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Driver C, Boyes A, Mohamed AZ, Levenstein JM, Parker M, Hermens DF. Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study. J Youth Adolesc 2024; 53:1029-1046. [PMID: 38217837 PMCID: PMC10980632 DOI: 10.1007/s10964-024-01939-2] [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: 09/11/2023] [Accepted: 01/04/2024] [Indexed: 01/15/2024]
Abstract
Wellbeing is protective against the emergence of psychopathology. Neurobiological markers associated with mental wellbeing during adolescence are important to understand. Limited research has examined neural networks (white matter tracts) and mental wellbeing in early adolescence specifically. A cross-sectional diffusion tensor imaging analysis approach was conducted, from the Longitudinal Adolescent Brain study, First Hundred Brains cohort (N = 99; 46.5% female; Mage = 13.01, SD = 0.55). Participants completed self-report measures including wellbeing, quality-of-life, and psychological distress. Potential neurobiological profiles using fractional anisotropy, axial, and radial diffusivity were determined via a whole brain voxel-wise approach, and hierarchical cluster analysis of fractional anisotropy values, obtained from 21 major white matter tracts. Three cluster groups with significantly different neurobiological profiles were distinguished. No significant differences were found between the three cluster groups and measures of wellbeing, but two left lateralized significant associations between white matter tracts and wellbeing measures were found. These results provide preliminary evidence for potential neurobiological markers of mental health and wellbeing in early adolescence and should be tracked longitudinally to provide more detailed and robust findings.
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Affiliation(s)
- Christina Driver
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia.
| | - Amanda Boyes
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia
| | - Abdalla Z Mohamed
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia
| | - Jacob M Levenstein
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia
| | - Marcella Parker
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, 12 Innovation Parkway, Birtinya, Sunshine Coast, QLD, Australia
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Kobayashi H, Sasabayashi D, Takahashi T, Furuichi A, Kido M, Takayanagi Y, Noguchi K, Suzuki M. The relationship between gray/white matter contrast and cognitive performance in first-episode schizophrenia. Cereb Cortex 2024; 34:bhae009. [PMID: 38265871 DOI: 10.1093/cercor/bhae009] [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: 02/10/2023] [Revised: 01/04/2024] [Accepted: 01/04/2024] [Indexed: 01/26/2024] Open
Abstract
Previous postmortem brain studies have revealed disturbed myelination in the intracortical regions in patients with schizophrenia, possibly reflecting anomalous brain maturational processes. However, it currently remains unclear whether this anomalous myelination is already present in early illness stages and/or progresses during the course of the illness. In this magnetic resonance imaging study, we examined gray/white matter contrast (GWC) as a potential marker of intracortical myelination in 63 first-episode schizophrenia (FESz) patients and 77 healthy controls (HC). Furthermore, we investigated the relationships between GWC findings and clinical/cognitive variables in FESz patients. GWC in the bilateral temporal, parietal, occipital, and insular regions was significantly higher in FESz patients than in HC, which was partly associated with the durations of illness and medication, the onset age, and lower executive and verbal learning performances. Because higher GWC implicates lower myelin in the deeper layers of the cortex, these results suggest that schizophrenia patients have less intracortical myelin at the time of their first psychotic episode, which underlies lower cognitive performance in early illness stages.
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Affiliation(s)
- Haruko Kobayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Mikio Kido
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Kido Clinic, 244 Honoki, Imizu City, Toyama, 934-0053, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Arisawabashi Hospital, 5-5 Hane-Shin, Fuchu-Machi, Toyama, 939-2704, Japan
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama, 930-0194, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama 930-0194, Japan
- Research Center for idling Brain Science, University of Toyama, 2630 Sugitani, Toyama, 930-0194, Japan
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Synaptic plasticity and mental health: methods, challenges and opportunities. Neuropsychopharmacology 2023; 48:113-120. [PMID: 35810199 PMCID: PMC9700665 DOI: 10.1038/s41386-022-01370-w] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/13/2022] [Accepted: 06/20/2022] [Indexed: 12/14/2022]
Abstract
Activity-dependent synaptic plasticity is a ubiquitous property of the nervous system that allows neurons to communicate and change their connections as a function of past experiences. Through reweighting of synaptic strengths, the nervous system can remodel itself, giving rise to durable memories that create the biological basis for mental function. In healthy individuals, synaptic plasticity undergoes characteristic developmental and aging trajectories. Dysfunctional plasticity, in turn, underlies a wide spectrum of neuropsychiatric disorders including depression, schizophrenia, addiction, and posttraumatic stress disorder. From a mechanistic standpoint, synaptic plasticity spans the gamut of spatial and temporal scales, from microseconds to the lifespan, from microns to the entire nervous system. With the numbers and strengths of synapses changing on such wide scales, there is an important need to develop measurement techniques with complimentary sensitivities and a growing number of approaches are now being harnessed for this purpose. Through hemodynamic measures, structural and tracer imaging, and noninvasive neuromodulation, it is possible to image structural and functional changes that underlie synaptic plasticity and associated behavioral learning. Here we review the mechanisms of neural plasticity and the historical and future trends in techniques that allow imaging of synaptic changes that accompany psychiatric disorders, highlighting emerging therapeutics and the challenges and opportunities accompanying this burgeoning area of study.
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Shah R, Ghosh A, Avasthi A, Ahuja CK, Khandelwal N, Nehra R. White Matter Microstructure and Gray Matter Volume in Cannabis-Induced Psychosis and Schizophrenia With Cannabis Use. J Neuropsychiatry Clin Neurosci 2022; 34:406-413. [PMID: 35872614 DOI: 10.1176/appi.neuropsych.21070172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE This study explored the differences in white matter (WM) microstructural integrity and gray matter (GM) volume between cannabis-induced psychosis (CIP) and schizophrenia with cannabis use (SZC). METHODS This cross-sectional study with convenience sampling involved three groups of 20 participants each (CIP, SZC, and a control group without substance use), matched on age, handedness, and education. CIP and SZC were diagnosed with the Psychiatric Research Interview for Substance and Mental Disorders. Diffusion tensor and kurtosis imaging were done, and fractional anisotropy (FA), mean diffusivity, and mean kurtosis were estimated. GM volume was measured with voxel-based morphometry. RESULTS Group comparisons revealed comparable age at initiation and duration and frequency of cannabis use between participants in the SZC and CIP groups. Participants with SZC had lower FA than controls in the anterior and retrolenticular internal capsule limbs, cingulate gyrus hippocampal formation, fornix, and superior fronto-occipital fasciculus (all p<0.05). Participants with CIP had lower FA than controls in the left fornix and right superior fronto-occipital fasciculus but higher FA than those with SZC in the left corticospinal tract (all p<0.05). On morphometry, participants with CIP had greater cerebellar GM volume than those with SZC and greater inferior frontal gyrus volumes than controls (all p<0.05). CONCLUSIONS Widespread WM microstructural abnormalities were observed in participants with SZC, and fewer but significant WM disruptions were observed in those with CIP. Better WM integrity in some WM fiber tracts and greater GM volumes in crucial brain areas among those with CIP may have prevented the transition to schizophrenia.
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Affiliation(s)
- Raghav Shah
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Abhishek Ghosh
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Ajit Avasthi
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Chirag K Ahuja
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Niranjan Khandelwal
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Ritu Nehra
- Department of Psychiatry (Shah, Ghosh, Avasthi, Nehra) and Department of Radiodiagnosis and Imaging (Ahuja, Khandelwal), Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
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Sadeghi D, Shoeibi A, Ghassemi N, Moridian P, Khadem A, Alizadehsani R, Teshnehlab M, Gorriz JM, Khozeimeh F, Zhang YD, Nahavandi S, Acharya UR. An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works. Comput Biol Med 2022; 146:105554. [DOI: 10.1016/j.compbiomed.2022.105554] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 04/11/2022] [Accepted: 04/11/2022] [Indexed: 12/21/2022]
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Kritikos M, Clouston SAP, Huang C, Pellecchia AC, Mejia-Santiago S, Carr MA, Kotov R, Lucchini RG, Gandy SE, Bromet EJ, Luft BJ. Cortical complexity in world trade center responders with chronic posttraumatic stress disorder. Transl Psychiatry 2021; 11:597. [PMID: 34815383 PMCID: PMC8611009 DOI: 10.1038/s41398-021-01719-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/18/2021] [Accepted: 10/29/2021] [Indexed: 12/19/2022] Open
Abstract
Approximately 23% of World Trade Center (WTC) responders are experiencing chronic posttraumatic stress disorder (PTSD) associated with their exposures at the WTC following the terrorist attacks of 9/11/2001, which has been demonstrated to be a risk factor for cognitive impairment raising concerns regarding their brain health. Cortical complexity, as measured by analyzing Fractal Dimension (FD) from T1 MRI brain images, has been reported to be reduced in a variety of psychiatric and neurological conditions. In this report, we hypothesized that FD would be also reduced in a case-control sample of 99 WTC responders as a result of WTC-related PTSD. The results of our surface-based morphometry cluster analysis found alterations in vertex clusters of complexity in WTC responders with PTSD, with marked reductions in regions within the frontal, parietal, and temporal cortices, in addition to whole-brain absolute bilateral and unilateral complexity. Furthermore, region of interest analysis identified that the magnitude of changes in regional FD severity was associated with increased PTSD symptoms (reexperiencing, avoidance, hyperarousal, negative affect) severity. This study confirms prior findings on FD and psychiatric disorders and extends our understanding of FD associations with posttraumatic symptom severity. The complex and traumatic experiences that led to WTC-related PTSD were associated with reductions in cortical complexity. Future work is needed to determine whether reduced cortical complexity arose prior to, or concurrently with, onset of PTSD.
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Affiliation(s)
- Minos Kritikos
- Program in Public Health and Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Sean A P Clouston
- Program in Public Health and Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
| | - Chuan Huang
- Department of Radiology, Renaissance School of Medicine at Stony Brook, Stony Brook, NY, USA
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Alison C Pellecchia
- World Trade Center Health and Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Stephanie Mejia-Santiago
- World Trade Center Health and Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Melissa A Carr
- World Trade Center Health and Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Roman Kotov
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Roberto G Lucchini
- Department of Environmental Health Sciences, Robert Stempel School of Public Health, Florida International University, Miami, FL, USA
| | - Samuel E Gandy
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry and Mount Sinai Alzheimer's Disease Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Evelyn J Bromet
- Department of Psychiatry, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Benjamin J Luft
- World Trade Center Health and Wellness Program, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
- Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
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7
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Li D, Tang W, Yan T, Zhang N, Xiang J, Niu Y, Wang B. Abnormalities in hemispheric lateralization of intra- and inter-hemispheric white matter connections in schizophrenia. Brain Imaging Behav 2021; 15:819-832. [PMID: 32767209 DOI: 10.1007/s11682-020-00292-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Hemispheric lateralization is a prominent feature of the human brain and is grounded into intra- and inter-hemispheric white matter (WM) connections. However, disruptions in hemispheric lateralization involving both intra- and inter-hemispheric WM connections in schizophrenia is still unclear. Hence, a quantitative measure of the hemispheric lateralization of intra- and inter-hemispheric WM connections could provide new insights into schizophrenia. This work performed diffusion tensor imaging on 50 patients and 58 matched healthy controls. Using graph theory, the global and nodal efficiencies were computed for both intra- and inter-hemispheric networks. We found that patients with schizophrenia showed significantly decrease in both global and nodal efficiency of hemispheric networks relative to healthy controls. Specially, deficits in intra-hemispheric integration and inter-hemispheric communication were revealed in frontal and temporal regions for schizophrenia. We also found disrupted hemispheric asymmetries in brain regions associated with emotion, memory, and visual processes for schizophrenia. Moreover, abnormal hemispheric asymmetry of nodal efficiency was significantly correlated with the symptom of the patients. Our finding indicated that the hemispheric WM lateralization of intra- and inter-hemispheric connections could serve as a potential imaging biomarker for schizophrenia.
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Affiliation(s)
- Dandan Li
- College of Information and Computer, Taiyuan University of Technology, Shanxi, China
| | - Wenjing Tang
- School of Mechanical, Electrical and Information Engineering, Shandong University at Weihai, Shandong, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Shanxi, China
| | - Nan Zhang
- College of Information and Computer, Taiyuan University of Technology, Shanxi, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Shanxi, China
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, Shanxi, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Shanxi, China.
- Translational Medicine Research Center, Shanxi Medical University, Shanxi, China.
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Zbtb16 regulates social cognitive behaviors and neocortical development. Transl Psychiatry 2021; 11:242. [PMID: 33895774 PMCID: PMC8068730 DOI: 10.1038/s41398-021-01358-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 03/28/2021] [Accepted: 04/09/2021] [Indexed: 02/02/2023] Open
Abstract
Zinc finger and BTB domain containing 16 (ZBTB16) play the roles in the neural progenitor cell proliferation and neuronal differentiation during development, however, how the function of ZBTB16 is involved in brain function and behaviors unknown. Here we show the deletion of Zbtb16 in mice leads to social impairment, repetitive behaviors, risk-taking behaviors, and cognitive impairment. To elucidate the mechanism underlying the behavioral phenotypes, we conducted histological analyses and observed impairments in thinning of neocortical layer 6 (L6) and a reduction of TBR1+ neurons in Zbtb16 KO mice. Furthermore, we found increased dendritic spines and microglia, as well as developmental defects in oligodendrocytes and neocortical myelination in the prefrontal cortex (PFC) of Zbtb16 KO mice. Using genomics approaches, we identified the Zbtb16 transcriptome that includes genes involved in neocortical maturation such as neurogenesis and myelination, and both autism spectrum disorder (ASD) and schizophrenia (SCZ) pathobiology. Co-expression networks further identified Zbtb16-correlated modules that are unique to ASD or SCZ, respectively. Our study provides insight into the novel roles of ZBTB16 in behaviors and neocortical development related to the disorders.
