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Manns M, Juckel G, Freund N. The Balance in the Head: How Developmental Factors Explain Relationships Between Brain Asymmetries and Mental Diseases. Brain Sci 2025; 15:169. [PMID: 40002502 PMCID: PMC11852682 DOI: 10.3390/brainsci15020169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2024] [Revised: 01/29/2025] [Accepted: 02/07/2025] [Indexed: 02/27/2025] Open
Abstract
Cerebral lateralisation is a core organising principle of the brain that is characterised by a complex pattern of hemispheric specialisations and interhemispheric interactions. In various mental disorders, functional and/or structural hemispheric asymmetries are changed compared to healthy controls, and these alterations may contribute to the primary symptoms and cognitive impairments of a specific disorder. Since multiple genetic and epigenetic factors influence both the pathogenesis of mental illness and the development of brain asymmetries, it is likely that the neural developmental pathways overlap or are even causally intertwined, although the timing, magnitude, and direction of interactions may vary depending on the specific disorder. However, the underlying developmental steps and neuronal mechanisms are still unclear. In this review article, we briefly summarise what we know about structural, functional, and developmental relationships and outline hypothetical connections, which could be investigated in appropriate animal models. Altered cerebral asymmetries may causally contribute to the development of the structural and/or functional features of a disorder, as neural mechanisms that trigger neuropathogenesis are embedded in the asymmetrical organisation of the developing brain. Therefore, the occurrence and severity of impairments in neural processing and cognition probably cannot be understood independently of the development of the lateralised organisation of intra- and interhemispheric neuronal networks. Conversely, impaired cellular processes can also hinder favourable asymmetry development and lead to cognitive deficits in particular.
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Affiliation(s)
- Martina Manns
- Research Division Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44809 Bochum, Germany;
| | - Georg Juckel
- Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44791 Bochum, Germany;
| | - Nadja Freund
- Research Division Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44809 Bochum, Germany;
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2
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Parlatini V, Radua J, Robertsson N, Lintas A, Atuk E, dell'Acqua F, Thiebaut de Schotten M, Murphy D. Asymmetry of attentive networks contributes to adult Attention-deficit/hyperactivity disorder (ADHD) pathophysiology. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01927-4. [PMID: 39487888 DOI: 10.1007/s00406-024-01927-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 10/19/2024] [Indexed: 11/04/2024]
Abstract
Diffusion imaging studies in Attention-deficit/hyperactivity disorder (ADHD) have revealed alterations in anatomical brain connections, such as the fronto-parietal connection known as superior longitudinal fasciculus (SLF). Studies in neurotypical adults have shown that the three SLF branches (SLF I, II, III) support distinct brain functions, such as attention and inhibition; and that their pattern of lateralization is associated with attention performance. However, most studies in ADHD have investigated the SLF as a single bundle and in children; thus, the potential contribution of the lateralization of the SLF branches to adult ADHD pathophysiology remains to be elucidated. We used diffusion-weighted spherical deconvolution tractography to dissect the SLF branches in 60 adults with ADHD (including 26 responders and 34 non-responders to methylphenidate, MPH) and 20 controls. Volume and hindrance modulated orientational anisotropy (HMOA), which respectively reflect white matter macro- and microstructure, were extracted to calculate the corresponding lateralization indices. We tested whether neurotypical controls differed from adults with ADHD, and from treatment response groups in sensitivity analyses; and investigated associations with clinico-neuropsychological profiles. All the three SLF branches were lateralized in adults with ADHD, but not in controls. The lateralization of the SLF I HMOA was associated with performance at the line bisection, not that of the SLF II volume as previously reported in controls. Further, an increased left-lateralization of the SLF I HMOA was associated with higher hyperactivity levels in the ADHD group. Thus, an altered asymmetry of the SLF, perhaps especially of the dorsal branch, may contribute to adult ADHD pathophysiology.
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Affiliation(s)
- Valeria Parlatini
- Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.
- Centre for Innovation in Mental Health, School of Psychology, University of Southampton, Southampton, UK.
- Solent NHS Trust, Southampton, UK.
| | - Joaquim Radua
- Imaging of Mood and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS), Campus Casanova, Casanova, 143, 08036, Barcelona, Spain
| | - Naianna Robertsson
- Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Alessandra Lintas
- Neuroheuristic Research Group, HEC Lausanne, University of Lausanne, UNIL-Chamberonne, 1015, Lausanne, Quartier, Switzerland
| | - Emel Atuk
- Sussex Partnership NHS Foundation Trust, Dartford, DA1 2EN, UK
| | - Flavio dell'Acqua
- Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Institute of Psychiatry, NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Foundation Trust and King's College London, London, SE5 8AF, UK
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Group, Sorbonne Universities, Paris, France
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Declan Murphy
- Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
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3
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Bogdańska-Chomczyk E, Wojtacha P, Tsai ML, Huang ACW, Kozłowska A. Age-related changes in the architecture and biochemical markers levels in motor-related cortical areas of SHR rats-an ADHD animal model. Front Mol Neurosci 2024; 17:1414457. [PMID: 39246601 PMCID: PMC11378348 DOI: 10.3389/fnmol.2024.1414457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Accepted: 06/25/2024] [Indexed: 09/10/2024] Open
Abstract
Introduction Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder whose exact pathophysiology has not been fully understood yet. Numerous studies have suggested disruptions in the cellular architecture and neuronal activity within brain structures of individuals with ADHD, accompanied by imbalances in the immune system, oxidative stress, and metabolism. Methods This study aims to assess two functionally and histologically distinct brain areas involved in motor control and coordination: the motor cortex (MC) and prefrontal cortex (PFC). Namely, the morphometric analysis of the MC throughout the developmental stages of Spontaneously Hypertensive Rats (SHRs) and Wistar Kyoto Rats (WKYs). Additionally, the study aimed to investigate the levels and activities of specific immune, oxidative stress, and metabolic markers in the PFC of juvenile and maturing SHRs in comparison to WKYs. Results The most significant MC volume reductions occurred in juvenile SHRs, accompanied by alterations in neuronal density in these brain areas compared to WKYs. Furthermore, juvenile SHRs exhibit heightened levels and activity of various markers, including interleukin-1α (IL-1α), IL-6, serine/threonine-protein mammalian target of rapamycin, RAC-alpha serine/threonine-protein kinase, glucocorticoid receptor β, malondialdehyde, sulfhydryl groups, superoxide dismutase, peroxidase, glutathione reductase, glutathione S-transferase, glucose, fructosamine, iron, lactic acid, alanine, aspartate transaminase, and lactate dehydrogenase. Discussion Significant changes in the MC morphometry and elevated levels of inflammatory, oxidative, and metabolic markers in PFC might be associated with disrupted brain development and maturation in ADHD.
