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Soumier A, Lio G, Demily C. Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders. Mol Psychiatry 2024:10.1038/s41380-024-02487-8. [PMID: 38443634 DOI: 10.1038/s41380-024-02487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.
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Affiliation(s)
- Amelie Soumier
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France.
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France.
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France.
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France.
| | - Guillaume Lio
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
| | - Caroline Demily
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France
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2
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Ding N, Fu L, Qian L, Sun B, Li C, Gao H, Lei T, Ke X. The correlation between brain structure characteristics and emotion regulation ability in children at high risk of autism spectrum disorder. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02369-y. [PMID: 38402375 DOI: 10.1007/s00787-024-02369-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 01/08/2024] [Indexed: 02/26/2024]
Abstract
As indicated by longitudinal observation, autism has difficulty controlling emotions to a certain extent in early childhood, and most children's emotional and behavioral problems are further aggravated with the growth of age. This study aimed at exploring the correlation between white matter and white matter fiber bundle connectivity characteristics and their emotional regulation ability in children with autism using machine learning methods, which can lay an empirical basis for early clinical intervention of autism. Fifty-five high risk of autism spectrum disorder (HR-ASD) children and 52 typical development (TD) children were selected to complete the skull 3D-T1 structure and diffusion tensor imaging (DTI). The emotional regulation ability of the two groups was compared using the still-face paradigm (SFP). The classification and regression models of white matter characteristics and white matter fiber bundle connections of emotion regulation ability in the HR-ASD group were built based on the machine learning method. The volume of the right amygdala (R2 = 0.245) and the volume of the right hippocampus (R2 = 0.197) affected constructive emotion regulation strategies. FA (R2 = 0.32) and MD (R2 = 0.34) had the predictive effect on self-stimulating behaviour. White matter fiber bundle connection predicted constructive regulation strategies (positive edging R2 = 0.333, negative edging R2 = 0.334) and mother-seeking behaviors (positive edging R2 = 0.667, negative edging R2 = 0.363). The emotional regulation ability of HR-ASD children is significantly correlated with the connections of multiple white matter fiber bundles, which is a potential neuro-biomarker of emotional regulation ability.
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Affiliation(s)
- Ning Ding
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
- Qingdao Women and Children' s Hospital, Qingdao University, Qingdao, 266011, China
| | - Linyan Fu
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Lu Qian
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Bei Sun
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Chunyan Li
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Huiyun Gao
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Tianyu Lei
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Xiaoyan Ke
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
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3
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França LGS, Ciarrusta J, Gale-Grant O, Fenn-Moltu S, Fitzgibbon S, Chew A, Falconer S, Dimitrova R, Cordero-Grande L, Price AN, Hughes E, O'Muircheartaigh J, Duff E, Tuulari JJ, Deco G, Counsell SJ, Hajnal JV, Nosarti C, Arichi T, Edwards AD, McAlonan G, Batalle D. Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment. Nat Commun 2024; 15:16. [PMID: 38331941 PMCID: PMC10853532 DOI: 10.1038/s41467-023-44050-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 11/28/2023] [Indexed: 02/10/2024] Open
Abstract
Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.
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Affiliation(s)
- Lucas G S França
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sean Fitzgibbon
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Eugene Duff
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
- Department of Brain Sciences, Imperial College London, London, W12 0BZ, UK
- UK Dementia Research Institute at Imperial College London, London, W12 0BZ, UK
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, 20500, Turku, Finland
- Turku Collegium for Science and Medicine and Technology, University of Turku, 20500, Turku, Finland
- Department of Psychiatry, University of Turku and Turku University Hospital, 20500, Turku, Finland
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Pompeu Fabra University, 08002, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, 08010, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, VIC, 3010, Australia
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
- Department of Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, SE1 7EH, UK
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK.
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Wang M, Xu D, Zhang L, Jiang H. Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review. Diagnostics (Basel) 2023; 13:3027. [PMID: 37835770 PMCID: PMC10571992 DOI: 10.3390/diagnostics13193027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.
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Affiliation(s)
- Miaoyan Wang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Dandan Xu
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Lili Zhang
- Department of Child Health Care, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China
| | - Haoxiang Jiang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
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5
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Dawson G, Rieder AD, Johnson MH. Prediction of autism in infants: progress and challenges. Lancet Neurol 2023; 22:244-254. [PMID: 36427512 PMCID: PMC10100853 DOI: 10.1016/s1474-4422(22)00407-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 09/17/2022] [Accepted: 09/27/2022] [Indexed: 11/24/2022]
Abstract
Autism spectrum disorder (henceforth autism) is a neurodevelopmental condition that can be reliably diagnosed in children by age 18-24 months. Prospective longitudinal studies of infants aged 1 year and younger who are later diagnosed with autism are elucidating the early developmental course of autism and identifying ways of predicting autism before diagnosis is possible. Studies that use MRI, EEG, and near-infrared spectroscopy have identified differences in brain development in infants later diagnosed with autism compared with infants without autism. Retrospective studies of infants younger than 1 year who received a later diagnosis of autism have also showed an increased prevalence of health conditions, such as sleep disorders, gastrointestinal disorders, and vision problems. Behavioural features of infants later diagnosed with autism include differences in attention, vocalisations, gestures, affect, temperament, social engagement, sensory processing, and motor abilities. Although research findings offer insight on promising screening approaches for predicting autism in infants, individual-level predictions remain a future goal. Multiple scientific challenges and ethical questions remain to be addressed to translate research on early brain-based and behavioural predictors of autism into feasible and reliable screening tools for clinical practice.
