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Duan K, Eyler L, Pierce K, Lombardo MV, Datko M, Hagler DJ, Taluja V, Zahiri J, Campbell K, Barnes CC, Arias S, Nalabolu S, Troxel J, Ji P, Courchesne E. Differences in regional brain structure in toddlers with autism are related to future language outcomes. Nat Commun 2024; 15:5075. [PMID: 38871689 PMCID: PMC11176156 DOI: 10.1038/s41467-024-48952-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/20/2024] [Indexed: 06/15/2024] Open
Abstract
Language and social symptoms improve with age in some autistic toddlers, but not in others, and such outcome differences are not clearly predictable from clinical scores alone. Here we aim to identify early-age brain alterations in autism that are prognostic of future language ability. Leveraging 372 longitudinal structural MRI scans from 166 autistic toddlers and 109 typical toddlers and controlling for brain size, we find that, compared to typical toddlers, autistic toddlers show differentially larger or thicker temporal and fusiform regions; smaller or thinner inferior frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most differences are replicated in an independent cohort of 75 toddlers. These brain alterations improve accuracy for predicting language outcome at 6-month follow-up beyond intake clinical and demographic variables. Temporal, fusiform, and inferior frontal alterations are related to autism symptom severity and cognitive impairments at early intake ages. Among autistic toddlers, brain alterations in social, language and face processing areas enhance the prediction of the child's future language ability.
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Affiliation(s)
- Kuaikuai Duan
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA.
| | - Lisa Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, 92093, USA
- VISN 22 Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, 92161, USA
| | - Karen Pierce
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Michael V Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, 38068, Italy
| | - Michael Datko
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Donald J Hagler
- Center for Multimodal Imaging and Genetics, Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Vani Taluja
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Javad Zahiri
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Kathleen Campbell
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Cynthia Carter Barnes
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Steven Arias
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Srinivasa Nalabolu
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Jaden Troxel
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA
| | - Peng Ji
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Eric Courchesne
- Autism Center of Excellence, Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92037, USA.
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2
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Zhang X, Gao Y, Zhang Y, Li F, Li H, Lei F. Identification of Autism Spectrum Disorder Using Topological Data Analysis. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:1023-1037. [PMID: 38351222 PMCID: PMC11169318 DOI: 10.1007/s10278-024-01002-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/30/2023] [Accepted: 11/21/2023] [Indexed: 06/13/2024]
Abstract
Autism spectrum disorder (ASD) is a pervasive brain development disease. Recently, the incidence rate of ASD has increased year by year and posed a great threat to the lives and families of individuals with ASD. Therefore, the study of ASD has become very important. A suitable feature representation that preserves the data intrinsic information and also reduces data complexity is very vital to the performance of established models. Topological data analysis (TDA) is an emerging and powerful mathematical tool for characterizing shapes and describing intrinsic information in complex data. In TDA, persistence barcodes or diagrams are usually regarded as visual representations of topological features of data. In this paper, the Regional Homogeneity (ReHo) data of subjects obtained from Autism Brain Imaging Data Exchange (ABIDE) database were used to extract features by using TDA. The average accuracy of cross validation on ABIDE I database was 95.6% that was higher than any other existing methods (the highest accuracy among existing methods was 93.59%). The average accuracy for sampling with the same resolutions with the ABIDE I on the ABIDE II database was 96.5% that was also higher than any other existing methods (the highest accuracy among existing methods was 75.17%).
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Affiliation(s)
- Xudong Zhang
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China
| | - Yaru Gao
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China
| | - Yunge Zhang
- School of Biomedical Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Fengling Li
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China.
| | - Huanjie Li
- School of Biomedical Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Fengchun Lei
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China
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3
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Leyhausen J, Schäfer T, Gurr C, Berg LM, Seelemeyer H, Pretzsch CM, Loth E, Oakley B, Buitelaar JK, Beckmann CF, Floris DL, Charman T, Bourgeron T, Banaschewski T, Jones EJH, Tillmann J, Chatham C, Murphy DG, Ecker C. Differences in Intrinsic Gray Matter Connectivity and Their Genomic Underpinnings in Autism Spectrum Disorder. Biol Psychiatry 2024; 95:175-186. [PMID: 37348802 DOI: 10.1016/j.biopsych.2023.06.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 06/02/2023] [Accepted: 06/10/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Autism is a heterogeneous neurodevelopmental condition accompanied by differences in brain connectivity. Structural connectivity in autism has mainly been investigated within the white matter. However, many genetic variants associated with autism highlight genes related to synaptogenesis and axonal guidance, thus also implicating differences in intrinsic (i.e., gray matter) connections in autism. Intrinsic connections may be assessed in vivo via so-called intrinsic global and local wiring costs. METHODS Here, we examined intrinsic global and local wiring costs in the brain of 359 individuals with autism and 279 healthy control participants ages 6 to 30 years from the EU-AIMS LEAP (Longitudinal European Autism Project). FreeSurfer was used to derive surface mesh representations to compute the estimated length of connections required to wire the brain within the gray matter. Vertexwise between-group differences were assessed using a general linear model. A gene expression decoding analysis based on the Allen Human Brain Atlas was performed to link neuroanatomical differences to putative underpinnings. RESULTS Group differences in global and local wiring costs were predominantly observed in medial and lateral prefrontal brain regions, in inferior temporal regions, and at the left temporoparietal junction. The resulting neuroanatomical patterns were enriched for genes that had been previously implicated in the etiology of autism at genetic and transcriptomic levels. CONCLUSIONS Based on intrinsic gray matter connectivity, the current study investigated the complex neuroanatomy of autism and linked between-group differences to putative genomic and/or molecular mechanisms to parse the heterogeneity of autism and provide targets for future subgrouping approaches.
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Affiliation(s)
- Johanna Leyhausen
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany; Department of Biosciences, Goethe University Frankfurt, Frankfurt am Main, Germany.
| | - Tim Schäfer
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Caroline Gurr
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Lisa M Berg
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Hanna Seelemeyer
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany
| | - Charlotte M Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands; Methods of Plasticity Research, Department of Psychology, University of Zürich, Zurich, Switzerland
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Thomas Bourgeron
- Institut Pasteur, Human Genetics and Cognitive Functions Unit, Paris, France
| | - Tobias Banaschewski
- Child and Adolescent Psychiatry, Central Institute of Mental Health, University of Heidelberg, Medical Faculty Mannheim, Mannheim, Germany
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - Julian Tillmann
- F. Hoffmann-La Roche, Innovation Center Basel, Basel, Switzerland
| | - Chris Chatham
- F. Hoffmann-La Roche, Innovation Center Basel, Basel, Switzerland
| | - Declan G Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany; Brain Imaging Center, Goethe University, Frankfurt am Main, Germany; Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
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Louie AY, Rund LA, Komiyama-Kasai KA, Weisenberger KE, Stanke KL, Larsen RJ, Leyshon BJ, Kuchan MJ, Das T, Steelman AJ. A hydrolyzed lipid blend diet promotes myelination in neonatal piglets in a region and concentration-dependent manner. J Neurosci Res 2023; 101:1864-1883. [PMID: 37737490 DOI: 10.1002/jnr.25243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 08/11/2023] [Accepted: 09/04/2023] [Indexed: 09/23/2023]
Abstract
The impact of early life nutrition on myelin development is of interest given that cognitive and behavioral function depends on proper myelination. Evidence shows that myelination can be altered by dietary lipid, but most of these studies have been performed in the context of disease or impairment. Here, we assessed the effects of lipid blends containing various levels of a hydrolyzed fat (HF) system on myelination in healthy piglets. Piglets were sow-reared, fed a control diet, or a diet containing 12%, 25%, or 53% HF consisting of cholesterol, fatty acids, monoglycerides, and phospholipid from lecithin. At postnatal day 28/29, magnetic resonance imaging (MRI) was performed to assess changes to brain development, followed by brain collection for microscopic analyses of myelin in targeted regions using CLARITY tissue clearing, immunohistochemistry, and electron microscopy techniques. Sow-reared piglets exhibited the highest overall brain white matter volume by MRI. However, a 25% HF diet resulted in the greatest total myelin density in the prefrontal cortex based on 3D modeling analysis of myelinated filaments. Nodal gap length and g-ratio were inversely correlated with percentage of HF in the corpus callosum, as well as in the PFC and internal capsule for g-ratio, indicating that a 53% HF diet resulted in the thickest myelin per axon and a 0% HF control diet the thinnest in specific brain regions. These findings indicate that HF promoted myelination in the neonatal piglet in a region- and concentration-dependent manner.
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Affiliation(s)
- Allison Y Louie
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Laurie A Rund
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Karin A Komiyama-Kasai
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Kelsie E Weisenberger
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Kayla L Stanke
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Ryan J Larsen
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Department of Psychology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | | | | | - Tapas Das
- Abbott Nutrition, Columbus, Ohio, USA
| | - Andrew J Steelman
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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5
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Abbott N, Love T. Bridging the Divide: Brain and Behavior in Developmental Language Disorder. Brain Sci 2023; 13:1606. [PMID: 38002565 PMCID: PMC10670267 DOI: 10.3390/brainsci13111606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 11/14/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
Developmental language disorder (DLD) is a heterogenous neurodevelopmental disorder that affects a child's ability to comprehend and/or produce spoken and/or written language, yet it cannot be attributed to hearing loss or overt neurological damage. It is widely believed that some combination of genetic, biological, and environmental factors influences brain and language development in this population, but it has been difficult to bridge theoretical accounts of DLD with neuroimaging findings, due to heterogeneity in language impairment profiles across individuals and inconsistent neuroimaging findings. Therefore, the purpose of this overview is two-fold: (1) to summarize the neuroimaging literature (while drawing on findings from other language-impaired populations, where appropriate); and (2) to briefly review the theoretical accounts of language impairment patterns in DLD, with the goal of bridging the disparate findings. As will be demonstrated with this overview, the current state of the field suggests that children with DLD have atypical brain volume, laterality, and activation/connectivity patterns in key language regions that likely contribute to language difficulties. However, the precise nature of these differences and the underlying neural mechanisms contributing to them remain an open area of investigation.
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Affiliation(s)
- Noelle Abbott
- School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA 92182, USA;
- San Diego State University/University of California San Diego Joint Doctoral Program in Language and Communicative Disorders, San Diego, CA 92182, USA
| | - Tracy Love
- School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA 92182, USA;
- San Diego State University/University of California San Diego Joint Doctoral Program in Language and Communicative Disorders, San Diego, CA 92182, USA
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6
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DiPiero M, Cordash H, Prigge MB, King CK, Morgan J, Guerrero-Gonzalez J, Adluru N, King JB, Lange N, Bigler ED, Zielinski BA, Alexander AL, Lainhart JE, Dean DC. Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males. Front Neurosci 2023; 17:1231719. [PMID: 37829720 PMCID: PMC10565827 DOI: 10.3389/fnins.2023.1231719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 09/07/2023] [Indexed: 10/14/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males. Methods Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated. Results All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores. Conclusion Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.