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Affiliation(s)
- E Bogdańska-Chomczyk
- Department of Human Physiology and Pathophysiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - P Wojtacha
- Department of Psychology and Sociology of Health and Public Health, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
| | - M L Tsai
- Department of Biomechatronic Engineering, National Ilan University, Yilan, Taiwan
| | - A C W Huang
- Department of Psychology, Fo Guang University, Yilan, Taiwan
| | - A Kozłowska
- Department of Human Physiology and Pathophysiology, School of Medicine, Collegium Medicum, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
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4
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Ocklenburg S, Mundorf A, Gerrits R, Karlsson EM, Papadatou-Pastou M, Vingerhoets G. Clinical implications of brain asymmetries. Nat Rev Neurol 2024; 20:383-394. [PMID: 38783057 DOI: 10.1038/s41582-024-00974-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/08/2024] [Indexed: 05/25/2024]
Abstract
No two human brains are alike, and with the rise of precision medicine in neurology, we are seeing an increased emphasis on understanding the individual variability in brain structure and function that renders every brain unique. Functional and structural brain asymmetries are a fundamental principle of brain organization, and recent research suggests substantial individual variability in these asymmetries that needs to be considered in clinical practice. In this Review, we provide an overview of brain asymmetries, variations in such asymmetries and their relevance in the clinical context. We review recent findings on brain asymmetries in neuropsychiatric and neurodevelopmental disorders, as well as in specific learning disabilities, with an emphasis on large-scale database studies and meta-analyses. We also highlight the relevance of asymmetries for disease symptom onset in neurodegenerative diseases and their implications for lateralized treatments, including brain stimulation. We conclude that alterations in brain asymmetry are not sufficiently specific to act as diagnostic biomarkers but can serve as meaningful symptom or treatment response biomarkers in certain contexts. On the basis of these insights, we provide several recommendations for neurological clinical practice.
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Affiliation(s)
- Sebastian Ocklenburg
- Department of Psychology, MSH Medical School Hamburg, Hamburg, Germany.
- ICAN Institute for Cognitive and Affective Neuroscience, MSH Medical School Hamburg, Hamburg, Germany.
- Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.
| | - Annakarina Mundorf
- ISM Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
- Division of Cognitive Neuroscience, Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robin Gerrits
- Department of Experimental-Clinical and Health Psychology, Ghent University, Ghent, Belgium
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Emma M Karlsson
- Department of Experimental-Clinical and Health Psychology, Ghent University, Ghent, Belgium
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Marietta Papadatou-Pastou
- National and Kapodistrian University of Athens, Athens, Greece
- Biomedical Research Foundation, Academy of Athens, Athens, Greece
| | - Guy Vingerhoets
- Department of Experimental-Clinical and Health Psychology, Ghent University, Ghent, Belgium
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
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5
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Abdolmaleky HM, Nohesara S, Thiagalingam S. Epigenome Defines Aberrant Brain Laterality in Major Mental Illnesses. Brain Sci 2024; 14:261. [PMID: 38539649 PMCID: PMC10968810 DOI: 10.3390/brainsci14030261] [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: 01/30/2024] [Revised: 03/01/2024] [Accepted: 03/05/2024] [Indexed: 11/03/2024] Open
Abstract
Brain-hemisphere asymmetry/laterality is a well-conserved biological feature of normal brain development. Several lines of evidence, confirmed by the meta-analysis of different studies, support the disruption of brain laterality in mental illnesses such as schizophrenia (SCZ), bipolar disorder (BD), attention-deficit/hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), and autism. Furthermore, as abnormal brain lateralization in the planum temporale (a critical structure in auditory language processing) has been reported in patients with SCZ, it has been considered a major cause for the onset of auditory verbal hallucinations. Interestingly, the peripheral counterparts of abnormal brain laterality in mental illness, particularly in SCZ, have also been shown in several structures of the human body. For instance, the fingerprints of patients with SCZ exhibit aberrant asymmetry, and while their hair whorl rotation is random, 95% of the general population exhibit a clockwise rotation. In this work, we present a comprehensive literature review of brain laterality disturbances in mental illnesses such as SCZ, BD, ADHD, and OCD, followed by a systematic review of the epigenetic factors that may be involved in the disruption of brain lateralization in mental health disorders. We will conclude with a discussion on whether existing non-pharmacological therapies such as rTMS and ECT may be used to influence the altered functional asymmetry of the right and left hemispheres of the brain, along with their epigenetic and corresponding gene-expression patterns.
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Affiliation(s)
- Hamid Mostafavi Abdolmaleky
- Department of Medicine (Biomedical Genetics), Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Surgery, Nutrition/Metabolism Laboratory, BIDMC, Harvard Medical School, Boston, MA 02215, USA
| | - Shabnam Nohesara
- Department of Medicine (Biomedical Genetics), Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, USA;
| | - Sam Thiagalingam
- Department of Medicine (Biomedical Genetics), Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Pathology & Laboratory Medicine, Boston University Chobanian and Avedisian School of Medicine, Boston, MA 02118, USA
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6
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Luo N, Luo X, Zheng S, Yao D, Zhao M, Cui Y, Zhu Y, Calhoun VD, Sun L, Sui J. Aberrant brain dynamics and spectral power in children with ADHD and its subtypes. Eur Child Adolesc Psychiatry 2023; 32:2223-2234. [PMID: 35996018 PMCID: PMC10576687 DOI: 10.1007/s00787-022-02068-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 08/08/2022] [Indexed: 12/16/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants (54 ADHD-Is and 53 ADHD-Cs and 54 healthy controls). Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (p = 1.46e-3), while the duration and contribution of frontal-parietal network (state D) were increased (p = 1.57e-3; p = 1.26e-4). Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I (p = 9.35e-5; p = 1.51e-8), suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD.
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Affiliation(s)
- Na Luo
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiangsheng Luo
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Suli Zheng
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Dongren Yao
- Massachusetts Eye and Ear Infirmary, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02114, USA
| | - Min Zhao
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yue Cui
- Institute of Automation, Chinese Academy of Sciences, Brainnetome Center and National Laboratory of Pattern Recognition, Beijing, 100190, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yu Zhu
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA
| | - Li Sun
- Peking University Sixth Hospital and, Peking University Institute of Mental Health, Beijing, 100191, China.
- NHC Key Laboratory of Mental Health (Peking University) and National Clinical Research Center for Mental Disorders, (Peking University Sixth Hospital), Beijing, 100191, China.
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA.
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
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7
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Parlatini V, Itahashi T, Lee Y, Liu S, Nguyen TT, Aoki YY, Forkel SJ, Catani M, Rubia K, Zhou JH, Murphy DG, Cortese S. White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis. Mol Psychiatry 2023; 28:4098-4123. [PMID: 37479785 PMCID: PMC10827669 DOI: 10.1038/s41380-023-02173-1] [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: 02/26/2023] [Revised: 06/23/2023] [Accepted: 06/28/2023] [Indexed: 07/23/2023]
Abstract
Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.
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Affiliation(s)
- Valeria Parlatini
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK.
| | - Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, 6-11-11 Kita-karasuyama, Setagaya-ku, Tokyo, Japan
| | - Yeji Lee
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Siwei Liu
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Thuan T Nguyen
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
| | - Yuta Y Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, 6-11-11 Kita-karasuyama, Setagaya-ku, Tokyo, Japan
- Department of Psychiatry, Aoki Clinic, Tokyo, Japan
| | - Stephanie J Forkel
- Donders Centre for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Marco Catani
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - Juan H Zhou
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Declan G Murphy
- Sackler Institute of Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, SE5 8AF, London, UK
| | - Samuele Cortese
- Centre for Innovation in Mental Health, School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
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8
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Sharpley CF, Bitsika V, Shadli SM, Jesulola E, Agnew LL. EEG frontal lobe asymmetry as a function of sex, depression severity, and depression subtype. Behav Brain Res 2023; 443:114354. [PMID: 36801473 DOI: 10.1016/j.bbr.2023.114354] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/29/2023] [Accepted: 02/16/2023] [Indexed: 02/19/2023]
Abstract
To investigate possible contributors to the inconsistent association between frontal lobe asymmetry (FLA) and depression, EEG data were collected across five frontal sites, and examined for their associations with four subtypes of depression (Depressed mood, Anhedonia, Cognitive depression, Somatic depression). One hundred community volunteers (54 males, 46 females) aged at least 18 yr completed standardized scales for depression and anxiety, and gave EEG data under Eyes Open and Eyes Closed conditions. Results indicated that, although there was no significant correlation between the differences in EEG power across each of the five pairs of frontal sites and total depression scores, there were several meaningful correlations (accounting for at least 10% of the variance) between specific EEG site differences data and each of the four depression subtypes. There were also different patterns of association between FLA and the depression subtypes according to sex, and total depression severity. These findings help to explain the apparent inconsistency in previous FLA-depression results, and argue for a more nuanced approach to this hypothesis.
