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Lin Y, Gao B, Du Y, Li M, Liu Y, Zhao X. Cortical thickness and structural covariance network alterations in cerebral amyloid angiopathy: A graph theoretical analysis. Neurobiol Dis 2025; 210:106911. [PMID: 40239845 DOI: 10.1016/j.nbd.2025.106911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2025] [Revised: 04/13/2025] [Accepted: 04/13/2025] [Indexed: 04/18/2025] Open
Abstract
AIMS This study investigates large-scale brain network alterations in cerebral amyloid angiopathy (CAA) using structural covariance network (SCN) analysis and graph theory based on 7 T MRI. METHODS We employed structural covariance network (SCN) analysis based on cortical thickness data from ultra-high field 7 T MRI to investigate network alterations in CAA patients. Graph theoretical analysis was applied to quantify topological properties, including small-worldness, nodal centrality, and network efficiency. Between-group differences were assessed using permutation tests and false discovery rate (FDR) correction. RESULTS CAA patients exhibited significant alterations in small-world properties, with decreased Gamma (p = 0.002) and Sigma (p < 0.001), suggesting a shift toward a less optimal network configuration. Local efficiency was significantly different between groups (p = 0.045), while global efficiency remained unchanged (p = 0.127), indicating regionally disrupted rather than globally impaired network efficiency. At the nodal level, the right superior frontal gyrus exhibited increased betweenness centrality (p = 0.013), whereas the right banks of the superior temporal sulcus, left postcentral gyrus, and left superior temporal gyrus showed significantly reduced centrality (all p < 0.05). Additionally, nodal degree and efficiency were altered in key memory-related and association regions, including the entorhinal cortex, fusiform gyrus, and temporal pole. CONCLUSION SCN analysis combined with graph theory offers a valuable approach for understanding disease-related connectivity disruptions and may contribute to the development of network-based biomarkers for CAA.
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Affiliation(s)
- Yijun Lin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Bin Gao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yang Du
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mengyao Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanfang Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
| | - Xingquan Zhao
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; China National Clinical Research Center for Neurological Diseases, Beijing, China.
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Fattal J, Giljen M, Vargas T, Damme KSF, Calkins ME, Pinkham AE, Mittal VA. A Developmental Perspective on Early and Current Motor Abnormalities and Psychotic-Like Symptoms. Schizophr Bull 2025; 51:522-530. [PMID: 38728386 PMCID: PMC11908870 DOI: 10.1093/schbul/sbae062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
BACKGROUND AND HYPOTHESIS Psychotic-like experiences (PLEs) are prevalent in the general population and, because they represent a lower end of the psychosis vulnerability spectrum, may be useful in informing mechanistic understanding. Although it is well-understood that motor signs characterize formal psychotic disorders, the developmental trajectory of these features and their relationships with PLEs are less well-understood. STUDY DESIGN Data from 7559 adolescents and young adults (age 11-21) in the Philadelphia Neurodevelopmental Cohort were used to investigate whether early-life milestone-attainment delays relate to current adolescent sensorimotor functioning and positive and negative PLEs. Current sensorimotor functioning was assessed using the Computerized Finger Tapping task (assessing motor slowing) and Mouse Practice task (assessing sensorimotor planning). STUDY RESULTS Early developmental abnormalities were related to current adolescent-aged motor slowing (t(7415.3) = -7.74, corrected-P < .001) and impaired sensorimotor planning (t(7502.5) = 5.57, corrected-P < .001). There was a significant interaction between developmental delays and current sensorimotor functioning on positive and negative PLEs (t = 1.67-4.51), such that individuals with early developmental delays had a stronger positive relationship between sensorimotor dysfunction and PLEs. Importantly, interaction models were significantly better at explaining current PLEs than those treating early and current sensorimotor dysfunction independently (χ2 = 4.89-20.34). CONCLUSIONS These findings suggest a relationship between early developmental delays and current sensorimotor functioning in psychosis proneness and inform an understanding of heterotypic continuity as well as a neurodevelopmental perspective of motor circuits. Furthermore, results indicate that motor signs are a clear factor in the psychosis continuum, suggesting that they may represent a core feature of psychosis vulnerability.
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Affiliation(s)
- Jessica Fattal
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Maksim Giljen
- Department of Psychological Science, University of California, Irvine, Irvine, CA, USA
| | - Teresa Vargas
- Department of Psychology, Harvard University, Cambridge, MA, USA
| | | | - Monica E Calkins
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy E Pinkham
- Department of Psychology, University of Texas at Dallas, Richardson, TX, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA
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3
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Sasabayashi D, Tsugawa S, Nakajima S, Takahashi T, Takayanagi Y, Koike S, Katagiri N, Katsura M, Furuichi A, Mizukami Y, Nishiyama S, Kobayashi H, Yuasa Y, Tsujino N, Sakuma A, Ohmuro N, Sato Y, Tomimoto K, Okada N, Tada M, Suga M, Maikusa N, Plitman E, Wannan CMJ, Zalesky A, Chakravarty M, Noguchi K, Yamasue H, Matsumoto K, Nemoto T, Tomita H, Mizuno M, Kasai K, Suzuki M. Increased structural covariance of cortical measures in individuals with an at-risk mental state. Prog Neuropsychopharmacol Biol Psychiatry 2025; 136:111197. [PMID: 39579961 DOI: 10.1016/j.pnpbp.2024.111197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 11/01/2024] [Accepted: 11/15/2024] [Indexed: 11/25/2024]
Abstract
An anomalous pattern of structural covariance has been reported in schizophrenia, which has been suggested to represent connectome changes during brain maturation and neuroprogressive processes. It remains unclear whether similar differences exist in a clinical high-risk state for psychosis, and if they are associated with a prodromal phenotype and/or later psychosis onset. This multicenter magnetic resonance imaging study cross-sectionally examined structural covariance in a large at-risk mental state (ARMS) sample with different outcomes. The whole-brain structural covariance of four cortical measures (thickness, area, volume, and gyrification) was assessed in 155 individuals with ARMS, who were subclassified into 26 (16.8 %) with a later psychosis onset (ARMS-P), 44 with persistent subthreshold psychotic symptoms, and 53 with the remission of psychotic symptoms (ARMS-R) during the clinical follow-up, and 191 healthy controls. The relationships of changes in structural covariance with clinical symptoms and cognitive impairments were also investigated in the ARMS subsample. Structural covariance was significantly higher in widespread cortical regions in the ARMS group than in the controls, with each cortical measure having a different pattern in affected cortical regions. The higher structural covariance of the cortical area was partly related to severe suspiciousness-persecutory ideation. Structural covariance was significantly higher, mainly in fronto-parietal gyrification, in the ARMS-P group than in the ARMS-R group. The present results suggest that changes in structural covariance result in psychosis vulnerability and the excessive structural covariance of brain gyrification in ARMS subjects may contribute to their later clinical course.
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Affiliation(s)
- Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan.
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582, Japan; Brain Health Imaging Centre, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario M5T 1R8, Canada
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Arisawabashi Hospital, 5-5 Hane-Shin, Toyama city, Toyama 939-2704, Japan
| | - Shinsuke Koike
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, Komaba 3-8-1, Meguro-ku, Tokyo 153-8902, Japan; Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan; International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, 6-11-1 Omori-nishi, Ota-ku, Tokyo 143-8541, Japan
| | - Masahiro Katsura
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; Canal Kotodai General Mental Clinic, 2-4-8 Honcho, Aoba-ku, Sendai 980-0014, Japan
| | - Atsushi Furuichi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
| | - Yuko Mizukami
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
| | - Shimako Nishiyama
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Center for Health Care and Human Sciences, University of Toyama, 3190 Gofuku, Toyama 930-8555, Japan
| | - Haruko Kobayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
| | - Yusuke Yuasa
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
| | - Naohisa Tsujino
- Department of Neuropsychiatry, Toho University School of Medicine, 6-11-1 Omori-nishi, Ota-ku, Tokyo 143-8541, Japan; Department of Psychiatry, Saiseikai Yokohamashi Tobu Hospital, 3-6-1 Shimosueyoshi, Tsurumi-ku, Yokohama, Kanagawa 230-8765, Japan
| | - Atsushi Sakuma
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan
| | - Noriyuki Ohmuro
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; Osaki Citizen Hospital, 3-8-1 Honami, Osaki, Miyagi 989-6183, Japan
| | - Yutaro Sato
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan
| | - Kazuho Tomimoto
- Department of Psychiatry, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan
| | - Naohiro Okada
- International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Mariko Tada
- International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Motomu Suga
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan; Graduate School of Clinical Psychology, Teikyo Heisei University, 2-51-4 Higashi Ikebukuro, Toshima-ku, Tokyo 170-8445, Japan
| | - Norihide Maikusa
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Eric Plitman
- Department of Psychiatry, University of Toronto, 250 College Street, Toronto, Ontario M5T 1R8, Canada
| | - Cassandra M J Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Orygen, Parkville, 35 Poplar Road, Parkville, Victoria 3052, Australia; Centre for Youth Mental Health, The University of Melbourne, 35 Poplar Road, Parkville, Victoria 3052, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Melbourne School of Engineering, University of Melbourne, Melbourne, Grattan Street, Parkville, Victoria 3010, Australia
| | - Mallar Chakravarty
- Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, 6875 LaSalle Boulevard, Montreal, Quebec H4H 1R3, Canada; Department of Psychiatry, McGill University, 1033 Pine Avenue West, Montreal, Quebec H3A 1A1, Canada; Biological and Biomedical Engineering, McGill University, 3655 Promenade Sir-William-Osler, Montreal, Quebec H3G 1Y6, Canada
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama City, Toyama 930-0194, Japan
| | - Hidenori Yamasue
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan; Department of Psychiatry, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu 431-3192, Japan
| | - Kazunori Matsumoto
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; Kokoro no Clinic OASIS, 17-27 Futsukamachi, Aoba-ku, Sendai 980-0802, Japan
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University School of Medicine, 6-11-1 Omori-nishi, Ota-ku, Tokyo 143-8541, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; Department of Psychiatry, Tohoku University Graduate School of Medicine, 1-1, Seiryo-machi, Aoba-ku, Sendai 980-8574, Japan; Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, 468-1 Aoba, Aramaki, Aoba-ku, Sendai 980-8572, Japan
| | - Masafumi Mizuno
- Department of Neuropsychiatry, Toho University School of Medicine, 6-11-1 Omori-nishi, Ota-ku, Tokyo 143-8541, Japan; Tokyo Metropolitan Matsuzawa Hospital, 2-1-1 Kamikitazawa, Setagaya-ku, Tokyo 156-0057, Japan
| | - Kiyoto Kasai
- International Research Center for Neurointelligence, The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan; Research Center for Idling Brain Science, University of Toyama, 2630 Sugitani, Toyama city, Toyama 930-0194, Japan
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Wilson S, Cromb D, Bonthrone AF, Uus A, Price A, Egloff A, Van Poppel MPM, Steinweg JK, Pushparajah K, Simpson J, Lloyd DFA, Razavi R, O'Muircheartaigh J, Edwards AD, Hajnal JV, Rutherford M, Counsell SJ. Structural Covariance Networks in the Fetal Brain Reveal Altered Neurodevelopment for Specific Subtypes of Congenital Heart Disease. J Am Heart Assoc 2024; 13:e035880. [PMID: 39450739 PMCID: PMC11935691 DOI: 10.1161/jaha.124.035880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 09/27/2024] [Indexed: 10/26/2024]
Abstract
BACKGROUND Altered structural brain development has been identified in fetuses with congenital heart disease (CHD), suggesting that the neurodevelopmental impairment observed later in life might originate in utero. There are many interacting factors that may perturb neurodevelopment during the fetal period and manifest as structural brain alterations, such as altered cerebral substrate delivery and aberrant fetal hemodynamics. METHODS AND RESULTS We extracted structural covariance networks from the log Jacobian determinants of 435 in utero T2 weighted image magnetic resonance imaging scans, (n=67 controls, 368 with CHD) acquired during the third trimester. We fit general linear models to test whether age, sex, expected cerebral substrate delivery, and CHD diagnosis were significant predictors of structural covariance. We identified significant effects of age, sex, cerebral substrate delivery, and specific CHD diagnosis across a variety of structural covariance networks, including primary motor and sensory cortices, cerebellar regions, frontal cortex, extra-axial cerebrospinal fluid, thalamus, brainstem, and insula, consistent with widespread coordinated aberrant maturation of specific brain regions over the third trimester. CONCLUSIONS Structural covariance networks offer a sensitive, data-driven approach to explore whole-brain structural changes without anatomical priors. We used them to stratify a heterogenous patient cohort with CHD, highlighting similarities and differences between diagnoses during fetal neurodevelopment. Although there was a clear effect of abnormal fetal hemodynamics on structural brain maturation, our results suggest that this alone does not explain all the variation in brain development between individuals with CHD.