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Affiliation(s)
- Marissa DiPiero
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Hassan Cordash
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
| | - Molly B. Prigge
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Carolyn K. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Jubel Morgan
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | | | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Jace B. King
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, United States
| | - Erin D. Bigler
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Psychiatry, University of Utah, Salt Lake City, UT, United States
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, United States
- Department of Neurology, University of California, Davis, Davis, CA, United States
| | - Brandon A. Zielinski
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Department of Pediatrics, University of Utah, Salt Lake City, UT, United States
- Departments of Pediatrics and Neurology, University of Florida, Gainesville, FL, United States
- McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
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7
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Rabelo LN, Queiroz JPG, Castro CCM, Silva SP, Campos LD, Silva LC, Nascimento EB, Martínez-Cerdeño V, Fiuza FP. Layer-Specific Changes in the Prefrontal Glia/Neuron Ratio Characterizes Patches of Gene Expression Disorganization in Children with Autism. J Autism Dev Disord 2023; 53:3648-3658. [PMID: 35704132 PMCID: PMC10084744 DOI: 10.1007/s10803-022-05626-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/25/2022] [Indexed: 10/18/2022]
Abstract
Autism spectrum disorder (ASD) is manifested by abnormal cell numbers and patches of gene expression disruption in higher-order brain regions. Here, we investigated whether layer-specific changes in glia/neuron ratios (GNR) characterize patches in the dorsolateral prefrontal cortex (DL-PFC) of children with ASD. We analyzed high-resolution digital images of postmortem human brains from 11 ASD and 11 non-ASD children obtained from the Autism Study of the Allen Human Brain Atlas. We found the GNR is overall reduced in the ASD DL-PFC. Moreover, layers II-III belonging to patches presented a lower GNR in comparison with layers V-VI. We here provide a new insight into how brain cells are arranged within patches that contributes to elucidate how neurodevelopmental programs are altered in ASD.
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Affiliation(s)
- Livia Nascimento Rabelo
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - José Pablo Gonçalves Queiroz
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Carla Cristina Miranda Castro
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Sayonara Pereira Silva
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Laura Damasceno Campos
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | - Larissa Camila Silva
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil
| | | | - Veronica Martínez-Cerdeño
- Department of Pathology and Laboratory Medicine, Institute for Pediatric Regenerative Medicine, Shriners Hospitals for Children of Northern California, MIND Institute, UC Davis Medical Center, Sacramento, CA, 95817, USA
| | - Felipe Porto Fiuza
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, RN, 59280-000, Brazil.
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8
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Dong Q, Li J, Ju Y, Xiao C, Li K, Shi B, Zheng W, Zhang Y. Altered Relationship between Functional Connectivity and Fiber-Bundle Structure in High-Functioning Male Adults with Autism Spectrum Disorder. Brain Sci 2023; 13:1098. [PMID: 37509029 PMCID: PMC10377258 DOI: 10.3390/brainsci13071098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/04/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterized by abnormalities in structure and function of the brain. However, how ASD affects the relationship between fiber-bundle microstructures and functional connectivity (FC) remains unclear. Here, we analyzed structural and functional images of 26 high-functioning adult males with ASD, alongside 26 age-, gender-, and full-scale IQ-matched typically developing controls (TDCs) from the BNI dataset in the ABIDE database. We utilized fixel-based analysis to extract microstructural information from fiber tracts, which was then used to predict FC using a multilinear model. Our results revealed that the structure-function relationships in both ASD and TDC cohorts were strongly aligned in the primary cortex but decoupled in the high-order cortex, and the ASD patients exhibited reduced structure-function relationships throughout the cortex compared to the TDCs. Furthermore, we observed that the disrupted relationships in ASD were primarily driven by alterations in FC rather than fiber-bundle microstructures. The structure-function relationships in the left superior parietal cortex, right precentral and inferior temporal cortices, and bilateral insula could predict individual differences in clinical symptoms of ASD patients. These findings underscore the significance of altered relationships between fiber-bundle microstructures and FC in the etiology of ASD.
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Affiliation(s)
- Qiangli Dong
- Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou 730000, China
| | - Jialong Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yumeng Ju
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Chuman Xiao
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Kangning Li
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Bin Shi
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yan Zhang
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
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9
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Du Y, Chen L, Yan MC, Wang YL, Zhong XL, Xv CX, Li YB, Cheng Y. Neurometabolite levels in the brains of patients with autism spectrum disorders: A meta-analysis of proton magnetic resonance spectroscopy studies (N = 1501). Mol Psychiatry 2023; 28:3092-3103. [PMID: 37117459 DOI: 10.1038/s41380-023-02079-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 04/30/2023]
Abstract
Evidence suggests that neurometabolite alterations may be involved in the pathophysiology of autism spectrum disorders (ASDs). We performed a meta-analysis of proton magnetic resonance spectroscopy (1H-MRS) studies to examine the neurometabolite levels in the brains of patients with ASD. A systematic search of PubMed and Web of Science identified 54 studies for the meta-analysis. A random-effects meta-analysis demonstrated that compared with the healthy controls, patients with ASD had lower N-acetyl-aspartate-containing compound (NAA) and choline-containing compound (Cho) levels and NAA/(creatine-containing compound) Cr ratios in the gray matter and lower NAA and glutamate + glutamine (Glx) levels in the white matter. Furthermore, NAA and gamma-aminobutyric acid (GABA) levels, NAA/Cr ratios, and GABA/Cr ratios were significantly decreased in the frontal cortex of patients with ASD, whereas glutamate (Glu) levels were increased in the prefrontal cortex. Additionally, low NAA levels and GABA/Cr ratios in the temporal cortex, low NAA levels and NAA/Cr ratios in the parietal and dorsolateral prefrontal cortices, and low NAA levels in the cerebellum and occipital cortex were observed in patients with ASD. Meta-regression analysis revealed that age was positively associated with effect size in studies analyzing the levels of gray matter NAA and white matter Glx. Taken together, these results provide strong clinical evidence that neurometabolite alterations in specific brain regions are associated with ASD and age is a confounding factor for certain neurometabolite levels in patients with ASD.
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Affiliation(s)
- Yang Du
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Lei Chen
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Mei-Chen Yan
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Yan-Li Wang
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Xiao-Lin Zhong
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Chen-Xi Xv
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Yao-Bo Li
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China
| | - Yong Cheng
- Key Laboratory of Ethnomedicine of Ministry of Education, Center on Translational Neuroscience, College of Life and Environmental Sciences, Minzu University of China, Beijing, China.
- Institute of National Security, Minzu University of China, Beijing, China.
- NHC Key Laboratory of Birth Defect Research, Prevention, and Treatment (Hunan Provincial Maternal and Child Health-Care Hospital), Changsha, Hunan, China.
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10
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Cremone IM, Nardi B, Amatori G, Palego L, Baroni D, Casagrande D, Massimetti E, Betti L, Giannaccini G, Dell'Osso L, Carpita B. Unlocking the Secrets: Exploring the Biochemical Correlates of Suicidal Thoughts and Behaviors in Adults with Autism Spectrum Conditions. Biomedicines 2023; 11:1600. [PMID: 37371695 DOI: 10.3390/biomedicines11061600] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/27/2023] [Accepted: 05/28/2023] [Indexed: 06/29/2023] Open
Abstract
Involving 1 million people a year, suicide represents one of the major topics of psychiatric research. Despite the focus in recent years on neurobiological underpinnings, understanding and predicting suicide remains a challenge. Many sociodemographical risk factors and prognostic markers have been proposed but they have poor predictive accuracy. Biomarkers can provide essential information acting as predictive indicators, providing proof of treatment response and proposing potential targets while offering more assurance than psychological measures. In this framework, the aim of this study is to open the way in this field and evaluate the correlation between blood levels of serotonin, brain derived neurotrophic factor, tryptophan and its metabolites, IL-6 and homocysteine levels and suicidality. Blood samples were taken from 24 adults with autism, their first-degree relatives, and 24 controls. Biochemical parameters were measured with enzyme-linked immunosorbent assays. Suicidality was measured through selected items of the MOODS-SR. Here we confirm the link between suicidality and autism and provide more evidence regarding the association of suicidality with increased homocysteine (0.278) and IL-6 (0.487) levels and decreased tryptophan (-0.132) and kynurenic acid (-0.253) ones. Our results suggest a possible transnosographic association between these biochemical parameters and increased suicide risk.
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Affiliation(s)
- Ivan Mirko Cremone
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
| | - Benedetta Nardi
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
| | - Giulia Amatori
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
| | - Lionella Palego
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy
| | - Dario Baroni
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy
| | - Danila Casagrande
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
| | - Enrico Massimetti
- ASST Bergamo Ovest, SSD Psychiatric Diagnosis and Treatment Service, 24047 Treviglio, Italy
| | - Laura Betti
- Department of Pharmacy, University of Pisa, 56126 Pisa, Italy
| | | | - Liliana Dell'Osso
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
| | - Barbara Carpita
- Department of Clinical and Experimental Medicine, University of Pisa, via Roma 67, 56126 Pisa, Italy
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11
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Lee JH, Yun J, Hwang H, Kim SM, Han DH. The Study on the Identification of Musical Passages for an Emotion Perception Scale for People With Developmental Disabilities. J Korean Med Sci 2023; 38:e30. [PMID: 36747361 PMCID: PMC9902668 DOI: 10.3346/jkms.2023.38.e30] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/27/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Emotion recognition is essential to the social adjustment and social interaction of people with intellectual and developmental disabilities (IDDs). Given that music is a medium for expressing and conveying human emotion, we conducted this preliminary study to identify musical passages representing the basic human emotions of happiness, sadness, and anger, with the goal of developing a music-based emotion perception scale for IDDs. METHODS To identify musical passages for emotion perception, 20 certified music therapists evaluated 100 selected musical passages and established 60 pieces that yielded the highest agreement for each emotion category. During the second phase of this study, 300 neurotypical participants rated 60 passages in terms of the perceived type and intensity of emotions expressed. RESULTS The 60 passages showed high reliability and were statistically classified into three factors: happiness, sadness, and anger. The k-means cluster analysis yielded a cut-off score of 41 for the low emotion perception group (F = 1120.63, P < 0.001). The hierarchical logistic regression analysis revealed that only model 3 (musical passages) was significantly associated with low emotion perception (step χ² = 227.8, P < 0.001). CONCLUSION The selected musical passages demonstrated high reliability and established three factors for identifying perceptions of happiness, sadness, and anger. Neither psychological status nor individual demographic characteristics affected the emotion perception results.
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Affiliation(s)
- Jin Hyung Lee
- Department of Psychiatry, Chung Ang University School of Medicine, Seoul, Korea
| | - Juri Yun
- Department of Music Therapy, Ewha Womans University, Seoul, Korea
| | - Hyunchan Hwang
- Department of Psychiatry, Chung Ang University School of Medicine, Seoul, Korea
| | - Sun Mi Kim
- Department of Psychiatry, Chung Ang University School of Medicine, Seoul, Korea
| | - Doug Hyun Han
- Department of Psychiatry, Chung Ang University School of Medicine, Seoul, Korea.
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12
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Duan K, Eyler L, Pierce K, Lombardo M, Datko M, Hagler D, Taluja V, Zahiri J, Campbell K, Barnes C, Arias S, Nalabolu S, Troxel J, Courchesne E. Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome. RESEARCH SQUARE 2023:rs.3.rs-2451837. [PMID: 36778379 PMCID: PMC9915795 DOI: 10.21203/rs.3.rs-2451837/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.