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Affiliation(s)
- Geraldine Dawson
- Duke Center for Autism and Brain Development, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.
| | - Amber D Rieder
- Duke Center for Autism and Brain Development, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; Duke Global Health Institute, Duke University, Durham, NC, USA
| | - Mark H Johnson
- Department of Psychology, University of Cambridge, Cambridge, UK; Centre for Brain and Cognitive Development, Birkbeck, University of London, London, UK
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6
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Sun F, Chen Y, Gao Q, Zhao Z. Abnormal gray matter structure in children and adolescents with high-functioning autism spectrum disorder. Psychiatry Res Neuroimaging 2022; 327:111564. [PMID: 36384063 DOI: 10.1016/j.pscychresns.2022.111564] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/14/2022] [Accepted: 11/04/2022] [Indexed: 11/11/2022]
Abstract
The present study aimed to explore the brain structural mechanisms underlying clinical dysfunction in patients with ASD using magnetic resonance imaging (MRI). After screening T1 structural images from the Autism Brain Imaging Data Exchange (ABIDE) database, 111 children and adolescents with high-functioning ASD and 151 typically developing (TD) subjects matched were included in this study. We first compared the differences in gray matter volume (GMV) and gray matter density (GMD) between the two groups. Then, the relationships between GMV/GMD and clinical assessments in ASD patients were evaluated. We found that compared with the TD group, the ASD group showed increased GMV/GMD in the precuneus, thalamus, hippocampus and cingulate gyrus. Moreover, in the ASD group, social interaction was negatively correlated with GMD in the bilateral superior temporal gyrus and limbic system; communication was positively correlated with GMD in the right middle temporal gyrus, inferior frontal gyrus, and anterior cingulate gyrus; and repetitive behavior was positively correlated with GMD in the cerebellum and negatively correlated with GMV in the prefrontal cortex. In conclusion, the gray matter structure in children and adolescents with ASD was abnormal, and different clinical dysfunctions in ASD patients were related to structural abnormalities in specific regions.
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Affiliation(s)
- Fenfen Sun
- Center for Brain, Mind, and Education, Shaoxing University, Shaoxing 312000, China; Department of Psychology, Shaoxing University, Shaoxing 312000, China
| | - Yue Chen
- Center for Brain, Mind, and Education, Shaoxing University, Shaoxing 312000, China; Department of Psychology, Shaoxing University, Shaoxing 312000, China
| | - Qiyang Gao
- Center for Brain, Mind, and Education, Shaoxing University, Shaoxing 312000, China; Department of Psychology, Shaoxing University, Shaoxing 312000, China
| | - Zhiyong Zhao
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China.
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Hadders‐Algra M. Emerging signs of autism spectrum disorder in infancy: Putative neural substrate. Dev Med Child Neurol 2022; 64:1344-1350. [PMID: 35801808 PMCID: PMC9796067 DOI: 10.1111/dmcn.15333] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 06/06/2022] [Accepted: 06/07/2022] [Indexed: 12/30/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by altered development of the social brain with prominent atypical features in the fronto-temporo-parietal cortex and cerebellum. Early signs of ASD emerge between 6 and 12 months: reduced social communication, slightly less advanced motor development, and repetitive behaviour. The fronto-temporo-parietal cortex and cerebellum play a prominent role in the development of social communication, whereas fronto-parietal-cerebellar networks are involved in the planning of movements, that is, movement selection. Atypical sensory responsivity, a core feature of ASD, may result in impaired development of social communication and motor skills and/or selection of atypical repetitive behaviour. In the first postnatal year, the brain areas involved are characterized by gradual dissolution of temporary structures: the fronto-temporo-parietal cortical subplate and cerebellar external granular layer. It is hypothesized that altered dissolution of the transient structures opens the window for the expression of early signs of ASD arising in the impaired developing permanent networks. WHAT THIS PAPER ADDS: The early social and motor signs of autism spectrum disorder emerge between the ages of 6 and 12 months. Altered dissolution of transient brain structures in the fronto-temporo-parietal cortex and cerebellum may underlie the emergence of these early signs.
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Affiliation(s)
- Mijna Hadders‐Algra
- University of Groningen, University Medical Center GroningenDepartment of Paediatrics, Section of Developmental NeurologyGroningenthe Netherlands,University of Groningen, Faculty of Theology and Religious StudiesGroningenthe Netherlands
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Carey C, Singh N, Dunn JT, Sementa T, Mendez MA, Velthuis H, Pereira AC, Pretzsch CM, Horder J, Hader S, Lythgoe DJ, Rotaru DG, Gee A, Cash D, Veronese M, Murphy D, McAlonan G. From bench to bedside: The mGluR5 system in people with and without Autism Spectrum Disorder and animal model systems. Transl Psychiatry 2022; 12:395. [PMID: 36127322 DOI: 10.1038/s41398-022-02143-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 08/19/2022] [Accepted: 09/01/2022] [Indexed: 11/08/2022] Open
Abstract
The metabotropic glutamate receptor 5 (mGluR5) is a key regulator of excitatory (E) glutamate and inhibitory (I) γ-amino butyric acid (GABA) signalling in the brain. Despite the close functional ties between mGluR5 and E/I signalling, no-one has directly examined the relationship between mGluR5 and glutamate or GABA in vivo in the human brain of autistic individuals. We measured [18F] FPEB (18F-3-fluoro-5-[(pyridin-3-yl)ethynyl]benzonitrile) binding in 15 adults (6 with Autism Spectrum Disorder) using two regions of interest, the left dorsomedial prefrontal cortex and a region primarily composed of left striatum and thalamus. These two regions were mapped out using MEGA-PRESS voxels and then superimposed on reconstructed PET images. This allowed for direct comparison between mGluR5, GABA + and Glx. To better understand the molecular underpinnings of our results we used an autoradiography study of mGluR5 in three mouse models associated with ASD: Cntnap2 knockout, Shank3 knockout, and 16p11.2 deletion. Autistic individuals had significantly higher [18F] FPEB binding (t (13) = -2.86, p = 0.047) in the left striatum/thalamus region of interest as compared to controls. Within this region, there was a strong negative correlation between GABA + and mGluR5 density across the entire cohort (Pearson's correlation: r (14) = -0.763, p = 0.002). Cntnap2 KO mice had significantly higher mGlu5 receptor binding in the striatum (caudate-putamen) as compared to wild-type (WT) mice (n = 15, p = 0.03). There were no differences in mGluR5 binding for mice with the Shank3 knockout or 16p11.2 deletion. Given that Cntnap2 is associated with a specific striatal deficit of parvalbumin positive GABA interneurons and 'autistic' features, our findings suggest that an increase in mGluR5 in ASD may relate to GABAergic interneuron abnormalities.
