience, Hospital Clínic, Villarroel 170, 08036 Barcelona, Spain; Medicina i Recerca Traslacional, University of Barcelona, Casanova 143, 08036 Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.
| | - Anton Albajes-Eizagirre
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), 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, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
| | - Josefina Castro-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neuroscience, Hospital Clínic, Villarroel 170, 08036 Barcelona, Spain; Medicina i Recerca Traslacional, University of Barcelona, Casanova 143, 08036 Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.
| | - Elena De la Serna
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.
| | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, Division of Neuroradiology, 600 N Wolfe Street Phipps B100F, 21287 Baltimore, MD, USA
| | - André F Carvalho
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Center of Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain; Barcelona Bipolar Disorders and Depressive Unit, Hospital Clinic, Institute of Neurosciences, University of Barcelona, Villarroel 170, 08036 Barcelona, Spain.
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institute of Neuroscience, Hospital Clínic, Villarroel 170, 08036 Barcelona, Spain; Fundació Clínic per a la Recerca Biomèdica (FCRB), Esther Koplowitz Centre, Rosselló 153, 08036 Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Rosselló 149, 08036 Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain.
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Nakamura R, Asami T, Yoshimi A, Kato D, Fujita E, Takaishi M, Abe K, Hattori S, Suda A, Shiozaki K, Kase A, Hirayasu Y, Hishimoto A. Illness management and recovery program induced neuroprotective effects on language network in schizophrenia. Schizophr Res 2021; 230:101-103. [PMID: 32950322 DOI: 10.1016/j.schres.2020.08.028] [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: 07/31/2020] [Revised: 08/28/2020] [Accepted: 08/29/2020] [Indexed: 11/24/2022]
Affiliation(s)
- Ryota Nakamura
- Psychiatric Center, Yokohama City University Medical Center, 4-57, Urafune-cho, Minami-ku, Yokohama 232-0024, Japan.
| | - Takeshi Asami
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan.
| | - Asuka Yoshimi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Daiji Kato
- Totsuka Nishiguchi Rindou Clinic, Totsuka-cho, Totsuka-ku, Yokohama, Kanagawa 244-0003, Japan
| | - Emi Fujita
- Yokohama City University Hospital, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Masao Takaishi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Kie Abe
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Saki Hattori
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Akira Suda
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
| | - Kazumasa Shiozaki
- Yokohama Comprehensive Care Continuum, 1735 Karasuyama-cho, Kouhoku-ku, Yokohama, Kanagawa 222-0035, Japan
| | - Akihiko Kase
- Yokohama Maioka Hospital, 3482 Maioka-cho, Totsuka-ku, Yokohama, Kanagawa 244-0813, Japan
| | - Yoshio Hirayasu
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan; Hirayasu Hospital, 346 Kyouzuka, Urasoe, Okinawa 901-2553, Japan
| | - Akitoyo Hishimoto
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan
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Alkan E, Davies G, Evans SL. Cognitive impairment in schizophrenia: relationships with cortical thickness in fronto-temporal regions, and dissociability from symptom severity. NPJ SCHIZOPHRENIA 2021; 7:20. [PMID: 33737508 PMCID: PMC7973472 DOI: 10.1038/s41537-021-00149-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 02/08/2021] [Indexed: 12/21/2022]
Abstract
Cognitive impairments are a core and persistent characteristic of schizophrenia with implications for daily functioning. These show only limited response to antipsychotic treatment and their neural basis is not well characterised. Previous studies point to relationships between cortical thickness and cognitive performance in fronto-temporal brain regions in schizophrenia patients (SZH). There is also evidence that these relationships might be independent of symptom severity, suggesting dissociable disease processes. We set out to explore these possibilities in a sample of 70 SZH and 72 age and gender-matched healthy controls (provided by the Center of Biomedical Research Excellence (COBRE)). Cortical thickness within fronto-temporal regions implicated by previous work was considered in relation to performance across various cognitive domains (from the MATRICS Cognitive Battery). Compared to controls, SZH had thinner cortices across most fronto-temporal regions and significantly lower performance on all cognitive domains. Robust relationships with cortical thickness were found: visual learning and attention performance correlated with bilateral superior and middle frontal thickness in SZH only. Correlations between attention performance and right transverse temporal thickness were also specific to SZH. Findings point to the importance of these regions for cognitive performance in SZH, possibly reflecting compensatory processes and/or aberrant connectivity. No links to symptom severity were observed in these regions, suggesting these relationships are dissociable from underlying psychotic symptomology. Findings enhance understanding of the brain structural underpinnings and possible aetiology of cognitive impairment in SZH.
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Affiliation(s)
- Erkan Alkan
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, UK
| | - Geoff Davies
- Brighton & Sussex Medical School/Sussex Partnership NHS Foundation Trust, Sussex, UK
| | - Simon L Evans
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, UK.
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Tong J, Zhou Y, Huang J, Zhang P, Fan F, Chen S, Tian B, Cui Y, Tian L, Tan S, Wang Z, Feng W, Yang F, Hare S, Goldwaser EL, Bruce HA, Kvarta M, Chen S, Kochunov P, Tan Y, Hong LE. N-methyl-D-aspartate Receptor Antibody and White Matter Deficits in Schizophrenia Treatment-Resistance. Schizophr Bull 2021; 47:1463-1472. [PMID: 33515249 PMCID: PMC8379535 DOI: 10.1093/schbul/sbab003] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Insufficient or lack of response to antipsychotic medications in some patients with schizophrenia is a major challenge in psychiatry, but the underlying mechanisms remain unclear. Two seemingly unrelated observations, cerebral white matter and N-methyl-D-aspartate receptor (NMDAR) hypofunction, have been linked to treatment-resistant schizophrenia (TRS). As NMDARs are critical to axonal myelination and signal transduction, we hypothesized that NMDAR antibody (Ab), when present in schizophrenia, may impair NMDAR functions and white matter microstructures, contributing to TRS. In this study, 50 patients with TRS, 45 patients with nontreatment-resistant schizophrenia (NTRS), 53 patients with schizophrenia at treatment initiation schizophrenia (TIS), and 90 healthy controls were enrolled. Serum NMDAR Ab levels and white matter diffusion tensor imaging fractional anisotropy (FA) were assessed. The white matter specificity effects by NMDAR Ab were assessed by comparing with effects on cortical and subcortical gray matter. Serum NMDAR Ab levels of the TRS were significantly higher than those of the NTRS (P = .035). In patients with TRS, higher NMDAR Ab levels were significantly associated with reduced whole-brain average FA (r = -.37; P = .026), with the strongest effect at the genu of corpus callosum (r = -.50; P = .0021, significant after correction for multiple comparisons). Conversely, there was no significant correlation between whole-brain or regional cortical thickness or any subcortical gray matter structural volume and NMDAR Ab levels in TRS. Our finding highlights a potential NMDAR mechanism on white matter microstructure impairment in schizophrenia that may contribute to their treatment resistance to antipsychotic medications.