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Affiliation(s)
- Kuaikuai Duan
- Georgia Institute of Technology, Emory University, Georgia State University
| | | | | | | | | | - Donald Hagler
- Department of Radiology, School of Medicine, University of California San Diego, USA
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13
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Li C, Zhang T, Li J. Identifying autism spectrum disorder in resting-state fNIRS signals based on multiscale entropy and a two-branch deep learning network. J Neurosci Methods 2023; 383:109732. [PMID: 36349567 DOI: 10.1016/j.jneumeth.2022.109732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/10/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND The demand for early and precise identification of autism spectrum disorder (ASD) presented a challenge to the prediction of ASD with a non-invasive neuroimaging method. NEW METHOD A deep learning model was proposed to identify children with ASD using the resting-state functional near-infrared spectroscopy (fNIRS) signals. In this model, the input was the pattern of brain complexity represented by multiscale entropy of fNIRS time-series signals, with the purpose to solve the problem of deep learning analysis when the raw signals were limited by length and the number of subjects. The model consisted of a two-branch deep learning network, where one branch was a convolution neural network and the other was a long short-term memory neural network based on an attention mechanism. RESULTS Our model could achieve an identification accuracy of 94%. Further analysis used the SHapley Additive exPlanations (SHAP) method to balance the accuracy and the number of optical channels, thus reducing the complexity of fNIRS experiment. COMPARISON WITH PREVIOUSLY USED METHOD(S): in identification accuracy, our model was about 14% higher than previously used deep learning models with the same input and 4% higher than the same model but directly using fNIRS signals as input. We could obtain a discriminative accuracy of 90% with nearly half of the measurement channels by the SHAP method. CONCLUSIONS Using the pattern of brain complexity as input was effective in the deep learning model when the fNIRS signals were insufficient. With the SHAP method, it was possible to reduce the number of optical channels, while maintaining high accuracy in ASD identification.
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Affiliation(s)
- Chengxin Li
- South China Academy of Advanced Optoelectronics, South China Normal University, China
| | - Tingzhen Zhang
- South China Academy of Advanced Optoelectronics, South China Normal University, China
| | - Jun Li
- South China Academy of Advanced Optoelectronics, South China Normal University, China.
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14
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Sultan S. Translating neuroimaging changes to neuro-endophenotypes of autistic spectrum disorder: a narrative review. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2022. [DOI: 10.1186/s41983-022-00578-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Abstract
Background
Autism-spectrum disorder is a neurodevelopmental disorder with heterogeneity in etiopathogenesis and clinical presentation. Neuroanatomical and neurophysiological abnormalities may represent neural endophenotypes for autism spectrum disorders which may help identify subgroups of patients seemingly similar in clinical presentation yet different in their pathophysiological underpinnings. Furthermore, a thorough understanding of the pathophysiology of disease can pave the way to effective treatments, prevention, and prognostic predictions. The aim of this review is to identify the predominant neural endophenotypes in autism-spectrum disorder. The evidence was researched at the following electronic databases: Pubmed, PsycINFO, Scopus, Web of Science, and EMBASE.
Results
Enlarged brain, especially frontotemporal cortices have been consistently reported by structural neuroimaging, whereas functional neuroimaging has revealed frontotemporal dysconnectivity.
Conclusions
Regrettably, many of these findings have not been consistent. Therefore, translating these findings into neural endophenotype is by far an attempt in its budding stage. The structural and functional neuroimaging changes may represent neural endophenotypes unique to autism-spectrum disorder. Despite inconsistent results, a clinically meaningful finding may require combined efforts of autism-spectrum-disorder researchers focused on different aspects of basic, genetic, neuroimaging, and clinical research.
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15
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Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that occurs during early childhood. The change from being normal across several contexts to displaying the behavioral phenotype of ASD occurs in infants and toddlers with autism. Findings provided by magnetic resonance imaging (MRI)-based research owing to the developmental phase, including potential pathways underlying the pathogenesis of the condition and the potential for signs and symptomatic risk prediction. The present study focuses on the characteristic features of magnetic resonance imaging autistic brain, how these changes are correlated to autism signs and symptoms and the implications of MRI as a potential tool for the early diagnosis of ASD. PRISMA style was used to conduct this review. Research articles related to the key concepts of this review, which is looking at MRI brain changes in autistic patients, were revised and incorporated with what is known with the pathophysiology of brain regions in relation to signs and symptoms of autism. Studies on brain MRI of autism were revied for major brain features and regions such as brain volume, cortex and hippocampus. This review reveals that brain changes seen in MRI are highly correlated with the signs and symptoms of autism. There are numerous distinct features noted in an autistic brain using MRI. Based on these findings, various developmental brain paths and autistic behavior culminate in a typical diagnosis, and it is possible that addressing these trajectories would improve the accuracy in which children are detected and provide the necessary treatment.
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Affiliation(s)
- Nahla L. Faizo
- Radiological Sciences Department, College of Applied Medical Sciences, Taif University, KSA
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16
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Zhang Y, Zhang S, Chen B, Jiang L, Li Y, Dong L, Feng R, Yao D, Li F, Xu P. Predicting the Symptom Severity in Autism Spectrum Disorder Based on EEG Metrics. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1898-1907. [PMID: 35788457 DOI: 10.1109/tnsre.2022.3188564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Autism spectrum disorder (ASD) is associated with the impaired integrating and segregating of related information that is expanded within the large-scale brain network. The varying ASD symptom severities have been explored, relying on their behaviors and related brain activity, but how to effectively predict ASD symptom severity needs further exploration. In this study, we aim to investigate whether the ASD symptom severity could be predicted with electroencephalography (EEG) metrics. Based on a publicly available dataset, the EEG brain networks were constructed, and four types of EEG metrics were calculated. Then, we statistically compared the brain network differences among ASD children with varying severities, i.e., high/low autism diagnostic observation schedule (ADOS) scores, as well as with the typically developing (TD) children. Thereafter, the EEG metrics were utilized to validate whether they could facilitate the prediction of the ASD symptom severity. The results demonstrated that both high- and low-scoring ASD children showed the decreased long-range frontal-occipital connectivity, increased anterior frontal connectivity and altered network properties. Furthermore, we found that the four types of EEG metrics are significantly correlated with the ADOS scores, and their combination can serve as the features to effectively predict the ASD symptom severity. The current findings will expand our knowledge of network dysfunction in ASD children and provide new EEG metrics for predicting the symptom severity.
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17
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Rochat MJ, Gallese V. The Blurred Vital Contours of Intersubjectivity in Autism Spectrum Disorder: Early Signs and Neurophysiological Hypotheses. PSYCHOANALYTIC INQUIRY 2022. [DOI: 10.1080/07351690.2022.2007022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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18
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McKinney WS, Kelly SE, Unruh KE, Shafer RL, Sweeney JA, Styner M, Mosconi MW. Cerebellar Volumes and Sensorimotor Behavior in Autism Spectrum Disorder. Front Integr Neurosci 2022; 16:821109. [PMID: 35592866 PMCID: PMC9113114 DOI: 10.3389/fnint.2022.821109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Background Sensorimotor issues are common in autism spectrum disorder (ASD), though their neural bases are not well understood. The cerebellum is vital to sensorimotor control and reduced cerebellar volumes in ASD have been documented. Our study examined the extent to which cerebellar volumes are associated with multiple sensorimotor behaviors in ASD. Materials and Methods Fifty-eight participants with ASD and 34 typically developing (TD) controls (8-30 years) completed a structural MRI scan and precision grip testing, oculomotor testing, or both. Force variability during precision gripping as well as absolute error and trial-to-trial error variability of visually guided saccades were examined. Volumes of cerebellar lobules, vermis, and white matter were quantified. The relationships between each cerebellar region of interest (ROI) and force variability, saccade error, and saccade error variability were examined. Results Relative to TD controls, individuals with ASD showed increased force variability. Individuals with ASD showed a reduced volume of cerebellar vermis VI-VII relative to TD controls. Relative to TD females, females with ASD showed a reduced volume of bilateral cerebellar Crus II/lobule VIIB. Increased volume of Crus I was associated with increased force variability. Increased volume of vermal lobules VI-VII was associated with reduced saccade error for TD controls but not individuals with ASD. Increased right lobule VIII and cerebellar white matter volumes as well as reduced right lobule VI and right lobule X volumes were associated with greater ASD symptom severity. Reduced volumes of right Crus II/lobule VIIB were associated with greater ASD symptom severity in only males, while reduced volumes of right Crus I were associated with more severe restricted and repetitive behaviors only in females. Conclusion Our finding that increased force variability in ASD is associated with greater cerebellar Crus I volumes indicates that disruption of sensory feedback processing supported by Crus I may contribute to skeletomotor differences in ASD. Results showing that volumes of vermal lobules VI-VII are associated with saccade precision in TD but not ASD implicates atypical organization of the brain systems supporting oculomotor control in ASD. Associations between volumes of cerebellar subregions and ASD symptom severity suggest cerebellar pathological processes may contribute to multiple developmental challenges in ASD.
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Affiliation(s)
- Walker S. McKinney
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, United States
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, United States
| | - Shannon E. Kelly
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, United States
- Department of Psychology, University of Kansas, Lawrence, KS, United States
| | - Kathryn E. Unruh
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, United States
| | - Robin L. Shafer
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, United States
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Martin Styner
- Department of Psychiatry and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Matthew W. Mosconi
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, United States
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, United States
- Department of Psychology, University of Kansas, Lawrence, KS, United States
- *Correspondence: Matthew W. Mosconi,
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Pitzianti M, Fagioli S, Pontis M, Pasini A. Attention Deficits Influence the Development of Motor Abnormalities in High Functioning Autism. Child Psychiatry Hum Dev 2021; 52:1131-1142. [PMID: 33145671 PMCID: PMC8528792 DOI: 10.1007/s10578-020-01088-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/18/2020] [Indexed: 11/27/2022]
Abstract
Early attentional dysfunction is one of the most consistent findings in autism spectrum disorder (ASD), including the high functioning autism (HFA). There are no studies that assess how the atypical attentional processes affect the motor functioning in HFA. In this study, we evaluated attentional and motor functioning in a sample of 15 drug-naive patients with HFA and 15 healthy children (HC), and possible link between attentional dysfunction and motor impairment in HFA. Compared to HC, HFA group was seriously impaired in a considerable number of attentional processes and showed a greater number of motor abnormalities. Significant correlations between attention deficits and motor abnormalities were observed in HFA group. These preliminary findings suggest that deficit of attentional processes can be implied in motor abnormalities in HFA.
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Affiliation(s)
- Mariabernarda Pitzianti
- Unit of Child Neurology and Psychiatry, Department of Systems Medicine, "Tor Vergata" University, Via Montpellier 1, 00133, Rome, Italy
- Child Neuropsychiatry, USL Umbria-2, Viale VIII Marzo, 05100, Terni, Italy
| | - Sabrina Fagioli
- Department of Education, University of "Roma Tre", Via del Castro Pretorio 20, 00185, Rome, Italy.
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Via Ardeatina 306, 00179, Rome, Italy.
| | - Marco Pontis
- Comprehensive Rehabilitation Center Ctr Asl 8, Cagliari, Italy
| | - Augusto Pasini
- Unit of Child Neurology and Psychiatry, Department of Systems Medicine, "Tor Vergata" University, Via Montpellier 1, 00133, Rome, Italy
- Child Neuropsychiatry, USL Umbria-2, Viale VIII Marzo, 05100, Terni, Italy
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20
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Brennan C, Weintraub H, Tennant S, Meyers C. Speech, Language, and Communication Deficits and Intervention in a Single Case of Pediatric Autoimmune Encephalitis. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2021; 30:2350-2367. [PMID: 34491819 DOI: 10.1044/2021_ajslp-20-00395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Purpose The current literature on pediatric autoimmune encephalitis (AE) focuses on medical identification/diagnosis and medical treatments. Data about the identification and treatment of communication disorders in these children are limited. This clinical focus article provides an example of the speech, language, and communication characteristics, intervention, and recovery of a single child with medical diagnoses of pediatric AE and pediatric acute-onset neuropsychiatric syndrome (PANS) and special education eligibility under the autism spectrum disorder category. Method This is an in-depth illustrative/descriptive case study. Medical, educational, and speech-language documentation of one child diagnosed with AE at age 7 years was reviewed. Methods included interviews with family members, teachers, and the school speech-language pathologist and reviews of documentation including evaluations, reports, and Individualized Education Programs. Results This child received special education and therapy services through his public school and a university speech-language clinic. He concurrently received medical treatment for AE and PANS. Comprehensive augmentative and alternative communication (AAC) intervention included the use of core words, modeling, parallel talk, self-talk, expansive recasts, shared book reading, family counseling, and collaboration with the parents and the school speech-language pathologist. The child made progress on all goals despite irregular attendance to therapy due to medical complications. Discussion Because experimental research including this population is currently limited, this descriptive case study provides valuable information to clinicians, educators, pediatricians, medical diagnosticians, and anyone providing services to a child with a complex neuropsychological disorder like AE. Future research is needed with more children who have AE, especially experimental investigations of the intervention methods utilized here. Additional research of more children with AE can provide information about the scope and severity of speech, language, and communication needs and the trajectory of recovery given AAC intervention.
