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Sun Y, Wu D, Yang X, Tang B, Xia C, Luo C, Gong Q, Lui S, Hu N. The associations of peripheral interleukin alterations and hippocampal subfield volume deficits in schizophrenia. Cereb Cortex 2024; 34:bhae308. [PMID: 39077921 DOI: 10.1093/cercor/bhae308] [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: 05/08/2024] [Revised: 07/03/2024] [Accepted: 07/11/2024] [Indexed: 07/31/2024] Open
Abstract
The hippocampus is one of the brain regions most vulnerable to inflammatory insults, and the relationships between peripheral inflammation and hippocampal subfields in patients with schizophrenia remain unclear. In this study, forty-six stably medicated patients with schizophrenia and 48 demographically matched healthy controls (HCs) were recruited. The serum levels of IL - 1β, IL-6, IL-10, and IL-12p70 were measured, and 3D high-resolution T1-weighted magnetic resonance imaging was performed. The IL levels and hippocampal subfield volumes were both compared between patients and HCs. The associations of altered IL levels with hippocampal subfield volumes were assessed in patients. Patients with schizophrenia demonstrated higher serum levels of IL-6 and IL-10 but lower levels of IL-12p70 than HCs. In patients, the levels of IL-6 were positively correlated with the volumes of the left granule cell layer of the dentate gyrus (GCL) and cornu Ammonis (CA) 4, while the levels of IL-10 were negatively correlated with the volumes of those subfields. IL-6 and IL-10 might have antagonistic roles in atrophy of the left GCL and CA4. This suggests a complexity of peripheral cytokine dysregulation and the potential for its selective effects on hippocampal substructures, which might be related to the pathophysiology of schizophrenia.
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Affiliation(s)
- Yuan Sun
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Dongsheng Wu
- Department of Radiology, West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 18, Section 3, South Renmin Road, Chengdu 610041, China
| | - Xiyue Yang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Biqiu Tang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Chao Xia
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Chunyan Luo
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
| | - Na Hu
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
- Department of Radiology, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu 610041, China
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Liu S, Guo Z, Cao H, Li H, Hu X, Cheng L, Li J, Liu R, Xu Y. Altered asymmetries of resting-state MRI in the left thalamus of first-episode schizophrenia. Chronic Dis Transl Med 2022; 8:207-217. [PMID: 36161199 PMCID: PMC9481880 DOI: 10.1002/cdt3.41] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 11/12/2022] Open
Abstract
Background Schizophrenia (SCZ) is a complex psychiatric disorder associated with widespread alterations in the subcortical brain structure. Hemispheric asymmetries are a fundamental organizational principle of the human brain and relate to human psychological and behavioral characteristics. We aimed to explore the state of thalamic lateralization of SCZ. Methods We used voxel-based morphometry (VBM) analysis, whole-brain analysis of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and resting-state seed-based functional connectivity (FC) analysis to investigate brain structural and functional deficits in SCZ. Also, we applied Pearson's correlation analysis to validate the correlation between Positive and Negative Symptom Scale (PANSS) scores and them. Results Compared with healthy controls, SCZ showed increased gray matter volume (GMV) of the left thalamus (t = 2.214, p = 0.029), which positively correlated with general psychosis (r = 0.423, p = 0.010). SCZ also showed increased ALFF in the putamen, the caudate nucleus, the thalamus, fALFF in the nucleus accumbens (NAc), and the caudate nucleus, and decreased fALFF in the precuneus. The left thalamus showed significantly weaker resting-state FC with the amygdala and insula in SCZ. PANSS negative symptom scores were negatively correlated with the resting-state FC between the thalamus and the insula (r = -0.414, p = 0.025). Conclusions Collectively, these results suggest the possibility of aberrant laterality in the left thalamus and its FC with other related brain regions involved in the limbic system.
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Affiliation(s)
- Sha Liu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental DisorderFirst Hospital of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Zhenglong Guo
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Hongbao Cao
- School of Systems BiologyGeorge Mason UniversityManassasVirginiaUSA
| | - Hong Li
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental DisorderFirst Hospital of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Xiaodong Hu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Long Cheng
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Jianying Li
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
| | - Ruize Liu
- Stanley Center for Psychiatric ResearchBroad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - Yong Xu
- Department of PsychiatryFirst Hospital/First Clinical Medical College of Shanxi Medical UniversityTaiyuanShanxiChina
- Department of Mental HealthShanxi Medical UniversityTaiyuanShanxiChina
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3
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Gutman BA, van Erp TG, Alpert K, Ching CRK, Isaev D, Ragothaman A, Jahanshad N, Saremi A, Zavaliangos‐Petropulu A, Glahn DC, Shen L, Cong S, Alnæs D, Andreassen OA, Doan NT, Westlye LT, Kochunov P, Satterthwaite TD, Wolf DH, Huang AJ, Kessler C, Weideman A, Nguyen D, Mueller BA, Faziola L, Potkin SG, Preda A, Mathalon DH, Bustillo J, Calhoun V, Ford JM, Walton E, Ehrlich S, Ducci G, Banaj N, Piras F, Piras F, Spalletta G, Canales‐Rodríguez EJ, Fuentes‐Claramonte P, Pomarol‐Clotet E, Radua J, Salvador R, Sarró S, Dickie EW, Voineskos A, Tordesillas‐Gutiérrez D, Crespo‐Facorro B, Setién‐Suero E, van Son JM, Borgwardt S, Schönborn‐Harrisberger F, Morris D, Donohoe G, Holleran L, Cannon D, McDonald C, Corvin A, Gill M, Filho GB, Rosa PGP, Serpa MH, Zanetti MV, Lebedeva I, Kaleda V, Tomyshev A, Crow T, James A, Cervenka S, Sellgren CM, Fatouros‐Bergman H, Agartz I, Howells F, Stein DJ, Temmingh H, Uhlmann A, de Zubicaray GI, McMahon KL, Wright M, Cobia D, Csernansky JG, Thompson PM, Turner JA, Wang L. A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium. Hum Brain Mapp 2022; 43:352-372. [PMID: 34498337 PMCID: PMC8675416 DOI: 10.1002/hbm.25625] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 01/06/2023] Open
Abstract
Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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Affiliation(s)
- Boris A. Gutman
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Institute for Information Transmission Problems (Kharkevich Institute)MoscowRussia
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Dmitry Isaev
- Department of Biomedical EngineeringDuke UniversityDurhamNorth CarolinaUSA
| | - Anjani Ragothaman
- Department of biomedical engineeringOregon Health and Science universityPortlandOregonUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Arvin Saremi
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Artemis Zavaliangos‐Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - David C. Glahn
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Li Shen
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shan Cong
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dag Alnæs
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Ole Andreas Andreassen
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Nhat Trung Doan
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Theodore D. Satterthwaite
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexander J. Huang
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Charles Kessler
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Andrea Weideman
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Dana Nguyen
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Lawrence Faziola
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Steven G. Potkin
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Adrian Preda
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Daniel H. Mathalon
- Department of Psychiatry and Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
| | - Juan Bustillo
- Departments of Psychiatry & NeuroscienceUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology]Emory UniversityAtlantaGeorgiaUSA
- Department of Electrical and Computer EngineeringThe University of New MexicoAlbuquerqueNew MexicoUSA
| | - Judith M. Ford
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental NeurosciencesFaculty of Medicine, TU‐DresdenDresdenGermany
| | | | - Nerisa Banaj
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Fabrizio Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Federica Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Gianfranco Spalletta
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | | | | | | | - Joaquim Radua
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
- Institut d'Investigacions Biomdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Erin W. Dickie
- Centre for Addiction and Mental Health (CAMH)TorontoCanada
| | | | | | | | | | | | - Stefan Borgwardt
- Department of PsychiatryUniversity of BaselBaselSwitzerland
- Department of Psychiatry and PsychotherapyUniversity of LübeckLübeckGermany
| | | | - Derek Morris
- Centre for Neuroimaging and Cognitive Genomics, Discipline of BiochemistryNational University of Ireland GalwayGalwayIreland
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Dara Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Geraldo Busatto Filho
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Hospital Sirio‐LibanesSao PauloSPBrazil
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Vasily Kaleda
- Department of Endogenous Mental DisordersMental Health Research CenterMoscowRussia
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Tim Crow
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Anthony James
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Simon Cervenka
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Carl M Sellgren
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden
| | - Helena Fatouros‐Bergman
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Ingrid Agartz
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Fleur Howells
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
- SA MRC Unit on Risk & Resilience in Mental DisordersUniversity of Cape TownCape TownWCSouth Africa
| | - Henk Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Department of Child and Adolescent PsychiatryTU DresdenGermany
| | - Greig I. de Zubicaray
- School of Psychology, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Katie L. McMahon
- School of Clinical SciencesQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Margie Wright
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQLDAustralia
| | - Derin Cobia
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychology and Neuroscience CenterBrigham Young UniversityProvoUtahUSA
| | - John G. Csernansky
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Lei Wang
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychiatry and Behavioral HealthOhio State University Wexner Medical CenterColumbusOhioUSA
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Cobia D, Rich C, Smith MJ, Mamah D, Csernansky JG, Wang L. Basal ganglia shape features differentiate schizoaffective disorder from schizophrenia. Psychiatry Res Neuroimaging 2021; 317:111352. [PMID: 34399283 PMCID: PMC8545830 DOI: 10.1016/j.pscychresns.2021.111352] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 06/14/2021] [Accepted: 07/30/2021] [Indexed: 01/18/2023]
Abstract
There is growing evidence that schizophrenia and schizoaffective disorder represent closely related syndromes that vary in severity along a neurobiological continuum. In the present study, volume and shape of the basal ganglia was examined in people with schizophrenia and schizoaffective disorder relative to healthy controls and hypothesized that unique neuroanatomical differences would be observed in each patient group. Magnetic resonance 1.5T images were obtained from schizophrenia (n = 47), schizoaffective disorder (n = 15), and from healthy control (n = 42) participants, matched for age, gender, parental socioeconomic status, and race. The caudate, putamen, and globus pallidus were characterized using high-dimensional brain mapping procedures (Csernansky et al., 2004b). Results revealed significant shape deformations between schizophrenia and schizoaffective disorder that also differed from control subjects. Relative to schizophrenia, schizoaffective subjects showed exaggerated inward deformations indicative of localized volume loss in subregions of the caudate, putamen, and globus pallidus (all p < 0.001). These shape features correlated with mental flexibility and negative symptoms in schizophrenia (all p < 0.05), but not schizoaffective disorder. To the extent that differences in important basal ganglia substructures reflect biological heterogeneity among these two psychotic illnesses, this data could prove useful in improving diagnostic precision, as well as informing the affective component of mental illness.
