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Panikratova YR, Tomyshev AS, Abdullina EG, Rodionov GI, Arkhipov AY, Tikhonov DV, Bozhko OV, Kaleda VG, Strelets VB, Lebedeva IS. Resting-state functional connectivity correlates of brain structural aging in schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01837-5. [PMID: 38914851 DOI: 10.1007/s00406-024-01837-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/27/2024] [Indexed: 06/26/2024]
Abstract
A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls. Eighty-four male schizophrenia patients and eighty-six male healthy controls underwent structural MRI and resting-state fMRI. The brain-predicted age difference (b-PAD) was a measure of brain structural aging. Resting-state fMRI was applied to obtain global correlation (GCOR) maps comprising voxelwise values of the strength and sign of functional connectivity of a given voxel with the rest of the brain. Schizophrenia patients had higher b-PAD compared to controls (mean between-group difference + 2.9 years). Greater b-PAD in schizophrenia patients, compared to controls, was associated with lower whole-brain functional connectivity of a region in frontal orbital cortex, inferior frontal gyrus, Heschl's Gyrus, plana temporale and polare, insula, and opercular cortices of the right hemisphere (rFTI). According to post hoc seed-based correlation analysis, decrease of functional connectivity with the posterior cingulate gyrus, left superior temporal cortices, as well as right angular gyrus/superior lateral occipital cortex has mainly driven the results. Lower functional connectivity of the rFTI was related to worse verbal working memory and language production. Our findings demonstrate that well-established frontotemporal functional abnormalities in schizophrenia are related to increased brain structural aging.
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Affiliation(s)
| | | | | | - Georgiy I Rodionov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | - Andrey Yu Arkhipov
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
| | | | | | | | - Valeria B Strelets
- Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Moscow, Russia
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2
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Kittleson AR, Woodward ND, Heckers S, Sheffield JM. The insula: Leveraging cellular and systems-level research to better understand its roles in health and schizophrenia. Neurosci Biobehav Rev 2024; 160:105643. [PMID: 38531518 DOI: 10.1016/j.neubiorev.2024.105643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 03/04/2024] [Accepted: 03/22/2024] [Indexed: 03/28/2024]
Abstract
Schizophrenia is a highly heterogeneous disorder characterized by a multitude of complex and seemingly non-overlapping symptoms. The insular cortex has gained increasing attention in neuroscience and psychiatry due to its involvement in a diverse range of fundamental human experiences and behaviors. This review article provides an overview of the insula's cellular and anatomical organization, functional and structural connectivity, and functional significance. Focusing on specific insula subregions and using knowledge gained from humans and preclinical studies of insular tracings in non-human primates, we review the literature and discuss the functional roles of each subregion, including in somatosensation, interoception, salience processing, emotional processing, and social cognition. Building from this foundation, we then extend these findings to discuss reported abnormalities of these functions in individuals with schizophrenia, implicating insular involvement in schizophrenia pathology. This review underscores the insula's vast role in the human experience and how abnormal insula structure and function could result in the wide-ranging symptoms observed in schizophrenia.
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Affiliation(s)
- Andrew R Kittleson
- Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN 37235, United States; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
| | - Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States.
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Rivera AD, Normanton JR, Butt AM, Azim K. The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials. Int J Mol Sci 2024; 25:4452. [PMID: 38674040 PMCID: PMC11050044 DOI: 10.3390/ijms25084452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/28/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.
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Affiliation(s)
- Andrea D. Rivera
- Department of Neuroscience, Institute of Human Anatomy, University of Padova, Via A. Gabelli 65, 35127 Padua, Italy;
| | - John R. Normanton
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
| | - Arthur M. Butt
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
- School of Pharmacy and Biomedical Science, University of Portsmouth, Hampshire PO1 2UP, UK
| | - Kasum Azim
- GliaGenesis Limited, Orchard Lea, Horns Lane, Oxfordshire, Witney OX29 8NH, UK; (J.R.N.); (K.A.)