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Affiliation(s)
- Christine Brennan
- Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder
| | - Haley Weintraub
- Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder
| | - Sherri Tennant
- Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder
| | - Christina Meyers
- Department of Speech, Language, and Hearing Sciences, University of Colorado Boulder
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21
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Comparan-Meza M, Vargas de la Cruz I, Jauregui-Huerta F, Gonzalez-Castañeda RE, Gonzalez-Perez O, Galvez-Contreras AY. Biopsychological correlates of repetitive and restricted behaviors in autism spectrum disorders. Brain Behav 2021; 11:e2341. [PMID: 34472728 PMCID: PMC8553330 DOI: 10.1002/brb3.2341] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 07/31/2021] [Accepted: 08/10/2021] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) is considered a neurodevelopmental condition that is characterized by alterations in social interaction and communication, as well as patterns of restrictive and repetitive behaviors (RRBs). RRBs are defined as broad behaviors that comprise stereotypies, insistence on sameness, and attachment to objects or routines. RRBs can be divided into lower-level behaviors (motor, sensory, and object-manipulation behaviors) and higher-level behaviors (restrictive interests, insistence on sameness, and repetitive language). According to the DSM-5, the grade of severity in ASD partially depends on the frequency of RRBs and their consequences for disrupting the life of patients, affecting their adaptive skills, and increasing the need for parental support. METHODS We conducted a systematic review to examine the biopsychological correlates of the symptomatic domains of RRBs according to the type of RRBs (lower- or higher-level). We searched for articles from the National Library of Medicine (PubMed) using the terms: autism spectrum disorders, ASD, and autism-related to executive functions, inhibitory control, inflexibility, cognitive flexibility, hyper or hypo connectivity, and behavioral approaches. For describing the pathophysiological mechanism of ASD, we also included animal models and followed PRISMA guidelines. RESULTS One hundred and thirty-one articles were analyzed to explain the etiology, continuance, and clinical evolution of these behaviors observed in ASD patients throughout life. CONCLUSIONS Biopsychological correlates involved in the origin of RRBs include alterations in a) neurotransmission system, b) brain volume, c) inadequate levels of growth factors, d) hypo- or hyper-neural connectivity, e) impairments in behavioral inhibition, cognitive flexibility, and monitoring and f) non-stimulating environments. Understanding these lower- and higher-level of RRBs can help professionals to improve or design novel therapeutic strategies.
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Affiliation(s)
- Miguel Comparan-Meza
- Maestría en Neuropsicología, Departamento de Neurociencias, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara, JAL, Mexico
| | - Ivette Vargas de la Cruz
- Unidad de Atención en Neurociencias, Departamento de Neurociencias, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara, JAL, Mexico
| | - Fernando Jauregui-Huerta
- Laboratorio de Microscopia de Alta Resolución, Departamento de Neurociencias, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara, JAL, Mexico
| | - Rocio E Gonzalez-Castañeda
- Laboratorio de Microscopia de Alta Resolución, Departamento de Neurociencias, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara, JAL, Mexico
| | - Oscar Gonzalez-Perez
- Laboratorio de Neurociencias, Facultad de Psicología, Universidad de Colima, Colima, COL, Mexico
| | - Alma Y Galvez-Contreras
- Unidad de Atención en Neurociencias, Departamento de Neurociencias, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara, JAL, Mexico
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22
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Morimoto C, Nakamura Y, Kuwabara H, Abe O, Kasai K, Yamasue H, Koike S. Unique Morphometric Features of the Cerebellum and Cerebellocerebral Structural Correlation Between Autism Spectrum Disorder and Schizophrenia. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 1:219-228. [PMID: 36325298 PMCID: PMC9616290 DOI: 10.1016/j.bpsgos.2021.05.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 05/13/2021] [Accepted: 05/23/2021] [Indexed: 12/13/2022] Open
Abstract
Background Although cerebellar morphological involvement has been increasingly recognized in autism spectrum disorder (ASD) and schizophrenia (SZ), the extent to which there are morphological differences between them has not been definitively quantified. Furthermore, although previous studies have demonstrated increased anatomical cerebellocerebral correlations in both conditions, differences between their associations have not been well characterized. Methods We compared cerebellar volume between males with ASD (n = 31), males with SZ (n = 28), and typically developing males (n = 49). A total of 31 cerebellar subregions were investigated with the cerebellum segmented into their constituent lobules, in gray matter (GM) and white matter (WM) separately. Additionally, structural correlations with the contralateral cerebrum were analyzed for each cerebellar lobule. Results We found significantly larger WM volume in the bilateral lobules VI and Crus I in the ASD group than in other groups. While WM or GM volumes of these right lobules had positive associations with ASD symptoms, there was a negative association between GM volume of the right Crus I and SZ symptoms. We further observed, in the ASD group specifically, significant correlations between WM of the right lobule VI and WM of the left frontal pole (r = 0.67) and between GM of the right lobule VI and the left caudate (r = 0.60). Conclusions Our findings support evidence that cerebellar morphology is involved in ASD and SZ with different mechanisms. Furthermore, this study showed that these biological differences require consideration when determining diagnostic criteria and treatment for these disorders.
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Affiliation(s)
- Chie Morimoto
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Yuko Nakamura
- UTokyo Center for Integrative Science of Human Behaviour, Graduate School of Art and Sciences, University of Tokyo, Tokyo, Japan
| | - Hitoshi Kuwabara
- Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu City, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science, Graduate School of Art and Sciences, University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence, University of Tokyo Institutes for Advanced Study, University of Tokyo, Tokyo, Japan
- UTokyo Institute for Diversity and Adaptation of Human Mind, University of Tokyo, Tokyo, Japan
| | - Hidenori Yamasue
- Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu City, Japan
| | - Shinsuke Koike
- UTokyo Center for Integrative Science of Human Behaviour, Graduate School of Art and Sciences, University of Tokyo, Tokyo, Japan
- Center for Evolutionary Cognitive Science, Graduate School of Art and Sciences, University of Tokyo, Tokyo, Japan
- International Research Center for Neurointelligence, University of Tokyo Institutes for Advanced Study, University of Tokyo, Tokyo, Japan
- UTokyo Institute for Diversity and Adaptation of Human Mind, University of Tokyo, Tokyo, Japan
- Address correspondence to Shinsuke Koike, M.D., Ph.D.
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23
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Clausi S, Olivito G, Siciliano L, Lupo M, Laghi F, Baiocco R, Leggio M. The cerebellum is linked to theory of mind alterations in autism. A direct clinical and MRI comparison between individuals with autism and cerebellar neurodegenerative pathologies. Autism Res 2021; 14:2300-2313. [PMID: 34374492 PMCID: PMC9291804 DOI: 10.1002/aur.2593] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 07/28/2021] [Accepted: 07/29/2021] [Indexed: 01/03/2023]
Abstract
In recent years, structural and functional alterations in the cerebellum have been reported in autism spectrum disorder (ASD). Intriguingly, recent studies demonstrated that the social behavioral profile of individuals with cerebellar pathologies is characterized by a theory of mind (ToM) impairment, one of the main behavioral hallmarks of ASD. The aim of the present study was to compare ToM abilities and underlying cerebello-cortical structural patterns between ASD individuals and individuals with cerebellar atrophy to further specify the cerebellar role in mentalizing alterations in ASD. Twenty-one adults with ASD without language and intellectual impairments (based on DSM-5), 36 individuals affected by degenerative cerebellar damage (CB), and 67 healthy participants were enrolled in the study. ToM abilities were assessed using the reading the mind in the eyes test and the faux pas test. One-way ANCOVA was conducted to compare the performances between the two cohorts. Three-dimensional T1-weighted magnetic resonance scans were collected, and a voxel-based morphometry analysis was performed to characterize the brain structural alterations in the two cohorts. ASD and CB participants had comparable ToM performance with similar difficulties in both the tests. CB and ASD participants showed an overlapping pattern of gray matter (GM) reduction in a specific cerebellar portion (Crus-II). Our study provides the first direct comparison of ToM abilities between ASD and CB individuals, boosting the idea that specific cerebellar structural alterations impact the mentalizing process. The present findings open a new perspective for considering the cerebellum as a potential target for treatment implementation. The present work will critically advance current knowledge about the cerebellar role in ToM alterations of ASD, in particular, elucidating the presence of common cerebellar structural abnormalities in ASD and cerebellar individuals that may underlie specific mentalizing alterations. These findings may pave the way for alternative therapeutic indications, such as cerebellar neuromodulation, with a strong clinical impact. LAY SUMMARY: The present work will critically advance current knowledge about the cerebellar role in theory of mind alterations of autism spectrum disorder (ASD), in particular, elucidating the presence of common cerebellar structural abnormalities in ASD and cerebellar individuals that may underlie specific mentalizing alterations. These findings may pave the way for alternative therapeutic indications, such as cerebellar neuromodulation, with a strong clinical impact.
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Affiliation(s)
- Silvia Clausi
- Ataxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Giusy Olivito
- Ataxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.,Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Libera Siciliano
- PhD Program in Behavioral Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Michela Lupo
- Ataxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fiorenzo Laghi
- Department of Developmental and Social Psychology, Sapienza University of Rome, Rome, Italy
| | - Roberto Baiocco
- Department of Developmental and Social Psychology, Sapienza University of Rome, Rome, Italy
| | - Maria Leggio
- Ataxia Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.,Department of Psychology, Sapienza University of Rome, Rome, Italy
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24
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Squarcina L, Nosari G, Marin R, Castellani U, Bellani M, Bonivento C, Fabbro F, Molteni M, Brambilla P. Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine. Brain Behav 2021; 11:e2238. [PMID: 34264004 PMCID: PMC8413814 DOI: 10.1002/brb3.2238] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 05/10/2021] [Accepted: 05/23/2021] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core symptoms. We apply support vector machine, a supervised machine learning method, in order to identify specific cortical thickness alterations in ASD subjects. METHODS A sample of 76 subjects (9.5 ± 3.4 years old) has been selected, 40 diagnosed with ASD and 36 typically developed subjects. All children underwent a magnetic resonance imaging (MRI) examination; T1-MPRAGE sequences were analyzed to extract features for the characterization and parcellation of regions of interests (ROI); average cortical thickness (CT) has been measured for each ROI. For the classification process, the extracted features were used as input for a classifier to identify ASD subjects through a "learning by example" procedure; the features with best performance was then selected by "greedy forward-feature selection." Finally, this model underwent a leave-one-out cross-validation approach. RESULTS From the training set of 68 ROIs, five ROIs reached accuracies of over 70%. After this phase, we used a recursive feature selection process in order to identify the eight features with the best accuracy (84.2%). CT resulted higher in ASD compared to controls in all the ROIs identified at the end of the process. CONCLUSION We found increased CT in various brain regions in ASD subjects, confirming their role in the pathogenesis of this condition. Considering the brain development curve during ages, these changes in CT may normalize during development. Further validation on a larger sample is required.
