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Dong J, Zhu XN, Zeng PM, Cao DD, Yang Y, Hu J, Luo ZG. A hominoid-specific signaling axis regulating the tempo of synaptic maturation. Cell Rep 2024; 43:114548. [PMID: 39052482 DOI: 10.1016/j.celrep.2024.114548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 04/15/2024] [Accepted: 07/12/2024] [Indexed: 07/27/2024] Open
Abstract
Human cortical neurons (hCNs) exhibit high dendritic complexity and synaptic density, and the maturation process is greatly protracted. However, the molecular mechanism governing these specific features remains unclear. Here, we report that the hominoid-specific gene TBC1D3 promotes dendritic arborization and protracts the pace of synaptogenesis. Ablation of TBC1D3 in induced hCNs causes reduction of dendritic growth and precocious synaptic maturation. Forced expression of TBC1D3 in the mouse cortex protracts synaptic maturation while increasing dendritic growth. Mechanistically, TBC1D3 functions via interaction with MICAL1, a monooxygenase that mediates oxidation of actin filament. At the early stage of differentiation, the TBC1D3/MICAL1 interaction in the cytosol promotes dendritic growth via F-actin oxidation and enhanced actin dynamics. At late stages, TBC1D3 escorts MICAL1 into the nucleus and downregulates the expression of genes related with synaptic maturation through interaction with the chromatin remodeling factor ATRX. Thus, this study delineates the molecular mechanisms underlying human neuron development.
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Affiliation(s)
- Jian Dong
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Xiao-Na Zhu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Peng-Ming Zeng
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Dong-Dong Cao
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yang Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Ji Hu
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Zhen-Ge Luo
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China.
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2
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Park S, Haak KV, Oldham S, Cho H, Byeon K, Park BY, Thomson P, Chen H, Gao W, Xu T, Valk S, Milham MP, Bernhardt B, Di Martino A, Hong SJ. A shifting role of thalamocortical connectivity in the emergence of cortical functional organization. Nat Neurosci 2024; 27:1609-1619. [PMID: 38858608 DOI: 10.1038/s41593-024-01679-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 05/13/2024] [Indexed: 06/12/2024]
Abstract
The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.
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Affiliation(s)
- Shinwon Park
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
- Autism Center, Child Mind Institute, New York, NY, USA
| | - Koen V Haak
- Department of Cognitive Science and Artificial Intelligence, Tilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, The Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute, Radboud University, Radboud, The Netherlands
| | - Stuart Oldham
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Hanbyul Cho
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
| | - Kyoungseob Byeon
- Center for Integrative Developing Brain, Child Mind Institute, New York, NY, USA
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea
- Department of Data Science, Inha University, Incheon, South Korea
| | | | - Haitao Chen
- Department of Biomedical Sciences and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Bioengineering, University of California at Los Angeles, Los Angeles, CA, USA
| | - Wei Gao
- Department of Biomedical Sciences and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Medicine, University of California at Los Angeles, Los Angeles, CA, USA
| | - Ting Xu
- Center for Integrative Developing Brain, Child Mind Institute, New York, NY, USA
| | - Sofie Valk
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7), Brain and Behavior, Forschungszentrum, Juelich, Germany
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | | | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea.
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea.
- Department of MetaBioHealth, Sungkyunkwan University, Suwon, South Korea.
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Barzó P, Szöts I, Tóth M, Csajbók ÉA, Molnár G, Tamás G. Electrophysiology and Morphology of Human Cortical Supragranular Pyramidal Cells in a Wide Age Range. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598792. [PMID: 38915496 PMCID: PMC11195274 DOI: 10.1101/2024.06.13.598792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The basic excitatory neurons of the cerebral cortex, the pyramidal cells, are the most important signal integrators for the local circuit. They have quite characteristic morphological and electrophysiological properties that are known to be largely constant with age in the young and adult cortex. However, the brain undergoes several dynamic changes throughout life, such as in the phases of early development and cognitive decline in the aging brain. We set out to search for intrinsic cellular changes in supragranular pyramidal cells across a broad age range: from birth to 85 years of age and we found differences in several biophysical properties between defined age groups. During the first year of life, subthreshold and suprathreshold electrophysiological properties changed in a way that shows that pyramidal cells become less excitable with maturation, but also become temporarily more precise. According to our findings, the morphological features of the three-dimensional reconstructions from different life stages showed consistent morphological properties and systematic dendritic spine analysis of an infantile and an old pyramidal cell showed clear significant differences in the distribution of spine shapes. Overall, the changes that occur during development and aging may have lasting effects on the properties of pyramidal cells in the cerebral cortex. Understanding these changes is important to unravel the complex mechanisms underlying brain development, cognition and age-related neurodegenerative diseases.
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Affiliation(s)
- Pál Barzó
- Department of Neurosurgery, University of Szeged, Szeged, Hungary
| | - Ildikó Szöts
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Martin Tóth
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Éva Adrienn Csajbók
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Gábor Molnár
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
| | - Gábor Tamás
- ELKH-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy and Neuroscience, University of Szeged, Szeged, Hungary
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Lotter LD, Saberi A, Hansen JY, Misic B, Paquola C, Barker GJ, Bokde ALW, Desrivieres S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Bruehl R, Martinot JL, Paillere ML, Artiges E, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Froehner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Nees F, Banaschewski T, Eickhoff SB, Dukart J. Regional patterns of human cortex development colocalize with underlying neurobiology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.05.539537. [PMID: 37205539 PMCID: PMC10187287 DOI: 10.1101/2023.05.05.539537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cerebral cortex development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.
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Krethlow G, Fargier R, Atanasova T, Ménétré E, Laganaro M. Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan. Cereb Cortex 2024; 34:bhae187. [PMID: 38715409 PMCID: PMC11077060 DOI: 10.1093/cercor/bhae187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 04/05/2024] [Accepted: 04/18/2024] [Indexed: 05/12/2024] Open
Abstract
Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.
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Affiliation(s)
- Giulia Krethlow
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | | | - Tanja Atanasova
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | - Eric Ménétré
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
| | - Marina Laganaro
- Faculty of Psychology and Educational Sciences, University of Geneva, Bd du Pont d’Arve 40, 1205, Geneva, Switzerland
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Gonçalves PD, Martins SS, Gebru NM, Ryan-Pettes SR, Allgaier N, Potter A, Thompson WK, Johnson ME, Garavan H, Talati A, Albaugh MD. Associations Between Family History of Alcohol and/or Substance Use Problems and Frontal Cortical Development From 9 to 13 Years of Age: A Longitudinal Analysis of the ABCD Study. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100284. [PMID: 38312852 PMCID: PMC10837483 DOI: 10.1016/j.bpsgos.2023.100284] [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: 07/13/2023] [Revised: 11/24/2023] [Accepted: 12/02/2023] [Indexed: 02/06/2024] Open
Abstract
Background Previous investigations that have examined associations between family history (FH) of alcohol/substance use and adolescent brain development have been primarily cross-sectional. Here, leveraging a large population-based sample of youths, we characterized frontal cortical trajectories among 9- to 13-year-olds with (FH+) versus without (FH-) an FH and examined sex as a potential moderator. Methods We used data from 9710 participants in the Adolescent Brain Cognitive Development (ABCD) Study (release 4.0). FH+ was defined as having ≥1 biological parents and/or ≥2 biological grandparents with a history of alcohol/substance use problems (n = 2433). Our primary outcome was frontal cortical structural measures obtained at baseline (ages 9-11) and year 2 follow-up (ages 11-13). We used linear mixed-effects models to examine the extent to which FH status qualified frontal cortical development over the age span studied. Finally, we ran additional interactions with sex to test whether observed associations between FH and cortical development differed significantly between sexes. Results For FH+ (vs. FH-) youths, we observed increased cortical thinning from 9 to 13 years across the frontal cortex as a whole. When we probed for sex differences, we observed significant declines in frontal cortical thickness among boys but not girls from ages 9 to 13 years. No associations were observed between FH and frontal cortical surface area or volume. Conclusions Having a FH+ is associated with more rapid thinning of the frontal cortex across ages 9 to 13, with this effect driven primarily by male participants. Future studies will need to test whether the observed pattern of accelerated thinning predicts future substance use outcomes.
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Affiliation(s)
- Priscila Dib Gonçalves
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
- New York State Psychiatric Institute and Department of Psychiatry, Columbia University, New York, New York
| | - Silvia S. Martins
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Nioud Mulugeta Gebru
- Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, Rhode Island
| | | | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Wesley K. Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, Oklahoma
| | - Micah E. Johnson
- Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa, Florida
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Ardesheer Talati
- New York State Psychiatric Institute and Department of Psychiatry, Columbia University, New York, New York
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Norbom LB, Rokicki J, Eilertsen EM, Wiker T, Hanson J, Dahl A, Alnæs D, Fernández‐Cabello S, Beck D, Agartz I, Andreassen OA, Westlye LT, Tamnes CK. Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years. JCPP ADVANCES 2024; 4:e12220. [PMID: 38486948 PMCID: PMC10933599 DOI: 10.1002/jcv2.12220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 12/21/2023] [Indexed: 03/17/2024] Open
Abstract
Background A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth. Methods To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Results Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. Conclusion Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.
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Affiliation(s)
- Linn B. Norbom
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
| | - Jaroslav Rokicki
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Centre of Research and Education in Forensic PsychiatryOslo University HospitalOsloNorway
| | - Espen M. Eilertsen
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
| | - Thea Wiker
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Jamie Hanson
- Learning Research and Development Center University of PittsburghPennsylvaniaPittsburghUSA
- Department of PsychologyUniversity of PittsburghPennsylvaniaPittsburghUSA
| | - Andreas Dahl
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Dag Alnæs
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of PsychologyPedagogy and LawKristiania University CollegeOsloNorway
| | | | - Dani Beck
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
| | - Ingrid Agartz
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet & Stockholm Health Care ServicesStockholmSweden
| | - Ole A. Andreassen
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Lars T. Westlye
- Department of PsychologyUniversity of OsloOsloNorway
- K.G Jebsen Center for Neurodevelopmental DisordersUniversity of OsloOsloNorway
- NORMENTDivision of Mental Health and AddictionOslo University Hospital & Institute of Clinical MedicineUniversity of OsloOsloNorway
| | - Christian K. Tamnes
- PROMENTA Research CenterDepartment of PsychologyUniversity of OsloOsloNorway
- NORMENTInstitute of Clinical MedicineUniversity of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
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Gan Y, Chen Y, Zhong H, Liu Z, Geng J, Wang H, Wang W. Gut microbes in central nervous system development and related disorders. Front Immunol 2024; 14:1288256. [PMID: 38343438 PMCID: PMC10854220 DOI: 10.3389/fimmu.2023.1288256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/22/2023] [Indexed: 02/15/2024] Open
Abstract
The association between gut microbiota and central nervous system (CNS) development has garnered significant research attention in recent years. Evidence suggests bidirectional communication between the CNS and gut microbiota through the brain-gut axis. As a long and complex process, CNS development is highly susceptible to both endogenous and exogenous factors. The gut microbiota impacts the CNS by regulating neurogenesis, myelination, glial cell function, synaptic pruning, and blood-brain barrier permeability, with implication in various CNS disorders. This review outlines the relationship between gut microbiota and stages of CNS development (prenatal and postnatal), emphasizing the integral role of gut microbes. Furthermore, the review explores the implications of gut microbiota in neurodevelopmental disorders, such as autism spectrum disorder, Rett syndrome, and Angelman syndrome, offering insights into early detection, prompt intervention, and innovative treatments.
