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Chauvel M, Pascucci M, Uszynski I, Herlin B, Mangin JF, Hopkins WD, Poupon C. Comparative analysis of the chimpanzee and human brain superficial structural connectivities. Brain Struct Funct 2024:10.1007/s00429-024-02823-2. [PMID: 39020215 DOI: 10.1007/s00429-024-02823-2] [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: 12/18/2023] [Accepted: 06/16/2024] [Indexed: 07/19/2024]
Abstract
Diffusion MRI tractography (dMRI) has fundamentally transformed our ability to investigate white matter pathways in the human brain. While long-range connections have extensively been studied, superficial white matter bundles (SWMBs) have remained a relatively underexplored aspect of brain connectivity. This study undertakes a comprehensive examination of SWMB connectivity in both the human and chimpanzee brains, employing a novel combination of empirical and geometric methodologies to classify SWMB morphology in an objective manner. Leveraging two anatomical atlases, the Ginkgo Chauvel chimpanzee atlas and the Ginkgo Chauvel human atlas, comprising respectively 844 and 1375 superficial bundles, this research focuses on sparse representations of the morphology of SWMBs to explore the little-understood superficial connectivity of the chimpanzee brain and facilitate a deeper understanding of the variability in shape of these bundles. While similar, already well-known in human U-shape fibers were observed in both species, other shapes with more complex geometry such as 6 and J shapes were encountered. The localisation of the different bundle morphologies, putatively reflecting the brain gyrification process, was different between humans and chimpanzees using an isomap-based shape analysis approach. Ultimately, the analysis aims to uncover both commonalities and disparities in SWMBs between chimpanzees and humans, shedding light on the evolution and organization of these crucial neural structures.
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Affiliation(s)
- Maëlig Chauvel
- BAOBAB, NeuroSpin, Paris-Saclay University, CNRS, CEA, Gif-sur-Yvette, France.
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Marco Pascucci
- BAOBAB, NeuroSpin, Paris-Saclay University, CNRS, CEA, Gif-sur-Yvette, France
| | - Ivy Uszynski
- BAOBAB, NeuroSpin, Paris-Saclay University, CNRS, CEA, Gif-sur-Yvette, France
| | - Bastien Herlin
- BAOBAB, NeuroSpin, Paris-Saclay University, CNRS, CEA, Gif-sur-Yvette, France
- Rehabilitation Unit, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | | | - William D Hopkins
- Department of Comparative Medicine, Michale E Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, USA
| | - Cyril Poupon
- BAOBAB, NeuroSpin, Paris-Saclay University, CNRS, CEA, Gif-sur-Yvette, France
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2
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Mendoza C, Román C, Mangin JF, Hernández C, Guevara P. Short fiber bundle filtering and test-retest reproducibility of the Superficial White Matter. Front Neurosci 2024; 18:1394681. [PMID: 38737100 PMCID: PMC11088237 DOI: 10.3389/fnins.2024.1394681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 04/08/2024] [Indexed: 05/14/2024] Open
Abstract
In recent years, there has been a growing interest in studying the Superficial White Matter (SWM). The SWM consists of short association fibers connecting near giry of the cortex, with a complex organization due to their close relationship with the cortical folding patterns. Therefore, their segmentation from dMRI tractography datasets requires dedicated methodologies to identify the main fiber bundle shape and deal with spurious fibers. This paper presents an enhanced short fiber bundle segmentation based on a SWM bundle atlas and the filtering of noisy fibers. The method was tuned and evaluated over HCP test-retest probabilistic tractography datasets (44 subjects). We propose four fiber bundle filters to remove spurious fibers. Furthermore, we include the identification of the main fiber fascicle to obtain well-defined fiber bundles. First, we identified four main bundle shapes in the SWM atlas, and performed a filter tuning in a subset of 28 subjects. The filter based on the Convex Hull provided the highest similarity between corresponding test-retest fiber bundles. Subsequently, we applied the best filter in the 16 remaining subjects for all atlas bundles, showing that filtered fiber bundles significantly improve test-retest reproducibility indices when removing between ten and twenty percent of the fibers. Additionally, we applied the bundle segmentation with and without filtering to the ABIDE-II database. The fiber bundle filtering allowed us to obtain a higher number of bundles with significant differences in fractional anisotropy, mean diffusivity, and radial diffusivity of Autism Spectrum Disorder patients relative to controls.
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Affiliation(s)
- Cristóbal Mendoza
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
| | - Claudio Román
- Centro de Investigación y Desarrollo en Ingeniería en Salud, Universidad de Valparaíso, Valparaíso, Chile
| | | | - Cecilia Hernández
- Department of Computer Science, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
- Center for Biotechnology and Bioengineering (CeBiB), Santiago, Chile
| | - Pamela Guevara
- Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, Concepción, Chile
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3
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Yoshino M, Shiraishi Y, Saito K, Kameya N, Hamabe-Horiike T, Shinmyo Y, Nakada M, Ozaki N, Kawasaki H. Distinct subdivisions of subcortical U-fiber regions in the gyrencephalic ferret brain. Neurosci Res 2024; 200:1-7. [PMID: 37866527 DOI: 10.1016/j.neures.2023.10.004] [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: 01/20/2023] [Revised: 09/29/2023] [Accepted: 10/17/2023] [Indexed: 10/24/2023]
Abstract
The human cerebrum contains a large amount of cortico-cortical association fibers. Among them, U-fibers are short-range association fibers located in white matter immediately deep to gray matter. Although U-fibers are thought to be crucial for higher cognitive functions, the organization within U-fiber regions are still unclear. Here we investigated the properties of U-fiber regions in the ferret cerebrum using neurochemical, neuronal tracing, immunohistochemical and electron microscopic techniques. We found that U-fiber regions can be subdivided into two regions, which we named outer and inner U-fiber regions. We further uncovered that outer U-fiber regions have smaller-diameter axons with thinner myelin compared with inner U-fiber regions. These findings may indicate functional complexity within U-fiber regions in the cerebrum.
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Affiliation(s)
- Mayuko Yoshino
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Yoshitake Shiraishi
- Department of Functional Anatomy, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan; Engineering and Technology Department, Kanazawa University, Ishikawa 920-8640, Japan
| | - Kengo Saito
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Narufumi Kameya
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Toshihide Hamabe-Horiike
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Yohei Shinmyo
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Mitsutoshi Nakada
- Department of Neurosurgery, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8641, Japan
| | - Noriyuki Ozaki
- Department of Functional Anatomy, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan
| | - Hiroshi Kawasaki
- Department of Medical Neuroscience, Graduate School of Medical Sciences, Kanazawa University, Ishikawa 920-8640, Japan.
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4
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Luo D, Peng Y, Zhu Q, Zheng Q, Luo Q, Han Y, Chen X, Li Y. U-fiber diffusion kurtosis and susceptibility characteristics in relapsing-remitting multiple sclerosis may be related to cognitive deficits and neurodegeneration. Eur Radiol 2024; 34:1422-1433. [PMID: 37658142 DOI: 10.1007/s00330-023-10114-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 05/30/2023] [Accepted: 07/01/2023] [Indexed: 09/03/2023]
Abstract
OBJECTIVES To evaluate the diffusion kurtosis and susceptibility change in the U-fiber region of patients with relapsing-remitting multiple sclerosis (pwRRMS) and their correlations with cognitive status and degeneration. MATERIALS AND METHODS Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), kurtosis fractional anisotropy (KFA), and the mean relative quantitative susceptibility mapping (mrQSM) values in the U-fiber region were compared between 49 pwRRMS and 48 healthy controls (HCs). The U-fiber were divided into upper and deeper groups based on the location. The whole brain volume, gray and white matter volume, and cortical thickness were obtained. The correlations between the mrQSM values, DKI-derived metrics in the U-fiber region and clinical scale scores, brain morphologic parameters were further investigated. RESULTS The decreased MK, AK, RK, KFA, and increased mrQSM values in U-fiber lesions (p < 0.001, FDR corrected), decreased RK, KFA, and increased mrQSM values in U-fiber non-lesions (p = 0.034, p < 0.001, p < 0.001, FDR corrected) were found in pwRRMS. There were differences in DKI-derived metrics and susceptibility values between the upper U-fiber region and the deeper one for U-fiber non-lesion areas of pwRRMS and HCs (p < 0.05), but not for U-fiber lesions in DKI-derived metrics. The DKI-derived metrics and susceptibility values were widely related with cognitive tests and brain atrophy. CONCLUSION RRMS patients show abnormal diffusion kurtosis and susceptibility characteristics in the U-fiber region, and these underlying tissue abnormalities are correlated with cognitive deficits and degeneration. CLINICAL RELEVANCE STATEMENT The macroscopic and microscopic tissue damages of U-fiber help to identify cognitive impairment and brain atrophy in multiple sclerosis and provide underlying pathophysiological mechanism. KEY POINTS • Diffusion kurtosis and susceptibility changes are present in the U-fiber region of multiple sclerosis. • There are gradients in diffusion kurtosis and susceptibility characteristics in the U-fiber region. • Tissue damages in the U-fiber region are correlated with cognitive impairment and brain atrophy.
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Affiliation(s)
- Dan Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yuling Peng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qiyuan Zhu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qiao Zheng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qi Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yongliang Han
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Xiaoya Chen
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
| | - Yongmei Li
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
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5
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Gangadin SS, Mandl RCW, de Witte LD, van Haren NEM, Schutte MJL, Begemann MJH, Kahn RS, Sommer IEC. Lower fractional anisotropy without evidence for neuro-inflammation in patients with early-phase schizophrenia spectrum disorders. Schizophr Res 2024; 264:557-566. [PMID: 36577563 DOI: 10.1016/j.schres.2022.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 12/28/2022]
Abstract
Various lines of research suggest immune dysregulation as a potential therapeutic target for negative and cognitive symptoms in schizophrenia spectrum disorders (SSD). Immune dysregulation would lead to higher extracellular free-water (EFW) in cerebral white matter (WM), which may partially underlie the frequently reported lower fractional anisotropy (FA) in SSD. We aim to investigate differences in EFW concentrations - a presumed proxy for neuro-inflammation - between early-phase SSD patients (n = 55) and healthy controls (HC; n = 37), and to explore immunological and cognitive correlates. To increase specificity for EFW, we study several complementary magnetic resonance imaging contrasts that are sensitive to EFW. FA, mean diffusivity (MD), magnetization transfer ratio (MTR), myelin water fraction (MWF) and quantitative T1 and T2 were calculated from diffusion-weighted imaging (DWI), magnetization transfer imaging (MTI) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT). For each measure, WM skeletons were constructed with tract-based spatial statistics. Multivariate SSD-HC comparisons with WM skeletons and their average values (i.e. global WM) were not statistically significant. In voxel-wise analyses, FA was significantly lower in SSD in the genu of the corpus callosum and in the left superior longitudinal fasciculus (p < 0.04). Global WM measures did not correlate with immunological markers (i.e. IL1-RA, IL-6, IL-8, IL-10 and CRP) or cognition in HC and SSD after corrections for multiple comparisons. We confirmed lower FA in early-phase SSD patients. However, nonFA measures did not provide additional evidence for immune dysregulation or for higher EFW as the primary mechanism underlying the reported lower FA values in SSD.
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Affiliation(s)
- Shiral S Gangadin
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René C W Mandl
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Neeltje E M van Haren
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, the Netherlands.
| | - Maya J L Schutte
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - Marieke J H Begemann
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, NY, USA.
| | - Iris E C Sommer
- Section Cognitive Neuroscience, Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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6
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Komnenić D, Phillips OR, Joshi SH, Chien C, Schmitz-Hübsch T, Asseyer S, Paul F, Finke C. Superficial white matter integrity in neuromyelitis optica spectrum disorder and multiple sclerosis. Mult Scler J Exp Transl Clin 2024; 10:20552173231226107. [PMID: 38269006 PMCID: PMC10807332 DOI: 10.1177/20552173231226107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 12/26/2023] [Indexed: 01/26/2024] Open
Abstract
Background Superficial white matter (SWM) is a particularly vulnerable area of white matter adjacent to cerebral cortex that was shown to be a sensitive marker of disease severity in several neurological and psychiatric disorders, including multiple sclerosis (MS), but has not been studied in neuromyelitis optica spectrum disorder (NMOSD). Objective To compare the integrity of SWM between MS patients, NMOSD patients and healthy controls, and explore the correlation of SWM integrity with cognitive performance and overall disability. Methods Forty NMOSD patients, 48 MS patients and 52 healthy controls were included in the study. Mean diffusivity (MD) values obtained by diffusion tensor imaging were used as a measure of SWM integrity. Cognitive performance and overall disability were assessed with standardized tests. Results Superficial white matter MD was increased in MS patients compared to healthy controls. Higher MD was associated with poorer spatial memory (most prominently in right temporal and right limbic lobe) and poorer information processing speed in MS patients. After adjusting for age, no significant differences of SWM MD were observed between NMOSD patients and healthy controls. Conclusion Integrity of SWM is compromised in MS, but not in NMOSD, and can serve as a sensitive marker of disease severity.