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Nees F, Banaschewski T, Bokde ALW, Desrivières S, Grigis A, Garavan H, Gowland P, Grimmer Y, Heinz A, Brühl R, Isensee C, Becker A, Martinot JL, Paillère Martinot ML, Artiges E, Papadopoulos Orfanos D, Lemaître H, Stringaris A, van Noort B, Paus T, Penttilä J, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Poustka L. Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence. Brain Sci 2022; 12:1187. [PMID: 36138923 PMCID: PMC9496772 DOI: 10.3390/brainsci12091187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/17/2022] [Accepted: 08/23/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.
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Affiliation(s)
- Frauke Nees
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, 24118 Kiel, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L. W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Sylvane Desrivières
- Institute of Psychiatry, Psychology & Neuroscience, Centre for Population Neuroscience and Precision Medicine (PONS), SGDP Centre, King’s College London, London WC2R 2LS, UK
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT 05405, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2QL, UK
| | - Yvonne Grimmer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM and Berlin Institute of Health, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), 38116 Braunschweig, Germany
| | - Corinna Isensee
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Andreas Becker
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, 91190 Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, 91190 Gif-sur-Yvette, France
- Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, AP-HP Sorbonne Université, 75013 Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, 91190 Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Gif-sur-Yvette, 91150 Etampes, France
| | | | - Hervé Lemaître
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, 33076 Bordeaux, France
| | - Argyris Stringaris
- National Institute of Mental Health/NIH, 15K North Drive, Bethesda, MD 20892, USA
| | - Betteke van Noort
- MSB Medical School Berlin, Hochschule für Gesundheit und Medizin, Siemens Villa, 14197 Berlin, Germany
| | - Tomáš Paus
- Departments of Psychology, University of Toronto, Toronto, ON M5T 2S8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 2S8, Canada
| | - Jani Penttilä
- CanadaDepartment of Social and Health Care, Psychosocial Services Adolescent Outpatient Clinic Kauppakatu 14, 15140 Lahti, Finland
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry, Neuroimaging Center, Technische Universität Dresden, 01069 Dresden, Germany
| | - Michael N. Smolka
- School of Psychology, Global Brain Health Institute, Trinity College Dublin, Dublin 2, Ireland
| | - Henrik Walter
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Robert Whelan
- School of Psychology, Global Brain Health Institute, Trinity College Dublin, Dublin 2, Ireland
| | - Gunter Schumann
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
- PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, 10117 Berlin, Germany
- Leibniz Institute for Neurobiology, 39118 Magdeburg, Germany
- Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai 200437, China
| | - Luise Poustka
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 “Trajectoires Développementales en Psychiatrie”, Université Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS, Centre Borelli, 91190 Gif-sur-Yvette, France
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10
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Okada NJ, Liu J, Tsang T, Nosco E, McDonald N, Cummings KK, Jung J, Patterson G, Bookheimer SY, Green SA, Jeste SS, Dapretto M. Atypical cerebellar functional connectivity at 9 months of age predicts delayed socio-communicative profiles in infants at high and low risk for autism. J Child Psychol Psychiatry 2022; 63:1002-1016. [PMID: 34882790 PMCID: PMC9177892 DOI: 10.1111/jcpp.13555] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/02/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND While the cerebellum is traditionally known for its role in sensorimotor control, emerging research shows that particular subregions, such as right Crus I (RCrusI), support language and social processing. Indeed, cerebellar atypicalities are commonly reported in autism spectrum disorder (ASD), a neurodevelopmental disorder characterized by socio-communicative impairments. However, the cerebellum's contribution to early socio-communicative development remains virtually unknown. METHODS Here, we characterized functional connectivity within cerebro-cerebellar networks implicated in language/social functions in 9-month-old infants who exhibit distinct 3-year socio-communicative developmental profiles. We employed a data-driven clustering approach to stratify our sample of infants at high (n = 82) and low (n = 37) familial risk for ASD into three cohorts-Delayed, Late-Blooming, and Typical-who showed unique socio-communicative trajectories. We then compared the cohorts on indices of language and social development. Seed-based functional connectivity analyses with RCrusI were conducted on infants with fMRI data (n = 66). Cohorts were compared on connectivity estimates from a-priori regions, selected on the basis of reported coactivation with RCrusI during language/social tasks. RESULTS The three trajectory-based cohorts broadly differed in social communication development, as evidenced by robust differences on numerous indices of language and social skills. Importantly, at 9 months, the cohorts showed striking differences in cerebro-cerebellar circuits implicated in language/social functions. For all regions examined, the Delayed cohort exhibited significantly weaker RCrusI connectivity compared to both the Late-Blooming and Typical cohorts, with no significant differences between the latter cohorts. CONCLUSIONS We show that hypoconnectivity within distinct cerebro-cerebellar networks in infancy predicts altered socio-communicative development before delays overtly manifest, which may be relevant for early detection and intervention. As the cerebellum is implicated in prediction, our findings point to probabilistic learning as a potential intermediary mechanism that may be disrupted in infancy, cascading into alterations in social communication.