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Affiliation(s)
- Yumeng Gan
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Yao Chen
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Huijie Zhong
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zhuo Liu
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Jiawei Geng
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Huishan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Wenxue Wang
- Department of Infectious Disease and Hepatic Disease, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, China
- School of Basic Medicine, Yunnan University of Chinese Medicine, Kunming, Yunnan, China
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Kang J, Mao W, Wu J, Huang X, Casanova MF, Sokhadze EM, Li X, Geng X. Development of EEG connectivity from preschool to school-age children. Front Neurosci 2024; 17:1277786. [PMID: 38274502 PMCID: PMC10808652 DOI: 10.3389/fnins.2023.1277786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 12/28/2023] [Indexed: 01/27/2024] Open
Abstract
Introduction Many studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, rather, on the interaction between different brain regions. In this regard studying the connectivity between brain regions is of great importance towards understanding higher cognitive functions and its underlying mechanisms. Methods In this study, EEG data of children (N = 253; 3-10 years old; 113 females, 140 males) from pre-school to schoolage was collected, and the weighted phase delay index and directed transfer function method was used to find the electrophysiological indicators of both functional connectivity and effective connectivity. A general linear model was built between the indicators and age, and the change trend of electrophysiological indicators analyzed for age. Results The results showed an age trend for the functional and effective connectivity of the brain of children. Discussion The results are of importance in understanding normative brain development and in defining those conditions that deviate from typical growth trajectories.
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Affiliation(s)
- Jiannan Kang
- Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, China
| | - Wenqin Mao
- Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, China
| | - Juanmei Wu
- Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, China
| | - Xinping Huang
- Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, China
| | - Manuel F. Casanova
- Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Prisma Health System, Greenville, SC, United States
| | - Estate M. Sokhadze
- Department of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Prisma Health System, Greenville, SC, United States
- Duke University, Durham, NC, United States
| | - Xiaoli Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xinling Geng
- School of Biomedical Engineering, Capital Medical University, Beijing, China
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10
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Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. Hum Brain Mapp 2024; 45:e26528. [PMID: 37994234 PMCID: PMC10789199 DOI: 10.1002/hbm.26528] [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: 07/06/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/24/2023] Open
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-diffusion tensor imaging [DTI] and neurite orientation dispersion and density imaging [NODDI] multicompartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased, and fwe-DTI metrics decreased with age. By applying nonlinear growth models in a vertex-wise analysis, we observed a general posterior-to-anterior pattern of maturation, where the fwe-DTI measures mean diffusivity and radial diffusivity reached peak maturation earlier than the NODDI metrics neurite density index. Using non-negative matrix factorization, we found occipito-parietal cortical regions that correspond to lower order sensory domains mature earlier than fronto-temporal higher order association domains. Our findings corroborate previous histological and neuroimaging studies that show spatially varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically determined regional patterns of change.
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Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
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11
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Seidlitz J, Mallard TT, Vogel JW, Lee YH, Warrier V, Ball G, Hansson O, Hernandez LM, Mandal AS, Wagstyl K, Lombardo MV, Courchesne E, Glessner JT, Satterthwaite TD, Bethlehem RAI, Bernstock JD, Tasaki S, Ng B, Gaiteri C, Smoller JW, Ge T, Gur RE, Gandal MJ, Alexander-Bloch AF. The molecular genetic landscape of human brain size variation. Cell Rep 2023; 42:113439. [PMID: 37963017 DOI: 10.1016/j.celrep.2023.113439] [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: 11/09/2022] [Revised: 06/13/2023] [Accepted: 10/27/2023] [Indexed: 11/16/2023] Open
Abstract
Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.
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Affiliation(s)
- Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Jacob W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Younga H Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK; Department of Psychology, University of Cambridge, Cambridge CB2 1TN, UK
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, VIC 3052, Australia; Department of Paediatrics, University of Melbourne, Melbourne, Melbourne, VIC 3052, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö P663+Q9, Sweden; Memory Clinic, Skåne University Hospital, Malmö P663+Q9, Sweden
| | - Leanna M Hernandez
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Ayan S Mandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London WC1N 3AR, UK
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, 38068 Rovereto, Italy
| | - Eric Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA 92093, USA; Autism Center of Excellence, University of California, San Diego, San Diego, CA 92093, USA
| | - Joseph T Glessner
- The Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | | | - Joshua D Bernstock
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard University, Boston, MA 02115, USA; Department of Neurosurgery, Boston Children's Hospital, Harvard University, Boston, MA 02115, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shinya Tasaki
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Bernard Ng
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA 02142, USA; Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Raquel E Gur
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael J Gandal
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
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12
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Liu J, Chen H, Cornea E, Gilmore JH, Gao W. Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy. Cereb Cortex 2023; 33:10367-10379. [PMID: 37585708 PMCID: PMC10545442 DOI: 10.1093/cercor/bhad288] [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: 12/05/2022] [Revised: 07/13/2023] [Indexed: 08/18/2023] Open
Abstract
Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.
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Affiliation(s)
- Janelle Liu
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
| | - Haitao Chen
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC 27514, United States
| | - Wei Gao
- Department of Biomedical Sciences, and Imaging, Cedars–Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, CA 90048, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, United States
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13
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Kim JI, Kim BN, Lee YA, Shin CH, Hong YC, Døssing LD, Hildebrandt G, Lim YH. Association between early-childhood exposure to perfluoroalkyl substances and ADHD symptoms: A prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 879:163081. [PMID: 36972880 DOI: 10.1016/j.scitotenv.2023.163081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 03/01/2023] [Accepted: 03/22/2023] [Indexed: 05/17/2023]
Abstract
There is evidence that exposure to perfluoroalkyl substances (PFAS) is associated with attention-deficit/hyperactivity disorder (ADHD) symptoms. Previous studies have focused on prenatal exposure to PFAS, and only few studies have examined the associations of early-childhood exposure, especially at low exposure levels. This study explored the association between early-childhood exposure to PFAS and ADHD symptoms later in childhood. In 521 children, we measured the serum levels of six PFAS in peripheral blood at the ages of 2 and 4 years, including perfluorooctanoate (PFOA), perfluornonanoicacid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorohexane sulfonic acid (PFHxS), and perfluorooctane sulfonate (PFOS). The ADHD Rating Scale IV (ARS) was utilized to measure ADHD traits at 8 years of age. We explored the relationship between PFAS and ARS scores using Poisson regression models after adjusting for potential confounders. Levels of exposure to individual PFAS and the summed value were divided into quartiles to examine possible nonlinear relationships. All six PFAS exhibited inverted U-shaped curves. Children in the 2nd and 3rd quartile levels of each PFAS showed higher ARS scores than those in the1st quartile level. Below the 3rd quartile of the summed levels of six PFAS (ΣPFAS), a doubling of the ΣPFAS was associated with an 20.0 % (95 % CI: 9.5 %, 31.5 %) increase in ADHD scores. However, at the age of 4 years, none of the evaluated PFAS exhibited linear or nonlinear associations with the ARS scores. Thus, school-aged children may be vulnerable to the neurotoxic effects of exposure to PFAS at age 2 that contribute to ADHD, particularly at low to mid-levels.
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Affiliation(s)
- Johanna Inhyang Kim
- Department of Psychiatry, Hanyang University Medical Center, 222 Wangsimni-ro, Seondong-gu, Seoul 04763, Republic of Korea
| | - Bung-Nyun Kim
- Division of Children and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea
| | - Young Ah Lee
- Department of Pediatrics, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea
| | - Choong Ho Shin
- Department of Pediatrics, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea
| | - Yun-Chul Hong
- Department of Preventive Medicine, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea; Environmental Health Center, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea; Institute of Environmental Medicine, Seoul National University Medical Research Center, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea
| | - Lise Dalgaard Døssing
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Oster Farmagsgade 5, 1014 Kobenhavn, Denmark
| | - Gustav Hildebrandt
- Section of Environmental Health, Department of Public Health, University of Copenhagen, Oster Farmagsgade 5, 1014 Kobenhavn, Denmark
| | - Youn-Hee Lim
- Environmental Health Center, Seoul National University College of Medicine, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea; Institute of Environmental Medicine, Seoul National University Medical Research Center, 103 Daehangno, Jongno-gu, Seoul 03080, Republic of Korea; Section of Environmental Health, Department of Public Health, University of Copenhagen, Oster Farmagsgade 5, 1014 Kobenhavn, Denmark.
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14
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Mamah D. A Review of Potential Neuroimaging Biomarkers of Schizophrenia-Risk. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2023; 8:e230005. [PMID: 37427077 PMCID: PMC10327607 DOI: 10.20900/jpbs.20230005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
The risk for developing schizophrenia is increased among first-degree relatives of those with psychotic disorders, but the risk is even higher in those meeting established criteria for clinical high risk (CHR), a clinical construct most often comprising of attenuated psychotic experiences. Conversion to psychosis among CHR youth has been reported to be about 15-35% over three years. Accurately identifying individuals whose psychotic symptoms will worsen would facilitate earlier intervention, but this has been difficult to do using behavior measures alone. Brain-based risk markers have the potential to improve the accuracy of predicting outcomes in CHR youth. This narrative review provides an overview of neuroimaging studies used to investigate psychosis risk, including studies involving structural, functional, and diffusion imaging, functional connectivity, positron emission tomography, arterial spin labeling, magnetic resonance spectroscopy, and multi-modality approaches. We present findings separately in those observed in the CHR state and those associated with psychosis progression or resilience. Finally, we discuss future research directions that could improve clinical care for those at high risk for developing psychotic disorders.
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Affiliation(s)
- Daniel Mamah
- Department of Psychiatry, Washington University Medical School, St. Louis, MO, 63110, USA
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15
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Levy WB, Baxter RA. Growing dendrites enhance a neuron's computational power and memory capacity. Neural Netw 2023; 164:275-309. [PMID: 37163846 DOI: 10.1016/j.neunet.2023.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/12/2023]
Abstract
Neocortical pyramidal neurons have many dendrites, and such dendrites are capable of, in isolation of one-another, generating a neuronal spike. It is also now understood that there is a large amount of dendritic growth during the first years of a humans life, arguably a period of prodigious learning. These observations inspire the construction of a local, stochastic algorithm based on an earlier stochastic, homeostatic, Hebbian developmental theory. Here we investigate the neurocomputational advantages and limits on this novel algorithm that combines dendritogenesis with supervised adaptive synaptogenesis. Neurons created with this algorithm have enhanced memory capacity, can avoid catastrophic interference (forgetting), and have the ability to unmix mixture distributions. In particular, individual dendrites develop within each class, in an unsupervised manner, to become feature-clusters that correspond to the mixing elements of class-conditional mixture distribution. Error-free classification is demonstrated with input perturbations up to 40%. Although discriminative problems are used to understand the capabilities of the stochastic algorithm and the neuronal connectivity it produces, the algorithm is in the generative class, it thus seems ideal for decisions that require generalization, i.e., extrapolation beyond previous learning.