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Sacks DD, Schwenn PE, McLoughlin LT, Lagopoulos J, Hermens DF. Phase-Amplitude Coupling, Mental Health and Cognition: Implications for Adolescence. Front Hum Neurosci 2021; 15:622313. [PMID: 33841115 PMCID: PMC8032979 DOI: 10.3389/fnhum.2021.622313] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/02/2021] [Indexed: 01/01/2023] Open
Abstract
Identifying biomarkers of developing mental disorder is crucial to improving early identification and treatment-a key strategy for reducing the burden of mental disorders. Cross-frequency coupling between two different frequencies of neural oscillations is one such promising measure, believed to reflect synchronization between local and global networks in the brain. Specifically, in adults phase-amplitude coupling (PAC) has been shown to be involved in a range of cognitive processes, including working and long-term memory, attention, language, and fluid intelligence. Evidence suggests that increased PAC mediates both temporary and lasting improvements in working memory elicited by transcranial direct-current stimulation and reductions in depressive symptoms after transcranial magnetic stimulation. Moreover, research has shown that abnormal patterns of PAC are associated with depression and schizophrenia in adults. PAC is believed to be closely related to cortico-cortico white matter (WM) microstructure, which is well established in the literature as a structural mechanism underlying mental health. Some cognitive findings have been replicated in adolescents and abnormal patterns of PAC have also been linked to ADHD in young people. However, currently most research has focused on cross-sectional adult samples. Whereas initial hypotheses suggested that PAC was a state-based measure due to an early focus on cognitive, task-based research, current evidence suggests that PAC has both state-based and stable components. Future longitudinal research focusing on PAC throughout adolescent development could further our understanding of the relationship between mental health and cognition and facilitate the development of new methods for the identification and treatment of youth mental health.
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Affiliation(s)
- Dashiell D Sacks
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD, Australia
| | - Paul E Schwenn
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD, Australia
| | - Larisa T McLoughlin
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD, Australia
| | - Jim Lagopoulos
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD, Australia
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, Sunshine Coast, QLD, Australia
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Zhang T, Song J, Chen C, Li R, Li Y, Sun Y, Fang T, Xu W, Tian H, Zhuo C. Brain features of nearly drug-naïve female monozygotic twins with first-episode schizophrenia and the classification accuracy of brain feature patterns: A pilot study. Brain Behav 2021; 11:e01992. [PMID: 33295156 PMCID: PMC7882158 DOI: 10.1002/brb3.1992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 11/13/2020] [Accepted: 11/23/2020] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Data on differences in brain features between monozygotic (MZ) twins with and without schizophrenia are scarce. METHODS We compared brain features of female MZ twins with and without first-episode schizophrenia and healthy controls (n = 20 each). Voxel-based morphometry and tract-based spatial statistics were used to analyze differences in brain structure. Whole-brain effective connectivity (EC) and functional connectivity (FC) networks were constructed using resting-state functional magnetic resonance imaging (rs-fMRI) data. RESULTS Female twins with schizophrenia exhibited abnormal gray matter volume (GMV) in the basal ganglia and prefrontal and parietal cortices, impairments in the arcuate fasciculus, and significant disruptions (primarily decreases) in nine EC networks. They exhibited rs-EC alterations involving the limbic areas and subcortex. Combined rs-EC and rs-FC data distinguished twins with first-episode schizophrenia with high accuracy. Combined consideration of structural and functional features enabled the distinction of female MZ twins with schizophrenia from those without schizophrenia and healthy controls with 100% accuracy. CONCLUSIONS Female MZ twins with schizophrenia exhibited increased GMV, white matter impairment, and disruptions in EC and FC networks. The combination of rs-EC + rs-FC data could distinguish female twins with schizophrenia from twins without schizophrenia and healthy controls with 97.4% accuracy, and the addition of structural brain features yielded a 100% accuracy rate. These findings may provide pivotal insight for further study of the mechanisms underlying schizophrenia.
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Affiliation(s)
- Tao Zhang
- Department of PsychiatryDongying Shengli HospitalDongyingChina
| | - Jie Song
- Department of PsychiatryShanghai Qingpu District Mental Health CenterShanghaiChina
| | - Ce Chen
- Department of PsychiatryWenzhou Seventh HospitalWenzhouChina
| | - Ran Li
- Psychiatric‐Neuroimaging‐Genetics and Comorbidity LaboratoryTianjin Mental Health CentreTianjin Anding HospitalTianjin Medical University Mental Health Teaching HospitalTianjinChina
- Department of PsychiatryTianjin Medical UniversityTianjinChina
| | - Yachen Li
- Psychiatric‐Neuroimaging‐Genetics and Comorbidity LaboratoryTianjin Mental Health CentreTianjin Anding HospitalTianjin Medical University Mental Health Teaching HospitalTianjinChina
- Department of PsychiatryTianjin Medical UniversityTianjinChina
| | - Yun Sun
- Psychiatric‐Neuroimaging‐Genetics and Comorbidity LaboratoryTianjin Mental Health CentreTianjin Anding HospitalTianjin Medical University Mental Health Teaching HospitalTianjinChina
- Department of PsychiatryTianjin Medical UniversityTianjinChina
| | - Tao Fang
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPP_Lab)Tianjin Fourth Center HospitalTianjin Fourth Center Hospital Affiliated to Nankai UniversityTianjinChina
| | - Weiwei Xu
- Department of PsychiatryDongying Shengli HospitalDongyingChina
| | - Hongjun Tian
- Department of PsychiatryTianjin Medical UniversityTianjinChina
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPP_Lab)Tianjin Fourth Center HospitalTianjin Fourth Center Hospital Affiliated to Nankai UniversityTianjinChina
| | - Chuanjun Zhuo
- Department of PsychiatryWenzhou Seventh HospitalWenzhouChina
- Psychiatric‐Neuroimaging‐Genetics and Comorbidity LaboratoryTianjin Mental Health CentreTianjin Anding HospitalTianjin Medical University Mental Health Teaching HospitalTianjinChina
- Department of PsychiatryTianjin Medical UniversityTianjinChina
- Key Laboratory of Sensory Information Processing Abnormalities in Schizophrenia (SIPP_Lab)Tianjin Fourth Center HospitalTianjin Fourth Center Hospital Affiliated to Nankai UniversityTianjinChina
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11
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Sacks DD, Lagopoulos J, Hatton SN, Iorfino F, Carpenter JS, Crouse JJ, Naismith SL, Scott EM, Hickie IB, Hermens DF. White Matter Integrity According to the Stage of Mental Disorder in Youth. Psychiatry Res Neuroimaging 2021; 307:111218. [PMID: 33162289 DOI: 10.1016/j.pscychresns.2020.111218] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 07/31/2020] [Accepted: 10/30/2020] [Indexed: 10/23/2022]
Abstract
The present study investigated differences in white matter (WM) integrity between 96 young people with affective and/or psychotic symptoms classified at an early stage of mental disorder (i.e. 'attenuated syndrome'; stage 1b), 85 young people classified at a more advanced stage of mental disorder (i.e. 'discrete disorder'; stage 2), and 81 demographically matched healthy controls using diffusion tensor imaging. The relationship between WM integrity (indexed by fractional anisotropy; FA) across the tracts and neuropsychological functioning was also investigated. A significant reduction in FA was identified in those with more advanced disorder in the body of the corpus callosum. Clinical stage groups were associated with significant neuropsychological impairment, which was significantly greater in those with discrete disorders. Compared to those in the earlier stage of disorder, participants at the later clinical stage showed decreased FA in the body of the corpus callosum that was associated with worse performance in attentional set formation maintenance, shifting and flexibility. These results provide further support for clinical staging of mental disorder and highlight the potential for utilising neuroanatomical biomarkers to support the classification of stages of mental disorder in the future.
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Affiliation(s)
- Dashiell D Sacks
- Thompson Institute, University of the Sunshine Coast, QLD, Australia.
| | - Jim Lagopoulos
- Thompson Institute, University of the Sunshine Coast, QLD, Australia
| | - Sean N Hatton
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Frank Iorfino
- Brain & Mind Centre, University of Sydney, NSW, Australia
| | | | - Jacob J Crouse
- Brain & Mind Centre, University of Sydney, NSW, Australia
| | | | | | - Ian B Hickie
- Brain & Mind Centre, University of Sydney, NSW, Australia
| | - Daniel F Hermens
- Thompson Institute, University of the Sunshine Coast, QLD, Australia
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12
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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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13
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Luckhoff HK, du Plessis S, Scheffler F, Phahladira L, Kilian S, Buckle C, Smit R, Chiliza B, Asmal L, Emsley R. Fronto-limbic white matter fractional anisotropy and body mass index in first-episode schizophrenia spectrum disorder patients compared to healthy controls. Psychiatry Res Neuroimaging 2020; 305:111173. [PMID: 32896691 DOI: 10.1016/j.pscychresns.2020.111173] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/27/2020] [Accepted: 08/31/2020] [Indexed: 12/18/2022]
Abstract
In this diffusion tensor imaging study, we explored the associations of body mass index (BMI) with white matter microstructure in first-episode schizophrenia spectrum disorder patients (n = 69) versus healthy controls (n = 93). We focused on fractional anisotropy (FA) measures for fronto-limbic white matter tracts known to connect brain regions which form part of a "core eating network". Secondary objectives included the associations of body mass with global illness severity, psychopathology and depressive symptoms. In a multivariate analysis of covariance (MANCOVA) model, there was a significant interaction between BMI and group (patient versus control) across the fronto-limbic white matter tracts of interest (F(1,155)= 4.91, p = 0.03). In a sub-analysis, BMI was significantly inversely correlated with FA measures for the genu and body of the corpus callosum, left and right tapetum, and left superior fronto-occipital fasciculus in controls. In patients, BMI was significantly positively correlated with white matter FA for the genu of the corpus callosum and left tapetum. Lower BMI was significantly correlated with more severe negative symptoms, as was earlier age of illness onset. Body mass may be differentially associated with fronto-limbic white matter microstructure in first-episode schizophrenia spectrum disorder compared to controls.
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Affiliation(s)
- H K Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa.
| | - S du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - F Scheffler
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - L Phahladira
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - S Kilian
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - C Buckle
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - R Smit
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - B Chiliza
- Department of Psychiatry, Nelson R Mandela School of Medicine, University of Kwazulu-Natal, Durban, South Africa
| | - L Asmal
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
| | - R Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape 7500, South Africa
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14
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Language in schizophrenia: relation with diagnosis, symptomatology and white matter tracts. NPJ SCHIZOPHRENIA 2020; 6:10. [PMID: 32313047 PMCID: PMC7171150 DOI: 10.1038/s41537-020-0099-3] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 02/28/2020] [Indexed: 01/04/2023]
Abstract
Language deviations are a core symptom of schizophrenia. With the advances in computational linguistics, language can be easily assessed in exact and reproducible measures. This study investigated how language characteristics relate to schizophrenia diagnosis, symptom, severity and integrity of the white matter language tracts in patients with schizophrenia and healthy controls. Spontaneous speech was recorded and diffusion tensor imaging was performed in 26 schizophrenia patients and 22 controls. We were able to classify both groups with a sensitivity of 89% and a specificity of 82%, based on mean length of utterance and clauses per utterance. Language disturbances were associated with negative symptom severity. Computational language measures predicted language tract integrity in patients (adjusted R2 = 0.467) and controls (adjusted R2 = 0.483). Quantitative language analyses have both clinical and biological validity, offer a simple, helpful marker of both severity and underlying pathology, and provide a promising tool for schizophrenia research and clinical practice.
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15
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Kyriakopoulos M, Bargiotas T, Barker GJ, Frangou S. Diffusion tensor imaging in schizophrenia. Eur Psychiatry 2020; 23:255-73. [DOI: 10.1016/j.eurpsy.2007.12.004] [Citation(s) in RCA: 103] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2007] [Revised: 11/19/2007] [Accepted: 12/03/2007] [Indexed: 12/12/2022] Open
Abstract
AbstractDiffusion tensor imaging (DTI) is a magnetic resonance imaging technique that is increasingly being used for the non-invasive evaluation of brain white matter abnormalities. In this review, we discuss the basic principles of DTI, its roots and the contribution of European centres in its development, and we review the findings from DTI studies in schizophrenia. We searched EMBASE, PubMed, PsychInfo, and Medline from February 1998 to December 2006 using as keywords ‘schizophrenia’, ‘diffusion’, ‘tensor’, and ‘DTI’. Forty studies fulfilling the inclusion criteria of this review were included and systematically reviewed. White matter abnormalities in many diverse brain regions were identified in schizophrenia. Although the findings are not completely consistent, frontal and temporal white matter seems to be more commonly affected. Limitations and future directions of this method are discussed.
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16
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Komatsu H, Takeuchi H, Kikuchi Y, Ono C, Yu Z, Iizuka K, Takano Y, Kakuto Y, Funakoshi S, Ono T, Ito J, Kunii Y, Hino M, Nagaoka A, Iwasaki Y, Yamamori H, Yasuda Y, Fujimoto M, Azechi H, Kudo N, Hashimoto R, Yabe H, Yoshida M, Saito Y, Kakita A, Fuse N, Kawashima R, Taki Y, Tomita H. Ethnicity-Dependent Effects of Schizophrenia Risk Variants of the OLIG2 Gene on OLIG2 Transcription and White Matter Integrity. Schizophr Bull 2020; 46:1619-1628. [PMID: 32285113 PMCID: PMC7846078 DOI: 10.1093/schbul/sbaa049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Previous studies have indicated associations between several OLIG2 gene single-nucleotide polymorphisms (SNPs) and susceptibility to schizophrenia among Caucasians. Consistent with these findings, postmortem brain and diffusion tensor imaging studies have indicated that the schizophrenia-risk-associated allele (A) in the OLIG2 SNP rs1059004 predicts lower OLIG2 gene expression in the dorsolateral prefrontal cortex (DLPFC) of schizophrenia patients and reduced white matter (WM) integrity of the corona radiata in normal brains among Caucasians. In an effort to replicate the association between this variant and WM integrity among healthy Japanese, we found that the number of A alleles was positively correlated with WM integrity in some fiber tracts, including the right posterior limb of the internal capsule, and with mean blood flow in a widespread area, including the inferior frontal operculum, orbital area, and triangular gyrus. Because the A allele affected WM integrity in opposite directions in Japanese and Caucasians, we investigated a possible association between the OLIG2 gene SNPs and the expression level of OLIG2 transcripts in postmortem DLPFCs. We evaluated rs1059004 and additional SNPs in the 5' upstream and 3' downstream regions of rs1059004 to cover the broader region of the OLIG2 gene. The 2 SNPs (rs1059004 and rs9653711) had opposite effects on OLIG2 gene expression in the DLPFC in Japanese and Caucasians. These findings suggest ethnicity-dependent opposite effects of OLIG2 gene SNPs on WM integrity and OLIG2 gene expression in the brain, which may partially explain the failures in replicating associations between genetic variants and psychiatric phenotypes among ethnicities.