- Independent Data Lab UG, Frauenmantelanger 31, 80937 Munich, Germany
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Wu YK, Su YA, Zhu LL, Li JT, Li Q, Dai YR, Lin JY, Li K, Si TM. Intrinsic functional connectivity correlates of cognitive deficits involving sustained attention and executive function in bipolar disorder. BMC Psychiatry 2023; 23:584. [PMID: 37568112 PMCID: PMC10416380 DOI: 10.1186/s12888-023-05083-2] [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: 04/13/2023] [Accepted: 08/07/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND The neural correlate of cognitive deficits in bipolar disorder (BD) is an issue that warrants further investigation. However, relatively few studies have examined the intrinsic functional connectivity (FC) underlying cognitive deficits involving sustained attention and executive function at both the region and network levels, as well as the different relationships between connectivity patterns and cognitive performance, in BD patients and healthy controls (HCs). METHODS Patients with BD (n = 59) and HCs (n = 52) underwent structural and resting-state functional magnetic resonance imaging and completed the Wisconsin Card Sorting Test (WCST), the continuous performance test and a clinical assessment. A seed-based approach was used to evaluate the intrinsic FC alterations in three core neurocognitive networks (the default mode network [DMN], the central executive network [CEN] and the salience network [SN]). Finally, we examined the relationship between FC and cognitive performance by using linear regression analyses. RESULTS Decreased FC was observed within the DMN, in the DMN-SN and DMN-CEN and increased FC was observed in the SN-CEN in BD. The alteration direction of regional FC was consistent with that of FC at the brain network level. Decreased FC between the left posterior cingulate cortex and right anterior cingulate cortex was associated with longer WCST completion time in BD patients (but not in HCs). CONCLUSIONS These findings emphasize the dominant role of the DMN in the psychopathology of BD and provide evidence that cognitive deficits in BD may be associated with aberrant FC between the anterior and posterior DMN.
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Affiliation(s)
- Yan-Kun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Yun-Ai Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Lin-Lin Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Ji-Tao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Qian Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - You-Ran Dai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Jing-Yu Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Ke Li
- PLA Strategic Support Force Characteristic Medical Center, Beijing, 100101, China
| | - Tian-Mei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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Yang H, Zhao X, Wang T, Zhou Z, Cheng Z, Zhao X, Cao Y. Hypoconnectivity within the cingulo-opercular network in patients with mild cognitive impairment in Chinese communities. Int J Geriatr Psychiatry 2023; 38:e5979. [PMID: 37548525 DOI: 10.1002/gps.5979] [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: 11/03/2022] [Accepted: 07/11/2023] [Indexed: 08/08/2023]
Abstract
INTRODUCTION At rest, the brain's higher cognitive systems engage in correlated activity patterns, forming networks. With mild cognitive impairment (MCI), it is essential to understand how functional connectivity within and between resting-state networks changes. This study used resting-state functional connectivity to identify significant differences within and between the cingulo-opercular network (CON) and default mode network (DMN). METHODS We assessed cognitive function in patients using the Chinese version of the Alzheimer's disease assessment scale-Cognitive subscale (ADAS-Cog). A group of MCI subjects (ages 60-83 years, n = 45) was compared to age-matched healthy controls (n = 70). Resting-state functional connectivity was used to determine functional connectivity strength within and between the CON and DMN. RESULTS Compared to healthy controls, the MCI group showed significantly lower functional connectivity within the CON (F = 10.76, df = 1, p = 0.001, FDR adjusted p = 0.003). Additionally, the MCI group displayed no distinct differences in functional connectivity within DMN (F = 0.162, df = 1, p = 0.688, FDR adjusted p = 0.688) and between CON and DMN (F = 2.270, df = 1, p = 0.135, FDR adjusted p = 0.262). Moreover, we found no correlation between ADAS-Cog and within- or between-connectivity metrics among subjects with MCI. CONCLUSIONS Our findings indicate that specific patterns of hypoconnectivity within CON circuitry may characterize MCI relative to healthy controls. This work improves our understanding of network dysfunction underlying MCI and could inform more targeted treatment.