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Affiliation(s)
- Christopher F Sharpley
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia.
| | - Vicki Bitsika
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
| | - Shabah M Shadli
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
| | - Emmanuel Jesulola
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia; Emmanuel Jesulola is now at Department of Neurosurgery, The Alfred Hospital, Melbourne, Australia
| | - Linda L Agnew
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia; Linda Agnew is now at Griffith University, Qld, Australia
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9
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Ohnishi T, Toda W, Itagaki S, Sato A, Matsumoto J, Ito H, Ishii S, Miura I, Yabe H. Disrupted structural connectivity and less efficient network system in patients with the treatment-naive adult attention-deficit/hyperactivity disorder. Front Psychiatry 2023; 14:1093522. [PMID: 37009101 PMCID: PMC10061975 DOI: 10.3389/fpsyt.2023.1093522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 02/17/2023] [Indexed: 03/18/2023] Open
Abstract
Introduction Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder whose primary symptoms are hyperactivity, impulsivity, and inattention. Historically, ADHD was recognized as a disease of childhood and adolescence. However, many patients are known to have persistent symptoms into adulthood. Many researchers consider the neuropathology of ADHD to be based on abnormalities in multiple parallel and intersecting pathways rather than a single anatomical area, but such alterations remain to be clarified. Methods Using diffusion tensor imaging, we investigated differences in the global network metrics estimated by graph theory and the degree of connectivity between adjacent voxels within a white matter (WM) fascicle defined by the density of the diffusing spins (connectometry) between 19 drug-naive Japanese patients with adult ADHD and 19 matched healthy controls (HCs). In adult patients with ADHD, we examined the relationships between the symptomatology of ADHD and global network metrics and WM abnormalities. Results Compared with HCs, adult patients with ADHD showed a reduced rich-club coefficient and decreased connectivity in widely distributed WMs such as the corpus callosum, the forceps, and the cingulum bundle. Correlational analyses demonstrated that the general severity of ADHD symptoms was associated with several global network metrics, such as lower global efficiency, clustering coefficient, small worldness, and longer characteristic path length. The connectometry revealed that the severity of hyperactive/impulsive symptoms was associated with overconnectivity in the corticostriatal, corticospinal, and corticopontine tracts, the inferior fronto-occipital fasciculus, and the extreme capsule but dysconnectivity in the cerebellum. The severity of inattentive symptoms was associated with dysconnectivity in the intracerebellar circuit and some other fibers. Conclusion The results of the present study indicated that patients with treatment-naive adult ADHD showed disrupted structural connectivity, which contributes to less efficient information transfer in the ADHD brain and pathophysiology of ADHD. Trial registration UMIN Clinical Trials Registry (UMIN-CTR) UMIN000025183, Registered: 5 January 2017.
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Affiliation(s)
- Takashi Ohnishi
- Medical Affairs Division, Janssen Pharmaceutical K.K., Tokyo, Japan
| | - Wataru Toda
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
| | - Shuntaro Itagaki
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
| | - Aya Sato
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
| | - Junya Matsumoto
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Hiroshi Ito
- Department of Radiology and Nuclear Medicine, Fukushima Medical University, Fukushima, Japan
| | - Shiro Ishii
- Department of Radiology and Nuclear Medicine, Fukushima Medical University, Fukushima, Japan
| | - Itaru Miura
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
| | - Hirooki Yabe
- Department of Neuropsychiatry, Fukushima Medical University, Fukushima, Japan
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10
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Wang B, Guo M, Pan T, Li Z, Li Y, Xiang J, Cui X, Niu Y, Yang J, Wu J, Liu M, Li D. Altered higher-order coupling between brain structure and function with embedded vector representations of connectomes in schizophrenia. Cereb Cortex 2022; 33:5447-5456. [PMID: 36482789 DOI: 10.1093/cercor/bhac432] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/05/2022] [Accepted: 10/07/2022] [Indexed: 12/13/2022] Open
Abstract
Abstract
It has been shown that the functional dependency of the brain exists in both direct and indirect regional relationships. Therefore, it is necessary to map higher-order coupling in brain structure and function to understand brain dynamic. However, how to quantify connections between not directly regions remains unknown to schizophrenia. The word2vec is a common algorithm through create embeddings of words to solve these problems. We apply the node2vec embedding representation to characterize features on each node, their pairwise relationship can give rise to correspondence relationships between brain regions. Then we adopt pearson correlation to quantify the higher-order coupling between structure and function in normal controls and schizophrenia. In addition, we construct direct and indirect connections to quantify the coupling between their respective functional connections. The results showed that higher-order coupling is significantly higher in schizophrenia. Importantly, the anomalous cause of coupling mainly focus on indirect structural connections. The indirect structural connections play an essential role in functional connectivity–structural connectivity (SC–FC) coupling. The similarity between embedded representations capture more subtle network underlying information, our research provides new perspectives for understanding SC–FC coupling. A strong indication that the structural backbone of the brain has an intimate influence on the resting-state functional.
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Affiliation(s)
- Bin Wang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Min Guo
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Tingting Pan
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Zhifeng Li
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Ying Li
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Xiaohong Cui
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
| | - Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, 3-1-1 Tsushimanaka, kita-ku, Okayama-shi, Okayama, 700-8530, Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, 3-1-1 Tsushimanaka, kita-ku, Okayama-shi, Okayama, 700-8530, Japan
| | - Miaomiao Liu
- School of Psychology, Shenzhen University, No. 3688, Nanhai Avenue, Nanshan District, Shenzhen, 518061, China
| | - Dandan Li
- College of Information and Computer, Taiyuan University of Technology, No. 79, Yingze West Street, Taiyuan, Shanxi, 030024, China
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11
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He W, Liu W, Mao M, Cui X, Yan T, Xiang J, Wang B, Li D. Reduced Modular Segregation of White Matter Brain Networks in Attention Deficit Hyperactivity Disorder. J Atten Disord 2022; 26:1591-1604. [PMID: 35373644 DOI: 10.1177/10870547221085505] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Despite studies reporting alterations in the brain networks of patients with ADHD, alterations in the modularity of white matter (WM) networks are still unclear. METHOD Based on the results of module division by generalized Louvain algorithm, the modularity of ADHD was evaluated. The correlation between the modular changes of ADHD and its clinical characteristics was analyzed. RESULTS The participation coefficient and the connectivity between modules of ADHD increased, and the modularity coefficient decreased. Provincial hubs of ADHD did not change, and the number of connector hubs increased. All results showed that the modular segregation of WM networks of ADHD decreased. Modules with reduced modular segregation are mainly responsible for language and motor functions. Moreover, modularity showed evident correlation with the symptoms of ADHD. CONCLUSION The modularity changes in WM network provided a novel insight into the understanding of brain cognitive alterations in ADHD.