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Affiliation(s)
- Derin Cobia
- Department of Psychology and Neuroscience Center, Brigham Young University, 1036 KMBL, Provo, UT 84602, USA; Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
| | - Chaz Rich
- Department of Psychology, University of Notre Dame, Notre Dame, Indiana, USA
| | - Matthew J Smith
- School of Social Work, University of Michigan, Ann Arbor, Michigan, USA
| | - Daniel Mamah
- Department of Psychiatry, Washington University, St. Louis, Missouri, USA
| | - John G Csernansky
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, Ohio, USA
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Interhemispheric co-alteration of brain homotopic regions. Brain Struct Funct 2021; 226:2181-2204. [PMID: 34170391 PMCID: PMC8354999 DOI: 10.1007/s00429-021-02318-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 06/07/2021] [Indexed: 11/11/2022]
Abstract
Asymmetries in gray matter alterations raise important issues regarding the pathological co-alteration between hemispheres. Since homotopic areas are the most functionally connected sites between hemispheres and gray matter co-alterations depend on connectivity patterns, it is likely that this relationship might be mirrored in homologous interhemispheric co-altered areas. To explore this issue, we analyzed data of patients with Alzheimer’s disease, schizophrenia, bipolar disorder and depressive disorder from the BrainMap voxel-based morphometry database. We calculated a map showing the pathological homotopic anatomical co-alteration between homologous brain areas. This map was compared with the meta-analytic homotopic connectivity map obtained from the BrainMap functional database, so as to have a meta-analytic connectivity modeling map between homologous areas. We applied an empirical Bayesian technique so as to determine a directional pathological co-alteration on the basis of the possible tendencies in the conditional probability of being co-altered of homologous brain areas. Our analysis provides evidence that: the hemispheric homologous areas appear to be anatomically co-altered; this pathological co-alteration is similar to the pattern of connectivity exhibited by the couples of homologues; the probability to find alterations in the areas of the left hemisphere seems to be greater when their right homologues are also altered than vice versa, an intriguing asymmetry that deserves to be further investigated and explained.
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Abstract
Basal ganglia, which include the striatum and thalamus, have key roles in motivation, emotion, motor function, also contribute to higher-order cognitive function. Previous researches have documented structural and functional alterations in basal ganglia in schizophrenia. While few studies have assessed asymmetries of these characters in basal ganglia of schizophrenia. The current study investigated this issue by using diffusion tensor imaging, anatomic T1-weight image and resting-state functional data from 88 chronic schizophrenic subjects and 92 healthy controls. The structural characteristic, including fractional anisotropy, mean diffusivity (MD) and volume, were extracted and quantified from the subregions of basal ganglia, including caudate, putamen, pallidum and thalamus, through automated atlas-based method. The resting-state functional maps of these regions were also calculated through seed-based functional connectivity. Then, the laterality indexes of structural and functional features were calculated. Compared with healthy controls, schizophrenic subjects showed increased left laterality of volume in striatum and reduced left laterality of volume in thalamus. Furthermore, the difference of laterality of subregions in thalamus is compensatory in schizophrenic subjects. Importantly, the severity of patients' positive symptom was negative corelated with reduced left laterality of volume in thalamus. Our findings provide preliminary evidence demonstrating that the possibility of aberrant laterality in neural pathways and connectivity patterns related to the basal ganglia in schizophrenia.
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Roeske MJ, McHugo M, Vandekar S, Blackford JU, Woodward ND, Heckers S. Incomplete hippocampal inversion in schizophrenia: prevalence, severity, and impact on hippocampal structure. Mol Psychiatry 2021; 26:5407-5416. [PMID: 33437006 PMCID: PMC8589684 DOI: 10.1038/s41380-020-01010-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 12/16/2020] [Accepted: 12/17/2020] [Indexed: 11/09/2022]
Abstract
Incomplete hippocampal inversion (IHI) is an anatomical variant of the human brain resulting from an arrest in brain development, especially prevalent in the left hemisphere. We hypothesized that IHI is more common in schizophrenia and contributes to the well-known hippocampal structural differences. We studied 199 schizophrenia patients and 161 healthy control participants with 3 T MRI to establish IHI prevalence and the relationship of IHI with hippocampal volume and asymmetry. IHI was more prevalent (left hemisphere: 15% of healthy control participants, 27% of schizophrenia patients; right hemisphere: 4% of healthy control participants, 10% of schizophrenia patients) and more severe in schizophrenia patients compared to healthy control participants. Severe IHI cases were associated with a higher rate of automated segmentation failure. IHI contributed to smaller hippocampal volume and increased R > L volume asymmetry in schizophrenia. The increased prevalence and severity of IHI supports the neurodevelopmental model of schizophrenia. The impact of this developmental variant deserves further exploration in studies of the hippocampus in schizophrenia.
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Affiliation(s)
- Maxwell J. Roeske
- grid.412807.80000 0004 1936 9916Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN USA
| | - Maureen McHugo
- grid.412807.80000 0004 1936 9916Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN USA
| | - Simon Vandekar
- grid.412807.80000 0004 1936 9916Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN USA
| | - Jennifer Urbano Blackford
- grid.412807.80000 0004 1936 9916Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN USA ,grid.413806.8Research Health Scientist, Research and Development, Veterans Affairs Medical Center, Nashville, TN USA
| | - Neil D. Woodward
- grid.412807.80000 0004 1936 9916Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN USA
| | - Stephan Heckers
- grid.412807.80000 0004 1936 9916Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN USA
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8
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Martins SB, Telea AC, Falcão AX. Investigating the impact of supervoxel segmentation for unsupervised abnormal brain asymmetry detection. Comput Med Imaging Graph 2020; 85:101770. [PMID: 32854021 DOI: 10.1016/j.compmedimag.2020.101770] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 07/27/2020] [Accepted: 07/31/2020] [Indexed: 11/26/2022]
Abstract
Several brain disorders are associated with abnormal brain asymmetries (asymmetric anomalies). Several computer-based methods aim to detect such anomalies automatically. Recent advances in this area use automatic unsupervised techniques that extract pairs of symmetric supervoxels in the hemispheres, model normal brain asymmetries for each pair from healthy subjects, and treat outliers as anomalies. Yet, there is no deep understanding of the impact of the supervoxel segmentation quality for abnormal asymmetry detection, especially for small anomalies, nor of the added value of using a specialized model for each supervoxel pair instead of a single global appearance model. We aim to answer these questions by a detailed evaluation of different scenarios for supervoxel segmentation and classification for detecting abnormal brain asymmetries. Experimental results on 3D MR-T1 brain images of stroke patients confirm the importance of high-quality supervoxels fit anomalies and the use of a specific classifier for each supervoxel. Next, we present a refinement of the detection method that reduces the number of false-positive supervoxels, thereby making the detection method easier to use for visual inspection and analysis of the found anomalies.
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Affiliation(s)
- Samuel B Martins
- Laboratory of Image Data Science (LIDS), Institute of Computing, University of Campinas, Brazil; Bernoulli Institute, University of Groningen, The Netherlands; Federal Institute of São Paulo, Campinas, Brazil
| | - Alexandru C Telea
- Department of Information and Computing Sciences, Utrecht University, The Netherlands
| | - Alexandre X Falcão
- Laboratory of Image Data Science (LIDS), Institute of Computing, University of Campinas, Brazil
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9
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Martins SB, Telea AC, Falcao AX. Extending Supervoxel-based Abnormal Brain Asymmetry Detection to the Native Image Space. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:450-453. [PMID: 31945935 DOI: 10.1109/embc.2019.8857447] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Most neurological diseases are associated with abnormal brain asymmetries. Recent advances in automatic unsupervised techniques model normal brain asymmetries from healthy subjects only and treat anomalies as outliers. Outlier detection is usually done in a common standard coordinate space that limits its usability. To alleviate the problem, we extend a recent fully unsupervised supervoxel-based approach (SAAD) for abnormal asymmetry detection in the native image space of MR brain images. Experimental results using our new method, called N-SAAD, show that it can achieve higher accuracy in detection with considerably less false positives than a method based on unsupervised deep learning for a large set of MR-T1 images.
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10
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Xie W, Peng CK, Huang CC, Lin CP, Tsai SJ, Yang AC. Functional brain lateralization in schizophrenia based on the variability of resting-state fMRI signal. Prog Neuropsychopharmacol Biol Psychiatry 2018; 86:114-121. [PMID: 29807061 DOI: 10.1016/j.pnpbp.2018.05.020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 05/09/2018] [Accepted: 05/24/2018] [Indexed: 01/20/2023]
Abstract
Abnormal brain lateralization has been implicated in schizophrenia but few studies have focused on the variability of resting-state fMRI signal and its lateralization in schizophrenia. Here we utilized standard deviations (SD) to quantify the variability of resting-state fMRI signal and measured the lateralization index (LI), on the basis of SD of the resting-state fMRI signal in order to assess the difference of brain signal variability across the hemispheres. We recruited 180 patients with schizophrenia and 358 age- and sex-matched healthy volunteers. Between-group comparison revealed that in comparison to healthy volunteers, schizophrenia patients have significantly higher SD of resting-state fMRI activity in left inferior temporal, left fusiform, and right superior medial frontal cortex, and lower SD in right precuneus, posterior cingulum on both sides, right lingual, and left calcarine in the occipital region. Using region of interest approach, most brain regions showed increased leftward lateralization in patients with schizophrenia, as compared with healthy controls. SD and LI were also found to be correlated to age of onset or duration of illness. These results provide further evidence that abnormal variability and lateralization exist in schizophrenia patients, and abnormality in fusiform, lingual and inferior temporal could have potential help to identify the dysfunctional brain lateralization in schizophrenia.
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Affiliation(s)
- Wanqing Xie
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA; School of Information Science and Technology, University of Science and Technology of China, Hefei, China
| | - Chung-Kang Peng
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA
| | - Chu-Chung Huang
- Institute of Brain Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Brain Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Institute of Brain Sciences, National Yang-Ming University, Taipei, Taiwan; Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Albert C Yang
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, USA; Institute of Brain Sciences, National Yang-Ming University, Taipei, Taiwan.
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11
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Pawełczyk A, Kotlicka-Antczak M, Łojek E, Ruszpel A, Pawełczyk T. Schizophrenia patients have higher-order language and extralinguistic impairments. Schizophr Res 2018; 192:274-280. [PMID: 28438437 DOI: 10.1016/j.schres.2017.04.030] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Revised: 04/13/2017] [Accepted: 04/16/2017] [Indexed: 10/19/2022]
Abstract
INTRODUCTION The extralinguistic and paralinguistic aspects of the language refer to higher-order language functions such as lexical-semantic processes, prosody, indirect speech acts or discourse comprehension and production. Studies suggest that these processes are mediated by the Right Hemisphere (RH) and there is also some evidence of RH dysfunctions in schizophrenia. The aim of the paper is to investigate the extralinguistic and paralinguistic processing mediated by Right Hemisphere in schizophrenia patients using a validated and standardized battery of tests. METHODS Two groups of participants were examined: a schizophrenia sample (40 participants) and a control group (39 participants). Extralinguistic and paralinguistic processing was assessed in all subjects by the Polish version of the Right Hemisphere Language Battery (RHLB-PL), which measures comprehension of implicit information, naming, understanding humor, inappropriate remarks and comments, explanation and understanding of metaphors, understanding emotional and language prosody and discourse understanding. RESULTS Schizophrenia patients scored significantly lower than controls in subtests measuring comprehension of implicit information, interpretation of humor, explanation of metaphors, inappropriate remarks and comments, discernment of emotional and language prosody and comprehension of discourse. No differences were observed in naming, understanding metaphors or in processing visuo-spatial information. CONCLUSIONS Extralinguistic and paralinguistic dysfunctions appear to be present in schizophrenia patients and they suggest that RH processing may be disturbed in that group of patients. As the disturbances of higher-order language processes mediated by the RH may cause serious impairments in the social communication of patients, it is worth evaluating them during clinical examination.