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Affiliation(s)
- Siân Wilson
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Fetal‐Neonatal Neuroimaging & Developmental Science CenterBoston Children’s HospitalBostonMAUSA
- Division of Newborn MedicineBoston Children’s HospitalBostonMAUSA
- Department of Pediatrics, Harvard Medical SchoolBostonMAUSA
| | - Daniel Cromb
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Alexandra F. Bonthrone
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Alena Uus
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Anthony Price
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Alexia Egloff
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Milou P. M. Van Poppel
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - Johannes K. Steinweg
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - Kuberan Pushparajah
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - John Simpson
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - David F. A. Lloyd
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - Reza Razavi
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Department of Congenital Heart DiseaseEvelina London Children’s HospitalLondonUnited Kingdom
| | - Jonathan O'Muircheartaigh
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental DisordersKing’s College LondonLondonUnited Kingdom
- Department of Forensic and Neurodevelopmental SciencesKing’s College LondonLondonUnited Kingdom
| | - A. David Edwards
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental DisordersKing’s College LondonLondonUnited Kingdom
| | - Joseph V. Hajnal
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Mary Rutherford
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
| | - Serena J. Counsell
- Research Department of Early Life Imaging, School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUnited Kingdom
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Tsugawa S, Honda S, Noda Y, Wannan C, Zalesky A, Tarumi R, Iwata Y, Ogyu K, Plitman E, Ueno F, Mimura M, Uchida H, Chakravarty M, Graff-Guerrero A, Nakajima S. Associations Between Structural Covariance Network and Antipsychotic Treatment Response in Schizophrenia. Schizophr Bull 2024; 50:382-392. [PMID: 37978044 PMCID: PMC10919786 DOI: 10.1093/schbul/sbad160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is associated with widespread cortical thinning and abnormality in the structural covariance network, which may reflect connectome alterations due to treatment effect or disease progression. Notably, patients with treatment-resistant schizophrenia (TRS) have stronger and more widespread cortical thinning, but it remains unclear whether structural covariance is associated with treatment response in schizophrenia. STUDY DESIGN We organized a multicenter magnetic resonance imaging study to assess structural covariance in a large population of TRS and non-TRS, who had been resistant and responsive to non-clozapine antipsychotics, respectively. Whole-brain structural covariance for cortical thickness was assessed in 102 patients with TRS, 77 patients with non-TRS, and 79 healthy controls (HC). Network-based statistics were used to examine the difference in structural covariance networks among the 3 groups. Moreover, the relationship between altered individual differentiated structural covariance and clinico-demographics was also explored. STUDY RESULTS Patients with non-TRS exhibited greater structural covariance compared with HC, mainly in the fronto-temporal and fronto-occipital regions, while there were no significant differences in structural covariance between TRS and non-TRS or HC. Higher individual differentiated structural covariance was associated with lower general scores of the Positive and Negative Syndrome Scale in the non-TRS group, but not in the TRS group. CONCLUSIONS These findings suggest that reconfiguration of brain networks via coordinated cortical thinning is related to treatment response in schizophrenia. Further longitudinal studies are warranted to confirm if greater structural covariance could serve as a marker for treatment response in this disease.
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Affiliation(s)
- Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Shiori Honda
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Cassandra Wannan
- Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Andrew Zalesky
- Department of Biomedical Engineering, Melbourne School of Engineering, the University of Melbourne, Melbourne, Australia
| | - Ryosuke Tarumi
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
- Department of Psychiatry, Komagino Hospital, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi, Yamanashi, Japan
| | - Kamiyu Ogyu
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
- Department of Psychiatry, National Hospital Organization Shimofusa Psychiatric Medical Center, Chiba, Japan
| | - Eric Plitman
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Fumihiko Ueno
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University, Tokyo, Japan
| | - Mallar Chakravarty
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canada
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Mamah D. A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2023; 8:e230005. [PMID: 37427077 PMCID: PMC10327607 DOI: 10.20900/jpbs.20230005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.
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Affiliation(s)
- Daniel Mamah
- Department of Psychiatry, Washington University Medical School, St. Louis, MO, 63110, USA
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Saiz-Masvidal C, Contreras F, Soriano-Mas C, Mezquida G, Díaz-Caneja CM, Vieta E, Amoretti S, Lobo A, González-Pinto A, Janssen J, Sagué-Vilavella M, Castro-Fornieles J, Bergé D, Bioque M, Lois NG, Parellada M, Bernardo M. Structural covariance predictors of clinical improvement at 2-year follow-up in first-episode psychosis. Prog Neuropsychopharmacol Biol Psychiatry 2023; 120:110645. [PMID: 36181960 DOI: 10.1016/j.pnpbp.2022.110645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/07/2022] [Accepted: 09/22/2022] [Indexed: 11/30/2022]
Abstract
The relationship between structural brain alterations and prediction of clinical improvement in first-episode psychosis (FEP) has been scarcely studied. We investigated whether structural covariance, a well-established approach to identify abnormal patterns of volumetric correlation across distant brain regions, which allows incorporating network-level information to structural assessments, is associated with longitudinal clinical course. We assessed a sample of 74 individuals from a multicenter study. Magnetic resonance imaging scans were acquired at baseline, and clinical assessments at baseline and at a 2-year follow-up. Participants were split in two groups as a function of their clinical improvement after 2 years (i.e., ≥ < 40% reduction in psychotic symptom severity, (n = 29, n = 45)). We performed a seed-based approach and focused our analyses on 3 cortical and 4 subcortical regions of interest to identify alterations in cortical and cortico-subcortical networks. Improvers presented an increased correlation between the volumes of the right posterior cingulate cortex (PCC) and the left precentral gyrus, and between the left PCC and the left middle occipital gyrus. They also showed an increased correlation between right posterior hippocampus and left angular gyrus volumes. Our study provides a novel mean to identify structural correlates of clinical improvement in FEP, describing clinically-relevant anatomical differences in terms of large-scale brain networks, which is better aligned with prevailing neurobiological models of psychosis. The results involve brain regions considered to participate in the multisensory processing of bodily signals and the construction of bodily self-consciousness, which resonates with recent theoretical accounts in psychosis research.
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Affiliation(s)
- Cristina Saiz-Masvidal
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Department of Clinical Sciences, School of Medicine, University of Barcelona, Spain
| | - Fernando Contreras
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Social Psychology and Quantitative Psychology, University of Barcelona, Spain.