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Affiliation(s)
- Nana J. Okada
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Janelle Liu
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Tawny Tsang
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Erin Nosco
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Nicole McDonald
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Kaitlin K. Cummings
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Jiwon Jung
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Genevieve Patterson
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Susan Y. Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Shulamite A. Green
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
| | - Shafali S. Jeste
- Children’s Hospital Los Angeles, USC Keck School of Medicine, Los Angeles
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles
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11
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Jensen AR, Lane AL, Werner BA, McLees SE, Fletcher TS, Frye RE. Modern Biomarkers for Autism Spectrum Disorder: Future Directions. Mol Diagn Ther 2022; 26:483-495. [PMID: 35759118 PMCID: PMC9411091 DOI: 10.1007/s40291-022-00600-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2022] [Indexed: 11/19/2022]
Abstract
Autism spectrum disorder is an increasingly prevalent neurodevelopmental disorder in the world today, with an estimated 2% of the population being affected in the USA. A major complicating factor in diagnosing, treating, and understanding autism spectrum disorder is that defining the disorder is solely based on the observation of behavior. Thus, recent research has focused on identifying specific biological abnormalities in autism spectrum disorder that can provide clues to diagnosis and treatment. Biomarkers are an objective way to identify and measure biological abnormalities for diagnostic purposes as well as to measure changes resulting from treatment. This current opinion paper discusses the state of research of various biomarkers currently in development for autism spectrum disorder. The types of biomarkers identified include prenatal history, genetics, neurological including neuroimaging, neurophysiologic, and visual attention, metabolic including abnormalities in mitochondrial, folate, trans-methylation, and trans-sulfuration pathways, immune including autoantibodies and cytokine dysregulation, autonomic nervous system, and nutritional. Many of these biomarkers have promising preliminary evidence for prenatal and post-natal pre-symptomatic risk assessment, confirmation of diagnosis, subtyping, and treatment response. However, most biomarkers have not undergone validation studies and most studies do not investigate biomarkers with clinically relevant comparison groups. Although the field of biomarker research in autism spectrum disorder is promising, it appears that it is currently in the early stages of development.
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Affiliation(s)
- Amanda R Jensen
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA
| | - Alison L Lane
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA
| | - Brianna A Werner
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA
| | - Sallie E McLees
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA
| | - Tessa S Fletcher
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA.,Department of Child Health, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, USA
| | - Richard E Frye
- Section on Neurodevelopmental Disorders, Barrow Neurological Institute at Phoenix Children's Hospital, 1919 E Thomas Rd, Phoenix, AZ, 85016, USA.
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12
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Ayoub MJ, Keegan L, Tager-Flusberg H, Gill SV. Neuroimaging Techniques as Descriptive and Diagnostic Tools for Infants at Risk for Autism Spectrum Disorder: A Systematic Review. Brain Sci 2022; 12:602. [PMID: 35624989 PMCID: PMC9139416 DOI: 10.3390/brainsci12050602] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 02/04/2023] Open
Abstract
Autism Spectrum Disorder (ASD) has traditionally been evaluated and diagnosed via behavioral assessments. However, increasing research suggests that neuroimaging as early as infancy can reliably identify structural and functional differences between autistic and non-autistic brains. The current review provides a systematic overview of imaging approaches used to identify differences between infants at familial risk and without risk and predictive biomarkers. Two primary themes emerged after reviewing the literature: (1) neuroimaging methods can be used to describe structural and functional differences between infants at risk and infants not at risk for ASD (descriptive), and (2) neuroimaging approaches can be used to predict ASD diagnosis among high-risk infants and developmental outcomes beyond infancy (predicting later diagnosis). Combined, the articles highlighted that several neuroimaging studies have identified a variety of neuroanatomical and neurological differences between infants at high and low risk for ASD, and among those who later receive an ASD diagnosis. Incorporating neuroimaging into ASD evaluations alongside traditional behavioral assessments can provide individuals with earlier diagnosis and earlier access to supportive resources.
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Affiliation(s)
- Maria J. Ayoub
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Laura Keegan
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA;
| | - Simone V. Gill
- College of Health and Rehabilitation Sciences: Sargent College, Boston University, 635 Commonwealth Avenue, Boston, MA 02215, USA; (M.J.A.); (L.K.)
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13
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Seng GJ, Lai MC, Goh JOS, Tseng WYI, Gau SSF. Gray matter volume alteration is associated with insistence on sameness and cognitive flexibility in autistic youth. Autism Res 2022; 15:1209-1221. [PMID: 35491911 DOI: 10.1002/aur.2732] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 02/08/2022] [Accepted: 02/22/2022] [Indexed: 11/08/2022]
Abstract
Restricted and repetitive behaviors (RRBs) are hallmark characteristics of autism spectrum disorder (ASD). Previous studies suggest that insistence on sameness (IS) characterized as higher-order RRBs may be a promising subgrouping variable for ASD. Cognitive inflexibility may underpin IS behaviors. However, the neuroanatomical correlates of IS and associated cognitive functions remain unclear. We analyzed data from 140 autistic youth and 124 typically developing (TD) youth (mean age = 15.8 years). Autistic youth were stratified by median-split based on three current IS items in the autism diagnostic interview-revised into two groups (high, HIS, n = 70, and low, LIS, n = 70). Differences in cognitive flexibility were assessed by the Cambridge neuropsychological test automated battery (CANTAB). T1-weighted brain structural images were analyzed using voxel-based morphometry (VBM) to identify differences in gray matter (GM) volume among the three groups. GM volume of regions showing group differences was then correlated with cognitive flexibility. The HIS group showed decreased GM volumes in the left supramarginal gyrus compared to the LIS group and increased GM volumes in the vermis VIII and left cerebellar lobule VIII compared to TD individuals. We did not find significant correlations between regional GM volumes and extra-dimensional shift errors. IS may be a unique RRB component and a potentially valuable stratifier of ASD. However, the neurocognitive underpinnings require further clarification. LAY SUMMARY: The present study found parietal, temporal and cerebellar gray matter volume alterations in autistic youth with greater insistence on sameness. The findings suggest that insistence on sameness may be a useful feature to parse the heterogeneity of the autism spectrum yet further research investigating the underlying neurocognitive mechanism is warranted.