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Affiliation(s)
- Darko Komnenić
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin School of Mind and Brain, Berlin, Germany
| | - Owen Robert Phillips
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Stanford University School of Medicine, Stanford, CA, USA
| | - Shantanu H Joshi
- Department of Neurology, Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Claudia Chien
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tanja Schmitz-Hübsch
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
| | - Susanna Asseyer
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
| | - Friedemann Paul
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Carsten Finke
- Humboldt-Universität zu Berlin, Berlin School of Mind and Brain, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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7
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Chauvel M, Uszynski I, Herlin B, Popov A, Leprince Y, Mangin JF, Hopkins WD, Poupon C. In vivo mapping of the deep and superficial white matter connectivity in the chimpanzee brain. Neuroimage 2023; 282:120362. [PMID: 37722605 DOI: 10.1016/j.neuroimage.2023.120362] [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: 04/05/2023] [Revised: 06/27/2023] [Accepted: 09/03/2023] [Indexed: 09/20/2023] Open
Abstract
Mapping the chimpanzee brain connectome and comparing it to that of humans is key to our understanding of similarities and differences in primate evolution that occurred after the split from their common ancestor around 6 million years ago. In contrast to studies on macaque species' brains, fewer studies have specifically addressed the structural connectivity of the chimpanzee brain and its comparison with the human brain. Most comparative studies in the literature focus on the anatomy of the cortex and deep nuclei to evaluate how their morphology and asymmetry differ from that of the human brain, and some studies have emerged concerning the study of brain connectivity among humans, monkeys, and apes. In this work, we established a new white matter atlas of the deep and superficial white matter structural connectivity in chimpanzees. In vivo anatomical and diffusion-weighted magnetic resonance imaging (MRI) data were collected on a 3-Tesla MRI system from 39 chimpanzees. These datasets were subsequently processed using a novel fiber clustering pipeline adapted to the chimpanzee brain, enabling us to create two novel deep and superficial white matter connectivity atlases representative of the chimpanzee brain. These atlases provide the scientific community with an important and novel set of reference data for understanding the commonalities and differences in structural connectivity between the human and chimpanzee brains. We believe this study to be innovative both in its novel approach and in mapping the superficial white matter bundles in the chimpanzee brain, which will contribute to a better understanding of hominin brain evolution.
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Affiliation(s)
- Maëlig Chauvel
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France.
| | - Ivy Uszynski
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - Bastien Herlin
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France; Hôpital de la Pitié-Salpêtrière, 47-83 Boulevard de l'Hôpital, 75013 Paris, France
| | - Alexandros Popov
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - Yann Leprince
- UNIACT, NeuroSpin, Université Paris-Saclay, CEA, Gif-sur-Yvette, France
| | - Jean-François Mangin
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France
| | - William D Hopkins
- Department of Comparative Medicine, Michale E Keeling Center for Comparative Medicine and Research, The University of Texas MD Anderson Cancer Center, Bastrop, TX, United States of America
| | - Cyril Poupon
- BAOBAB, UMR 9027, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-sur-Yvette, France.
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8
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Huang P, Tint MT, Lee M, Ngoh ZM, Gluckman P, Chong YS, Han W, Fu Y, Wee CL, Fortier MV, Ang KK, Lee YS, Yap F, Eriksson JG, Meaney MJ, Tan AP. Functional activity of the caudate mediates the relation between early childhood microstructural variations and elevated metabolic syndrome scores. Neuroimage 2023; 278:120273. [PMID: 37473977 DOI: 10.1016/j.neuroimage.2023.120273] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/10/2023] [Accepted: 07/11/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Metabolic syndrome score in children assesses the risk of developing cardiovascular disease in future. We aim to probe the role of the caudate in relation to the metabolic syndrome score. Furthermore, using both functional and structural neuroimaging, we aim to examine the interplay between functional and structural measures. METHODS A longitudinal birth cohort study with functional and structural neuroimaging data obtained at 4.5, 6.0 and 7.5 years and metabolic syndrome scores at 8.0 years was used. Pearson correlation and linear regression was used to test for correlation fractional anisotropy (FA) and fractional amplitude of low frequency fluctuations (fALFF) of the caudate with metabolic syndrome scores. Mediation analysis was used to test if later brain measures mediated the relation between earlier brain measures and metabolic syndrome scores. Inhibitory control was also tested as a mediator of the relation between caudate brain measures and metabolic syndrome scores. RESULTS FA at 4.5 years and fALFF at 7.5 years of the left caudate was significantly correlated with metabolic syndrome scores. Post-hoc mediation analysis showed that fALFF at 7.5 years fully mediated the relation between FA at 4.5 years and metabolic syndrome scores. Inhibitory control was significantly correlated with fALFF at 7.5 years, but did not mediate the relation between fALFF at 7.5 years and metabolic syndrome scores. CONCLUSIONS We found that variations in caudate microstructure at 4.5 years predict later variation in functional activity at 7.5 years. This later variation in functional activity fully mediates the relation between microstructural changes in early childhood and metabolic syndrome scores at 8.0 years.
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Affiliation(s)
- Pei Huang
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Mya Thway Tint
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Marissa Lee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Peter Gluckman
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Obstetrics & Gynaecology, National University Hospital Singapore, Singapore
| | - Weiping Han
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore; Center for Neuro-Metabolism and Regeneration Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yu Fu
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Caroline Lei Wee
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Diagnostic and Interventional Radiology, KK Women's and Children's Hospital, Singapore
| | - Kai Keng Ang
- Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore; School of Computer Science and Engineering, Nanyang Technological University, Singapore
| | - Yung Seng Lee
- Department of Paedatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Fabian Yap
- Department of Paediatrics, Endocrinology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Johan G Eriksson
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Brain - Body Initiative, Agency for Science and Technology (A*STAR), Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Diagnostic Imaging, National University Hospital Singapore, Singapore.
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9
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Joo SW, Jo YT, Ahn S, Choi YJ, Choi W, Kim SK, Joe S, Lee J. Structural impairment in superficial and deep white matter in schizophrenia. Acta Neuropsychiatr 2023:1-10. [PMID: 37620164 DOI: 10.1017/neu.2023.44] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
OBJECTIVE Although disconnectivity among brain regions has been one of the main hypotheses for schizophrenia, the superficial white matter (SWM) has received less attention in schizophrenia research than the deep white matter (DWM) owing to the challenge of consistent reconstruction across subjects. METHODS We obtained the diffusion magnetic resonance imaging (dMRI) data of 223 healthy controls and 143 patients with schizophrenia. After harmonising the raw dMRIs from three different studies, we performed whole-brain two-tensor tractography and fibre clustering on the tractography data. We compared the fractional anisotropy (FA) of white matter tracts between healthy controls and patients with schizophrenia. Spearman's rho was adopted for the associations with clinical symptoms measured by the Positive and Negative Syndrome Scale (PANSS). The Bonferroni correction was used to adjust multiple testing. RESULTS Among the 33 DWM and 8 SWM tracts, patients with schizophrenia had a lower FA in 14 DWM and 4 SWM tracts than healthy controls, with small effect sizes. In the patient group, the FA deviations of the corticospinal and superficial-occipital tracts were negatively correlated with the PANSS negative score; however, this correlation was not evident after adjusting for multiple testing. CONCLUSION We observed the structural impairments of both the DWM and SWM tracts in patients with schizophrenia. The SWM could be a potential target of interest in future research on neural biomarkers for schizophrenia.
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Affiliation(s)
- Sung Woo Joo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea
| | - Soojin Ahn
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Jae Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Woohyeok Choi
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sang Kyoung Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Soohyun Joe
- Brain Laboratory, Department of Psychiatry, University of California San Diego, School of Medicine, San Diego, CA, USA
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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10
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Dolma S, Joshi A. The Node of Ranvier as an Interface for Axo-Glial Interactions: Perturbation of Axo-Glial Interactions in Various Neurological Disorders. J Neuroimmune Pharmacol 2023; 18:215-234. [PMID: 37285016 DOI: 10.1007/s11481-023-10072-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 05/19/2023] [Indexed: 06/08/2023]
Abstract
The action potential conduction along the axon is highly dependent on the healthy interactions between the axon and myelin-producing glial cells. Myelin, which facilitates action potential, is the protective insulation around the axon formed by Schwann cells and oligodendrocytes in the peripheral (PNS) and central nervous system (CNS), respectively. Myelin is a continuous structure with intermittent gaps called nodes of Ranvier, which are the sites enriched with ion channels, transmembrane, scaffolding, and cytoskeletal proteins. Decades-long extensive research has identified a comprehensive proteome with strictly regularized localization at the node of Ranvier. Concurrently, axon-glia interactions at the node of Ranvier have gathered significant attention as the pathophysiological targets for various neurodegenerative disorders. Numerous studies have shown the alterations in the axon-glia interactions culminating in neurological diseases. In this review, we have provided an update on the molecular composition of the node of Ranvier. Further, we have discussed in detail the consequences of disruption of axon-glia interactions during the pathogenesis of various CNS and PNS disorders.
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Affiliation(s)
- Sonam Dolma
- Department of Pharmacy, Birla Institute of Technology and Sciences- Pilani, Hyderabad campus, Telangana state, India
| | - Abhijeet Joshi
- Department of Pharmacy, Birla Institute of Technology and Sciences- Pilani, Hyderabad campus, Telangana state, India.
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11
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Kai J, Mackinley M, Khan AR, Palaniyappan L. Aberrant frontal lobe "U"-shaped association fibers in first-episode schizophrenia: A 7-Tesla Diffusion Imaging Study. Neuroimage Clin 2023; 38:103367. [PMID: 36913907 PMCID: PMC10011060 DOI: 10.1016/j.nicl.2023.103367] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 02/08/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023]
Abstract
Schizophrenia is believed to be a developmental disorder with one hypothesis suggesting that symptoms arise due to abnormal interactions (or disconnectivity) between different brain regions. While some major deep white matter pathways have been extensively studied (e.g. arcuate fasciculus), studies of short-ranged, "U"-shaped tracts have been limited in patients with schizophrenia, in part due to the sheer abundance of tracts present and due to the spatial variations across individuals that defy probabilistic characterization in the absence of reliable templates. In this study, we use diffusion magnetic resonance imaging (dMRI) to investigate frontal lobe superficial white matter that are present in the majority of study participants, comparing healthy controls and minimally treated patients with first-episode schizophrenia (<3 median days of lifetime treatment). Through group comparisons, 3 out of 63 frontal lobe "U"-shaped tracts were found to demonstrate localized aberrations affecting the microstructural tissue properties (via diffusion tensor metrics) in this early stage of disease. No associations were found in patients between aberrant segments of affected tracts and clinical or cognitive variables. Aberrations in the frontal lobe "U"-shaped tracts in early untreated stages of psychosis occur irrespective of symptom burden, and are distributed across critical functional networks associated with executive function and salience processing. While we limited the investigation to the frontal lobe, a framework has been developed to study such connections in other brain regions, enabling further extensive investigations jointly with the major deep white matter pathways.
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Affiliation(s)
- Jason Kai
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Michael Mackinley
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada
| | - Ali R Khan
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Lena Palaniyappan
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada; Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
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12
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Lee S, Shin HG, Kim M, Lee J. Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study. Neuroimage 2023; 273:120058. [PMID: 36997135 DOI: 10.1016/j.neuroimage.2023.120058] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023] Open
Abstract
The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive (χpos) and negative (χneg) susceptibility maps, to generate the depth-wise profiles of χpos and χneg as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χpos profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χneg profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χneg profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R2*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.