| | - Gisela Mezquida
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
| | - Covadonga M Díaz-Caneja
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Eduard Vieta
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Silvia Amoretti
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain; Group of Psychiatry, Mental Health and Addictions, Psychiatric Genetics Unit, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Antonio Lobo
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Medicine and Psychiatry, Universidad de Zaragoza, Zaragoza, Spain; Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
| | - Ana González-Pinto
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Instituto de Investigación Sanitaria Bioaraba (BIOARABA), Vitoria, Spain; Department of Psychiatry, Hospital Universitario de Alava, Vitoria, Spain; Universidad del País Vasco/ Euskal Harriko Unibertsitatea (UPV/EHU), País Vasco, Spain
| | - Joost Janssen
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Maria Sagué-Vilavella
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Bipolar and Depressive Disorders Unit, Clinical Institute of Neurosciences, Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Josefina Castro-Fornieles
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Child and Adolescent Psychiatry and Psychology, 2017SGR881, Institut Clínic de Neurociències, Hospital Clínic Universitari, Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Daniel Bergé
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Institute of Neuropsychiatry and Addiction of the Barcelona MAR Health Park, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Department of Medicine and Life Sciences, Pompeu Fabra University (UPF), Barcelona, Spain
| | - Miquel Bioque
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Noemi G Lois
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Mara Parellada
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón and School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Miguel Bernardo
- Biomedical Research Networking Center for Mental Health Network (CIBERSAM), Madrid, Spain; Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Clinical Foundations, Pharmacology Unit, University of Barcelona, Barcelona, Spain
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8
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Prasad K, Rubin J, Mitra A, Lewis M, Theis N, Muldoon B, Iyengar S, Cape J. Structural covariance networks in schizophrenia: A systematic review Part II. Schizophr Res 2022; 239:176-191. [PMID: 34902650 PMCID: PMC8785680 DOI: 10.1016/j.schres.2021.11.036] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 09/02/2021] [Accepted: 11/23/2021] [Indexed: 01/10/2023]
Abstract
BACKGROUND Examination of structural covariance network (SCN) is gaining prominence among the strategies to delineate dysconnectivity that case-control morphometric comparisons cannot address. Part II of this review extends on the part I of the review that included SCN studies using statistical approaches by examining SCN studies applying graph theoretic approaches to elucidate network properties in schizophrenia. This review also includes SCN studies using graph theoretic or statistical approaches on persons at-risk for schizophrenia. METHODS A systematic literature search was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia and risk for schizophrenia. Thirteen studies on schizophrenia and five on persons at risk for schizophrenia met the criteria. RESULTS A variety of findings from over the last 1½ decades showing qualitative and quantitative differences in the global and local structural connectome in schizophrenia are described. These observations include altered hub patterns, disrupted network topology and hierarchical organization of the brain, and impaired connections that may be localized to default mode, executive control, and dorsal attention networks. Some of these connectomic alterations were observed in persons at-risk for schizophrenia before the onset of the illness. CONCLUSIONS Observed disruptions may reduce network efficiency and capacity to integrate information. Further, global connectomic changes were not schizophrenia-specific but local network changes were. Existing studies have used different atlases for brain parcellation, examined different morphometric features, and patients at different stages of illness making it difficult to conduct meta-analysis. Future studies should harmonize such methodological differences to facilitate meta-analysis and also elucidate causal underpinnings of dysconnectivity.
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Affiliation(s)
- Konasale Prasad
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara St, Pittsburgh, PA 15213, United States of America; University of Pittsburgh Swanson School of Engineering, 3700 O'Hara St, Pittsburgh, PA 15213, United States of America; VA Pittsburgh Healthcare System, University Dr C, Pittsburgh, PA 15240, United States of America.
| | - Jonathan Rubin
- Department of Mathematics, University of Pittsburgh, 917 Cathedral of Learning, Pittsburgh, PA 15260, United States of America
| | - Anirban Mitra
- Department of Statistics, University of Pittsburgh, 230 South Bouquet Street, Pittsburgh, PA 15260, United States of America
| | - Madison Lewis
- University of Pittsburgh Swanson School of Engineering, 3700 O'Hara St, Pittsburgh, PA 15213, United States of America
| | - Nicholas Theis
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara St, Pittsburgh, PA 15213, United States of America
| | - Brendan Muldoon
- University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O'Hara St, Pittsburgh, PA 15213, United States of America
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, 230 South Bouquet Street, Pittsburgh, PA 15260, United States of America
| | - Joshua Cape
- Department of Statistics, University of Pittsburgh, 230 South Bouquet Street, Pittsburgh, PA 15260, United States of America
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9
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Ge R, Hassel S, Arnott SR, Davis AD, Harris JK, Zamyadi M, Milev R, Frey BN, Strother SC, Müller DJ, Rotzinger S, MacQueen GM, Kennedy SH, Lam RW, Vila-Rodriguez F. Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110194. [PMID: 33296696 DOI: 10.1016/j.pnpbp.2020.110194] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 09/25/2020] [Accepted: 11/30/2020] [Indexed: 11/26/2022]
Abstract
BACKGROUND AND METHODS Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs. RESULTS The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network. CONCLUSIONS Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.
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Affiliation(s)
- Ruiyang Ge
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Stefanie Hassel
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada
| | | | - Andrew D Davis
- Department of Psychology, Neuroscience & Behaviour, McMaster University, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Roumen Milev
- Department of Psychiatry, Queen's University and Providence Care Hospital, Kingston, ON, Canada; Department of Psychology, Queen's University, Kingston, ON, Canada
| | - Benicio N Frey
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada; Mood Disorders Program and Women's Health Concerns Clinic, St. Joseph's Healthcare, Hamilton, ON, Canada
| | | | - Daniel J Müller
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Susan Rotzinger
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Glenda M MacQueen
- Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Sidney H Kennedy
- Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, Krembil Research Centre, University Health Network, University of Toronto, Toronto, ON, Canada; Department of Psychiatry, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada; Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Raymond W Lam
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.
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10
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Resolving heterogeneity in schizophrenia through a novel systems approach to brain structure: individualized structural covariance network analysis. Mol Psychiatry 2021; 26:7719-7731. [PMID: 34316005 DOI: 10.1038/s41380-021-01229-4] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 06/15/2021] [Accepted: 07/05/2021] [Indexed: 12/12/2022]
Abstract
Reliable mapping of system-level individual differences is a critical first step toward precision medicine for complex disorders such as schizophrenia. Disrupted structural covariance indicates a system-level brain maturational disruption in schizophrenia. However, most studies examine structural covariance at the group level. This prevents subject-level inferences. Here, we introduce a Network Template Perturbation approach to construct individual differential structural covariance network (IDSCN) using regional gray-matter volume. IDSCN quantifies how structural covariance between two nodes in a patient deviates from the normative covariance in healthy subjects. We analyzed T1 images from 1287 subjects, including 107 first-episode (drug-naive) patients and 71 controls in the discovery datasets and established robustness in 213 first-episode (drug-naive), 294 chronic, 99 clinical high-risk patients, and 494 controls from the replication datasets. Patients with schizophrenia were highly variable in their altered structural covariance edges; the number of altered edges was related to severity of hallucinations. Despite this variability, a subset of covariance edges, including the left hippocampus-bilateral putamen/globus pallidus edges, clustered patients into two distinct subgroups with opposing changes in covariance compared to controls, and significant differences in their anxiety and depression scores. These subgroup differences were stable across all seven datasets with meaningful genetic associations and functional annotation for the affected edges. We conclude that the underlying physiology of affective symptoms in schizophrenia involves the hippocampus and putamen/pallidum, predates disease onset, and is sufficiently consistent to resolve morphological heterogeneity throughout the illness course. The two schizophrenia subgroups identified thus have implications for the nosology and clinical treatment.
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11
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Song J, Li J, Chen L, Lu X, Zheng S, Yang Y, Cao B, Weng Y, Chen Q, Ding J, Huang R. Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury. Brain Imaging Behav 2021; 15:1840-1854. [PMID: 32880075 DOI: 10.1007/s11682-020-00378-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.
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Affiliation(s)
- Jie Song
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,School of Psychology, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Jie Li
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Lixiang Chen
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,School of Psychology, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Xingqi Lu
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Senning Zheng
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,School of Psychology, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Ying Yang
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China
| | - Bolin Cao
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,School of Psychology, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Yihe Weng
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,School of Psychology, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Qinyuan Chen
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China.,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.,Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Jianping Ding
- Department of Radiology, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, 310015, China. .,School of Medicine, Hangzhou Normal University, Hangzhou, 310015, China.
| | - Ruiwang Huang
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, 510631, China. .,School of Psychology, South China Normal University, Guangzhou, 510631, China. .,Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.
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12
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Vanes LD, Hadaya L, Kanel D, Falconer S, Ball G, Batalle D, Counsell SJ, Edwards AD, Nosarti C. Associations Between Neonatal Brain Structure, the Home Environment, and Childhood Outcomes Following Very Preterm Birth. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 1:146-155. [PMID: 34471914 PMCID: PMC8367847 DOI: 10.1016/j.bpsgos.2021.05.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/16/2021] [Accepted: 05/06/2021] [Indexed: 12/31/2022] Open
Abstract
Background Very preterm birth is associated with an increased risk of childhood psychopathology and cognitive deficits. However, the extent to which these developmental problems associated with preterm birth are amenable to environmental factors or determined by neurobiology at birth remains unclear. Methods We derived neonatal brain structural covariance networks using non-negative matrix factorization in 384 very preterm infants (median gestational age [range], 30.29 [23.57–32.86] weeks) who underwent magnetic resonance imaging at term-equivalent age (median postmenstrual age, 42.57 [37.86–44.86] weeks). Principal component analysis was performed on 32 behavioral and cognitive measures assessed at preschool age (n = 206; median age, 4.65 [4.19–7.17] years) to identify components of childhood psychopathology and cognition. The Cognitively Stimulating Parenting Scale assessed the level of cognitively stimulating experiences available to the child at home. Results Cognitively stimulating parenting was associated with reduced expression of a component reflecting developmental psychopathology and executive dysfunction consistent with the preterm phenotype (inattention-hyperactivity, autism spectrum behaviors, and lower executive function scores). In contrast, a component reflecting better general cognitive abilities was associated with larger neonatal gray matter volume in regions centered on key nodes of the salience network, but not with cognitively stimulating parenting. Conclusions Our results suggest that while neonatal brain structure likely influences cognitive abilities in very preterm children, the severity of behavioral symptoms that are typically observed in these children is sensitive to a cognitively stimulating home environment. Very preterm children may derive meaningful mental health benefits from access to cognitively stimulating experiences during childhood.
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Affiliation(s)
- Lucy D. Vanes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Address correspondence to Lucy D. Vanes, Ph.D.
| | - Laila Hadaya
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Dana Kanel
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Gareth Ball
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - A. David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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13
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Zhao K, Zheng Q, Che T, Dyrba M, Li Q, Ding Y, Zheng Y, Liu Y, Li S. Regional radiomics similarity networks (R2SNs) in the human brain: Reproducibility, small-world properties and a biological basis. Netw Neurosci 2021; 5:783-797. [PMID: 34746627 PMCID: PMC8567836 DOI: 10.1162/netn_a_00200] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 05/08/2021] [Indexed: 12/13/2022] Open
Abstract
A structural covariance network (SCN) has been used successfully in structural magnetic resonance imaging (sMRI) studies. However, most SCNs have been constructed by a unitary marker that is insensitive for discriminating different disease phases. The aim of this study was to devise a novel regional radiomics similarity network (R2SN) that could provide more comprehensive information in morphological network analysis. R2SNs were constructed by computing the Pearson correlations between the radiomics features extracted from any pair of regions for each subject (AAL atlas). We further assessed the small-world property of R2SNs, and we evaluated the reproducibility in different datasets and through test-retest analysis. The relationships between the R2SNs and general intelligence/interregional coexpression of genes were also explored. R2SNs could be replicated in different datasets, regardless of the use of different feature subsets. R2SNs showed high reproducibility in the test-retest analysis (intraclass correlation coefficient > 0.7). In addition, the small-word property (σ > 2) and the high correlation between gene expression (R = 0.29, p < 0.001) and general intelligence were determined for R2SNs. Furthermore, the results have also been repeated in the Brainnetome atlas. R2SNs provide a novel, reliable, and biologically plausible method to understand human morphological covariance based on sMRI.