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Affiliation(s)
- Letizia Squarcina
- Department of Pathophysiology and TransplantationUniversity of MilanVia Festa del Perdono, 7, 20122 MilanItaly
| | - Guido Nosari
- Department of Pathophysiology and TransplantationUniversity of MilanVia Festa del Perdono, 7, 20122 MilanItaly
| | - Riccardo Marin
- Department of InformaticsUniversity of VeronaVeronaItaly
| | | | - Marcella Bellani
- Department of NeurosciencesBiomedicine and Movement SciencesSection of PsychiatryUniversity of VeronaVeronaItaly
| | - Carolina Bonivento
- IRCCS “E. Medea”, Polo Friuli Venezia GiuliaSan Vito al Tagliamento (PN)Italy
| | | | - Massimo Molteni
- IRCCS “E. Medea”, Polo Friuli Venezia GiuliaSan Vito al Tagliamento (PN)Italy
| | - Paolo Brambilla
- Department of Pathophysiology and TransplantationUniversity of MilanVia Festa del Perdono, 7, 20122 MilanItaly
- Department of Neurosciences and Mental Health Department of Neurosciences and Mental HealthFondazione IRCCS Ca' Granda Ospedale Maggiore Policlinicovia Francesco Sforza 28, 20122 MilanItaly
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25
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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] [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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26
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Zoltowski AR, Lyu I, Failla M, Mash LE, Dunham K, Feldman JI, Woynaroski TG, Wallace MT, Barquero LA, Nguyen TQ, Cutting LE, Kang H, Landman BA, Cascio CJ. Cortical Morphology in Autism: Findings from a Cortical Shape-Adaptive Approach to Local Gyrification Indexing. Cereb Cortex 2021; 31:5188-5205. [PMID: 34195789 DOI: 10.1093/cercor/bhab151] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 04/09/2021] [Accepted: 05/04/2021] [Indexed: 11/14/2022] Open
Abstract
It has been challenging to elucidate the differences in brain structure that underlie behavioral features of autism. Prior studies have begun to identify patterns of changes in autism across multiple structural indices, including cortical thickness, local gyrification, and sulcal depth. However, common approaches to local gyrification indexing used in prior studies have been limited by low spatial resolution relative to functional brain topography. In this study, we analyze the aforementioned structural indices, utilizing a new method of local gyrification indexing that quantifies this index adaptively in relation to specific sulci/gyri, improving interpretation with respect to functional organization. Our sample included n = 115 autistic and n = 254 neurotypical participants aged 5-54, and we investigated structural patterns by group, age, and autism-related behaviors. Differing structural patterns by group emerged in many regions, with age moderating group differences particularly in frontal and limbic regions. There were also several regions, particularly in sensory areas, in which one or more of the structural indices of interest either positively or negatively covaried with autism-related behaviors. Given the advantages of this approach, future studies may benefit from its application in hypothesis-driven examinations of specific brain regions and/or longitudinal studies to assess brain development in autism.
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Affiliation(s)
- Alisa R Zoltowski
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA
| | - Ilwoo Lyu
- Department of Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, South Korea
| | - Michelle Failla
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA.,College of Nursing, Ohio State University, Columbus, OH 43210, USA
| | - Lisa E Mash
- San Diego Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA 92120, USA
| | - Kacie Dunham
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37232, USA
| | - Jacob I Feldman
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN 37212, USA
| | - Tiffany G Woynaroski
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN 37212, USA.,Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Mark T Wallace
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA.,Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN 37212, USA.,Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA.,Department of Psychology and Human Development, Vanderbilt University, Nashville, TN 37203, USA
| | - Laura A Barquero
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN 37203, USA
| | - Tin Q Nguyen
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Special Education, Vanderbilt University, Nashville, TN 37203, USA
| | - Laurie E Cutting
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Department of Psychology and Human Development, Vanderbilt University, Nashville, TN 37203, USA.,Department of Special Education, Vanderbilt University, Nashville, TN 37203, USA.,Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hakmook Kang
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
| | - Bennett A Landman
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA.,Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37232, USA.,Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37212, USA
| | - Carissa J Cascio
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA.,Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN 37212, USA.,Frist Center for Autism and Innovation, Vanderbilt University, Nashville, TN 37212, USA.,Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN 37203, USA.,Department of Psychology and Human Development, Vanderbilt University, Nashville, TN 37203, USA
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27
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Implications of Extended Inhibitory Neuron Development. Int J Mol Sci 2021; 22:ijms22105113. [PMID: 34066025 PMCID: PMC8150951 DOI: 10.3390/ijms22105113] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 05/05/2021] [Accepted: 05/06/2021] [Indexed: 12/23/2022] Open
Abstract
A prolonged developmental timeline for GABA (γ-aminobutyric acid)-expressing inhibitory neurons (GABAergic interneurons) is an amplified trait in larger, gyrencephalic animals. In several species, the generation, migration, and maturation of interneurons take place over several months, in some cases persisting after birth. The late integration of GABAergic interneurons occurs in a region-specific pattern, especially during the early postnatal period. These changes can contribute to the formation of functional connectivity and plasticity, especially in the cortical regions responsible for higher cognitive tasks. In this review, we discuss GABAergic interneuron development in the late gestational and postnatal forebrain. We propose the protracted development of interneurons at each stage (neurogenesis, neuronal migration, and network integration), as a mechanism for increased complexity and cognitive flexibility in larger, gyrencephalic brains. This developmental feature of interneurons also provides an avenue for environmental influences to shape neural circuit formation.
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28
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Node Centrality Measures Identify Relevant Structural MRI Features of Subjects with Autism. Brain Sci 2021; 11:brainsci11040498. [PMID: 33919984 PMCID: PMC8071038 DOI: 10.3390/brainsci11040498] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/09/2021] [Accepted: 04/10/2021] [Indexed: 11/29/2022] Open
Abstract
Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental conditions characterized by impairments in social interaction and communication and restricted patterns of behavior, interests, and activities. Although the etiopathogenesis of idiopathic ASD has not been fully elucidated, compelling evidence suggests an interaction between genetic liability and environmental factors in producing early alterations of structural and functional brain development that are detectable by magnetic resonance imaging (MRI) at the group level. This work shows the results of a network-based approach to characterize not only variations in the values of the extracted features but also in their mutual relationships that might reflect underlying brain structural differences between autistic subjects and healthy controls. We applied a network-based analysis on sMRI data from the Autism Brain Imaging Data Exchange I (ABIDE-I) database, containing 419 features extracted with FreeSurfer software. Two networks were generated: one from subjects with autistic disorder (AUT) (DSM-IV-TR), and one from typically developing controls (TD), adopting a subsampling strategy to overcome class imbalance (235 AUT, 418 TD). We compared the distribution of several node centrality measures and observed significant inter-class differences in averaged centralities. Moreover, a single-node analysis allowed us to identify the most relevant features that distinguished the groups.
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29
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Wang J, Wang X, Wang R, Duan X, Chen H, He C, Zhai J, Wu L, Chen H. Atypical Resting-State Functional Connectivity of Intra/Inter-Sensory Networks Is Related to Symptom Severity in Young Boys With Autism Spectrum Disorder. Front Physiol 2021; 12:626338. [PMID: 33868000 PMCID: PMC8044873 DOI: 10.3389/fphys.2021.626338] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 02/16/2021] [Indexed: 11/21/2022] Open
Abstract
Autism spectrum disorder (ASD) has been reported to have altered brain connectivity patterns in sensory networks, assessed using resting-state functional magnetic imaging (rs-fMRI). However, the results have been inconsistent. Herein, we aimed to systematically explore the interaction between brain sensory networks in 3–7-year-old boys with ASD (N = 29) using independent component analysis (ICA). Participants were matched for age, head motion, and handedness in the MRI scanner. We estimated the between-group differences in spatial patterns of the sensory resting-state networks (RSNs). Subsequently, the time series of each RSN were extracted from each participant’s preprocessed data and associated estimates of interaction strength between intra- and internetwork functional connectivity (FC) and symptom severity in children with ASD. The auditory network (AN), higher visual network (HVN), primary visual network (PVN), and sensorimotor network (SMN) were identified. Relative to TDs, individuals with ASD showed increased FC in the AN and SMN, respectively. Higher positive connectivity between the PVN and HVN in the ASD group was shown. The strength of such connections was associated with symptom severity. The current study might suggest that the abnormal connectivity patterns of the sensory network regions may underlie impaired higher-order multisensory integration in ASD children, and be associated with social impairments.
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Affiliation(s)
- Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xiaomin Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China.,Pediatric Health Care Section, Ningbo Women & Children's Hospital, Ningbo, China
| | - Runshi Wang
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xujun Duan
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Heng Chen
- School of Medicine, Guizhou University, Guiyang, China
| | - Changchun He
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jinhe Zhai
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Huafu Chen
- Ministry of Education (MOE), Key Lab for NeuroInformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China
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30
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Sasabayashi D, Takahashi T, Takayanagi Y, Suzuki M. Anomalous brain gyrification patterns in major psychiatric disorders: a systematic review and transdiagnostic integration. Transl Psychiatry 2021; 11:176. [PMID: 33731700 PMCID: PMC7969935 DOI: 10.1038/s41398-021-01297-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 02/14/2021] [Accepted: 02/24/2021] [Indexed: 01/31/2023] Open
Abstract
Anomalous patterns of brain gyrification have been reported in major psychiatric disorders, presumably reflecting their neurodevelopmental pathology. However, previous reports presented conflicting results of patients having hyper-, hypo-, or normal gyrification patterns and lacking in transdiagnostic consideration. In this article, we systematically review previous magnetic resonance imaging studies of brain gyrification in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder at varying illness stages, highlighting the gyral pattern trajectory for each disorder. Patients with each psychiatric disorder may exhibit deviated primary gyri formation under neurodevelopmental genetic control in their fetal life and infancy, and then exhibit higher-order gyral changes due to mechanical stress from active brain changes (e.g., progressive reduction of gray matter volume and white matter integrity) thereafter, representing diversely altered pattern trajectories from those of healthy controls. Based on the patterns of local connectivity and changes in neurodevelopmental gene expression in major psychiatric disorders, we propose an overarching model that spans the diagnoses to explain how deviated gyral pattern trajectories map onto clinical manifestations (e.g., psychosis, mood dysregulation, and cognitive impairments), focusing on the common and distinct gyral pattern changes across the disorders in addition to their correlations with specific clinical features. This comprehensive understanding of the role of brain gyrification pattern on the pathophysiology may help to optimize the prediction and diagnosis of psychiatric disorders using objective biomarkers, as well as provide a novel nosology informed by neural circuits beyond the current descriptive diagnostics.