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13
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Schilling KG, Archer D, Yeh FC, Rheault F, Cai LY, Shafer A, Resnick SM, Hohman T, Jefferson A, Anderson AW, Kang H, Landman BA. Short superficial white matter and aging: a longitudinal multi-site study of 1293 subjects and 2711 sessions. AGING BRAIN 2023; 3:100067. [PMID: 36817413 PMCID: PMC9937516 DOI: 10.1016/j.nbas.2023.100067] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
It is estimated that short association fibers running immediately beneath the cortex may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in superficial white matter (SWM) tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several SWM systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in SWM throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of SWM volume and length decrease with age in a heterogenous manner across the brain, with different rates of change in inter-gyri and intra-gyri SWM, and at slower rates than well-studied long-range white matter pathways. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Derek Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Leon Y Cai
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Andrea Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Timothy Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Angela Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam W Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN, United States
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
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14
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Vinogradov S, Chafee MV, Lee E, Morishita H. Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity. Neuropsychopharmacology 2023; 48:168-185. [PMID: 36180784 PMCID: PMC9700720 DOI: 10.1038/s41386-022-01451-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/17/2022] [Accepted: 08/21/2022] [Indexed: 01/05/2023]
Abstract
Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.
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Affiliation(s)
- Sophia Vinogradov
- Department of Psychiatry & Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Matthew V Chafee
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Erik Lee
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
- University of Minnesota Informatics Institute, University of Minnesota, Minneapolis, MN, USA
| | - Hirofumi Morishita
- Department of Psychiatry, Neuroscience, & Ophthalmology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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15
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Roychaudhuri R, Gadalla MM, West T, Snyder SH. A Novel Stereospecific Bioluminescent Assay for Detection of Endogenous d-Cysteine. ACS Chem Neurosci 2022; 13:3257-3262. [PMID: 36403160 DOI: 10.1021/acschemneuro.2c00528] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The presence of endogenous d-stereoisomers of amino acids in mammals dispels a long-standing dogma about their existence. d-Serine and d-aspartate function as novel neurotransmitters in mammals. However, the stereoisomer with the fastest, spontaneous in vitro racemization rate, d-cysteine, has not been reported. We utilized a novel, stereospecific, bioluminescent assay to identify endogenous d-cysteine in substantial amounts in the eye, brain, and pancreas of mice. d-Cysteine is enriched in mice embryonic brains at day E9.5 (4.5 mM) and decreases progressively with development (μM levels). d-Cysteine is also present in significantly higher amounts in the human brain white matter compared with gray matter. In the luciferase assay, d-cysteine conjugates with cyano hydroxy benzothiazole in the presence of a base and reducing agent to form d-luciferin. d-Luciferin, subsequently, in the presence of firefly luciferase and ATP, emits bioluminescence proportional to the concentration of d-cysteine. The assay is stereospecific and allows the quantitative estimation of endogenous d-cysteine in tissues in addition to its specificity for d-cysteine. Future efforts aimed at bioluminescent in vivo imaging of d-cysteine may allow a more noninvasive means of its detection, thereby elucidating its function.
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Affiliation(s)
- Robin Roychaudhuri
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Moataz M Gadalla
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, United States
| | - Timothy West
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States
| | - Solomon H Snyder
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, United States.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, United States.,Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, United States
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16
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Wang S, Zhang F, Huang P, Hong H, Jiaerken Y, Yu X, Zhang R, Zeng Q, Zhang Y, Kikinis R, Rathi Y, Makris N, Lou M, Pasternak O, Zhang M, O'Donnell LJ. Superficial white matter microstructure affects processing speed in cerebral small vessel disease. Hum Brain Mapp 2022; 43:5310-5325. [PMID: 35822593 PMCID: PMC9812245 DOI: 10.1002/hbm.26004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 06/10/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.
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Affiliation(s)
- Shuyue Wang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Peiyu Huang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Hui Hong
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yeerfan Jiaerken
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Xinfeng Yu
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ruiting Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Qingze Zeng
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Yao Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ron Kikinis
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nikos Makris
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Center for Morphometric AnalysisMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Min Lou
- Department of Neurologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
| | - Ofer Pasternak
- Brigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Minming Zhang
- Department of Radiologythe Second Affiliated Hospital of Zhejiang University School of MedicineChina
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17
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Shastin D, Genc S, Parker GD, Koller K, Tax CMW, Evans J, Hamandi K, Gray WP, Jones DK, Chamberland M. Surface-based tracking for short association fibre tractography. Neuroimage 2022; 260:119423. [PMID: 35809886 PMCID: PMC10009610 DOI: 10.1016/j.neuroimage.2022.119423] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 05/30/2022] [Accepted: 06/29/2022] [Indexed: 11/16/2022] Open
Abstract
It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short (≤30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surface-based measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.
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Affiliation(s)
- Dmitri Shastin
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom.
| | - Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Greg D Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Kristin Koller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - John Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom; Department of Neurology, University Hospital of Wales, Cardiff, United Kingdom
| | - William P Gray
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Department of Neurosurgery, University Hospital of Wales, Cardiff, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; BRAIN Biomedical Research Unit, Health & Care Research Wales, Cardiff, United Kingdom
| | - Maxime Chamberland
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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18
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Wide Dissection Trans-Sulcal Approach for Resection of Deep Intra-Axial Lesions in Eloquent Brain Areas. Curr Oncol 2022; 29:7396-7410. [PMID: 36290858 PMCID: PMC9600937 DOI: 10.3390/curroncol29100581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 11/05/2022] Open
Abstract
Introduction: Resection of intra-axial tumors (IaT) in eloquent brain regions risks major postoperative neurological deficits. Awake craniotomy is often used to navigate these areas; however, some patients are ineligible for awake procedures. The trans-sulcal approach (TScal) was introduced to reduce parenchymal trauma during tumor resection. We report our experiences utilizing TScal for resection of deep IaT located in eloquent areas. Materials and Methods: This is a single-center retrospective analysis of patients who underwent IaT resection in eloquent areas via TScal from January 2013 to April 2021. Seventeen cases were reviewed, and relevant data was collected. Fluorescence-guided surgery with 5-aminolevulinic acid (ALA) and intraoperative ultrasound was performed in some cases. Results: Seventeen patients (10 males, 7 females) averaging 61.2 years-old (range, 21-76) were included in this study. Average length of stay was 4.8 days, and only 2 patients (11.8%) required hospital readmission within 30 days. Gross total resection (GTR) was achieved in 15 patients (88.2%), while subtotal resection occurred in 2 patients (11.8%). Eleven patients (64.7%) reported full resolution of symptoms, 4 patients (23.5%) reported deficit improvement, and 2 patients (11.8%) experienced no change from their preoperative deficits. No patient developed new permanent deficits postoperatively. Discussion: GTR, preoperative deficit reduction, and complications were comparable to awake craniotomy and other TScal studies. Ancillary intraoperative techniques, such as brain mapping, 5-ALA and intraoperative ultrasound, are afforded by TScal to improve resection rates and overall outcomes. Conclusions: TScal can be an option for patients with deep lesions in eloquent areas who are not candidates for awake surgeries.
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Corpus Callosum Microstructural Tract Integrity Relates to Longer Emotion Recognition Reaction Time in People with Schizophrenia. Brain Sci 2022; 12:brainsci12091208. [PMID: 36138944 PMCID: PMC9496923 DOI: 10.3390/brainsci12091208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 11/16/2022] Open
Abstract
Objective: Schizophrenia is a complex functionally debilitating neurodevelopmental disorder, with associated social cognitive impairment. Corpus Callosum (CC) white matter tracts deficits are reported for people with schizophrenia; however, few studies focus on interhemispheric processing relative to social cognition tasks. This study aimed to determine if a relationship between the CC and social cognition exists. Method: In this cross-section study, a sample of n = 178 typical controls and n = 58 people with schizophrenia completed measures of mentalising (Reading the Mind in the Eyes), emotion recognition outcome and reaction time (Emotion Recognition Test), and clinical symptoms (Positive and Negative Symptom Scale), alongside diffusion-based tract imaging. The CC and its subregions, i.e., the genu, body, and splenium were the regions of interest (ROI). Results: Reduced white matter tract integrity was observed in the CC for patients when compared to controls. Patients performed slower, and less accurately on emotion recognition tasks, which significantly and negatively correlated to the structural integrity of the CC genu. Tract integrity further significantly and negatively related to clinical symptomatology. Conclusions: People with schizophrenia have altered white matter integrity in the genu of the CC, compared to controls, which relates to cognitive deficits associated with recognising emotional stimuli accurately and quickly, and severity of clinical symptoms.
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20
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Superficial white matter bundle atlas based on hierarchical fiber clustering over probabilistic tractography data. Neuroimage 2022; 262:119550. [DOI: 10.1016/j.neuroimage.2022.119550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 11/20/2022] Open
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21
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Zhang S, Wang Y, Zheng S, Seger C, Zhong S, Huang H, Hu H, Chen G, Chen L, Jia Y, Huang L, Huang R. Multimodal MRI reveals alterations of the anterior insula and posterior cingulate cortex in bipolar II disorders: A surface-based approach. Prog Neuropsychopharmacol Biol Psychiatry 2022; 116:110533. [PMID: 35151795 DOI: 10.1016/j.pnpbp.2022.110533] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 11/29/2021] [Accepted: 02/05/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Bipolar disorder (BD) is a mental disorder with severe implications for those affected and their families. Previous studies detected brain structural and functional alterations in BD patients. However, very few studies conducted a multimodal MRI fusion analysis, and little is known about the role of common anomalies in the connectivity of BD. METHODS We collected sMRI, rs-fMRI, and DTI data from 56 patients with unmedicated BD-II depression and 72 age-, sex- and handedness-matched healthy controls. We applied data-driven approaches to analyze multimodal MRI data and detected brain areas with significant group differences in cortical thickness (CT), amplitude of low frequency fluctuations (ALFF), and fractional anisotropy (FA) of the superficial white matter. We observed the common abnormal areas and took these areas as seeds to analyze the resting-state functional connectivity (RSFC) patterns in BD patients by overlapping these abnormal areas. RESULTS The BD patients showed two common abnormal areas: (1) the left anterior insula (AI) with abnormal CT and FA, and (2) the left posterior cingulate cortex (PCC) with abnormal CT and ALFF. Seed-based analyses showed RSFC between the left AI and left occipital sensory cortex, the left AI and left superior and inferior parietal cortex, and the left PCC and right medial prefrontal cortex were uniformly lower in the BD patients than controls. Correlation analyses showed negative correction between AI's FA and disease episodes and between AI's FA and disease duration in depressed BD-II patients. CONCLUSIONS We observed abnormal brain structural and functional properties in the left AI and left PCC in BD patients. The abnormal RSFC patterns may suggest sensory and cognitive dysfunction in BD.
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Affiliation(s)
- Shufei Zhang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China.
| | - Senning Zheng
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China
| | - Carol Seger
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China; Department of Psychology and Program in Molecular, Cellular, and Integrative Neuroscience, Colorado State University, Fort Collins, CO 80523, USA
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Huiyuan Huang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China
| | - Huiqing Hu
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Lixiang Chen
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Ruiwang Huang
- School of Psychology, Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, South China Normal University, Guangzhou 510631, China.
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22
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Chen CL, Hwang TJ, Tung YH, Yang LY, Hsu YC, Liu CM, Lin YT, Hsieh MH, Liu CC, Chien YL, Hwu HG, Tseng WYI. Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics. Neuroimage Clin 2022; 34:103003. [PMID: 35413648 PMCID: PMC9018160 DOI: 10.1016/j.nicl.2022.103003] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 03/24/2022] [Accepted: 04/04/2022] [Indexed: 11/28/2022]
Abstract
Novel metrics are proposed using the brain age paradigm with normative modeling. Normative brain age is validated to reveal advanced aging in schizophrenia. Men with schizophrenia have older brain age than women with the disorder. The brain age in white matter is positively associated with the negative symptom. The precuneus and uncinate fasciculus are markedly related to the advanced aging.