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Affiliation(s)
- Kun Zhao
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Qiang Zheng
- School of Computer and Control Engineering, Yantai University, Yantai, China
| | - Tongtong Che
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Qiongling Li
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
| | - Yanhui Ding
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yuanjie Zheng
- School of Information Science and Engineering, Shandong Normal University, Jinan, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing, China
| | - Shuyu Li
- School of Biological Science & Medical Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, China
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Chen S, Wang M, Dong H, Wang L, Jiang Y, Hou X, Zhuang Q, Dong GH. Internet gaming disorder impacts gray matter structural covariance organization in the default mode network. J Affect Disord 2021; 288:23-30. [PMID: 33839555 DOI: 10.1016/j.jad.2021.03.077] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 03/19/2021] [Accepted: 03/23/2021] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Although previous studies have revealed that dysfunctional brain organization is associated with internet gamingdisorder (IGD), the neuroanatomical basis that underlies IGD remains elusive. In this work, we aimed to investigate gray matter (GM) volume alterations and structural covariance patterns in relation to IGD severity. METHODS Structural magnetic resonance imaging data were acquired from two hundred and thirty young adults encompassing a wide range of IGD severity. Voxel-based morphometry (VBM) analysis was applied to examine GM volume changes associated with IGD severity. Furthermore, the organization of whole-brain structural covariance network (SCN) was analyzed using the regions identified as seeds from VBM analysis. RESULTS Individuals with greater IGD severity had increased GM volumes in the midline components of the default mode network (DMN), namely, the right medial prefrontal cortex (mPFC) and precuneus. More importantly, the SCN results revealed impaired patterns of structural covariance between the DMN-related regions and areas associated with visuospatial attention and reward craving processing as the addiction severity of IGD worsened. LIMITATIONS Only young Chinese adults were enrolled in our study andthe extent to which findings generalize to samples in other age groups and diverse cultures is unclear. CONCLUSIONS These results showed volume expansion of the DMN components and its weakened structural association with visuospatial attention and motivational craving regions with increasing IGD severity. This study deepens our understanding of the underlying neuroanatomical correlates of IGD, which may help to explain why some individuals are more vulnerable to compulsive gaming usage than others.
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Affiliation(s)
- Shuaiyu Chen
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China
| | - Min Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China
| | - Haohao Dong
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China
| | - Lingxiao Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China
| | - Yuchao Jiang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
| | - Xin Hou
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qian Zhuang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
| | - Guang-Heng Dong
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China.
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15
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"First-episode psychosis: Structural covariance deficits in salience network correlate with symptoms severity". J Psychiatr Res 2021; 136:409-420. [PMID: 33647856 DOI: 10.1016/j.jpsychires.2021.01.044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 01/08/2021] [Accepted: 01/23/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms' severity. METHODS Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated. RESULTS Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms. CONCLUSION Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection.
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16
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Vargas T, Damme KSF, Ered A, Capizzi R, Frosch I, Ellman LM, Mittal VA. Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:166-177. [PMID: 32788085 PMCID: PMC7725930 DOI: 10.1016/j.bpsc.2020.06.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 06/01/2020] [Accepted: 06/02/2020] [Indexed: 12/26/2022]
Abstract
Psychotic disorders are highly debilitating and constitute a major public health burden. Identifying markers of psychosis risk and resilience is a necessary step toward understanding etiology and informing prevention and treatment efforts in individuals at clinical high risk (CHR) for psychosis. In this context, it is important to consider that neural risk markers have been particularly useful in identifying mechanistic determinants along with predicting clinical outcomes. Notably, despite a growing body of supportive literature and the promise of recent findings identifying potential neural markers, the current work on CHR resilience markers has received little attention. The present review provides a brief overview of brain-based risk markers with a focus on predicting symptom course. Next, the review turns to protective markers, examining research from nonpsychiatric and schizophrenia fields to build an understanding of framing, priorities, and potential, applying these ideas to contextualizing a small but informative body of resiliency-relevant CHR research. Four domains (neurocognition, emotion regulation, allostatic load, and sensory and sensorimotor function) were identified and are discussed in terms of behavioral and neural markers. Taken together, the literature suggests significant predictive value for brain-based markers for individuals at CHR for psychosis, and the limited but compelling resiliency work highlights the critical importance of expanding this promising area of inquiry.
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Affiliation(s)
- Teresa Vargas
- Department of Psychology, Northwestern University, Evanston, Illinois.
| | | | - Arielle Ered
- Department of Psychology, Temple University, Philadelphia, Pennsylvania
| | - Riley Capizzi
- Department of Psychology, Temple University, Philadelphia, Pennsylvania
| | - Isabelle Frosch
- Department of Psychology, Northwestern University, Evanston, Illinois
| | - Lauren M Ellman
- Department of Psychology, Temple University, Philadelphia, Pennsylvania
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, Illinois; Department of Psychiatry, Northwestern University, Evanston, Illinois; Department of Medical Social Sciences, Northwestern University, Evanston, Illinois; Institute for Policy Research, Northwestern University, Evanston, Illinois; Institute for Innovations in Developmental Sciences, Northwestern University, Evanston, Illinois
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17
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Cai S, Wang X, Yang F, Chen D, Huang L. Differences in Brain Structural Covariance Network Characteristics in Children and Adults With Autism Spectrum Disorder. Autism Res 2021; 14:265-275. [PMID: 33386783 DOI: 10.1002/aur.2464] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 11/07/2022]
Abstract
Systematically describing the structural topological configuration of human brain during development is an essential task. Autism spectrum disorder (ASD) represents a powerful challenge for psychiatry and neuroscience researchers. In this study, we investigated variations in the structural covariance network properties of 441 patients with ASD ranging in age from 7 to 45 years and in 426 age-matched healthy controls (HCs) using structural magnetic resonance neuroimaging from the ABIDE database. We applied a sliding window approach to study topological variation during development using comprehensive graph theoretical analysis. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and participants with ASD, with the latter exhibiting a 7-year delay in reaching the maximum value, (2) network resilience to targeted attacks peaked at 18' and 19' in the HCs and at 25' in the participants with ASD, and the weakest resilience occurred at age 7', (3) the HCs and participants with ASD exhibited normalized mean degree differences in the right amygdala, and (4) significant differences in the network characteristics were observed in the 18' age group at most of the densities analyzed. We used cross-sectional analysis to infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. Our findings are consistent with the notion that adolescence is a sensitive period of brain development with strong potential for brain plasticity, offering opportunities for environmental adaptation and social integration and for increasing vulnerability. ASD may be a product of susceptibility. LAY SUMMARY: We used cross-sectional analysis to preliminarily infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and participants with ASD, with the latter exhibiting a 7-year delay in reaching the maximum value, (2) Network resilience to targeted attacks peaked at 18' and 19' in the HCs and at 25' in the participants with ASD, and the weakest resilience occurred at age 7', (3) The HCs and participants with ASD exhibited normalized mean degree differences in the right amygdala, and (4) significant differences in the network characteristics were observed in the 18' age group at most of the densities analyzed.
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Affiliation(s)
- Suping Cai
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Xuwen Wang
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Fan Yang
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Dihui Chen
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
| | - Liyu Huang
- School of Life Sciences and Technology, Xidian University, Xi'an, Shaanxi, China
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18
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Andreou C, Borgwardt S. Structural and functional imaging markers for susceptibility to psychosis. Mol Psychiatry 2020; 25:2773-2785. [PMID: 32066828 PMCID: PMC7577836 DOI: 10.1038/s41380-020-0679-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 01/15/2020] [Accepted: 01/31/2020] [Indexed: 12/21/2022]
Abstract
The introduction of clinical criteria for the operationalization of psychosis high risk provided a basis for early detection and treatment of vulnerable individuals. However, about two-thirds of people meeting clinical high-risk (CHR) criteria will never develop a psychotic disorder. In the effort to increase prognostic precision, structural and functional neuroimaging have received growing attention as a potentially useful resource in the prediction of psychotic transition in CHR patients. The present review summarizes current research on neuroimaging biomarkers in the CHR state, with a particular focus on their prognostic utility and limitations. Large, multimodal/multicenter studies are warranted to address issues important for clinical applicability such as generalizability and replicability, standardization of clinical definitions and neuroimaging methods, and consideration of contextual factors (e.g., age, comorbidity).
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Affiliation(s)
- Christina Andreou
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany.
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland.
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19
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Rosengard RJ, Makowski C, Chakravarty M, Malla AK, Joober R, Shah JL, Lepage M. Pre-onset sub-threshold psychotic symptoms and cortical organization in the first episode of psychosis. Prog Neuropsychopharmacol Biol Psychiatry 2020; 100:109879. [PMID: 32004638 DOI: 10.1016/j.pnpbp.2020.109879] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 01/20/2020] [Accepted: 01/27/2020] [Indexed: 12/12/2022]
Abstract
Individuals with sub-threshold psychotic symptoms (STPS) are considered at clinical high risk for psychosis (CHR). Imaging studies comparing CHR and patients shortly after a first episode of psychosis (FEP) support progressive cortical thinning by illness stage. However, at least 30% of FEP patients deny pre-onset STPS, suggesting no history of CHR. This calls into question the generalizability of previous imaging findings. To better understand the physiology of early psychosis symptomology, we investigated the relationship between pre-onset STPS and cortical thickness (CT) among FEP patients, examining regional CT and structural covariance (SC). Patients (N = 93) were recruited from PEPP-Montreal, a FEP clinic at the Douglas Mental Health University Institute. The Circumstances of Onset and Relapse Schedule was administered to retrospectively identify patients who recalled at least one of nine expert-selected STPS prior to their FEP (STPS+, N = 67) and to identify those who did not (STPS-, N = 26). Age and sex-matched healthy controls (HC) were recruited (N = 84) for comparison. Participants were scanned between one and three times over the course of two years. CT values of 320 scans (143 HC, 123 STPS+, 54 STPS-) that passed quality control were extracted for group analysis. Linear mixed effects models accounting for effects of age, sex, education, and mean thickness were applied for vertex-wise, group comparisons of cortical thickness and SC. Multiple comparison corrections were applied with Random Field Theory (p-cluster = 0.001). Compared to controls, only STPS- patients exhibited significantly reduced CT in a cluster of the right ventral lateral prefrontal cortex. The vertex with the highest t-statistic within this cluster was employed as a seed in the subsequent SC analysis. After RFT-correction, STPS+ patients exhibited significantly stronger SC between the seed and right pars orbitalis compared to STPS- patients, and HC exhibited significantly stronger SC between the seed and right middle temporal gyrus compared to STPS- patients. Our results revealed patterns of SC that differentiated patient subgroups and patterns of cortical thinning unique to STPS- patients. Our study demonstrates that the early course of sub-threshold psychotic symptoms holds significance in predicting patterns of CT during FEP.