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Affiliation(s)
- Jinghui Tong
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Yanfang Zhou
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Junchao Huang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Ping Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Yimin Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, P. R. China
| | - Li Tian
- Institute of Biomedicine and Translational Medicine, Department of Physiology, Faculty of Medicine, University of Tartu, Tartu, Estonia
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Wei Feng
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Eric L Goldwaser
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Heather A Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Mark Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, P. R. China,To whom correspondence should be addressed; tel: +86-(10)-83024319, fax: +86-(10)-62710156, e-mail:
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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Bagautdinova J, Zöller D, Schaer M, Padula MC, Mancini V, Schneider M, Eliez S. Altered cortical thickness development in 22q11.2 deletion syndrome and association with psychotic symptoms. Mol Psychiatry 2021; 26:7671-7678. [PMID: 34253864 PMCID: PMC8873018 DOI: 10.1038/s41380-021-01209-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 06/15/2021] [Accepted: 06/23/2021] [Indexed: 02/06/2023]
Abstract
Schizophrenia has been extensively associated with reduced cortical thickness (CT), and its neurodevelopmental origin is increasingly acknowledged. However, the exact timing and extent of alterations occurring in preclinical phases remain unclear. With a high prevalence of psychosis, 22q11.2 deletion syndrome (22q11DS) is a neurogenetic disorder that represents a unique opportunity to examine brain maturation in high-risk individuals. In this study, we quantified trajectories of CT maturation in 22q11DS and examined the association of CT development with the emergence of psychotic symptoms. Longitudinal structural MRI data with 1-6 time points were collected from 324 participants aged 5-35 years (N = 148 22q11DS, N = 176 controls), resulting in a total of 636 scans (N = 334 22q11DS, N = 302 controls). Mixed model regression analyses were used to compare CT trajectories between participants with 22q11DS and controls. Further, CT trajectories were compared between participants with 22q11DS who developed (N = 61, 146 scans), or remained exempt of (N = 47; 98 scans) positive psychotic symptoms during development. Compared to controls, participants with 22q11DS showed widespread increased CT, focal reductions in the posterior cingulate gyrus and superior temporal gyrus (STG), and accelerated cortical thinning during adolescence, mainly in frontotemporal regions. Within 22q11DS, individuals who developed psychotic symptoms showed exacerbated cortical thinning in the right STG. Together, these findings suggest that genetic predisposition for psychosis is associated with increased CT starting from childhood and altered maturational trajectories of CT during adolescence, affecting predominantly frontotemporal regions. In addition, accelerated thinning in the STG may represent an early biomarker associated with the emergence of psychotic symptoms.
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Affiliation(s)
- Joëlle Bagautdinova
- Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Daniela Zöller
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland ,grid.5333.60000000121839049Medical Image Processing Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland ,grid.8591.50000 0001 2322 4988Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Marie Schaer
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Maria Carmela Padula
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Mancini
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Maude Schneider
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland ,grid.8591.50000 0001 2322 4988Clinical Psychology Unit for Intellectual and Developmental Disabilities, Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Stephan Eliez
- grid.8591.50000 0001 2322 4988Developmental Imaging and Psychopathology Laboratory, Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
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38
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Feng R, Womer FY, Edmiston EK, Chen Y, Wang Y, Chang M, Yin Z, Wei Y, Duan J, Ren S, Li C, Liu Z, Jiang X, Wei S, Li S, Zhang X, Zuo XN, Tang Y, Wang F. Antipsychotic Effects on Cortical Morphology in Schizophrenia and Bipolar Disorders. Front Neurosci 2020; 14:579139. [PMID: 33362453 PMCID: PMC7758211 DOI: 10.3389/fnins.2020.579139] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 11/10/2020] [Indexed: 11/30/2022] Open
Abstract
Background: Previous studies of atypical antipsychotic effects on cortical structures in schizophrenia (SZ) and bipolar disorder (BD) have findings that vary between the short and long term. In particular, there has not been a study exploring the effects of atypical antipsychotics on age-related cortical structural changes in SZ and BD. This study aimed to determine whether mid- to long-term atypical antipsychotic treatment (mean duration = 20 months) is associated with cortical structural changes and whether age-related cortical structural changes are affected by atypical antipsychotics. Methods: Structural magnetic resonance imaging images were obtained from 445 participants consisting of 88 medicated patients (67 with SZ, 21 with BD), 84 unmedicated patients (50 with SZ, 34 with BD), and 273 healthy controls (HC). Surface-based analyses were employed to detect differences in thickness and area among the three groups. We examined the age-related effects of atypical antipsychotics after excluding the potential effects of illness duration. Results: Significant differences in cortical thickness were observed in the frontal, temporal, parietal, and insular areas and the isthmus of the cingulate gyrus. The medicated group showed greater cortical thinning in these regions than the unmediated group and HC; furthermore, there were age-related differences in the effects of atypical antipsychotics, and these effects did not relate to illness duration. Moreover, cortical thinning was significantly correlated with lower symptom scores and Wisconsin Card Sorting Test (WCST) deficits in patients. After false discovery rate correction, cortical thinning in the right middle temporal gyrus in patients was significantly positively correlated with lower HAMD scores. The unmedicated group showed only greater frontotemporal thickness than the HC group. Conclusion: Mid- to long-term atypical antipsychotic use may adversely affect cortical thickness over the course of treatment and ageing and may also result in worsening cognitive function.