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Affiliation(s)
- Agnieszka Pawełczyk
- Department of Affective and Psychotic Disorders, Medical University of Lodz, Poland.
| | | | - Emila Łojek
- Department of Cognitive Neuropsychology, University of Warsaw, Poland
| | - Anna Ruszpel
- Department of Cognitive Neuropsychology, University of Warsaw, Poland
| | - Tomasz Pawełczyk
- Department of Affective and Psychotic Disorders, Medical University of Lodz, Poland
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12
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Kalmady SV, Shivakumar V, Arasappa R, Subramaniam A, Gautham S, Venkatasubramanian G, Gangadhar BN. Clinical correlates of hippocampus volume and shape in antipsychotic-naïve schizophrenia. Psychiatry Res Neuroimaging 2017; 263:93-102. [PMID: 28371658 DOI: 10.1016/j.pscychresns.2017.03.014] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Revised: 03/09/2017] [Accepted: 03/20/2017] [Indexed: 01/25/2023]
Abstract
While volume deficit of hippocampus is an established finding in schizophrenia, very few studies have examined large sample of patients without the confounding effect of antipsychotic treatment. Concurrent evaluation of hippocampus shape will offer additional information on the hippocampal aberrations in schizophrenia. In this study, we analyzed the volume and shape of hippocampus in antipsychotic-naïve schizophrenia patients (N=71) in comparison to healthy controls (N=82). Using 3-T MRI data, gray matter (GM) volume (anterior and posterior sub-divisions) and shape of the hippocampus were analyzed. Schizophrenia patients had significant hippocampal GM volume deficits (specifically the anterior sub-division) in comparison to healthy controls. There were significant positive correlations between anterior hippocampus volume and psychopathology scores of positive syndrome. Shape analyses revealed significant inward deformation of bilateral hippocampal surface in patients. In conclusion, our study findings add robust support for volume deficit in hippocampus in antipsychotic-naïve schizophrenia. Hippocampal shape deficits in schizophrenia observed in this study map to anterior CA1 sub-region. The differential relationship of anterior hippocampus (but not posterior hippocampus) with clinical symptoms is in tune with the findings in animal models. Further systematic studies are needed to evaluate the relationship between these hippocampal gray matter deficits with white matter and functional connectivity to facilitate understanding the hippocampal network abnormalities in schizophrenia.
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Affiliation(s)
- Sunil Vasu Kalmady
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Translational Psychiatry Laboratory, Cognitive Neurobiology Division, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India
| | - Venkataram Shivakumar
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Translational Psychiatry Laboratory, Cognitive Neurobiology Division, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India
| | - Rashmi Arasappa
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India
| | - Aditi Subramaniam
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India
| | - S Gautham
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India
| | - Ganesan Venkatasubramanian
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Translational Psychiatry Laboratory, Cognitive Neurobiology Division, Neurobiology Research Centre, National Institute of Mental Health and Neuro Sciences, Bangalore, India.
| | - Bangalore N Gangadhar
- The Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health and Neuro Sciences, Bangalore, India
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13
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Crum WR, Danckaers F, Huysmans T, Cotel MC, Natesan S, Modo MM, Sijbers J, Williams SCR, Kapur S, Vernon AC. Chronic exposure to haloperidol and olanzapine leads to common and divergent shape changes in the rat hippocampus in the absence of grey-matter volume loss. Psychol Med 2016; 46:3081-3093. [PMID: 27516217 PMCID: PMC5108303 DOI: 10.1017/s0033291716001768] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 06/23/2016] [Accepted: 06/23/2016] [Indexed: 12/15/2022]
Abstract
BACKGROUND One of the most consistently reported brain abnormalities in schizophrenia (SCZ) is decreased volume and shape deformation of the hippocampus. However, the potential contribution of chronic antipsychotic medication exposure to these phenomena remains unclear. METHOD We examined the effect of chronic exposure (8 weeks) to clinically relevant doses of either haloperidol (HAL) or olanzapine (OLZ) on adult rat hippocampal volume and shape using ex vivo structural MRI with the brain retained inside the cranium to prevent distortions due to dissection, followed by tensor-based morphometry (TBM) and elastic surface-based shape deformation analysis. The volume of the hippocampus was also measured post-mortem from brain tissue sections in each group. RESULTS Chronic exposure to either HAL or OLZ had no effect on the volume of the hippocampus, even at exploratory thresholds, which was confirmed post-mortem. In contrast, shape deformation analysis revealed that chronic HAL and OLZ exposure lead to both common and divergent shape deformations (q = 0.05, FDR-corrected) in the rat hippocampus. In particular, in the dorsal hippocampus, HAL exposure led to inward shape deformation, whereas OLZ exposure led to outward shape deformation. Interestingly, outward shape deformations that were common to both drugs occurred in the ventral hippocampus. These effects remained significant after controlling for hippocampal volume suggesting true shape changes. CONCLUSIONS Chronic exposure to either HAL or OLZ leads to both common and divergent effects on rat hippocampal shape in the absence of volume change. The implications of these findings for the clinic are discussed.
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Affiliation(s)
- W. R. Crum
- Department of Neuroimaging,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience,
Centre for Neuroimaging Sciences, De Crespigny
Park, London, UK
| | - F. Danckaers
- Department of Physics,
iMinds-Vision Laboratory, University of
Antwerp, Antwerp, Belgium
| | - T. Huysmans
- Department of Physics,
iMinds-Vision Laboratory, University of
Antwerp, Antwerp, Belgium
| | - M.-C. Cotel
- Department of Psychosis Studies,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience, De
Crespigny Park, London, UK
| | - S. Natesan
- Department of Psychosis Studies,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience, De
Crespigny Park, London, UK
| | - M. M. Modo
- Department of Basic and Clinical
Neuroscience, King's College London,
Institute of Psychiatry, Psychology and
Neuroscience, Maurice Wohl Institute for Clinical
Neuroscience, London, UK
| | - J. Sijbers
- Department of Physics,
iMinds-Vision Laboratory, University of
Antwerp, Antwerp, Belgium
| | - S. C. R. Williams
- Department of Neuroimaging,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience,
Centre for Neuroimaging Sciences, De Crespigny
Park, London, UK
| | - S. Kapur
- Department of Psychosis Studies,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience, De
Crespigny Park, London, UK
| | - A. C. Vernon
- Department of Psychosis Studies,
King's College London, Institute of
Psychiatry, Psychology and Neuroscience, De
Crespigny Park, London, UK
- Department of Basic and Clinical
Neuroscience, King's College London,
Institute of Psychiatry, Psychology and
Neuroscience, Maurice Wohl Institute for Clinical
Neuroscience, London, UK
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14
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Okada N, Fukunaga M, Yamashita F, Koshiyama D, Yamamori H, Ohi K, Yasuda Y, Fujimoto M, Watanabe Y, Yahata N, Nemoto K, Hibar DP, van Erp TGM, Fujino H, Isobe M, Isomura S, Natsubori T, Narita H, Hashimoto N, Miyata J, Koike S, Takahashi T, Yamasue H, Matsuo K, Onitsuka T, Iidaka T, Kawasaki Y, Yoshimura R, Watanabe Y, Suzuki M, Turner JA, Takeda M, Thompson PM, Ozaki N, Kasai K, Hashimoto R. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry 2016; 21:1460-6. [PMID: 26782053 PMCID: PMC5030462 DOI: 10.1038/mp.2015.209] [Citation(s) in RCA: 250] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2015] [Revised: 11/06/2015] [Accepted: 11/13/2015] [Indexed: 12/31/2022]
Abstract
Subcortical structures, which include the basal ganglia and parts of the limbic system, have key roles in learning, motor control and emotion, but also contribute to higher-order executive functions. Prior studies have reported volumetric alterations in subcortical regions in schizophrenia. Reported results have sometimes been heterogeneous, and few large-scale investigations have been conducted. Moreover, few large-scale studies have assessed asymmetries of subcortical volumes in schizophrenia. Here, as a work completely independent of a study performed by the ENIGMA consortium, we conducted a large-scale multisite study of subcortical volumetric differences between patients with schizophrenia and controls. We also explored the laterality of subcortical regions to identify characteristic similarities and differences between them. T1-weighted images from 1680 healthy individuals and 884 patients with schizophrenia, obtained with 15 imaging protocols at 11 sites, were processed with FreeSurfer. Group differences were calculated for each protocol and meta-analyzed. Compared with controls, patients with schizophrenia demonstrated smaller bilateral hippocampus, amygdala, thalamus and accumbens volumes as well as intracranial volume, but larger bilateral caudate, putamen, pallidum and lateral ventricle volumes. We replicated the rank order of effect sizes for subcortical volumetric changes in schizophrenia reported by the ENIGMA consortium. Further, we revealed leftward asymmetry for thalamus, lateral ventricle, caudate and putamen volumes, and rightward asymmetry for amygdala and hippocampal volumes in both controls and patients with schizophrenia. Also, we demonstrated a schizophrenia-specific leftward asymmetry for pallidum volume. These findings suggest the possibility of aberrant laterality in neural pathways and connectivity patterns related to the pallidum in schizophrenia.
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Affiliation(s)
- N Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - M Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan
| | - F Yamashita
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
| | - D Koshiyama
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - H Yamamori
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - K Ohi
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Y Yasuda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - M Fujimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Y Watanabe
- Department of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan
| | - N Yahata
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, Japan
| | - K Nemoto
- Department of Neuropsychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - D P Hibar
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - H Fujino
- Graduate School of Human Sciences, Osaka University, Osaka, Japan
| | - M Isobe
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - S Isomura
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - T Natsubori
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - H Narita
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - N Hashimoto
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - J Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - S Koike
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Office for Mental Health Support, Division for Counseling and Support, The University of Tokyo, Tokyo, Japan
| | - T Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - H Yamasue
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - K Matsuo
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
| | - T Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - T Iidaka
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Y Kawasaki
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - R Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Fukuoka, Japan
| | - Y Watanabe
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
| | - M Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
| | - J A Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Department of Neuroscience, Georgia State University, Atlanta, GA, USA
| | - M Takeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - P M Thompson
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - N Ozaki
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - K Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - R Hashimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - COCORO
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
- Department of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan
- Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, Japan
- Department of Neuropsychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- Graduate School of Human Sciences, Osaka University, Osaka, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
- Office for Mental Health Support, Division for Counseling and Support, The University of Tokyo, Tokyo, Japan
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
- Department of Psychiatry, University of Occupational and Environmental Health, Fukuoka, Japan
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Department of Neuroscience, Georgia State University, Atlanta, GA, USA
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
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15
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Social cognition and brain morphology: implications for developmental brain dysfunction. Brain Imaging Behav 2016; 9:264-74. [PMID: 24788335 DOI: 10.1007/s11682-014-9304-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The social-cognitive deficits associated with several neurodevelopmental and neuropsychiatric disorders have been linked to structural and functional brain anomalies. Given the recent appreciation for quantitative approaches to behavior, in this study we examined the brain-behavior links in social cognition in healthy young adults from a quantitative approach. Twenty-two participants were administered quantitative measures of social cognition, including the social responsiveness scale (SRS), the empathizing questionnaire (EQ) and the systemizing questionnaire (SQ). Participants underwent a structural, 3-T magnetic resonance imaging (MRI) procedure that yielded both volumetric (voxel count) and asymmetry indices. Model fitting with backward elimination revealed that a combination of cortical, limbic and striatal regions accounted for significant variance in social behavior and cognitive styles that are typically associated with neurodevelopmental and neuropsychiatric disorders. Specifically, as caudate and amygdala volumes deviate from the typical R > L asymmetry, and cortical gray matter becomes more R > L asymmetrical, overall SRS and Emotion Recognition scores increase. Social Avoidance was explained by a combination of cortical gray matter, pallidum (rightward asymmetry) and caudate (deviation from rightward asymmetry). Rightward asymmetry of the pallidum was the sole predictor of Interpersonal Relationships and Repetitive Mannerisms. Increased D-scores on the EQ-SQ, an indication of greater systemizing relative to empathizing, was also explained by deviation from the typical R > L asymmetry of the caudate.These findings extend the brain-behavior links observed in neurodevelopmental disorders to the normal distribution of traits in a healthy sample.