Conceptualizing mental disorders as deviations from normative functioning provides a statistical perspective for understanding the individual heterogeneity underlying psychiatric disorders. To broaden the understanding of the idiosyncrasy of brain aging in schizophrenia, we introduced an imaging-derived brain age paradigm combined with normative modeling as novel brain age metrics. We constructed brain age models based on GM, WM, and their combination (multimodality) features of 482 normal participants. The normalized predicted age difference (nPAD) was estimated in 147 individuals with schizophrenia and their 130 demographically matched controls through normative models of brain age metrics and compared between the groups. Regression analyses were also performed to investigate the associations of nPAD with illness duration, onset age, symptom severity, and intelligence quotient. Finally, regional contributions to advanced brain aging in schizophrenia were investigated. The results showed that the individuals exhibited significantly higher nPAD (P < 0.001), indicating advanced normative brain age than the normal controls in GM, WM, and multimodality models. The nPAD measure based on WM was positively associated with the negative symptom score (P = 0.009), and negatively associated with the intelligence quotient (P = 0.039) and onset age (P = 0.006). The imaging features that contributed to nPAD mostly involved the prefrontal, temporal, and parietal lobes, especially the precuneus and uncinate fasciculus. This study demonstrates that normative brain age metrics could detect advanced brain aging and associated clinical and neuroanatomical features in schizophrenia. The proposed nPAD measures may be useful to investigate aberrant brain aging in mental disorders and their brain-phenotype relationships.
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Affiliation(s)
- Chang-Le Chen
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tzung-Jeng Hwang
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yu-Hung Tung
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Li-Ying Yang
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Chih-Min Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Tin Lin
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Ming-Hsien Hsieh
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Chung Liu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Yi-Ling Chien
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Hai-Gwo Hwu
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan; AcroViz Inc., Taipei, Taiwan; Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan; Molecular Imaging Center, National Taiwan University, Taipei, Taiwan.
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23
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Luttenbacher I, Phillips A, Kazemi R, Hadipour AL, Sanghvi I, Martinez J, Adamson MM. Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review. J Psychiatr Res 2022; 147:324-348. [PMID: 35151030 DOI: 10.1016/j.jpsychires.2021.12.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/08/2021] [Accepted: 12/19/2021] [Indexed: 12/09/2022]
Abstract
Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.
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Affiliation(s)
- Ines Luttenbacher
- Department of Social & Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands; Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Angela Phillips
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Reza Kazemi
- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
| | - Abed L Hadipour
- Department of Cognitive Sciences, University of Messina, Messina, Italy
| | - Isha Sanghvi
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neuroscience, University of Southern California, Los Angeles, CA, USA
| | - Julian Martinez
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto University, Palo Alto, CA, USA
| | - Maheen M Adamson
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA.
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24
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Chang X, Jia X, Wang Y, Dong D. Alterations of cerebellar white matter integrity and associations with cognitive impairments in schizophrenia. Front Psychiatry 2022; 13:993866. [PMID: 36226106 PMCID: PMC9549145 DOI: 10.3389/fpsyt.2022.993866] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/08/2022] [Indexed: 11/17/2022] Open
Abstract
"Cognitive dysmetria" theory of schizophrenia (SZ) has highlighted that the cerebellum plays a critical role in understanding the pathogenesis and cognitive impairment in SZ. Despite some studies have reported the structural disruption of the cerebellum in SZ using whole brain approach, specific focus on the voxel-wise changes of cerebellar WM microstructure and its associations with cognition impairments in SZ were less investigated. To further explore the voxel-wise structural disruption of the cerebellum in SZ, the present study comprehensively examined volume and diffusion features of cerebellar white matter in SZ at the voxel level (42 SZ vs. 52 controls) and correlated the observed alterations with the cognitive impairments measured by MATRICS Consensus Cognitive Battery. Combing voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) methods, we found, compared to healthy controls (HCs), SZ patients did not show significant alteration in voxel-level cerebellar white matter (WM) volume and tract-wise and skeletonized DTI features. In voxel-wise DTI features of cerebellar peduncles, compared to HCs, SZ patients showed decreased fractional anisotropy and increased radial diffusivity mainly located in left middle cerebellar peduncles (MCP) and inferior cerebellar peduncles (ICP). Interestingly, these alterations were correlated with overall composite and different cognitive domain (including processing speed, working memory, and attention vigilance) in HCs but not in SZ patients. The present findings suggested that the voxel-wise WM integrity analysis might be a more sensitive way to investigate the cerebellar structural abnormalities in SZ patients. Correlation results suggested that inferior and MCP may be a crucial neurobiological substrate of cognition impairments in SZ, thus adding the evidence for taking the cerebellum as a novel therapeutic target for cognitive impairments in SZ patients.
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Affiliation(s)
- Xuebin Chang
- Department of Information Sciences, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China
| | - Xiaoyan 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, Xi'an, China
| | - Yulin Wang
- Key Laboratory of Cognition and Personality, Southwest University (SWU), Ministry of Education, Chongqing, China.,Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Debo Dong
- Key Laboratory of Cognition and Personality, Southwest University (SWU), Ministry of Education, Chongqing, China.,Faculty of Psychology, Southwest University (SWU), Chongqing, China.,Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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25
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Buyukturkoglu K, Vergara C, Fuentealba V, Tozlu C, Dahan JB, Carroll BE, Kuceyeski A, Riley CS, Sumowski JF, Guevara Oliva C, Sitaram R, Guevara P, Leavitt VM. Machine learning to investigate superficial white matter integrity in early multiple sclerosis. J Neuroimaging 2022; 32:36-47. [PMID: 34532924 PMCID: PMC8752496 DOI: 10.1111/jon.12934] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 09/01/2021] [Accepted: 09/03/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND AND PURPOSE This study aims todetermine the sensitivity of superficial white matter (SWM) integrity as a metric to distinguish early multiple sclerosis (MS) patients from healthy controls (HC). METHODS Fractional anisotropy and mean diffusivity (MD) values from SWM bundles across the cortex and major deep white matter (DWM) tracts were extracted from 29 early MS patients and 31 age- and sex-matched HC. Thickness of 68 cortical regions and resting-state functional-connectivity (RSFC) among them were calculated. The distribution of structural and functional metrics between groups were compared using Wilcoxon rank-sum test. Utilizing a machine learning method (adaptive boosting), 6 models were built based on: 1-SWM, 2-DWM, 3-SWM and DWM, 4-cortical thickness, or 5-RSFC measures. In model 6, all features from previous models were incorporated. The models were trained with nested 5-folds cross-validation. Area under the receiver operating characteristic curve (AUCroc ) values were calculated to evaluate classification performance of each model. Permutation tests were used to compare the AUCroc values. RESULTS Patients had higher MD in SWM bundles including insula, inferior frontal, orbitofrontal, superior and medial temporal, and pre- and post-central cortices (p < .05). No group differences were found for any other MRI metric. The model incorporating SWM and DWM features provided the best classification (AUCroc = 0.75). The SWM model provided higher AUCroc (0.74), compared to DWM (0.63), cortical thickness (0.67), RSFC (0.63), and all-features (0.68) models (p < .001 for all). CONCLUSION Our results reveal a non-random pattern of SWM abnormalities at early stages of MS even before pronounced structural and functional alterations emerge.
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Affiliation(s)
- Korhan Buyukturkoglu
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | | | | | - Ceren Tozlu
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Jacob B. Dahan
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | - Britta E. Carroll
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Claire S. Riley
- Multiple Sclerosis Center, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - James F. Sumowski
- Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai Hospital, New York, NY. USA
| | | | - Ranganatha Sitaram
- Diagnostic Imaging Department, St. Jude Children’s Research Hospital, Memphis TN. USA
| | | | - Victoria M. Leavitt
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
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26
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Bigham B, Zamanpour SA, Zare H. Features of the superficial white matter as biomarkers for the detection of Alzheimer's disease and mild cognitive impairment: A diffusion tensor imaging study. Heliyon 2022; 8:e08725. [PMID: 35071808 PMCID: PMC8761704 DOI: 10.1016/j.heliyon.2022.e08725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 10/02/2021] [Accepted: 01/05/2022] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND With the development of medical imaging and processing tools, accurate diagnosis of diseases has been made possible by intelligent systems. Owing to the remarkable ability of support vector machines (SVMs) for diseases diagnosis, extensive research has been conducted using the SVM algorithm for the classification of Alzheimer's disease (AD) and mild cognitive impairment (MCI). OBJECTIVES In this study, we applied an automated method to classify patients with AD and MCI and healthy control (HC) subjects based on the diffusion tensor imaging (DTI) features in the superficial white matter (SWM). PARTICIPANTS For this purpose, DTI data were downloaded from the Alzheimer's Disease Neuroimaging Initiative (ADNI). This method employed DTI data from 72 subjects: 24 subjects as HC, 24 subjects with MCI, and 24 subjects with AD. MEASURE ments: DTI processing was performed using DSI Studio software and all machine learning analyses were performed using MATLAB software. RESULTS The linear kernel of SVM was the best classifier, with an accuracy of 95.8% between the AD and HC groups, followed by the quadratic kernel of SVM with an accuracy of 83.3% between the MCI and HC groups and the Gaussian kernel of SVM with an accuracy of 83.3% between the AD and MCI groups. CONCLUSIONS Given the importance of diagnosing AD and MCI as well as the role of superficial white matter in the diagnosis of neurodegenerative diseases, in this study, the features of different DTI methods of the SWM are discussed, which could be a useful tool to assist in the diagnosis of AD and MCI.
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Affiliation(s)
- Bahare Bigham
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyed Amir Zamanpour
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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27
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Kochunov P, Hong LE, Dennis EL, Morey RA, Tate DF, Wilde EA, Logue M, Kelly S, Donohoe G, Favre P, Houenou J, Ching CRK, Holleran L, Andreassen OA, van Velzen LS, Schmaal L, Villalón-Reina JE, Bearden CE, Piras F, Spalletta G, van den Heuvel OA, Veltman DJ, Stein DJ, Ryan MC, Tan Y, van Erp TGM, Turner JA, Haddad L, Nir TM, Glahn DC, Thompson PM, Jahanshad N. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research. Hum Brain Mapp 2022; 43:194-206. [PMID: 32301246 PMCID: PMC8675425 DOI: 10.1002/hbm.24998] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 03/06/2020] [Accepted: 03/17/2020] [Indexed: 12/25/2022] Open
Abstract
The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Emily L Dennis
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, Massachusetts, USA
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - David F Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen VA, Salt Lake City, Utah, USA
| | - Mark Logue
- VA Boston Healthcare System, National Center for PTSD, Boston, Massachusetts, USA
- Boston University School of Medicine, Department of Psychiatry, Boston, Massachusetts, USA
- Boston University School of Medicine, Biomedical Genetics, Boston, Massachusetts, USA
- Boston University School of Public Health, Department of Biostatistics, Boston, Massachusetts, USA
| | - Sinead Kelly
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Pauline Favre
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
| | - Josselin Houenou
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- INSERM Unit U955, team "Translational Neuro-Psychiatry", Créteil, France
- Psychiatry Department, Assistance Publique-Hôpitaux de Paris (AP-HP), CHU Mondor, Créteil, France
- Faculté de Médecine, Université Paris Est Créteil, Créteil, France
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Laura S van Velzen
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia
| | - Julio E Villalón-Reina
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, California, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, California, USA
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
- Division of Neuropsychiatry, Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dick J Veltman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, University of Cape Town, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry, University of California Irvine, Irvine, California, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, California, USA
| | - Jessica A Turner
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, Georgia, USA
| | - Liz Haddad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Talia M Nir
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Olin Neuropsychiatric Research Center, Hartford Hospital, Hartford, Connecticut, USA
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
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28
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Quidé Y, Watkeys OJ, Girshkin L, Kaur M, Carr VJ, Cairns MJ, Green MJ. Interactive effects of polygenic risk and cognitive subtype on brain morphology in schizophrenia spectrum and bipolar disorders. Eur Arch Psychiatry Clin Neurosci 2022; 272:1205-1218. [PMID: 35792918 PMCID: PMC9508053 DOI: 10.1007/s00406-022-01450-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 06/12/2022] [Indexed: 11/29/2022]
Abstract
Grey matter volume (GMV) may be associated with polygenic risk for schizophrenia (PRS-SZ) and severe cognitive deficits in people with schizophrenia, schizoaffective disorder (collectively SSD), and bipolar disorder (BD). This study examined the interactive effects of PRS-SZ and cognitive subtypes of SSD and BD in relation to GMV. Two-step cluster analysis was performed on 146 clinical cases (69 SSD and 77 BD) assessed on eight cognitive domains (verbal and visual memory, executive function, processing speed, visual processing, language ability, working memory, and planning). Among them, 55 BD, 51 SSD, and 58 healthy controls (HC), contributed to focal analyses of the relationships between cognitive subtypes, PRS-SZ and their interaction on GMV. Two distinct cognitive subtypes were evident among the combined sample of cases: a 'cognitive deficit' group (CD; N = 31, 20SSD/11BD) showed severe impairment across all cognitive indices, and a 'cognitively spared' (CS; N = 75; 31SSD/44BD) group showed intermediate cognitive performance that was significantly worse than the HC group but better than the CD subgroup. A cognitive subgroup-by-PRS-SZ interaction was significantly associated with GMV in the left precentral gyrus. Moderation analyses revealed a significant negative relationship between PRS-SZ and GMV in the CD group only. At low and average (but not high) PRS-SZ, larger precentral GMV was evident in the CD group compared to both CS and HC groups, and in the CS group compared to HCs. This study provides evidence for a relationship between regional GMV changes and PRS-SZ in psychosis spectrum cases with cognitive deficits, but not in cases cognitively spared.