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Affiliation(s)
- Huan Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | | | - Tenglong Wang
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Zhenhe Zhou
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Zaohuo Cheng
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Xingfu Zhao
- Wuxi Mental Health Center, Nanjing Medical University, Wuxi, China
| | - Yuping Cao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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Zovetti N, Rossetti MG, Perlini C, Brambilla P, Bellani M. Brain ageing and neurodegeneration in bipolar disorder. J Affect Disord 2023; 323:171-175. [PMID: 36435402 DOI: 10.1016/j.jad.2022.11.066] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 11/11/2022] [Accepted: 11/20/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Bipolar disorder (BD) is a psychiatric condition characterized by alternating episodes of mania and depression frequently associated with cognitive impairments. BD is associated with brain alterations in fronto-temporal and limbic networks. Recent conceptualizations view BD as a neurodegenerative disorder characterized by progressive deterioration of grey and white matter (GM, WM) volumes and accelerated brain ageing. Therefore, we conducted a review gathering neuroimaging evidence about neurodegenerative processes in BD. METHODS A literature search was conducted on the PubMed, Scopus and Web of Science databases in September 2021. After title and abstract screening of the retrieved records, 19 studies that met our inclusion criteria were included in the review. RESULTS The available evidence suggests the presence of a progressive reduction of GM volumes at the whole-brain level and in the amygdala, prefrontal regions and the anterior cingulate cortex. Conversely, WM lesions and alterations seem to emerge only in the early phases of the condition masking the effects of normal ageing. Lastly, machine learning models indicate that the gap between predicted and chronological brain age differs considerably between healthy controls and BD patients, as the latter are characterized by larger gaps. LIMITATIONS The included studies had cross-sectional study design, small sample sizes and heterogeneous methodology, and lack of control for pharmacological treatment. CONCLUSIONS BD seems to be associated with generalized age-related structural GM volumes reductions and functional brain alterations thus suggesting the presence of neurodegenerative processes. Future systematic reviews and meta-analyses should be conducted to quantify the magnitude of brain ageing-related effects in BD.
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Affiliation(s)
- Niccolò Zovetti
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Maria Gloria Rossetti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Cinzia Perlini
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Clinical Psychology, University of Verona, Verona, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
| | - Marcella Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
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Kuo SS, Roalf DR, Prasad KM, Musket CW, Rupert PE, Wood J, Gur RC, Almasy L, Gur RE, Nimgaonkar VL, Pogue-Geile MF. Age-dependent effects of schizophrenia genetic risk on cortical thickness and cortical surface area: Evaluating evidence for neurodevelopmental and neurodegenerative models of schizophrenia. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2022; 131:674-688. [PMID: 35737559 PMCID: PMC9339500 DOI: 10.1037/abn0000765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Risk for schizophrenia peaks during early adulthood, a critical period for brain development. Although several influential theoretical models have been proposed for the developmental relationship between brain pathology and clinical onset, to our knowledge, no study has directly evaluated the predictions of these models for schizophrenia developmental genetic effects on brain structure. To address this question, we introduce a framework to estimate the effects of schizophrenia genetic variation on brain structure phenotypes across the life span. Five-hundred and six participants, including 30 schizophrenia probands, 200 of their relatives (aged 12-85 years) from 32 families with at least two first-degree schizophrenia relatives, and 276 unrelated controls, underwent MRI to assess regional cortical thickness (CT) and cortical surface area (CSA). Genetic variance decomposition analyses were conducted to distinguish among schizophrenia neurogenetic effects that are most salient before schizophrenia peak age-of-risk (i.e., early neurodevelopmental effects), after peak age-of-risk (late neurodevelopmental effects), and during the later plateau of age-of-risk (neurodegenerative effects). Genetic correlations between schizophrenia and cortical traits suggested early neurodevelopmental effects for frontal and insula CSA, late neurodevelopmental effects for overall CSA and frontal, parietal, and occipital CSA, and possible neurodegenerative effects for temporal CT and parietal CSA. Importantly, these developmental neurogenetic effects were specific to schizophrenia and not found with nonpsychotic depression. Our findings highlight the potentially dynamic nature of schizophrenia genetic effects across the lifespan and emphasize the utility of integrating neuroimaging methods with developmental behavior genetic approaches to elucidate the nature and timing of risk-conferring processes in psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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The distinct disrupted plasticity in structural and functional network in mild stroke with basal ganglia region infarcts. Brain Imaging Behav 2022; 16:2199-2219. [DOI: 10.1007/s11682-022-00689-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/11/2022] [Indexed: 12/20/2022]
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9