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Affiliation(s)
- Wenbo He
- Taiyuan University of Technology, Shanxi, China
| | - Weichen Liu
- Taiyuan University of Technology, Shanxi, China
| | - Min Mao
- Taiyuan University of Technology, Shanxi, China
| | | | - Ting Yan
- Shanxi Medical University, Taiyuan, China
| | - Jie Xiang
- Taiyuan University of Technology, Shanxi, China
| | - Bin Wang
- Taiyuan University of Technology, Shanxi, China
| | - Dandan Li
- Taiyuan University of Technology, Shanxi, China
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12
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Nastou E, Ocklenburg S, Hoogman M, Papadatou-Pastou M. Handedness in ADHD: Meta-Analyses. Neuropsychol Rev 2022; 32:877-892. [PMID: 35064524 DOI: 10.1007/s11065-021-09530-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 10/11/2021] [Indexed: 01/02/2023]
Abstract
Meta-analyses have shown that several neurodevelopmental and psychiatric disorders, such as autism spectrum disorder and schizophrenia, are associated with a higher prevalence of atypical (left-, non-right-, or mixed-) handedness. One neurodevelopmental disorder for which this association is unclear is attention deficit hyperactivity disorder (ADHD). Here, some empirical studies have found evidence for a higher prevalence of atypical handedness in individuals with ADHD compared to neurotypical individuals. However, other studies failed to establish such an association. Therefore, meta-analytic integration is critical to estimate whether or not there is an association between handedness and ADHD. We report the results of three meta-analyses (left-, mixed-, and non-right-handedness) comparing handedness in individuals with ADHD to controls (typically developing individuals). The results show evidence of a trend towards elevated levels of atypical handedness when it comes to differences in left- and mixed-handedness (p = 0.09 and p = 0.07, respectively), but do show clear evidence of elevated levels of non-right-handedness between individuals with ADHD and controls (p = 0.02). These findings are discussed in the context of the hypothesis that ADHD is a disorder in which mostly right-hemispheric brain networks are affected. Since right-handedness represents a dominance of the left motor cortex for fine motor behavior, such as writing, as well as a left-hemispheric dominance for language functions, and about 90% of individuals are right-handers, this hypothesis might explain why there is not stronger evidence for an association of left-handedness with ADHD. We suggest that the mechanisms involved in the pathogenesis of ADHD might show an overlap with the mechanisms involved in handedness strength, but not handedness direction.
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Affiliation(s)
- Evgenia Nastou
- Department of Primary Education, National and Kapodistrian University of Athens, 13A Navarinou Street, 10680, Athens, Greece
| | | | | | - Marietta Papadatou-Pastou
- Department of Primary Education, National and Kapodistrian University of Athens, 13A Navarinou Street, 10680, Athens, Greece. .,Biomedical Research Foundation, Academy of Athens, Athens, Greece.
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13
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Bu X, Cao M, Huang X, He Y. The structural connectome in ADHD. PSYCHORADIOLOGY 2021; 1:257-271. [PMID: 38666220 PMCID: PMC10939332 DOI: 10.1093/psyrad/kkab021] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 02/05/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) has been conceptualized as a brain dysconnectivity disorder. In the past decade, noninvasive diffusion magnetic resonance imaging (dMRI) studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome, and that these alterations are associated with core symptoms and cognitive deficits in patients. This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-, tractography-, and network-based perspectives. Voxel- and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts, the corpus callosum, the corticospinal tracts, and the cingulum bundle in patients with ADHD. Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes. The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification. These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation. However, given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations, these ADHD-related white matter alterations are still far from informing clinical practice. Future studies with larger and more homogeneous samples are needed to validate the consistency of current results; advanced dMRI techniques can help to generate much more precise estimation of white matter pathways and assure specific fiber configurations; and finally, dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.
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Affiliation(s)
- Xuan Bu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Miao Cao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China
| | - Xiaoqi Huang
- Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
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14
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Postema MC, Hoogman M, Ambrosino S, Asherson P, Banaschewski T, Bandeira CE, Baranov A, Bau CH, Baumeister S, Baur-Streubel R, Bellgrove MA, Biederman J, Bralten J, Brandeis D, Brem S, Buitelaar JK, Busatto GF, Castellanos FX, Cercignani M, Chaim-Avancini TM, Chantiluke KC, Christakou A, Coghill D, Conzelmann A, Cubillo AI, Cupertino RB, de Zeeuw P, Doyle AE, Durston S, Earl EA, Epstein JN, Ethofer T, Fair DA, Fallgatter AJ, Faraone SV, Frodl T, Gabel MC, Gogberashvili T, Grevet EH, Haavik J, Harrison NA, Hartman CA, Heslenfeld DJ, Hoekstra PJ, Hohmann S, Høvik MF, Jernigan TL, Kardatzki B, Karkashadze G, Kelly C, Kohls G, Konrad K, Kuntsi J, Lazaro L, Lera-Miguel S, Lesch KP, Louza MR, Lundervold AJ, Malpas CB, Mattos P, McCarthy H, Namazova-Baranova L, Rosa N, Nigg JT, Novotny SE, Weiss EO, Tuura RLO, Oosterlaan J, Oranje B, Paloyelis Y, Pauli P, Picon FA, Plessen KJ, Ramos-Quiroga JA, Reif A, Reneman L, Rosa PG, Rubia K, Schrantee A, Schweren LJ, Seitz J, Shaw P, Silk TJ, Skokauskas N, Vila JCS, Stevens MC, Sudre G, Tamm L, Tovar-Moll F, van Erp TG, Vance A, Vilarroya O, Vives-Gilabert Y, von Polier GG, Walitza S, Yoncheva YN, Zanetti MV, Ziegler GC, Glahn DC, Jahanshad N, et alPostema MC, Hoogman M, Ambrosino S, Asherson P, Banaschewski T, Bandeira CE, Baranov A, Bau CH, Baumeister S, Baur-Streubel R, Bellgrove MA, Biederman J, Bralten J, Brandeis D, Brem S, Buitelaar JK, Busatto GF, Castellanos FX, Cercignani M, Chaim-Avancini TM, Chantiluke KC, Christakou A, Coghill D, Conzelmann A, Cubillo AI, Cupertino RB, de Zeeuw P, Doyle AE, Durston S, Earl EA, Epstein JN, Ethofer T, Fair DA, Fallgatter AJ, Faraone SV, Frodl T, Gabel MC, Gogberashvili T, Grevet EH, Haavik J, Harrison NA, Hartman CA, Heslenfeld DJ, Hoekstra PJ, Hohmann S, Høvik MF, Jernigan TL, Kardatzki B, Karkashadze G, Kelly C, Kohls G, Konrad K, Kuntsi J, Lazaro L, Lera-Miguel S, Lesch KP, Louza MR, Lundervold AJ, Malpas CB, Mattos P, McCarthy H, Namazova-Baranova L, Rosa N, Nigg JT, Novotny SE, Weiss EO, Tuura RLO, Oosterlaan J, Oranje B, Paloyelis Y, Pauli P, Picon FA, Plessen KJ, Ramos-Quiroga JA, Reif A, Reneman L, Rosa PG, Rubia K, Schrantee A, Schweren LJ, Seitz J, Shaw P, Silk TJ, Skokauskas N, Vila JCS, Stevens MC, Sudre G, Tamm L, Tovar-Moll F, van Erp TG, Vance A, Vilarroya O, Vives-Gilabert Y, von Polier GG, Walitza S, Yoncheva YN, Zanetti MV, Ziegler GC, Glahn DC, Jahanshad N, Medland SE, Thompson PM, Fisher SE, Franke B, Francks C. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets. J Child Psychol Psychiatry 2021; 62:1202-1219. [PMID: 33748971 PMCID: PMC8455726 DOI: 10.1111/jcpp.13396] [Show More Authors] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/19/2020] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. METHODS We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. RESULTS There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing. CONCLUSION Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
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Affiliation(s)
- Merel C. Postema
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Radboud university medical center, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Sara Ambrosino
- NICHE lab, Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Philip Asherson
- Social, Genetic and Developmental Psychiatry Centre; Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany
| | - Cibele E. Bandeira
- Adulthood ADHD Outpatient Program (ProDAH), Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Alexandr Baranov
- Research Institute of Pediatrics and child health of Central clinical hospital of the Russian Academy of Sciences of the Ministry of Science and Higher Education of the Russian Federation, Moscow, Russia