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Affiliation(s)
- Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan. .,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan.
| | - Tsutomu Takahashi
- grid.267346.20000 0001 2171 836XDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan ,grid.267346.20000 0001 2171 836XResearch Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Yoichiro Takayanagi
- grid.267346.20000 0001 2171 836XDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan ,Arisawabashi Hospital, Toyama, Japan
| | - Michio Suzuki
- grid.267346.20000 0001 2171 836XDepartment of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan ,grid.267346.20000 0001 2171 836XResearch Center for Idling Brain Science, University of Toyama, Toyama, Japan
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31
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Lorsung E, Karthikeyan R, Cao R. Biological Timing and Neurodevelopmental Disorders: A Role for Circadian Dysfunction in Autism Spectrum Disorders. Front Neurosci 2021; 15:642745. [PMID: 33776640 PMCID: PMC7994532 DOI: 10.3389/fnins.2021.642745] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 02/03/2021] [Indexed: 01/07/2023] Open
Abstract
Autism spectrum disorders (ASDs) are a spectrum of neurodevelopmental disorders characterized by impaired social interaction and communication, as well as stereotyped and repetitive behaviors. ASDs affect nearly 2% of the United States child population and the worldwide prevalence has dramatically increased in recent years. The etiology is not clear but ASD is thought to be caused by a combination of intrinsic and extrinsic factors. Circadian rhythms are the ∼24 h rhythms driven by the endogenous biological clock, and they are found in a variety of physiological processes. Growing evidence from basic and clinical studies suggest that the dysfunction of the circadian timing system may be associated with ASD and its pathogenesis. Here we review the findings that link circadian dysfunctions to ASD in both experimental and clinical studies. We first introduce the organization of the circadian system and ASD. Next, we review physiological indicators of circadian rhythms that are found disrupted in ASD individuals, including sleep-wake cycles, melatonin, cortisol, and serotonin. Finally, we review evidence in epidemiology, human genetics, and biochemistry that indicates underlying associations between circadian regulation and the pathogenesis of ASD. In conclusion, we propose that understanding the functional importance of the circadian clock in normal and aberrant neurodevelopmental processes may provide a novel perspective to tackle ASD, and clinical treatments for ASD individuals should comprise an integrative approach considering the dynamics of daily rhythms in physical, mental, and social processes.
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Affiliation(s)
- Ethan Lorsung
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
| | - Ramanujam Karthikeyan
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
| | - Ruifeng Cao
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, United States
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Shorter P1m Response in Children with Autism Spectrum Disorder without Intellectual Disabilities. Int J Mol Sci 2021; 22:ijms22052611. [PMID: 33807635 PMCID: PMC7961676 DOI: 10.3390/ijms22052611] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 03/01/2021] [Accepted: 03/01/2021] [Indexed: 12/01/2022] Open
Abstract
(1) Background: Atypical auditory perception has been reported in individuals with autism spectrum disorder (ASD). Altered auditory evoked brain responses are also associated with childhood ASD. They are likely to be associated with atypical brain maturation. (2) Methods: This study examined children aged 5–8 years old: 29 with ASD but no intellectual disability and 46 age-matched typically developed (TD) control participants. Using magnetoencephalography (MEG) data obtained while participants listened passively to sinusoidal pure tones, bilateral auditory cortical response (P1m) was examined. (3) Results: Significantly shorter P1m latency in the left hemisphere was found for children with ASD without intellectual disabilities than for children with TD. Significant correlation between P1m latency and language conceptual ability was found in children with ASD, but not in children with TD. (4) Conclusions: These findings demonstrated atypical brain maturation in the auditory processing area in children with ASD without intellectual disability. Findings also suggest that ASD has a common neural basis for pure-tone sound processing and language development. Development of brain networks involved in language concepts in early childhood ASD might differ from that in children with TD.
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Xu L, Sun Z, Xie J, Yu J, Li J, Wang J. Identification of autism spectrum disorder based on short-term spontaneous hemodynamic fluctuations using deep learning in a multi-layer neural network. Clin Neurophysiol 2021; 132:457-468. [PMID: 33450566 DOI: 10.1016/j.clinph.2020.11.037] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 10/25/2020] [Accepted: 11/17/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To classify children with autism spectrum disorder (ASD) and typical development (TD) using short-term spontaneous hemodynamic fluctuations and to explore the abnormality of inferior frontal gyrus and temporal lobe in ASD. METHODS 25 ASD children and 22 TD children were measured with functional near-infrared spectroscopy located on the inferior frontal gyrus and temporal lobe. To extract features used to classify ASD and TD, a multi-layer neural network was applied, combining with a three-layer convolutional neural network, a layer of long and short-term memory network (LSTM) and a layer of LSTM with Attention mechanism. In order to shorten the time of data collection and get more information from limited samples, a sliding window with 3.5 s width was utilized after comparisons, and numerous short (3.5 s) fNIRS time series were then obtained and used as the input of the multi-layer neural network. RESULTS A good classification between ASD and TD was obtained with considerably high accuracy by using a multi-layer neural network in different brain regions, especially in the left temporal lobe, where sensitivity of 90.6% and specificity of 97.5% achieved. CONCLUSIONS The "CLAttention" multi-layer neural network has the potential to excavate more meaningful features to distinguish between ASD and TD. Moreover, the temporal lobe may be worth further study. SIGNIFICANCE The findings in this study may have implications for rapid diagnosis of children with ASD and provide a new perspective for future medical diagnosis.
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Affiliation(s)
- Lingyu Xu
- Department of Computer Engineering and Science, Shanghai University, Shanghai, China; Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China
| | - Zhiyong Sun
- Department of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Jiang Xie
- Department of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Jie Yu
- Department of Computer Engineering and Science, Shanghai University, Shanghai, China
| | - Jun Li
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, China; Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
| | - JinHong Wang
- Department of Medical Imaging Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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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] [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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Cárdenas-de-la-Parra A, Lewis JD, Fonov VS, Botteron KN, McKinstry RC, Gerig G, Pruett JR, Dager SR, Elison JT, Styner MA, Evans AC, Piven J, Collins DL. A voxel-wise assessment of growth differences in infants developing autism spectrum disorder. NEUROIMAGE-CLINICAL 2020; 29:102551. [PMID: 33421871 PMCID: PMC7806791 DOI: 10.1016/j.nicl.2020.102551] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/25/2020] [Accepted: 12/21/2020] [Indexed: 12/21/2022]
Abstract
Pediatric neuroimaging study of Autism Spectrum Disorder. Longitudinal Tensor Based Morphometry of the presymptomatic period of ASD. Differences in voxelwise growth trajectories of children with ASD. Regions with differences have been implicated in the core symptoms of ASD.
Autism Spectrum Disorder (ASD) is a phenotypically and etiologically heterogeneous developmental disorder typically diagnosed around 4 years of age. The development of biomarkers to help in earlier, presymptomatic diagnosis could facilitate earlier identification and therefore earlier intervention and may lead to better outcomes, as well as providing information to help better understand the underlying mechanisms of ASD. In this study, magnetic resonance imaging (MRI) scans of infants at high familial risk, from the Infant Brain Imaging Study (IBIS), at 6, 12 and 24 months of age were included in a morphological analysis, fitting a mixed-effects model to Tensor Based Morphometry (TBM) results to obtain voxel-wise growth trajectories. Subjects were grouped by familial risk and clinical diagnosis at 2 years of age. Several regions, including the posterior cingulate gyrus, the cingulum, the fusiform gyrus, and the precentral gyrus, showed a significant effect for the interaction of group and age associated with ASD, either as an increased or a decreased growth rate of the cerebrum. In general, our results showed increased growth rate within white matter with decreased growth rate found mostly in grey matter. Overall, the regions showing increased growth rate were larger and more numerous than those with decreased growth rate. These results detail, at the voxel level, differences in brain growth trajectories in ASD during the first years of life, previously reported in terms of overall brain volume and surface area.
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Affiliation(s)
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - V S Fonov
- Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - K N Botteron
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA
| | - R C McKinstry
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO 63110, USA
| | - G Gerig
- Tandon School of Engineering, New York University, New York, New York 10003, USA
| | - J R Pruett
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - S R Dager
- Department of Radiology, University of Washington, Seattle, WA 98105, USA
| | - J T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - M A Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - A C Evans
- Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - J Piven
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - D L Collins
- Montreal Neurological Institute, McGill University, Montreal, Quebec H3A 0G4, Canada
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Conti E, Retico A, Palumbo L, Spera G, Bosco P, Biagi L, Fiori S, Tosetti M, Cipriani P, Cioni G, Muratori F, Chilosi A, Calderoni S. Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study. J Pers Med 2020; 10:E275. [PMID: 33322765 PMCID: PMC7768516 DOI: 10.3390/jpm10040275] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/07/2020] [Accepted: 12/09/2020] [Indexed: 01/08/2023] Open
Abstract
Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34-74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.
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Affiliation(s)
- Eugenia Conti
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Alessandra Retico
- National Institute for Nuclear Physics (INFN), Pisa Division, 56127 Pisa, Italy; (A.R.); (L.P.); (G.S.)
| | - Letizia Palumbo
- National Institute for Nuclear Physics (INFN), Pisa Division, 56127 Pisa, Italy; (A.R.); (L.P.); (G.S.)
| | - Giovanna Spera
- National Institute for Nuclear Physics (INFN), Pisa Division, 56127 Pisa, Italy; (A.R.); (L.P.); (G.S.)
| | - Paolo Bosco
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Laura Biagi
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Simona Fiori
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Michela Tosetti
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Paola Cipriani
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Giovanni Cioni
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
| | - Filippo Muratori
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
| | - Anna Chilosi
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
| | - Sara Calderoni
- IRCCS Fondazione Stella Maris, 56128 Pisa, Italy; (E.C.); (P.B.); (L.B.); (S.F.); (M.T.); (P.C.); (G.C.); (F.M.); (A.C.)
- Department of Clinical and Experimental Medicine, University of Pisa, 56126 Pisa, Italy
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Crucitti J, Hyde C, Stokes MA. Hammering that Nail: Varied Praxis Motor Skills in Younger Autistic Children. J Autism Dev Disord 2020; 50:3253-3262. [PMID: 31297643 DOI: 10.1007/s10803-019-04136-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Previous studies measuring praxis abilities in young autistic children have only used praxis measures that were not optimised for autistic individuals. Hence, we used the FAB-R to measure praxis skills in autistic (n = 38) and typically developing (TD) children (n = 38) aged between four and 10 years. Praxis abilities were generally not different between autistic and TD children. However, total dyspraxia and errors during verbal command and tool use were impaired in autistic children from a specialist autistic school (SAS). In contrast, autistic participants from the GC typically did not differ in praxis performance compared to controls. Hence, praxis abilities significantly vary between autistic younger children. Exploring mediating influences of such variability is imperative.
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Affiliation(s)
- Joel Crucitti
- School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia
| | - Christian Hyde
- School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia
| | - Mark A Stokes
- School of Psychology, Faculty of Health, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia.
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Lai M, Lee J, Chiu S, Charm J, So WY, Yuen FP, Kwok C, Tsoi J, Lin Y, Zee B. A machine learning approach for retinal images analysis as an objective screening method for children with autism spectrum disorder. EClinicalMedicine 2020; 28:100588. [PMID: 33294809 PMCID: PMC7700906 DOI: 10.1016/j.eclinm.2020.100588] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 09/17/2020] [Accepted: 09/24/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is characterised by many of features including problem in social interactions, different ways of learning, some children showing a keen interest in specific subjects, inclination to routines, challenges in typical communication, and particular ways of processing sensory information. Early intervention and suitable supports for these children may make a significant contribution to their development. However, considerable difficulties have been encountered in the screening and diagnosis of ASD. The literature has indicated that certain retinal features are significantly associated with ASD. In this study, we investigated the use of machine learning approaches on retinal images to further enhance the classification accuracy. METHODS Forty-six ASD participants were recruited from three special needs schools and 24 normal control were recruited from the community. Among them, 23 age-gender matched ASD and normal control participant-pairs were constructed for the primary analysis. All retinal images were captured using a nonmydriatic fundus camera. Automatic retinal image analysis (ARIA) methodology applying machine-learning technology was used to optimise the information of the retina to develop a classification model for ASD. The model's validity was then assessed using a 10-fold cross-validation approach to assess its validity. FINDINGS The sensitivity and specificity were 95.7% (95% CI 76.0%, 99.8%) and 91.3% (95% CI 70.5%, 98.5%) respectively. The area under the ROC curve was 0.974 (95% CI 0.934, 1.000); however, it was noted that the specificity for female participants might not be as high as that for male participants. INTERPRETATION Because ARIA is a fully automatic cloud-based algorithm and relies only on retinal images, it can be used as a risk assessment tool for ASD screening. Further diagnosis and confirmation can then be made by professionals, and potential treatment may be provided at a relatively early stage.