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16
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Kalmady SV, Shivakumar V, Gautham S, Arasappa R, Jose DA, Venkatasubramanian G, Gangadhar BN. Dermatoglyphic correlates of hippocampus volume: Evaluation of aberrant neurodevelopmental markers in antipsychotic-naïve schizophrenia. Psychiatry Res 2015; 234:113-20. [PMID: 26385539 DOI: 10.1016/j.pscychresns.2015.09.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Revised: 07/23/2015] [Accepted: 09/02/2015] [Indexed: 12/31/2022]
Abstract
Schizophrenia is a disorder of aberrant neurodevelopment is marked by abnormalities in brain structure and dermatoglyphic traits. However, the link between these two (i.e. dermatoglyphic parameters and brain structure) which share ectodermal origin and common developmental window has not been explored extensively. The current study examined dermatoglyphic correlates of hippocampal volume in antipsychotic-naïve schizophrenia patients in comparison with matched healthy controls. Ridge counts and asymmetry measures for palmar inter-digital areas (a-b, b-c, c-d) were obtained using high resolution digital scans of palms from 89 schizophrenia patients [M:F=48:41] and 48 healthy controls [M:F=30:18]. Brain scans were obtained for subset of subjects including 26 antipsychotic-naïve patients [M:F=13:13] and 29 healthy controls [M:F=19:10] using 3 T-MRI. Hippocampal volume and palmar ridge counts were measured by blinded raters with good inter-rater reliability using valid methods. Directional asymmetry (DA) of b-c and bilateral hippocampal volume were significantly lower in patients than controls. Significant positive correlation was found between DA and ridge count of b-c with bilateral anterior hippocampal volume. Study demonstrates the utility of dermatoglyphic markers in identifying structural changes in the brain which may form the basis for neurodevelopmental pathogenesis in schizophrenia.
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Affiliation(s)
- Sunil V Kalmady
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India; Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
| | - Venkataram Shivakumar
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India; Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
| | - S Gautham
- Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
| | - Rashmi Arasappa
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India; Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
| | - Dania A Jose
- Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
| | - Ganesan Venkatasubramanian
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India; Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India.
| | - B N Gangadhar
- InSTAR Program, Schizophrenia Clinic, Department of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS), Bangalore, India; Translational Psychiatry Laboratory, Neurobiology Research Centre, NIMHANS, Bangalore, India
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17
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Kogan A, Alpert K, Ambite JL, Marcus DS, Wang L. Northwestern University schizophrenia data sharing for SchizConnect: A longitudinal dataset for large-scale integration. Neuroimage 2015; 124:1196-1201. [PMID: 26087378 DOI: 10.1016/j.neuroimage.2015.06.030] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2015] [Revised: 05/06/2015] [Accepted: 06/02/2015] [Indexed: 10/23/2022] Open
Abstract
In this paper, we describe an instance of the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), a schizophrenia-related dataset hosted at XNAT Central, and the SchizConnect data portal used for accessing and sharing the dataset. NUSDAST was built and extended upon existing, standard schemas available for data sharing on XNAT Central (http://central.xnat.org/). With the creation of SchizConnect, we were able to link NUSDAST to other neuroimaging data sources and create a powerful, federated neuroimaging resource.
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Affiliation(s)
- Alex Kogan
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jose Luis Ambite
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA; Digital Government Research Center, Marina del Rey, CA, USA; Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Daniel S Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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18
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Smith MJ, Cobia DJ, Reilly JL, Gilman JM, Roberts AG, Alpert KI, Wang L, Breiter HC, Csernansky JG. Cannabis-related episodic memory deficits and hippocampal morphological differences in healthy individuals and schizophrenia subjects. Hippocampus 2015; 25:1042-51. [PMID: 25760303 DOI: 10.1002/hipo.22427] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 01/22/2015] [Accepted: 01/22/2015] [Indexed: 11/07/2022]
Abstract
Cannabis use has been associated with episodic memory (EM) impairments and abnormal hippocampus morphology among both healthy individuals and schizophrenia subjects. Considering the hippocampus' role in EM, research is needed to evaluate the relationship between cannabis-related hippocampal morphology and EM among healthy and clinical groups. We examined differences in hippocampus morphology between control and schizophrenia subjects with and without a past (not current) cannabis use disorder (CUD). Subjects group-matched on demographics included 44 healthy controls (CON), 10 subjects with a CUD history (CON-CUD), 28 schizophrenia subjects with no history of substance use disorders (SCZ), and 15 schizophrenia subjects with a CUD history (SCZ-CUD). Large-deformation, high-dimensional brain mapping with MRI produced surface-based representations of the hippocampus that were compared across all four groups and correlated with EM and CUD history. Surface maps of the hippocampus were generated to visualize morphological differences. CON-CUD and SCZ-CUD were characterized by distinct cannabis-related hippocampal shape differences and parametric deficits in EM performance. Shape differences observed in CON-CUD were associated with poorer EM performance, while shape differences observed in SCZ-CUD were associated with a longer duration of CUD and shorter duration of CUD remission. A past history of CUD may be associated with notable differences in hippocampal morphology and EM impairments among adults with and without schizophrenia. Although the results may be compatible with a causal hypothesis, we must consider that the observed cannabis-related shape differences in the hippocampus could also be explained as biomarkers of a neurobiological susceptibility to poor memory or the effects of cannabis.
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Affiliation(s)
- Matthew J Smith
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Warren Wright Adolescent Center, Chicago, Illinois
| | - Derin J Cobia
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Warren Wright Adolescent Center, Chicago, Illinois
| | - James L Reilly
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Warren Wright Adolescent Center, Chicago, Illinois
| | - Jodi M Gilman
- Center for Addiction Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Andrea G Roberts
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Warren Wright Adolescent Center, Chicago, Illinois
| | - Kathryn I Alpert
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Hans C Breiter
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- Warren Wright Adolescent Center, Chicago, Illinois
| | - John G Csernansky
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois
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19
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Ming J, Harms MP, Morris JC, Beg MF, Wang L. Integrated cortical structural marker for Alzheimer's disease. Neurobiol Aging 2014; 36 Suppl 1:S53-9. [PMID: 25444604 DOI: 10.1016/j.neurobiolaging.2014.03.042] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2013] [Revised: 02/21/2014] [Accepted: 03/07/2014] [Indexed: 11/16/2022]
Abstract
In this article, we propose an approach to integrate cortical morphology measures for improving the discrimination of individuals with and without very mild Alzheimer's disease (AD). FreeSurfer was applied to scans collected from 83 participants with very mild AD and 124 cognitively normal individuals. We generated cortex thickness, white matter convexity (aka "sulcal depth"), and white matter surface metric distortion measures on a normalized surface atlas in this first study to integrate high resolution gray matter thickness and white matter surface geometric measures in identifying very mild AD. Principal component analysis was applied to each individual structural measure to generate eigenvectors. Discrimination power based on individual and combined measures are compared, based on stepwise logistic regression and 10-fold cross-validation. Global AD likelihood index and surface-based likelihood maps were also generated. Our results show complementary patterns on the cortical surface between thickness, which reflects gray matter atrophy, convexity, which reflects white matter sulcal depth changes and metric distortion, which reflects white matter surface area changes. The classifier integrating all 3 types of surface measures significantly improved classification performance compared with classification based on single measures. The principal component analysis-based approach provides a framework for achieving high discrimination power by integrating high-dimensional data, and this method could be very powerful in future studies for early diagnosis of diseases that are known to be associated with abnormal gyral and sulcal patterns.
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Affiliation(s)
- Jing Ming
- Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, USA.
| | - Michael P Harms
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA; Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - M Faisal Beg
- Biomedical Engineering, Simon Fraser University, British Columbia, Canada
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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20
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Wang L, Kogan A, Cobia D, Alpert K, Kolasny A, Miller MI, Marcus D. Northwestern University Schizophrenia Data and Software Tool (NUSDAST). Front Neuroinform 2013; 7:25. [PMID: 24223551 PMCID: PMC3819522 DOI: 10.3389/fninf.2013.00025] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2013] [Accepted: 10/12/2013] [Indexed: 11/13/2022] Open
Abstract
The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR) datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST), an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data), cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function), clinical (demographic, sibling relationship, SAPS and SANS psychopathology), and genetic (20 polymorphisms) data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions.
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Affiliation(s)
- Lei Wang
- Department of Radiology, Northwestern University Feinberg School of MedicineChicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA
| | - Alex Kogan
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA
| | - Derin Cobia
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of MedicineChicago, IL, USA
| | - Anthony Kolasny
- Department of Biomedical Engineering, Center for Imaging Science, Johns Hopkins UniversityBaltimore, MD, USA
| | - Michael I. Miller
- Department of Biomedical Engineering, Center for Imaging Science, Johns Hopkins UniversityBaltimore, MD, USA
| | - Daniel Marcus
- Department of Radiology, Washington University School of MedicineSt. Louis, MO, USA
- Department of Psychology, Washington University School of MedicineSt. Louis, MO, USA
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21
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Williams AC, McNeely ME, Greene DJ, Church JA, Warren SL, Hartlein JM, Schlaggar BL, Black KJ, Wang L. A pilot study of basal ganglia and thalamus structure by high dimensional mapping in children with Tourette syndrome. F1000Res 2013; 2:207. [PMID: 24715957 PMCID: PMC3976104 DOI: 10.12688/f1000research.2-207.v1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/07/2013] [Indexed: 01/18/2023] Open
Abstract
Background: Prior brain imaging and autopsy studies have suggested
that structural abnormalities of the basal ganglia (BG) nuclei may be present in Tourette Syndrome (TS). These studies have focused mainly on the volume differences of the BG structures and not their anatomical shapes. Shape differences of various brain structures have been demonstrated in other neuropsychiatric disorders using large-deformation, high dimensional brain mapping (HDBM-LD). A previous study of a small sample of adult TS patients demonstrated the validity of the method, but did not find significant differences compared to controls. Since TS usually begins in childhood and adult studies may show structure differences due to adaptations, we hypothesized that differences in BG and thalamus structure geometry and volume due to etiological changes in TS might be better characterized in children. Objective: Pilot the HDBM-LD method in children and estimate effect sizes. Methods: In this pilot study, T1-weighted MRIs were collected in 13 children with TS and 16 healthy, tic-free, control children. The groups were well matched for age. The primary outcome measures were the first 10 eigenvectors which are derived using HDBM-LD methods and represent the majority of the geometric shape of each structure, and the volumes of each structure adjusted for whole brain volume. We also compared hemispheric right/left asymmetry and estimated effect sizes for both volume and shape differences between groups. Results: We found no statistically significant differences between the TS subjects and controls in volume, shape, or right/left asymmetry. Effect sizes were greater for shape analysis than for volume. Conclusion: This study represents one of the first efforts to study the shape as opposed to the volume of the BG in TS, but power was limited by sample size. Shape analysis by the HDBM-LD method may prove more sensitive to group differences.