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Affiliation(s)
- William B Levy
- Department of Neurosurgery, University of Virginia School of Medicine, Charlottesville, VA 22908, United States of America; Informed Simplifications, Earlysville, VA 22936, United States of America.
| | - Robert A Baxter
- Department of Neurosurgery, University of Virginia School of Medicine, Charlottesville, VA 22908, United States of America; Baxter Adaptive Systems, Bedford, MA 01730, United States of America
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16
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Albaugh MD, Hudziak JJ, Spechler PA, Chaarani B, Lepage C, Jeon S, Rioux P, Evans AC, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Poustka L, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Potter AS, Garavan H. Conduct problems are associated with accelerated thinning of emotion-related cortical regions in a community-based sample of adolescents. Psychiatry Res Neuroimaging 2023; 330:111614. [PMID: 36812809 DOI: 10.1016/j.pscychresns.2023.111614] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023]
Abstract
Few studies have examined the association between conduct problems and cerebral cortical development. Herein, we characterize the association between age-related brain change and conduct problems in a large longitudinal, community-based sample of adolescents. 1,039 participants from the IMAGEN study possessed psychopathology and surface-based morphometric data at study baseline (M = 14.42 years, SD = 0.40; 559 females) and 5-year follow-up. Self-reports of conduct problems were obtained using the Strengths and Difficulties Questionnaire (SDQ). Vertex-level linear mixed effects models were implemented using the Matlab toolbox, SurfStat. To investigate the extent to which cortical thickness maturation was qualified by dimensional measures of conduct problems, we tested for an interaction between age and SDQ Conduct Problems (CP) score. There was no main effect of CP score on cortical thickness; however, a significant "Age by CP" interaction was revealed in bilateral insulae, left inferior frontal gyrus, left rostral anterior cingulate, left posterior cingulate, and bilateral inferior parietal cortices. Across regions, follow-up analysis revealed higher levels of CP were associated with accelerated age-related thinning. Findings were not meaningfully altered when controlling for alcohol use, co-occurring psychopathology, and socioeconomic status. Results may help to further elucidate neurodevelopmental patterns linking adolescent conduct problems with adverse adult outcomes.
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Affiliation(s)
- Matthew D Albaugh
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America.
| | - James J Hudziak
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Philip A Spechler
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Claude Lepage
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Seun Jeon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Pierre Rioux
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Alan C Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany [or depending on journal requirements can be: Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2 - 12, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrieȝ, University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli; Gif-sur-Yvette, Paris; France; AP-HP. Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris; France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany; Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany; Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Alexandra S Potter
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
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17
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Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.31.534636. [PMID: 37034810 PMCID: PMC10081273 DOI: 10.1101/2023.03.31.534636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-DTI and NODDI multi-compartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased and fwe-DTI metrics decreased with age. Using non-negative matrix factorization, we found cortical regions that correspond to lower-order sensory regions mature earlier than higher-order association regions. Our findings corroborate previous histological and neuroimaging studies that show spatially-varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically-determined regional patterns of change.
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Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
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18
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Ge R, Sassi R, Yatham LN, Frangou S. Neuroimaging profiling identifies distinct brain maturational subtypes of youth with mood and anxiety disorders. Mol Psychiatry 2023; 28:1072-1078. [PMID: 36577839 PMCID: PMC10005933 DOI: 10.1038/s41380-022-01925-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 12/07/2022] [Accepted: 12/13/2022] [Indexed: 12/29/2022]
Abstract
Mood and anxiety disorders typically begin in adolescence and have overlapping clinical features but marked inter-individual variation in clinical presentation. The use of multimodal neuroimaging data may offer novel insights into the underlying brain mechanisms. We applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9-10 years, with mood and anxiety disorders (N = 1931) compared to typically developing youth (N = 2823). We identified three subtypes that were robust to permutation testing and sample composition. Subtype 1 evidenced a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning and myelination and greater cortical surface expansion globally. Subtype 2 displayed a pattern of delayed cortical maturation indicated by higher cortical thickness and lower cortical surface area expansion and myelination compared to the typically developing group. Subtype 3 showed evidence of atypical brain maturation involving globally lower cortical thickness and surface coupled with higher myelination and neural density. Subtype 1 had superior cognitive function in contrast to the other two subtypes that underperformed compared to the typically developing group. Higher levels of parental psychopathology, family conflict, and social adversity were common to all subtypes, with subtype 3 having the highest burden of adverse exposures. These analyses comprehensively characterize pre-adolescent mood and anxiety disorders, the biopsychosocial context in which they arise, and lay the foundation for the examination of the longitudinal evolution of the subtypes identified as the study sample transitions through adolescence.
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Affiliation(s)
- Ruiyang Ge
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roberto Sassi
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital, Vancouver, BC, Canada
| | - Lakshmi N Yatham
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Sophia Frangou
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. .,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. .,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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19
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Vanderhaeghen P, Polleux F. Developmental mechanisms underlying the evolution of human cortical circuits. Nat Rev Neurosci 2023; 24:213-232. [PMID: 36792753 PMCID: PMC10064077 DOI: 10.1038/s41583-023-00675-z] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/10/2023] [Indexed: 02/17/2023]
Abstract
The brain of modern humans has evolved remarkable computational abilities that enable higher cognitive functions. These capacities are tightly linked to an increase in the size and connectivity of the cerebral cortex, which is thought to have resulted from evolutionary changes in the mechanisms of cortical development. Convergent progress in evolutionary genomics, developmental biology and neuroscience has recently enabled the identification of genomic changes that act as human-specific modifiers of cortical development. These modifiers influence most aspects of corticogenesis, from the timing and complexity of cortical neurogenesis to synaptogenesis and the assembly of cortical circuits. Mutations of human-specific genetic modifiers of corticogenesis have started to be linked to neurodevelopmental disorders, providing evidence for their physiological relevance and suggesting potential relationships between the evolution of the human brain and its sensitivity to specific diseases.
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Affiliation(s)
- Pierre Vanderhaeghen
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium.
- Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium.
| | - Franck Polleux
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA.
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
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20
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Shao F, Shen Z. How can artificial neural networks approximate the brain? Front Psychol 2023; 13:970214. [PMID: 36698593 PMCID: PMC9868316 DOI: 10.3389/fpsyg.2022.970214] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023] Open
Abstract
The article reviews the history development of artificial neural networks (ANNs), then compares the differences between ANNs and brain networks in their constituent unit, network architecture, and dynamic principle. The authors offer five points of suggestion for ANNs development and ten questions to be investigated further for the interdisciplinary field of brain simulation. Even though brain is a super-complex system with 1011 neurons, its intelligence does depend rather on the neuronal type and their energy supply mode than the number of neurons. It might be possible for ANN development to follow a new direction that is a combination of multiple modules with different architecture principle and multiple computation, rather than very large scale of neural networks with much more uniformed units and hidden layers.
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Affiliation(s)
- Feng Shao
- Beijing Key Laboratory of Behavior and Mental Health, School of Psychological and Cognitive Sciences, Peking University, Beijing, China
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21
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Wang W, Yu Q, Liang W, Xu F, Li Z, Tang Y, Liu S. Altered cortical microstructure in preterm infants at term-equivalent age relative to term-born neonates. Cereb Cortex 2023; 33:651-662. [PMID: 35259759 DOI: 10.1093/cercor/bhac091] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 01/11/2022] [Accepted: 02/08/2022] [Indexed: 02/03/2023] Open
Abstract
Preterm (PT) birth is a potential factor for abnormal brain development. Although various alterations of cortical structure and functional connectivity in preterm infants have been reported, the underlying microstructural foundation is still undetected thoroughly in PT infants relative to full-term (FT) neonates. To detect the very early cortical microstructural alteration noninvasively with advanced neurite orientation dispersion and density imaging (NODDI) on a whole-brain basis, we used multi-shell diffusion MRI of healthy newborns selected from the Developing Human Connectome Project. 73 PT infants and 69 FT neonates scanned at term-equivalent age were included in this study. By extracting the core voxels of gray matter (GM) using GM-based spatial statistics (GBSS), we found that comparing to FT neonates, infants born preterm showed extensive lower neurite density in both primary and higher-order association cortices (FWE corrected, P < 0.025). Higher orientation dispersion was only found in very preterm subgroup in the orbitofrontal cortex, fronto-insular cortex, entorhinal cortex, a portion of posterior cingular gyrus, and medial parieto-occipital cortex. This study provided new insights into exploring structural MR for functional and behavioral variations in preterm population, and these findings may have marked clinical importance, particularly in the guidance of ameliorating the development of premature brain.
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Affiliation(s)
- Wenjun Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Wenjia Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Zhuoran Li
- Department of Ultrasound, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
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22
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Thomas MSC, Coecke S. Associations between Socioeconomic Status, Cognition, and Brain Structure: Evaluating Potential Causal Pathways Through Mechanistic Models of Development. Cogn Sci 2023; 47:e13217. [PMID: 36607218 DOI: 10.1111/cogs.13217] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 10/14/2022] [Accepted: 10/24/2022] [Indexed: 01/07/2023]
Abstract
Differences in socioeconomic status (SES) correlate both with differences in cognitive development and in brain structure. Associations between SES and brain measures such as cortical surface area and cortical thickness mediate differences in cognitive skills such as executive function and language. However, causal accounts that link SES, brain, and behavior are challenging because SES is a multidimensional construct: correlated environmental factors, such as family income and parental education, are only distal markers for proximal causal pathways. Moreover, the causal accounts themselves must span multiple levels of description, employ a developmental perspective, and integrate genetic effects on individual differences. Nevertheless, causal accounts have the potential to inform policy and guide interventions to reduce gaps in developmental outcomes. In this article, we review the range of empirical data to be integrated in causal accounts of developmental effects on the brain and cognition associated with variation in SES. We take the specific example of language development and evaluate the potential of a multiscale computational model of development, based on an artificial neural network, to support the construction of causal accounts. We show how, with bridging assumptions that link properties of network structure to magnetic resonance imaging (MRI) measures of brain structure, different sets of empirical data on SES effects can be connected. We use the model to contrast two possible causal pathways for environmental influences that are associated with SES: differences in prenatal brain development and differences in postnatal cognitive stimulation. We then use the model to explore the implications of each pathway for the potential to intervene to reduce gaps in developmental outcomes. The model points to the cumulative effects of social disadvantage on multiple pathways as the source of the poorest response to interventions. Overall, we highlight the importance of implemented models to test competing accounts of environmental influences on individual differences.
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Affiliation(s)
- Michael S C Thomas
- Developmental Neurocognition Laboratory, Department of Psychological Sciences, Birkbeck, University of London, 3 Quantinuum, UK.,Centre for Educational Neuroscience, Birkbeck, University of London
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23
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Renner J, Rasia-Filho AA. Morphological Features of Human Dendritic Spines. ADVANCES IN NEUROBIOLOGY 2023; 34:367-496. [PMID: 37962801 DOI: 10.1007/978-3-031-36159-3_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Dendritic spine features in human neurons follow the up-to-date knowledge presented in the previous chapters of this book. Human dendrites are notable for their heterogeneity in branching patterns and spatial distribution. These data relate to circuits and specialized functions. Spines enhance neuronal connectivity, modulate and integrate synaptic inputs, and provide additional plastic functions to microcircuits and large-scale networks. Spines present a continuum of shapes and sizes, whose number and distribution along the dendritic length are diverse in neurons and different areas. Indeed, human neurons vary from aspiny or "relatively aspiny" cells to neurons covered with a high density of intermingled pleomorphic spines on very long dendrites. In this chapter, we discuss the phylogenetic and ontogenetic development of human spines and describe the heterogeneous features of human spiny neurons along the spinal cord, brainstem, cerebellum, thalamus, basal ganglia, amygdala, hippocampal regions, and neocortical areas. Three-dimensional reconstructions of Golgi-impregnated dendritic spines and data from fluorescence microscopy are reviewed with ultrastructural findings to address the complex possibilities for synaptic processing and integration in humans. Pathological changes are also presented, for example, in Alzheimer's disease and schizophrenia. Basic morphological data can be linked to current techniques, and perspectives in this research field include the characterization of spines in human neurons with specific transcriptome features, molecular classification of cellular diversity, and electrophysiological identification of coexisting subpopulations of cells. These data would enlighten how cellular attributes determine neuron type-specific connectivity and brain wiring for our diverse aptitudes and behavior.