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Affiliation(s)
- Yann Quidé
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia
| | - Oliver J. Watkeys
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia
| | - Leah Girshkin
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia
| | - Manreena Kaur
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia
| | - Vaughan J. Carr
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia ,Department of Psychiatry, Monash University, Clayton, VIC Australia
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW Australia ,Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW Australia ,Hunter Medical Research Institute, New Lambton Heights, NSW Australia
| | - Melissa J. Green
- School of Clinical Medicine, Discipline of Psychiatry and Mental Health, University of New South Wales (UNSW), Sydney, NSW Australia ,Neuroscience Research Australia, Randwick, NSW Australia
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Yang M, Gao S, Xiong W, Zhang XY. Sex-differential associations between cognitive impairments and white matter abnormalities in first episode and drug-naïve schizophrenia. Early Interv Psychiatry 2021; 15:1179-1187. [PMID: 33058544 DOI: 10.1111/eip.13059] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 08/24/2020] [Accepted: 09/26/2020] [Indexed: 11/30/2022]
Abstract
AIM Previous evidence has suggested that schizophrenia patients may display sex differences in cognitive impairments and cognitive impairments are related to disrupted white matter (WM) microstructure. The current research aims to address the intriguing possibility for the sex-specific association between cognitive deficits and WM abnormalities in first-episode and drug-naïve schizophrenia. METHODS Cognitive performance on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was measured in 39 FEND patients (females:males = 23:16) and 30 healthy controls (females:males = 17:13), together with whole-brain WM fractional anisotropy (FA) values determined using voxel-based diffusion tensor imaging. Correlations between cognitive performance and FA values were assessed. RESULTS Patients performed significantly worse than healthy controls in the total score and most of the subscores of MCCB. Female patients displayed better cognitive performance than male patients on the Trail Making A Test, the Hopkins Verbal Learning Test and the Spatial Span Test in the Wechsler Memory Scale. More importantly, sex-differential association between cognitive performance and FA values was found in patients, but not in healthy controls. In particular, FA values in the cerebellum were negatively correlated with the continuous performance and digital sequence scores in male patients but positively correlated with the performance on the Spatial Span Test in the Wechsler Memory Scale in female patients. CONCLUSIONS These findings suggest sex-specific neurobiological substrates involved in cognitive deficits in early-onset schizophrenia and have important implications for differentially targeted interventions between males and females.
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Affiliation(s)
- Mi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Shan Gao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Weisen Xiong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Xiang Yang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Zhang Y, Huang B, Chen Q, Wang L, Zhang L, Nie K, Huang Q, Huang R. Altered microstructural properties of superficial white matter in patients with Parkinson's disease. Brain Imaging Behav 2021; 16:476-491. [PMID: 34410610 DOI: 10.1007/s11682-021-00522-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2021] [Indexed: 12/31/2022]
Abstract
Parkinson's disease (PD), a chronic neurodegenerative disease, is characterized by sensorimotor and cognitive deficits. Previous diffusion tensor imaging (DTI) studies found abnormal DTI metrics in white matter bundles, such as the corpus callosum, cingulate, and frontal-parietal bundles, in PD patients. These studies mainly focused on alterations in microstructural features of long-range bundles within the deep white matter (DWM) that connects pairs of distant cortical regions. However, less is known about the DTI metrics of the superficial white matter (SWM) that connects local cortical regions in PD patients. To determine whether the DTI metrics of the SWM were different between the PD patients and the healthy controls, we recruited DTI data from 34 PD patients and 29 gender- and age-matched healthy controls. Using a probabilistic tractographic approach, we first defined a population-based SWM mask across all the subjects. Using a tract-based spatial statistical (TBSS) analytic approach, we then identified the SWM bundles showing abnormal DTI metrics in the PD patients. We found that the PD patients showed significantly lower DTI metrics in the SWM bundles connecting the sensorimotor cortex, cingulate cortex, posterior parietal cortex (PPC), and parieto-occipital cortex than the healthy controls. We also found that the clinical measures in the PD patients was significantly negatively correlated with the fractional anisotropy in the SWM (FASWM) that connects core regions in the default mode network (DMN). The FASWM in the bundles that connected the PPC was significantly positively correlated with cognitive performance in the PD patients. Our findings suggest that SWM may serve as the brain structural basis underlying the sensorimotor deficits and cognitive degeneration in PD patients.
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Affiliation(s)
- Yichen Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Biao Huang
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Guangzhou, 510080 , China.
| | - Qinyuan Chen
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Guangzhou, 510080, China
| | - Lu Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Kun Nie
- Department of Neurology, Guangdong Academy of Medical Sciences, Guangdong Provincial People's Hospital, Guangzhou, 510080, China
| | - Qinda Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Ruiwang Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China.
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Murray AJ, Rogers JC, Katshu MZUH, Liddle PF, Upthegrove R. Oxidative Stress and the Pathophysiology and Symptom Profile of Schizophrenia Spectrum Disorders. Front Psychiatry 2021; 12:703452. [PMID: 34366935 PMCID: PMC8339376 DOI: 10.3389/fpsyt.2021.703452] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 06/28/2021] [Indexed: 12/12/2022] Open
Abstract
Schizophrenia is associated with increased levels of oxidative stress, as reflected by an increase in the concentrations of damaging reactive species and a reduction in anti-oxidant defences to combat them. Evidence has suggested that whilst not the likely primary cause of schizophrenia, increased oxidative stress may contribute to declining course and poor outcomes associated with schizophrenia. Here we discuss how oxidative stress may be implicated in the aetiology of schizophrenia and examine how current understanding relates associations with symptoms, potentially via lipid peroxidation induced neuronal damage. We argue that oxidative stress may be a good target for future pharmacotherapy in schizophrenia and suggest a multi-step model of illness progression with oxidative stress involved at each stage.
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Affiliation(s)
- Alex J. Murray
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom
| | - Jack C. Rogers
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom
| | - Mohammad Zia Ul Haq Katshu
- Institute of Mental Health, Division of Mental Health and Neurosciences University of Nottingham, Nottingham, United Kingdom
- Nottinghamshire Healthcare National Health Service Foundation Trust, Nottingham, United Kingdom
| | - Peter F. Liddle
- Institute of Mental Health, Division of Mental Health and Neurosciences University of Nottingham, Nottingham, United Kingdom
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom
- Early Intervention Service, Birmingham Women's and Children's National Health Service Foundation Trust, Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
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White matter brain aging in relationship to schizophrenia and its cognitive deficit. Schizophr Res 2021; 230:9-16. [PMID: 33667860 PMCID: PMC8222174 DOI: 10.1016/j.schres.2021.02.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 01/26/2021] [Accepted: 02/18/2021] [Indexed: 11/21/2022]
Abstract
We hypothesized that cerebral white matter deficits in schizophrenia (SZ) are driven in part by accelerated white matter aging and are associated with cognitive deficits. We used a machine learning model to predict individual age from diffusion tensor imaging features and calculated the delta age (Δage) as the difference between predicted and chronological age. Through this approach, we translated multivariate white matter imaging features into an age-scaled metric and used it to test the temporal trends of accelerated aging-related white matter deficit in SZ and its association with the cognition. A feature selection procedure was first employed to choose fractional anisotropy values in 34 of 43 white fiber tracts. Using these features, a machine learning model was trained based on a training set consisted of 107 healthy controls (HC). The brain age of 166 SZs and 107 HCs in the testing set were calculated using this model. Then, we examined the SZ-HC group effect on Δage and whether this effect was moderated by chronological age using the regression spline model. The results showed that Δage was significantly elevated in the age > 30 group in patients (p < 0.001) but not in age ≤ 30 group (p = 0.364). Δage in patients was significantly and negatively associated with both working memory (β = -0.176, p = 0.007) and processing speed (β = -0.519, p = 0.035) while adjusting sex and chronological age. Overall, these findings indicate that the Δage is elevated in SZs and become significantly from the third decade of life; the increase of Δage in SZs is associated with the declined neurocognitive performance.
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33
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Thomas MB, Raghava JM, Pantelis C, Rostrup E, Nielsen MØ, Jensen MH, Glenthøj BY, Mandl RCW, Ebdrup BH, Fagerlund B. Associations between cognition and white matter microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls: A multivariate pattern analysis. Cortex 2021; 139:282-297. [PMID: 33933719 DOI: 10.1016/j.cortex.2021.03.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 01/19/2021] [Accepted: 03/01/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Cognitive functions have been associated with white matter (WM) microstructure in schizophrenia, but most studies are limited by examining only select cognitive measures and single WM tracts in chronic, medicated patients. It is unclear if the cognition-WM relationship differs between antipsychotic-naïve patients with schizophrenia and healthy controls, as differential associations have not been directly examined. Here we examine if there are differential patterns of associations between cognition and WM microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls, and we characterize reliable contributors to the pattern of associations across multiple cognitive domains and WM regions, in order to elucidate white matter contribution to the neural underpinnings of cognitive deficits. METHODS Thirty-six first-episode antipsychotic-naïve patients with schizophrenia and 52 matched healthy controls underwent cognitive tests and diffusion-weighted imaging on a 3T Magnetic Resonance Imaging scanner. Using a multivariate partial least squares correlation analysis, we included 14 cognitive variables and mean fractional anisotropy values of 48 WM regions. RESULTS Initial analyses showed significant group differences in both measures of WM and cognition. There was no group interaction effect in the pattern of associations between cognition and WM microstructure. The combined analysis of patients and controls lead to a significant pattern of associations (omnibus test p = .015). Thirty-four regions and seven cognitive functions contributed reliably to the associations. CONCLUSIONS The lack of an interaction effect suggests similar associations in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls. This, together with the differences in both WM and cognitive measurements, supports the involvement of WM in cognitive deficits in schizophrenia. Our findings add to the field by showing a coherent picture of the overall pattern of association between cognition and WM. These findings increase our understanding of the impact of WM on cognition, contributing to the search for neuromarkers of cognitive deficits in schizophrenia.
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Affiliation(s)
- Marie B Thomas
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
| | - Jayachandra M Raghava
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Christos Pantelis
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, Victoria, Australia.
| | - Egill Rostrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Mette Ø Nielsen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Maria H Jensen
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark.
| | - Birte Y Glenthøj
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - René C W Mandl
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; UMC Brain Center, University Medical Center Utrecht, Utrecht, Netherlands.
| | - Bjørn H Ebdrup
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Birgitte Fagerlund
- Centre for Neuropsychiatric Schizophrenia Research, CNSR and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark.