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Affiliation(s)
- Hiroshi Komatsu
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan,Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,To whom correspondence should be addressed; Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aobaku, Sendai, 980-8573, Japan; Department of Psychiatry, Miyagi Psychiatric Center, Mubanchi, Tekurada, Natori, 981-1231, Japan; tel: +81-22-384-2236, fax: +81-22-384-9100, e-mail:
| | - Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yoshie Kikuchi
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Chiaki Ono
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Zhiqian Yu
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Kunio Iizuka
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yuji Takano
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Yoshihisa Kakuto
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan
| | - Shunichi Funakoshi
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan,Department of Community Psychiatry, Tohoku University, Sendai, Japan
| | - Takashi Ono
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan
| | - Junko Ito
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Yasuto Kunii
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan,Department of Psychiatry, Aizu Medical Center Fukushima Medical University, Fukushima, Japan
| | - Mizuki Hino
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Atsuko Nagaoka
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Yasushi Iwasaki
- Department of Neuropathology, Institute for Medical Science of Aging, Aichi Medical University, Nagakute, Japan
| | - Hidenaga Yamamori
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Michiko Fujimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hirotsugu Azechi
- Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Noriko Kudo
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan,Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Hirooki Yabe
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Mari Yoshida
- Department of Neuropathology, Institute for Medical Science of Aging, Aichi Medical University, Nagakute, Japan
| | - Yuko Saito
- Department of Pathology and Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Ryuta Kawashima
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan,Smart Aging International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yasuyuki Taki
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Hiroaki Tomita
- Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan,Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
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17
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Jo YT, Lee J, Joo SW, Kim H, Shon SH, Yoon W, Hong Y. Additive Burden of Abnormal Diffusivity in the Brain with Schizophrenia: A Diffusion Tensor Imaging Study with Public Neuroimaging Data. Psychiatry Investig 2020; 17:341-349. [PMID: 32252513 PMCID: PMC7176571 DOI: 10.30773/pi.2019.0200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 01/20/2020] [Indexed: 11/27/2022] Open
Abstract
OBJECTIVE Diffusion tensor imaging has been extensively applied to schizophrenia research. In this study, we counted the number of abnormal brain regions with altered diffusion measures in patients with schizophrenia to enumerate the burden of abnormal diffusivity in the brain. METHODS The public neuroimaging data of the COBRE project from SchizConnect were used for the study. The studied dataset consisted of data from 57 patients with schizophrenia and 71 healthy participants. FreeSurfer and FSL were applied for image processing and analysis. After verifying 161 regions of interest (ROIs), mean diffusion measures in every single ROI in all study participants were measured and normalized into Z-scores. Each ROI was then defined as normal or abnormal on the basis of a cutoff absolute Z-score of 1.96. The number of abnormal ROIs was obtained by each diffusion measure. RESULTS The numbers of ROIs with increased radial diffusivity and increased trace were significantly larger in the patient group than in healthy participants. CONCLUSION Thus, the patient group showed a significant increase in abnormal ROIs, strongly indicating that schizophrenia is not caused by the pathology of a single brain region, but is instead attributable to the additive burden of structural alterations within multiple brain regions.
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Affiliation(s)
- Young Tak Jo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sung Woo Joo
- Republic of Korea Navy, Donghae, Republic of Korea
| | - Harin Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Seung-Hyun Shon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Woon Yoon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Youjin Hong
- Department of Psychiatry, Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung, Republic of Korea
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18
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Hermens DF, Hatton SN, White D, Lee RSC, Guastella AJ, Scott EM, Naismith SL, Hickie IB, Lagopoulos J. A data-driven transdiagnostic analysis of white matter integrity in young adults with major psychiatric disorders. Prog Neuropsychopharmacol Biol Psychiatry 2019; 89:73-83. [PMID: 30171994 DOI: 10.1016/j.pnpbp.2018.08.032] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 08/12/2018] [Accepted: 08/29/2018] [Indexed: 01/08/2023]
Abstract
Diffusion tensor imaging (DTI) has been utilized to index white matter (WM) integrity in the major psychiatric disorders. However, the findings within and across such disorders have been mixed. Given this, transdiagnostic sampling with data-driven statistical approaches may lead to new and better insights about the clinical and functional factors associated with WM abnormalities. Thus, we undertook a cross-sectional DTI study of 401 young adult (18-30 years old) outpatients with a major psychiatric (depressive, bipolar, psychotic, or anxiety) disorder and 61 healthy controls. Participants also completed self-report questionnaires and underwent neuropsychological assessment. Fractional anisotropy (FA) as well as axial (AD) and radial (RD) diffusivity was determined via a whole brain voxel-wise approach (tract-based spatial statistics). Hierarchical cluster analysis was performed on FA scores in patients only, obtained from 20 major WM tracts (that is, association, projection and commissural fibers). The three cluster groups derived were distinguished by having consistently increased or decreased FA scores across all tracts. Compared to controls, the largest cluster (N = 177) showed significantly increased FA in 55% of tracts, the second cluster (N = 169) demonstrated decreased FA (in 90% of tracts) and the final cluster (N = 55) exhibited the most increased FA (in 95% of tracts). Importantly, the distribution of primary diagnosis did not significantly differ among the three clusters. Furthermore, the clusters showed comparable functional, clinical and neuropsychological measures, with the exception of alcohol use, medication status and verbal fluency. Overall, this study provides evidence that among young adults with a major psychiatric disorder there are subgroups with either abnormally high or low FA and that either pattern is associated with suboptimal functioning. Importantly, these neuroimaging-based subgroups appear despite diagnostic and clinical factors, suggesting differential treatment strategies are warranted.
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Affiliation(s)
- Daniel F Hermens
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia; Sunshine Coast Mind and Neuroscience Thompson Institute, University of the Sunshine Coast, Birtinya, QLD, Australia.
| | - Sean N Hatton
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia; Department of Psychiatry, University of California, San Diego, CA, USA
| | - Django White
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Rico S C Lee
- Brain and Mental Health Laboratory, Monash University, Melbourne, VIC, Australia
| | - Adam J Guastella
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Elizabeth M Scott
- School of Medicine, University of Notre Dame, Sydney, NSW, Australia
| | - Sharon L Naismith
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Ian B Hickie
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - Jim Lagopoulos
- Sunshine Coast Mind and Neuroscience Thompson Institute, University of the Sunshine Coast, Birtinya, QLD, Australia
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19
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Takayanagi Y, Sasabayashi D, Takahashi T, Komori Y, Furuichi A, Kido M, Nishikawa Y, Nakamura M, Noguchi K, Suzuki M. Altered brain gyrification in deficit and non-deficit schizophrenia. Psychol Med 2019; 49:573-580. [PMID: 29739476 DOI: 10.1017/s0033291718001228] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Patients with the deficit form of schizophrenia (D-SZ) are characterized by severe primary negative symptoms and differ from patients with the non-deficit form of schizophrenia (ND-SZ) in several aspects. No study has measured brain gyrification, which is a potential marker of neurodevelopment, in D-SZ and ND-SZ. METHODS We obtained magnetic resonance scans from 135 schizophrenia patients and 50 healthy controls. The proxy scale for deficit syndrome (PDS) was used for the classification of D-SZ and ND-SZ. The local gyrification index (LGI) of the entire cortex was measured using FreeSurfer. Thirty-seven D-SZ and 36 ND-SZ patients were included in the LGI analyses. We compared LGI across the groups. RESULTS SZ patients exhibited hyper-gyral patterns in the bilateral dorsal medial prefrontal and ventromedial prefrontal cortices, bilateral anterior cingulate gyri and right lateral parietal/occipital cortices as compared with HCs. Although patients with D-SZ or ND-SZ had higher LGI in similar regions compared with HC, the hyper-gyral patterns were broader in ND-SZ. ND-SZ patients exhibited a significantly higher LGI in the left inferior parietal lobule relative to D-SZ patients. Duration of illness inversely associated with LGI in broad regions only among ND-SZ patients. CONCLUSIONS The common hyper-gyral patterns among D-SZ and ND-SZ suggest that D-SZ and ND-SZ may share neurodevelopmental abnormalities. The different degrees of cortical gyrification seen in the left parietal regions, and the distinct correlation between illness chronicity and LGI observed in the prefrontal and insular cortices may be related to the differences in the clinical manifestations among D-SZ and ND-SZ.
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Affiliation(s)
- Yoichiro Takayanagi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Tsutomu Takahashi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Yuko Komori
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Mikio Kido
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Yumiko Nishikawa
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Mihoko Nakamura
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Kyo Noguchi
- Department of Radiology,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
| | - Michio Suzuki
- Department of Neuropsychiatry,University of Toyama Graduate School of Medicine and Pharmaceutical Sciences,Toyama,Japan
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20
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Mohammadi A, Rashidi E, Amooeian VG. Brain, blood, cerebrospinal fluid, and serum biomarkers in schizophrenia. Psychiatry Res 2018; 265:25-38. [PMID: 29680514 DOI: 10.1016/j.psychres.2018.04.036] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 03/20/2018] [Accepted: 04/11/2018] [Indexed: 12/29/2022]
Abstract
Over the last decade, finding a reliable biomarker for the early detection of schizophrenia (Scz) has been a topic of interest. The main goal of the current review is to provide a comprehensive view of the brain, blood, cerebrospinal fluid (CSF), and serum biomarkers of Scz disease. Imaging studies have demonstrated that the volumes of the corpus callosum, thalamus, hippocampal formation, subiculum, parahippocampal gyrus, superior temporal gyrus, prefrontal and orbitofrontal cortices, and amygdala-hippocampal complex were reduced in patients diagnosed with Scz. It has been revealed that the levels of interleukin 1β (IL-1β), IL-6, IL-8, and TNF-α were increased in patients with Scz. Decreased mRNA levels of brain-derived neurotrophic factor (BDNF), tropomyosin receptor kinase B (TrkB), neurotrophin-3 (NT-3), nerve growth factor (NGF), and vascular endothelial growth factor (VEGF) genes have also been reported in Scz patients. Genes with known strong relationships with this disease include BDNF, catechol-O-methyltransferase (COMT), regulator of G-protein signaling 4 (RGS4), dystrobrevin-binding protein 1 (DTNBP1), neuregulin 1 (NRG1), Reelin (RELN), Selenium-binding protein 1 (SELENBP1), glutamic acid decarboxylase 67 (GAD 67), and disrupted in schizophrenia 1 (DISC1). The levels of dopamine, tyrosine hydroxylase (TH), serotonin or 5-hydroxytryptamine (5-HT) receptor 1A and B (5-HTR1A and 5-HTR1B), and 5-HT1B were significantly increased in Scz patients, while the levels of gamma-aminobutyric acid (GABA), 5-HT transporter (5-HTT), and 5-HT receptor 2A (5-HTR2A) were decreased. The increased levels of SELENBP1 and Glycogen synthase kinase 3 subunit α (GSK3α) genes in contrast with reduced levels of B-cell translocation gene 1 (BTG1), human leukocyte antigen DRB1 (HLA-DRB1), heterogeneous nuclear ribonucleoprotein A3 (HNRPA3), and serine/arginine-rich splicing factor 1 (SFRS1) genes have also been reported. This review covers various dysregulation of neurotransmitters and also highlights the strengths and weaknesses of studies attempting to identify candidate biomarkers.
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Affiliation(s)
- Alireza Mohammadi
- Neuroscience Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| | - Ehsan Rashidi
- Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Ghasem Amooeian
- Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
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21
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Agcaoglu O, Miller R, Damaraju E, Rashid B, Bustillo J, Cetin MS, Van Erp TGM, McEwen S, Preda A, Ford JM, Lim KO, Manoach DS, Mathalon DH, Potkin SG, Calhoun VD. Decreased hemispheric connectivity and decreased intra- and inter- hemisphere asymmetry of resting state functional network connectivity in schizophrenia. Brain Imaging Behav 2018; 12:615-630. [PMID: 28434159 PMCID: PMC5651208 DOI: 10.1007/s11682-017-9718-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Many studies have shown that schizophrenia patients have aberrant functional network connectivity (FNC) among brain regions, suggesting schizophrenia manifests with significantly diminished (in majority of the cases) connectivity. Schizophrenia is also associated with a lack of hemispheric lateralization. Hoptman et al. (2012) reported lower inter-hemispheric connectivity in schizophrenia patients compared to controls using voxel-mirrored homotopic connectivity. In this study, we merge these two points of views together using a group independent component analysis (gICA)-based approach to generate hemisphere-specific timecourses and calculate intra-hemisphere and inter-hemisphere FNC on a resting state fMRI dataset consisting of age- and gender-balanced 151 schizophrenia patients and 163 healthy controls. We analyzed the group differences between patients and healthy controls in each type of FNC measures along with age and gender effects. The results reveal that FNC in schizophrenia patients shows less hemispheric asymmetry compared to that of the healthy controls. We also found a decrease in connectivity in all FNC types such as intra-left (L_FNC), intra-right (R_FNC) and inter-hemisphere (Inter_FNC) in the schizophrenia patients relative to healthy controls, but general patterns of connectivity were preserved in patients. Analyses of age and gender effects yielded results similar to those reported in whole brain FNC studies.