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Affiliation(s)
- Josué Renner
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
| | - Alberto A Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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24
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Petanjek Z, Banovac I, Sedmak D, Hladnik A. Dendritic Spines: Synaptogenesis and Synaptic Pruning for the Developmental Organization of Brain Circuits. ADVANCES IN NEUROBIOLOGY 2023; 34:143-221. [PMID: 37962796 DOI: 10.1007/978-3-031-36159-3_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Synaptic overproduction and elimination is a regular developmental event in the mammalian brain. In the cerebral cortex, synaptic overproduction is almost exclusively correlated with glutamatergic synapses located on dendritic spines. Therefore, analysis of changes in spine density on different parts of the dendritic tree in identified classes of principal neurons could provide insight into developmental reorganization of specific microcircuits.The activity-dependent stabilization and selective elimination of the initially overproduced synapses is a major mechanism for generating diversity of neural connections beyond their genetic determination. The largest number of overproduced synapses was found in the monkey and human cerebral cortex. The highest (exceeding adult values by two- to threefold) and most protracted overproduction (up to third decade of life) was described for associative layer IIIC pyramidal neurons in the human dorsolateral prefrontal cortex.Therefore, the highest proportion and extraordinarily extended phase of synaptic spine overproduction is a hallmark of neural circuitry in human higher-order associative areas. This indicates that microcircuits processing the most complex human cognitive functions have the highest level of developmental plasticity. This finding is the backbone for understanding the effect of environmental impact on the development of the most complex, human-specific cognitive and emotional capacities, and on the late onset of human-specific neuropsychiatric disorders, such as autism and schizophrenia.
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Affiliation(s)
- Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia.
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia.
| | - Ivan Banovac
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
| | - Ana Hladnik
- Department of Anatomy and Clinical Anatomy, School of Medicine, University of Zagreb, Zagreb, Croatia
- Department of Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Zagreb, Croatia
- Center of Excellence for Basic, Clinical and Translational Neuroscience, School of Medicine, University of Zagreb, Zagreb, Croatia
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25
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Rasia-Filho AA, Calcagnotto ME, von Bohlen Und Halbach O. Introduction: What Are Dendritic Spines? ADVANCES IN NEUROBIOLOGY 2023; 34:1-68. [PMID: 37962793 DOI: 10.1007/978-3-031-36159-3_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Dendritic spines are cellular specializations that greatly increase the connectivity of neurons and modulate the "weight" of most postsynaptic excitatory potentials. Spines are found in very diverse animal species providing neural networks with a high integrative and computational possibility and plasticity, enabling the perception of sensorial stimuli and the elaboration of a myriad of behavioral displays, including emotional processing, memory, and learning. Humans have trillions of spines in the cerebral cortex, and these spines in a continuum of shapes and sizes can integrate the features that differ our brain from other species. In this chapter, we describe (1) the discovery of these small neuronal protrusions and the search for the biological meaning of dendritic spines; (2) the heterogeneity of shapes and sizes of spines, whose structure and composition are associated with the fine-tuning of synaptic processing in each nervous area, as well as the findings that support the role of dendritic spines in increasing the wiring of neural circuits and their functions; and (3) within the intraspine microenvironment, the integration and activation of signaling biochemical pathways, the compartmentalization of molecules or their spreading outside the spine, and the biophysical properties that can affect parent dendrites. We also provide (4) examples of plasticity involving dendritic spines and neural circuits relevant to species survival and comment on (5) current research advancements and challenges in this exciting research field.
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Affiliation(s)
- Alberto A Rasia-Filho
- Department of Basic Sciences/Physiology and Graduate Program in Biosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Maria Elisa Calcagnotto
- Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Graduate Program in Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Graduate Program in Psychiatry and Behavioral Science, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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26
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Liu N, Liu Q, Yang Z, Xu J, Fu G, Zhou Y, Li H, Wang Y, Liu L, Qian Q. Different functional alteration in attention-deficit/hyperactivity disorder across developmental age groups: A meta-analysis and an independent validation of resting-state functional connectivity studies. CNS Neurosci Ther 2022; 29:60-69. [PMID: 36468409 PMCID: PMC9804052 DOI: 10.1111/cns.14032] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/21/2022] [Accepted: 10/09/2022] [Indexed: 12/09/2022] Open
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a highly complex and heterogeneous disorder. Abnormal brain connectivity in ADHD might be influenced by developmental ages which might lead to the lacking of significant spatial convergence across studies. However, the developmental patterns and mechanisms of ADHD brain connectivity remain to be fully uncovered. METHODS In the present study, we searched PubMed, Scopus, Web of Science, and Embase for seed-based whole-brain resting-state functional connectivity studies of ADHD published through October 12th, 2020. The seeds meeting inclusion criteria were categorized into the cortex group and subcortex group, as previous studies suggested that the cortex and subcortex have different temporal patterns of development. Activation likelihood estimation meta-analysis was performed to investigate the abnormal connectivity in different age groups (all-age group, younger: <12 years, older: ≥12 years). Moreover, significant convergence of reported foci was used as seeds for validation with our independent dataset. RESULTS As with previous studies, scarce results were found in the all-age group. However, we found that the younger group consistently exhibited hyper-connectivity between different parts of the cortex and left middle frontal gyrus, and hypo-connectivity between different parts of the cortex and left putamen/pallidus/amygdala. Whereas, the older group (mainly for adults) showed hyper-connectivity between the cortex and right precuneus/sub-gyral/cingulate gyrus. Besides, the abnormal cortico-cortical and cortico-subcortical functional connectivity in children, and the abnormal cortico-cortical functional connectivity in adults were verified in our independent dataset. CONCLUSION Our study emphasizes the importance of developmental age effects on the study of brain networks in ADHD. Further, we proposed that cortico-cortical and cortico-subcortical connectivity might play an important role in the pathophysiology of children with ADHD, while abnormal cortico-cortical connections were more important for adults with ADHD. This work provided a potential new insight to understand the neurodevelopmental mechanisms and possible clinical application of ADHD.
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Affiliation(s)
- Ningning Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Qianrong Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Ziqi Yang
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Jie Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen UniversityShenzhenChina,Department of Biomedical Sciences of Cells & Systems, Section Cognitive Neuroscience, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Guanghui Fu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Yi Zhou
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Haimei Li
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Yufeng Wang
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Lu Liu
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
| | - Qiujin Qian
- Peking University Sixth Hospital, Institute of Mental HealthBeijingChina,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital)BeijingChina
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27
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Galakhova AA, Hunt S, Wilbers R, Heyer DB, de Kock CPJ, Mansvelder HD, Goriounova NA. Evolution of cortical neurons supporting human cognition. Trends Cogn Sci 2022; 26:909-922. [PMID: 36117080 PMCID: PMC9561064 DOI: 10.1016/j.tics.2022.08.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 01/12/2023]
Abstract
Human cognitive abilities are generally thought to arise from cortical expansion over the course of human brain evolution. In addition to increased neuron numbers, this cortical expansion might be driven by adaptations in the properties of single neurons and their local circuits. We review recent findings on the distinct structural, functional, and transcriptomic features of human cortical neurons and their organization in cortical microstructure. We focus on the supragranular cortical layers, which showed the most prominent expansion during human brain evolution, and the properties of their principal cells: pyramidal neurons. We argue that the evolutionary adaptations in neuronal features that accompany the expansion of the human cortex partially underlie interindividual variability in human cognitive abilities.
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Affiliation(s)
- A A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - S Hunt
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - R Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - D B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - C P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - H D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands
| | - N A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, De Boelelaan 1085, Amsterdam 1081 HV, The Netherlands.
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28
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Liang W, Yu Q, Wang W, Dhollander T, Suluba E, Li Z, Xu F, Hu Y, Tang Y, Liu S. A comparative study of the superior longitudinal fasciculus subdivisions between neonates and young adults. Brain Struct Funct 2022; 227:2713-2730. [PMID: 36114859 PMCID: PMC9618541 DOI: 10.1007/s00429-022-02565-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 09/03/2022] [Indexed: 12/04/2022]
Abstract
The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.
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Affiliation(s)
- Wenjia Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Wenjun Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Emmanuel Suluba
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Zhuoran Li
- Department of Ultrasound, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yang Hu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
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Hanson KL, Grant SE, Funk LH, Schumann CM, Bauman MD. Impact of Maternal Immune Activation on Nonhuman Primate Prefrontal Cortex Development: Insights for Schizophrenia. Biol Psychiatry 2022; 92:460-469. [PMID: 35773097 PMCID: PMC9888668 DOI: 10.1016/j.biopsych.2022.04.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/30/2022] [Accepted: 04/13/2022] [Indexed: 02/02/2023]
Abstract
Late adolescence is a period of dynamic change in the brain as humans learn to navigate increasingly complex environments. In particular, prefrontal cortical (PFC) regions undergo extensive remodeling as the brain is fine-tuned to orchestrate cognitive control over attention, reasoning, and emotions. Late adolescence also presents a uniquely vulnerable period as neurodevelopmental illnesses, such as schizophrenia, become evident and worsen into young adulthood. Challenges in early development, including prenatal exposure to infection, may set the stage for a cascade of maladaptive events that ultimately result in aberrant PFC connectivity and function before symptoms emerge. A growing body of research suggests that activation of the mother's immune system during pregnancy may act as a disease primer, in combination with other environmental and genetic factors, contributing to an increased risk of neurodevelopmental disorders, including schizophrenia. Animal models provide an invaluable opportunity to examine the course of brain and behavioral changes in offspring exposed to maternal immune activation (MIA). Although the vast majority of MIA research has been carried out in rodents, here we highlight the translational utility of the nonhuman primate (NHP) as a model species more closely related to humans in PFC structure and function. In this review, we consider the protracted period of brain and behavioral maturation in the NHP, describe emerging findings from MIA NHP offspring in the context of rodent preclinical models, and lastly explore the translational relevance of the NHP MIA model to expand understanding of the etiology and developmental course of PFC pathology in schizophrenia.
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Affiliation(s)
- Kari L Hanson
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; MIND Institute, University of California, Davis, Davis, California
| | - Simone E Grant
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California
| | - Lucy H Funk
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California
| | - Cynthia M Schumann
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; MIND Institute, University of California, Davis, Davis, California.
| | - Melissa D Bauman
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, California; MIND Institute, University of California, Davis, Davis, California; California National Primate Research Center, University of California, Davis, Davis, California.
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Hendry A, Greenhalgh I, Bailey R, Fiske A, Dvergsdal H, Holmboe K. Development of directed global inhibition, competitive inhibition and behavioural inhibition during the transition between infancy and toddlerhood. Dev Sci 2022; 25:e13193. [PMID: 34811852 DOI: 10.1111/desc.13193] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 09/17/2021] [Accepted: 11/01/2021] [Indexed: 01/04/2023]
Abstract
Inhibitory control (IC) is a core executive function integral to self-regulation and cognitive control, yet is itself multi-componential. Directed global inhibition entails stopping an action on demand. Competitive inhibition is engaged when an alternative response must also be produced. Related, but not an executive function, is temperamentally-driven wariness of novelty, known as behavioural inhibition. Understanding early development of these components has been hampered by a shortage of suitable measures. We combine established and novel measures to capture directed global inhibition (Toy Prohibition, Touchscreen Prohibition), competitive inhibition (A-not-B, Early Childhood Inhibitory Touchscreen Task; ECITT) and behavioural inhibition (Touchscreen Approach) in 113 10- and 16-month-olds (73 seen longitudinally). ECITT performance shows good 1-week test-retest reliability at 10-months (r = 0.30-0.60) but little stability to 16-months. Directed global inhibition performance shows developmental progression but little stability of individual differences from 10 to 16 months. Performance on measures targeting similar IC components shows greater coherence at 16-months (r = 0.23-0.59) compared with 10-months (r = 0.09-0.35). Probing of ECITT condition effects indicates toddlers are more able, compared with infants, to override immediate prepotencies; indicative of increasingly flexible control over behaviour. However, exerting IC over cumulative prepotencies appears just as challenging for toddlers as infants. Exploratory analyses show little evidence for cross-sectional or longitudinal associations between behavioural, directed global and competitive inhibition. In combination, these findings indicate that IC is not yet a stable, unidimensional construct during the transition between infancy and toddlerhood, and highlight the need for careful selection of multiple measures for those interested in capturing early variation in IC.