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Affiliation(s)
- Ruiqi Feng
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - E Kale Edmiston
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yifan Chen
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yinshan Wang
- CAS Key Laboratory of Behavioral Science and Research Center for Lifespan Development of Mind and Brain (CLIMB), Institute of Psychology, Beijing, China
| | - Miao Chang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhiyang Yin
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jia Duan
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sihua Ren
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Chao Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zhuang Liu
- School of Public Health, China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shengnan Wei
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Songbai Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Xi-Nian Zuo
- Key Laboratory of Brain and Education Sciences, School of Education Sciences, Nanning Normal University, Nanning, China
| | - Yanqing Tang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
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39
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Kirschner M, Schmidt A, Hodzic-Santor B, Burrer A, Manoliu A, Zeighami Y, Yau Y, Abbasi N, Maatz A, Habermeyer B, Abivardi A, Avram M, Brandl F, Sorg C, Homan P, Riecher-Rössler A, Borgwardt S, Seifritz E, Dagher A, Kaiser S. Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum. Schizophr Bull 2020; 47:849-863. [PMID: 33257954 PMCID: PMC8084448 DOI: 10.1093/schbul/sbaa169] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Negative symptoms such as anhedonia and apathy are among the most debilitating manifestations of schizophrenia (SZ). Imaging studies have linked these symptoms to morphometric abnormalities in 2 brain regions implicated in reward and motivation: the orbitofrontal cortex (OFC) and striatum. Higher negative symptoms are generally associated with reduced OFC thickness, while higher apathy specifically maps to reduced striatal volume. However, it remains unclear whether these tissue losses are a consequence of chronic illness and its treatment or an underlying phenotypic trait. Here, we use multicentre magnetic resonance imaging data to investigate orbitofrontal-striatal abnormalities across the SZ spectrum from healthy populations with high schizotypy to unmedicated and medicated first-episode psychosis (FEP), and patients with chronic SZ. Putamen, caudate, accumbens volume, and OFC thickness were estimated from T1-weighted images acquired in all 3 diagnostic groups and controls from 4 sites (n = 337). Results were first established in 1 discovery dataset and replicated in 3 independent samples. There was a negative correlation between apathy and putamen/accumbens volume only in healthy individuals with schizotypy; however, medicated patients exhibited larger putamen volume, which appears to be a consequence of antipsychotic medications. The negative association between reduced OFC thickness and total negative symptoms also appeared to vary along the SZ spectrum, being significant only in FEP patients. In schizotypy, there was increased OFC thickness relative to controls. Our findings suggest that negative symptoms are associated with a temporal continuum of orbitofrontal-striatal abnormalities that may predate the occurrence of SZ. Thicker OFC in schizotypy may represent either compensatory or pathological mechanisms prior to the disease onset.
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Affiliation(s)
- Matthias Kirschner
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada,Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,To whom correspondence should be addressed; 3801 Rue University, Montréal QC, H3A 2B4 Canada; tel: +1 514-398-1726, fax: +1 514–398–8948, e-mail:
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | | | - Achim Burrer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Andrei Manoliu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,Wellcome Centre for Human Neuroimaging, University College London, London, UK,Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London, UK
| | - Yashar Zeighami
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Yvonne Yau
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Nooshin Abbasi
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Anke Maatz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | | | - Aslan Abivardi
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Mihai Avram
- Department of Neuroradiology and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany,Department of Psychiatry, Psychosomatics and Psychotherapy, Schleswig Holstein University Hospital, University Lübeck, Lübeck Germany
| | - Felix Brandl
- Department of Psychiatry and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Sorg
- Department of Neuroradiology and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany,Department of Psychiatry and TUM-NIC Neuroimaging Center, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, New York, NY,Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Northwell/Hofstra, Hempstead, NY
| | | | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Erich Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Stefan Kaiser
- Department of Psychiatry, Division of Adult Psychiatry, Geneva University Hospitals, Geneva, Switzerland
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40
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Yamamoto M, Bagarinao E, Kushima I, Takahashi T, Sasabayashi D, Inada T, Suzuki M, Iidaka T, Ozaki N. Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites. PLoS One 2020; 15:e0239615. [PMID: 33232334 PMCID: PMC7685428 DOI: 10.1371/journal.pone.0239615] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 09/10/2020] [Indexed: 12/17/2022] Open
Abstract
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy controls by detecting subtle and spatially distributed patterns of structural alterations. We aimed to use a support vector machine to distinguish patients with schizophrenia from control participants on the basis of structural magnetic resonance imaging data and delineate the patterns of structural alterations that significantly contributed to the classification performance. We used independent datasets from different sites with different magnetic resonance imaging scanners, protocols and clinical characteristics of the patient group to achieve a more accurate estimate of the classification performance of support vector machines. We developed a support vector machine classifier using the dataset from one site (101 participants) and evaluated the performance of the trained support vector machine using a dataset from the other site (97 participants) and vice versa. We assessed the performance of the trained support vector machines in each support vector machine classifier. Both support vector machine classifiers attained a classification accuracy of >70% with two independent datasets indicating a consistently high performance of support vector machines even when used to classify data from different sites, scanners and different acquisition protocols. The regions contributing to the classification accuracy included the bilateral medial frontal cortex, superior temporal cortex, insula, occipital cortex, cerebellum, and thalamus, which have been reported to be related to the pathogenesis of schizophrenia. These results indicated that the support vector machine could detect subtle structural brain alterations and might aid our understanding of the pathophysiology of these changes in schizophrenia, which could be one of the diagnostic findings of schizophrenia.