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Affiliation(s)
- Alton C Williams
- Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Marie E McNeely
- Division of Biology and Biomedical Sciences, Washington University, St. Louis, MO 63110, USA ; Current affiliation: Centene Corporation, St. Louis, MO 63105, USA
| | - Deanna J Greene
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jessica A Church
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Current affiliation: Department of Psychology in The College of Liberal, University of Texas- Austin, Austin, TX 78712, USA
| | - Stacie L Warren
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA ; Current affiliation: Department of Mental Health, St. Louis VA Medical Center, St. Louis, MO 63110, USA
| | - Johanna M Hartlein
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Bradley L Schlaggar
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Anatomy & Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Kevin J Black
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA ; Department of Anatomy & Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lei Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA ; Current affiliation: Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine Chicago, Chicago, IL 60611, USA ; Current affiliation: Department of Radiology, Northwestern University Feinberg School of Medicine Chicago, Chicago, IL 60611, USA
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22
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Epifanio I, Ventura-Campos N. Hippocampal shape analysis in Alzheimer's disease using functional data analysis. Stat Med 2013; 33:867-80. [PMID: 24105806 DOI: 10.1002/sim.5968] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Accepted: 08/21/2013] [Indexed: 01/18/2023]
Abstract
The hippocampus is one of the first affected regions in Alzheimer's disease. The left hippocampi of control subjects, patients with mild cognitive impairment and patients with Alzheimer's disease are represented by spherical harmonics. Functional data analysis is used in the hippocampal shape analysis. Functional principal component analysis and functional independent component analysis are defined for multivariate functions with two arguments. A functional linear discriminant function is also defined. Comparisons with other approaches are carried out. Our functional approach gives promising results, especially in shape classification.
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Affiliation(s)
- Irene Epifanio
- Dept. Matemàtiques, Universitat Jaume I, Campus del Riu Sec, 12071 Castelló, Spain
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23
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Hoogenboom WS, Perlis RH, Smoller JW, Zeng-Treitler Q, Gainer VS, Murphy SN, Churchill SE, Kohane IS, Shenton ME, Iosifescu DV. Feasibility of studying brain morphology in major depressive disorder with structural magnetic resonance imaging and clinical data from the electronic medical record: a pilot study. Psychiatry Res 2013; 211:202-13. [PMID: 23149041 PMCID: PMC3574623 DOI: 10.1016/j.pscychresns.2012.07.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2011] [Revised: 06/13/2012] [Accepted: 07/11/2012] [Indexed: 01/17/2023]
Abstract
For certain research questions related to long-term outcomes or to rare disorders, designing prospective studies is impractical or prohibitively expensive. Such studies could instead utilize clinical and magnetic resonance imaging data (MRI) collected as part of routine clinical care, stored in the electronic medical record (EMR). Using major depressive disorder (MDD) as a disease model, we examined the feasibility of studying brain morphology and associations with remission using clinical and MRI data exclusively drawn from the EMR. Advanced automated tools were used to select MDD patients and controls from the EMR who had brain MRI data, but no diagnosed brain pathology. MDD patients were further assessed for remission status by review of clinical charts. Twenty MDD patients (eight full-remitters, six partial-remitters, and six non-remitters), and 15 healthy control subjects met all study criteria for advanced morphometric analyses. Compared to controls, MDD patients had significantly smaller right rostral-anterior cingulate volume, and level of non-remission was associated with smaller left hippocampus and left rostral-middle frontal gyrus volume. The use of EMR data for psychiatric research may provide a timely and cost-effective approach with the potential to generate large study samples reflective of the real population with the illness studied.
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Affiliation(s)
- Wouter S. Hoogenboom
- Depression Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, United States,Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, United States,Corresponding author: Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, 1249 Boylston Street, Boston, MA 02215, United States, Tel: +1 617 455 8929, Fax: +1 617 525 6150,
| | - Roy H. Perlis
- Depression Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, United States,Center for Human Genetic Research, Laboratory of Psychiatric Pharmacogenomics, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Jordan W. Smoller
- Psychiatric Genetics Program in Mood and Anxiety Disorders, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Qing Zeng-Treitler
- University of Utah, Department of Biomedical Informatics, Salt Lake City, UT 84112, United States,VA Salt Lake City Health Care System, Salt Lake City, UT, 84148, United States
| | - Vivian S. Gainer
- Information Systems, Partners HealthCare System, Inc., Charlestown, MA 02129, United States
| | - Shawn N. Murphy
- Information Systems, Partners HealthCare System, Inc., Charlestown, MA 02129, United States,Laboratory of Computer Science, Massachusetts General Hospital, Boston, MA 02114, United States
| | - Susanne E. Churchill
- i2b2 National Center for Biomedical Computing, Brigham and Women’s Hospital, Boston, MA 02115, United States
| | - Isaac S. Kohane
- i2b2 National Center for Biomedical Computing, Brigham and Women’s Hospital, Boston, MA 02115, United States
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02215, United States,Clinical Neuroscience Division, Laboratory of Neuroscience, Department of Psychiatry, VA Boston Healthcare System, Brockton Division, Brockton, MA 02301 and Harvard Medical School, Boston, MA 02115, United States
| | - Dan V. Iosifescu
- Depression Clinical and Research Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, United States,Mood and Anxiety Disorders Program, Mount Sinai School of Medicine, New York, NY 10029, United States
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24
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Zierhut KC, Graßmann R, Kaufmann J, Steiner J, Bogerts B, Schiltz K. Hippocampal CA1 deformity is related to symptom severity and antipsychotic dosage in schizophrenia. Brain 2013; 136:804-14. [DOI: 10.1093/brain/aws335] [Citation(s) in RCA: 71] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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25
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Hou G, Yang X, Yuan TF. Hippocampal asymmetry: differences in structures and functions. Neurochem Res 2013; 38:453-60. [PMID: 23283696 DOI: 10.1007/s11064-012-0954-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2012] [Revised: 12/11/2012] [Accepted: 12/19/2012] [Indexed: 12/12/2022]
Abstract
The structural asymmetry of bilateral hippocampus in mammals has been well recognized. Recent findings highlighted the accompanying functional asymmetries, as well as the molecular differences of the hippocampus. The present paper summarized these recent advances in understanding the hippocampal asymmetries at molecular, circuit and functional levels. Additionally, the addition of new neurons to the hippocampal circuit during adulthood is asymmetrical. We conclude that these differences in molecules and structures of bilateral hippocampus determined the variances in functionality between the two sides.
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Affiliation(s)
- Gonglin Hou
- Centre of Cognitive Research, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
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26
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Ertekin T, Acer N, Içer S, Ilıca AT. Comparison of two methods for the estimation of subcortical volume and asymmetry using magnetic resonance imaging: a methodological study. Surg Radiol Anat 2012; 35:301-9. [DOI: 10.1007/s00276-012-1036-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2012] [Accepted: 10/25/2012] [Indexed: 01/18/2023]
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27
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Conrad MS, Dilger RN, Johnson RW. Brain growth of the domestic pig (Sus scrofa) from 2 to 24 weeks of age: a longitudinal MRI study. Dev Neurosci 2012; 34:291-8. [PMID: 22777003 DOI: 10.1159/000339311] [Citation(s) in RCA: 128] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2012] [Accepted: 05/03/2012] [Indexed: 11/19/2022] Open
Abstract
An animal model with brain growth similar to humans, that can be used in MRI studies to investigate brain development, would be valuable. Our laboratory has developed and validated MRI methods for regional brain volume quantification in the neonatal piglet. The aim of this study was to utilize the MRI-based volume quantification technique in a longitudinal study to determine brain growth in domestic pigs from 2 to 24 weeks of age. MRI data were acquired from pigs 2-24 weeks of age using a 3-dimensional magnetization-prepared gradient echo sequence on a Magnetom Trio 3-tesla imager. Manual segmentation was performed for volume estimates of total brain, cortical, diencephalon, brainstem, cerebellar and hippocampal regions. Logistic modeling procedures were used to characterize brain growth. Total brain volume increased 130% (±12%) and 121% (±7%) from 2 to 24 weeks in males and females, respectively. The maximum increase in total brain volume occurred about the age of 4 weeks and 95% of whole brain growth occurred by the age of 21-23 weeks. Logistical modeling suggests there are sexually dimorphic effects on brain growth. For example, in females, the cortex was smaller (p = 0.04). Furthermore, the maximum growth of the hippocampus occurred about 5 weeks earlier in females than males, and the window for hippocampal growth was significantly shorter in females than males (p = 0.02, p = 0.002 respectively). These sexual dimorphisms are similar to what is seen in humans. In addition to providing important data on brain growth for pigs, this study shows pigs can be used to obtain longitudinal MRI data. The large increase in brain volume in the postnatal period is similar to that of human neonates and suggests pigs can be used to investigate brain development.
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Affiliation(s)
- Matthew S Conrad
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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28
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Karnik-Henry MS, Wang L, Barch DM, Harms MP, Campanella C, Csernansky JG. Medial temporal lobe structure and cognition in individuals with schizophrenia and in their non-psychotic siblings. Schizophr Res 2012; 138:128-35. [PMID: 22542243 PMCID: PMC3372633 DOI: 10.1016/j.schres.2012.03.015] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2011] [Revised: 03/05/2012] [Accepted: 03/07/2012] [Indexed: 12/15/2022]
Abstract
Medial temporal lobe (MTL) structures play a central role in episodic memory. Prior studies suggest that individuals with schizophrenia have deficits in episodic memory as well as structural abnormalities of the medial temporal lobe (MTL). While correlations have been reported between MTL volume loss and episodic memory deficits in such individuals, it is not clear whether such correlations reflect the influence of the disease state or of underlying genetic influences that might contribute to risk. We used high resolution magnetic resonance imaging and probabilistic algorithms for image analysis to determine whether MTL structure, episodic memory performance and the relationship between the two differed among groups of 47 healthy control subjects, 50 control siblings, 39 schizophrenia subjects, and 33 siblings of schizophrenia subjects. High-dimensional large deformation brain mapping was used to obtain volume measures of the hippocampus. Cortical distance mapping was used to obtain volume and thickness measures of the parahippocampal gyrus (PHG) and its substructures: the entorhinal cortex (ERC), the perirhinal cortex (PRC), and the parahippocampal cortex (PHC). Neuropsychological data was used to establish an episodic memory domain score for each subject. Both schizophrenia subjects and their siblings displayed abnormalities in episodic memory performance. Siblings of individuals with schizophrenia, and to a lesser extent, individuals with schizophrenia themselves, displayed abnormalities in measures of MTL structure (volume loss or cortical thinning) as compared to control groups. Further, we observed correlations between structural measures and memory performance in both schizophrenia subjects and their siblings, but not in their respective control groups. These findings suggest that disease-specific genetic factors present in both patients and their relatives may be responsible for correlated abnormalities of MTL structure and memory impairment. The observed attenuated effect of such factors on MTL structure in individuals with schizophrenia may be due to non-genetic influences related to the development and progression of the disease on global brain structure and cognitive processing.