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Affiliation(s)
- O Agcaoglu
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA.
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA.
| | - R Miller
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
| | - E Damaraju
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - B Rashid
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - J Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - M S Cetin
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
| | - T G M Van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - S McEwen
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - A Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - J M Ford
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - K O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - D S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - D H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - S G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - V D Calhoun
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
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22
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McNabb CB, Sundram F, Soosay I, Kydd RR, Russell BR. Increased sensorimotor network connectivity associated with clozapine eligibility in people with schizophrenia. Psychiatry Res Neuroimaging 2018; 275:36-42. [PMID: 29650266 DOI: 10.1016/j.pscychresns.2018.02.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 02/22/2018] [Accepted: 02/24/2018] [Indexed: 01/30/2023]
Abstract
Schizophrenia is a heterogeneous disorder that exhibits variable responsiveness to treatment between individuals. Here we conducted a resting-state functional magnetic resonance imaging (rs-fMRI) study to determine whether resistance to first-line antipsychotics is reflected in resting-state connectivity. rs-fMRI data were collected from 15 people who had failed to respond to first-line antipsychotics (clozapine-eligible) and 10 first-line treatment responders (FLR). Image pre-processing and analysis were performed using FMRIB's software library (FSL). Data was decomposed into spatial and temporal components using independent components analysis. Connectivity within each independent component was compared between groups using t-tests and the Bonferroni correction for multiple comparisons. Gender was added as a covariate. Clozapine-eligible individuals exhibited enhanced functional connectivity within the sensorimotor network compared with FLR. Those eligible for clozapine showed additional connectivity with the precuneus compared with FLR. No other comparisons reached statistical significance and no effect of gender was observed. These data reveal differences in functional connectivity between FLR and those eligible for clozapine and suggest that greater connectivity between the SMN and precuneus may be indicative of treatment resistance in people with schizophrenia.
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Affiliation(s)
| | - Frederick Sundram
- Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Ian Soosay
- Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Robert R Kydd
- Department of Psychological Medicine, University of Auckland, Auckland, New Zealand
| | - Bruce Roy Russell
- School of Pharmacy, University of Otago, PO Box 56, 9054 Dunedin, New Zealand.
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23
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Hallgrímsson HT, Cieslak M, Foschini L, Grafton ST, Singh AK. Spatial coherence of oriented white matter microstructure: Applications to white matter regions associated with genetic similarity. Neuroimage 2018; 172:390-403. [PMID: 29410205 DOI: 10.1016/j.neuroimage.2018.01.050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 12/31/2017] [Accepted: 01/19/2018] [Indexed: 11/26/2022] Open
Abstract
We present a method to discover differences between populations with respect to the spatial coherence of their oriented white matter microstructure in arbitrarily shaped white matter regions. This method is applied to diffusion MRI scans of a subset of the Human Connectome Project dataset: 57 pairs of monozygotic and 52 pairs of dizygotic twins. After controlling for morphological similarity between twins, we identify 3.7% of all white matter as being associated with genetic similarity (35.1 k voxels, p<10-4, false discovery rate 1.5%), 75% of which spatially clusters into twenty-two contiguous white matter regions. Furthermore, we show that the orientation similarity within these regions generalizes to a subset of 47 pairs of non-twin siblings, and show that these siblings are on average as similar as dizygotic twins. The regions are located in deep white matter including the superior longitudinal fasciculus, the optic radiations, the middle cerebellar peduncle, the corticospinal tract, and within the anterior temporal lobe, as well as the cerebellum, brain stem, and amygdalae. These results extend previous work using undirected fractional anisotrophy for measuring putative heritable influences in white matter. Our multidirectional extension better accounts for crossing fiber connections within voxels. This bottom up approach has at its basis a novel measurement of coherence within neighboring voxel dyads between subjects, and avoids some of the fundamental ambiguities encountered with tractographic approaches to white matter analysis that estimate global connectivity.
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Affiliation(s)
| | - Matthew Cieslak
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA
| | - Luca Foschini
- Department of Computer Science, University of California, Santa Barbara, CA 93106, USA
| | - Scott T Grafton
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA
| | - Ambuj K Singh
- Department of Computer Science, University of California, Santa Barbara, CA 93106, USA
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24
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McNabb CB, Tait RJ, McIlwain ME, Anderson VM, Suckling J, Kydd RR, Russell BR. Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia. Schizophr Res 2018; 195:160-167. [PMID: 29042073 DOI: 10.1016/j.schres.2017.10.015] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 09/25/2017] [Accepted: 10/09/2017] [Indexed: 12/21/2022]
Abstract
Schizophrenia may develop from disruptions in functional connectivity regulated by neurotransmitters such as dopamine and acetylcholine. The modulatory effects of these neurotransmitters might explain how antipsychotics attenuate symptoms of schizophrenia and account for the variable response to antipsychotics observed in clinical practice. Based on the putative mechanisms of antipsychotics and evidence of disrupted connectivity in schizophrenia, we hypothesised that functional network connectivity, as assessed using network-based statistics, would exhibit differences between treatment response subtypes of schizophrenia and healthy controls. Resting-state functional MRI data were obtained from 17 healthy controls as well as individuals with schizophrenia who responded well to first-line atypical antipsychotics (first-line responders; FLR, n=18), had failed at least two trials of antipsychotics but responded to clozapine (treatment-resistant schizophrenia; TRS, n=18), or failed at least two trials of antipsychotics and a trial of clozapine (ultra-treatment-resistant schizophrenia; UTRS, n=16). Data were pre-processed using the Advanced Normalization Toolkit and BrainWavelet Toolbox. Network connectivity was assessed using the Network-Based Statistics toolbox in Matlab. ANOVA revealed a significant difference in functional connectivity between groups that extended between cerebellar and parietal regions to the frontal cortex (p<0.05). Post-hoc t-tests revealed weaker network connectivity in individuals with UTRS compared with healthy controls but no other differences between groups. Results demonstrated distinct differences in functional connectivity between individuals with UTRS and healthy controls. Future work must determine whether these changes occur prior to the onset of treatment and if they can be used to predict resistance to antipsychotics during first-episode psychosis.
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Affiliation(s)
- Carolyn B McNabb
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Roger J Tait
- Department of Psychiatry, University of Cambridge, Cambridge and Peterborough Foundation NHS Trust, Herchel Smith Buidling for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
| | - Meghan E McIlwain
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - Valerie M Anderson
- School of Pharmacy, University of Auckland, 85 Park Road, Grafton, Auckland 1023, New Zealand
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge and Peterborough Foundation NHS Trust, Herchel Smith Buidling for Brain & Mind Sciences, Forvie Site, Robinson Way, Cambridge CB2 0SZ, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Downing Street, Cambridge CB2 3EB, United Kingdom
| | - Robert R Kydd
- Department of Psychological Medicine, University of Auckland, Auckland City Hospital, 2 Park Road, Grafton, Auckland 1023, New Zealand
| | - Bruce R Russell
- School of Pharmacy, University of Otago, PO Box 56, Dunedin 9054, New Zealand.
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25
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Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, Andreassen OA, Arango C, Banaj N, Bouix S, Bousman CA, Brouwer RM, Bruggemann J, Bustillo J, Cahn W, Calhoun V, Cannon D, Carr V, Catts S, Chen J, Chen JX, Chen X, Chiapponi C, Cho KK, Ciullo V, Corvin AS, Crespo-Facorro B, Cropley V, De Rossi P, Diaz-Caneja CM, Dickie EW, Ehrlich S, Fan FM, Faskowitz J, Fatouros-Bergman H, Flyckt L, Ford JM, Fouche JP, Fukunaga M, Gill M, Glahn DC, Gollub R, Goudzwaard ED, Guo H, Gur RE, Gur RC, Gurholt TP, Hashimoto R, Hatton SN, Henskens FA, Hibar DP, Hickie IB, Hong LE, Horacek J, Howells FM, Hulshoff Pol HE, Hyde CL, Isaev D, Jablensky A, Jansen PR, Janssen J, Jönsson EG, Jung LA, Kahn RS, Kikinis Z, Liu K, Klauser P, Knöchel C, Kubicki M, Lagopoulos J, Langen C, Lawrie S, Lenroot RK, Lim KO, Lopez-Jaramillo C, Lyall A, Magnotta V, Mandl RCW, Mathalon DH, McCarley RW, McCarthy-Jones S, McDonald C, McEwen S, McIntosh A, Melicher T, Mesholam-Gately RI, Michie PT, Mowry B, Mueller BA, Newell DT, O'Donnell P, Oertel-Knöchel V, Oestreich L, Paciga SA, Pantelis C, Pasternak O, Pearlson G, Pellicano GR, Pereira A, Pineda Zapata J, Piras F, Potkin SG, Preda A, Rasser PE, Roalf DR, Roiz R, Roos A, Rotenberg D, Satterthwaite TD, Savadjiev P, Schall U, Scott RJ, Seal ML, Seidman LJ, Shannon Weickert C, Whelan CD, Shenton ME, Kwon JS, Spalletta G, Spaniel F, Sprooten E, Stäblein M, Stein DJ, Sundram S, Tan Y, Tan S, Tang S, Temmingh HS, Westlye LT, Tønnesen S, Tordesillas-Gutierrez D, Doan NT, Vaidya J, van Haren NEM, Vargas CD, Vecchio D, Velakoulis D, Voineskos A, Voyvodic JQ, Wang Z, Wan P, Wei D, Weickert TW, Whalley H, White T, Whitford TJ, Wojcik JD, Xiang H, Xie Z, Yamamori H, Yang F, Yao N, Zhang G, Zhao J, van Erp TGM, Turner J, Thompson PM, Donohoe G. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 2018; 23:1261-1269. [PMID: 29038599 PMCID: PMC5984078 DOI: 10.1038/mp.2017.170] [Citation(s) in RCA: 439] [Impact Index Per Article: 73.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Revised: 05/02/2017] [Accepted: 06/07/2017] [Indexed: 12/15/2022]
Abstract
The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
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Affiliation(s)
- S Kelly
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA,Harvard Medical School, Boston, MA, USA,Imaging Genetics Center, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292, USA. E-mail:
| | - N Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - P Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - I Agartz
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - C Alloza
- University of Edinburgh, Edinburgh, UK
| | | | - C Arango
- Child and Adolescent Psychiatry Department, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - N Banaj
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - S Bouix
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - C A Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia,Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia,Department of General Practice, The University of Melbourne, Parkville, VIC, Australia,Swinburne University of Technology, Melbourne, VIC, Australia
| | - R M Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - J Bruggemann
- Neuroscience Research Australia and School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - J Bustillo
- University of New Mexico, Albuquerque, NM, USA
| | - W Cahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - V Calhoun
- The Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA,The Mind Research Network, Albuquerque, NM, USA
| | - D Cannon
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - V Carr
- Neuroscience Research Australia and School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - S Catts
- Discipline of Psychiatry, School of Medicine, University of Queensland, Herston, QLD, Australia
| | - J Chen
- Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
| | - J-x Chen
- Beijing Huilongguan Hospital, Beijing, China
| | - X Chen
- Worldwide Research and Development, Pfizer, Cambridge, MA, USA
| | | | - Kl K Cho
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - V Ciullo
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - A S Corvin
- Department of Psychiatry and Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland
| | - B Crespo-Facorro
- University Hospital Marqués de Valdecilla, IDIVAL, Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain,CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain
| | - V Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - P De Rossi
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy,Department NESMOS, Faculty of Medicine and Psychology, University ‘Sapienza’ of Rome, Rome, Italy,Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - C M Diaz-Caneja
- Child and Adolescent Psychiatry Department, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - E W Dickie
- Center for Addiction and Mental Health, Toronto, ON, Canada
| | - S Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden, Germany
| | - F-m Fan
- Beijing Huilongguan Hospital, Beijing, China
| | - J Faskowitz
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - H Fatouros-Bergman
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - L Flyckt
- University of New South Wales, School of Psychiatry, Sydney, NSW, Australia,The University of Queensland, Queensland Brain Institute and Centre for Advanced Imaging, Brisbane, QLD, Australia
| | - J M Ford
- University of California, VAMC, San Francisco, CA, USA
| | - J-P Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - M Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan
| | - M Gill
- Department of Psychiatry and Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland
| | - D C Glahn
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital and Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - R Gollub
- Harvard Medical School, Boston, MA, USA,Departments of Psychiatry and Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - E D Goudzwaard
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - H Guo
- Zhumadian Psychiatry Hospital, Henan Province, China
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - T P Gurholt
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - R Hashimoto
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - S N Hatton
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - F A Henskens
- School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, Australia,Health Behaviour Research Group, University of Newcastle, Callaghan, NSW, Australia,Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - D P Hibar
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - I B Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - L E Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - J Horacek
- National Institute of Mental Health, Klecany, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - F M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - H E Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C L Hyde
- Worldwide Research and Development, Pfizer, Cambridge, MA, USA
| | - D Isaev
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - A Jablensky
- University of Western Australia, Perth, WA, Australia
| | - P R Jansen
- Erasmus University Medical Center, Rotterdam, The Netherlands
| | - J Janssen
- Child and Adolescent Psychiatry Department, Hospital General Universitario Gregorio Marañón, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - E G Jönsson
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden
| | - L A Jung
- Laboratory for Neuroimaging, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University, Frankfurt/Main, Germany
| | - R S Kahn
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Z Kikinis
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - K Liu
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - P Klauser
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia,Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia,Department of Psychiatry, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - C Knöchel
- Laboratory for Neuroimaging, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University, Frankfurt/Main, Germany
| | - M Kubicki
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Lagopoulos
- Sunshine Coast Mind and Neuroscience Institute, University of the Sunshine Coast QLD, Australia, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - C Langen
- Erasmus University Medical Center, Rotterdam, The Netherlands
| | - S Lawrie
- University of Edinburgh, Edinburgh, UK
| | - R K Lenroot