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Affiliation(s)
- Maeri Yamamoto
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
| | | | - Itaru Kushima
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
- Medical Genomics Center, Nagoya University Hospital, Nagoya, Aichi, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Toshiya Inada
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Toyama, Japan
| | - Tetsuya Iidaka
- Brain & Mind Research Center, Nagoya University, Nagoya, Aichi, Japan
- * E-mail:
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University, Graduate School of Medicine, Nagoya, Aichi, Japan
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41
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Individual-specific functional connectivity markers track dimensional and categorical features of psychotic illness. Mol Psychiatry 2020; 25:2119-2129. [PMID: 30443042 PMCID: PMC6520219 DOI: 10.1038/s41380-018-0276-1] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 08/09/2018] [Accepted: 08/13/2018] [Indexed: 12/23/2022]
Abstract
Neuroimaging studies of psychotic disorders have demonstrated abnormalities in structural and functional connectivity involving widespread brain networks. However, these group-level observations have failed to yield any biomarkers that can provide confirmatory evidence of a patient's current symptoms, predict future symptoms, or predict a treatment response. Lack of precision in both neuroanatomical and clinical boundaries have likely contributed to the inability of even well-powered studies to resolve these key relationships. Here, we employed a novel approach to defining individual-specific functional connectivity in 158 patients diagnosed with schizophrenia (n = 49), schizoaffective disorder (n = 37), or bipolar disorder with psychosis (n = 72), and identified neuroimaging features that track psychotic symptoms in a dimension- or disorder-specific fashion. Using individually specified functional connectivity, we were able to estimate positive, negative, and manic symptoms that showed correlations ranging from r = 0.35 to r = 0.51 with the observed symptom scores. Comparing optimized estimation models among schizophrenia spectrum patients, positive and negative symptoms were associated with largely non-overlapping sets of cortical connections. Comparing between schizophrenia spectrum and bipolar disorder patients, the models for positive symptoms were largely non-overlapping between the two disorder classes. Finally, models derived using conventional region definition strategies performed at chance levels for most symptom domains. Individual-specific functional connectivity analyses revealed important new distinctions among cortical circuits responsible for the positive and negative symptoms, as well as key new information about how circuits underlying symptom expressions may vary depending on the underlying etiology and illness syndrome from which they manifest.
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42
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Kirschner M, Shafiei G, Markello RD, Makowski C, Talpalaru A, Hodzic-Santor B, Devenyi GA, Paquola C, Bernhardt BC, Lepage M, Chakravarty MM, Dagher A, Mišić B. Latent Clinical-Anatomical Dimensions of Schizophrenia. Schizophr Bull 2020; 46:1426-1438. [PMID: 32744604 PMCID: PMC8496914 DOI: 10.1093/schbul/sbaa097] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Widespread structural brain abnormalities have been consistently reported in schizophrenia, but their relation to the heterogeneous clinical manifestations remains unknown. In particular, it is unclear whether anatomical abnormalities in discrete regions give rise to discrete symptoms or whether distributed abnormalities give rise to the broad clinical profile associated with schizophrenia. Here, we apply a multivariate data-driven approach to investigate covariance patterns between multiple-symptom domains and distributed brain abnormalities in schizophrenia. Structural magnetic resonance imaging and clinical data were derived from one discovery sample (133 patients and 113 controls) and one independent validation sample (108 patients and 69 controls). Disease-related voxel-wise brain abnormalities were estimated using deformation-based morphometry. Partial least-squares analysis was used to comprehensively map clinical, neuropsychological, and demographic data onto distributed deformation in a single multivariate model. The analysis identified 3 latent clinical-anatomical dimensions that collectively accounted for 55% of the covariance between clinical data and brain deformation. The first latent clinical-anatomical dimension was replicated in an independent sample, encompassing cognitive impairments, negative symptom severity, and brain abnormalities within the default mode and visual networks. This cognitive-negative dimension was associated with low socioeconomic status and was represented across multiple races. Altogether, we identified a continuous cognitive-negative dimension of schizophrenia, centered on 2 intrinsic networks. By simultaneously taking into account both clinical manifestations and neuroanatomical abnormalities, the present results open new avenues for multi-omic stratification and biotyping of individuals with schizophrenia.
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Affiliation(s)
- Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland,McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Golia Shafiei
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Carolina Makowski
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Alexandra Talpalaru
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada
| | - Benazir Hodzic-Santor
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Gabriel A Devenyi
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Martin Lepage
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, Canada,Department of Biological and Biomedical Engineering, McGill University, Montréal, Canada,Department of Psychiatry, McGill University, Montréal, Canada
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada
| | - Bratislav Mišić
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montreal, Canada,To whom correspondence should be addressed; tel: 514-398-1857, fax: 514-398-1857, e-mail:
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43
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Koshiyama D, Miura K, Nemoto K, Okada N, Matsumoto J, Fukunaga M, Hashimoto R. Neuroimaging studies within Cognitive Genetics Collaborative Research Organization aiming to replicate and extend works of ENIGMA. Hum Brain Mapp 2020; 43:182-193. [PMID: 32501580 PMCID: PMC8675417 DOI: 10.1002/hbm.25040] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Revised: 04/10/2020] [Accepted: 05/10/2020] [Indexed: 12/13/2022] Open
Abstract
Reproducibility is one of the most important issues for generalizing the results of clinical research; however, low reproducibility in neuroimaging studies is well known. To overcome this problem, the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium, an international neuroimaging consortium, established standard protocols for imaging analysis and employs either meta‐ and mega‐analyses of psychiatric disorders with large sample sizes. The Cognitive Genetics Collaborative Research Organization (COCORO) in Japan promotes neurobiological studies in psychiatry and has successfully replicated and extended works of ENIGMA especially for neuroimaging studies. For example, (a) the ENIGMA consortium showed subcortical regional volume alterations in patients with schizophrenia (n = 2,028) compared to controls (n = 2,540) across 15 cohorts using meta‐analysis. COCORO replicated the volumetric changes in patients with schizophrenia (n = 884) compared to controls (n = 1,680) using the ENIGMA imaging analysis protocol and mega‐analysis. Furthermore, a schizophrenia‐specific leftward asymmetry for the pallidum volume was demonstrated; and (b) the ENIGMA consortium identified white matter microstructural alterations in patients with schizophrenia (n = 1,963) compared to controls (n = 2,359) across 29 cohorts. Using the ENIGMA protocol, a study from COCORO showed similar results in patients with schizophrenia (n = 696) compared to controls (n = 1,506) from 12 sites using mega‐analysis. Moreover, the COCORO study found that schizophrenia, bipolar disorder (n = 211) and autism spectrum disorder (n = 126), but not major depressive disorder (n = 398), share similar white matter microstructural alterations, compared to controls. Further replication and harmonization of the ENIGMA consortium and COCORO will contribute to the generalization of their research findings.