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Affiliation(s)
- Meghana S. Karnik-Henry
- Department of Psychology, Green Mountain College,Corresponding Author: Meghana S. Karnik-Henry, 1 Brennan Circle, Poultney, VT 05764,
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL
| | - Deanna M. Barch
- Department of Psychology, Washington University, St. Louis, MO,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Michael P. Harms
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | | | - John G. Csernansky
- Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL
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Woolard AA, Heckers S. Anatomical and functional correlates of human hippocampal volume asymmetry. Psychiatry Res 2012; 201:48-53. [PMID: 22285719 PMCID: PMC3289761 DOI: 10.1016/j.pscychresns.2011.07.016] [Citation(s) in RCA: 84] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2011] [Revised: 07/24/2011] [Accepted: 07/28/2011] [Indexed: 10/14/2022]
Abstract
Hemispheric asymmetry of the human hippocampus is well established, but poorly understood. We studied 110 healthy subjects with 3-Tesla MRI to explore the anatomical and functional correlates of the R>L volume asymmetry. We found that the asymmetry is limited to the anterior hippocampus (hemisphere×region interaction: F(1,109)=42.6, p<.001). Anterior hippocampal volume was correlated strongly with the volumes of all four cortical lobes. In contrast, posterior hippocampal volume was correlated strongly only with occipital lobe volume, moderately with the parietal and temporal lobe volumes and not with the frontal lobe volume. The degree of R>L anterior hippocampal volume asymmetry predicted performance on a measure of basic cognitive abilities. This provides evidence for regional specificity and functional implications of the well-known hemispheric asymmetry of hippocampal volume. We suggest that the developmental profile, genetic mechanisms and functional implications of R>L anterior hippocampal volume asymmetry in the human brain deserve further study.
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Affiliation(s)
- Austin A Woolard
- Vaderbilt University, Department of Osychiatry, Nashville, TN, USA
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30
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Maltbie E, Bhatt K, Paniagua B, Smith RG, Graves MM, Mosconi MW, Peterson S, White S, Blocher J, El-Sayed M, Hazlett HC, Styner MA. Asymmetric bias in user guided segmentations of brain structures. Neuroimage 2012; 59:1315-23. [PMID: 21889995 PMCID: PMC3230681 DOI: 10.1016/j.neuroimage.2011.08.025] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2011] [Revised: 07/27/2011] [Accepted: 08/11/2011] [Indexed: 10/17/2022] Open
Abstract
Brain morphometric studies often incorporate comparative hemispheric asymmetry analyses of segmented brain structures. In this work, we present evidence that common user guided structural segmentation techniques exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. In this study, MRI scans from ten pediatric subjects were employed for studying segmentations of amygdala, globus pallidus, putamen, caudate, and lateral ventricle. Additionally, two pediatric and three adult scans were used for studying hippocampus segmentation. Segmentations of the sub-cortical structures were performed by skilled raters using standard manual and semi-automated methods. The left-right mirrored versions of each image were included in the data and segmented in a random order to assess potential left-right asymmetric bias. Using shape analysis we further assessed whether the asymmetric bias is consistent across subjects and raters with the focus on the hippocampus. The user guided segmentation techniques on the sub-cortical structures exhibited left-right asymmetric volume bias with the hippocampus displaying the most significant asymmetry values (p<<0.01). The hippocampal shape analysis revealed the bias to be strongest on the lateral side of the body and medial side of the head and tail. The origin of this asymmetric bias is considered to be based in laterality of visual perception; therefore segmentations with any degree of user interaction contain an asymmetric bias. The aim of our study is to raise awareness in the neuroimaging community regarding the presence of the asymmetric bias and its influence on any left-right hemispheric analyses. We also recommend reexamining previous research results in the light of this new finding.
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Affiliation(s)
- Eric Maltbie
- Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA.
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31
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Mamah D, Harms MP, Barch D, Styner M, Lieberman JA, Wang L. Hippocampal shape and volume changes with antipsychotics in early stage psychotic illness. Front Psychiatry 2012; 3:96. [PMID: 23162479 PMCID: PMC3495266 DOI: 10.3389/fpsyt.2012.00096] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2012] [Accepted: 10/24/2012] [Indexed: 11/30/2022] Open
Abstract
Progression of hippocampal shape and volume abnormalities has been described in psychotic disorders such as schizophrenia. However it is unclear how specific antipsychotic medications influence the development of hippocampal structure. We conducted a longitudinal, randomized, controlled, multisite, double-blind study involving 14 academic medical centers (United States 11, Canada 1, Netherlands 1, and England 1). One hundred thirty-four first-episode psychosis patients (receiving either haloperidol [HAL] or olanzapine [OLZ]) and 51 healthy controls were followed for up to 104 weeks using magnetic resonance imaging and large-deformation high-dimensional brain mapping of the hippocampus. Changes in hippocampal volume and shape metrics (i.e., percentage of negative surface vertex slopes, and surface deformation) were evaluated. Mixed-models analysis did not show a significant group-by-time interaction for hippocampal volume. However, the cumulative distribution function of hippocampal surface vertex slopes showed a notable left shift with HAL treatment compared to OLZ treatment and to controls. OLZ treatment was associated with a significantly lower percentage of "large magnitude" negative surface vertex slopes compared to HAL treatment (p = 0.004). Surface deformation maps however did not localize any hippocampal regions that differentially contracted over time with OLZ treatment, after FDR correction. These results indicate that surface analysis provides supplementary information to volumetry in detecting differential treatment effects of the hippocampus. Our results suggest that OLZ is associated with less longitudinal hippocampal surface deformation than HAL, however the hippocampal regions affected appear to be variable across patients.
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Affiliation(s)
- Daniel Mamah
- Department of Psychiatry, Washington University St. Louis, MO, USA
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32
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Xie J, Carmichael O. Brain shape regression components. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2012:2680-3. [PMID: 23366477 PMCID: PMC3770859 DOI: 10.1109/embc.2012.6346516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Identifying associations between the shape properties of brain regions, measured from magnetic resonance imaging (MRI), and numerical measures of neurodegenerative disease burden can clarify whether disease processes lead to distinctive spatial patterns of brain atrophy. However, prior methods for identifying such associations between shape and clinical variables either failed to summarize shape patterns into a concise set of summary measurements, or risked failing to discover such associations by extracting summary shape features blinded to the clinical variables. We present a method that overcomes these limitations by directly searching for a small set of linear shape features--shape regression components--that simultaneously account for a large amount of population shape variability and are highly correlated with a numerical clinical variable of interest. When applied to hippocampi of 299 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, the method identified correlations between hippocampal atrophy and markers of AD pathology and cogniton that were stronger than, and covered a more extended spatial region than, those identified by competing approaches.
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Affiliation(s)
- Jing Xie
- Graduate Group in Computer Science, University of California, Davis, Davis, CA, 95616
| | - Owen Carmichael
- Department of Neurology, University of California, Davis, Davis, CA, 95616
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Quantization and analysis of hippocampal morphometric changes due to dementia of Alzheimer type using metric distances based on large deformation diffeomorphic metric mapping. Comput Med Imaging Graph 2011; 35:275-93. [PMID: 21345652 DOI: 10.1016/j.compmedimag.2011.01.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2009] [Revised: 09/02/2010] [Accepted: 01/21/2011] [Indexed: 11/20/2022]
Abstract
The metric distance obtained from the large deformation diffeomorphic metric mapping (LDDMM) algorithm is used to quantize changes in morphometry of brain structures due to neuropsychiatric diseases. For illustrative purposes we consider changes in hippocampal morphometry (shape and size) due to very mild dementia of the Alzheimer type (DAT). LDDMM, which was previously used to calculate dense one-to-one correspondence vector fields between hippocampal shapes, measures the morphometric differences with respect to a template hippocampus by assigning metric distances on the space of anatomical images thereby allowing for direct comparison of morphometric differences. We characterize what information the metric distances provide in terms of size and shape given the hippocampal, brain and intracranial volumes. We demonstrate that metric distance is a measure of morphometry (i.e., shape and size) but mostly a measure of shape, while volume is mostly a measure of size. Moreover, we show how metric distances can be used in cross-sectional, longitudinal analysis, as well as left-right asymmetry comparisons, and provide how the metric distances can serve as a discriminative tool using logistic regression. Thus, we show that metric distances with respect to a template computed via LDDMM can be a powerful tool in detecting differences in shape.
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34
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Samara A, Vougas K, Papadopoulou A, Anastasiadou E, Baloyanni N, Paronis E, Chrousos G, Tsangaris G. Proteomics reveal rat hippocampal lateral asymmetry. Hippocampus 2010; 21:108-19. [DOI: 10.1002/hipo.20727] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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35
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Coleman MJ, Titone D, Krastoshevsky O, Krause V, Huang Z, Mendell NR, Eichenbaum H, Levy DL. Reinforcement ambiguity and novelty do not account for transitive inference deficits in schizophrenia. Schizophr Bull 2010; 36:1187-200. [PMID: 19460878 PMCID: PMC2963057 DOI: 10.1093/schbul/sbp039] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
The capacity for transitive inference (TI), a form of relational memory organization, is impaired in schizophrenia patients. In order to disambiguate deficits in TI from the effects of ambiguous reinforcement history and novelty, 28 schizophrenia and 20 nonpsychiatric control subjects were tested on newly developed TI and non-TI tasks that were matched on these 2 variables. Schizophrenia patients performed significantly worse than controls on the TI task but were able to make equivalently difficult nontransitive judgments as well as controls. Neither novelty nor reinforcement ambiguity accounted for the selective deficit of the patients on the TI task. These findings implicate a disturbance in relational memory organization, likely subserved by hippocampal dysfunction, in the pathophysiology of schizophrenia.
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Affiliation(s)
| | - Debra Titone
- Department of Psychology, McGill University, Montreal, Quebec, Canada
| | | | - Verena Krause
- Psychology Research Laboratory, McLean Hospital, Belmont, MA 02478
| | - Zhuying Huang
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
| | - Nancy R. Mendell
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY
| | | | - Deborah L. Levy
- Psychology Research Laboratory, McLean Hospital, Belmont, MA 02478,To whom correspondence should be addressed; tel: 617-855-2854, fax: 617-855-2778, e-mail:
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36
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Comparison of manual and automated determination of hippocampal volumes in MCI and early AD. Brain Imaging Behav 2010; 4:86-95. [PMID: 20454594 DOI: 10.1007/s11682-010-9088-x] [Citation(s) in RCA: 63] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
MRI-based hippocampal volume analysis has been extensively employed given its potential as a biomarker for brain disorders such as Alzheimer's disease (AD), and accurate and efficient determination of hippocampal volumes from brain images is still a challenging issue. We compared an automated method, FreeSurfer (V4), with a published manual protocol for the determination of hippocampal volumes from T1-weighted MRI scans. Our study included MRI data from 125 older adult subjects: healthy controls with no significant cognitive complaints or deficits (HC, n=38), euthymic individuals with cognitive complaints (CC, n=39) but intact neuropsychological performance, and patients with amnestic mild cognitive impairment (MCI, n=37) or a clinical diagnosis of probable AD (AD, n=11). Pearson correlations and intraclass correlation coefficients (ICCs) were calculated to evaluate the relationship between results of the manual tracing and FreeSurfer methods and to estimate their agreement. Results indicated that these two methods derived highly correlated results with strong agreement. After controlling for the age, sex and intracranial volume in statistical group analysis, both the manual tracing and FreeSurfer methods yield similar patterns: both the MCI group and the AD group showed hippocampal volume reduction compared to both the HC group and the CC group, and the HC and CC groups did not differ. These comparisons suggest that FreeSurfer has the potential to be used in automated determination of hippocampal volumes for large-scale MCI/AD-related MRI studies, where manual methods are inefficient or not feasible.