- Neuroscience Research Australia and School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - K O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - C Lopez-Jaramillo
- Research Group in Psychiatry (GIPSI), Department of Psychiatry, Faculty of Medicine, Universidad de Antioquia, Mood Disorder Program, Hospital Universitario San Vicente Fundación, Medellín, Colombia
| | - A Lyall
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | - R C W Mandl
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - D H Mathalon
- University of California, VAMC, San Francisco, CA, USA
| | | | - S McCarthy-Jones
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - C McDonald
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - S McEwen
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - T Melicher
- Third Faculty of Medicine, Charles University, Prague, Czech Republic,The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - R I Mesholam-Gately
- Harvard Medical School and Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess, Medical Center, Boston, MA, USA
| | - P T Michie
- Hunter Medical Research Institute, Newcastle, NSW, Australia,The University of Newcastle, Newcastle, NSW, Australia,Schizophrenia Research Institute, Sydney, NSW, Australia
| | - B Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia and Queensland Centre for Mental Health Research, Brisbane and Queensland Centre for Mental Health Research, Brisbane, QLD, Australia
| | - B A Mueller
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - D T Newell
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - P O'Donnell
- Worldwide Research and Development, Pfizer, Cambridge, MA, USA
| | - V Oertel-Knöchel
- Laboratory for Neuroimaging, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University, Frankfurt/Main, Germany
| | - L Oestreich
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia and Queensland Centre for Mental Health Research, Brisbane and Queensland Centre for Mental Health Research, Brisbane, QLD, Australia
| | - S A Paciga
- Worldwide Research and Development, Pfizer, Cambridge, MA, USA
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia,Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia,Schizophrenia Research Institute, Sydney, NSW, Australia,Centre for Neural Engineering (CfNE), Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC, Australia
| | - O Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - G Pearlson
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital and Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - G R Pellicano
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - A Pereira
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | | | - F Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy,School of Biomedical Sciences, Faculty of Health, the University of Newcastle, Callaghan, NSW, Australia
| | - S G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - A Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - P E Rasser
- Hunter Medical Research Institute, Newcastle, NSW, Australia,Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - D R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - R Roiz
- University Hospital Marqués de Valdecilla, IDIVAL, Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain,CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain
| | - A Roos
- SU/UCT MRC Unit on Anxiety and Stress Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - D Rotenberg
- Center for Addiction and Mental Health, Toronto, ON, Canada
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - P Savadjiev
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - U Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia,Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - R J Scott
- Hunter Medical Research Institute, Newcastle, NSW, Australia,School of Biomedical Sciences, Faculty of Health, the University of Newcastle, Callaghan, NSW, Australia
| | - M L Seal
- Murdoch Childrens Research Institute, The Royal Children’s Hospital, Parkville, VIC, Australia
| | - L J Seidman
- Harvard Medical School, Boston, MA, USA,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA,Harvard Medical School and Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess, Medical Center, Boston, MA, USA
| | - C Shannon Weickert
- Schizophrenia Research Institute, Sydney, NSW, Australia,Neuroscience Research Australia, Sydney, NSW, Australia,School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - C D Whelan
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - M E Shenton
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA,VA Boston Healthcare System, Boston, MA, USA
| | - J S Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - G Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy,Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - F Spaniel
- National Institute of Mental Health, Klecany, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - E Sprooten
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital and Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - M Stäblein
- Laboratory for Neuroimaging, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe University, Frankfurt/Main, Germany
| | - D J Stein
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa,Department of Psychiatry and MRC Unit on Anxiety and Stress Disorders, University of Cape Town, Cape Town, South Africa
| | - S Sundram
- Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia,Department of Psychiatry, School of Clinical Sciences, Monash University and Monash Health, Clayton, VIC, Australia
| | - Y Tan
- Beijing Huilongguan Hospital, Beijing, China
| | - S Tan
- Beijing Huilongguan Hospital, Beijing, China
| | - S Tang
- Chongqing Three Gorges Central Hospital, Chongqing, China
| | - H S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - L T Westlye
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway,Department of Psychology, University of Oslo, Oslo, Norway
| | - S Tønnesen
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - D Tordesillas-Gutierrez
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain,Neuroimaging Unit, Technological Facilities, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
| | - N T Doan
- NORMENT, KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - J Vaidya
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - N E M van Haren
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - C D Vargas
- Research Group in Psychiatry (GIPSI), Department of Psychiatry, Faculty of Medicine, Universidad de Antioquia, Medellín, Colombia
| | - D Vecchio
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - D Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - A Voineskos
- Kimel Family Translational Imaging-Genetics Research Laboratory, Campbell Family Mental Health Research Institute, CAMH Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - J Q Voyvodic
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Z Wang
- Beijing Huilongguan Hospital, Beijing, China
| | - P Wan
- Zhumadian Psychiatry Hospital, Henan Province, China
| | - D Wei
- Luoyang Fifth People's Hospital, Henan Province, China
| | - T W Weickert
- Schizophrenia Research Institute, Sydney, NSW, Australia,Neuroscience Research Australia, Sydney, NSW, Australia,School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
| | - H Whalley
- University of Edinburgh, Edinburgh, UK
| | - T White
- Erasmus University Medical Center, Rotterdam, The Netherlands
| | - T J Whitford
- University of New South Wales, School of Psychiatry, Sydney, NSW, Australia
| | - J D Wojcik
- Harvard Medical School and Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess, Medical Center, Boston, MA, USA
| | - H Xiang
- Chongqing Three Gorges Central Hospital, Chongqing, China
| | - Z Xie
- Worldwide Research and Development, Pfizer, Cambridge, MA, USA
| | - H Yamamori
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - F Yang
- Beijing Huilongguan Hospital, Beijing, China
| | - N Yao
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - G Zhang
- Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore, MD, USA
| | - J Zhao
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland,School of Psychology, Shaanxi Normal University and Key Laboratory for Behavior and Cognitive Neuroscience of Shaanxi Province, Xi’an, Shaanxi, China
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - J Turner
- Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - P M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - G Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
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26
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Scholtens LH, van den Heuvel MP. Multimodal Connectomics in Psychiatry: Bridging Scales From Micro to Macro. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:767-776. [PMID: 29779726 DOI: 10.1016/j.bpsc.2018.03.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 02/28/2018] [Accepted: 03/16/2018] [Indexed: 01/21/2023]
Abstract
The human brain is a highly complex system, with a large variety of microscale cellular morphologies and macroscale global properties. Working at multiple scales, it forms an efficient system for processing and integration of multimodal information. Studies have repeatedly demonstrated strong associations between modalities of both microscales and macroscales of brain organization. These consistent observations point toward potential common organization principles where regions with a microscale architecture supportive of a larger computational load have more and stronger connections in the brain network on the macroscale. Conversely, disruptions observed on one organizational scale could modulate the other. First neuropsychiatric micro-macro comparisons in, among other conditions, Alzheimer's disease and schizophrenia, have, for example, shown overlapping alterations across both scales. We give an overview of recent findings on associations between microscale and macroscale organization observed in the healthy brain, followed by a summary of microscale and macroscale findings reported in the context of brain disorders. We conclude with suggestions for future multiscale connectome comparisons linking multiple scales and modalities of organization and suggest how such comparisons could contribute to a more complete fundamental understanding of brain organization and associated disease-related alterations.
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Affiliation(s)
- Lianne H Scholtens
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, VU Amsterdam, Amsterdam, The Netherlands
| | - Martijn P van den Heuvel
- Connectome Lab, Department of Complex Traits Genetics, Center for Neurogenomics and Cognitive Research, VU Amsterdam, Amsterdam, The Netherlands; Department of Clinical Genetics, VU University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands.
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27
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Lee J, Chon MW, Kim H, Rathi Y, Bouix S, Shenton ME, Kubicki M. Diagnostic value of structural and diffusion imaging measures in schizophrenia. NEUROIMAGE-CLINICAL 2018; 18:467-474. [PMID: 29876254 PMCID: PMC5987843 DOI: 10.1016/j.nicl.2018.02.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 02/03/2018] [Accepted: 02/05/2018] [Indexed: 12/24/2022]
Abstract
Objectives Many studies have attempted to discriminate patients with schizophrenia from healthy controls by machine learning using structural or functional MRI. We included both structural and diffusion MRI (dMRI) and performed random forest (RF) and support vector machine (SVM) in this study. Methods We evaluated the performance of classifying schizophrenia using RF method and SVM with 504 features (volume and/or fractional anisotropy and trace) from 184 brain regions. We enrolled 47 patients and 23 age- and sex-matched healthy controls and resampled our data into a balanced dataset using a Synthetic Minority Oversampling Technique method. We randomly permuted the classification of all participants as a patient or healthy control 100 times and ran the RF and SVM with leave one out cross validation for each permutation. We then compared the sensitivity and specificity of the original dataset and the permuted dataset. Results Classification using RF with 504 features showed a significantly higher rate of performance compared to classification by chance: sensitivity (87.6% vs. 47.0%) and specificity (95.9 vs. 48.4%) performed by RF, sensitivity (89.5% vs. 48.0%) and specificity (94.5% vs. 47.1%) performed by SVM. Conclusions Machine learning using RF and SVM with both volume and diffusion measures can discriminate patients with schizophrenia with a high degree of performance. Further replications are required.
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Affiliation(s)
- Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea; Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Myong-Wuk Chon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Harin Kim
- Department of psychiatry, Korean Armed Forces Capital Hospital, Bundang-gu, Republic of Korea
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Brockton Division, Brockton, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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28
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Sun Y, Chen Y, Collinson SL, Bezerianos A, Sim K. Reduced Hemispheric Asymmetry of Brain Anatomical Networks Is Linked to Schizophrenia: A Connectome Study. Cereb Cortex 2018; 27:602-615. [PMID: 26503264 DOI: 10.1093/cercor/bhv255] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Despite convergent evidence indicating a variety of regional abnormalities of hemispheric asymmetry in schizophrenia, patterns of wider neural network asymmetry remain to be determined. In this study, we investigated alterations in hemispheric white matter topology in schizophrenia and their association with clinical manifestations of the illness. Weighted hemispheric brain anatomical networks were constructed for each of 116 right-handed patients with schizophrenia and 66 matched healthy participants. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that although small-world properties were preserved in the hemispheric network, a significant hemispheric-independent deficit of global integration was found in schizophrenia. Furthermore, a significant group-by-hemisphere interaction was revealed in the characteristic path length and global efficiency, attributing to significantly reduced hemispheric asymmetry of global integration in patients compared with healthy controls. Specifically, we found reduced asymmetric nodal efficiency in several frontal regions and the hippocampus. Finally, the abnormal hemispheric asymmetry of brain anatomical network topology was associated with clinical features (duration of illness and psychotic psychopathology) in patients. Our findings provide new insights into lateralized nature of hemispheric dysconnectivity and highlight the potential for using brain network measures of hemispheric asymmetry as neural biomarkers for schizophrenia and its clinical features.
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Affiliation(s)
- Yu Sun
- Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Sciences
| | - Yu Chen
- Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Sciences
| | - Simon L Collinson
- Department of Psychology, National University of Singapore, Singapore
| | | | - Kang Sim
- Department of General Psychiatry.,Department of Research, Institute of Mental Health (IMH), Singapore
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29
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Fullerton JM, Klauser P, Lenroot RK, Shaw AD, Overs B, Heath A, Cairns MJ, Atkins J, Scott R, Schofield PR, Weickert CS, Pantelis C, Fornito A, Whitford TJ, Weickert TW, Zalesky A. Differential effect of disease-associated ST8SIA2 haplotype on cerebral white matter diffusion properties in schizophrenia and healthy controls. Transl Psychiatry 2018; 8:21. [PMID: 29353880 PMCID: PMC5802561 DOI: 10.1038/s41398-017-0052-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 09/23/2017] [Indexed: 11/09/2022] Open
Abstract
Brain white matter abnormalities are evident in individuals with schizophrenia, and also their first-degree relatives, suggesting that some alterations may relate to underlying genetic risk. The ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 2 (ST8SIA2) gene, which encodes the alpha-2,8-sialyltransferase 8B enzyme that aids neuronal migration and synaptic plasticity, was previously implicated as a schizophrenia susceptibility gene. This study examined the extent to which specific haplotypes in ST8SIA2 influence white matter microstructure using diffusion-weighted imaging of individuals with schizophrenia (n = 281) and healthy controls (n = 172), recruited across five Australian sites. Interactions between diagnostic status and the number of haplotype copies (0 or ≥1) were tested across all white matter voxels with cluster-based statistics. Fractional anisotropy (FA) in the right parietal lobe was found to show a significant interaction between diagnosis and ST8SIA2 protective haplotype (p < 0.05, family-wise error rate (FWER) cluster-corrected). The protective haplotype was associated with increased FA in controls, but this effect was reversed in people with schizophrenia. White matter fiber tracking revealed that the region-of-interest was traversed by portions of the superior longitudinal fasciculus, corona radiata, and posterior limb of internal capsule. Post hoc analysis revealed that reduced FA in this regional juncture correlated with reduced IQ in people with schizophrenia. The ST8SIA2 risk haplotype copy number did not show any differential effects on white matter. This study provides a link between a common disease-associated haplotype and specific changes in white matter microstructure, which may relate to resilience or risk for mental illness, providing further compelling evidence for involvement of ST8SIA2 in the pathophysiology of schizophrenia.