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Kochunov P, Zavaliangos-Petropulu A, Jahanshad N, Thompson PM, Ryan MC, Chiappelli J, Chen S, Du X, Hatch K, Adhikari B, Sampath H, Hare S, Kvarta M, Goldwaser E, Yang F, Olvera RL, Fox PT, Curran JE, Blangero J, Glahn DC, Tan Y, Hong LE. A White Matter Connection of Schizophrenia and Alzheimer's Disease. Schizophr Bull 2021; 47:197-206. [PMID: 32681179 PMCID: PMC7825012 DOI: 10.1093/schbul/sbaa078] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Schizophrenia (SZ) is a severe psychiatric illness associated with an elevated risk for developing Alzheimer's disease (AD). Both SZ and AD have white matter abnormalities and cognitive deficits as core disease features. We hypothesized that aging in SZ patients may be associated with the development of cerebral white matter deficit patterns similar to those observed in AD. We identified and replicated aging-related increases in the similarity between white matter deficit patterns in patients with SZ and AD. The white matter "regional vulnerability index" (RVI) for AD was significantly higher in SZ patients compared with healthy controls in both the independent discovery (Cohen's d = 0.44, P = 1·10-5, N = 173 patients/230 control) and replication (Cohen's d = 0.78, P = 9·10-7, N = 122 patients/64 controls) samples. The degree of overlap with the AD deficit pattern was significantly correlated with age in patients (r = .21 and .29, P < .01 in discovery and replication cohorts, respectively) but not in controls. Elevated RVI-AD was significantly associated with cognitive measures in both SZ and AD. Disease and cognitive specificities were also tested in patients with mild cognitive impairment and showed intermediate overlap. SZ and AD have diverse etiologies and clinical courses; our findings suggest that white matter deficits may represent a key intersecting point for these 2 otherwise distinct diseases. Identifying mechanisms underlying this white matter deficit pattern may yield preventative and treatment targets for cognitive deficits in both SZ and AD patients.
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Affiliation(s)
- Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Artemis Zavaliangos-Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California of USC, Marina del Rey, CA
| | - Meghann C Ryan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Joshua Chiappelli
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Shuo Chen
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Xiaoming Du
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Kathryn Hatch
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Bhim Adhikari
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Hemalatha Sampath
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Stephanie Hare
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Mark Kvarta
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Eric Goldwaser
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Rene L Olvera
- Department of Psychiatry, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas Rio Grande Valley, Brownsville, TX
| | - David C Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, MA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD
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Hegde RR, Kelly S, Lutz O, Guimond S, Karayumak SC, Mike L, Mesholam-Gately RI, Pasternak O, Kubicki M, Eack SM, Keshavan MS. Association of white matter microstructure and extracellular free-water with cognitive performance in the early course of schizophrenia. Psychiatry Res Neuroimaging 2020; 305:111159. [PMID: 32919288 DOI: 10.1016/j.pscychresns.2020.111159] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 07/26/2020] [Accepted: 08/12/2020] [Indexed: 10/23/2022]
Abstract
Schizophrenia (SZ) is proposed as a disorder of dysconnectivity underlying cognitive impairments and clinical manifestations. Although previous studies have shown extracellular changes in white matter of first-episode SZ, little is known about the transition period towards chronicity and its association with cognition. Free-water (FW) imaging was applied to 79 early course SZ participants and 29 controls to detect white matter axonal and extracellular differences during this phase of illness. Diffusion-weighted images were collected from two sites, harmonized, and processed using a pipeline separately modeling water diffusion in tissue (FAt) and extracellular space (FW). Tract-Based Spatial Statistics was performed using the ENIGMA-DTI protocols. SZ showed FAt reductions in the posterior thalamic radiation (PTR) and FW elevations in the cingulum compared to controls, suggesting FAt and FW changes in the early course of SZ. In SZ, greater FAt of the fornix & stria terminalis (FXST) was positively associated with Theory of Mind performance; average whole-brain FAt, FAt of the FXST and the PTR were positively associated with greater working memory performance; average whole-brain FAt was positively associated with visual learning. Further studies are necessary to better understand the neurobiological mechanisms of SZ for developing intervention strategies to preserve brain structure and function.
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Affiliation(s)
- Rachal R Hegde
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Olivia Lutz
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Synthia Guimond
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; The Royal's Institute of Mental Health Research, Department of Psychiatry, University of Ottawa, ON, Canada
| | - Suheyla Cetin Karayumak
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Luke Mike
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Raquelle I Mesholam-Gately
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Shaun M Eack
- Department of Psychiatry and School of Social Work, University of Pittsburgh, Pittsburgh, PA, USA
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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36
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Yang M, Gao S, Zhang X. Cognitive deficits and white matter abnormalities in never-treated first-episode schizophrenia. Transl Psychiatry 2020; 10:368. [PMID: 33139736 PMCID: PMC7608674 DOI: 10.1038/s41398-020-01049-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 09/11/2020] [Accepted: 09/29/2020] [Indexed: 02/06/2023] Open
Abstract
Cognitive impairment is viewed as a core symptom of schizophrenia (SCZ), but its pathophysiological mechanism remains unclear. White matter (WM) disruption is considered to be a central abnormality that may contribute to cognitive impairment in SCZ patients. However, few studies have addressed the association between cognition and WM integrity in never-treated first-episode (NTFE) patients with SCZ. In this study, we used the MATRICS Consensus Cognitive Battery (MCCB) to evaluate cognitive function in NTFE patients (n = 39) and healthy controls (n = 30), and associated it with whole-brain fractional anisotropy (FA) values obtained via voxel-based diffusion tensor imaging. We found that FA was lower in five brain areas of SCZ patients, including the cingulate gyrus, internal capsule, corpus callosum, cerebellum, and brainstem. Compared with the healthy control group, the MCCB's total score and 8 out of 10 subscores were significantly lower in NTFE patients (all p < 0.001). Moreover, in patients but not healthy controls, the performance in the Trail Making Test was negatively correlated with the FA value in the left cingulate. Our findings provide evidence that WM disconnection is involved in some cognitive impairment in the early course of SCZ.
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Affiliation(s)
- Mi Yang
- grid.54549.390000 0004 0369 4060The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China ,grid.54549.390000 0004 0369 4060School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, China ,The Fourth People’s Hospital of Chengdu, Chengdu, China
| | - Shan Gao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.
| | - Xiangyang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China. .,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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Kristensen TD, Ebdrup BH, Hjorthøj C, Mandl RCW, Raghava JM, Jepsen JRM, Fagerlund B, Glenthøj LB, Wenneberg C, Krakauer K, Pantelis C, Glenthøj BY, Nordentoft M. No Effects of Cognitive Remediation on Cerebral White Matter in Individuals at Ultra-High Risk for Psychosis-A Randomized Clinical Trial. Front Psychiatry 2020; 11:873. [PMID: 33005161 PMCID: PMC7485415 DOI: 10.3389/fpsyt.2020.00873] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 08/10/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Individuals at ultra-high risk for psychosis (UHR) present with subtle alterations in cerebral white matter (WM), which appear to be associated with clinical and functional outcome. The effect of cognitive remediation on WM organization in UHR individuals has not been investigated previously. METHODS In a randomized, clinical trial, UHR individuals aged 18 to 40 years were assigned to treatment as usual (TAU) or TAU plus cognitive remediation for 20 weeks. Cognitive remediation comprised 20 x 2-h sessions of neurocognitive and social-cognitive training. Primary outcome was whole brain fractional anisotropy derived from diffusion weighted imaging, statistically tested as an interaction between timepoint and treatment group. Secondary outcomes were restricted to five predefined region of interest (ROI) analyses on fractional anisotropy, axial diffusivity, radial diffusivity and mean diffusivity. For significant timepoint and treatment group interactions within these five ROIs, we explored associations between longitudinal changes in WM and cognitive functions/clinical symptoms. Finally, we explored dose-response effects of cognitive remediation on WM. RESULTS A total of 111 UHR individuals were included. Attrition-rate was 26%. The cognitive remediation group completed on average 12 h of neurocognitive training, which was considerably lower than per protocol. We found no effect of cognitive remediation on whole-brain FA when compared to treatment as usual. Secondary ROI analyses revealed a nominal significant interaction between timepoint*treatment of AD in left medial lemniscus (P=0.016) which did not survive control for multiple comparisons. The exploratory test showed that this change in AD correlated to improvements of mental flexibility in the cognitive remediation group (p=0.001). We found no dose-response effect of neurocognitive training on WM. CONCLUSIONS Cognitive remediation comprising 12 h of neurocognitive training on average did not improve global or regional WM organization in UHR individuals. Further investigations of duration and intensity of cognitive training as necessary prerequisites of neuroplasticity-based changes are warranted. CLINICAL TRIAL REGISTRATION ClinicalTrials.gov, identifier NCT02098408.
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Affiliation(s)
- Tina D Kristensen
- Copenhagen Research Center for Mental Health, CORE, Mental Health Centre Copenhagen, University of Copenhagen, Hellerup, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Bjørn H Ebdrup
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Melbourne Neuropsychiatry Center, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Carsten Hjorthøj
- Copenhagen Research Center for Mental Health, CORE, Mental Health Centre Copenhagen, University of Copenhagen, Hellerup, Denmark
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - René C W Mandl
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Jayachandra M Raghava
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, University of Copenhagen, Glostrup, Denmark
| | - Jens Richardt M Jepsen
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, University of Copenhagen, Hellerup, Denmark
| | - Birgitte Fagerlund
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Psychology, Faculty of Social Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Louise B Glenthøj
- Copenhagen Research Center for Mental Health, CORE, Mental Health Centre Copenhagen, University of Copenhagen, Hellerup, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Christina Wenneberg
- Copenhagen Research Center for Mental Health, CORE, Mental Health Centre Copenhagen, University of Copenhagen, Hellerup, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Kristine Krakauer
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Christos Pantelis
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Melbourne Neuropsychiatry Center, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - Birte Y Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Merete Nordentoft
- Copenhagen Research Center for Mental Health, CORE, Mental Health Centre Copenhagen, University of Copenhagen, Hellerup, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, CINS, and Center for Neuropsychiatric Schizophrenia Research, CNSR, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Zhong S, Wei L, Zhao C, Yang L, Di Z, Francks C, Gong G. Interhemispheric Relationship of Genetic Influence on Human Brain Connectivity. Cereb Cortex 2020; 31:77-88. [DOI: 10.1093/cercor/bhaa207] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 07/03/2020] [Accepted: 07/07/2020] [Indexed: 12/25/2022] Open
Abstract
Abstract
To understand the origins of interhemispheric differences and commonalities/coupling in human brain wiring, it is crucial to determine how homologous interregional connectivities of the left and right hemispheres are genetically determined and related. To address this, in the present study, we analyzed human twin and pedigree samples with high-quality diffusion magnetic resonance imaging tractography and estimated the heritability and genetic correlation of homologous left and right white matter (WM) connections. The results showed that the heritability of WM connectivity was similar and coupled between the 2 hemispheres and that the degree of overlap in genetic factors underlying homologous WM connectivity (i.e., interhemispheric genetic correlation) varied substantially across the human brain: from complete overlap to complete nonoverlap. Particularly, the heritability was significantly stronger and the chance of interhemispheric complete overlap in genetic factors was higher in subcortical WM connections than in cortical WM connections. In addition, the heritability and interhemispheric genetic correlations were stronger for long-range connections than for short-range connections. These findings highlight the determinants of the genetics underlying WM connectivity and its interhemispheric relationships, and provide insight into genetic basis of WM connectivity asymmetries in both healthy and disease states.
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Affiliation(s)
- Suyu Zhong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Long Wei
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong 250101, China
| | - Chenxi Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Zengru Di
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, 6525 EN Nijmegen, The Netherlands
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
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Talukder MA. Relating diffusion-weighted magnetic resonance imaging of brain white matter to cognitive processing-speed deficits in schizophrenia. Biomed Phys Eng Express 2020; 6:055007. [PMID: 33444238 DOI: 10.1088/2057-1976/aba3ba] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) analyses of diffusion-weighted magnetic resonance imaging (MRI) show that diffusional fractional anisotropy (FA) and kurtosis anisotropy (KA) of water inside brain white matter decrease for schizophrenic patients from that for healthy persons. DTI and DKI are statistical approaches and do not directly point to the underlying neurobiological reasons. In schizophrenia, it is believed that the demyelination of axons-microstructures that constitute the brain white matter-increases lateral diffusion of water and causes defective neural communications, resulting cognitive processing-speed deficits. Here, we use a simple but realistic neurobiological model for brain white matter and solve the Bloch-Torrey equation using numerical finite-element method to find out the underlying reasons of cognitive deficits in schizophrenia. FA and KA are calculated from computationally obtained diffusion-weighted MRI data after a Stejskal-Tanner gradient pulse sequence is applied to a periodic array of tubular axons with circular cross-sections. The calculated FA and KA decrease when the axon walls are more permeable to water, agree with the experimental findings, and correlate with the cognitive processing speeds of healthy persons and schizophrenic patients, and thus, help to understand the underlying reasons of cognitive processing-speed deficits in schizophrenia.