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Affiliation(s)
- R J Rosengard
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - C Makowski
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada; McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - M Chakravarty
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - A K Malla
- Douglas Mental Health University Institute, Montreal, QC, Canada; Prevention and Early Intervention Program for Psychoses (PEPP-Montreal), Montreal, QC, Canada
| | - R Joober
- Douglas Mental Health University Institute, Montreal, QC, Canada; Prevention and Early Intervention Program for Psychoses (PEPP-Montreal), Montreal, QC, Canada
| | - J L Shah
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada; Prevention and Early Intervention Program for Psychoses (PEPP-Montreal), Montreal, QC, Canada
| | - M Lepage
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada; Prevention and Early Intervention Program for Psychoses (PEPP-Montreal), Montreal, QC, Canada.
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20
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Ma Q, Tang Y, Wang F, Liao X, Jiang X, Wei S, Mechelli A, He Y, Xia M. Transdiagnostic Dysfunctions in Brain Modules Across Patients with Schizophrenia, Bipolar Disorder, and Major Depressive Disorder: A Connectome-Based Study. Schizophr Bull 2020; 46:699-712. [PMID: 31755957 PMCID: PMC7147584 DOI: 10.1093/schbul/sbz111] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Psychiatric disorders, including schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD), share clinical and neurobiological features. Because previous investigations of functional dysconnectivity have mainly focused on single disorders, the transdiagnostic alterations in the functional connectome architecture of the brain remain poorly understood. We collected resting-state functional magnetic resonance imaging data from 512 participants, including 121 with SCZ, 100 with BD, 108 with MDD, and 183 healthy controls. Individual functional brain connectomes were constructed in a voxelwise manner, and the modular architectures were examined at different scales, including (1) global modularity, (2) module-specific segregation and intra- and intermodular connections, and (3) nodal participation coefficients. The correlation of these modular measures with clinical scores was also examined. We reliably identify common alterations in modular organization in patients compared to controls, including (1) lower global modularity; (2) lower modular segregation in the frontoparietal, subcortical, visual, and sensorimotor modules driven by more intermodular connections; and (3) higher participation coefficients in several network connectors (the dorsolateral prefrontal cortex and angular gyrus) and the thalamus. Furthermore, the alterations in the SCZ group are more widespread than those of the BD and MDD groups and involve more intermodular connections, lower modular segregation and higher connector integrity. These alterations in modular organization significantly correlate with clinical scores in patients. This study demonstrates common hyper-integrated modular architectures of functional brain networks among patients with SCZ, BD, and MDD. These findings reveal a transdiagnostic mechanism of network dysfunction across psychiatric disorders from a connectomic perspective.
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Affiliation(s)
- Qing Ma
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xuhong Liao
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiaowei Jiang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Shengnan Wei
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Yong He
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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21
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Heinze K, Shen X, Hawkins E, Harris MA, de Nooij L, McIntosh AM, Wood SJ, Whalley HC. Aberrant structural covariance networks in youth at high familial risk for mood disorder. Bipolar Disord 2020; 22:155-162. [PMID: 31724284 PMCID: PMC7155114 DOI: 10.1111/bdi.12868] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Current research suggests significant disruptions in functional brain networks in individuals with mood disorder, and in those at familial risk. Studies of structural brain networks provide important insights into synchronized maturational change but have received less attention. We aimed to investigate developmental relationships of large-scale brain networks in mood disorder using structural covariance (SC) analyses. METHODS We conducted SC analysis of baseline structural imaging data from 121 at the time of scanning unaffected high risk (HR) individuals (29 later developed mood disorder after a median time of 4.95 years), and 89 healthy controls (C-well) with no familial risk from the Scottish Bipolar Family Study (age 15-27, 64% female). Voxel-wise analyses of covariance were conducted to compare the associations between each seed region in visual, auditory, motor, speech, semantic, executive-control, salience and default-mode networks and the whole brain signal. SC maps were compared for (a) HR(all) versus C-well individuals, and (b) between those who remained well (HR-well), versus those who subsequently developed mood disorder (HR-MD), and C-well. RESULTS There were no significant differences between HR(all) and C-well individuals. On splitting the HR group based on subsequent clinical outcome, the HR-MD group however displayed greater baseline SC in the salience and executive-control network, and HR-well individuals showed less SC in the salience network, compared to C-well, respectively (P < .001). CONCLUSIONS These findings indicate differences in network-level inter-regional relationships, especially within the salience network, which precede onset of mood disorder in those at familial risk.
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Affiliation(s)
- Kareen Heinze
- School of PsychologyUniversity of BirminghamBirminghamUK,Institute for Mental HealthUniversity of BirminghamBirminghamUK,Centre for Human Brain HealthUniversity of BirminghamBirminghamUK
| | - Xueyi Shen
- Division of PsychiatryUniversity of EdinburghEdinburghUK
| | - Emma Hawkins
- Division of PsychiatryUniversity of EdinburghEdinburghUK
| | | | - Laura de Nooij
- Division of PsychiatryUniversity of EdinburghEdinburghUK
| | | | - Stephen J. Wood
- School of PsychologyUniversity of BirminghamBirminghamUK,Institute for Mental HealthUniversity of BirminghamBirminghamUK,Orygen, The National Centre of Excellence in Youth Mental HealthMelbourneVic.Australia,Centre for Youth Mental HealthUniversity of MelbourneMelbourneVic.Australia
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22
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Abstract
Psychotic disorders are severe, debilitating, and even fatal. The development of targeted and effective interventions for psychosis depends upon on clear understanding of the timing and nature of disease progression to target processes amenable to intervention. Strong evidence suggests early and ongoing neuroprogressive changes, but timing and inflection points remain unclear and likely differ across cognitive, clinical, and brain measures. Additionally, granular evidence across modalities is particularly sparse in the "bridging years" between first episode and established illness-years that may be especially critical for improving outcomes and during which interventions may be maximally effective. Our objective is the systematic, multimodal characterization of neuroprogression through the early course of illness in a cross-diagnostic sample of patients with psychosis. We aim to (1) interrogate neurocognition, structural brain measures, and network connectivity at multiple assessments over the first eight years of illness to map neuroprogressive trajectories, and (2) examine trajectories as predictors of clinical and functional outcomes. We will recruit 192 patients with psychosis and 36 healthy controls. Assessments will occur at baseline and 8- and 16-month follow ups using clinical, cognitive, and imaging measures. We will employ an accelerated longitudinal design (ALD), which permits ascertainment of data across a longer timeframe and at more frequent intervals than would be possible in a single cohort longitudinal study. Results from this study are expected to hasten identification of actionable treatment targets that are closely associated with clinical outcomes, and identify subgroups who share common neuroprogressive trajectories toward the development of individualized treatments.
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23
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Spreng RN, DuPre E, Ji JL, Yang G, Diehl C, Murray JD, Pearlson GD, Anticevic A. Structural Covariance Reveals Alterations in Control and Salience Network Integrity in Chronic Schizophrenia. Cereb Cortex 2019; 29:5269-5284. [PMID: 31066899 PMCID: PMC6918933 DOI: 10.1093/cercor/bhz064] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2015] [Revised: 02/07/2019] [Accepted: 02/07/2019] [Indexed: 12/20/2022] Open
Abstract
Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ.
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Affiliation(s)
- R Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Departments of Psychiatry and Psychology, McGill University, Montreal, QC, Canada
| | - Elizabeth DuPre
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jie Lisa Ji
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Genevieve Yang
- Department of Psychiatry, Mount Sinai School of Medicine, New York, NY
| | - Caroline Diehl
- Department of Psychology, University of California at Los Angeles, Los Angeles, CA
| | - John D Murray
- Center for Neural Science, New York University, New York, NY, USA
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, CT, USA
- Center for Neural Science, New York University, New York, NY, USA
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychology, Yale University, CT, USA
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, CT, USA
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24
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Systematic review and multi-modal meta-analysis of magnetic resonance imaging findings in 22q11.2 deletion syndrome: Is more evidence needed? Neurosci Biobehav Rev 2019; 107:143-153. [DOI: 10.1016/j.neubiorev.2019.09.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 08/07/2019] [Accepted: 09/02/2019] [Indexed: 11/20/2022]
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25
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Li XB, Wang LB, Xiong YB, Bo QJ, He F, Li F, Hou WP, Wen YJ, Wang XQ, Yang NB, Mao Z, Dong QH, Zhang FF, Yang R, Wang D, Xiang YT, Zhu YY, Tang YL, Yang Z, Wang CY. Altered resting-state functional connectivity of the insula in individuals with clinical high-risk and patients with first-episode schizophrenia. Psychiatry Res 2019; 282:112608. [PMID: 31655405 DOI: 10.1016/j.psychres.2019.112608] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 10/09/2019] [Accepted: 10/10/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVES Abnormalities in insular functional connectivity have been implicated in many clinical features of schizophrenia. The aim of this study was to determine to what degree such abnormalities occur in individuals with clinical high risk for psychosis (CHR), and whether which is associated with symptom severity. METHODS Resting-state fMRI data were collected from 47 healthy controls, 24 CHR individuals and 19 patients with first-episode schizophrenia. Using the posterior, dorsal and ventral insular subregions as separate seeds, we examined resting-state functional connectivity differences between different groups and the association between concurrent symptom severity and dysconnectivity. RESULTS Compared with healthy controls, both CHR individuals and schizophrenia patients showed hypoconnectivity between posterior insula (PI) and somatosensory areas, and between dorsal anterior insula (dAI) and putamen. Schizophrenia patients also showed dAI and ventral anterior insula(vAI) hyperconnectivity with visual areas relative to controls and CHR individuals. Correlation analysis revealed that dAI functional connectivity with superior temporal gyrus was positively correlated with positive symptoms of CHR, and vAI connectivity with dorsolateral prefrontal cortex was negatively correlated with the severity of the symptoms of first-episode schizophrenia. CONCLUSIONS Our findings suggest that insular functional dysconnectivity with the sensory cortex may be a system-level neural substrate preceding the onset of psychosis.