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Affiliation(s)
- Guan-Jye Seng
- Department of Psychiatry, National Taiwan University Hospital & College of Medicine, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Meng-Chuan Lai
- Department of Psychiatry, National Taiwan University Hospital & College of Medicine, Taipei, Taiwan.,The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry and Autism Research Unit, The Hospital for Sick Children, Toronto, Canada.,Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Canada.,Department of Psychiatry, Autism Research Centre, University of Cambridge, Cambridge, UK
| | - Joshua Oon Soo Goh
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan.,Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan
| | - Wen-Yih Issac Tseng
- College of Medicine, Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan
| | - Susan Shur-Fen Gau
- Department of Psychiatry, National Taiwan University Hospital & College of Medicine, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan.,Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan
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14
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Shiohama T, Ortug A, Warren JLA, Valli B, Levman J, Faja SK, Tsujimura K, Maunakea AK, Takahashi E. Small Nucleus Accumbens and Large Cerebral Ventricles in Infants and Toddlers Prior to Receiving Diagnoses of Autism Spectrum Disorder. Cereb Cortex 2022; 32:1200-1211. [PMID: 34455432 PMCID: PMC8924432 DOI: 10.1093/cercor/bhab283] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/17/2021] [Accepted: 07/18/2021] [Indexed: 11/14/2022] Open
Abstract
Early interventions for autism spectrum disorder (ASD) are increasingly available, while only 42-50% of ASD children are diagnosed before 3 years old (YO). To identify neuroimaging biomarkers for early ASD diagnosis, we evaluated surface- and voxel-based brain morphometry in participants under 3YO who were later diagnosed with ASD. Magnetic resonance imaging data were retrospectively obtained from patients later diagnosed with ASD at Boston Children's Hospital. The ASD participants with comorbidities such as congenital disorder, epilepsy, and global developmental delay/intellectual disability were excluded from statistical analyses. Eighty-five structural brain magnetic resonance imaging images were collected from 81 participants under 3YO and compared with 45 images from 45 gender- and age-matched nonautistic controls (non-ASD). Using an Infant FreeSurfer pipeline, 236 regionally distributed measurements were extracted from each scan. By t-tests and linear mixed models, the smaller nucleus accumbens and larger bilateral lateral, third, and fourth ventricles were identified in the ASD group. Vertex-wise t-statistical maps showed decreased thickness in the caudal anterior cingulate cortex and increased thickness in the right medial orbitofrontal cortex in ASD. The smaller bilateral accumbens nuclei and larger cerebral ventricles were independent of age, gender, or gestational age at birth, suggesting that there are MRI-based biomarkers in prospective ASD patients before they receive the diagnosis and that the volume of the nucleus accumbens and cerebral ventricles can be key MRI-based early biomarkers to predict the emergence of ASD.
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Affiliation(s)
- Tadashi Shiohama
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Department of Pediatrics, Chiba University Hospital, Chiba 2608670, Japan
| | - Alpen Ortug
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Jose Luis Alatorre Warren
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Briana Valli
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Behavioral Neuroscience Program, Northeastern University, Boston, MA 02115, USA
| | - Jacob Levman
- Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia B2G 2W5, Canada
| | - Susan K Faja
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Keita Tsujimura
- Group of Brain Function and Development, Nagoya University Neuroscience Institute of the Graduate School of Science, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan.,Research Unit for Developmental Disorders, Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602, Japan
| | - Alika K Maunakea
- Department of Anatomy, Biochemistry and Physiology, 651 Ilalo Street, John A. Burns School of Medicine, University of Hawaii, Manoa, HI 96813, USA
| | - Emi Takahashi
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
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15
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Tian J, Gao X, Yang L. Repetitive Restricted Behaviors in Autism Spectrum Disorder: From Mechanism to Development of Therapeutics. Front Neurosci 2022; 16:780407. [PMID: 35310097 PMCID: PMC8924045 DOI: 10.3389/fnins.2022.780407] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 02/09/2022] [Indexed: 01/28/2023] Open
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by deficits in social communication, social interaction, and repetitive restricted behaviors (RRBs). It is usually detected in early childhood. RRBs are behavioral patterns characterized by repetition, inflexibility, invariance, inappropriateness, and frequent lack of obvious function or specific purpose. To date, the classification of RRBs is contentious. Understanding the potential mechanisms of RRBs in children with ASD, such as neural connectivity disorders and abnormal immune functions, will contribute to finding new therapeutic targets. Although behavioral intervention remains the most effective and safe strategy for RRBs treatment, some promising drugs and new treatment options (e.g., supplementary and cell therapy) have shown positive effects on RRBs in recent studies. In this review, we summarize the latest advances of RRBs from mechanistic to therapeutic approaches and propose potential future directions in research on RRBs.
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16
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Clairmont C, Wang J, Tariq S, Sherman HT, Zhao M, Kong XJ. The Value of Brain Imaging and Electrophysiological Testing for Early Screening of Autism Spectrum Disorder: A Systematic Review. Front Neurosci 2022; 15:812946. [PMID: 35185452 PMCID: PMC8851356 DOI: 10.3389/fnins.2021.812946] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/09/2021] [Indexed: 11/13/2022] Open
Abstract
Given the significance of validating reliable tests for the early detection of autism spectrum disorder (ASD), this systematic review aims to summarize available evidence of neuroimaging and neurophysiological changes in high-risk infants to improve ASD early diagnosis. We included peer-reviewed, primary research in English published before May 21, 2021, involving the use of magnetic resonance imaging (MRI), electroencephalogram (EEG), or functional near-infrared spectroscopy (fNIRS) in children with high risk for ASD under 24 months of age. The main exclusion criteria includes diagnosis of a genetic disorder and gestation age of less the 36 weeks. Online research was performed on PubMed, Web of Science, PsycINFO, and CINAHL. Article selection was conducted by two reviewers to minimize bias. This research was funded by Massachusetts General Hospital Sundry funding. IRB approval was not submitted as it was deemed unnecessary. We included 75 primary research articles. Studies showed that high-risk infants had divergent developmental trajectories for fractional anisotropy and regional brain volumes, increased CSF volume, and global connectivity abnormalities on MRI, decreased sensitivity for familiar faces, atypical lateralization during facial and auditory processing, and different spectral powers across multiple band frequencies on EEG, and distinct developmental trajectories in functional connectivity and regional oxyhemoglobin concentrations in fNIRS. These findings in infants were found to be correlated with the core ASD symptoms and diagnosis at toddler age. Despite the lack of quantitative analysis of the research database, neuroimaging and electrophysiological biomarkers have promising value for the screening of ASD as early as infancy with high accuracy, which warrants further investigation.