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Affiliation(s)
- Janice M. Fullerton
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0004 4902 0432grid.1005.4School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia
| | - Paul Klauser
- 0000 0004 1936 7857grid.1002.3Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC Australia ,0000 0001 2179 088Xgrid.1008.9Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC Australia
| | - Rhoshel K. Lenroot
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia ,0000 0004 4902 0432grid.1005.4School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW Australia
| | - Alex D. Shaw
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia
| | - Bronwyn Overs
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia
| | - Anna Heath
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia
| | - Murray J. Cairns
- 0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia ,0000 0000 8831 109Xgrid.266842.cSchool of Biomedical Sciences, University of Newcastle, Newcastle, NSW Australia
| | - Joshua Atkins
- 0000 0000 8831 109Xgrid.266842.cSchool of Biomedical Sciences, University of Newcastle, Newcastle, NSW Australia
| | - Rodney Scott
- 0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia ,0000 0000 8831 109Xgrid.266842.cSchool of Biomedical Sciences, University of Newcastle, Newcastle, NSW Australia
| | | | - Peter R. Schofield
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0004 4902 0432grid.1005.4School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia
| | - Cyndi Shannon Weickert
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia ,0000 0004 4902 0432grid.1005.4School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW Australia
| | - Christos Pantelis
- 0000 0001 2179 088Xgrid.1008.9Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC Australia
| | - Alex Fornito
- 0000 0004 1936 7857grid.1002.3Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC Australia
| | - Thomas J. Whitford
- 0000 0004 4902 0432grid.1005.4School of Psychology, Faculty of Science, University of New South Wales, Sydney, NSW Australia
| | - Thomas W. Weickert
- 0000 0000 8900 8842grid.250407.4Neuroscience Research Australia, Randwick, Sydney, NSW Australia ,0000 0000 8696 2171grid.419558.4Schizophrenia Research Institute, Sydney, NSW Australia ,0000 0004 4902 0432grid.1005.4School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW Australia
| | - Andrew Zalesky
- 0000 0001 2179 088Xgrid.1008.9Melbourne Neuropsychiatry Centre, The University of Melbourne and Melbourne Health, Carlton South, VIC Australia
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30
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Krakauer K, Nordentoft M, Glenthøj BY, Raghava JM, Nordholm D, Randers L, Glenthøj LB, Ebdrup BH, Rostrup E. White matter maturation during 12 months in individuals at ultra-high-risk for psychosis. Acta Psychiatr Scand 2018; 137:65-78. [PMID: 29143980 DOI: 10.1111/acps.12835] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/25/2017] [Indexed: 12/12/2022]
Abstract
OBJECTIVE The neurodevelopmental hypothesis of psychosis suggests that disrupted white matter (WM) maturation underlies disease onset. In this longitudinal study, we investigated WM connectivity and compared WM changes between individuals at ultra-high-risk for psychosis (UHR) and healthy controls (HCs). METHOD Thirty UHR individuals and 23 HCs underwent MR diffusion tensor imaging before and after 12 months of non-manualized standard care. Positive and negative symptoms and level of functioning were assessed. Tract-based spatial statistics were employed. RESULTS During 12 months, none of the UHR individuals transitioned to psychosis. Both UHR individuals and HCs increased significantly in fractional anisotropy (FA). UHR individuals showed significant FA increases predominantly in the left superior longitudinal fasciculus (SLF) (P = 0.01), and HCs showed significant FA increases in the left uncinate fasciculus (P = 0.03). Within UHR individuals, a significant positive correlation between FA change and age was observed predominantly in the left SLF (P = 0.02). Within HCs, no significant correlation between FA change and age was observed. No significant correlations between baseline FA and clinical outcomes were observed; however, FA changes were significantly positively correlated to changes in negative symptoms (P = 0.04). CONCLUSION As normal brain maturation occurs in a posterior to frontal direction, our findings could suggest disturbed WM maturation in UHR individuals.
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Affiliation(s)
- K Krakauer
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark.,Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark.,Functional Imaging Unit, FIUNIT, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark
| | - M Nordentoft
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark.,Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - B Y Glenthøj
- Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark.,Centre for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - J M Raghava
- Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark.,Functional Imaging Unit, FIUNIT, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.,Centre for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - D Nordholm
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark.,Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - L Randers
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark.,Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - L B Glenthøj
- Mental Health Centre Copenhagen, Copenhagen University Hospital, Hellerup, Denmark.,Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - B H Ebdrup
- Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark.,Centre for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
| | - E Rostrup
- Functional Imaging Unit, FIUNIT, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.,Mental Health Centre Glostrup, Copenhagen University Hospital, Glostrup, Denmark
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31
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Shahab S, Stefanik L, Foussias G, Lai MC, Anderson KK, Voineskos AN. Sex and Diffusion Tensor Imaging of White Matter in Schizophrenia: A Systematic Review Plus Meta-analysis of the Corpus Callosum. Schizophr Bull 2018; 44:203-221. [PMID: 28449132 PMCID: PMC5767963 DOI: 10.1093/schbul/sbx049] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Sex is considered an understudied variable in health research. Schizophrenia is a brain disorder with known sex differences in epidemiology and clinical presentation. We systematically reviewed the literature for sex-based differences of diffusion properties of white matter tracts in schizophrenia. We then conducted a meta-analysis examining sex-based differences in the genu and splenium of the corpus callosum in schizophrenia. Medline and Embase were searched to identify relevant papers. Studies fulfilling the following criteria were included: (1) included individuals with a diagnosis of schizophrenia, (2) included a control group of healthy individuals, (3) included both sexes in the patient and the control groups, (4) used diffusion tensor imaging, and (5) involved analyzing metrics of white matter microstructural integrity. Fractional anisotropy (FA) was used as the measure of interest in the meta-analysis. Of 730 studies reviewed, 75 met the inclusion criteria. Most showed no effect of sex, however, those that did found either that females have lower FA than males, or that the effect of disease in females is larger than that in males. The findings of the meta-analysis in the corpus callosum supported this result. There is a recognized need for studies on schizophrenia with a sufficient sample of female patients. Lack of power undermines the ability to detect sex-based differences. Understanding the sex-specific impact of illness on neural circuits may help inform development of new treatments, and improvement of existing interventions.
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Affiliation(s)
- Saba Shahab
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada,Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada
| | - Laura Stefanik
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada,Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - George Foussias
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada,Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Meng-Chuan Lai
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada,Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada,Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK,Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Kelly K Anderson
- Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada,Department of Epidemiology & Biostatistics and Psychiatry, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, Canada
| | - Aristotle N Voineskos
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, ON, Canada,Centre for Addiction and Mental Health and Slaight Family Centre for Youth in Transition, Toronto, ON, Canada,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada,Department of Psychiatry, University of Toronto, Toronto, ON, Canada,To whom correspondence should be addressed; 250 College Street, Toronto, ON M5T 1R8, Canada; tel: 416-535-8501 ext. 33977, fax: 416-260-4162, e-mail:
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Correlation of reduced social communicational and interactional skills with regional grey matter volumes in schizophrenia patients. Acta Neuropsychiatr 2017; 29:374-381. [PMID: 28393745 DOI: 10.1017/neu.2017.9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Recent studies have detected similarities between autism spectrum disorder and schizophrenia. We investigated structural abnormalities associated with autistic-like traits in patients with schizophrenia by voxel-based morphometry. METHODS Patients with schizophrenia and healthy subjects were evaluated by the adult version of the social responsiveness scale (SRS-A), which is sensitive to autistic traits and symptoms even under subthreshold conditions, and magnetic resonance imaging. RESULTS There were significant decreases in the anterior cingulate cortex, bilateral hippocampi, cerebellums, and right insula of patients with schizophrenia, compared with healthy subjects. We found significant negative correlations of the social communication and interaction (SCI) score, a subscale of SRS-A, with grey matter volume in the left posterior superior temporal region of schizophrenia patients. When subscales of SCI were examined separately in schizophrenic patients, negative correlations were observed between the social cognition score and the volumes of the left posterior superior temporal region, and between social motivation and the posterior cingulate cortex. CONCLUSION We found significant negative correlation between the SCI score and the grey matter volume in the left posterior superior temporal region of schizophrenia patients. This area was the region affected in previous studies of autistic spectrum disorders. Further, this area was associated with the theory of mind. Schizophrenia patients not necessarily show the impairment of SCI, nor this correlated region was not always the point with schizophrenia-specific change. However, we reveal the relationship between the left posterior superior temporal gyrus and the severity of the SCI in schizophrenia by using with SRS-A.
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Kanaan RA, Picchioni MM, McDonald C, Shergill SS, McGuire PK. White matter deficits in schizophrenia are global and don't progress with age. Aust N Z J Psychiatry 2017; 51:1020-1031. [PMID: 28382844 PMCID: PMC5624299 DOI: 10.1177/0004867417700729] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Diffusion tensor imaging has revealed differences in all examined white matter tracts in schizophrenia, with a range of explanations for why this may be. The distribution and timing of differences may help explain their origin; however, results are usually dependent on the analytical method. We therefore sought to examine the extent of differences and their relationship with age using two different methods. METHODS A combined voxel-based whole-brain study and a tract-based spatial-statistics study of 104 patients with schizophrenia and 200 matched healthy controls, aged between 17 and 63 years. RESULTS Fractional anisotropy was reduced throughout the brain in both analyses. The relationship of fractional anisotropy with age differed between patients and controls, with controls showing the gentle fractional anisotropy decline widely noted but patients showing an essentially flat relationship: younger patients had lower fractional anisotropy than controls, but the difference disappeared with age. Mean diffusivity was widely increased in patients. CONCLUSION Reduction in fractional anisotropy and increase in mean diffusivity would be consistent with global disruption in myelination; the relationship with age would suggest this is present already at the onset of their illness, but does not progress.
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Affiliation(s)
- Richard A Kanaan
- Department of Psychiatry, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Marco M Picchioni
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- St Andrew’s Academic Department and King’s College London, Northampton, UK
| | - Colm McDonald
- National University of Ireland (NUI), Galway, Ireland
| | - Sukhwinder S Shergill
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Philip K McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
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A probabilistic atlas of fiber crossings for variability reduction of anisotropy measures. Brain Struct Funct 2017; 223:635-651. [PMID: 28905121 DOI: 10.1007/s00429-017-1508-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Accepted: 08/31/2017] [Indexed: 12/13/2022]
Abstract
Diffusion imaging enables assessment of human brain white matter (WM) in vivo. WM microstructural integrity is routinely quantified via fractional anisotropy (FA). However, FA is also influenced by the number of differentially oriented fiber populations per voxel. To date, the precise statistical relationship between FA and fiber populations has not been characterized, complicating microstructural integrity assessment. Here, we used 630 state-of-the-art diffusion datasets from the Human Connectome Project, which allowed us to infer the number of fiber populations per voxel in a model-free fashion. Beyond the known impact on mean FA, variance of anisotropy distributions was drastically impacted, not only for FA, but also the more recent anisotropy indices generalized FA and multidimensional anisotropy. To ameliorate this bias, we introduce a probabilistic WM atlas delineating the number of distinctly oriented fiber populations per voxel. Our atlas shows that the majority of WM voxels features two differentially directed fiber populations (44.7%) rather than unidirectional fibers (32.9%) and identified WM regions with high numbers of crossing fibers, referred to as crossing pockets. Compartmentalizing anisotropy drastically reduced variance in group comparisons ranging from the whole brain to a few voxels in a single slice. In summary, we demonstrate a systematic effect of intra-voxel diffusion inhomogeneity on anisotropy. Moreover, we introduce a potential solution: The provided probabilistic WM atlas can easily be used with any given diffusion dataset to enhance the statistical robustness of anisotropy measures and increase their neurobiological utility.
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Fornix Structural Connectivity and Allostatic Load: Empirical Evidence From Schizophrenia Patients and Healthy Controls. Psychosom Med 2017; 79:770-776. [PMID: 28498274 PMCID: PMC5573616 DOI: 10.1097/psy.0000000000000487] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The fornix is a white matter tract carrying the fibers connecting the hippocampus and the hypothalamus, two essential stress-regulatory structures of the brain. We tested the hypothesis that allostatic load (AL), derived from a battery of peripheral biomarkers indexing the cumulative effects of stress, is associated with abnormalities in brain white matter microstructure, especially the fornix, and that higher AL may help explain the white matter abnormalities in schizophrenia. METHODS Using 13 predefined biomarkers, we tested AL in 44 schizophrenic patients and 33 healthy controls. Diffusion tensor imaging was used to obtain fractional anisotropy (FA) values of the fornix and other white matter tracts. RESULTS AL scores were significantly elevated in patients compared with controls (F(3,77) = 7.87, p = .006). AL was significantly and inversely correlated with FA of fornix in both controls (r = -.58, p = .001) and patients (r = -.36, p = .023). Several nominally significant (p < .05 but did not survive Bonferroni correction for multiple comparison) correlations were also observed between AL and FA of other white matter tracts in schizophrenic patients. However, the fornix was the only tract exhibiting a correlation with AL in both groups. CONCLUSIONS These results provide initial evidence that allostatic processes are linked to fornix microstructure in clinical participants.
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Quantitative assessment of optic nerve in patients with Leber’s hereditary optic neuropathy using reduced field-of-view diffusion tensor imaging. Eur J Radiol 2017; 93:24-29. [DOI: 10.1016/j.ejrad.2017.05.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Accepted: 05/21/2017] [Indexed: 11/22/2022]
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Bopp MHA, Zöllner R, Jansen A, Dietsche B, Krug A, Kircher TTJ. White matter integrity and symptom dimensions of schizophrenia: A diffusion tensor imaging study. Schizophr Res 2017; 184:59-68. [PMID: 28012640 DOI: 10.1016/j.schres.2016.11.045] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 11/27/2016] [Accepted: 11/28/2016] [Indexed: 01/15/2023]
Abstract
Impaired fiber bundle connectivity between brain regions is a key neuropathological finding in schizophrenia. Symptom dimensions in schizophrenia can be clustered into factor models. Single syndromes have been related to grey and white matter brain structure alterations. We associated all core syndromes of schizophrenia in a single patient group with changes in white matter integrity. Diffusion weighted images (3T MRI) and SAPS/SANS scores were measured in 26 male patients and 26 healthy controls. First, group differences in fractional anisotropy (FA) were calculated with TBSS. Second, core symptom dimensions of schizophrenia were correlated with FA within these altered tracts. We found differences between groups in nine white matter tracts. Hallucinations were positively correlated with FA in the left uncinate fasciculus and left corticospinal tract. Ego-disturbances (passivity phenomena) showed a positive correlation with FA in the right anterior thalamic radiation. Positive formal thought disorders (FTD) corresponded negatively with FA in the right cingulum bundle. Negative symptoms were positively associated with the right anterior thalamic radiation and negatively with the right ventral cingulum bundle. For the first time, we analyzed the whole range of psychopathological factors in one schizophrenia patient group. We could validate our novel results for positive FTD and passivity phenomena by replicating findings for hallucinations and negative symptoms. Only those brain circuits which are most vulnerable at a given time during neurodevelopment are affected by a particular pathological impact (genetic, environmental). This scenario could explain the predominance of particular psychopathological syndromes related to specific white matter anomalies.