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Affiliation(s)
- Maria Lai
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | - Jack Lee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | | | | | - Wing Yee So
- The Jockey Club Hong Chi School, Wan Chai, Hong Kong SAR
| | - Fung Ping Yuen
- The Hong Chi Morninghill School, Tuen Mun, Hong Kong SAR
| | - Chloe Kwok
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | - Jasmine Tsoi
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | - Yuqi Lin
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
| | - Benny Zee
- Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR
- Clinical Trials and Biostatistics Lab, CUHK Shenzhen Research Institute, Shenzhen, China
- Corresponding author at: Centre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong SAR
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Wang J, Wang X, Wang X, Zhang H, Zhou Y, Chen L, Li Y, Wu L. Increased EEG coherence in long-distance and short-distance connectivity in children with autism spectrum disorders. Brain Behav 2020; 10:e01796. [PMID: 32815287 PMCID: PMC7559606 DOI: 10.1002/brb3.1796] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/20/2022] Open
Abstract
INTRODUCTION Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD. METHODS Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long-distance and short-distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD. RESULTS Compared with TD group, individuals with ASD showed increased coherence in short-distance electrode pairs in the right temporal-parietal region (delta, alpha, beta bands), left temporal-parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central-parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long-distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal-occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity. DISCUSSION Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism.
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Affiliation(s)
- Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xiaomin Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Xuelai Wang
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huiying Zhang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Yong Zhou
- Heilongjiang Province Center for Disease Control and Prevention, Harbin, China
| | - Lei Chen
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Yutong Li
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin, China
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Genovese A, Butler MG. Clinical Assessment, Genetics, and Treatment Approaches in Autism Spectrum Disorder (ASD). Int J Mol Sci 2020; 21:E4726. [PMID: 32630718 PMCID: PMC7369758 DOI: 10.3390/ijms21134726] [Citation(s) in RCA: 93] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 06/24/2020] [Accepted: 06/27/2020] [Indexed: 12/16/2022] Open
Abstract
Autism spectrum disorder (ASD) consists of a genetically heterogenous group of neurobehavioral disorders characterized by impairment in three behavioral domains including communication, social interaction, and stereotypic repetitive behaviors. ASD affects more than 1% of children in Western societies, with diagnoses on the rise due to improved recognition, screening, clinical assessment, and diagnostic testing. We reviewed the role of genetic and metabolic factors which contribute to the causation of ASD with the use of new genetic technology. Up to 40 percent of individuals with ASD are now diagnosed with genetic syndromes or have chromosomal abnormalities including small DNA deletions or duplications, single gene conditions, or gene variants and metabolic disturbances with mitochondrial dysfunction. Although the heritability estimate for ASD is between 70 and 90%, there is a lower molecular diagnostic yield than anticipated. A likely explanation may relate to multifactorial causation with etiological heterogeneity and hundreds of genes involved with a complex interplay between inheritance and environmental factors influenced by epigenetics and capabilities to identify causative genes and their variants for ASD. Behavioral and psychiatric correlates, diagnosis and genetic evaluation with testing are discussed along with psychiatric treatment approaches and pharmacogenetics for selection of medication to treat challenging behaviors or comorbidities commonly seen in ASD. We emphasize prioritizing treatment based on targeted symptoms for individuals with ASD, as treatment will vary from patient to patient based on diagnosis, comorbidities, causation, and symptom severity.
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Affiliation(s)
| | - Merlin G. Butler
- Department of Psychiatry & Behavioral Sciences, University of Kansas Medical Center, Kansas City, KS 66160, USA;
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Saxena R, Babadi M, Namvarhaghighi H, Roullet FI. Role of environmental factors and epigenetics in autism spectrum disorders. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 173:35-60. [PMID: 32711816 DOI: 10.1016/bs.pmbts.2020.05.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder thought to be caused by predisposing high-risk genes that may be altered during the early development by environmental factors. The impact of maternal challenges during pregnancy on the prevalence of ASD has been widely studied in clinical and animal studies. Here, we review some clinical and pre-clinical evidence that links environmental factors (i.e., infection, air pollution, pesticides, valproic acid and folic acid) and the risk of ASD. Additionally, certain prenatal environmental challenges such as the valproate and folate prenatal exposures allow us to study mechanisms possibly linked to the etiology of ASD, for instance the epigenetic processes. These mechanistic pathways are also presented and discussed in this chapter.
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Affiliation(s)
- Roheeni Saxena
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, United States
| | - Melika Babadi
- School of Interdisciplinary Science, McMaster University, Hamilton, ON, Canada
| | | | - Florence I Roullet
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
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Yankowitz LD, Herrington JD, Yerys BE, Pereira JA, Pandey J, Schultz RT. Evidence against the "normalization" prediction of the early brain overgrowth hypothesis of autism. Mol Autism 2020; 11:51. [PMID: 32552879 PMCID: PMC7301552 DOI: 10.1186/s13229-020-00353-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 05/21/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND The frequently cited Early Overgrowth Hypothesis of autism spectrum disorder (ASD) postulates that there is overgrowth of the brain in the first 2 years of life, which is followed by a period of arrested growth leading to normalized brain volume in late childhood and beyond. While there is consistent evidence for early brain overgrowth, there is mixed evidence for normalization of brain volume by middle childhood. The outcome of this debate is important to understanding the etiology and neurodevelopmental trajectories of ASD. METHODS Brain volume was examined in two very large single-site samples of children, adolescents, and adults. The primary sample comprised 456 6-25-year-olds (ASD n = 240, typically developing controls (TDC) n = 216), including a large number of females (n = 102) and spanning a wide IQ range (47-158). The replication sample included 175 males. High-resolution T1-weighted anatomical MRI images were examined for group differences in total brain, cerebellar, ventricular, gray, and white matter volumes. RESULTS The ASD group had significantly larger total brain, cerebellar, gray matter, white matter, and lateral ventricular volumes in both samples, indicating that brain volume remains enlarged through young adulthood, rather than normalizing. There were no significant age or sex interactions with diagnosis in these measures. However, a significant diagnosis-by-IQ interaction was detected in the larger sample, such that increased brain volume was related to higher IQ in the TDCs, but not in the ASD group. Regions-of-significance analysis indicated that total brain volume was larger in ASD than TDC for individuals with IQ less than 115, providing a potential explanation for prior inconsistent brain size results. No relationships were found between brain volume and measures of autism symptom severity within the ASD group. LIMITATIONS Our cross-sectional sample may not reflect individual changes over time in brain volume and cannot quantify potential changes in volume prior to age 6. CONCLUSIONS These findings challenge the "normalization" prediction of the brain overgrowth hypothesis by demonstrating that brain enlargement persists across childhood into early adulthood. The findings raise questions about the clinical implications of brain enlargement, since we find that it neither confers cognitive benefits nor predicts increased symptom severity in ASD.
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Affiliation(s)
- Lisa D Yankowitz
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA.
- Department of Psychology, University of Pennsylvania, 425 S. University Ave, Philadelphia, PA, 19104, USA.
| | - John D Herrington
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA
| | - Benjamin E Yerys
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA
| | - Joseph A Pereira
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA
- Harvard Medical School, 25 Shattuck St, Boston, MA, 02115, USA
| | - Juhi Pandey
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA
| | - Robert T Schultz
- Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA
- Department of Pediatrics Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA
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Ikemoto S, Hamano SI, Yokota S, Koichihara R, Hirata Y, Matsuura R. High-power, frontal-dominant ripples in absence status epilepticus during childhood. Clin Neurophysiol 2020; 131:1204-1209. [DOI: 10.1016/j.clinph.2020.02.024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 01/28/2020] [Accepted: 02/12/2020] [Indexed: 11/25/2022]
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Thompson A, Shahidiani A, Fritz A, O’Muircheartaigh J, Walker L, D’Almeida V, Murphy C, Daly E, Murphy D, Williams S, Deoni S, Ecker C. Age-related differences in white matter diffusion measures in autism spectrum condition. Mol Autism 2020; 11:36. [PMID: 32423424 PMCID: PMC7236504 DOI: 10.1186/s13229-020-00325-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 03/03/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions. METHODS Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age. RESULTS We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls. LIMITATIONS The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group. CONCLUSIONS Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.
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Affiliation(s)
- Abigail Thompson
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Developmental Change & Plasticity Lab, Department of Psychology & Language Sciences, University College London, 26 Bedford Way, Bloomsbury, London, WC1H 0AP UK
| | - Asal Shahidiani
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Anne Fritz
- The Centre for Research in Autism and Education (CRAE), Psychology and Human Development, UCL, London, UK
| | - Jonathan O’Muircheartaigh
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, St. Thomas’ Hospital, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Lindsay Walker
- Advanced Baby Imaging Lab, Hasbro Childrens Hospital, Providence, RI USA
- Pediatrics and Radiology, Warren Alpert medical school, Brown University, Providence, USA
| | - Vera D’Almeida
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Clodagh Murphy
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Eileen Daly
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Declan Murphy
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Steve Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, UK
| | - Sean Deoni
- Advanced Baby Imaging Lab, Hasbro Childrens Hospital, Providence, RI USA
- Pediatrics and Radiology, Warren Alpert medical school, Brown University, Providence, USA
- Maternal, Newborn & Child Health Discovery & Tools at the Bill and Melinda Gates Foundation, Seattle, USA
| | - Christine Ecker
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Deutschordenstrasse 50, 60528 Frankfurt am Main, Germany
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The role of neuroglia in autism spectrum disorders. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 173:301-330. [PMID: 32711814 DOI: 10.1016/bs.pmbts.2020.04.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Neuroglia are a large class of neural cells of ectodermal (astroglia, oligodendroglia, and peripheral glial cells) and mesodermal (microglia) origin. Neuroglial cells provide homeostatic support, protection, and defense to the nervous tissue. Pathological potential of neuroglia has been acknowledged since their discovery. Research of the recent decade has shown the key role of all classes of glial cells in autism spectrum disorders (ASD), although molecular mechanisms defining glial contribution to ASD are yet to be fully characterized. This narrative conceptualizes recent findings of the broader roles of glial cells, including their active participation in the control of cerebral environment and regulation of synaptic development and scaling, highlighting their putative involvement in the etiopathogenesis of ASD.
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Geng X, Kang X, Wong PCM. Autism spectrum disorder risk prediction: A systematic review of behavioral and neural investigations. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2020; 173:91-137. [PMID: 32711819 DOI: 10.1016/bs.pmbts.2020.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
A reliable diagnosis of autism spectrum disorder (ASD) is difficult to make until after toddlerhood. Detection in an earlier age enables early intervention, which is typically more effective. Recent studies of the development of brain and behavior in infants and toddlers have provided important insights in the diagnosis of autism. This extensive review focuses on published studies of predicting the diagnosis of autism during infancy and toddlerhood younger than 3 years using behavioral and neuroimaging approaches. After screening a total of 782 papers, 17 neuroimaging and 43 behavioral studies were reviewed. The features for prediction consist of behavioral measures using screening tools, observational and experimental methods, brain volumetric measures, and neural functional activation and connectivity patterns. The classification approaches include logistic regression, linear discriminant function, decision trees, support vector machine, and deep learning based methods. Prediction performance has large variance across different studies. For behavioral studies, the sensitivity varies from 20% to 100%, and specificity ranges from 48% to 100%. The accuracy rates range from 61% to 94% in neuroimaging studies. Possible factors contributing to this inconsistency may be partially due to the heterogeneity of ASD, different targeted populations (i.e., high-risk group for ASD and general population), age when the features were collected, and validation procedures. The translation to clinical practice requires extensive further research including external validation with large sample size and optimized feature selection. The use of multi-modal features, e.g., combination of neuroimaging and behavior, is worth further investigation to improve the prediction accuracy.