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Affiliation(s)
- Alexandra Hendry
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | | | | | - Abigail Fiske
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Henrik Dvergsdal
- Division of Entrepreneurship and Innovation, Nord University Business School, Bodø, Norway
| | - Karla Holmboe
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- School of Psychological Science, University of Bristol, Bristol, UK
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Romero-Morales AI, Gama V. Revealing the Impact of Mitochondrial Fitness During Early Neural Development Using Human Brain Organoids. Front Mol Neurosci 2022; 15:840265. [PMID: 35571368 PMCID: PMC9102998 DOI: 10.3389/fnmol.2022.840265] [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: 12/20/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Mitochondrial homeostasis -including function, morphology, and inter-organelle communication- provides guidance to the intrinsic developmental programs of corticogenesis, while also being responsive to environmental and intercellular signals. Two- and three-dimensional platforms have become useful tools to interrogate the capacity of cells to generate neuronal and glia progeny in a background of metabolic dysregulation, but the mechanistic underpinnings underlying the role of mitochondria during human neurogenesis remain unexplored. Here we provide a concise overview of cortical development and the use of pluripotent stem cell models that have contributed to our understanding of mitochondrial and metabolic regulation of early human brain development. We finally discuss the effects of mitochondrial fitness dysregulation seen under stress conditions such as metabolic dysregulation, absence of developmental apoptosis, and hypoxia; and the avenues of research that can be explored with the use of brain organoids.
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Affiliation(s)
| | - Vivian Gama
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, United States
- Vanderbilt Center for Stem Cell Biology, Vanderbilt University, Nashville, TN, United States
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, United States
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32
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Fehlbaum LV, Peters L, Dimanova P, Roell M, Borbás R, Ansari D, Raschle NM. Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain's reading network. Dev Cogn Neurosci 2022; 53:101058. [PMID: 34999505 PMCID: PMC8749220 DOI: 10.1016/j.dcn.2022.101058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/19/2021] [Accepted: 01/03/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads. METHODS Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children's age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit. RESULTS Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT. CONCLUSION Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.
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Affiliation(s)
- Lynn V Fehlbaum
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Lien Peters
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Plamina Dimanova
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Margot Roell
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Réka Borbás
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Daniel Ansari
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Nora M Raschle
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland.
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王 菲, 王 路, 熊 玥, 邓 静, 吕 明, 汤 博, 张 潇, 李 英. [Mechanism of valproic acid-induced dendritic spine and synaptic impairment in the prefrontal cortex for causing core autistic symptoms in mice]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2022; 42:101-107. [PMID: 35249876 PMCID: PMC8901407 DOI: 10.12122/j.issn.1673-4254.2022.01.12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Indexed: 01/24/2023]
Abstract
OBJECTIVE To investigate the mechanism of valproic acid (VPA) -induced impairment of the dendritic spines and synapses in the prefrontal cortex (PFC) for causing core symptoms of autism spectrum disorder (ASD) in mice. METHODS Female C57 mice were subjected to injections of saline or VPA on gestational days 10 and 12, and the male offspring mice in the two groups were used as the normal control group and ASD model group (n=10), respectively. Another 20 male mice with fetal exposure to VPA were randomized into two groups for stereotactic injection of DMSO or Wortmannin into the PFC (n=10). Open field test, juvenile play test and 3-chamber test were used to evaluate autistic behaviors of the mice. The density of dendrite spines in the PFC was observed with Golgi staining. Western blotting and immunofluorescence staining were used to detect the expressions of p-PI3K, PI3K, p-AKT, AKT, p-mTOR, mTOR and the synaptic proteins PSD95, p-Syn, and Syn in the PFC of the mice. RESULTS Compared with the normal control mice, the mice with fetal exposure to VPA exhibited obvious autism-like behaviors with significantly decreased density of total, mushroom and stubby dendritic spines (P < 0.05) and increased filopodia dendritic spines (P < 0.05) in the PFC. The VPA-exposed mice also showed significantly increased expressions of p-PI3K/PI3K, p-AKT/AKT, and p-mTOR/mTOR (P < 0.01) and lowered expressions of PSD95 and p-Syn/Syn in the PFC (P < 0.05 or 0.001). Wortmannin injection into the PFC obviously improved the ASD-like phenotype and dendritic spine development, down-regulated PI3K/Akt/mTOR signaling pathway and up-regulated the synaptic proteins in VPA-exposed mice. CONCLUSION In male mice with fetal exposure to VPA, excessive activation of PI3K/Akt/mTOR signaling pathway and decreased expressions of the synaptic proteins PSD95 and p-Syn cause dendritic spine damage and synaptic development disturbance in the PFC, which eventually leads to ASD-like phenotype.
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Affiliation(s)
- 菲菲 王
- 重庆医科大学基础医学院生理学教研室,重庆 400016Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - 路义 王
- 重庆医科大学基础医学院生理学教研室,重庆 400016Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - 玥 熊
- 重庆医科大学基础医学院生理学教研室,重庆 400016Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - 静 邓
- 重庆医科大学基础医学院生理学教研室,重庆 400016Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - 明其 吕
- 重庆医科大学实验教学管理中心,重庆 400016Experimental Teaching Management Center, Chongqing Medical University, Chongqing 400016, China
| | - 博诣 汤
- 重庆医科大学临床医学院,重庆 400016Clinical Medical College, Chongqing Medical University, Chongqing 400016, China
| | - 潇月 张
- 重庆医科大学临床医学院,重庆 400016Clinical Medical College, Chongqing Medical University, Chongqing 400016, China
| | - 英博 李
- 重庆医科大学基础医学院生理学教研室,重庆 400016Department of Physiology, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
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Abstract
During evolution, the cerebral cortex advances by increasing in surface and the introduction of new cytoarchitectonic areas among which the prefrontal cortex (PFC) is considered to be the substrate of highest cognitive functions. Although neurons of the PFC are generated before birth, the differentiation of its neurons and development of synaptic connections in humans extend to the 3rd decade of life. During this period, synapses as well as neurotransmitter systems including their receptors and transporters, are initially overproduced followed by selective elimination. Advanced methods applied to human and animal models, enable investigation of the cellular mechanisms and role of specific genes, non-coding regulatory elements and signaling molecules in control of prefrontal neuronal production and phenotypic fate, as well as neuronal migration to establish layering of the PFC. Likewise, various genetic approaches in combination with functional assays and immunohistochemical and imaging methods reveal roles of neurotransmitter systems during maturation of the PFC. Disruption, or even a slight slowing of the rate of neuronal production, migration and synaptogenesis by genetic or environmental factors, can induce gross as well as subtle changes that eventually can lead to cognitive impairment. An understanding of the development and evolution of the PFC provide insight into the pathogenesis and treatment of congenital neuropsychiatric diseases as well as idiopathic developmental disorders that cause intellectual disabilities.
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Affiliation(s)
- Sharon M Kolk
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, The Netherlands.
| | - Pasko Rakic
- Department of Neuroscience and Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut, USA.
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35
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Campbell KA. The neurobiology of childhood trauma, from early physical pain onwards: as relevant as ever in today's fractured world. Eur J Psychotraumatol 2022; 13:2131969. [PMID: 36276555 PMCID: PMC9586666 DOI: 10.1080/20008066.2022.2131969] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Background: The situation in the world today, encompassing multiple armed conflicts, notably in Ukraine, the Coronavirus pandemic and the effects of climate change, increases the likelihood of childhood exposure to physical injury and pain. Other effects of these worldwide hardships include poverty, malnutrition and starvation, also bringing with them other forms of trauma, including emotional harm, neglect and deliberate maltreatment. Objective: To review the neurobiology of the systems in the developing brain that are most affected by physical and emotional trauma and neglect. Method: The review begins with those that mature first, such as the somatosensory system, progressing to structures that have a more protracted development, including those involved in cognition and emotional regulation. Explored next are developing stress response systems, especially the hypothalamic-pituitary-adrenal axis and its central regulator, corticotropin-releasing hormone. Also examined are reward and anti-reward systems and genetic versus environmental influences. The behavioural consequences of interpersonal childhood trauma, focusing on self-harm and suicide, are also surveyed briefly. Finally, pointers to effective treatment are proffered. Results: The low-threshold nature of circuitry in the developing brain and lack of inhibitory connections therein result in heightened excitability, making the consequences of both physical and emotional trauma more intense. Sensitive and critical periods in the development of structures such as the amygdala render the nervous system more vulnerable to insults occurring at those points, increasing the likelihood of psychiatric disorders, culminating in self-harm and even suicide. Conclusion: In view of the greater excitability of the developing nervous system, and its vulnerability to physical and psychological injuries, the review ends with an exhortation to consider the long-term consequences of childhood trauma, often underestimated or missed altogether when faced with adults suffering mental health problems.
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Wilder L, Semendeferi K. Infant Brain Development and Plasticity from an Evolutionary Perspective. EVOLUTIONARY PSYCHOLOGY 2022. [DOI: 10.1007/978-3-030-76000-7_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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37
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Natsuyama T, Okamoto N, Watanabe K, Chibaatar E, Tesen H, Hayasaki G, Ikenouchi A, Kakeda S, Yoshimura R. Gyrification patterns in first-episode, drug-naïve major depression: Associations with plasma levels of brain-derived neurotrophic factor and psychiatric symptoms. Front Psychiatry 2022; 13:1031386. [PMID: 36684011 PMCID: PMC9852994 DOI: 10.3389/fpsyt.2022.1031386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/06/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Cortical structural changes in major depressive disorder (MDD) are usually studied using a voxel-based morphometry approach to delineate the cortical gray matter volume. Among cortical structures, gyrification patterns are considered a relatively stable indicator. In this study, we investigated differences in gyrification patterns between MDD patients and healthy controls (HCs) and explored the association of gyrification patterns with plasma brain-derived neurotrophic factor (BDNF) levels and depressive symptoms in MDD patients. METHODS We evaluated 79 MDD patients and 94 HCs and assessed depression severity in the patients using the 17-item Hamilton Depression Rating Scale (HAM-D). Blood samples of both groups were collected to measure plasma BDNF levels. Magnetic resonance imaging (MRI) data were obtained using three-dimensional fast-spoiled gradient-recalled acquisition. Differences in plasma BDNF levels between groups were examined using the Mann-Whitney U test. Principal component analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to investigate the gyrification patterns which were significantly different between the groups, i.e., those with variable importance in projection (VIP) scores of >1.5 and p-value < 0.05 in multiple regression analyses adjusted for age and sex. Finally, multiple regression analysis was performed on the selected gyrification patterns to examine their association with BDNF levels in the two groups and HAM-D in the patients. RESULTS There were no significant differences in plasma BDNF levels between the groups. We found that 108 (71.0%) of 152 total local gyrification indices were MDD < HC. We identified 10 disease-differentiating factors based on critical gyrification features (VIP > 1.5 and p-value adjusted for age and sex < 0.05). However, we found no significant correlations between the 10 gyrification patterns and plasma BDNF levels and no interaction with group. Moreover, no significant correlations were observed between the local gyrification indices and HAM-D total scores. CONCLUSION These results suggest that abnormal early cortical neurodevelopment may mediate vulnerability to MDD, independent of plasma BDNF levels and depressive symptoms.