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Affiliation(s)
- Cullen Clairmont
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Jiuju Wang
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China
| | - Samia Tariq
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Hannah Tayla Sherman
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
| | - Mingxuan Zhao
- Department of Business Analytics, Bentley University, Waltham, MA, United States
| | - Xue-Jun Kong
- Synapse Lab, Athinoula A. Martinos Center, Massachusetts General Hospital, Boston, MA, United States
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
- *Correspondence: Xue-Jun Kong,
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17
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Qin Y, Du Y, Chen L, Liu Y, Xu W, Liu Y, Li Y, Leng J, Wang Y, Zhang XY, Feng J, Zhang F, Jin L, Qiu Z, Gong X, Wang H. A recurrent SHANK1 mutation implicated in autism spectrum disorder causes autistic-like core behaviors in mice via downregulation of mGluR1-IP3R1-calcium signaling. Mol Psychiatry 2022; 27:2985-98. [PMID: 35388181 DOI: 10.1038/s41380-022-01539-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 03/09/2022] [Accepted: 03/21/2022] [Indexed: 12/27/2022]
Abstract
The genetic etiology and underlying mechanism of autism spectrum disorder (ASD) remain elusive. SHANK family genes (SHANK1/2/3) are well known ASD-related genes. However, little is known about how SHANK missense mutations contribute to ASD. Here, we aimed to clarify the molecular mechanism of and the multilevel neuropathological features induced by Shank1 mutations in knock-in (KI) mice. In this study, by sequencing the SHANK1 gene in a cohort of 615 ASD patients and 503 controls, we identified an ASD-specific recurrent missense mutation, c.2621 G > A (p.R874H). This mutation demonstrated strong pathogenic potential in in vitro experiments, and we generated the corresponding Shank1 R882H-KI mice. Shank1 R882H-KI mice displayed core symptoms of ASD, namely, social disability and repetitive behaviors, without confounding comorbidities of abnormal motor function and heightened anxiety. Brain structural changes in the frontal cortex, hippocampus and cerebellar cortex were observed in Shank1 R882H-KI mice via structural magnetic resonance imaging. These key brain regions also showed severe and consistent downregulation of mGluR1-IP3R1-calcium signaling, which subsequently affected the release of intracellular calcium. Corresponding cellular structural and functional changes were present in Shank1 R882H-KI mice, including decreased spine size, reduced spine density, abnormal morphology of postsynaptic densities, and impaired hippocampal long-term potentiation and basal excitatory transmission. These findings demonstrate the causative role of SHANK1 in ASD and elucidate the underlying biological mechanism of core symptoms of ASD. We also provide a reliable model of ASD with core symptoms for future studies, such as biomarker identification and therapeutic intervention studies.
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18
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Díaz-Caneja CM, State MW, Hagerman RJ, Jacquemont S, Marín O, Bagni C, Umbricht D, Simonoff E, de Andrés-Trelles F, Kaale A, Pandina G, Gómez-Mancilla B, Wang PP, Cusak J, Siafis S, Leucht S, Parellada M, Loth E, Charman T, Buitelaar JK, Murphy D, Arango C. A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders. Eur Neuropsychopharmacol 2021; 48:49-88. [PMID: 33781629 DOI: 10.1016/j.euroneuro.2021.02.020] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 02/08/2021] [Accepted: 02/15/2021] [Indexed: 12/20/2022]
Abstract
In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the 'New Frontiers Meeting' on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies.
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19
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Pretzsch CM, Floris DL, Voinescu B, Elsahib M, Mendez MA, Wichers R, Ajram L, Ivin G, Heasman M, Pretzsch E, Williams S, Murphy DGM, Daly E, McAlonan GM. Modulation of striatal functional connectivity differences in adults with and without autism spectrum disorder in a single-dose randomized trial of cannabidivarin. Mol Autism 2021; 12:49. [PMID: 34210360 PMCID: PMC8252312 DOI: 10.1186/s13229-021-00454-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 06/17/2021] [Indexed: 11/17/2022] Open
Abstract
Background Autism spectrum disorder (ASD) has a high cost to affected individuals and society, but treatments for core symptoms are lacking. To expand intervention options, it is crucial to gain a better understanding of potential treatment targets, and their engagement, in the brain. For instance, the striatum (caudate, putamen, and nucleus accumbens) plays a central role during development and its (atypical) functional connectivity (FC) may contribute to multiple ASD symptoms. We have previously shown, in the adult autistic and neurotypical brain, the non-intoxicating cannabinoid cannabidivarin (CBDV) alters the balance of striatal ‘excitatory–inhibitory’ metabolites, which help regulate FC, but the effects of CBDV on (atypical) striatal FC are unknown. Methods To examine this in a small pilot study, we acquired resting state functional magnetic resonance imaging data from 28 men (15 neurotypicals, 13 ASD) on two occasions in a repeated-measures, double-blind, placebo-controlled study. We then used a seed-based approach to (1) compare striatal FC between groups and (2) examine the effect of pharmacological probing (600 mg CBDV/matched placebo) on atypical striatal FC in ASD. Visits were separated by at least 13 days to allow for drug washout. Results Compared to the neurotypicals, ASD individuals had lower FC between the ventral striatum and frontal and pericentral regions (which have been associated with emotion, motor, and vision processing). Further, they had higher intra-striatal FC and higher putamenal FC with temporal regions involved in speech and language. In ASD, CBDV reduced hyperconnectivity to the neurotypical level. Limitations Our findings should be considered in light of several methodological aspects, in particular our participant group (restricted to male adults), which limits the generalizability of our findings to the wider and heterogeneous ASD population. Conclusion In conclusion, here we show atypical striatal FC with regions commonly associated with ASD symptoms. We further provide preliminary proof of concept that, in the adult autistic brain, acute CBDV administration can modulate atypical striatal circuitry towards neurotypical function. Future studies are required to determine whether modulation of striatal FC is associated with a change in ASD symptoms. Trial registration clinicaltrials.gov, Identifier: NCT03537950. Registered May 25th, 2018—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03537950?term=NCT03537950&draw=2&rank=1. Supplementary Information The online version contains supplementary material available at 10.1186/s13229-021-00454-6.