| | - Claiton H.D. Bau
- Adulthood ADHD Outpatient Program (ProDAH), Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany
| | - Ramona Baur-Streubel
- Department of Biological Psychology, Clinical Psychology and Psychotherapy, University of Würzburg, Würzburg, Germany
| | - Mark A. Bellgrove
- Turner Institute for Brain and Mental Health and School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Joseph Biederman
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, USA
| | - Janita Bralten
- Department of Human Genetics, Radboud university medical center, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- The Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Silvia Brem
- The Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Jan K. Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboudumc, Nijmegen, The Netherlands
- Karakter child and adolescent psychiatry University Center, Nijmegen, The Netherlands
| | - Geraldo F. Busatto
- Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Hospital das Clinicas HCFMUSP, Faculty of Medicine, University of São Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Francisco X. Castellanos
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Mara Cercignani
- Department of Neuroscience, Brighton and Sussex Medical School, Falmer, Brighton, UK
| | - Tiffany M. Chaim-Avancini
- Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Hospital das Clinicas HCFMUSP, Faculty of Medicine, University of São Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Kaylita C. Chantiluke
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anastasia Christakou
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
- School of Psychology and Clinical Language Sciences, Centre for Integrative Neuroscience and Neurodynamics, University of Reading, Reading, UK
| | - David Coghill
- Departments of Paediatrics and Psychiatry, University of Melbourne, Melbourne, Australia
- Murdoch Children’s Research Institute, Melbourne, Australia
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Tübingen, Germany
- PFH – Private University of Applied Sciences, Department of Psychology (Clinical Psychology II), Göttingen, Germany
| | - Ana I. Cubillo
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Renata B. Cupertino
- Adulthood ADHD Outpatient Program (ProDAH), Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Patrick de Zeeuw
- NICHE Lab, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Alysa E. Doyle
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, USA
| | - Sarah Durston
- NICHE Lab, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Eric A. Earl
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Jeffery N. Epstein
- Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH
| | - Thomas Ethofer
- Clinic for Psychiatry/Psychotherapy Tübingen / Department for Biomedical Magnetic Resonance, Tübingen
| | - Damien A. Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
| | - Andreas J. Fallgatter
- Department of Psychiatry and Psychotherapy, University Hospital of Tuebingen, Tuebingen, Germany
- LEAD Graduate School, University of Tuebingen, Germany
| | - Stephen V. Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Germany
- Department of Psychiatry, Trinity College Dublin, Ireland
| | - Matt C. Gabel
- Department of Neuroscience, Brighton and Sussex Medical School, Falmer, Brighton, UK
| | - Tinatin Gogberashvili
- National Medical Research Center for Children’s Health, Laboratory of Neurology and Cognitive Health, Moscow, Russia
| | - Eugenio H. Grevet
- Adulthood ADHD Outpatient Program (ProDAH), Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Jan Haavik
- K.G. Jebsen Centre for Neuropsychiatric Disorders, Department of Biomedicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Neil A. Harrison
- Department of Neuroscience, Brighton and Sussex Medical School, Falmer, Brighton, UK
- Sussex Partnership NHS Foundation Trust, Swandean, East Sussex, UK
| | - Catharina A. Hartman
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
| | - Dirk J. Heslenfeld
- Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Pieter J. Hoekstra
- University of Groningen, University Medical Center Groningen, Department of Child and Adolescent Psychiatry
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim / Heidelberg University, Mannheim, Germany
| | - Marie F. Høvik
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | | | - Bernd Kardatzki
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Georgii Karkashadze
- Research Institute of Pediatrics and child health of Central clinical hospital of the Russian Academy of Sciences of the Ministry of Science and Higher Education of the Russian Federation, Moscow, Russia
| | - Clare Kelly
- School of Psychology and Department of Psychiatry at the School of Medicine, Trinity College Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Ireland
| | - Gregor Kohls
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany
- JARA Institute Molecular Neuroscience and Neuroimaging (INM-11), Institute for Neuroscience and Medicine, Research Center Jülich, Germany
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry Centre; Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Luisa Lazaro
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Center on Mental Health (CIBERSAM), Barcelona, Spain
- Department of Medicine, University of Barcelona, Spain
| | - Sara Lera-Miguel
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciencies, Hospital Clínic, Barcelona
| | - Klaus-Peter Lesch
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
- Laboratory of Psychiatric Neurobiology, Institute of Molecular Medicine, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Mario R. Louza
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
| | - Astri J. Lundervold
- K.G. Jebsen Centre for Neuropsychiatric Disorders, Department of Biomedicine, University of Bergen, Bergen, Norway
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Charles B Malpas
- Developmental Imaging Group, Murdoch Children’s Research Institute, Melbourne, Australia
- Clinical Outcomes Research Unit (CORe), Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
| | - Paulo Mattos
- D’Or Institute for Research and Education, Rio de Janeiro, Brazil
- Federal University of Rio de Janeiro
| | - Hazel McCarthy
- Department of Psychiatry, Trinity College Dublin, Ireland
- Centre of Advanced Medical Imaging, St James’s Hospital, Dublin, Ireland
| | - Leyla Namazova-Baranova
- Research Institute of Pediatrics and child health of Central clinical hospital of the Russian Academy of Sciences of the Ministry of Science and Higher Education of the Russian Federation, Moscow, Russia
- Russian National Research Medical University Ministry of Health of the Russian Federation, Moscow, Russia
| | - Nicolau Rosa
- Department of Child and Adolescent Psychiatry and Psychology, Institut of Neurosciencies, Hospital Clínic, Barcelona, Spain
| | - Joel T Nigg
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland OR, USA
- Department of Psychiatry, Oregon Health & Science University, Portland OR, USA
| | | | - Eileen Oberwelland Weiss
- Translational Neuroscience, Child and Adolescent Psychiatry, University Hospital RWTH Aachen, Aachen, Germany
- Cognitive Neuroscience (INM-3), Institute for Neuroscience and Medicine, Research Center Jülich
| | - Ruth L. O’Gorman Tuura
- Center for MR Research, University Children’s Hospital, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology (ZIHP)
| | - Jaap Oosterlaan
- Clinical Neuropsychology Section, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Emma Children’s Hospital Amsterdam University Medical Centers, University of Amsterdam, Emma Neuroscience Group, department of Pediatrics, Amsterdam Reproduction & Development, Amsterdam, The Netherlands
| | - Bob Oranje
- NICHE Lab, Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, The Netherlands
| | - Yannis Paloyelis
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Paul Pauli
- Department of Psychology (Biological Psychology, Clinical Psychology and Psychotherapy) and Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Felipe A. Picon
- Adulthood ADHD Outpatient Program (ProDAH), Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Kerstin J. Plessen
- Child and Adolescent Mental Health Centre, Capital Region Copenhagen, Denmark
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, University Hospital Lausanne, Switzerland
| | - J. Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d’Hebron, Barcelona, Catalonia, Spain
- Group of Psychiatry, Mental Health and Addictions, Vall d’Hebron Research Institute (VHIR), Barcelona, Catalonia, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Catalonia, Spain
- Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt, Germany