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Affiliation(s)
- Daisuke Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
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44
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Thompson PM, Jahanshad N, Ching CRK, Salminen LE, Thomopoulos SI, Bright J, Baune BT, Bertolín S, Bralten J, Bruin WB, Bülow R, Chen J, Chye Y, Dannlowski U, de Kovel CGF, Donohoe G, Eyler LT, Faraone SV, Favre P, Filippi CA, Frodl T, Garijo D, Gil Y, Grabe HJ, Grasby KL, Hajek T, Han LKM, Hatton SN, Hilbert K, Ho TC, Holleran L, Homuth G, Hosten N, Houenou J, Ivanov I, Jia T, Kelly S, Klein M, Kwon JS, Laansma MA, Leerssen J, Lueken U, Nunes A, Neill JO, Opel N, Piras F, Piras F, Postema MC, Pozzi E, Shatokhina N, Soriano-Mas C, Spalletta G, Sun D, Teumer A, Tilot AK, Tozzi L, van der Merwe C, Van Someren EJW, van Wingen GA, Völzke H, Walton E, Wang L, Winkler AM, Wittfeld K, Wright MJ, Yun JY, Zhang G, Zhang-James Y, Adhikari BM, Agartz I, Aghajani M, Aleman A, Althoff RR, Altmann A, Andreassen OA, Baron DA, Bartnik-Olson BL, Marie Bas-Hoogendam J, Baskin-Sommers AR, Bearden CE, Berner LA, Boedhoe PSW, Brouwer RM, Buitelaar JK, Caeyenberghs K, Cecil CAM, Cohen RA, Cole JH, Conrod PJ, De Brito SA, de Zwarte SMC, Dennis EL, Desrivieres S, Dima D, Ehrlich S, Esopenko C, Fairchild G, Fisher SE, Fouche JP, Francks C, Frangou S, Franke B, Garavan HP, Glahn DC, Groenewold NA, Gurholt TP, Gutman BA, Hahn T, Harding IH, Hernaus D, Hibar DP, Hillary FG, Hoogman M, Hulshoff Pol HE, Jalbrzikowski M, Karkashadze GA, Klapwijk ET, Knickmeyer RC, Kochunov P, Koerte IK, Kong XZ, Liew SL, Lin AP, Logue MW, Luders E, Macciardi F, Mackey S, Mayer AR, McDonald CR, McMahon AB, Medland SE, Modinos G, Morey RA, Mueller SC, Mukherjee P, Namazova-Baranova L, Nir TM, Olsen A, Paschou P, Pine DS, Pizzagalli F, Rentería ME, Rohrer JD, Sämann PG, Schmaal L, Schumann G, Shiroishi MS, Sisodiya SM, Smit DJA, Sønderby IE, Stein DJ, Stein JL, Tahmasian M, Tate DF, Turner JA, van den Heuvel OA, van der Wee NJA, van der Werf YD, van Erp TGM, van Haren NEM, van Rooij D, van Velzen LS, Veer IM, Veltman DJ, Villalon-Reina JE, Walter H, Whelan CD, Wilde EA, Zarei M, Zelman V. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl Psychiatry 2020; 10:100. [PMID: 32198361 PMCID: PMC7083923 DOI: 10.1038/s41398-020-0705-1] [Citation(s) in RCA: 280] [Impact Index Per Article: 70.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 12/11/2019] [Accepted: 12/20/2019] [Indexed: 02/07/2023] Open
Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Sara Bertolín
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Willem B Bruin
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Jian Chen
- Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Carolien G F de Kovel
- Biometris Wageningen University and Research, Wageningen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Gary Donohoe
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Desert-Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Pauline Favre
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
| | - Courtney A Filippi
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Daniel Garijo
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
| | - Yolanda Gil
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Katrina L Grasby
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- National Institute of Mental Health, Klecany, Czech Republic
| | - Laura K M Han
- Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Sean N Hatton
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tiffany C Ho
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Psychiatry & Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Laurena Holleran
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Norbert Hosten
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Josselin Houenou
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
- APHP, Mondor University Hospitals, School of Medicine, DMU Impact, Psychiatry Department, Créteil, France
| | - Iliyan Ivanov
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
| | - Marieke Klein
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Joseph O' Neill
- Child & Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Merel C Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Elena Pozzi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
| | - Natalia Shatokhina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
- CIBERSAM-G17, Madrid, Spain
- Department of Psychobiology and Methodology in Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Daqiang Sun
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Amanda K Tilot
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Leonardo Tozzi
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Celia van der Merwe
- Stanley Center for Psychiatric Research, The Broad Institute, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Eus J W Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Psychiatry and Integrative Neurophysiology, VU University, Amsterdam UMC, Amsterdam, The Netherlands
| | - Guido A van Wingen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Lei Wang
- Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Anderson M Winkler
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Guohao Zhang
- Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, MD, USA
| | - Yanli Zhang-James
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Bhim M Adhikari
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Research & Innovation, GGZ InGeest, Amsterdam, The Netherlands
| | - André Aleman
- University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Robert R Althoff
- Psychiatry, Pediatrics, and Psychological Sciences, University of Vermont, Burlington, VT, USA
| | - Andre Altmann
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David A Baron
- Provost and Senior Vice President, Western University of Health Sciences, Pomona, CA, USA
| | | | - Janna Marie Bas-Hoogendam
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | | | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Laura A Berner
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Premika S W Boedhoe
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC, Australia
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ronald A Cohen
- Center for Cognitive Aging and Memory, University of Florida, Gainesville, FL, USA
- Clinical and Health Psychology, Gainesville, FL, USA
| | - James H Cole
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Patricia J Conrod
- Universite de Montreal, Centre de Recherche CHU Ste-Justine, Montreal, QC, Canada
| | - Stephane A De Brito
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Sonja M C de Zwarte
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Emily L Dennis
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvane Desrivieres
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Danai Dima
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Carrie Esopenko
- Department of Rehabilitation and Movement Sciences, School of Health Professions, Rutgers Biomedical Health Sciences, Newark, NJ, USA
| | | | - Simon E Fisher
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Jean-Paul Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SU/UCT MRC Unit on Risk & Resilience in Mental Disorders, University of Stellenbosch, Stellenbosch, South Africa