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Affiliation(s)
- Muhammad Anisuzzaman Talukder
- Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1205, Bangladesh
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40
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Guevara M, Guevara P, Román C, Mangin JF. Superficial white matter: A review on the dMRI analysis methods and applications. Neuroimage 2020; 212:116673. [DOI: 10.1016/j.neuroimage.2020.116673] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 02/17/2020] [Accepted: 02/19/2020] [Indexed: 12/12/2022] Open
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The origin and development of subcortical U-fibers in gyrencephalic ferrets. Mol Brain 2020; 13:37. [PMID: 32156301 PMCID: PMC7063767 DOI: 10.1186/s13041-020-00575-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 02/27/2020] [Indexed: 11/17/2022] Open
Abstract
In the white matter of the human cerebrum, the majority of cortico-cortical fibers are of short range, connecting neighboring cortical areas. U-fibers represent connections between neighboring areas and are located in the white matter immediately deep to the cerebral cortex. Using gyrencephalic carnivore ferrets, here we investigated the neurochemical, anatomical and developmental features of U-fibers. We demonstrate that U-fibers were derived from neighboring cortical areas in ferrets. U-fiber regions in ferrets were intensely stained with Gallyas myelin staining and Turnbull blue iron staining. We further found that U-fibers were derived from neurons in both upper and lower layers in neighboring areas of the cerebral cortex and that U-fibers were formed later than axons in the deep white matter during development. Our findings shed light on the fundamental features of U-fibers in the gyrencephalic cerebral cortex. Because genetic manipulation techniques for ferrets are now available, ferrets should be an important option for investigating the development, functions and pathophysiological changes of U-fibers.
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Bigham B, Zamanpour SA, Zemorshidi F, Boroumand F, Zare H. Identification of Superficial White Matter Abnormalities in Alzheimer's Disease and Mild Cognitive Impairment Using Diffusion Tensor Imaging. J Alzheimers Dis Rep 2020; 4:49-59. [PMID: 32206757 PMCID: PMC7081087 DOI: 10.3233/adr-190149] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/03/2020] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) estimates the microstructural alterations of the brain, as a magnetic resonance imaging (MRI)-based neuroimaging technique. Prior DTI studies reported decreased structural integrity of the superficial white matter (SWM) in the brain diseases. OBJECTIVE This study aimed to determine the diffusion characteristics of SWM in Alzheimer's disease (AD) and mild cognitive impairment (MCI) using tractography and region of interest (ROI) approaches. METHODS The diffusion MRI data were downloaded from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database on 24 patients with AD, 24 with MCI, and 24 normal control (NC) subjects. DTI processing was performed using DSI Studio software. First, for ROI-based analysis, The superficial white matter was divided into right and left frontal, parietal, temporal, insula, limbic and occipital regions by the Talairach Atlas, Then, for tractography-based analysis, the tractography of each of these regions was performed with 100000 seeds. Finally, the average diffusion values were extracted from voxels within the ROIs and tracts. RESULTS Both tractography and ROI analyses showed a significant difference in radial, axial and mean diffusivity values between the three groups (p < 0.05) across most of the SWM. Furthermore, The Mini-Mental State Examination was significantly correlated with radial, axial, and mean diffusivity values in parietal and temporal lobes SWM in the AD group (p < 0.05). CONCLUSION DTI provided information indicating microstructural changes in the SWM of patients with AD and MCI. Therefore, assessment of the SWM using DTI may be helpful for the clinical diagnosis of patients with AD and MCI.
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Affiliation(s)
- Bahare Bigham
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyed Amir Zamanpour
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fariba Zemorshidi
- Department of Neurology, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Farzaneh Boroumand
- Student Research Committee, Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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Wang S, Gong G, Zhong S, Duan J, Yin Z, Chang M, Wei S, Jiang X, Zhou Y, Tang Y, Wang F. Neurobiological commonalities and distinctions among 3 major psychiatric disorders: a graph theoretical analysis of the structural connectome. J Psychiatry Neurosci 2020; 45:15-22. [PMID: 31368294 PMCID: PMC6919917 DOI: 10.1503/jpn.180162] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND White matter network alterations have increasingly been implicated in major depressive disorder, bipolar disorder and schizophrenia. The aim of this study was to identify shared and distinct white matter network alterations among the 3 disorders. METHODS We used analysis of covariance, with age and gender as covariates, to investigate white matter network alterations in 123 patients with schizophrenia, 123 with bipolar disorder, 124 with major depressive disorder and 209 healthy controls. RESULTS We found significant group differences in global network efficiency (F = 3.386, p = 0.018), nodal efficiency (F = 8.015, p < 0.001 corrected for false discovery rate [FDR]) and nodal degree (F = 5.971, pFDR < 0.001) in the left middle occipital gyrus, as well as nodal efficiency (F = 6.930, pFDR < 0.001) and nodal degree (F = 5.884, pFDR < 0.001) in the left postcentral gyrus. We found no significant alterations in patients with major depressive disorder. Post hoc analyses revealed that compared with healthy controls, patients in the schizophrenia and bipolar disorder groups showed decreased global network efficiency, nodal efficiency and nodal degree in the left middle occipital gyrus. Furthermore, patients in the schizophrenia group showed decreased nodal efficiency and nodal degree in the left postcentral gyrus compared with healthy controls. LIMITATIONS Our findings could have been confounded in part by treatment differences. CONCLUSION Our findings implicate graded white matter network alterations across the 3 disorders, enhancing our understanding of shared and distinct pathophysiological mechanisms across diagnoses and providing vital insights into neuroimaging-based methods for diagnosis and research.
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Affiliation(s)
- Shuai Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Gaolang Gong
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Suyu Zhong
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Jia Duan
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Zhiyang Yin
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Miao Chang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Shengnan Wei
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Xiaowei Jiang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Yifang Zhou
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Yanqing Tang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
| | - Fei Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Yin, Tang, F. Wang); the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China (Gong, Zhong); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Chang, Wei, Jiang, F. Wang); the Brain Function Research Section, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (S. Wang, Duan, Chang, Wei, Jiang, Zhou, Tang, F. Wang); and the Department of Gerontology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China (Zhou, Tang)
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Makowski C, Lewis JD, Lepage C, Malla AK, Joober R, Lepage M, Evans AC. Structural Associations of Cortical Contrast and Thickness in First Episode Psychosis. Cereb Cortex 2019; 29:5009-5021. [PMID: 30844050 PMCID: PMC6918925 DOI: 10.1093/cercor/bhz040] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 01/22/2019] [Indexed: 01/22/2023] Open
Abstract
There is growing evidence that psychosis is characterized by brain network abnormalities. Analyzing morphological abnormalities with T1-weighted structural MRI may be limited in discovering the extent of deviations in cortical associations. We assess whether structural associations of either cortical white-gray contrast (WGC) or cortical thickness (CT) allow for a better understanding of brain structural relationships in first episode of psychosis (FEP) patients. Principal component and structural covariance analyses were applied to WGC and CT derived from T1-weighted MRI for 116 patients and 88 controls, to explore sets of brain regions that showed group differences, and associations with symptom severity and cognitive ability in patients. We focused on 2 principal components: one encompassed primary somatomotor regions, which showed trend-like group differences in WGC, and the second included heteromodal cortices. Patients' component scores were related to general psychopathology for WGC, but not CT. Structural covariance analyses with WGC revealed group differences in pairwise correlations across widespread brain regions, mirroring areas derived from PCA. More group differences were uncovered with WGC compared with CT. WGC holds potential as a proxy measure of myelin from commonly acquired T1-weighted MRI and may be sensitive in detecting systems-level aberrations in early psychosis, and relationships with clinical/cognitive profiles.
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Affiliation(s)
- Carolina Makowski
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
- Department of Psychiatry, McGill University, Verdun, Canada
| | - John D Lewis
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Claude Lepage
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
| | - Ashok K Malla
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Ridha Joober
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Martin Lepage
- Department of Psychiatry, McGill University, Verdun, Canada
- Prevention and Early Intervention Program for Psychosis, Douglas Mental Health University Institute, Verdun, Canada
| | - Alan C Evans
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada
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Haigh SM, Eack SM, Keller T, Minshew NJ, Behrmann M. White matter structure in schizophrenia and autism: Abnormal diffusion across the brain in schizophrenia. Neuropsychologia 2019; 135:107233. [PMID: 31655160 PMCID: PMC6884694 DOI: 10.1016/j.neuropsychologia.2019.107233] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 10/14/2019] [Accepted: 10/14/2019] [Indexed: 01/23/2023]
Abstract
BACKGROUND Schizophrenia and autism share many behavioral and neurological similarities, including altered white matter tract structure. However, because schizophrenia and autism are rarely compared directly, it is difficult to establish whether white matter abnormalities are disorder-specific or are common across these disorders that share some symptomatology. METHODS In the current study, we compared white matter water diffusion using tensor imaging in 25 adults with autism, 15 adults with schizophrenia, all with IQ scores above 88, and 19 neurotypical adults. RESULTS Although the three groups evinced no statistically significant differences in measures of fractional anisotropy (FA), the schizophrenia group showed significantly greater mean diffusivity (MD; Cohen's d > 0.77), due to greater radial diffusivity (RD; Cohen's d > 0.92), compared to both the autism and control groups. This effect was evident across the brain rather than specific to a particular tract. CONCLUSIONS The greater MD and RD in schizophrenia appears to be diagnosis-specific. The altered diffusion may reflect subtle abnormalities in myelination, which could be a potential mechanism underlying the widespread behavioral deficits associated with schizophrenia.
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Affiliation(s)
- Sarah M Haigh
- Department of Psychology, Carnegie Mellon University, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University, USA; Department of Psychology and Center for Integrative Neuroscience, University of Nevada, Reno, USA.
| | - Shaun M Eack
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; School of Social Work, University of Pittsburgh, USA
| | - Timothy Keller
- Department of Psychology, Carnegie Mellon University, USA
| | - Nancy J Minshew
- Department of Psychiatry, University of Pittsburgh School of Medicine, USA; Department of Neurology, University of Pittsburgh, USA
| | - Marlene Behrmann
- Department of Psychology, Carnegie Mellon University, USA; Center for the Neural Basis of Cognition, Carnegie Mellon University, USA
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46
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Stojanovski S, Nazeri A, Lepage C, Ameis S, Voineskos AN, Wheeler AL. Microstructural abnormalities in deep and superficial white matter in youths with mild traumatic brain injury. NEUROIMAGE-CLINICAL 2019; 24:102102. [PMID: 31795058 PMCID: PMC6889799 DOI: 10.1016/j.nicl.2019.102102] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 09/23/2019] [Accepted: 11/19/2019] [Indexed: 11/19/2022]
Abstract
BACKGROUND Diffusion Tensor Imaging (DTI) studies of traumatic brain injury (TBI) have focused on alterations in microstructural features of deep white matter fibers (DWM), though post-mortem studies have demonstrated that injured axons are often observed at the gray-white matter interface where superficial white matter fibers (SWM) mediate local connectivity. OBJECTIVES To examine microstructural alterations in SWM and DWM in youths with a history of mild TBI and examine the relationship between white matter alterations and attention. METHODS Using DTIDWM fractional anisotropy (FA) and SWM FA in youths with mild TBI (TBI, n=63) were compared to typically developing and psychopathology matched control groups (n=63 each). Following tract-based spatial statistics, SWM FA was assessed by applying a probabilistic tractography derived SWM mask, and DWM FA was captured with a white matter fiber tract mask. Voxel-wise z-score calculations were used to derive a count of voxels with abnormally high and low FA for each participant. Analyses examined DWM and SWM FA differences between TBI and control groups, the relationship between attention and DWM and SWM FA and the relative susceptibility of SWM compared to DWM FA to alterations associated with mild TBI. RESULTS Case-based comparisons revealed more voxels with low FA and fewer voxels with high FA in SWM in youths with mild TBI compared to both control groups. Equivalent comparisons in DWM revealed a similar pattern of results, however, no group differences for low FA in DWM were found between mild TBI and the control group with matched psychopathology. Slower processing speed on the attention task was correlated with the number of voxels with low FA in SWM in youths with mild TBI. CONCLUSIONS Within a sample of youths with a history of mild TBI, this study identified abnormalities in SWM microstructure associated with processing speed. The majority of DTI studies of TBI have focused on long-range DWM fiber tracts, often overlooking the SWM fiber type.