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37
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Coplan JD, Mathew SJ, Abdallah CG, Mao X, Kral JG, Smith ELP, Rosenblum LA, Perera TD, Dwork AJ, Hof PR, Gorman JM, Shungu DC. Early-life stress and neurometabolites of the hippocampus. Brain Res 2010; 1358:191-9. [PMID: 20713023 DOI: 10.1016/j.brainres.2010.08.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2010] [Revised: 08/04/2010] [Accepted: 08/08/2010] [Indexed: 12/29/2022]
Abstract
We tested the hypothesis that early life stress would persistently compromise neuronal viability of the hippocampus of the grown nonhuman primate. Neuronal viability was assessed through ascertainment of N-acetyl aspartate (NAA)-an amino acid considered reflective of neuronal density/functional integrity-using in vivo proton magnetic resonance spectroscopic imaging (MRSI). The subjects reported herein represent a re-analysis of a sample of nineteen adult male bonnet macaques that had been reared in infancy under induced stress by maternal variable foraging demand (VFD) (N=10) or control rearing conditions (N=9). The MRSI spectral readings were recorded using a GE 1.5 Tesla machine under anesthesia. Relative NAA values were derived using NAA as numerator and both choline (Cho) or creatine (Cr) as denominators. Left medial temporal lobe (MTL) NAA/Cho but not NAA/Cr was decreased in VFD subjects versus controls. An MTL NAA/Cho ratio deficit remained significant when controlling for multiple confounding variables. Regression analyses suggested that the NAA/Choline finding was due to independently low left NAA and high left choline. Right MTL showed no rearing effects for NAA, but right NAA was positively related to body mass, irrespective of denominator. The current data indicate that decreased left MTL NAA/Cho may reflect low neuronal viability of the hippocampus following early life stress in VFD-reared versus normally-reared subjects. Given the importance of the hippocampus in stress-mediated toxicity, validation of these data using absolute quantification is suggested and correlative neurohistological studies of hippocampus are warranted.
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Affiliation(s)
- Jeremy D Coplan
- SUNY Downstate Medical Center, Nonhuman Primate Facility, Department of Psychiatry, Brooklyn, NY 11203, USA.
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Abstract
The hippocampus is abnormal in schizophrenia. Smaller hippocampal volume is the most consistent finding and is present already in the early stages of the illness. The underlying cellular substrate is a subtle, yet functionally significant reduction of hippocampal interneurons. Neuroimaging studies have revealed a pattern of increased hippocampal activity at baseline and decreased recruitment during the performance of memory tasks. Hippocampal lesion models in rodents have replicated some of the pharmacological, anatomical and behavioral phenotype of schizophrenia. Taken together, this pattern of findings points to a disinhibition of hippocampal pyramidal cells and abnormal cortico-hippocampal interactions in schizophrenia.
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Affiliation(s)
- Stephan Heckers
- Department of Psychiatry, Vanderbilt University, 1601 23rd Avenue South, Room 3060, Nashville, TN 37212, USA.
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Xie J, Alcantara D, Amenta N, Fletcher E, Martinez O, Persianinova M, DeCarli C, Carmichael O. Spatially localized hippocampal shape analysis in late-life cognitive decline. Hippocampus 2009; 19:526-32. [PMID: 19437501 DOI: 10.1002/hipo.20618] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
We present a method for generating data-driven, concise, and spatially localized parameterizations of hippocampal (HP) shape, and use the method to analyze HP atrophy in late-life cognitive decline. The method optimizes a set of shape basis vectors (shape components) that strike a balance between spatial locality and compact representation of population shape characteristics. The method can be used for exploratory analysis of localized shape deformations in any population of HP on which point-to-point correspondence mappings have been established via anatomical landmarking or high-dimensional warping. Experiments combine the method with an automated HP to HP mapping method to analyze tracings of 101 elderly subjects with normal cognition, mild cognitive impairment, and Alzheimer's Disease (AD) from an AD Center population. Results suggest that shape components corresponding to atrophy to the CA1 and subiculum HP fields--where early AD pathology is located--correlate strongly with robust measures of the cognitive dysfunction that is typical of early AD. Furthermore, the energy function minimized by the shape component optimization technique is shown to be smooth with few local minima, suggesting that the method may be relatively easy to apply in practice.
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Affiliation(s)
- Jing Xie
- Department of Computer Science, University of California, Davis, California 95618, USA.
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40
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Qiu A, Wang L, Younes L, Harms MP, Ratnanather JT, Miller MI, Csernansky JG. Neuroanatomical asymmetry patterns in individuals with schizophrenia and their non-psychotic siblings. Neuroimage 2009; 47:1221-9. [PMID: 19481156 DOI: 10.1016/j.neuroimage.2009.05.054] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2009] [Revised: 05/12/2009] [Accepted: 05/20/2009] [Indexed: 01/03/2023] Open
Abstract
Neuroanatomical endophenotypes may reveal insights into the processes by which genetic factors increase the risk of developing schizophrenia. To determine whether patterns of neuroanatomical asymmetries may be useful as schizophrenia-related endophenotypes, we compared patterns of structural asymmetries in patients with schizophrenia, healthy controls, and their respective siblings. The surfaces of the left and right amygdala, hippocampus, thalamus, caudate nucleus, putamen, globus pallidus, and nucleus accumbens were assessed in 40 pairs of healthy comparison controls (CON) and their siblings (CON-SIB) and 25 pairs of patients with schizophrenia (SCZ) and their siblings (SCZ-SIB) in magnetic resonance (MR) images using large deformation diffeomorphic metric mapping (LDDMM) and parallel transport techniques. The within-subject asymmetry deformation of each structure was first measured via LDDMM, and then translated to a global template via parallel transport for evaluation of the patterns of asymmetry both within and across siblings. Our results revealed that asymmetries observed in CON subjects occurred in the amygdala and the anterior segment of the hippocampus with more pronounced expansion deformation in the right-sided structures (R>L asymmetry) but not in the basal ganglia and thalamus. Disturbance in this pattern of asymmetries was observed in both SCZ and SCZ-SIB subjects. More specifically, exaggerations and reductions in the normative pattern of asymmetries were observed in the amygdala-hippocampus formation, basal ganglia, and thalamus. These altered patterns of asymmetries are present in subjects with schizophrenia and their siblings, and therefore may represent a schizophrenia-related endophenotype.
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Affiliation(s)
- Anqi Qiu
- Division of Bioengineering, National University of Singapore, Singapore.
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41
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Hogan RE, Bouilleret V, Liu YR, Wang L, Williams JP, Jupp B, Myers D, O'Brien TJ. MRI-based large deformation high dimensional mapping of the hippocampus in rats: Development and validation of the technique. J Magn Reson Imaging 2009; 29:1027-34. [DOI: 10.1002/jmri.21766] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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42
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Sonat F(A, Ercan I, Ozdemir ST, Ozkaya G, Noyan B. Statistical shape analysis of the rat hippocampus in epilepsy. Anat Sci Int 2009; 84:298-304. [DOI: 10.1007/s12565-009-0038-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2008] [Accepted: 02/26/2009] [Indexed: 01/01/2023]
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Ardekani S, Weiss RG, Lardo AC, George RT, Lima JAC, Wu KC, Miller MI, Winslow RL, Younes L. Computational method for identifying and quantifying shape features of human left ventricular remodeling. Ann Biomed Eng 2009; 37:1043-54. [PMID: 19322659 DOI: 10.1007/s10439-009-9677-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2008] [Accepted: 03/13/2009] [Indexed: 10/21/2022]
Abstract
Left ventricular remodeling during the development of heart failure is a strong predictor of cardiovascular mortality. However, methods to objectively quantify remodeling-associated shape changes are not routinely available but may be possible with new computational anatomy tools. In this study, we analyzed and compared multi-detector computed tomographic (MDCT) images of ventricular shape at end-systole (ES) and end-diastole (ED) to determine whether regional structural characteristics could be identified and, as a proof of principle, whether differences in hearts of patients with anterior myocardial infarction (MI) and ischemic cardiomyopathy (ICM) could be distinguished from those with global nonischemic cardiomyopathy (NICM). MDCT images of hearts from 11 patients (5 with ICM) with ejection fractions (EF) < 35% were analyzed. An average ventricular shape model (template) was constructed for each cardiac phase by bringing heart shapes into correspondence using linear and nonlinear image matching algorithms. Next, transformation fields were computed between the template image and individual heart images in the population. Principal component analysis (PCA) method was used to quantify ventricular shape differences described by the transformation vector fields. Statistical analysis of PCA coefficients revealed significant ventricular shape differences at ED (p = 0.03) and ES (p = 0.03). For validation, a second set of 14 EF-matched patients (8 with ICM) were evaluated. The discrimination rule learned from the training data set was able to differentiate ICM from NICM patients (p = 0.008). Application of a novel shape analysis method to in vivo human cardiac images acquired on a clinical scanner is feasible and can quantify regional shape differences at end-systole in remodeled myopathic human myocardium. This approach may be useful in identifying differences in the remodeling process between ICM and NICM populations and possibly in differentiating the populations.
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Affiliation(s)
- Siamak Ardekani
- Institute for Computational Medicine, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA.
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44
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Basal ganglia shape abnormalities in the unaffected siblings of schizophrenia patients. Biol Psychiatry 2008; 64:111-20. [PMID: 18295189 PMCID: PMC2486271 DOI: 10.1016/j.biopsych.2008.01.004] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2007] [Revised: 12/10/2007] [Accepted: 01/04/2008] [Indexed: 11/21/2022]
Abstract
BACKGROUND Abnormalities of basal ganglia structure in schizophrenia have been attributed to the effects of antipsychotic drugs. Our aim was to test the hypothesis that abnormalities of basal ganglia structure are intrinsic features of schizophrenia by assessing basal ganglia volume and shape in the unaffected siblings of schizophrenia subjects. METHOD The study involved 25 pairs of schizophrenia subjects and their unaffected siblings and 40 pairs of healthy control subjects and their siblings. Large-deformation, high-dimensional brain mapping was used to obtain surface representations of the caudate, putamen, and globus pallidus. Surfaces were derived from transformations of anatomic templates, and shapes were analyzed using reduced-dimensional measures of surface variability (i.e., principal components and canonical analysis). Canonical functions were derived using schizophrenia and control groups and were then used to compare shapes in the sibling groups. To visualize shape differences, maps of the estimated surface displacement between groups were created. RESULTS In the caudate, putamen, and globus pallidus, the degree of shape abnormality observed in the siblings of the schizophrenia subjects was intermediate between the schizophrenia and control subjects. In the schizophrenia subjects, significant correlations were observed between measures of caudate, putamen, and globus pallidus structure and the selected measures of lifetime psychopathology. CONCLUSIONS Attenuated abnormalities of basal ganglia structure are present in the unaffected siblings of schizophrenia subjects. This finding implies that basal ganglia structural abnormalities observed in subjects with schizophrenia are at least in part an intrinsic feature of the illness.