| | - Clyde Francks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- University of British Columbia, Vancouver, Canada
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hugh P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, CT, USA
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Boris A Gutman
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
- Institute for Information Transmission Problems, Kharkevich Institute, Moscow, Russian Federation
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Ian H Harding
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Dennis Hernaus
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Frank G Hillary
- Department of Psychology, Penn State University, University Park, PA, USA
- Social Life and Engineering Sciences Imaging Center, University Park, PA, USA
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - George A Karkashadze
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
| | - Eduard T Klapwijk
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Rebecca C Knickmeyer
- Department of Pediatrics, Michigan State University, East Lansing, MI, USA
- Institute for Quantitative Health Science and Engineering, East Lansing, MI, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- CBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Xiang-Zhen Kong
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sook-Lei Liew
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Chan Division of Occupational Science and Occupational Therapy, Los Angeles, CA, USA
| | - Alexander P Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mark W Logue
- National Center for PTSD at Boston VA Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland, New Zealand
- Laboratory of Neuro Imaging, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | | | - Carrie R McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Psychiatry, San Diego, CA, USA
| | - Agnes B McMahon
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- The Kavli Foundation, Los Angeles, CA, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Gemma Modinos
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rajendra A Morey
- Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA
- Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Sven C Mueller
- Experimental Clinical & Health Psychology, Ghent University, Ghent, Belgium
- Department of Personality, Psychological Assessment and Treatment, University of Deusto, Bilbao, Spain
| | | | - Leyla Namazova-Baranova
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
- Department of Pediatrics, Russian National Research Medical University MoH RF, Moscow, Russian Federation
| | - Talia M Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Daniel S Pine
- National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | | | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry and Psychotherapy, Charite, Humboldt University, Berlin, Germany
| | - Mark S Shiroishi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Radiology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, University College London, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Ida E Sønderby
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Jason L Stein
- Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - David F Tate
- Department of Neurology, TBI and Concussion Center, Salt Lake City, UT, USA
- Missouri Institute of Mental Health, Berkeley, MO, USA
| | - Jessica A Turner
- Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Ysbrand D van der Werf
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA
| | - Neeltje E M van Haren
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Laura S van Velzen
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Ilya M Veer
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Julio E Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Christopher D Whelan
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland
- Research and Early Development, Biogen Inc, Cambridge, MA, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- VA Salt Lake City Healthcare System, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - Vladimir Zelman
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
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Zhang W, Lei D, Keedy SK, Ivleva EI, Eum S, Yao L, Tamminga CA, Clementz BA, Keshavan MS, Pearlson GD, Gershon ES, Bishop JR, Gong Q, Lui S, Sweeney JA. Brain gray matter network organization in psychotic disorders. Neuropsychopharmacology 2020; 45:666-674. [PMID: 31812151 PMCID: PMC7021697 DOI: 10.1038/s41386-019-0586-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 11/25/2019] [Accepted: 11/30/2019] [Indexed: 02/05/2023]
Abstract
Abnormal neuroanatomic brain networks have been reported in schizophrenia, but their characterization across patients with psychotic disorders, and their potential alterations in nonpsychotic relatives, remain to be clarified. Participants recruited by the Bipolar and Schizophrenia Network for Intermediate Phenotypes consortium included 326 probands with psychotic disorders (107 with schizophrenia (SZ), 87 with schizoaffective disorder (SAD), 132 with psychotic bipolar disorder (BD)), 315 of their nonpsychotic first-degree relatives and 202 healthy controls. Single-subject gray matter graphs were extracted from structural MRI scans, and whole-brain neuroanatomic organization was compared across the participant groups. Compared with healthy controls, psychotic probands showed decreased nodal efficiency mainly in bilateral superior temporal regions. These regions had altered morphological relationships primarily with frontal lobe regions, and their network-level alterations were associated with positive symptoms of psychosis. Nonpsychotic relatives showed lower nodal centrality metrics in the prefrontal cortex and subcortical regions, and higher nodal centrality metrics in the left cingulate cortex and left thalamus. Diagnosis-specific analysis indicated that individuals with SZ had lower nodal efficiency in bilateral superior temporal regions than controls, probands with SAD only exhibited lower nodal efficiency in the left superior and middle temporal gyrus, and individuals with psychotic BD did not show significant differences from healthy controls. Our findings provide novel evidence of clinically relevant disruptions in the anatomic association of the superior temporal lobe with other regions of whole-brain networks in patients with psychotic disorders, but not in their unaffected relatives, suggesting that it is a disease-related trait. Network disorganization primarily involving frontal lobe and subcortical regions in nonpsychotic relatives may be related to familial illness risk.
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Affiliation(s)
- Wenjing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Sarah K Keedy
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Elena I Ivleva
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Seenae Eum
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Li Yao
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Carol A Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Brett A Clementz
- Department of Psychology, University of Georgia, Athens, GA, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Godfrey D Pearlson
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
| | - Elliot S Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA.