| | - Liesbeth Reneman
- Amsterdam University Medical Center, Academic Medical Center, Amsterdam, the Netherlands
| | - Pedro G.P. Rosa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Hospital das Clinicas HCFMUSP, Faculty of Medicine, University of São Paulo, Sao Paulo, Sao Paulo, Brazil
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam; the Netherlands
| | - Lizanne J.S. Schweren
- University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), Groningen, The Netherlands
| | - Jochen Seitz
- Child and Adolescent Psychiatry, University Hospital RWTH Aachen, Aachen, Germany
| | - Philip Shaw
- National Human Genome Research Institute and National Institute of Mental health, Bethesda, MD, USA
| | - Tim J. Silk
- Deakin University, School of Psychology, Geelong, Australia
- Murdoch Children’s Research Institute, Developmental Imaging, Melbourne, Australia
| | - Norbert Skokauskas
- Centre for child and adolescent mental health, NTNU, Norway
- Institute of Mental Health, Norwegian University of Science and Technology
| | | | - Michael C. Stevens
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, USA
- Department of Psychiatry, Yale University School of Medicine, USA
| | - Gustavo Sudre
- National Human Genome Research Institute, Bethesda, MD, USA
| | - Leanne Tamm
- Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, USA
- College of Medicine, University of Cincinnati, USA
| | - Fernanda Tovar-Moll
- D’Or Institute for Research and Education, Rio de Janeiro, Brazil
- Morphological Sciences Program, Federal University of Rio de Janeiro, Rio de Janeiro
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| | - Alasdair Vance
- Department of Paediatrics, University of Melbourne, Australia
| | - Oscar Vilarroya
- Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | | | - Georg G. von Polier
- Child and Adolescent Psychiatry, University Hospital RWTH Aachen, Aachen, Germany
- Brain and Behavior (INM-7), Institute for Neuroscience and Medicine, Research Center Jülich, Germany
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Yuliya N. Yoncheva
- Department of Child and Adolescent Psychiatry, NYU Child Study Center, Hassenfeld Children’s Hospital at NYU Langone
| | - Marcus V. Zanetti
- Department of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
- Hospital Sírio-Libanês, São Paulo Brazil
| | - Georg C. Ziegler
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Hartford Hospital, Hartford, CT, USA
- Department of Psychiatry, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115-5724, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90292
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Paul M. Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Simon E. Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Barbara Franke
- Department of Human Genetics, Radboud university medical center, Nijmegen, Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
- Department of Psychiatry, Radboud university medical center, Nijmegen, Netherlands
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
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15
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Siegel-Ramsay JE, Romaniuk L, Whalley HC, Roberts N, Branigan H, Stanfield AC, Lawrie SM, Dauvermann MR. Glutamate and functional connectivity - support for the excitatory-inhibitory imbalance hypothesis in autism spectrum disorders. Psychiatry Res Neuroimaging 2021; 313:111302. [PMID: 34030047 DOI: 10.1016/j.pscychresns.2021.111302] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/30/2021] [Accepted: 05/07/2021] [Indexed: 12/24/2022]
Abstract
It has been proposed that the Glutamate (Glu) system is implicated in autism spectrum disorders (ASD) via an imbalance between excitatory and inhibitory brain circuits, which impacts on brain function. Here, we investigated the excitatory-inhibitory imbalance theory by measuring Glu-concentrations and the relationship with resting-state function. Nineteen adult males with ASD and 19 age and sex-matched healthy controls (HC) (23 - 58 years) underwent Proton Magnetic Resonance Spectroscopy of the dorsal anterior cingulate cortex (dACC) and resting-state functional Magnetic Resonance Imaging (fMRI). Glu and Glx concentrations were compared between groups. Seed-based functional connectivity was analyzed with a priori seeds of the right and left dACC. Finally, metabolite concentrations were related to functional connectivity coefficients and compared between both groups. Individuals with ASD showed significantly negative associations between increased Glx concentrations and reduced functional connectivity between the dACC and insular, limbic and parietal regions. In contrast, HC displayed a positive relationship between the same metabolite and connectivity measures. We provided new evidence to support the excitatory-inhibitory imbalance theory, where excitatory Glx concentrations were related to functional dysconnectivity in ASD. Future research is needed to investigate large-scale functional networks in association with both excitatory and inhibitory metabolites in subpopulations of ASD.
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Affiliation(s)
- Jennifer E Siegel-Ramsay
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom; Department of Psychiatry and Behavioral Science, University of Texas, Austin, United States
| | - Liana Romaniuk
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Neil Roberts
- Centre for Reproductive Health (CRH), School of Clinical Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Holly Branigan
- School of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew C Stanfield
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom; Patrick Wild Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Maria R Dauvermann
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States.
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16
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Li D, Cui X, Yan T, Liu B, Zhang H, Xiang J, Wang B. Abnormal Rich Club Organization in Hemispheric White Matter Networks of ADHD. J Atten Disord 2021; 25:1215-1229. [PMID: 31884863 DOI: 10.1177/1087054719892887] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Objective: Brain network studies have revealed abnormal topology asymmetry of white matter (WM) in ADHD. Recently, rich club organization was proposed to be a key feature of brain network topology. However, abnormalities in the rich club organization of hemispheric WM networks in ADHD remain unclear. Method: Forty ADHD patients and 51 normal controls participated in this study. Structural networks were reconstructed based on diffusion tensor imaging (DTI) and analyzed with graph theory. Results: The two groups exhibited different patterns of asymmetry in connectivity measures of rich club connections. ADHD patients showed more feeder connections than normal controls. Reduced rightward asymmetry was observed in connectivity measures of local connections involving several peripheral regions of the ADHD patients. In addition, abnormal regional asymmetry scores were associated with ADHD symptoms. Conclusion: The topological changes in rich club organization provide a novel insight into the alteration of WM connections in ADHD.
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Affiliation(s)
- Dandan Li
- Taiyuan University of Technology, China
| | | | - Ting Yan
- Shanxi Medical University, Taiyuan, China
| | - Bo Liu
- First Hospital of Shanxi Medical University, Taiyuan, China
| | - Hui Zhang
- First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jie Xiang
- Taiyuan University of Technology, China
| | - Bing Wang
- Taiyuan University of Technology, China
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17
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Abstract
Objective: The aim of this work is to explore the relationship between temporal variability and brain lateralization in ADHD. Method: The temporal variabilities of 116 brain regions based on resting-state functional magnetic resonance imaging (rs-fMRI) data were calculated for analysis. Results: Between-group comparison revealed that in comparison with the controls, ADHD participants showed significantly higher temporal variability in the left superior frontal gyrus (medial), left rectus gyrus, left inferior parietal lobule and angular gyrus, and lower temporal variability in the amygdala, left caudate and putamen. Besides, ADHD patients exhibited significantly increased leftward lateralization in the orbitofrontal cortex (inferior), and decreased rightward lateralization in the orbitofrontal cortex (medial) and rectus gyrus, compared with controls. Lateralization indices were also found to be related with clinical characteristics of ADHD patients. Conclusion: Our results may help us deeper in understanding the pathology of ADHD.