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Affiliation(s)
- Tomoya Natsuyama
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Naomichi Okamoto
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Enkhmurun Chibaatar
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Hirofumi Tesen
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Gaku Hayasaki
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan.,Medical Center for Dementia, Hospital of University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
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Berg J, Sorensen SA, Ting JT, Miller JA, Chartrand T, Buchin A, Bakken TE, Budzillo A, Dee N, Ding SL, Gouwens NW, Hodge RD, Kalmbach B, Lee C, Lee BR, Alfiler L, Baker K, Barkan E, Beller A, Berry K, Bertagnolli D, Bickley K, Bomben J, Braun T, Brouner K, Casper T, Chong P, Crichton K, Dalley R, de Frates R, Desta T, Lee SD, D'Orazi F, Dotson N, Egdorf T, Enstrom R, Farrell C, Feng D, Fong O, Furdan S, Galakhova AA, Gamlin C, Gary A, Glandon A, Goldy J, Gorham M, Goriounova NA, Gratiy S, Graybuck L, Gu H, Hadley K, Hansen N, Heistek TS, Henry AM, Heyer DB, Hill D, Hill C, Hupp M, Jarsky T, Kebede S, Keene L, Kim L, Kim MH, Kroll M, Latimer C, Levi BP, Link KE, Mallory M, Mann R, Marshall D, Maxwell M, McGraw M, McMillen D, Melief E, Mertens EJ, Mezei L, Mihut N, Mok S, Molnar G, Mukora A, Ng L, Ngo K, Nicovich PR, Nyhus J, Olah G, Oldre A, Omstead V, Ozsvar A, Park D, Peng H, Pham T, Pom CA, Potekhina L, Rajanbabu R, Ransford S, Reid D, Rimorin C, Ruiz A, Sandman D, Sulc J, Sunkin SM, Szafer A, Szemenyei V, Thomsen ER, Tieu M, Torkelson A, Trinh J, Tung H, Wakeman W, Waleboer F, Ward K, Wilbers R, Williams G, Yao Z, Yoon JG, Anastassiou C, Arkhipov A, Barzo P, Bernard A, Cobbs C, de Witt Hamer PC, Ellenbogen RG, Esposito L, Ferreira M, Gwinn RP, Hawrylycz MJ, Hof PR, Idema S, Jones AR, Keene CD, Ko AL, Murphy GJ, Ng L, Ojemann JG, Patel AP, Phillips JW, Silbergeld DL, Smith K, Tasic B, Yuste R, Segev I, de Kock CPJ, Mansvelder HD, Tamas G, Zeng H, Koch C, Lein ES. Human neocortical expansion involves glutamatergic neuron diversification. Nature 2021; 598:151-158. [PMID: 34616067 PMCID: PMC8494638 DOI: 10.1038/s41586-021-03813-8] [Citation(s) in RCA: 121] [Impact Index Per Article: 40.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 07/07/2021] [Indexed: 11/09/2022]
Abstract
The neocortex is disproportionately expanded in human compared with mouse1,2, both in its total volume relative to subcortical structures and in the proportion occupied by supragranular layers composed of neurons that selectively make connections within the neocortex and with other telencephalic structures. Single-cell transcriptomic analyses of human and mouse neocortex show an increased diversity of glutamatergic neuron types in supragranular layers in human neocortex and pronounced gradients as a function of cortical depth3. Here, to probe the functional and anatomical correlates of this transcriptomic diversity, we developed a robust platform combining patch clamp recording, biocytin staining and single-cell RNA-sequencing (Patch-seq) to examine neurosurgically resected human tissues. We demonstrate a strong correspondence between morphological, physiological and transcriptomic phenotypes of five human glutamatergic supragranular neuron types. These were enriched in but not restricted to layers, with one type varying continuously in all phenotypes across layers 2 and 3. The deep portion of layer 3 contained highly distinctive cell types, two of which express a neurofilament protein that labels long-range projection neurons in primates that are selectively depleted in Alzheimer's disease4,5. Together, these results demonstrate the explanatory power of transcriptomic cell-type classification, provide a structural underpinning for increased complexity of cortical function in humans, and implicate discrete transcriptomic neuron types as selectively vulnerable in disease.
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Affiliation(s)
- Jim Berg
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Jonathan T Ting
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | | | | | | | | | | | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Brian Kalmbach
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Changkyu Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Brian R Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Eliza Barkan
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Allison Beller
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Kyla Berry
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Kris Bickley
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Peter Chong
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Tsega Desta
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - David Feng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Olivia Fong
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Szabina Furdan
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Anna A Galakhova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Clare Gamlin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Natalia A Goriounova
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | | | | | - Hong Gu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Tim S Heistek
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Alex M Henry
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Djai B Heyer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - DiJon Hill
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Chris Hill
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Madie Hupp
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Jarsky
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Sara Kebede
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lisa Keene
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Lisa Kim
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Caitlin Latimer
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Boaz P Levi
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Rusty Mann
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Desiree Marshall
- Department of Pathology, University of Washington, Seattle, WA, USA
| | | | - Medea McGraw
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Erica Melief
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Eline J Mertens
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Leona Mezei
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Norbert Mihut
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | | | - Gabor Molnar
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Alice Mukora
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lindsay Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kiet Ngo
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Julie Nyhus
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Gaspar Olah
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Aaron Oldre
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Attila Ozsvar
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Daniel Park
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | - David Reid
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Aaron Szafer
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Viktor Szemenyei
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | | | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Femke Waleboer
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Katelyn Ward
- Allen Institute for Brain Science, Seattle, WA, USA
| | - René Wilbers
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | | | - Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Pal Barzo
- Department of Neurosurgery, University of Szeged, Szeged, Hungary
| | - Amy Bernard
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Philip C de Witt Hamer
- Cancer Center Amsterdam, Brain Tumor Center, Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | | | | | - Manuel Ferreira
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | | | | | - Patrick R Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sander Idema
- Cancer Center Amsterdam, Brain Tumor Center, Department of Neurosurgery, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | | | - C Dirk Keene
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Andrew L Ko
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Gabe J Murphy
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jeffrey G Ojemann
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | - Anoop P Patel
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | | | - Daniel L Silbergeld
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
| | | | | | - Rafael Yuste
- NeuroTechnology Center, Columbia University, New York, NY, USA
| | - Idan Segev
- Edmond and Lily Safra Center for Brain Sciences and Department of Neurobiology, The Hebrew University Jerusalem, Jerusalem, Israel
| | - Christiaan P J de Kock
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Huibert D Mansvelder
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit, Amsterdam, The Netherlands
| | - Gabor Tamas
- MTA-SZTE Research Group for Cortical Microcircuits, Department of Physiology, Anatomy, and Neuroscience, University of Szeged, Szeged, Hungary
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, USA.
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA.
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39
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Heyer DB, Wilbers R, Galakhova AA, Hartsema E, Braak S, Hunt S, Verhoog MB, Muijtjens ML, Mertens EJ, Idema S, Baayen JC, de Witt Hamer P, Klein M, McGraw M, Lein ES, de Kock CPJ, Mansvelder HD, Goriounova NA. Verbal and General IQ Associate with Supragranular Layer Thickness and Cell Properties of the Left Temporal Cortex. Cereb Cortex 2021; 32:2343-2357. [PMID: 34550325 PMCID: PMC9157308 DOI: 10.1093/cercor/bhab330] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 11/27/2022] Open
Abstract
The left temporal lobe is an integral part of the language system and its cortical structure and function associate with general intelligence. However, whether cortical laminar architecture and cellular properties of this brain area relate to verbal intelligence is unknown. Here, we addressed this using histological analysis and cellular recordings of neurosurgically resected temporal cortex in combination with presurgical IQ scores. We find that subjects with higher general and verbal IQ scores have thicker left (but not right) temporal cortex (Brodmann area 21, BA21). The increased thickness is due to the selective increase in layers 2 and 3 thickness, accompanied by lower neuron densities, and larger dendrites and cell body size of pyramidal neurons in these layers. Furthermore, these neurons sustain faster action potential kinetics, which improves information processing. Our results indicate that verbal mental ability associates with selective adaptations of supragranular layers and their cellular micro-architecture and function in left, but not right temporal cortex.
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Affiliation(s)
- D B Heyer
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - R Wilbers
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - A A Galakhova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - E Hartsema
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Braak
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Hunt
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - M B Verhoog
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands.,Department of Human Biology, Neuroscience Institute, University of Cape Town, Cape Town 7925, South Africa
| | - M L Muijtjens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - E J Mertens
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - S Idema
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - J C Baayen
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - P de Witt Hamer
- Department of Neurosurgery, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - M Klein
- Department of Medical Psychology, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam 1081HZ, The Netherlands
| | - M McGraw
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - E S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - C P J de Kock
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - H D Mansvelder
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
| | - N A Goriounova
- Department of Integrative Neurophysiology, Amsterdam Neuroscience, Center for Neurogenomics and Cognitive Research (CNCR), Vrije Universiteit Amsterdam, Amsterdam 1081HV, The Netherlands
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40
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Banovac I, Sedmak D, Judaš M, Petanjek Z. Von Economo Neurons - Primate-Specific or Commonplace in the Mammalian Brain? Front Neural Circuits 2021; 15:714611. [PMID: 34539353 PMCID: PMC8440978 DOI: 10.3389/fncir.2021.714611] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/10/2021] [Indexed: 11/24/2022] Open
Abstract
The pioneering work by von Economo in 1925 on the cytoarchitectonics of the cerebral cortex revealed a specialized and unique cell type in the adult human fronto-insular (FI) and anterior cingulate cortex (ACC). In modern studies, these neurons are termed von Economo neurons (VENs). In his work, von Economo described them as stick, rod or corkscrew cells because of their extremely elongated and relatively thin cell body clearly distinguishable from common oval or spindle-shaped infragranular principal neurons. Before von Economo, in 1899 Cajal depicted the unique somato-dendritic morphology of such cells with extremely elongated soma in the FI. However, although VENs are increasingly investigated, Cajal’s observation is still mainly being neglected. On Golgi staining in humans, VENs have a thick and long basal trunk with horizontally oriented terminal branching (basilar skirt) from where the axon arises. They are clearly distinguishable from a spectrum of modified pyramidal neurons found in infragranular layers, including oval or spindle-shaped principal neurons. Spindle-shaped cells with highly elongated cell body were also observed in the ACC of great apes, but despite similarities in soma shape, their dendritic and axonal morphology has still not been described in sufficient detail. Studies identifying VENs in non-human species are predominantly done on Nissl or anti-NeuN staining. In most of these studies, the dendritic and axonal morphology of the analyzed cells was not demonstrated and many of the cells found on Nissl or anti-NeuN staining had a cell body shape characteristic for common oval or spindle-shaped cells. Here we present an extensive literature overview on VENs, which demonstrates that human VENs are specialized elongated principal cells with unique somato-dendritic morphology found abundantly in the FI and ACC of the human brain. More research is needed to properly evaluate the presence of such specialized cells in other primates and non-primate species.
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Affiliation(s)
- Ivan Banovac
- Department of Anatomy and Clinical Anatomy, University of Zagreb School of Medicine, Zagreb, Croatia.,Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Dora Sedmak
- Department of Anatomy and Clinical Anatomy, University of Zagreb School of Medicine, Zagreb, Croatia.,Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Miloš Judaš
- Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Zdravko Petanjek
- Department of Anatomy and Clinical Anatomy, University of Zagreb School of Medicine, Zagreb, Croatia.,Croatian Institute for Brain Research and Center of Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb School of Medicine, Zagreb, Croatia
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41
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Yu Q, Peng Y, Kang H, Peng Q, Ouyang M, Slinger M, Hu D, Shou H, Fang F, Huang H. Differential White Matter Maturation from Birth to 8 Years of Age. Cereb Cortex 2021; 30:2673-2689. [PMID: 31819951 PMCID: PMC7175013 DOI: 10.1093/cercor/bhz268] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 08/23/2019] [Accepted: 09/17/2019] [Indexed: 12/14/2022] Open
Abstract
Comprehensive delineation of white matter (WM) microstructural maturation from birth to childhood is critical for understanding spatiotemporally differential circuit formation. Without a relatively large sample of datasets and coverage of critical developmental periods of both infancy and early childhood, differential maturational charts across WM tracts cannot be delineated. With diffusion tensor imaging (DTI) of 118 typically developing (TD) children aged 0–8 years and 31 children with autistic spectrum disorder (ASD) aged 2–7 years, the microstructure of every major WM tract and tract group was measured with DTI metrics to delineate differential WM maturation. The exponential model of microstructural maturation of all WM was identified. The WM developmental curves were separated into fast, intermediate, and slow phases in 0–8 years with distinctive time period of each phase across the tracts. Shorter periods of the fast and intermediate phases in certain tracts, such as the commissural tracts, indicated faster earlier development. With TD WM maturational curves as the reference, higher residual variance of WM microstructure was found in children with ASD. The presented comprehensive and differential charts of TD WM microstructural maturation of all major tracts and tract groups in 0–8 years provide reference standards for biomarker detection of neuropsychiatric disorders.