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Affiliation(s)
- Xiujuan Geng
- Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong.
| | - Xin Kang
- Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, Hong Kong.
| | - Patrick C M Wong
- Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, Hong Kong; Department of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong, Shatin, Hong Kong
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47
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Li J, Lin X, Wang M, Hu Y, Xue K, Gu S, Lv L, Huang S, Xie W. Potential role of genomic imprinted genes and brain developmental related genes in autism. BMC Med Genomics 2020; 13:54. [PMID: 32216802 PMCID: PMC7099798 DOI: 10.1186/s12920-020-0693-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 02/11/2020] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Autism is a complex disease involving both environmental and genetic factors. Recent efforts have implicated the correlation of genomic imprinting and brain development in autism, however the pathogenesis of autism is not completely clear. Here, we used bioinformatic tools to provide a comprehensive analysis of the autism-related genes, genomic imprinted genes and the spatially and temporally differentially expressed genes of human brain, aiming to explore the relationship between autism, brain development and genomic imprinting. METHODS This study analyzed the distribution correlation between autism-related genes and imprinted genes on chromosomes using sliding windows and statistical methods. The normal brains' gene expression microarray data were reanalyzed to construct a spatio-temporal coordinate system of gene expression during brain development. Finally, we intersected the autism-related genes, imprinted genes and brain spatio-temporally differentially expressed genes for further analysis to find the major biological processes that these genes involved. RESULTS We found a positive correlation between the autism-related genes' and imprinted genes' distribution on chromosomes. Through the analysis of the normal brain microarray data, we constructed a spatio-temporal coordinate system of gene expression during human brain development, and obtained 13 genes that are differentially expressed in the process of brain development, which are both autism-related genes and imprinted genes. Furthermore, enrichment analysis illustrated that these genes are mainly involved in the biological processes, such as gamma-aminobutyric acid signaling pathway, neuron recognition, learning or memory, and regulation of synaptic transmission. Bioinformatic analysis implied that imprinted genes regulate the development and behavior of the brain. And its own mutation or changes in the epigenetic modification state of the imprinted control region could lead to some diseases, indicating that imprinted genes and brain development play an important role in diagnosis and prognosis of autism. CONCLUSION This study systematically correlates brain development and genomic imprinting with autism, which provides a new perspective for the study of genetic mechanisms of autism, and selected the potential candidate biomarkers for early diagnosis of autism in clinic.
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Affiliation(s)
- Jian Li
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China.
| | - Xue Lin
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, 211166, China
| | - Mingya Wang
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Yunyun Hu
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Kaiyu Xue
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Shuanglin Gu
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Li Lv
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China
| | - Saijun Huang
- Foshan Women and Children Hospital, Foshan, 528000, China
| | - Wei Xie
- Key Laboratory of DGHD, MOE, Institute of Life Sciences, Southeast University, Nanjing, 210096, China.
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Hegarty JP, Lazzeroni LC, Raman MM, Pegoraro LFL, Monterrey JC, Cleveland SC, Hallmayer JF, Wolke ON, Phillips JM, Reiss AL, Hardan AY. Genetic and Environmental Influences on Lobar Brain Structures in Twins With Autism. Cereb Cortex 2020; 30:1946-1956. [PMID: 31711118 DOI: 10.1093/cercor/bhz215] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 07/26/2019] [Accepted: 08/18/2019] [Indexed: 11/13/2022] Open
Abstract
This investigation examined whether the variation of cerebral structure is associated with genetic or environmental factors in children with autism spectrum disorder (ASD) compared with typically developing (TD) controls. T1-weighted magnetic resonance imaging scans were obtained from twin pairs (aged 6-15 years) in which at least one twin was diagnosed with ASD or both were TD. Good quality data were available from 30 ASD, 18 discordant, and 34 TD pairs (n = 164). Structural measures (volume, cortical thickness, and surface area) were generated with FreeSurfer, and ACE modeling was completed. Lobar structures were primarily genetically mediated in TD twins (a2 = 0.60-0.89), except thickness of the temporal (a2 = 0.33 [0.04, 0.63]) and occipital lobes (c2 = 0.61 [0.45, 0.77]). Lobar structures were also predominantly genetically mediated in twins with ASD (a2 = 0.70-1.00); however, thickness of the frontal (c2 = 0.81 [0.71, 0.92]), temporal (c2 = 0.77 [0.60, 0.93]), and parietal lobes (c2 = 0.87 [0.77, 0.97]), and frontal gray matter (GM) volume (c2 = 0.79 [0.63, 0.95]), were associated with environmental factors. Conversely, occipital thickness (a2 = 0.93 [0.75, 1.11]) did not exhibit the environmental contributions that were found in controls. Differences in GM volume were associated with social communication impairments for the frontal (r = 0.52 [0.18, 0.75]), temporal (r = 0.61 [0.30, 0.80]), and parietal lobes (r = 0.53 [0.19, 0.76]). To our knowledge, this is the first investigation to suggest that environmental factors influence GM to a larger extent in children with ASD, especially in the frontal lobe.
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Affiliation(s)
- John P Hegarty
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA.,Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Mira M Raman
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Luiz F L Pegoraro
- Department of Psychiatry, University of Campinas, Cidade Universitária Zeferino Vaz, Campinas 13083-970, Brazil
| | - Julio C Monterrey
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Sue C Cleveland
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Joachim F Hallmayer
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Olga N Wolke
- Department of Anesthesiology, Stanford University, Stanford, CA 94305, USA
| | - Jennifer M Phillips
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Allan L Reiss
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Antonio Y Hardan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
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Richards R, Greimel E, Kliemann D, Koerte IK, Schulte-Körne G, Reuter M, Wachinger C. Increased hippocampal shape asymmetry and volumetric ventricular asymmetry in autism spectrum disorder. NEUROIMAGE-CLINICAL 2020; 26:102207. [PMID: 32092683 PMCID: PMC7037573 DOI: 10.1016/j.nicl.2020.102207] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 01/20/2020] [Accepted: 02/03/2020] [Indexed: 02/06/2023]
Abstract
Found increased subcortical asymmetry associated with autism. Utilized a new measure of shape asymmetry for analysis of structural differences. Observed significantly increased shape asymmetry of the hippocampus. Observed significantly increased volumetric asymmetry in the lateral ventricles. Focalized abnormalities may result in detectable shape (but not volume) differences.
Autism spectrum disorder (ASD) is a prevalent and fast-growing pervasive neurodevelopmental disorder worldwide. Despite the increasing prevalence of ASD and the breadth of research conducted on the disorder, a conclusive etiology has yet to be established and controversy still exists surrounding the anatomical abnormalities in ASD. In particular, structural asymmetries have seldom been investigated in ASD, especially in subcortical regions. Additionally, the majority of studies for identifying structural biomarkers associated with ASD have focused on small sample sizes. Therefore, the present study utilizes a large-scale, multi-site database to investigate asymmetries in the amygdala, hippocampus, and lateral ventricles, given the potential involvement of these regions in ASD. Contrary to prior work, we are not only computing volumetric asymmetries, but also shape asymmetries, using a new measure of asymmetry based on spectral shape descriptors. This measure represents the magnitude of the asymmetry and therefore captures both directional and undirectional asymmetry. The asymmetry analysis is conducted on 437 individuals with ASD and 511 healthy controls using T1-weighted MRI scans from the Autism Brain Imaging Data Exchange (ABIDE) database. Results reveal significant asymmetries in the hippocampus and the ventricles, but not in the amygdala, in individuals with ASD. We observe a significant increase in shape asymmetry in the hippocampus, as well as increased volumetric asymmetry in the lateral ventricles in individuals with ASD. Asymmetries in these regions have not previously been reported, likely due to the different characterization of neuroanatomical asymmetry and smaller sample sizes used in previous studies. Given that these results were demonstrated in a large cohort, such asymmetries may be worthy of consideration in the development of neurodiagnostic classification tools for ASD.
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Affiliation(s)
- Rose Richards
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, University Hospital, Ludwig-Maximilian-University, Nussbaumstr. 5a, 80336 Munich, Germany.
| | - Ellen Greimel
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, University Hospital, Ludwig-Maximilian-University, Nussbaumstr. 5a, 80336 Munich, Germany
| | - Dorit Kliemann
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA
| | - Inga K Koerte
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, University Hospital, Ludwig-Maximilian-University, Nussbaumstr. 5a, 80336 Munich, Germany; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gerd Schulte-Körne
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, University Hospital, Ludwig-Maximilian-University, Nussbaumstr. 5a, 80336 Munich, Germany
| | - Martin Reuter
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 Thirteenth Street, Suite 2301, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA; Image Analysis, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Christian Wachinger
- Department of Child and Adolescent Psychiatry, Psychosomatic and Psychotherapy, University Hospital, Ludwig-Maximilian-University, Nussbaumstr. 5a, 80336 Munich, Germany.
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Dong Z, Chen W, Chen C, Wang H, Cui W, Tan Z, Robinson H, Gao N, Luo B, Zhang L, Zhao K, Xiong WC, Mei L. CUL3 Deficiency Causes Social Deficits and Anxiety-like Behaviors by Impairing Excitation-Inhibition Balance through the Promotion of Cap-Dependent Translation. Neuron 2020; 105:475-490.e6. [PMID: 31780330 PMCID: PMC7007399 DOI: 10.1016/j.neuron.2019.10.035] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 08/11/2019] [Accepted: 10/27/2019] [Indexed: 01/30/2023]
Abstract
Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with symptoms including social deficits, anxiety, and communication difficulties. However, ASD pathogenic mechanisms are poorly understood. Mutations of CUL3, which encodes Cullin 3 (CUL3), a component of an E3 ligase complex, are thought of as risk factors for ASD and schizophrenia (SCZ). CUL3 is abundant in the brain, yet little is known of its function. Here, we show that CUL3 is critical for neurodevelopment. CUL3-deficient mice exhibited social deficits and anxiety-like behaviors with enhanced glutamatergic transmission and neuronal excitability. Proteomic analysis revealed eIF4G1, a protein for Cap-dependent translation, as a potential target of CUL3. ASD-associated cellular and behavioral deficits could be rescued by pharmacological inhibition of the eIF4G1 function and chemogenetic inhibition of neuronal activity. Thus, CUL3 is critical to neural development, neurotransmission, and excitation-inhibition (E-I) balance. Our study provides novel insight into the pathophysiological mechanisms of ASD and SCZ.
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Affiliation(s)
- Zhaoqi Dong
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Wenbing Chen
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Chao Chen
- The Laboratory of Vector Biology and Control, College of Engineering, Beijing Normal University (Zhuhai), Zhuhai 519085, China
| | - Hongsheng Wang
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Wanpeng Cui
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Zhibing Tan
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Heath Robinson
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Nannan Gao
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Bin Luo
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Lei Zhang
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Kai Zhao
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA
| | - Wen-Cheng Xiong
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA; Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, USA
| | - Lin Mei
- Department of Neurosciences, School of Medicine, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA; Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, USA.
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