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Burdick KE. Brain-Based Abnormalities in Bipolar Disorder: Neuroprogression (and Neurodevelopment). Biol Psychiatry 2022; 91:529-530. [PMID: 35177205 DOI: 10.1016/j.biopsych.2021.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 12/13/2021] [Indexed: 11/02/2022]
Affiliation(s)
- Katherine E Burdick
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
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Xi YB, Wu XS, Cui LB, Bai LJ, Gan SQ, Jia XY, Li X, Xu YQ, Kang XW, Guo F, Yin H. Neuroimaging-based brain-age prediction of first-episode schizophrenia and the alteration of brain age after early medication. Br J Psychiatry 2021; 220:1-8. [PMID: 35049480 DOI: 10.1192/bjp.2021.169] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
BACKGROUND Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear. AIMS To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age. METHOD The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed. RESULTS The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = -0.326, P = 0.014). CONCLUSIONS The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.
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Affiliation(s)
- Yi-Bin Xi
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), China; and Department of Radiology, Xijing Hospital, Fourth Military Medical University, China
| | - Xu-Sha Wu
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), China; and School of Medical Technology, Shaanxi University of Chinese Medicine, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, China; and Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, China
| | - Li-Jun Bai
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, China
| | - Shuo-Qiu Gan
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, China
| | - Xiao-Yan Jia
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, China
| | - Xuan Li
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, China
| | - Yong-Qiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, China
| | - Xiao-Wei Kang
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), China; and Department of Radiology, Xijing Hospital, Fourth Military Medical University, China
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Abstract
Bipolar disorder (BD) is a highly disabling mental illness that affects approximately 1% of the global population. Cognitive capacity is a strong predictor of "everyday" functional outcome in BD and should thus be considered a key treatment target. Interventions to improve cognition have been largely unsuccessful, likely due to the substantial heterogeneity inherent to the illness. It is known that 40%-60% of people with BD have cognitive impairment, yet impairment is not "one size fits all"; in fact, the literature supports discrete cognitive subtypes in BD (e.g., intact, globally impaired, and selectively impaired). Gaining a better understanding of these cognitive subtypes, their longitudinal trajectories, and their biological underpinnings will be essential for improving patient outcomes. The prevailing hypothesis for the development of cognitive impairment in BD postulates a stepwise cumulative effect of repeated mood episodes causing wear-and-tear on the brain. However, a paucity of data supports this idea at the group level. We propose that studying heterogeneity longitudinally will allow for clearer delineation of the natural history of cognitive trajectories in BD. In sum, parsing heterogeneity in BD will allow us to identify causal mechanisms and optimize treatment at the level of the individual.
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Wu Z, Gao Y, Potter T, Benoit J, Shen J, Schulz PE, Zhang Y. Interactions Between Aging and Alzheimer's Disease on Structural Brain Networks. Front Aging Neurosci 2021; 13:639795. [PMID: 34177548 PMCID: PMC8222527 DOI: 10.3389/fnagi.2021.639795] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 05/11/2021] [Indexed: 11/13/2022] Open
Abstract
Normative aging and Alzheimer's disease (AD) propagation alter anatomical connections among brain parcels. However, the interaction between the trajectories of age- and AD-linked alterations in the topology of the structural brain network is not well understood. In this study, diffusion-weighted magnetic resonance imaging (MRI) datasets of 139 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were used to document their structural brain networks. The 139 participants consist of 45 normal controls (NCs), 37 with early mild cognitive impairment (EMCI), 27 with late mild cognitive impairment (LMCI), and 30 AD patients. All subjects were further divided into three subgroups based on their age (56-65, 66-75, and 71-85 years). After the structural connectivity networks were built using anatomically-constrained deterministic tractography, their global and nodal topological properties were estimated, including network efficiency, characteristic path length, transitivity, modularity coefficient, clustering coefficient, and betweenness. Statistical analyses were then performed on these metrics using linear regression, and one- and two-way ANOVA testing to examine group differences and interactions between aging and AD propagation. No significant interactions were found between aging and AD propagation in the global topological metrics (network efficiency, characteristic path length, transitivity, and modularity coefficient). However, nodal metrics (clustering coefficient and betweenness centrality) of some cortical parcels exhibited significant interactions between aging and AD propagation, with affected parcels including left superior temporal, right pars triangularis, and right precentral. The results collectively confirm the age-related deterioration of structural networks in MCI and AD patients, providing novel insight into the cross effects of aging and AD disorder on brain structural networks. Some early symptoms of AD may also be due to age-associated anatomic vulnerability interacting with early anatomic changes associated with AD.