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Affiliation(s)
- Qinlin Yu
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Huiying Kang
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Qinmu Peng
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Michelle Slinger
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Di Hu
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Haochang Shou
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100871, China.,Key Laboratory of Machine Perception, Peking University, Beijing 100871, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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42
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Seok JW, Bajaj S, Soltis-Vaughan B, Lerdahl A, Garvey W, Bohn A, Edwards R, Kratochvil CJ, Blair J, Hwang S. Structural atrophy of the right superior frontal gyrus in adolescents with severe irritability. Hum Brain Mapp 2021; 42:4611-4622. [PMID: 34288223 PMCID: PMC8410540 DOI: 10.1002/hbm.25571] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 05/22/2021] [Accepted: 06/10/2021] [Indexed: 12/27/2022] Open
Abstract
Severe irritability is common in youths with psychiatric disorders and results in significant dysfunction across domains (academic, social, and familial). Prior structural MRI studies in the pediatric population demonstrated that aberrations of cortical thickness (CT) and gray matter volume (GMV) in the fronto‐striatal‐temporal regions which have been associated with irritability. However, the directions of the correlations between structural alteration and irritability in the individual indices were not consistent. Thus, we aim to address this by implementing comprehensive assessments of CT, GMV, and local gyrification index (LGI) simultaneously in youths with severe levels of irritability by voxel‐based morphometry and surface‐based morphometry. One hundred and eight adolescents (46 youths with severe irritability and 62 healthy youths, average age = 14.08 years, standard deviation = 2.36) were scanned with a T1‐weighted MRI sequence. The severity of irritability was measured using the affective reactivity index. In youths with severe irritability, there was decreased CT, GMV, and LGI in the right superior frontal gyrus (SFG) compared to healthy youths, and negative correlations between these indices of the SFG and irritability. Our findings suggest that structural deficits in the SFG, potentially related to its role in inhibitory control, may be critical for the neurobiology of irritability.
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Affiliation(s)
- Ji-Woo Seok
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Sahil Bajaj
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | | | - Arica Lerdahl
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - William Garvey
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Alexandra Bohn
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Ryan Edwards
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | | | - James Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Soonjo Hwang
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
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43
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Ma L, Tian L, Hu T, Jiang T, Zuo N. Development of Individual Variability in Brain Functional Connectivity and Capability across the Adult Lifespan. Cereb Cortex 2021; 31:3925-3938. [PMID: 33822909 DOI: 10.1093/cercor/bhab059] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 01/26/2021] [Accepted: 02/07/2021] [Indexed: 11/14/2022] Open
Abstract
Individual variability exists in both brain function and behavioral performance. However, changes in individual variability in brain functional connectivity and capability across adult development and aging have not yet been clearly examined. Based on resting-state functional magnetic resonance imaging data from a large cohort of participants (543 adults, aged 18-88 years), brain functional connectivity was analyzed to characterize the spatial distribution and differences in individual variability across the adult lifespan. Results showed high individual variability in the association cortex over the adult lifespan, whereas individual variability in the primary cortex was comparably lower in the initial stage but increased with age. Individual variability was also negatively correlated with the strength/number of short-, medium-, and long-range functional connections in the brain, with long-range connections playing a more critical role in increasing global individual variability in the aging brain. More importantly, in regard to specific brain regions, individual variability in the motor cortex was significantly correlated with differences in motor capability. Overall, we identified specific patterns of individual variability in brain functional structure during the adult lifespan and demonstrated that functional variability in the brain can reflect behavioral performance. These findings advance our understanding of the underlying principles of the aging brain across the adult lifespan and suggest how to characterize degenerating behavioral capability using imaging biomarkers.
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Affiliation(s)
- Liying Ma
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Lixia Tian
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
| | - Tianyu Hu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100190, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100190, China.,Chinese Institute for Brain Research, Beijing 102206, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,Key Laboratory for Neuro-Information of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China.,Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| | - Nianming Zuo
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100190, China.,Chinese Institute for Brain Research, Beijing 102206, China
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44
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Dimitrova R, Arulkumaran S, Carney O, Chew A, Falconer S, Ciarrusta J, Wolfers T, Batalle D, Cordero-Grande L, Price AN, Teixeira RPAG, Hughes E, Egloff A, Hutter J, Makropoulos A, Robinson EC, Schuh A, Vecchiato K, Steinweg JK, Macleod R, Marquand AF, McAlonan G, Rutherford MA, Counsell SJ, Smith SM, Rueckert D, Hajnal JV, O’Muircheartaigh J, Edwards AD. Phenotyping the Preterm Brain: Characterizing Individual Deviations From Normative Volumetric Development in Two Large Infant Cohorts. Cereb Cortex 2021; 31:3665-3677. [PMID: 33822913 PMCID: PMC8258435 DOI: 10.1093/cercor/bhab039] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/15/2021] [Accepted: 02/05/2021] [Indexed: 12/20/2022] Open
Abstract
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterizing brain volumetric development in 274 term-born infants, modeling for age at scan and sex. We then compared 89 preterm infants scanned at term-equivalent age with these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalizability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, nonuniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguises a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterization of the cerebral consequences of preterm birth by profiling the individual neonatal brain.
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Affiliation(s)
- Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Judit Ciarrusta
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Thomas Wolfers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicacion, Universidad Politecnica de Madrid and CIBER-BBN, Madrid 28040, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Rui P A G Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Antonios Makropoulos
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Emma C Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Johannes K Steinweg
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Russell Macleod
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen 6525EN, the Netherlands
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
- South London and Maudsley NHS Foundation Trust, London SE5 8AZ, UK
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London SW7 2AZ, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
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Jalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, Uhlhaas PJ, Takahashi T, Sugranyes G, Kwak YB, Mathalon DH, Katagiri N, Hooker CI, Smigielski L, Colibazzi T, Via E, Tang J, Koike S, Rasser PE, Michel C, Lebedeva I, Hegelstad WTV, de la Fuente-Sandoval C, Waltz JA, Mizrahi R, Corcoran CM, Resch F, Tamnes CK, Haas SS, Lemmers-Jansen ILJ, Agartz I, Allen P, Amminger GP, Andreassen OA, Atkinson K, Bachman P, Baeza I, Baldwin H, Bartholomeusz CF, Borgwardt S, Catalano S, Chee MWL, Chen X, Cho KIK, Cooper RE, Cropley VL, Dolz M, Ebdrup BH, Fortea A, Glenthøj LB, Glenthøj BY, de Haan L, Hamilton HK, Harris MA, Haut KM, He Y, Heekeren K, Heinz A, Hubl D, Hwang WJ, Kaess M, Kasai K, Kim M, Kindler J, Klaunig MJ, Koppel A, Kristensen TD, Kwon JS, Lawrie SM, Lee J, León-Ortiz P, Lin A, Loewy RL, Ma X, McGorry P, McGuire P, Mizuno M, Møller P, Moncada-Habib T, Muñoz-Samons D, Nelson B, Nemoto T, Nordentoft M, Omelchenko MA, Oppedal K, Ouyang L, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Roach BJ, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Schiffman J, Schlagenhauf F, Schmidt A, Sørensen ME, Suzuki M, Theodoridou A, Tomyshev AS, Tor J, Værnes TG, Velakoulis D, Venegoni GD, Vinogradov S, Wenneberg C, Westlye LT, Yamasue H, Yuan L, Yung AR, van Amelsvoort TAMJ, Turner JA, van Erp TGM, Thompson PM, Hernaus D. Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group Mega-analysis. JAMA Psychiatry 2021; 78:753-766. [PMID: 33950164 PMCID: PMC8100913 DOI: 10.1001/jamapsychiatry.2021.0638] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/04/2021] [Indexed: 01/10/2023]
Abstract
Importance The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. Objective To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). Design, Setting, and Participants In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. Main Outcomes and Measures Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). Results Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001). Conclusions and Relevance This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.