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Affiliation(s)
- Miriam H A Bopp
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany; Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; International Clinical Research Center, St. Anne's University Hospital, Pekarska 53, 65691 Brno, Czech Republic.
| | - Rebecca Zöllner
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany; Core Facility Brain Imaging, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany
| | - Bruno Dietsche
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany
| | - Tilo T J Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf-Bultmann-Strasse 8, 35039 Marburg, Germany
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Willi TS, Barr AM, Gicas K, Lang DJ, Vila-Rodriguez F, Su W, Thornton AE, Leonova O, Giesbrecht CJ, Procyshyn RM, Rauscher A, MacEwan WG, Honer WG, Panenka WJ. Characterization of white matter integrity deficits in cocaine-dependent individuals with substance-induced psychosis compared with non-psychotic cocaine users. Addict Biol 2017; 22:873-881. [PMID: 26833821 DOI: 10.1111/adb.12363] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Revised: 11/10/2015] [Accepted: 12/11/2015] [Indexed: 01/19/2023]
Abstract
With sufficient drug exposure, some individuals develop transient psychotic symptoms referred to as 'substance-induced psychosis' (SIP), which closely resemble the symptoms observed in schizophrenia spectrum disorders. The comparability in psychotic presentation between SIP and the schizophrenias suggests that similar underlying neural deficits may contribute to the emergence of psychosis across these disorders. Only a small number of studies have investigated structural alterations in SIP, and all have been limited to volumetric imaging methods, with none controlling for the effects of chronic drug exposure. To investigate white matter abnormalities associated with SIP, diffusion tensor imaging was employed in a group of individuals with cocaine-associated psychosis (CAP; n = 24) and a cocaine-dependent non-psychotic (CDN) group (n = 43). Tract-based spatial statistics was used to investigate group differences in white matter diffusion parameters. The CAP group showed significantly lower fractional anisotropy values than the CDN group (p < 0.05) in voxels within white matter tracts of fronto-temporal, fronto-thalamic and interhemispheric pathways. The greatest differences in white matter integrity were present in the corpus callosum, corona radiata, bilateral superior longitudinal fasciculi and bilateral inferior longitudinal fasciculi. Additionally, the CAP group had voxels of significantly higher radial diffusivity in a subset of the previously mentioned pathways. These results are the first description of white matter integrity abnormalities in a SIP sample and indicate that differences in these pathways may be a shared factor in the expression of different forms of psychosis.
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Affiliation(s)
- Taylor S. Willi
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | - Alasdair M. Barr
- Department of Pharmacology; University of British Columbia; Vancouver Canada
| | - Kristina Gicas
- Department of Psychology; Simon Fraser University; Burnaby Canada
| | - Donna J. Lang
- Department of Radiology; University of British Columbia; Vancouver Canada
| | | | - Wayne Su
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | | | - Olga Leonova
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | | | - Ric M. Procyshyn
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | - Alexander Rauscher
- Department of Radiology; University of British Columbia; Vancouver Canada
| | - William G. MacEwan
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | - William G. Honer
- Department of Psychiatry; University of British Columbia; Vancouver Canada
| | - William J. Panenka
- Department of Psychiatry; University of British Columbia; Vancouver Canada
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Romme IAC, de Reus MA, Ophoff RA, Kahn RS, van den Heuvel MP. Connectome Disconnectivity and Cortical Gene Expression in Patients With Schizophrenia. Biol Psychiatry 2017; 81:495-502. [PMID: 27720199 DOI: 10.1016/j.biopsych.2016.07.012] [Citation(s) in RCA: 134] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 07/16/2016] [Accepted: 07/18/2016] [Indexed: 12/13/2022]
Abstract
BACKGROUND Genome-wide association studies have identified several common risk loci for schizophrenia (SCZ). In parallel, neuroimaging studies have shown consistent findings of widespread white matter disconnectivity in patients with SCZ. METHODS We examined the role of genes in brain connectivity in patients with SCZ by combining transcriptional profiles of 43 SCZ risk genes identified by the recent genome-wide association study of the Schizophrenia Working Group of the Psychiatric Genomics Consortium with data on macroscale connectivity reductions in patients with SCZ. Expression profiles of 43 Psychiatric Genomics Consortium SCZ risk genes were extracted from the Allen Human Brain Atlas, and their average profile across the cortex was correlated to the pattern of cortical disconnectivity as derived from diffusion-weighted magnetic resonance imaging data of patients with SCZ (n = 48) and matched healthy controls (n = 43). RESULTS The expression profile of SCZ risk genes across cortical regions was significantly correlated with the regional macroscale disconnectivity (r = .588; p = .017). In addition, effects were found to be potentially specific to SCZ, with transcriptional profiles not related to cortical disconnectivity in patients with bipolar I disorder (diffusion-weighted magnetic resonance imaging data; 216 patients, 144 controls). Further examination of correlations across all 20,737 genes present in the Allen Human Brain Atlas showed the set of top 100 strongest correlating genes to display significant enrichment for the disorder, potentially identifying new genes involved in the pathophysiology of SCZ. CONCLUSIONS Our results suggest that under disease conditions, cortical areas with pronounced expression of risk genes implicated in SCZ form central areas for white matter disconnectivity.
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Affiliation(s)
- Ingrid A C Romme
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marcel A de Reus
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Roel A Ophoff
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands; Center for Neurobehavioral Genetics and Department of Human Genetics , University of California Los Angeles, Los Angeles, California
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Martijn P van den Heuvel
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands.
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Klauser P, Baker ST, Cropley VL, Bousman C, Fornito A, Cocchi L, Fullerton JM, Rasser P, Schall U, Henskens F, Michie PT, Loughland C, Catts SV, Mowry B, Weickert TW, Shannon Weickert C, Carr V, Lenroot R, Pantelis C, Zalesky A. White Matter Disruptions in Schizophrenia Are Spatially Widespread and Topologically Converge on Brain Network Hubs. Schizophr Bull 2017; 43:425-435. [PMID: 27535082 PMCID: PMC5605265 DOI: 10.1093/schbul/sbw100] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.
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Affiliation(s)
- Paul Klauser
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia;,Lausanne University Hospital, Department of Psychiatry, Prilly, Switzerland
| | - Simon T. Baker
- Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Vanessa L. Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
| | - Chad Bousman
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Alex Fornito
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Luca Cocchi
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Janice M. Fullerton
- Neuroscience Research Australia, Randwick, New South Wales, Australia;,School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Paul Rasser
- Centre for Brain and Mental Health Research, University of Newcastle, Waratah, New South Wales, Australia;,Hunter Medical Research Institute, Newcastle, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research, University of Newcastle, Waratah, New South Wales, Australia;,Hunter Medical Research Institute, Newcastle, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia
| | - Frans Henskens
- School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, New South Wales, Australia
| | - Patricia T. Michie
- Centre for Brain and Mental Health Research, University of Newcastle, Waratah, New South Wales, Australia;,Hunter Medical Research Institute, Newcastle, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia;,School of Psychology, University of Newcastle, Callaghan, New South Wales, Australia
| | - Carmel Loughland
- Neuroscience Research Australia, Randwick, New South Wales, Australia;,Faculty of Health and Medicine, University of Newcastle, Callaghan, New South Wales, Australia
| | - Stanley V. Catts
- School of Medicine, The University of Queensland, Brisbane, Qeensland, Australia
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia;,Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Thomas W. Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Neuroscience Research Australia, Randwick, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia;,School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Cynthia Shannon Weickert
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Neuroscience Research Australia, Randwick, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia;,School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Vaughan Carr
- Schizophrenia Research Institute, Randwick, New South Wales, Australia;,School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia;,Department of Psychiatry, Monash University, Clayton, Victoria, Australia
| | - Rhoshel Lenroot
- Neuroscience Research Australia, Randwick, New South Wales, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia;,School of Psychiatry, University of New South Wales, Sydney, New South Wales, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia;,Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia;,Schizophrenia Research Institute, Randwick, New South Wales, Australia;,Centre for Neural Engineering, Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
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Godwin D, Ji A, Kandala S, Mamah D. Functional Connectivity of Cognitive Brain Networks in Schizophrenia during a Working Memory Task. Front Psychiatry 2017; 8:294. [PMID: 29312020 PMCID: PMC5743938 DOI: 10.3389/fpsyt.2017.00294] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2017] [Accepted: 12/11/2017] [Indexed: 11/21/2022] Open
Abstract
Task-based connectivity studies facilitate the understanding of how the brain functions during cognition, which is commonly impaired in schizophrenia (SZ). Our aim was to investigate functional connectivity during a working memory task in SZ. We hypothesized that the task-negative (default mode) network and the cognitive control (frontoparietal) network would show dysconnectivity. Twenty-five SZ patient and 31 healthy control scans were collected using the customized 3T Siemens Skyra MRI scanner, previously used to collect data for the Human Connectome Project. Blood oxygen level dependent signal during the 0-back and 2-back conditions were extracted within a network-based parcelation scheme. Average functional connectivity was assessed within five brain networks: frontoparietal (FPN), default mode (DMN), cingulo-opercular (CON), dorsal attention (DAN), and ventral attention network; as well as between the DMN or FPN and other networks. For within-FPN connectivity, there was a significant interaction between n-back condition and group (p = 0.015), with decreased connectivity at 0-back in SZ subjects compared to controls. FPN-to-DMN connectivity also showed a significant condition × group effect (p = 0.003), with decreased connectivity at 0-back in SZ. Across groups, connectivity within the CON and DAN were increased during the 2-back condition, while DMN connectivity with either CON or DAN were decreased during the 2-back condition. Our findings support the role of the FPN, CON, and DAN in working memory and indicate that the pattern of FPN functional connectivity differs between SZ patients and control subjects during the course of a working memory task.
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Affiliation(s)
- Douglass Godwin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Andrew Ji
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Sridhar Kandala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Daniel Mamah
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
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Lee JS, Kim CY, Joo YH, Newell D, Bouix S, Shenton ME, Kubicki M. Increased diffusivity in gray matter in recent onset schizophrenia is associated with clinical symptoms and social cognition. Schizophr Res 2016; 176:144-150. [PMID: 27554199 PMCID: PMC5392041 DOI: 10.1016/j.schres.2016.08.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 08/09/2016] [Accepted: 08/11/2016] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Diffusion weighted MRI (dMRI) is a method sensitive to pathological changes affecting tissue microstructure. Most dMRI studies in schizophrenia, however, have focused solely on white matter. There is a possibility, however, that subtle changes in diffusivity exist in gray matter (GM). Accordingly, we investigated diffusivity in GM in patients with recent onset schizophrenia. METHODS We enrolled 45 patients and 21 age and sex-matched healthy controls. All subjects were evaluated using the short form of the Wechsler Adult Intelligence Scale, the Positive and Negative Syndrome Scale (PANSS), and the video based social cognition scale. DMRI and T1W images were acquired on a 3 Tesla magnet, and mean Fractional Anisotropy (FA), Trace (TR) and volume were calculated for each of the 68 cortical GM Regions of Interest parcellated using FreeSurfer. RESULTS There was no significant difference of FA and GM volume between groups after Bonferroni correction. For the dMRI measures, however, patients evinced increased TR in the left bank of the superior temporal sulcus, the right inferior parietal, the right inferior temporal, and the right middle temporal gyri. In addition, higher TR in the right middle temporal gyrus and the right inferior temporal gyrus, respectively, was associated with decreased social function and higher PANSS score in patients with schizophrenia. CONCLUSION This study demonstrates high sensitivity of dMRI to subtle pathology in GM in recent onset schizophrenia, as well as an association between increased diffusivity in temporal GM regions and abnormalities in social cognition and exacerbation of psychiatric symptoms.
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Affiliation(s)
- Jung Sun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea; Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Chang-Yoon Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Yeon Ho Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Dominick Newell
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Brockton Division, Brockton, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Drakesmith M, Dutt A, Fonville L, Zammit S, Reichenberg A, Evans CJ, McGuire P, Lewis G, Jones DK, David AS. Volumetric, relaxometric and diffusometric correlates of psychotic experiences in a non-clinical sample of young adults. Neuroimage Clin 2016; 12:550-558. [PMID: 27689019 PMCID: PMC5031471 DOI: 10.1016/j.nicl.2016.09.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 09/01/2016] [Accepted: 09/02/2016] [Indexed: 12/20/2022]
Abstract
BACKGROUND Grey matter (GM) abnormalities are robust features of schizophrenia and of people at ultra high-risk for psychosis. However the extent to which neuroanatomical alterations are evident in non-clinical subjects with isolated psychotic experiences is less clear. METHODS Individuals (mean age 20 years) with (n = 123) or without (n = 125) psychotic experiences (PEs) were identified from a population-based cohort. All underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI, to characterise GM macrostructure, microstructure and myelination respectively. Differences in quantitative GM structure were assessed using voxel-based morphometry (VBM). Binary and ordinal models of PEs were tested. Correlations between socioeconomic and other risk factors for psychosis with cortical GM measures were also computed. RESULTS GM volume in the left supra-marginal gyrus was reduced in individuals with PEs relative to those with no PEs. The greater the severity of PEs, the greater the reduction in T1 relaxation rate (R1) across left temporoparietal and right pre-frontal cortices. In these regions, R1 was positively correlated with maternal education and inversely correlated with general psychopathology. CONCLUSIONS PEs in non-clinical subjects were associated with regional reductions in grey-matter volume reduction and T1 relaxation rate. The alterations in T1 relaxation rate were also linked to the level of general psychopathology. Follow up of these subjects should clarify whether these alterations predict the later development of an ultra high-risk state or a psychotic disorder.