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45
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Thompson PM, Apostolova LG. Computational anatomical methods as applied to ageing and dementia. Br J Radiol 2008; 80 Spec No 2:S78-91. [PMID: 18445748 DOI: 10.1259/bjr/20005470] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
The cellular hallmarks of Alzheimer's disease (AD) accumulate in the living brain up to 30 years before the characteristic symptoms of dementia can be identified. Brain changes in AD are difficult to distinguish from those in normal ageing, and this has led to the development of powerful computational methods to extract statistical information on the brain changes that are characteristic of AD, mild cognitive impairment (MCI) and different dementia subtypes. Time-lapse maps can be built to show how the disease spreads in the brain, and where treatment affects the disease trajectory. Here, we review three computational approaches to map brain deficits in AD: cortical thickness maps, tensor-based morphometry and hippocampal/ventricular surface modelling. Anatomical structures, modelled as three-dimensional geometrical surfaces, are mathematically combined across subjects for group or interval comparisons. Mathematical concepts from computational surface modelling, fluid mechanics and multivariate statistics are exploited to distinguish disease from normal variations in brain structure. These methods yield insight into the dynamics of AD and MCI, showing where brain changes correlate with cognitive or behavioural changes such as language dysfunction or apathy. We describe cortical and hippocampal changes that distinguish dementia subtypes (such as Lewy-body dementia, HIV-associated dementia and AD), and we describe brain changes that predict recovery or decline in those at risk. Finally, we indicate which computational methods are powerful enough to track dementia in clinical trials, on the basis of their efficiency and sensitivity to early change, and the detail in the measures they provide.
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Affiliation(s)
- P M Thompson
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive, Los Angeles, CA 90095-1769, USA.
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Zhao Z, Taylor WD, Styner M, Steffens DC, Krishnan KRR, MacFall JR. Hippocampus shape analysis and late-life depression. PLoS One 2008; 3:e1837. [PMID: 18350172 PMCID: PMC2265542 DOI: 10.1371/journal.pone.0001837] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2007] [Accepted: 02/06/2008] [Indexed: 11/19/2022] Open
Abstract
Major depression in the elderly is associated with brain structural changes and vascular lesions. Changes in the subcortical regions of the limbic system have also been noted. Studies examining hippocampus volumetric differences in depression have shown variable results, possibly due to any volume differences being secondary to local shape changes rather than differences in the overall volume. Shape analysis offers the potential to detect such changes. The present study applied spherical harmonic (SPHARM) shape analysis to the left and right hippocampi of 61 elderly subjects with major depression and 43 non-depressed elderly subjects. Statistical models controlling for age, sex, and total cerebral volume showed a significant reduction in depressed compared with control subjects in the left hippocampus (F1,103 = 5.26; p = 0.0240) but not right hippocampus volume (F1,103 = 0.41; p = 0.5213). Shape analysis showed significant differences in the mid-body of the left (but not the right) hippocampus between depressed and controls. When the depressed group was dichotomized into those whose depression was remitted at time of imaging and those who were unremitted, the shape comparison showed remitted subjects to be indistinguishable from controls (both sides) while the unremitted subjects differed in the midbody and the lateral side near the head. Hippocampal volume showed no difference between controls and remitted subjects but nonremitted subjects had significantly smaller left hippocampal volumes with no significant group differences in the right hippocampus. These findings may provide support to other reports of neurogenic effects of antidepressants and their relation to successful treatment for depressive symptoms.
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Affiliation(s)
- Zheen Zhao
- Neuropsychiatric Imaging Research Laboratory, Duke University Medical Center, Durham, North Carolina, United States of America.
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Qiu A, Younes L, Miller MI, Csernansky JG. Parallel transport in diffeomorphisms distinguishes the time-dependent pattern of hippocampal surface deformation due to healthy aging and the dementia of the Alzheimer's type. Neuroimage 2007; 40:68-76. [PMID: 18249009 DOI: 10.1016/j.neuroimage.2007.11.041] [Citation(s) in RCA: 50] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2007] [Revised: 11/01/2007] [Accepted: 11/29/2007] [Indexed: 10/22/2022] Open
Abstract
Hippocampal surface structure was assessed at twice 2 years apart in 26 nondemented subjects (CDR 0), in 18 subjects with early dementia of Alzheimer type (DAT, CDR 0.5), and in 9 subjects who converted from the nondemented (CDR 0) to the demented (CDR 0.5) state using magnetic resonance (MR) imaging. We used parallel transport in diffeomorphisms under the large deformation diffeomorphic metric mapping framework to translate within-subject deformation of the hippocampal surface as represented in the MR images between the two time points in a global template coordinate system. We then performed hypothesis testing on the longitudinal variation of hippocampal shape in the global template. Both subjects with early DAT and converters showed greater rates of hippocampal deformation across time than nondemented controls within every subfield of the hippocampus. In a random field analysis, inward surface deformation across time occurred in a non-uniform manner across the hippocampal surface in subjects with early DAT relative to the nondemented controls. Also, compared to the controls, the lateral aspect of the left hippocampal tail showed inward surface deformation in the converters. Using surface deformation patterns as features in a linear discriminant analysis, we were able to respectively distinguish converters and patients with early DAT from healthy nondemented controls at classification rates of 0.77 and 0.87, which were obtained in the same training set using the leave-one-out cross validation approach.
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Affiliation(s)
- Anqi Qiu
- Division of Bioengineering, National University of Singapore, 7 Engineering Drive 1, Singapore, Singapore.
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Rametti G, Segarra N, Junqué C, Bargalló N, Caldú X, Ibarretxe N, Bernardo M. Left posterior hippocampal density reduction using VBM and stereological MRI procedures in schizophrenia. Schizophr Res 2007; 96:62-71. [PMID: 17604968 DOI: 10.1016/j.schres.2007.04.034] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2007] [Revised: 04/27/2007] [Accepted: 04/29/2007] [Indexed: 11/15/2022]
Abstract
Structural deficits in the hippocampus have been implicated in the pathophysiology of schizophrenia. However the role played by structural impairments in the hippocampus in the memory deficits of schizophrenic patients remains unclear. Magnetic resonance imaging was used in this study to investigate left, right, anterior and posterior hippocampal volume and density in 28 schizophrenic patients and 33 normal controls. Voxel-based morphometry analysis showed that schizophrenics had significantly lower density in the right and posterior hippocampus than controls. MRI stereological analysis revealed significant differences in left posterior hippocampus than controls. MRI stereological analysis revealed significant differences in anterior and posterior on both sides, with the left posterior region predominating. Schizophrenics showed significant impairments in verbal learning and long term retention (P<0.001). The correlation analyses between hippocampal density and memory variables yielded a significant correlation between forgetting and density of the anterior hippocampus. These findings support the hypothesis of a regional atrophy within the hippocampus in schizophrenic patients.
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Affiliation(s)
- Giuseppina Rametti
- Department of Psychiatry and Clinical Psychobiology, University of Barcelona, Barcelona, Spain
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Qiu A, Younes L, Wang L, Ratnanather JT, Gillepsie SK, Kaplan G, Csernansky J, Miller MI. Combining anatomical manifold information via diffeomorphic metric mappings for studying cortical thinning of the cingulate gyrus in schizophrenia. Neuroimage 2007; 37:821-33. [PMID: 17613251 PMCID: PMC4465219 DOI: 10.1016/j.neuroimage.2007.05.007] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2007] [Revised: 04/27/2007] [Accepted: 05/04/2007] [Indexed: 11/18/2022] Open
Abstract
Spatial normalization is a crucial step in assessing patterns of neuroanatomical structure and function associated with health and disease. Errors that occur during spatial normalization can influence hypothesis testing due to the dimensionalities of mapping algorithms and anatomical manifolds (landmarks, curves, surfaces, volumes) used to drive the mapping algorithms. The primary aim of this paper is to improve statistical inference using multiple anatomical manifolds and large deformation diffeomorphic metric mapping (LDDMM) algorithms. We propose that combining information generated by the various manifolds and algorithms improves the reliability of hypothesis testing. We used this unified approach to assess variation in the thickness of the cingulate gyrus in subjects with schizophrenia and healthy comparison subjects. Three different LDDMM algorithms for mapping landmarks, curves and triangulated meshes were used to transform thickness maps of the cingulate surfaces into an atlas coordinate system. We then tested for group differences by combining the information from the three types of anatomical manifolds and LDDMM mapping algorithms. The unified approach provided reliable statistical results and eliminated ambiguous results due to surface mismatches. Subjects with schizophrenia had non-uniform cortical thinning over the left and right cingulate gyri, especially in the anterior portion, as compared to healthy comparison subjects.
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Affiliation(s)
- Anqi Qiu
- Division of Bioengineering, National University of Singapore, Singapore 117576.
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50
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Shi Y, Thompson PM, de Zubicaray GI, Rose SE, Tu Z, Dinov I, Toga AW. Direct mapping of hippocampal surfaces with intrinsic shape context. Neuroimage 2007; 37:792-807. [PMID: 17625918 PMCID: PMC2227952 DOI: 10.1016/j.neuroimage.2007.05.016] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2006] [Revised: 05/05/2007] [Accepted: 05/10/2007] [Indexed: 10/23/2022] Open
Abstract
We propose in this paper a new method for the mapping of hippocampal (HC) surfaces to establish correspondences between points on HC surfaces and enable localized HC shape analysis. A novel geometric feature, the intrinsic shape context, is defined to capture the global characteristics of the HC shapes. Based on this intrinsic feature, an automatic algorithm is developed to detect a set of landmark curves that are stable across population. The direct map between a source and target HC surface is then solved as the minimizer of a harmonic energy function defined on the source surface with landmark constraints. For numerical solutions, we compute the map with the approach of solving partial differential equations on implicit surfaces. The direct mapping method has the following properties: (1) it has the advantage of being automatic; (2) it is invariant to the pose of HC shapes. In our experiments, we apply the direct mapping method to study temporal changes of HC asymmetry in Alzheimer's disease (AD) using HC surfaces from 12 AD patients and 14 normal controls. Our results show that the AD group has a different trend in temporal changes of HC asymmetry than the group of normal controls. We also demonstrate the flexibility of the direct mapping method by applying it to construct spherical maps of HC surfaces. Spherical harmonics (SPHARM) analysis is then applied and it confirms our results on temporal changes of HC asymmetry in AD.
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Affiliation(s)
- Yonggang Shi
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA 1
| | - Paul M. Thompson
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA 1
| | - Greig I. de Zubicaray
- Centre for Magnetic Resonance, University of Queensland, Brisbane, QLD 4072, Australia
| | - Stephen E. Rose
- Centre for Magnetic Resonance, University of Queensland, Brisbane, QLD 4072, Australia
| | - Zhuowen Tu
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA 1
| | - Ivo Dinov
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA 1
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA 1
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA, Email address: (Arthur W. Toga)
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