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Affiliation(s)
- Sonja Stojanovski
- Neuroscience and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Arash Nazeri
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Stephanie Ameis
- Neuroscience and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; The Margaret and Wallace McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Aristotle N Voineskos
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, Toronto, Ontario; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Anne L Wheeler
- Neuroscience and Mental Health Program, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada.
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47
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Gahm JK, Shi Y. Surface-based Tracking of U-fibers in the Superficial White Matter. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2019; 11766:538-546. [PMID: 33860288 PMCID: PMC8046261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The superficial white matter (SWM) lies directly underneath the cortical ribbon and contains the short association fibers, or U-fibers, that connect neighboring gyri. Connectivity of these U-fibers is important for various neuroscientific research from the development to the aging of the brain. Nonetheless, conventional tractography methods can only provide a partial representation of these connections. Moreover, previous studies on U-fibers mainly extract tracts based on their shape characteristics without imposing the biologically critical condition that they should tightly follow the cortical surface. In this work we leverage the high resolution diffusion imaging data from the Human Connectome Project (HCP), and develop a novel surface-based framework for reconstructing the U-fibers. Guided by the projected fiber orientation distributions (FODs) on cortical surfaces, our method tracks the U-fibers from sulcal seed regions to neighboring gyrus on the triangular mesh representation of the cortex. Compared to volume-based tractography, the main advantage of our method is that it is intrinsic to the cortical geometry. More specifically, we define a novel approach for measuring the change of angles on the tangent space of the surface and use them to determine the U-fiber passing through a sulcal seed point. In experimental results, we compare our surface-based method with state-of-the-art FOD-based tractography from MRtrix on a large-scale dataset of 484 HCP subjects, and demonstrate that our method clearly achieves superior performance on the reconstruction of U-fibers between the precentral and postcentral gyrus.
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48
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Ji E, Guevara P, Guevara M, Grigis A, Labra N, Sarrazin S, Hamdani N, Bellivier F, Delavest M, Leboyer M, Tamouza R, Poupon C, Mangin JF, Houenou J. Increased and Decreased Superficial White Matter Structural Connectivity in Schizophrenia and Bipolar Disorder. Schizophr Bull 2019; 45:1367-1378. [PMID: 30953566 PMCID: PMC6811818 DOI: 10.1093/schbul/sbz015] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Schizophrenia (SZ) and bipolar disorder (BD) are often conceptualized as "disconnection syndromes," with substantial evidence of abnormalities in deep white matter tracts, forming the substrates of long-range connectivity, seen in both disorders. However, the study of superficial white matter (SWM) U-shaped short-range tracts remained challenging until recently, although findings from postmortem studies suggest they are likely integral components of SZ and BD neuropathology. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in vivo in both SZ and BD for the first time. We performed whole brain tractography in 31 people with SZ, 32 people with BD and 54 controls using BrainVISA and Connectomist 2.0. Segmentation and labeling of SWM tracts were performed using a novel, comprehensive U-fiber atlas. Analysis of covariances yielded significant generalized fractional anisotropy (gFA) differences for 17 SWM bundles in frontal, parietal, and temporal cortices. Post hoc analyses showed gFA reductions in both patient groups as compared with controls in bundles connecting regions involved in language processing, mood regulation, working memory, and motor function (pars opercularis, insula, anterior cingulate, precentral gyrus). We also found increased gFA in SZ patients in areas overlapping the default mode network (inferior parietal, middle temporal, precuneus), supporting functional hyperconnectivity of this network evidenced in SZ. We thus illustrate that short U-fibers are vulnerable to the pathological processes in major psychiatric illnesses, encouraging improved understanding of their anatomy and function.
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Affiliation(s)
- Ellen Ji
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,NeuroSpin CEA Saclay, Gif-sur-Yvette, France,Fondation Fondamental, Créteil, France,To whom correspondence should be addressed; INSERM U955, Hôpitaux Universitaires Mondor, 40 rue de Mesly, Créteil 94010, France; tel: +33-1-49-81-30-51, fax: +33-1-49-81-30-59, e-mail:
| | - Pamela Guevara
- Faculty of Engineering, Universidad de Concepción, Concepción, Chile
| | | | | | | | - Samuel Sarrazin
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,NeuroSpin CEA Saclay, Gif-sur-Yvette, France,Fondation Fondamental, Créteil, France
| | - Nora Hamdani
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,Fondation Fondamental, Créteil, France,AP-HP, Department of Psychiatry and Addictology, Mondor University Hospitals, School of Medicine, DHU PePsy, Créteil, France
| | - Frank Bellivier
- AP-HP, GH Saint-Louis - Lariboisière - F. Widal, Département de Psychiatrie et de Médecine Additologique, INSERM UMR-S1144, Paris Diderot University, Paris, France
| | - Marine Delavest
- AP-HP, GH Saint-Louis - Lariboisière - F. Widal, Département de Psychiatrie et de Médecine Additologique, INSERM UMR-S1144, Paris Diderot University, Paris, France
| | - Marion Leboyer
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,Fondation Fondamental, Créteil, France,AP-HP, Department of Psychiatry and Addictology, Mondor University Hospitals, School of Medicine, DHU PePsy, Créteil, France
| | - Ryad Tamouza
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,Fondation Fondamental, Créteil, France,AP-HP, GH Saint-Louis - Lariboisière - F. Widal, Département de Psychiatrie et de Médecine Additologique, INSERM UMR-S1144, Paris Diderot University, Paris, France
| | | | | | - Josselin Houenou
- INSERM U955 Unit, Mondor Institute for Biomedical Research, Team 15 “Translational Psychiatry”, Créteil, France,NeuroSpin CEA Saclay, Gif-sur-Yvette, France,Fondation Fondamental, Créteil, France,AP-HP, Department of Psychiatry and Addictology, Mondor University Hospitals, School of Medicine, DHU PePsy, Créteil, France
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Kochunov P, Huang J, Chen S, Li Y, Tan S, Fan F, Feng W, Wang Y, Rowland LM, Savransky A, Du X, Chiappelli J, Chen S, Jahanshad N, Thompson PM, Ryan MC, Adhikari B, Sampath H, Cui Y, Wang Z, Yang F, Tan Y, Hong LE. White Matter in Schizophrenia Treatment Resistance. Am J Psychiatry 2019; 176:829-838. [PMID: 31352812 PMCID: PMC6773514 DOI: 10.1176/appi.ajp.2019.18101212] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
OBJECTIVE Failure of antipsychotic medications to resolve symptoms in patients with schizophrenia creates a clinical challenge that is known as treatment resistance. The causes of treatment resistance are unknown, but it is associated with earlier age at onset and more severe cognitive deficits. The authors tested the hypothesis that white matter deficits that are involved in both neurodevelopment and severity of cognitive deficits in schizophrenia are associated with a higher risk of treatment resistance. METHODS The study sample (N=122; mean age, 38.2 years) included schizophrenia patients at treatment initiation (N=45), patients whose symptoms were treatment responsive (N=40), and patients whose symptoms were treatment resistant (N=37), as well as healthy control subjects (N=78; mean age, 39.2 years). White matter regional vulnerability index (RVI) was tested as a predictor of treatment resistance and cognitive deficits. Higher RVI is indicative of better agreement between diffusion tensor imaging fractional anisotropy across the brain in an individual and the pattern identified by the largest-to-date meta-analysis of white matter deficits in schizophrenia. RESULTS Patients with treatment-resistant symptoms showed the highest white matter RVI (mean=0.38 [SD=0.2]), which was significantly higher than the RVI among patients with treatment-responsive symptoms (mean=0.30 [SD=0.02]). At the onset of treatment, schizophrenia patients showed significantly higher RVI than healthy control subjects (mean=0.18 [SD=0.03] and mean=0.13 [SD=0.02], respectively). RVIs were significantly correlated with performance on processing speed and negative symptoms. CONCLUSIONS Schizophrenia affects white matter microstructure in specific regional patterns. Susceptibility to white matter regional deficits is associated with an increased likelihood of treatment resistance. Developments to overcome schizophrenia treatment resistance should consider white matter as an important target.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA,Corresponding Authors: Dr. Kochunov (), Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA, Phone: (410) 402-6110, Fax: (410) 402-6778; Dr. Tan (), Beijing Huilongguan Hospital, Peking University, Huilongguan Clinical Medical School, Beijing, P. R. China, Phone: (800) 010-83024532, Fax: (800) 010-83020156
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yanli Li
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Wei Feng
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yunhui Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Laura M. Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anya Savransky
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Meghann C. Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hemalatha Sampath
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yimin Cui
- Department of Pharmacy, Peking University First Hospital, Beijing, P.R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China,Corresponding Authors: Dr. Kochunov (), Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA, Phone: (410) 402-6110, Fax: (410) 402-6778; Dr. Tan (), Beijing Huilongguan Hospital, Peking University, Huilongguan Clinical Medical School, Beijing, P. R. China, Phone: (800) 010-83024532, Fax: (800) 010-83020156
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
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50
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Adhikari BM, Hong LE, Sampath H, Chiappelli J, Jahanshad N, Thompson PM, Rowland LM, Calhoun VD, Du X, Chen S, Kochunov P. Functional network connectivity impairments and core cognitive deficits in schizophrenia. Hum Brain Mapp 2019; 40:4593-4605. [PMID: 31313441 DOI: 10.1002/hbm.24723] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 07/03/2019] [Accepted: 07/08/2019] [Indexed: 12/19/2022] Open
Abstract
Cognitive deficits contribute to functional disability in patients with schizophrenia and may be related to altered functional networks that serve cognition. We evaluated the integrity of major functional networks and assessed their role in supporting two cognitive functions affected in schizophrenia: processing speed (PS) and working memory (WM). Resting-state functional magnetic resonance imaging (rsfMRI) data, N = 261 patients and 327 controls, were aggregated from three independent cohorts and evaluated using Enhancing NeuroImaging Genetics through Meta Analysis rsfMRI analysis pipeline. Meta- and mega-analyses were used to evaluate patient-control differences in functional connectivity (FC) measures. Canonical correlation analysis was used to study the association between cognitive deficits and FC measures. Patients showed consistent patterns of cognitive and resting-state FC (rsFC) deficits across three cohorts. Patient-control differences in rsFC calculated using seed-based and dual-regression approaches were consistent (Cohen's d: 0.31 ± 0.09 and 0.29 ± 0.08, p < 10-4 ). RsFC measures explained 12-17% of the individual variations in PS and WM in the full sample and in patients and controls separately, with the strongest correlations found in salience, auditory, somatosensory, and default-mode networks. The pattern of association between rsFC (within-network) and PS (r = .45, p = .07) and WM (r = .36, p = .16), and rsFC (between-network) and PS (r = .52, p = 8.4 × 10-3 ) and WM (r = .47, p = .02), derived from multiple networks was related to effect size of patient-control differences in the functional networks. No association was detected between rsFC and current medication dose or psychosis ratings. Patients demonstrated significant reduction in several FC networks that may partially underlie some of the core neurocognitive deficits in schizophrenia. The strength of connectivity-cognition relationships in different networks was strongly associated with network's vulnerability to schizophrenia.
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Affiliation(s)
- Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Hemalatha Sampath
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Joshua Chiappelli
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, California
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, California
| | - Laura M Rowland
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Vince D Calhoun
- Department of Electrical and Computer Engineering, The Mind Research Network, Albuquerque, New Mexico.,Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, New Mexico
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
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