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Affiliation(s)
- Zhanxiong Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, China
| | - Yunyuan Gao
- Department of Intelligent Control and Robotics Institute, College of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Thomas Potter
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
| | - Julia Benoit
- Texas Institute for Measurement Evaluation and Statistics, Department of Basic Vision Sciences, University of Houston, Houston, TX, United States
| | - Jian Shen
- Neurosurgery Department, The First Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, China
| | - Paul E. Schulz
- Department of Neurology, The McGovern Medical School of UTHealth-Houston, Houston, TX, United States
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX, United States
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13
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Liu X, Yang H, Becker B, Huang X, Luo C, Meng C, Biswal B. Disentangling age- and disease-related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree. Hum Brain Mapp 2021; 42:3023-3041. [PMID: 33960579 PMCID: PMC8193510 DOI: 10.1002/hbm.25403] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 02/23/2021] [Accepted: 02/25/2021] [Indexed: 02/05/2023] Open
Abstract
Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21–55 using resting‐state functional magnetic resonance imaging (rs‐fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity‐transitivity two‐dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star‐like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the “overloading” hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging‐related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.
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Affiliation(s)
- Xinyu Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Glasgow College, University of Electronic Science and Technology of China, Chengdu, China
| | - Hang Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chun Meng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
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14
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Yamashita M, Shimokawa T, Takahashi S, Yamada S, Terada M, Ukai S, Tanemura R. Cognitive functions relating to aberrant interactions between task-positive and task-negative networks: Resting fMRI study of patients with schizophrenia. APPLIED NEUROPSYCHOLOGY. ADULT 2020; 29:1122-1130. [PMID: 33280403 DOI: 10.1080/23279095.2020.1852565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Brain functional connectivity in the resting-state represents intrinsic functional states and correlates with cognitive performance. In patients with schizophrenia, reports on the relationships between forms of functional disconnectivity in local areas and cognitive disability have used resting-state functional magnetic resonance imaging data. Meanwhile, cognitive deficits in relation to inter-network forms of functional connectivity on a large scale are not well understood. This study examines cognitive functions in relation to the number of resting-state inter-network forms of functional connectivity focusing on task-positive networks (fronto-parietal network [FPN] and cingulo-opercular network [CON]) and task-negative network (default mode network [DMN]). We compare patients with schizophrenia (SCH group) and healthy controls (HC group). We conducted a functional network analysis by applying graph theory and evaluated cognitive functions using the Brief Assessment of Cognition in Schizophrenia. The number of forms of functional connectivity between FPN and DMN and between CON and DMN were significantly higher in SCH group than in HC group, and those in SCH group were also weakly correlated with their attention scores. It is suggested that fewer than typical functional segregations between task-positive and task-negative networks in SCH group relate to inefficient distribution of cognitive resources and low attentional abilities.