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Affiliation(s)
- Hongliang Zou
- Nanjing University of Science and Technology, P.R. China
| | - Jian Yang
- Nanjing University of Science and Technology, P.R. China
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18
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Chen S, Guan L, Tang J, He F, Zheng Y. Asymmetry in Cortical and Subcortical Structures of the Brain in Children and Adolescents with Attention-Deficit/Hyperactivity Disorder. Neuropsychiatr Dis Treat 2021; 17:493-502. [PMID: 33603386 PMCID: PMC7886251 DOI: 10.2147/ndt.s292444] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 01/11/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Human cognitive and emotional functions are asymmetrical between the left and right hemispheres. In neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) patients, the absence of aberrant asymmetry might serve as a neuroanatomical marker of ADHD. However, few studies have estimated abnormalities in cortical and subcortical asymmetry in children and adolescents of different ADHD subtypes. METHODS Data were from the results collected by the Peking University site in the "ADHD-200 sample" dataset, which comprised 31 eligible ADHD (20 inattentive ADHD (ADHD-I), 11 combined ADHD (ADHD-C)) and 31 matched typically developing (TD) individuals. The Asymmetry Indexes (AIs) in cortical thickness, cortical gray-matter volume and subcortical nucleus (SN) volume were calculated based on an automated surface-based approach. The differences in cortical thickness, cortical gray-matter volume, and SN volume AIs were evaluated among groups. We also analyzed the correlation between AIs and the severity of ADHD symptoms. RESULTS Compared with the TD group, SN asymmetry in ADHD group did not reveal significant differences. Altered cortical asymmetry of different subtypes in ADHD groups was located in the orbitofrontal and anterior cingulate circuits, including the medial orbitofrontal, paracentral, pars triangularis, caudal anterior cingulate, isthmus cingulate, and superior frontal regions. In the comparisons, cortical gray-matter volume AIs were significantly different in the caudal anterior cingulate, isthmus cingulate, and superior frontal regions between ADHD-I and ADHD-C groups. There were significant correlations between the severity of ADHD symptoms and asymmetric measurements in medial orbitofrontal, paracentral and isthmus cingulate regions. CONCLUSION These findings provide further evidence for the altered cortical morphological asymmetry in children and adolescents with ADHD, and these differences are associated (at least in part) with the severity of ADHD symptoms. Brain asymmetry could be an appropriate precursor of morphological alterations in neurodevelopmental disorders.
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Affiliation(s)
- Sijian Chen
- Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People's Republic of China
| | - Lin Guan
- Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People's Republic of China
| | - Jie Tang
- Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People's Republic of China
| | - Fan He
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People's Republic of China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Yi Zheng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, 100088, People's Republic of China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100069, People's Republic of China
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19
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Electroencephalographic and Neuroimaging Asymmetry Correlation in Patients with Attention-Deficit Hyperactivity Disorder. Neural Plast 2020; 2020:4838291. [PMID: 32952547 PMCID: PMC7481992 DOI: 10.1155/2020/4838291] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Revised: 07/21/2020] [Accepted: 08/18/2020] [Indexed: 11/17/2022] Open
Abstract
The present study explores the correlation between electroencephalographic and neuroimaging asymmetry index from EEG-MRI functional connectome and EEG power analysis in inattention, motion, and mixed profile subgroups of ADHD. Sixty-two subjects from Healthy Brain Network Biobank of the Child Mind Institute dataset were selected basing on the quotient score. From both MRI and EEG asymmetry index, Pearson's correlation, ANOVA, and partial least square analysis were performed matching left and right brain parcels and channels. The asymmetry index significantly correlated across subjects between fMRI and power-EEG in the inattention group in frontal and temporal areas for theta and alpha bands, an anticorrelation in the same areas for delta band was found. Significant patterns of hemispheric asymmetry index have been reported, involving EEG bands that underlie cognitive impairments in ADHD. Alpha and theta bands were altered in the inattention group of patients, reflecting widespread deficiency of basic attentional processing.
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20
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Cao R, Shi H, Wang X, Huo S, Hao Y, Wang B, Guo H, Xiang J. Hemispheric Asymmetry of Functional Brain Networks under Different Emotions Using EEG Data. ENTROPY 2020; 22:e22090939. [PMID: 33286708 PMCID: PMC7597206 DOI: 10.3390/e22090939] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/22/2020] [Accepted: 08/24/2020] [Indexed: 01/21/2023]
Abstract
Despite many studies reporting hemispheric asymmetry in the representation and processing of emotions, the essence of the asymmetry remains controversial. Brain network analysis based on electroencephalography (EEG) is a useful biological method to study brain function. Here, EEG data were recorded while participants watched different emotional videos. According to the videos’ emotional categories, the data were divided into four categories: high arousal high valence (HAHV), low arousal high valence (LAHV), low arousal low valence (LALV) and high arousal low valence (HALV). The phase lag index as a connectivity index was calculated in theta (4–7 Hz), alpha (8–13 Hz), beta (14–30 Hz) and gamma (31–45 Hz) bands. Hemispheric networks were constructed for each trial, and graph theory was applied to quantify the hemispheric networks’ topological properties. Statistical analyses showed significant topological differences in the gamma band. The left hemispheric network showed significantly higher clustering coefficient (Cp), global efficiency (Eg) and local efficiency (Eloc) and lower characteristic path length (Lp) under HAHV emotion. The right hemispheric network showed significantly higher Cp and Eloc and lower Lp under HALV emotion. The results showed that the left hemisphere was dominant for HAHV emotion, while the right hemisphere was dominant for HALV emotion. The research revealed the relationship between emotion and hemispheric asymmetry from the perspective of brain networks.
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Affiliation(s)
- Rui Cao
- Department of Software Engineering, College of Software, Taiyuan University of Technology, Taiyuan 030600, China; (H.S.); (S.H.); (Y.H.)
- Correspondence:
| | - Huiyu Shi
- Department of Software Engineering, College of Software, Taiyuan University of Technology, Taiyuan 030600, China; (H.S.); (S.H.); (Y.H.)
| | - Xin Wang
- Department of Computer Science and Technology, College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China; (X.W.); (B.W.); (H.G.); (J.X.)
| | - Shoujun Huo
- Department of Software Engineering, College of Software, Taiyuan University of Technology, Taiyuan 030600, China; (H.S.); (S.H.); (Y.H.)
| | - Yan Hao
- Department of Software Engineering, College of Software, Taiyuan University of Technology, Taiyuan 030600, China; (H.S.); (S.H.); (Y.H.)
| | - Bin Wang
- Department of Computer Science and Technology, College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China; (X.W.); (B.W.); (H.G.); (J.X.)
| | - Hao Guo
- Department of Computer Science and Technology, College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China; (X.W.); (B.W.); (H.G.); (J.X.)
| | - Jie Xiang
- Department of Computer Science and Technology, College of Information and Computer, Taiyuan University of Technology, Taiyuan 030600, China; (X.W.); (B.W.); (H.G.); (J.X.)
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21
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Srivishagan S, Perera AAI, Hojjat A, Ratnarajah N. Brain Network Measures for Groups of Nodes: Application to Normal Aging and Alzheimer's Disease. Brain Connect 2020; 10:316-327. [PMID: 32458697 DOI: 10.1089/brain.2020.0747] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: The nodal brain network measures (e.g., centrality measures) are defined for a single node and the global network measures (e.g., global efficiency) are defined for the whole brain in the literature. But a meaningful group of nodes will be benefited from a formulation that applies to a group of nodes rather than a single node or the whole brain. The question such as "which brain lobe is more structurally central in the older-adult brain?" could be answered to some extent by the application of a centrality measure that applied to the group of nodes from each lobe. In the brain asymmetric studies, path-based global measures were applied to the left and right hemispherical networks separately, considering only intrahemispheric edges. However, for a valid comparison, such global measures should include the interhemispheric edges as well. This problem can be solved by considering both hemispherical nodes as two groups in one network. Methods: Novel definitions for group nodes network measures are presented in this study, to solve a number of such group-context problems in the brain networks analysis. We apply the group measures to the structural connectomes of older adults and Alzheimer's disease (AD) subjects based on the brain lobes and hemispherical groups to demonstrate the effectiveness of the proposed measures. Results: The temporal and parietal lobes are the most central lobes in older adults and AD, but the strength of these lobes has been heavily affected in AD. However, the rewiring of the AD brain preserves the paths for communication between other regions through these lobes. Leftward efficiency revealed in older adults and the asymmetry disappeared in the rewired AD. Conclusion: We prove that the concepts of group network measures have the potential to solve a number of such group-context problems in the brain networks analysis and the group network measures change the way of analyzing brain networks.