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Affiliation(s)
- Xian-Bin Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lu-Bin Wang
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Yan-Bing Xiong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qi-Jing Bo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fan He
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Feng Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen-Peng Hou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Jie Wen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xue-Qi Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ning-Bo Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Zhen Mao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qian-Hong Dong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fei-Fei Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Rui Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Di Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Tao Xiang
- Unit of Psychiatry, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Center for Cognition and Brain Sciences, University of Macau, Macao SAR, China
| | - Yu-Yang Zhu
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Yi-Lang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Zheng Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China; Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Chuan-Yue Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
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26
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Tang Y, Pasternak O, Kubicki M, Rathi Y, Zhang T, Wang J, Li H, Woodberry KA, Xu L, Qian Z, Zhu A, Whitfield-Gabrieli S, Keshavan MS, Niznikiewicz M, Stone WS, McCarley RW, Shenton ME, Wang J, Seidman LJ. Altered Cellular White Matter But Not Extracellular Free Water on Diffusion MRI in Individuals at Clinical High Risk for Psychosis. Am J Psychiatry 2019; 176:820-828. [PMID: 31230461 PMCID: PMC7142275 DOI: 10.1176/appi.ajp.2019.18091044] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
OBJECTIVE Detecting brain abnormalities in clinical high-risk populations before the onset of psychosis is important for tracking pathological pathways and for identifying possible intervention strategies that may impede or prevent the onset of psychotic disorders. Co-occurring cellular and extracellular white matter alterations have previously been implicated after a first psychotic episode. The authors investigated whether or not cellular and extracellular alterations are already present in a predominantly medication-naive cohort of clinical high-risk individuals experiencing attenuated psychotic symptoms. METHODS Fifty individuals at clinical high risk, of whom 40 were never medicated, were compared with 50 healthy control subjects, group-matched for age, gender, and parental socioeconomic status. 3-T multishell diffusion MRI data were obtained to estimate free-water imaging white matter measures, including fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). RESULTS Significantly lower FAT was observed in the clinical high-risk group compared with the healthy control group, but no statistically significant FW alterations were observed between groups. Lower FAT in the clinical high-risk group was significantly associated with a decline in Global Assessment of Functioning Scale (GAF) score compared with highest GAF score in the previous 12 months. CONCLUSIONS Cellular but not extracellular alterations characterized the clinical high-risk group, especially in those who experienced a decline in functioning. These cellular changes suggest an early deficit that possibly reflects a predisposition to develop attenuated psychotic symptoms. In contrast, extracellular alterations were not observed in this clinical high-risk sample, suggesting that previously reported extracellular abnormalities may reflect an acute response to psychosis, which plays a more prominent role closer to or at onset of psychosis.
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Affiliation(s)
- Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China;,Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- 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
| | - 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
| | - Yogesh Rathi
- 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
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China;,Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Junjie Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China;,Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Huijun Li
- Department of Psychology, Florida A&M University, Tallahassee, FL, USA
| | - Kristen A. Woodberry
- Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhenying Qian
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Anni Zhu
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan Whitfield-Gabrieli
- McGovern Institute for Brain Research and Poitras Center for Affective Disorders Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matcheri S. Keshavan
- Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Margaret Niznikiewicz
- Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - William S. Stone
- Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Robert W. McCarley
- Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Martha E. Shenton
- 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;,Research and Development, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China;,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China;,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, China
| | - Larry J. Seidman
- Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA;,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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27
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Sánchez-González A, Oliveras I, Río-Álamos C, Piludu MA, Gerbolés C, Tapias-Espinosa C, Tobeña A, Aznar S, Fernández-Teruel A. Dissociation between schizophrenia-relevant behavioral profiles and volumetric brain measures after long-lasting social isolation in Roman rats. Neurosci Res 2019; 155:43-55. [PMID: 31306676 DOI: 10.1016/j.neures.2019.07.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 07/02/2019] [Accepted: 07/05/2019] [Indexed: 11/29/2022]
Abstract
Social isolation rearing of rodents is an environmental manipulation known to induce or potentiate psychotic-like symptoms and attentional and cognitive impairments relevant for schizophrenia. When subjected to a 28-week isolation rearing treatment, the Roman high-avoidance (RHA-I) rats display the common behavioral social isolation syndrome, with prepulse inhibition (PPI) deficits, hyperactivity, increased anxiety responses and learning/memory impairments when compared to their low-avoidance (RLA-I) counterparts. These results add face validity to the RHA-I rats as an animal model for schizophrenia-relevant behavioral and cognitive profiles and confirm previous results. The aim here was to further investigate the neuroanatomical effects of the isolation rearing, estimated through volume differences in medial prefrontal cortex (mPFC), dorsal striatum (dSt) and hippocampus (HPC). Results showed a global increase in volume in the mPFC in the isolated rats of both strains, as well as strain effects (RLA > RHA) in the three brain regions. These unexpected but robust results, might have unveiled some kind of compensatory mechanisms due to the particularly long-lasting isolation rearing period, much longer than those commonly used in the literature (which usually range from 4 to 12 weeks).
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Affiliation(s)
- A Sánchez-González
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain.
| | - I Oliveras
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - C Río-Álamos
- Dept. Psychology, School of Medicine, Austral University of Chile, Valdivia, Chile
| | - M A Piludu
- Dept. of Life and Environmental Sciences, Section of Pharmaceutical, Pharmacological and Nutraceutical Sciences, University of Cagliari, Cagliari, Italy
| | - C Gerbolés
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - C Tapias-Espinosa
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - A Tobeña
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - S Aznar
- Research Laboratory for Stereology and Neuroscience, Bispebjerg and Frederiksberg Hospitals, Copenhagen, Denmark.
| | - A Fernández-Teruel
- Dept. Psychiatry & Forensic Medicine, Institute of Neurosciences, Universidad Autónoma de Barcelona, Barcelona, Spain.
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28
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Ding Y, Ou Y, Pan P, Shan X, Chen J, Liu F, Zhao J, Guo W. Brain structural abnormalities as potential markers for detecting individuals with ultra-high risk for psychosis: A systematic review and meta-analysis. Schizophr Res 2019; 209:22-31. [PMID: 31104914 DOI: 10.1016/j.schres.2019.05.015] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Revised: 02/28/2019] [Accepted: 05/06/2019] [Indexed: 02/01/2023]
Abstract
OBJECTIVE This study aims to determine whether structural alterations can be used as neuroimaging markers to detect individuals with ultra-high risk (UHR) for psychosis for the diagnosis of schizophrenia and improvement of treatment outcomes. METHODS Embase and Pubmed databases were searched for related studies in July 2018. The search was performed without restriction on time and regions or languages. A total of 188 articles on voxel-based morphometry (VBM) and 96 articles on cortical thickness were obtained, and another 6 articles were included after the reference lists were checked. Our researchers assessed and extracted the data in accordance with the PRISMA guideline. The data were processed with a seed-based mapping method. RESULTS Fourteen VBM and nine cortical thickness studies were finally included in our study. In individuals with UHR, the gray matter volumes in the bilateral median cingulate (Z = 1.034), the right fusiform gyrus (Z = 1.051), the left superior temporal gyrus (Z = 1.048), and the right thalamus (Z = 1.039) increased relative to those of healthy controls. By contrast, the gray matter volumes in the right gyrus rectus (Z = -2.109), the right superior frontal gyrus (Z = -2.321), and the left superior frontal gyrus (Z = -2.228) decreased. The robustness of these findings was verified through Jackknife sensitivity analysis, and heterogeneity across studies was low. Typically, cortical thickness alterations were not detected in individuals with UHR. CONCLUSIONS Structural abnormalities of the thalamocortical circuit may underpin the neurophysiology of psychosis and mark the vulnerability of transition to psychosis in UHR subjects.
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Affiliation(s)
- Yudan Ding
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Yangpan Ou
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Pan Pan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Xiaoxiao Shan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Jindong Chen
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Wenbin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China.
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29
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Ge R, Kot P, Liu X, Lang DJ, Wang JZ, Honer WG, Vila-Rodriguez F. Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults. Hum Brain Mapp 2019; 40:3738-3752. [PMID: 31115118 DOI: 10.1002/hbm.24628] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 03/25/2019] [Accepted: 04/29/2019] [Indexed: 12/31/2022] Open
Abstract
The hippocampus is a key brain region that participates in a range of cognitive and affective functions, and is involved in the etiopathogenesis of numerous neuropsychiatric disorders. The structural complexity and functional diversity of the hippocampus suggest the existence of structural and functional subdivisions within this structure. For the first time, we parcellated the human hippocampus with two independent data sets, each of which consisted of 198 T1-weighted structural magnetic resonance imaging (sMRI) images of healthy young subjects. The method was based on gray matter volume (GMV) covariance, which was quantified by a bivariate voxel-to-voxel linear correlation approach, as well as a multivariate masked independent component analysis approach. We subsequently interrogated the relationship between the GMV covariance patterns and the functional connectivity patterns of the hippocampal subregions using sMRI and resting-state functional MRI (fMRI) data from the same participants. Seven distinct GMV covariance-based subregions were identified for bilateral hippocampi, with robust reproducibility across the two data sets. We further demonstrated that the structural covariance patterns of the hippocampal subregions had a correspondence with the intrinsic functional connectivity patterns of these subregions. Together, our results provide a topographical configuration of the hippocampus with converging structural and functional support. The resulting subregions may improve our understanding of the hippocampal connectivity and functions at a subregional level, which provides useful parcellations and masks for future neuroscience and clinical research on the structural and/or functional connectivity of the hippocampus.