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Affiliation(s)
- Madoka Yamashita
- Department of Rehabilitation Science, Graduate School of Health Sciences, Life and Medical Sciences Area, Kobe University, Hyogo, Japan.,Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka University, Osaka, Japan.,Department of Rehabilitation, Asakayama General Hospital, Osaka, Japan
| | - Tetsuya Shimokawa
- Department of Rehabilitation Science, Graduate School of Health Sciences, Life and Medical Sciences Area, Kobe University, Hyogo, Japan.,Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Osaka University, Osaka, Japan
| | - Shun Takahashi
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Shinichi Yamada
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | | | - Satoshi Ukai
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama, Japan
| | - Rumi Tanemura
- Department of Rehabilitation Science, Graduate School of Health Sciences, Life and Medical Sciences Area, Kobe University, Hyogo, Japan
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15
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DeLisi LE. What a Clinician Should Know About the Neurobiology of Schizophrenia: A Historical Perspective to Current Understanding. FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2020; 18:368-374. [PMID: 33343248 PMCID: PMC7725146 DOI: 10.1176/appi.focus.20200022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The brain is no doubt the "organ" of psychiatry; yet, over the years, few evidence-based classifications of psychiatric disorders have been based on brain mechanisms. The National Institute of Mental Health notably proposed one such system, known as Research Domain Criteria, although it has not yet influenced any changes in the DSM. Of all the major psychiatric disorders, the brain has been studied most extensively in schizophrenia, with its speculative pathology first documented by Emil Kraepelin as early as the beginning of the 20th century. Subsequently, the revolution in technology over the past 50 years has changed how investigators are able to view the brain before death without performing biopsies. Schizophrenia is thus found to have both structural and functional widespread brain anomalies that likely lead to its clinical deterioration. At the onset of illness, acquiring an MRI scan could be part of the routine evaluation to determine how progressive the disease has so far been. However, this practice is not yet recognized by the American Psychiatric Association in any of its guidelines on the treatment of schizophrenia.
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Affiliation(s)
- Lynn E DeLisi
- Department of Psychiatry, Harvard Medical School, Boston, and Cambridge Health Alliance, Cambridge Hospital, Cambridge, Massachusetts
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16
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Sheffield JM, Huang AS, Rogers BP, Giraldo-Chica M, Landman BA, Blackford JU, Heckers S, Woodward ND. Thalamocortical Anatomical Connectivity in Schizophrenia and Psychotic Bipolar Disorder. Schizophr Bull 2020; 46:1062-1071. [PMID: 32219397 PMCID: PMC7505173 DOI: 10.1093/schbul/sbaa022] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Anatomical connectivity between the thalamus and cortex, including the prefrontal cortex (PFC), is abnormal in schizophrenia. Overlapping phenotypes, including deficits in executive cognitive abilities dependent on PFC-thalamic circuitry, suggest dysrupted thalamocortical anatomical connectivity may extend to psychotic bipolar disorder. We tested this hypothesis and examined the impact of illness stage to inform when in the illness course thalamocortical dysconnectivity emerges. METHODS Diffusion-weighted imaging data were collected on 70 healthy individuals and 124 people with a psychotic disorder (schizophrenia spectrum = 75; psychotic bipolar disorder = 49), including 62 individuals in the early stage of psychosis. Anatomical connectivity between major divisions of the cortex and thalamus was quantified using probabilistic tractography and compared between groups. Associations between PFC-thalamic anatomical connectivity and executive cognitive abilities were examined using regression analysis. RESULTS Psychosis was associated with lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity. Follow-up analyses established that lower PFC-thalamic and elevated somatosensory-thalamic anatomical connectivity were present in both schizophrenia and psychotic bipolar disorder. Lower PFC-thalamic anatomical connectivity was also present in early-stage and chronic psychosis. Contrary to expectations, lower PFC-thalamic anatomical connectivity was not associated with impaired executive cognitive abilities. CONCLUSIONS Altered thalamocortical anatomical connectivity, especially reduced PFC-thalamic connectivity, is a transdiagnostic feature of psychosis detectable in the early stage of illness. Further work is required to elucidate the functional consequences of the full spectrum of thalamocortical connectivity abnormalities in psychosis.
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Affiliation(s)
- Julia M Sheffield
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN
| | - Anna S Huang
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Science, Nashville, TN
| | | | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Nashville, TN
- Vanderbilt University School of Engineering, Nashville, TN
| | - Jennifer Urbano Blackford
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN
- Research and Development, Department of Veterans Affairs Medical Center, Nashville, TN
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University School of Medicine, Nashville, TN
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