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Affiliation(s)
- Subaramya Srivishagan
- Faculty of Applied Science, Vavuniya Campus of the University of Jaffna, Vavuniya, Sri Lanka
| | | | - Ali Hojjat
- School of Computer Science, University of Kent, Canterbury, United Kingdom
| | - Nagulan Ratnarajah
- Faculty of Applied Science, Vavuniya Campus of the University of Jaffna, Vavuniya, Sri Lanka
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22
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Cao R, Wang X, Gao Y, Li T, Zhang H, Hussain W, Xie Y, Wang J, Wang B, Xiang J. Abnormal Anatomical Rich-Club Organization and Structural-Functional Coupling in Mild Cognitive Impairment and Alzheimer's Disease. Front Neurol 2020; 11:53. [PMID: 32117016 PMCID: PMC7013042 DOI: 10.3389/fneur.2020.00053] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 01/14/2020] [Indexed: 12/17/2022] Open
Abstract
Emerging research indicates interruptions in the wiring organization of the brain network in Mild cognitive impairment (MCI) and Alzheimer's disease (AD). Due to the important role of rich-club organization in distinguishing abnormalities of AD patients and the close relationship between structural connectivity (SC) and functional connectivity (FC), our study examined whether changes in SC-FC coupling and the relationship with abnormal rich-club organizations during the development of diseases may contribute to the pathophysiology of AD. Structural diffusion-tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) were performed in 38 normal controls (NCs), 40 MCI patients and 19 AD patients. Measures of the rich-club structure and its role in global structural-functional coupling were administered. Our study found decreased levels of feeder and local connectivity in MCI and AD patients, which were the main contributing factors to the lower efficiency of the brain structural network. Another important finding was that we have more accurately characterized the changing pattern of functional brain dynamics. The enhanced coupling between SC and FC in MCI and AD patients might be due to disruptions in optimal structural organization. More interestingly, we also found increases in the SC-FC coupling for feeder and local connections in MCI and AD patients. SC-FC coupling also showed significant differences between MCI and AD patients, mainly between the abnormal feeder connections. The connection density and coupling strength were significantly correlated with clinical metrics in patients. The present findings enhanced our understanding of the neurophysiologic mechanisms associated with MCI and AD.
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Affiliation(s)
- Rui Cao
- College of Software, Taiyuan University of Technology, Taiyuan, China
| | - Xin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Yuan Gao
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Ting Li
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Waqar Hussain
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Yunyan Xie
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Wang
- Department of Health management, Aerospace Center Hospital, Peking University Aerospace School of Clinical Medicine, Beijing, China
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
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23
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Wu ZM, Wang P, Yang L, Liu L, Sun L, An L, Cao QJ, Chan RCK, Yang BR, Wang YF. Altered brain white matter microstructural asymmetry in children with ADHD. Psychiatry Res 2020; 285:112817. [PMID: 32035376 DOI: 10.1016/j.psychres.2020.112817] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 01/25/2020] [Accepted: 01/25/2020] [Indexed: 01/23/2023]
Abstract
OBJECTIVES We aimed to examine brain white matter integrity in children with ADHD. METHODS In a cohort of children with ADHD (n = 83) and healthy controls (n = 122), we used tract-based spatial statistics on Diffusion Tensor Imaging (DTI) data to obtain the mean fractional anisotropy (FA) in 40 bilateral regions of interest (ROIs). Lateralization Index (LI) was calculated. The difference in LI between groups and correlations between the LI of each ROI and ADHD symptom scores as well as cognitive function were examined. RESULTS Children with ADHD had significantly greater LI at the posterior thalamic radiation (PTR) compared with healthy controls (mean LI in ADHD = 0.0096; in Control = 0.0044, p = 0.0143), and LI of the external capsule (EC) was significantly correlated with inattention symptoms in both groups (β = -0.00059, p = 0.0181). LI of the PTR was significantly correlated with inhibitory function in healthy controls (β = -0.0008510, p = 0.0248), but not in children with ADHD. CONCLUSION We found increased brain white matter asymmetry (leftward) in children with ADHD compared with healthy controls at the posterior thalamic radiation. Leftward lateralization of FA values at the external capsule was negatively correlated with ADHD symptoms in both children with ADHD and healthy controls.
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Affiliation(s)
- Zhao-Min Wu
- Shenzhen Children's Hospital, Shenzhen, 518000, China; Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China; Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands.
| | - Peng Wang
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Li Yang
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Li An
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Qing-Jiu Cao
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Bin-Rang Yang
- Shenzhen Children's Hospital, Shenzhen, 518000, China
| | - Yu-Feng Wang
- Peking University Sixth Hospital/Institute of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China; Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, 100191, China.
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Tan YW, Liu L, Wang YF, Li HM, Pan MR, Zhao MJ, Huang F, Wang YF, He Y, Liao XH, Qian QJ. Alterations of cerebral perfusion and functional brain connectivity in medication-naïve male adults with attention-deficit/hyperactivity disorder. CNS Neurosci Ther 2019; 26:197-206. [PMID: 31231983 PMCID: PMC6978256 DOI: 10.1111/cns.13185] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 06/01/2019] [Accepted: 06/04/2019] [Indexed: 12/17/2022] Open
Abstract
Aims Functional brain abnormalities, including altered cerebral perfusion and functional connectivities, have been illustrated in adults with attention‐deficit/hyperactivity disorder (aADHD). The present study attempted to explore the alterations of cerebral blood flow (CBF) and resting‐state functional connectivity (RSFC) simultaneously to understand the neural mechanisms for adults with ADHD comprehensively. Methods Resting‐state arterial spin labeling (ASL) and blood oxygenation level‐dependent (BOLD) magnetic resonance imaging (MRI) data were acquired for 69 male aADHD and 69 matched healthy controls (HCs). The altered CBFs associated with aADHD were explored based on both categorical (aADHD vs HCs) and dimensional (correlation with aADHD core symptoms) perspectives. Then, the seed‐based RSFC analyses were developed for the regions showing significant alterations of CBF. Results Significantly decreased CBF in the large‐scale resting‐state networks regions (eg, ventral attentional network, somatomotor network, limbic network) and subcortical regions was indicated in aADHD compared with HCs. The correlation analyses indicated that the hypoperfusion in left putamen/global pallidum and left amygdala/hippocampus was correlated with ADHD inattentive and total symptoms, respectively. Further, weaker negative functional connectivity between left amygdala and bilateral supplementary motor area, bilateral superior frontal gyrus, and left medial frontal gyrus was found in adults with ADHD. Conclusion The present findings suggested alterations of both cerebral perfusion and functional connectivity for the left amygdala in aADHD. The combination of CBF and RSFCs may help to interpret the neuropathogenesis of ADHD more comprehensively.
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Affiliation(s)
- Ya-Wen Tan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Yan-Fei Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Hai-Mei Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Mei-Rong Pan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Meng-Jie Zhao
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Fang Huang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Yu-Feng Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Xu-Hong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Qiu-Jin Qian
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital) & the NHC Key Laboratory of Mental Health (Peking University), Beijing, China
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