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Affiliation(s)
- Ruiyang Ge
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Paul Kot
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Xiang Liu
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Donna J Lang
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jane Z Wang
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, British Columbia, Canada
| | - William G Honer
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Fidel Vila-Rodriguez
- Non-Invasive Neurostimulation Therapies (NINET) Laboratory, Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
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30
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Li RR, Lyu HL, Liu F, Lian N, Wu RR, Zhao JP, Guo WB. Altered functional connectivity strength and its correlations with cognitive function in subjects with ultra-high risk for psychosis at rest. CNS Neurosci Ther 2018; 24:1140-1148. [PMID: 29691990 DOI: 10.1111/cns.12865] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 03/28/2018] [Accepted: 03/29/2018] [Indexed: 12/21/2022] Open
Abstract
AIMS Evidence of altered structural and functional connectivity in the frontal-occipital network is associated with cognitive deficits in patients with schizophrenia. However, the altered patterns of functional connectivity strength (FCS) in individuals with ultra-high risk (UHR) for psychosis remain unknown. In this study, whole-brain FCS was assessed to examine the altered patterns of FCS in UHR subjects. METHODS A total of 34 UHR subjects and 37 age- and sex-matched healthy controls were enrolled to undergo resting-state functional magnetic resonance imaging. The imaging data were analyzed using the graph theory method. RESULTS Compared with healthy controls, UHR subjects showed significantly decreased FCS in the left middle frontal gyrus and significantly increased FCS in the left calcarine cortex. The FCS values in the left middle frontal gyrus were positively correlated to the scores of the Brief Assessments of Cognitionin Schizophrenia Symbol Coding Test (r = 0.366, P = 0.033) in the UHR subjects. A negative correlation was found between the FCS values in the left calcarine cortex and the scores of the Stroop color-naming test (r = -0.475, P = 0.016) in the UHR subjects. A combination of the FCS values in the 2 brain areas showed an accuracy of 87.32%, a sensitivity of 73.53%, and a specificity of 100% for distinguishing UHR subjects from healthy controls. CONCLUSIONS Significantly altered FCS in the frontal-occipital network is observed in the UHR subjects. Furthermore, decreased FCS in the left middle frontal gyrus and increased FCS in the left calcarine have significant correlations with the cognitive measures of the UHR subjects and thus improve our understanding of the underlying pathophysiological mechanisms of schizophrenia. Moreover, a combination of the FCS values in the 2 brain areas can serve as a potential image marker to distinguish UHR subjects from healthy controls.
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Affiliation(s)
- Ran-Ran Li
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Hai-Long Lyu
- Department of Psychiatry, The First Affiliated Hospital, The Key Laboratory of Mental Disorder's Management of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Nan Lian
- The First Affiliated Hospital, Zhengzhou University, Zhengzhou, China
| | - Ren-Rong Wu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jing-Ping Zhao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Wen-Bin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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31
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Sasabayashi D, Takayanagi Y, Takahashi T, Koike S, Yamasue H, Katagiri N, Sakuma A, Obara C, Nakamura M, Furuichi A, Kido M, Nishikawa Y, Noguchi K, Matsumoto K, Mizuno M, Kasai K, Suzuki M. Increased Occipital Gyrification and Development of Psychotic Disorders in Individuals With an At-Risk Mental State: A Multicenter Study. Biol Psychiatry 2017; 82:737-745. [PMID: 28709499 DOI: 10.1016/j.biopsych.2017.05.018] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 05/17/2017] [Accepted: 05/18/2017] [Indexed: 12/13/2022]
Abstract
BACKGROUND Anomalies of brain gyrification have been reported in schizophrenia, possibly reflecting its neurodevelopmental pathology. However, it remains elusive whether individuals at risk for psychotic disorders exhibit deviated gyrification patterns, and whether such findings, if present, are predictive of transition to psychotic disorders. METHODS This multicenter magnetic resonance imaging study investigated brain gyrification and its relationship to later transition to psychotic disorders in a large sample of at-risk mental state (ARMS) individuals. T1-weighted magnetic resonance imaging scans were obtained from 104 ARMS individuals, of whom 21 (20.2%) exhibited the transition to psychotic disorders during clinical follow-up (mean = 4.9 years, SD = 2.6 years), and 104 healthy control subjects at 4 different sites. The local gyrification index (LGI) of the entire cortex was compared across the groups using FreeSurfer software. RESULTS Compared with the control subjects, ARMS individuals showed a significantly higher LGI in widespread cortical areas, including the bilateral frontal, temporal, parietal, and occipital regions, which was partly associated with prodromal symptomatology. ARMS individuals who exhibited the transition to psychotic disorders showed a significantly higher LGI in the left occipital region compared with individuals without transition. CONCLUSIONS These findings suggested that increased LGI in diverse cortical regions might represent vulnerability to psychopathology, while increased LGI in the left occipital cortex might be related to subsequent manifestation of florid psychotic disorders as a possible surrogate marker.
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Affiliation(s)
- Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.
| | - Yoichiro Takayanagi
- 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
| | - Shinsuke Koike
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hidenori Yamasue
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Atsushi Sakuma
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Chika Obara
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
| | - Mihoko Nakamura
- 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
| | - Kyo Noguchi
- Department of Radiology, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - Kazunori Matsumoto
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan; Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Masafumi Mizuno
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
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Abstract
PURPOSE OF REVIEW Motor abnormalities are an intrinsic feature of psychosis. Neurological soft signs, Parkinsonism, dyskinesia, and other motor phenomena are frequently observed in subjects at clinical or genetic risk for psychosis as well as first-episode patients, chronic patients. Here, we review the most recent literature on motor assessments and pathophysiology in psychosis. RECENT FINDINGS Instrumental measures of fine motor performance, balance, spontaneous motor activity, and gesture indicated motor abnormalities in subjects at risk and across stages of schizophrenia. Motor phenomena are associated with distinct symptom dimensions and may indicate poor outcomes. Neuroimaging studies demonstrated altered neural maturation within critical motor networks in subjects at risk. Furthermore, specific categories of motor dysfunction were associated with distinct structural and functional alterations in the motor system in schizophrenia. Motor abnormalities provide a unique window into the pathobiology of psychosis and have the potential to guide screening, staging, and outcome prediction.
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Affiliation(s)
- Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Murtenstrasse 21, 3008, Bern, Switzerland.
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA.,Department of Psychiatry, Northwestern University, Evanston, IL, USA.,Department of Medical Social Sciences, Northwestern University, Evanston, IL, USA.,Institute for Policy Research, Northwestern University, Evanston, IL, USA.,Institute for Developmental Science, Northwestern University, Evanston, IL, USA
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33
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Dukart J, Smieskova R, Harrisberger F, Lenz C, Schmidt A, Walter A, Huber C, Riecher-Rössler A, Simon A, Lang UE, Fusar-Poli P, Borgwardt S. Age-related brain structural alterations as an intermediate phenotype of psychosis. J Psychiatry Neurosci 2017; 42:307-319. [PMID: 28459416 PMCID: PMC5573573 DOI: 10.1503/jpn.160179] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND There is only limited agreement with respect to location, directionality and functional implications of brain structural alterations observed in patients with schizophrenia. Additionally, their link to occurrence of psychotic symptoms remains unclear. A viable way of addressing these questions is to examine populations in an at-risk mental state (ARMS) before the transition to psychosis. METHODS We tested for structural brain alterations in individuals in an ARMS compared with healthy controls and patients with first-episode psychosis (FEP) using voxel-based morphometry and measures of cortical thickness. Furthermore, we evaluated if these alterations were modified by age and whether they were linked to the observed clinical symptoms. RESULTS Our sample included 59 individuals with ARMS, 26 healthy controls and 59 patients with FEP. We found increased grey matter volume and cortical thickness in individuals with ARMS and a similar pattern of structural alterations in patients with FEP. We further found stronger age-related reductions in grey matter volume and cortical thickness in both patients with FEP and individuals with ARMS, linking these alterations to observed clinical symptoms. LIMITATIONS The ARMS group comprised subgroups with heterogeneous levels of psychosis risk and medication status. Furthermore, the cross-sectional nature of our study and the reduced number of older patients limit conclusions with respect to observed interactions with age. CONCLUSION Our findings on consistent structural alterations in individuals with ARMS and patients with FEP and their link to clinical symptoms have major implications for understanding their time of occurrence and relevance to psychotic symptoms. Interactions with age found for these alterations may explain the heterogeneity of findings reported in the literature.
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Affiliation(s)
- Juergen Dukart
- Correspondence to: J. Dukart, Biomarkers & Clinical Imaging, NORD DTA, F. Hoffmann-La Roche, Grenzacherstrasse 170, 4070 Basel, Switzerland;
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Geng X, Li G, Lu Z, Gao W, Wang L, Shen D, Zhu H, Gilmore JH. Structural and Maturational Covariance in Early Childhood Brain Development. Cereb Cortex 2017; 27:1795-1807. [PMID: 26874184 DOI: 10.1093/cercor/bhw022] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development.
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Affiliation(s)
- Xiujuan Geng
- Department of Psychiatry.,State Key Lab of Brain and Cognitive Sciences, University of Hong Kong, Hong Kong, Hong Kong.,Laboratory of Neuropsychology and Laboratory of Social Cognitive and Affective Neuroscience, University of Hong Kong
| | - Gang Li
- IDEA Lab, Department of Radiology and BRIC
| | - Zhaohua Lu
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Wei Gao
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC 27514, USA
| | - Li Wang
- IDEA Lab, Department of Radiology and BRIC
| | - Dinggang Shen
- IDEA Lab, Department of Radiology and BRIC.,Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
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Bartholomeusz CF, Cropley VL, Wannan C, Di Biase M, McGorry PD, Pantelis C. Structural neuroimaging across early-stage psychosis: Aberrations in neurobiological trajectories and implications for the staging model. Aust N Z J Psychiatry 2017; 51:455-476. [PMID: 27733710 DOI: 10.1177/0004867416670522] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE This review critically examines the structural neuroimaging evidence in psychotic illness, with a focus on longitudinal imaging across the first-episode psychosis and ultra-high-risk of psychosis illness stages. METHODS A thorough search of the literature involving specifically longitudinal neuroimaging in early illness stages of psychosis was conducted. The evidence supporting abnormalities in brain morphology and altered neurodevelopmental trajectories is discussed in the context of a clinical staging model. RESULTS In general, grey matter (and, to a lesser extent, white matter) declines across multiple frontal, temporal (especially superior regions), insular and parietal regions during the first episode of psychosis, which has a steeper trajectory than that of age-matched healthy counterparts. Although the ultra-high-risk of psychosis literature is considerably mixed, evidence indicates that certain volumetric structural aberrations predate psychotic illness onset (e.g. prefrontal cortex thinning), while other abnormalities present in ultra-high-risk of psychosis populations are potentially non-psychosis-specific (e.g. hippocampal volume reductions). CONCLUSION We highlight the advantages of longitudinal designs, discuss the implications such studies have on clinical staging and provide directions for future research.