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Affiliation(s)
- Maria Jalbrzikowski
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Rebecca A Hayes
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Stephen J Wood
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Dorte Nordholm
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Juan H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Paolo Fusar-Poli
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- EPIC Lab, Department of Psychosis Studies, King's College London, London, United Kingdom
| | - Peter J Uhlhaas
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
| | - Tsutomu Takahashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Gisela Sugranyes
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Naoyuki Katagiri
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Christine I Hooker
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
| | - Lukasz Smigielski
- Department of Child and Adolescent Psychiatry, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Tiziano Colibazzi
- Department of Psychiatry, Columbia University, New York, New York
- New York State Psychiatric Institute, New York
| | - Esther Via
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Medical Neurobiology of Zhejiang Province, School of Medicine, Zhejiang University Hangzhou, Hangzhou, China
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, Tokyo, Japan
| | - Paul E Rasser
- Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, Australia
- Priority Research Centre for Stroke and Brain Injury, The University of Newcastle, Newcastle, Australia
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Wenche Ten Velden Hegelstad
- Faculty of Social Sciences, University of Stavanger, Stavanger, Norway
- TIPS Centre for Clinical Research in Psychosis, Stavanger University Hospital, Stavanger, Norway
| | | | - James A Waltz
- Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore
| | - Romina Mizrahi
- Douglas Research Center, Montreal, Quebec, Canada
- McGill University, Department of Psychiatry, Montreal, Quebec, Canada
| | - Cheryl M Corcoran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Mental Illness Research, Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, New York, New York
| | - Franz Resch
- Clinic for Child and Adolescent Psychiatry, University Hospital of Heidelberg, Heidelberg, Germany
| | - Christian K Tamnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Imke L J Lemmers-Jansen
- Faculty of Behavioural and Movement Sciences, Department of Clinical, Neuro and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ingrid Agartz
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Paul Allen
- Department of Psychology, University of Roehampton, London, United Kingdom
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - G Paul Amminger
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kimberley Atkinson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Bachman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Inmaculada Baeza
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, 2017SGR-881, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Universitat de Barcelona, Barcelona, Spain
| | - Helen Baldwin
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom
| | - Cali F Bartholomeusz
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Stefan Borgwardt
- Department of Psychiatry, University of Basel, Basel, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Sabrina Catalano
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michael W L Chee
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Xiaogang Chen
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Rebecca E Cooper
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Montserrat Dolz
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Bjørn H Ebdrup
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Adriana Fortea
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clinic Barcelona, Fundació Clínic Recerca Biomèdica, Universitat de Barcelona, Barcelona, Spain
| | - Louise Birkedal Glenthøj
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Birte Y Glenthøj
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lieuwe de Haan
- Department of Psychiatry, Amsterdam University Medical Centre, Amsterdam, the Netherlands
- Arkin, Amsterdam, the Netherlands
| | - Holly K Hamilton
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Mathew A Harris
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kristen M Haut
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, Illinois
| | - Ying He
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Karsten Heekeren
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy I, LVR-Hospital Cologne, Cologne, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Daniela Hubl
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Wu Jeong Hwang
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Department of Child and Adolescent Psychiatry, Center of Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany
| | - Kiyoto Kasai
- The University of Tokyo Institute for Diversity and Adaptation of Human Mind, Tokyo, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence at The University of Tokyo Institutes for Advanced Study, The University of Tokyo, Tokyo, Japan
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Mallory J Klaunig
- Department of Psychology, University of Maryland, Baltimore County, Baltimore
| | - Alex Koppel
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario, Canada
| | - Tina D Kristensen
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Jimmy Lee
- Department of Psychosis, Institute of Mental Health, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Pablo León-Ortiz
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Ashleigh Lin
- Telethon Kids Institute, The University of Western Australia, Perth, Australia
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
| | - Xiaoqian Ma
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Patrick McGorry
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Masafumi Mizuno
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Paul Møller
- Department for Mental Health Research and Development, Division of Mental Health and Addiction, Vestre Viken Hospital Trust, Lier, Norway
| | - Tomas Moncada-Habib
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Daniel Muñoz-Samons
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Barnaby Nelson
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
| | - Takahiro Nemoto
- Department of Neuropsychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Merete Nordentoft
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | | | - Ketil Oppedal
- Stavanger Medical Imaging Laboratory, Department of Radiology, Stavanger University Hospital, Stavanger, Norway
| | - Lijun Ouyang
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia
| | - Jose C Pariente
- Magnetic Resonance Imaging Core Facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Jayachandra M Raghava
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
- Department of Clinical Physiology, Nuclear Medicine and PET, Functional Imaging Unit, University of Copenhagen, Glostrup, Denmark
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Brian J Roach
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Jan I Røssberg
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Wulf Rössler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Dean F Salisbury
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Ulrich Schall
- Priority Centre for Brain and Mental Health Research, The University of Newcastle, Newcastle, Australia
- Priority Research Centre Grow Up Well, The University of Newcastle, Newcastle, Australia
| | - Jason Schiffman
- Department of Psychology, University of Maryland, Baltimore County, Baltimore
- Department of Psychological Science, University of California, Irvine
| | - Florian Schlagenhauf
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Berlin, Germany
| | - Andre Schmidt
- Department of Psychiatry, University of Basel, Basel, Switzerland
| | - Mikkel E Sørensen
- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Michio Suzuki
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan
- Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Anastasia Theodoridou
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Jordina Tor
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Tor G Værnes
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Early Intervention in Psychosis Advisory Unit for South-East Norway, TIPS Sør-Øst, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Dennis Velakoulis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Neuropsychiatry, The Royal Melbourne Hospital, Melbourne, Australia
| | - Gloria D Venegoni
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
| | - Christina Wenneberg
- Copenhagen Research Center for Mental Health, Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Hidenori Yamasue
- Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu City, Japan
| | - Liu Yuan
- National Clinical Research Center for Mental Disorders and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Alison R Yung
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
- Orygen, Melbourne, Australia
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Thérèse A M J van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
| | | | - Theo G M van Erp
- Center for the Neurobiology of Learning and Memory, Irvine, California
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles
| | - Dennis Hernaus
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
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Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
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Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
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47
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Buffet-Bataillon S, Bellanger A, Boudry G, Gangneux JP, Yverneau M, Beuchée A, Blat S, Le Huërou-Luron I. New Insights Into Microbiota Modulation-Based Nutritional Interventions for Neurodevelopmental Outcomes in Preterm Infants. Front Microbiol 2021; 12:676622. [PMID: 34177860 PMCID: PMC8232935 DOI: 10.3389/fmicb.2021.676622] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 05/12/2021] [Indexed: 12/19/2022] Open
Abstract
Gut microbiota and the central nervous system have parallel developmental windows during pre and post-natal life. Increasing evidences suggest that intestinal dysbiosis in preterm infants predisposes the neonate to adverse neurological outcomes later in life. Understanding the link between gut microbiota colonization and brain development to tailor therapies aimed at optimizing initial colonization and microbiota development are promising strategies to warrant adequate brain development and enhance neurological outcomes in preterm infants. Breast-feeding has been associated with both adequate cognitive development and healthy microbiota in preterms. Infant formula are industrially produced substitutes for infant nutrition that do not completely recapitulate breast-feeding benefices and could be largely improved by the understanding of the role of breast milk components upon gut microbiota. In this review, we will first discuss the nutritional and bioactive component information on breast milk composition and its contribution to the assembly of the neonatal gut microbiota in preterms. We will then discuss the emerging pathways connecting the gut microbiota and brain development. Finally, we will discuss the promising microbiota modulation-based nutritional interventions (including probiotic and prebiotic supplementation of infant formula and maternal nutrition) for improving neurodevelopmental outcomes.
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Affiliation(s)
- Sylvie Buffet-Bataillon
- Institut NuMeCan, INRAE, INSERM, Univ Rennes, Saint-Gilles, France
- Department of Clinical Microbiology, CHU Rennes, Rennes, France
| | - Amandine Bellanger
- Institut NuMeCan, INRAE, INSERM, Univ Rennes, Saint-Gilles, France
- Department of Pediatrics-Neonatology, CHU Rennes, Rennes, France
| | - Gaelle Boudry
- Institut NuMeCan, INRAE, INSERM, Univ Rennes, Saint-Gilles, France
| | | | | | - Alain Beuchée
- Department of Pediatrics-Neonatology, Univ Rennes, CHU Rennes, LTSI-UMR 1099, Rennes, France
| | - Sophie Blat
- Institut NuMeCan, INRAE, INSERM, Univ Rennes, Saint-Gilles, France
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48
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Fox M, Lee SM, Wiley KS, Lagishetty V, Sandman CA, Jacobs JP, Glynn LM. Development of the infant gut microbiome predicts temperament across the first year of life. Dev Psychopathol 2021; 34:1-12. [PMID: 34108055 PMCID: PMC9463039 DOI: 10.1017/s0954579421000456] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Perturbations to the gut microbiome are implicated in altered neurodevelopmental trajectories that may shape life span risk for emotion dysregulation and affective disorders. However, the sensitive periods during which the microbiome may influence neurodevelopment remain understudied. We investigated relationships between gut microbiome composition across infancy and temperament at 12 months of age. In 67 infants, we examined if gut microbiome composition assessed at 1-3 weeks, 2, 6, and 12 months of age was associated with temperament at age 12 months. Stool samples were sequenced using the 16S Illumina MiSeq platform. Temperament was assessed using the Infant Behavior Questionnaire-Revised (IBQ-R). Beta diversity at age 1-3 weeks was associated with surgency/extraversion at age 12 months. Bifidobacterium and Lachnospiraceae abundance at 1-3 weeks of age was positively associated with surgency/extraversion at age 12 months. Klebsiella abundance at 1-3 weeks was negatively associated with surgency/extraversion at 12 months. Concurrent composition was associated with negative affectivity at 12 months, including a positive association with Ruminococcus-1 and a negative association with Lactobacillus. Our findings support a relationship between gut microbiome composition and infant temperament. While exploratory due to the small sample size, these results point to early and late infancy as sensitive periods during which the gut microbiome may exert effects on neurodevelopment.
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Affiliation(s)
- Molly Fox
- Department of Anthropology, UCLA, Los Angeles, CA, USA
- Department of Psychiatry & Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
| | - S. Melanie Lee
- Department of Psychiatry & Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Kyle S. Wiley
- Department of Anthropology, UCLA, Los Angeles, CA, USA
- Department of Psychiatry & Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
| | - Venu Lagishetty
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- The Vatche and Tamar Manoukian Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- UCLA Microbiome Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Curt A. Sandman
- Department of Psychiatry and Human Behavior, UC Irvine, Irvine, CA, USA
| | - Jonathan P. Jacobs
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- The Vatche and Tamar Manoukian Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- UCLA Microbiome Center, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Laura M. Glynn
- Department of Psychology, Chapman University, Orange, CA, USA
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49
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Khalil R, Farhat A, Dłotko P. Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis. Front Comput Neurosci 2021; 15:667696. [PMID: 34135746 PMCID: PMC8200563 DOI: 10.3389/fncom.2021.667696] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/05/2021] [Indexed: 11/18/2022] Open
Abstract
Neuronal morphology is characterized by salient features such as complex axonal and dendritic arbors. In the mammalian brain, variations in dendritic morphology among cell classes, brain regions, and animal species are thought to underlie known differences in neuronal function. In this work, we obtained a large dataset from http://neuromorpho.org/ comprising layer III pyramidal cells in different cortical areas of the ventral visual pathway (V1, V2, V4, TEO, and TE) of the macaque monkey at different developmental stages. We performed an in depth quantitative analysis of pyramidal cell morphology throughout development in an effort to determine which aspects mature early in development and which features require a protracted period of maturation. We were also interested in establishing if developmental changes in morphological features occur simultaneously or hierarchically in multiple visual cortical areas. We addressed these questions by performing principal component analysis (PCA) and hierarchical clustering analysis on relevant morphological features. Our analysis indicates that the maturation of pyramidal cell morphology is largely based on early development of topological features in most visual cortical areas. Moreover, the maturation of pyramidal cell morphology in V1, V2, V4, TEO, and TE is characterized by unique developmental trajectories.
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Affiliation(s)
- Reem Khalil
- Biology, Chemistry, and Environmental Sciences Department, American University of Sharjah, Sharjah, United Arab Emirates
| | - Ahmad Farhat
- Dioscuri Centre in Topological Data Analysis, Mathematical Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Paweł Dłotko
- Dioscuri Centre in Topological Data Analysis, Mathematical Institute, Polish Academy of Sciences, Warsaw, Poland
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50
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Vijayakumar N, Ball G, Seal ML, Mundy L, Whittle S, Silk T. The development of structural covariance networks during the transition from childhood to adolescence. Sci Rep 2021; 11:9451. [PMID: 33947919 PMCID: PMC8097025 DOI: 10.1038/s41598-021-88918-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 04/16/2021] [Indexed: 12/16/2022] Open
Abstract
Structural covariance conceptualizes how morphologic properties of brain regions are related to one another (across individuals). It can provide unique information to cortical structure (e.g., thickness) about the development of functionally meaningful networks. The current study investigated how structural covariance networks develop during the transition from childhood to adolescence, a period characterized by marked structural re-organization. Participants (N = 192; scans = 366) completed MRI assessments between 8.5 and 14.5 years of age. A sliding window approach was used to create “age-bins”, and structural covariance networks (based on cortical thickness) were created for each bin. Next, generalized additive models were used to characterize trajectories of age-related changes in network properties. Results revealed nonlinear trajectories with “peaks” in mean correlation and global density that are suggestive of a period of convergence in anatomical properties across the cortex during early adolescence, prior to regional specialization. “Hub” regions in sensorimotor cortices were present by late childhood, but the extent and strength of association cortices as “hubs” increased into mid-adolescence. Moreover, these regional changes were found to be related to rates of thinning across the cortex. In the context of neurocognitive networks, the frontoparietal, default mode, and attention systems exhibited age-related increases in within-network and between-network covariance. These regional and modular developmental patterns are consistent with continued refinement of socioemotional and other complex executive functions that are supported by higher-order cognitive networks during early adolescence.
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Affiliation(s)
- Nandita Vijayakumar
- School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia.
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, 3052, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, 3053, Australia
| | - Marc L Seal
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, 3052, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, 3053, Australia
| | - Lisa Mundy
- Department of Paediatrics, The University of Melbourne, Melbourne, 3053, Australia.,Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, 3052, Australia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, 3053, Australia
| | - Tim Silk
- School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia.,Developmental Imaging, Murdoch Children's Research Institute, Parkville, 3052, Australia.,Department of Paediatrics, The University of Melbourne, Melbourne, 3053, Australia
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