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Affiliation(s)
- Charlotte M Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Bogdan Voinescu
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Department of Liaison Psychiatry, Bristol Royal Infirmary, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK
| | - Malka Elsahib
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Maria A Mendez
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Robert Wichers
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Department of Psychiatry GGZ Geest, Amsterdam, The Netherlands
| | - Laura Ajram
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK.,Medicines Discovery Catapult, Alderley Park, Alderley Edge, SK10 4TG, Cheshire, UK
| | - Glynis Ivin
- South London and Maudsley NHS Foundation Trust Pharmacy, London, UK
| | - Martin Heasman
- South London and Maudsley NHS Foundation Trust Pharmacy, London, UK
| | - Elise Pretzsch
- Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Steven Williams
- Department of Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AF, UK
| | - Gráinne M McAlonan
- 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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20
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Nair A, Jalal R, Liu J, Tsang T, McDonald NM, Jackson L, Ponting C, Jeste SS, Bookheimer SY, Dapretto M. Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder. Cereb Cortex 2021; 31:4191-4205. [PMID: 33866373 DOI: 10.1093/cercor/bhab078] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.
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Affiliation(s)
- Aarti Nair
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92354, USA
| | - Rhideeta Jalal
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Janelle Liu
- Interdepartmental Neuroscience Program, University of California, Los Angeles, CA 90095, USA
| | - Tawny Tsang
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Nicole M McDonald
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Lisa Jackson
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Carolyn Ponting
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Shafali S Jeste
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
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21
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Li X, Zhang K, He X, Zhou J, Jin C, Shen L, Gao Y, Tian M, Zhang H. Structural, Functional, and Molecular Imaging of Autism Spectrum Disorder. Neurosci Bull 2021; 37:1051-1071. [PMID: 33779890 DOI: 10.1007/s12264-021-00673-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 12/20/2020] [Indexed: 12/21/2022] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder associated with both genetic and environmental risks. Neuroimaging approaches have been widely employed to parse the neurophysiological mechanisms underlying ASD, and provide critical insights into the anatomical, functional, and neurochemical changes. We reviewed recent advances in neuroimaging studies that focused on ASD by using magnetic resonance imaging (MRI), positron emission tomography (PET), or single-positron emission tomography (SPECT). Longitudinal structural MRI has delineated an abnormal developmental trajectory of ASD that is associated with cascading neurobiological processes, and functional MRI has pointed to disrupted functional neural networks. Meanwhile, PET and SPECT imaging have revealed that metabolic and neurotransmitter abnormalities may contribute to shaping the aberrant neural circuits of ASD. Future large-scale, multi-center, multimodal investigations are essential to elucidate the neurophysiological underpinnings of ASD, and facilitate the development of novel diagnostic biomarkers and better-targeted therapy.
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Affiliation(s)
- Xiaoyi Li
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China
| | - Kai Zhang
- Laboratory for Pathophysiological and Health Science, RIKEN Center for Biosystems Dynamics Research, Hyogo, 650-0047, Japan
| | - Xiao He
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China
| | - Jinyun Zhou
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China
| | - Chentao Jin
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China
| | - Lesang Shen
- Department of Surgical Oncology, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Yuanxue Gao
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China
| | - Mei Tian
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China.
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China.
| | - Hong Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China.
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China.
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, 310027, China.
- Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China.
- The College of Biomedical Engineering and Instrument Science of Zhejiang University, Hangzhou, 310027, China.
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22
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Hiremath CS, Sagar KJV, Yamini BK, Girimaji AS, Kumar R, Sravanti SL, Padmanabha H, Vykunta Raju KN, Kishore MT, Jacob P, Saini J, Bharath RD, Seshadri SP, Kumar M. Emerging behavioral and neuroimaging biomarkers for early and accurate characterization of autism spectrum disorders: a systematic review. Transl Psychiatry 2021; 11:42. [PMID: 33441539 PMCID: PMC7806884 DOI: 10.1038/s41398-020-01178-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/19/2020] [Accepted: 12/01/2020] [Indexed: 01/29/2023] Open
Abstract
The possibility of early treatment and a better outcome is the direct product of early identification and characterization of any pathological condition. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in social communication, restricted, and repetitive patterns of behavior. In recent times, various tools and methods have been developed for the early identification and characterization of ASD features as early as 6 months of age. Thorough and exhaustive research has been done to identify biomarkers in ASD using noninvasive neuroimaging and various molecular methods. By employing advanced assessment tools such as MRI and behavioral assessment methods for accurate characterization of the ASD features and may facilitate pre-emptive interventional and targeted therapy programs. However, the application of advanced quantitative MRI methods is still confined to investigational/laboratory settings, and the clinical implication of these imaging methods in personalized medicine is still in infancy. Longitudinal research studies in neurodevelopmental disorders are the need of the hour for accurate characterization of brain-behavioral changes that could be monitored over a period of time. These findings would be more reliable and consistent with translating into the clinics. This review article aims to focus on the recent advancement of early biomarkers for the characterization of ASD features at a younger age using behavioral and quantitative MRI methods.
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Affiliation(s)
- Chandrakanta S Hiremath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Kommu John Vijay Sagar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - B K Yamini
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Akhila S Girimaji
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Raghavendra Kumar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Sanivarapu Lakshmi Sravanti
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Hansashree Padmanabha
- Department of Neurology, National Institute of Mental Health and Neuroscience, Bengaluru, India
| | - K N Vykunta Raju
- Department of Pediatric Neurology, Indira Gandhi Institute of Child Health, Bengaluru, India
| | - M Thomas Kishore
- Department of Clinical Psychology, National Institute of Mental Health and Neuroscience, Bengaluru, India
| | - Preeti Jacob
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Rose D Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Shekhar P Seshadri
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India.