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46
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Takahashi S, Keeser D, Rauchmann BS, Schneider-Axmann T, Keller-Varady K, Maurus I, Dechent P, Wobrock T, Hasan A, Schmitt A, Ertl-Wagner B, Malchow B, Falkai P. Effect of aerobic exercise combined with cognitive remediation on cortical thickness and prediction of social adaptation in patients with schizophrenia. Schizophr Res 2020; 216:397-407. [PMID: 31806522 DOI: 10.1016/j.schres.2019.11.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 07/29/2019] [Accepted: 11/03/2019] [Indexed: 01/09/2023]
Abstract
Aerobic exercise is a promising intervention for patients with schizophrenia, but structural neuroplastic effects on brain regions relevant to the pathophysiology of the disease remain unclear. This study aimed to elucidate longitudinal changes in cortical thickness after aerobic exercise intervention in schizophrenia patients and the relationship of these changes to clinical correlates. We investigated 21 schizophrenia patients and 23 healthy controls who performed aerobic exercise and 21 schizophrenia patients who played table soccer. The 12-week exercise intervention was combined with computer-assisted cognitive remediation training from week 6 to week 12. Magnetic resonance imaging (MRI) scans were acquired at baseline and weeks 6, 12, and 24. The thickness of the entorhinal, parahippocampal, and lateral and medial prefrontal cortices was assessed with FreeSurfer 6.0. The schizophrenia aerobic exercise group showed a significant increase of cortical thickness in the right entorhinal cortex at week 6, and we found a significant correlation between the cortical thickness of the right lateral prefrontal cortex at baseline and improvement of social adaptation at week 12. In the schizophrenia table soccer and healthy control groups, we found no significant longitudinal change in cortical thickness through the intervention and follow-up period and no correlation of cortical thickness at baseline with clinical measures. Our results suggest that aerobic exercise in schizophrenia modulates the thickness of the entorhinal cortex, a structure adjacent to the hippocampus. Greater cortical thickness of the right lateral prefrontal cortex appears to predict better clinical response to an aerobic exercise intervention in patients with schizophrenia.
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Affiliation(s)
- Shun Takahashi
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Neuropsychiatry, Wakayama Medical University, 811-1 Kimiidera, 6410012, Wakayama, Japan.
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Thomas Schneider-Axmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Katriona Keller-Varady
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Isabel Maurus
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Peter Dechent
- Institute for Cognitive Neurology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Thomas Wobrock
- Department of Psychiatry and Psychotherapy, Georg-August-University, Von-Siebold-Str. 5, 37075, Göttingen, Germany; Centre of Mental Health, County Hospitals Darmstadt-Dieburg, Krankenhausstraße 7, 64823, Groß-Umstadt, Germany
| | - Alkomiet Hasan
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of Sao Paulo, 05403-010, São Paulo, Brazil
| | - Birgit Ertl-Wagner
- Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany; Department of Medical Imaging, University of Toronto, McCaul Street 263, Toronto, M5T1W7, Ontario, Canada
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Psychiatry and Psychotherapy, University of Jena, Philosophenweg 3, 07743, Jena, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
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van Haren NE, Setiaman N, Koevoets MG, Baalbergen H, Kahn RS, Hillegers MH. Brain structure, IQ, and psychopathology in young offspring of patients with schizophrenia or bipolar disorder. Eur Psychiatry 2020; 63:e5. [PMID: 32093799 PMCID: PMC8057400 DOI: 10.1192/j.eurpsy.2019.19] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 10/23/2019] [Accepted: 12/02/2019] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Studying offspring of schizophrenia (SZo) and bipolar disorder patients (BDo) provides important information on the putative neurodevelopmental trajectories underlying development toward severe mental illnesses. We compared intracranial volume (ICV), as a marker for neurodevelopment, and global and local brain measures between SZo or BDo and control offspring (Co) in relation to IQ and psychopathology. METHODS T1-weighted magnetic resonance imaging (MRI) brain scans were obtained from 146 participants (8-19 years; 40 SZo, 66 BDo, 40 Co). Linear mixed models were applied to compare ICV, global, and local brain measures between groups. To investigate the effect of ICV, IQ (four subtests Wechsler Intelligence Scale for Children/Wechsler Adult Intelligence Scale-III) or presence of psychopathology these variables were each added to the model. RESULTS SZo and BDo had significantly lower IQ and more often met criteria for a lifetime psychiatric disorder than Co. ICV was significantly smaller in SZo than in BDo (d = -0.56) and Co (d = -0.59), which was largely independent of IQ (respectively, d = -0.54 and d = -0.35). After ICV correction, the cortex was significantly thinner in SZo than in BDo (d = -0.42) and Co (d = -0.75) and lateral ventricles were larger in BDo than in Co (d = 0.55). Correction for IQ or lifetime psychiatric diagnosis did not change these findings. CONCLUSIONS Despite sharing a lower IQ and a higher prevalence of psychiatric disorders, brain abnormalities in BDo appear less pronounced (but are not absent) than in SZo. Lower ICV in SZo implies that familial risk for schizophrenia has a stronger association with stunted early brain development than familial risk for bipolar disorder.
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Affiliation(s)
- Neeltje E.M. van Haren
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Nikita Setiaman
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Martijn G.J.C. Koevoets
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
| | - Heleen Baalbergen
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
| | - Rene S. Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Manon H.J. Hillegers
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia Children’s Hospital, Rotterdam, The Netherlands
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48
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Nenadić I. [Brain imaging in schizophrenia : A review of current trends and developments]. DER NERVENARZT 2020; 91:18-25. [PMID: 31919551 DOI: 10.1007/s00115-019-00857-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Imaging methods have become the main approach for identifying dysfunctional neuronal networks in schizophrenia. This review article presents recent results of disorders of neuronal networks at structural and functional levels and summarizes the current developments. Large multicenter analyses have further established patterns of regional brain alterations, while novel methods in magnetic resonance (MR) morphometry have contributed to differentiating early from delayed brain structural changes. The use of machine learning approaches has not only enabled the establishment of classification models using biological data for future differential diagnostic use, it has also facilitated multivariate models for outcome prediction following therapeutic interventions. Novel methods, such as BrainAGE, a surrogate marker of accelerated brain aging processes, have added to longitudinal studies to gain insights into the brain structural dynamics from early brain developmental alterations to progressive structural brain changes after disease onset.