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Affiliation(s)
- Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Manidy Road, Cardiff CF24 4HQ, UK
- Neuroscience and Mental Health Research Institute (NMHRI), School of Medicine, Cardiff University, Maindy Road, Cardiff CF24 4HQ, UK
| | - Anirban Dutt
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, DeCrespigny Park, London SE5 8AF, UK
| | - Leon Fonville
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, DeCrespigny Park, London SE5 8AF, UK
| | - Stanley Zammit
- Neuroscience and Mental Health Research Institute (NMHRI), School of Medicine, Cardiff University, Maindy Road, Cardiff CF24 4HQ, UK
- Centre for Academic Mental Health, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - Abraham Reichenberg
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, DeCrespigny Park, London SE5 8AF, UK
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai Hospital, 1425 Madison Avenue, New York, NY 10029, USA
| | - C. John Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Manidy Road, Cardiff CF24 4HQ, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, DeCrespigny Park, London SE5 8AF, UK
| | - Glyn Lewis
- Division of Psychiatry, Faculty of Brain Sciences, University College London, Charles Bell House, 67–73 Riding House Street, London W1W 7EJ, UK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Manidy Road, Cardiff CF24 4HQ, UK
- Neuroscience and Mental Health Research Institute (NMHRI), School of Medicine, Cardiff University, Maindy Road, Cardiff CF24 4HQ, UK
| | - Anthony S. David
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, DeCrespigny Park, London SE5 8AF, UK
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van den Heuvel MP, Scholtens LH, de Reus MA, Kahn RS. Associated Microscale Spine Density and Macroscale Connectivity Disruptions in Schizophrenia. Biol Psychiatry 2016; 80:293-301. [PMID: 26632269 DOI: 10.1016/j.biopsych.2015.10.005] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Revised: 09/12/2015] [Accepted: 10/01/2015] [Indexed: 12/28/2022]
Abstract
BACKGROUND Schizophrenia is often described as a disorder of dysconnectivity, with disruptions in neural connectivity reported on the cellular microscale as well as the global macroscale level of brain organization. How these effects on these two scales are related is poorly understood. METHODS First (part I of this study), we collated data on layer 3 pyramidal spine density of the healthy brain from the literature and cross-analyzed these data with new data on macroscale connectivity as derived from diffusion imaging. Second (part II of this study), we examined how alterations in regional spine density in schizophrenia are related to changes in white matter connectivity. Data on group differences in spine density were collated from histology reports in the literature and examined in a meta-regression analysis in context of alterations in macroscale white matter connectivity as derived from diffusion imaging data of a (separately acquired) group of 61 patients and 55 matched control subjects. RESULTS Densely connected areas of the healthy human cortex were shown to overlap with areas that display high pyramidal complexity, with pyramidal neurons that are more spinous (p = .0027) compared with pyramidal neurons in areas of low macroscale connectivity. Cross-scale meta-regression analysis showed a significant association between regional variation in level of disease-related spine density reduction in schizophrenia and regional level of decrease in macroscale connectivity (two data sets examined, p = .0028 and p = .0011). CONCLUSIONS Our study presents evidence that regional disruptions in microscale neuronal connectivity in schizophrenia go hand in hand with changes in macroscale brain connectivity.
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Affiliation(s)
- Martijn P van den Heuvel
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Lianne H Scholtens
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marcel A de Reus
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - René S Kahn
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
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Sasabayashi D, Takayanagi Y, Nishiyama S, Takahashi T, Furuichi A, Kido M, Nishikawa Y, Nakamura M, Noguchi K, Suzuki M. Increased Frontal Gyrification Negatively Correlates with Executive Function in Patients with First-Episode Schizophrenia. Cereb Cortex 2016; 27:2686-2694. [DOI: 10.1093/cercor/bhw101] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
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46
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Rigucci S, Marques TR, Di Forti M, Taylor H, Dell'Acqua F, Mondelli V, Bonaccorso S, Simmons A, David AS, Girardi P, Pariante CM, Murray RM, Dazzan P. Effect of high-potency cannabis on corpus callosum microstructure. Psychol Med 2016; 46:841-854. [PMID: 26610039 PMCID: PMC4754829 DOI: 10.1017/s0033291715002342] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2015] [Revised: 09/30/2015] [Accepted: 10/02/2015] [Indexed: 12/26/2022]
Abstract
BACKGROUND The use of cannabis with higher Δ9-tetrahydrocannabinol content has been associated with greater risk, and earlier onset, of psychosis. However, the effect of cannabis potency on brain morphology has never been explored. Here, we investigated whether cannabis potency and pattern of use are associated with changes in corpus callosum (CC) microstructural organization, in patients with first-episode psychosis (FEP) and individuals without psychosis, cannabis users and non-users. METHOD The CC of 56 FEP (37 cannabis users) and 43 individuals without psychosis (22 cannabis users) was virtually dissected and segmented using diffusion tensor imaging tractography. The diffusion index of fractional anisotropy, mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity was calculated for each segment. RESULTS Across the whole sample, users of high-potency cannabis had higher total CC MD and higher total CC AD than both low-potency users and those who never used (p = 0.005 and p = 0.004, respectively). Daily users also had higher total CC MD and higher total CC AD than both occasional users and those who never used (p = 0.001 and p < 0.001, respectively). However, there was no effect of group (patient/individuals without psychosis) or group x potency interaction for either potency or frequency of use. The within-group analysis showed in fact that the effects of potency and frequency were similar in FEP users and in users without psychosis. CONCLUSIONS Frequent use of high-potency cannabis is associated with disturbed callosal microstructural organization in individuals with and without psychosis. Since high-potency preparations are now replacing traditional herbal drugs in many European countries, raising awareness about the risks of high-potency cannabis is crucial.
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Affiliation(s)
- S. Rigucci
- Department of Neurosciences,
Mental Health and Sensory Organs, Sapienza University
of Rome, Rome, Italy
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - T. R. Marques
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - M. Di Forti
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - H. Taylor
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - F. Dell'Acqua
- Centre for Neuroimaging Sciences,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - V. Mondelli
- Department of Psychological Medicine,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
- National Institute for Health Research (NIHR)
Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
and King's College London, London,
UK
| | - S. Bonaccorso
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - A. Simmons
- Centre for Neuroimaging Sciences,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
| | - A. S. David
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
- National Institute for Health Research (NIHR)
Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
and King's College London, London,
UK
| | - P. Girardi
- Department of Neurosciences,
Mental Health and Sensory Organs, Sapienza University
of Rome, Rome, Italy
| | - C. M. Pariante
- Department of Psychological Medicine,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
- National Institute for Health Research (NIHR)
Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
and King's College London, London,
UK
| | - R. M. Murray
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
- National Institute for Health Research (NIHR)
Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
and King's College London, London,
UK
| | - P. Dazzan
- Department of Psychosis Studies,
Institute of Psychiatry, Psychology and
Neuroscience, King's College London,
London, UK
- National Institute for Health Research (NIHR)
Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
and King's College London, London,
UK
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Monin A, Fournier M, Baumann PS, Cuénod M, Do KQ. Role of Redox Dysregulation in White Matter Anomalies Associated with Schizophrenia. HANDBOOK OF BEHAVIORAL NEUROSCIENCE 2016. [DOI: 10.1016/b978-0-12-800981-9.00028-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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Wu CH, Hwang TJ, Chen YJ, Hsu YC, Lo YC, Liu CM, Hwu HG, Liu CC, Hsieh MH, Chien YL, Chen CM, Isaac Tseng WY. Primary and secondary alterations of white matter connectivity in schizophrenia: A study on first-episode and chronic patients using whole-brain tractography-based analysis. Schizophr Res 2015; 169:54-61. [PMID: 26443482 DOI: 10.1016/j.schres.2015.09.023] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2015] [Revised: 09/15/2015] [Accepted: 09/21/2015] [Indexed: 01/12/2023]
Abstract
Schizophrenia is a debilitating mental disorder that is associated with an impaired connection of cerebral white matter. Studies on patients with chronic and first-episode schizophrenia have found widespread white matter abnormalities. However, it is unclear whether the altered connections are inherent in or secondary to the disease. Here, we sought to identify white matter tracts with altered connections and to distinguish primary or secondary alterations among 74 fiber tracts across the whole brain using an automatic tractography-based analysis method. Thirty-one chronic, 25 first-episode patients with schizophrenia and 31 healthy controls were recruited to receive diffusion spectrum magnetic resonance imaging at 3T. Seven tracts were found to exhibit significant differences between the groups; they included the right arcuate fasciculus, bilateral fornices, left superior longitudinal fasciculus I, and fibers of the corpus callosum to the bilateral dorsolateral prefrontal cortices (DLPFC), bilateral temporal poles, and bilateral hippocampi. Post-hoc between-group analyses revealed that the connection of the callosal fibers to the bilateral DLPFC was significantly decreased in chronic patients but not in first-episode patients. In a stepwise regression analysis, the decline of the tract connection was significantly predicted by the duration of illness. In contrast, the remaining six tracts showed significant alterations in both first-episode and chronic patients and did not associate with clinical variables. In conclusion, reduced white matter connectivity of the callosal fibers to the bilateral DLPFC may be a secondary change that degrades progressively in the chronic stage, whereas alterations in the other six tracts may be inherent in the disease.
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Affiliation(s)
- Chen-Hao Wu
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Medical Imaging and Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yu-Jen Chen
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yung-Chin Hsu
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Yu-Chun Lo
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan.
| | - Chen-Chung Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Ming H Hsieh
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Chung-Ming Chen
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan; Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Molecular Imaging Center, National Taiwan University, Taipei, Taiwan.
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Abstract
OBJECTIVES Although acute hypothalamic-pituitary-adrenal axis response to stress is often adaptive, prolonged responses may have detrimental effects. Many components of white matter structures are sensitive to prolonged cortisol exposure. We aimed to identify a behavioral laboratory assay for cortisol response related to brain pathophysiology in schizophrenia. We hypothesized that an abnormally prolonged cortisol response to stress may be linked to abnormal white matter integrity in patients with schizophrenia. METHODS Acute and prolonged salivary cortisol response was measured outside the scanner at pretest and then at 0, 20, and 40 minutes after a psychological stress task in patients with schizophrenia (n = 45) and controls (n = 53). Tract-averaged white matter was measured by 64-direction diffusion tensor imaging in a subset of patients (n = 30) and controls (n = 33). RESULTS Patients who did not tolerate the psychological stress task and quit had greater acute (t = 2.52 [p = .016] and t = 3.51 [p = .001] at 0 and 20 minutes) and prolonged (t = 3.62 [p = .001] at 40 minutes) cortisol reactivity compared with patients who finished the task. Abnormally prolonged cortisol reactivity in patients was significantly associated with reduced white matter integrity (r = -0.468, p = .009). Regardless of task completion status, acute cortisol response was not related to the white matter measures in patients or controls. CONCLUSIONS This paradigm was successful at identifying a subset of patients whose cortisol response was associated with brain pathophysiology. Abnormal cortisol response may adversely affect white matter integrity, partly explaining this pathology observed in schizophrenia. Prolonged stress responses may be targeted for intervention to test for protective effects against white matter damages.
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50
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Seehaus A, Roebroeck A, Bastiani M, Fonseca L, Bratzke H, Lori N, Vilanova A, Goebel R, Galuske R. Histological validation of high-resolution DTI in human post mortem tissue. Front Neuroanat 2015; 9:98. [PMID: 26257612 PMCID: PMC4511840 DOI: 10.3389/fnana.2015.00098] [Citation(s) in RCA: 97] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Accepted: 07/10/2015] [Indexed: 11/13/2022] Open
Abstract
Diffusion tensor imaging (DTI) is amongst the simplest mathematical models available for diffusion magnetic resonance imaging, yet still by far the most used one. Despite the success of DTI as an imaging tool for white matter fibers, its anatomical underpinnings on a microstructural basis remain unclear. In this study, we used 65 myelin-stained sections of human premotor cortex to validate modeled fiber orientations and oft used microstructure-sensitive scalar measures of DTI on the level of individual voxels. We performed this validation on high spatial resolution diffusion MRI acquisitions investigating both white and gray matter. We found a very good agreement between DTI and myelin orientations with the majority of voxels showing angular differences less than 10°. The agreement was strongest in white matter, particularly in unidirectional fiber pathways. In gray matter, the agreement was good in the deeper layers highlighting radial fiber directions even at lower fractional anisotropy (FA) compared to white matter. This result has potentially important implications for tractography algorithms applied to high resolution diffusion MRI data if the aim is to move across the gray/white matter boundary. We found strong relationships between myelin microstructure and DTI-based microstructure-sensitive measures. High FA values were linked to high myelin density and a sharply tuned histological orientation profile. Conversely, high values of mean diffusivity (MD) were linked to bimodal or diffuse orientation distributions and low myelin density. At high spatial resolution, DTI-based measures can be highly sensitive to white and gray matter microstructure despite being relatively unspecific to concrete microarchitectural aspects.
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Affiliation(s)
- Arne Seehaus
- Faculty of Psychology and Neuroscience, Maastricht University Maastricht, Netherlands ; Systems Neurophysiology, Technische Universität Darmstadt Darmstadt, Germany
| | - Alard Roebroeck
- Faculty of Psychology and Neuroscience, Maastricht University Maastricht, Netherlands
| | - Matteo Bastiani
- Faculty of Psychology and Neuroscience, Maastricht University Maastricht, Netherlands ; Jülich Research Centre, Institute of Neuroscience and Medicine (INM-4) Jülich, Germany
| | - Lúcia Fonseca
- Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven, Netherlands
| | | | - Nicolás Lori
- Visual Neuroscience Laboratory, Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra Coimbra, Portugal
| | - Anna Vilanova
- Department of Biomedical Engineering, Eindhoven University of Technology Eindhoven, Netherlands
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University Maastricht, Netherlands
| | - Ralf Galuske
- Systems Neurophysiology, Technische Universität Darmstadt Darmstadt, Germany
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