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23
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Molnar-Szakacs I, Kupis L, Uddin LQ. Neuroimaging Markers of Risk and Pathways to Resilience in Autism Spectrum Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging 2021; 6:200-10. [PMID: 32839155 DOI: 10.1016/j.bpsc.2020.06.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 06/04/2020] [Accepted: 06/28/2020] [Indexed: 01/22/2023]
Abstract
Autism spectrum disorder is a complex, heterogeneous neurodevelopmental condition of largely unknown etiology. This heterogeneity of symptom presentation, combined with high rates of comorbidity with other developmental disorders and a lack of reliable biomarkers, makes diagnosing and evaluating life outcomes for individuals with autism spectrum disorder a challenge. We review the growing literature on neuroimaging-based biomarkers of risk for the development of autism and explore evidence for resilience in some autistic individuals. The current literature suggests that neuroimaging during early infancy, in combination with prebirth and early genetic studies, is a promising tool for identifying biomarkers of risk, while studies of gene expression and DNA methylation have provided some key insights into mechanisms of resilience. With genetics and the environment contributing to both risk for the development of autism spectrum disorder and conditions for resilience, additional studies are needed to understand how risk and resilience interact mechanistically, whereby factors of risk may engender conditions for adaptation. Future studies should prioritize longitudinal designs in global cohorts, with the involvement of the autism community as partners in research to help identify domains of functioning that hold value and importance to the community.
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24
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Zhang W, Sweeney JA, Yao L, Li S, Zeng J, Xu M, Tallman MJ, Gong Q, DelBello MP, Lui S, Nery FG. Brain structural correlates of familial risk for mental illness: a meta-analysis of voxel-based morphometry studies in relatives of patients with psychotic or mood disorders. Neuropsychopharmacology 2020; 45:1369-79. [PMID: 32353861 DOI: 10.1038/s41386-020-0687-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 04/19/2020] [Accepted: 04/22/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.
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Abstract
PURPOSE OF REVIEW Impairments in social interaction/communication become apparent after 12 months of age in children who develop Autism spectrum disorder (ASD). Studies of baby siblings of children with ASD provide the means to detect changes in the brain that are present before behavioral symptoms appear. In this review, advances from brain imaging studies of infant siblings over the past 18 months are highlighted. RECENT FINDINGS During the first 2 months of life, functional differences in social brain regions and microstructural differences in dorsal language tracks are found in some high-risk baby siblings. At 4-6 months of age, differences in subcortical and cerebellum volumes and atypical cortical responses to social stimuli are evident. At 6 months, extra-axial cerebrospinal fluid is increased, and at 8 months there is evidence of cortical hyper-reactivity. Patterns of functional connectivity are distinct in infant siblings and suggest dysfunctional activation and integration of information across the cortex and neural networks underlying social behaviors. SUMMARY Further replication in very large independent samples is needed to verify the majority of the findings discussed and understand how they are related within individual infants. Much more research is needed before translation to clinical practice.
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26
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Harris JC. Editorial: Advances in understanding self-determination, mindfulness approaches, and behavioral interventions, outcomes in autistic siblings and substance abuse in neurodevelopmental disorders. Curr Opin Psychiatry 2020; 33:77-80. [PMID: 31833948 DOI: 10.1097/YCO.0000000000000578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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27
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Douglas PS. Pre-emptive Intervention for Autism Spectrum Disorder: Theoretical Foundations and Clinical Translation. Front Integr Neurosci 2019; 13:66. [PMID: 31798425 PMCID: PMC6877903 DOI: 10.3389/fnint.2019.00066] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2019] [Accepted: 11/04/2019] [Indexed: 12/28/2022] Open
Abstract
Autism spectrum disorders (ASD) are an emergent public health problem, placing significant burden upon the individual, family and health system. ASD are polygenetic spectrum disorders of neural connectome development, in which one or more feedback loops amplify small genetic, structural, or functional variations in the very early development of motor and sensory-motor pathways. These perturbations trigger a 'butterfly effect' of unpredictable cascades of structural and functional imbalances in the global neuronal workspace, resulting in atypical behaviors, social communication, and cognition long-term. The first 100 days post-term are critically neuroplastic and comprise an injury-sensitive developmental window, characterized by a neural biomarker, the persistence of the cortical subplate, and a behavioral biomarker, the crying diathesis. By the time potential diagnostic signs are identified, from 6 months of age, ASD neuropathy is already entrenched. The International Society for Autism Research Special Interest Group has called for pre-emptive intervention, based upon rigorous theoretical frames, and real world translation and evaluation. This paper responds to that call. It synthesizes heterogenous evidence concerning ASD etiologies from both psychosocial and biological research literatures with complexity science and evolutionary biology, to propose a theoretical framework for pre-emptive intervention. This paper hypothesizes that environmental factors resulting from a mismatch between environment of evolutionary adaptedness and culture initiate or perpetuate early motor and sensory-motor lesions, triggering a butterfly effect of multi-directional cascades of atypical developmental in the complex adaptive system of the parent and ASD-susceptible infant. Chronic sympathetic nervous system/hypothalamic-pituitary-adrenal axis hyperarousal and disrupted parent-infant biobehavioral synchrony are the key biologic and behavioral mechanisms perpetuating these atypical developmental cascades. A clinical translation of this evidence is proposed, for application antenatally and in the first 6 months of life, as pre-emptive intervention for ASD.
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Affiliation(s)
- Pamela S Douglas
- Transforming Maternity Care Collaborative, Griffith University, Brisbane, QLD, Australia.,Discipline of General Practice, The University of Queensland, Brisbane, QLD, Australia
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28
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Abstract
Autism spectrum disorder (ASD) emerges during early childhood and is marked by a relatively narrow window in which infants transition from exhibiting normative behavioral profiles to displaying the defining features of the ASD phenotype in toddlerhood. Prospective brain imaging studies in infants at high familial risk for autism have revealed important insights into the neurobiology and developmental unfolding of ASD. In this article, we review neuroimaging studies of brain development in ASD from birth through toddlerhood, relate these findings to candidate neurobiological mechanisms, and discuss implications for future research and translation to clinical practice.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA.
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, The University of North Carolina at Chapel Hill School of Medicine, 101 Renee Lynne Court, Chapel Hill, NC 27599, USA
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