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Affiliation(s)
- Igor Nenadić
- Klinik für Psychiatrie und Psychotherapie, Philipps Universität Marburg & Universitätsklinikum Gießen und Marburg (UKGM), Rudolf-Bultmann-Straße 8, 35039, Marburg, Deutschland.
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49
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Stan AD, Tamminga CA, Han K, Kim JB, Padmanabhan J, Tandon N, Hudgens-Haney ME, Keshavan MS, Clementz BA, Pearlson GD, Sweeney JA, Gibbons RD. Associating Psychotic Symptoms with Altered Brain Anatomy in Psychotic Disorders Using Multidimensional Item Response Theory Models. Cereb Cortex 2019; 30:2939-2947. [PMID: 31813988 DOI: 10.1093/cercor/bhz285] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 09/23/2019] [Accepted: 09/23/2019] [Indexed: 12/15/2022] Open
Abstract
Reduced cortical thickness has been demonstrated in psychotic disorders, but its relationship to clinical symptoms has not been established. We aimed to identify the regions throughout neocortex where clinical psychosis manifestations correlate with cortical thickness. Rather than perform a traditional correlation analysis using total scores on psychiatric rating scales, we applied multidimensional item response theory to identify a profile of psychotic symptoms that was related to a region where cortical thickness was reduced. This analysis was performed using a large population of probands with psychotic disorders (N = 865), their family members (N = 678) and healthy volunteers (N = 347), from the 5-site Bipolar-Schizophrenia Network for Intermediate Phenotypes. Regional cortical thickness from structural magnetic resonance scans was measured using FreeSurfer; individual symptoms were rated using the Positive and Negative Syndrome Scale, Montgomery-Asberg Depression Rating Scale, and Young Mania Rating Scale. A cluster of cortical regions whose thickness was inversely related to severity of psychosis symptoms was identified. The regions turned out to be located contiguously in a large region of heteromodal association cortex including temporal, parietal and frontal lobe regions, suggesting a cluster of contiguous neocortical regions important to psychosis expression. When we tested the relationship between reduced cortical surface area and high psychotic symptoms we found no linked regions describing a related cortical set.
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Affiliation(s)
- Ana D Stan
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | | | - Jong Bae Kim
- Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
| | - Jaya Padmanabhan
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | - Neeraj Tandon
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | | | | | - Brett A Clementz
- Departments of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA 30602, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT; Institute of Living, Hartford Hospital, Hartford, CT 06106, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45221, USA
| | - Robert D Gibbons
- Departments of Medicine and Public Health Sciences, University of Chicago, Chicago, IL 60637, USA
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50
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Nakamura R, Asami T, Yoshimi A, Kato D, Fujita E, Takaishi M, Yoshida H, Yamaguchi H, Shiozaki K, Kase A, Hirayasu Y. Clinical and brain structural effects of the Illness Management and Recovery program in middle-aged and older patients with schizophrenia. Psychiatry Clin Neurosci 2019; 73:731-737. [PMID: 31353759 DOI: 10.1111/pcn.12919] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 07/17/2019] [Accepted: 07/23/2019] [Indexed: 01/11/2023]
Abstract
AIMS In this study, we implemented the Illness Management and Recovery (IMR) program for middle-aged and older patients with schizophrenia hospitalized for long periods and assessed the effect of the IMR program on psychiatric symptoms and psychosocial function. The effects of the IMR program on brain structure were also evaluated. METHODS The IMR program was implemented for 19 patients with schizophrenia; 17 patients with schizophrenia receiving treatment as usual (TAU) were also recruited as controls. In all patients, mean age was 61.4 years (range, 50-77 years) and mean hospitalization duration was 13.1 years (range, 1-31 years) at enrollment. Structural magnetic resonance images and Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores as clinical variables were obtained at the beginning and end of the IMR program. Longitudinal analyses were performed to compare the effects of the IMR program on clinical symptoms and cortical thickness in the superior temporal gyrus (STG) between the IMR and TAU groups. RESULTS Significant improvements in GAF scores and the total, Insight and Judgment, and Positive components of the PANSS were found in the IMR group compared with the TAU group. Cortical thickness in the left STG was preserved in the IMR group compared with the TAU group. CONCLUSIONS This is the first report demonstrating the effectiveness of the IMR program for improving psychotic symptoms and psychosocial function and protecting brain structure in middle-aged and older inpatients with schizophrenia hospitalized for long periods.
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Affiliation(s)
- Ryota Nakamura
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan.,Department of Psychiatry, Yokohama Maioka Hospital, Yokohama, Japan
| | - Takeshi Asami
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Asuka Yoshimi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan.,Department of Psychiatry, Yokohama Maioka Hospital, Yokohama, Japan
| | - Daiji Kato
- Totsuka Nishiguchi Rindou Clinic, Yokohama, Japan
| | - Emi Fujita
- Division of Clinical Psychology, Yokohama City University Hospital, Yokohama, Japan
| | - Masao Takaishi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Haruhisa Yoshida
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Hiroyuki Yamaguchi
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan
| | - Kazumasa Shiozaki
- Department of Psychiatry, Yokohama Comprehensive Care Continuum, Yokohama, Japan
| | - Akihiko Kase
- Department of Psychiatry, Yokohama Maioka Hospital, Yokohama, Japan
| | - Yoshio Hirayasu
- Department of Psychiatry, Graduate School of Medicine, Yokohama City University, Yokohama, Japan.,Department of Psychiatry, Hirayasu Hospital, Urasoe, Japan
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