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Affiliation(s)
- Cali F Bartholomeusz
- 1 Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- 2 Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- 3 Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Vanessa L Cropley
- 3 Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Cassandra Wannan
- 1 Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- 2 Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
- 3 Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Maria Di Biase
- 3 Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Patrick D McGorry
- 1 Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- 2 Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Christos Pantelis
- 3 Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- 4 Centre for Neural Engineering, Department of Electrical and Electronic Engineering, The University of Melbourne, Carlton South, VIC, Australia
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Aberrant Temporal Connectivity in Persons at Clinical High Risk for Psychosis. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2017; 2:696-705. [PMID: 29202110 DOI: 10.1016/j.bpsc.2016.12.008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Background Schizophrenia, a neurodevelopmental disorder, involves abnormalities in functional connectivity (FC) across distributed neural networks, which are thought to antedate the emergence of psychosis. In a cohort of adolescents and young adults at clinical high risk (CHR) for psychosis, we applied data-driven approaches to resting-state fMRI data so as to systematically characterize FC abnormalities during this period and determine whether these abnormalities are associated with psychosis risk and severity of psychotic symptoms. Methods Fifty-one CHR participants and 47 matched healthy controls (HCs) were included in our analyses. Twelve of these CHR participants developed psychosis within 3.9 years. We estimated one multivariate measure of FC and studied its relationship to CHR status, conversion to psychosis and positive symptom severity. Results Multivariate analyses revealed between-group differences in whole-brain connectivity patterns of bilateral temporal areas, mostly affecting their functional connections to the thalamus. Further, more severe positive symptoms were associated with greater connectivity abnormalities in the anterior cingulate and frontal cortex. Conclusions Our study demonstrates that the well-established FC abnormalities of the thalamus and temporal areas observed in schizophrenia are also present in the CHR period, with aberrant connectivity of the temporal cortex most associated with psychosis risk.
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Schilbach L, Derntl B, Aleman A, Caspers S, Clos M, Diederen KMJ, Gruber O, Kogler L, Liemburg EJ, Sommer IE, Müller VI, Cieslik EC, Eickhoff SB. Differential Patterns of Dysconnectivity in Mirror Neuron and Mentalizing Networks in Schizophrenia. Schizophr Bull 2016; 42:1135-48. [PMID: 26940699 PMCID: PMC4988733 DOI: 10.1093/schbul/sbw015] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Impairments of social cognition are well documented in patients with schizophrenia (SCZ), but the neural basis remains poorly understood. In light of evidence that suggests that the "mirror neuron system" (MNS) and the "mentalizing network" (MENT) are key substrates of intersubjectivity and joint action, it has been suggested that dysfunction of these neural networks may underlie social difficulties in SCZ patients. Additionally, MNS and MENT might be associated differently with positive vs negative symptoms, given prior social cognitive and symptom associations. We assessed resting state functional connectivity (RSFC) in meta-analytically defined MNS and MENT networks in this patient group. Magnetic resonance imaging (MRI) scans were obtained from 116 patients and 133 age-, gender- and movement-matched healthy controls (HC) at 5 different MRI sites. Network connectivity was analyzed for group differences and correlations with clinical symptoms. Results demonstrated decreased connectivity within the MNS and also the MENT in patients compared to controls. Notably, dysconnectivity of the MNS was related to symptom severity, while no such relationship was observed for the MENT. In sum, these findings demonstrate that differential patterns of dysconnectivity exist in SCZ patients, which may contribute differently to the interpersonal difficulties commonly observed in the disorder.
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Affiliation(s)
- Leonhard Schilbach
- Max Planck Institute of Psychiatry, Munich, Germany;,Department of Psychiatry, University Hospital Cologne, Cologne, Germany;,These authors contributed equally
| | - Birgit Derntl
- Department of Psychiatry, Psychotherapy & Psychosomatics, RWTH University Aachen, Aachen, Germany; Jülich Aachen Research Alliance, JARA-BRAIN, Translational Brain Medicine, Jülich-Aachen, Germany; Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany;
| | - Andre Aleman
- BCN Neuroimaging Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany
| | - Mareike Clos
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany
| | - Kelly M. J. Diederen
- Neuroscience Division, University Medical Center Utrecht & Rudolf Magnus Institute for Neuroscience, Utrecht, Netherlands
| | - Oliver Gruber
- Department of Psychiatry and Psychotherapy, University of Göttingen, Göttingen, Germany;,Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - Lydia Kogler
- Department of Psychiatry, Psychotherapy & Psychosomatics, RWTH University Aachen, Aachen, Germany;,Jülich Aachen Research Alliance, JARA-BRAIN, Translational Brain Medicine, Jülich-Aachen, Germany;,Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Edith J. Liemburg
- BCN Neuroimaging Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Iris E. Sommer
- Neuroscience Division, University Medical Center Utrecht & Rudolf Magnus Institute for Neuroscience, Utrecht, Netherlands
| | - Veronika I. Müller
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
| | - Edna C. Cieslik
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich, Germany;,Institute of Clinical Neuroscience and Medical Psychology, HHU Duesseldorf, Duesseldorf, Germany
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Flores G, Morales-Medina JC, Diaz A. Neuronal and brain morphological changes in animal models of schizophrenia. Behav Brain Res 2016; 301:190-203. [DOI: 10.1016/j.bbr.2015.12.034] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Revised: 12/15/2015] [Accepted: 12/18/2015] [Indexed: 12/14/2022]
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Solé-Padullés C, Castro-Fornieles J, de la Serna E, Romero S, Calvo A, Sánchez-Gistau V, Padrós-Fornieles M, Baeza I, Bargalló N, Frangou S, Sugranyes G. Altered Cortico-Striatal Connectivity in Offspring of Schizophrenia Patients Relative to Offspring of Bipolar Patients and Controls. PLoS One 2016; 11:e0148045. [PMID: 26885824 PMCID: PMC4757444 DOI: 10.1371/journal.pone.0148045] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Accepted: 01/12/2016] [Indexed: 02/07/2023] Open
Abstract
Schizophrenia (SZ) and bipolar disorder (BD) share clinical features, genetic risk factors and neuroimaging abnormalities. There is evidence of disrupted connectivity in resting state networks in patients with SZ and BD and their unaffected relatives. Resting state networks are known to undergo reorganization during youth coinciding with the period of increased incidence for both disorders. We therefore focused on characterizing resting state network connectivity in youth at familial risk for SZ or BD to identify alterations arising during this period. We measured resting-state functional connectivity in a sample of 106 youth, aged 7-19 years, comprising offspring of patients with SZ (N = 27), offspring of patients with BD (N = 39) and offspring of community control parents (N = 40). We used Independent Component Analysis to assess functional connectivity within the default mode, executive control, salience and basal ganglia networks and define their relationship to grey matter volume, clinical and cognitive measures. There was no difference in connectivity within any of the networks examined between offspring of patients with BD and offspring of community controls. In contrast, offspring of patients with SZ showed reduced connectivity within the left basal ganglia network compared to control offspring, and they showed a positive correlation between connectivity in this network and grey matter volume in the left caudate. Our findings suggest that dysconnectivity in the basal ganglia network is a robust correlate of familial risk for SZ and can be detected during childhood and adolescence.
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Affiliation(s)
| | - Josefina Castro-Fornieles
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
- Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
| | - Elena de la Serna
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
| | - Soledad Romero
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
| | - Anna Calvo
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Magnetic Resonance Imaging Core facility, Hospital Clinic of Barcelona, Barcelona, Spain
- Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), GIB-UB, Barcelona, Spain
| | - Vanessa Sánchez-Gistau
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
| | - Marta Padrós-Fornieles
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
| | - Inmaculada Baeza
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
| | - Núria Bargalló
- Biomedical Research Networking Centre Consortium (CIBERSAM), Barcelona, Spain
- Magnetic Resonance Imaging Core facility, Hospital Clinic of Barcelona, Barcelona, Spain
- Centre for Diagnostic Imaging (CDI), Hospital Clinic of Barcelona, Barcelona, Spain
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, United States of America
| | - Gisela Sugranyes
- August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
- Department of Child and Adolescent Psychiatry and Psychology, SGR489, Institute of Neuroscience, Hospital Clínic of Barcelona, Barcelona, Spain
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Cannon TD. How Schizophrenia Develops: Cognitive and Brain Mechanisms Underlying Onset of Psychosis. Trends Cogn Sci 2015; 19:744-756. [PMID: 26493362 DOI: 10.1016/j.tics.2015.09.009] [Citation(s) in RCA: 144] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2015] [Revised: 09/10/2015] [Accepted: 09/11/2015] [Indexed: 12/12/2022]
Abstract
Identifying cognitive and neural mechanisms involved in the development of schizophrenia requires longitudinal observation of individuals prior to onset. Here recent studies of prodromal individuals who progress to full psychosis are briefly reviewed in relation to models of schizophrenia pathophysiology. Together, this body of work suggests that disruption in brain connectivity, driven primarily by a progressive reduction in dendritic spines on cortical pyramidal neurons, may represent a key triggering mechanism. The earliest disruptions appear to be in circuits involved in referencing experiences according to time, place, and agency, which may result in a failure to recognize particular cognitions as self-generated or to constrain interpretations of the meaning of events based on prior experiences, providing the scaffolding for faulty reality testing.
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Affiliation(s)
- Tyrone D Cannon
- Department of Psychology, Yale University, 2 Hillhouse Avenue, P.O. Box 208205, New Haven, CT 06520, USA.
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Cannon TD. Network dysconnectivity: a psychosis-triggering mechanism? Biol Psychiatry 2015; 77:927-8. [PMID: 25959565 DOI: 10.1016/j.biopsych.2015.03.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 03/18/2015] [Indexed: 02/03/2023]
Affiliation(s)
- Tyrone D Cannon
- Departments of Psychology and Psychiatry, Yale University, New Haven, Connecticut..
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