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Zadok N, Ast G, Sharan R. A network-based method for associating genes with autism spectrum disorder. FRONTIERS IN BIOINFORMATICS 2024; 4:1295600. [PMID: 38525240 PMCID: PMC10960359 DOI: 10.3389/fbinf.2024.1295600] [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: 09/16/2023] [Accepted: 02/26/2024] [Indexed: 03/26/2024] Open
Abstract
Autism spectrum disorder (ASD) is a highly heritable complex disease that affects 1% of the population, yet its underlying molecular mechanisms are largely unknown. Here we study the problem of predicting causal genes for ASD by combining genome-scale data with a network propagation approach. We construct a predictor that integrates multiple omic data sets that assess genomic, transcriptomic, proteomic, and phosphoproteomic associations with ASD. In cross validation our predictor yields mean area under the ROC curve of 0.87 and area under the precision-recall curve of 0.89. We further show that it outperforms previous gene-level predictors of autism association. Finally, we show that we can use the model to predict genes associated with Schizophrenia which is known to share genetic components with ASD.
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Affiliation(s)
- Neta Zadok
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
| | - Gil Ast
- Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Roded Sharan
- Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel
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2
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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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Parrella NF, Hill AT, Dipnall LM, Loke YJ, Enticott PG, Ford TC. Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review. J Psychiatr Res 2024; 169:113-125. [PMID: 38016393 DOI: 10.1016/j.jpsychires.2023.11.014] [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: 04/13/2023] [Revised: 09/04/2023] [Accepted: 11/15/2023] [Indexed: 11/30/2023]
Abstract
The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.
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Affiliation(s)
| | - Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Department of Psychiatry, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Lillian M Dipnall
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Early Life Epigenetics Group, Deakin University, Geelong, Australia
| | - Yuk Jing Loke
- Epigenetics Group, Murdoch Children's Research Institute, Melbourne, Victoria, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia
| | - Talitha C Ford
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia; Centre for Human Psychopharmacology, Faculty of Health, Arts and Design, Swinburne University of Technology, Melbourne, Victoria, Australia
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4
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Faraji R, Ganji Z, Zamanpour SA, Nikparast F, Akbari-Lalimi H, Zare H. Impaired white matter integrity in infants and young children with autism spectrum disorder: What evidence does diffusion tensor imaging provide? Psychiatry Res Neuroimaging 2023; 335:111711. [PMID: 37741094 DOI: 10.1016/j.pscychresns.2023.111711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 02/26/2023] [Accepted: 08/26/2023] [Indexed: 09/25/2023]
Abstract
BACKGROUND Abnormal functional connections are associated with impaired white matter tract integrity in the brain. Diffusion tensor imaging (DTI) is a promising method for evaluating white matter integrity in infants and young children. This work aims to shed light on the location and nature of the decrease in white matter integrity. METHODS Here, the results of 19 studies have been presented that investigated white matter integrity in infants and young children (6 months to 12 years) with autism using diffusion tensor imaging. RESULTS In most of the reviewed studies, an increase in Fractional Anisotropy (FA) and a decrease in Radial Diffusivity (RD) were reported in Corpus Callosum (CC), Uncinate Fasciculus (UF), Cingulum (Cg), Inferior Longitudinal Fasciculus (ILF), and Superior Longitudinal Fasciculus (SLF), and in the Inferior Fronto-Occipital Fasciculus (IFOF) tract, a decrease in FA and an increase in RD were reported. CONCLUSION In the reviewed articles, except for one study, the diffusion indices were different compared to the control group.
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Affiliation(s)
- Reyhane Faraji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Zohreh Ganji
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Seyed Amir Zamanpour
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Farzaneh Nikparast
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hossein Akbari-Lalimi
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hoda Zare
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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5
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Rasheed N. A brief report on autism awareness: A pervasive developmental brain disorder. Int J Health Sci (Qassim) 2023; 17:1-2. [PMID: 37151742 PMCID: PMC10155248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/09/2023] Open
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Repetitive transcranial magnetic stimulation modulates long-range functional connectivity in autism spectrum disorder. J Psychiatr Res 2023; 160:187-194. [PMID: 36841084 DOI: 10.1016/j.jpsychires.2023.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/12/2023] [Accepted: 02/20/2023] [Indexed: 02/23/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is growingly applied in autism spectrum disorder (ASD) due to its potential therapeutic value, however, its effects on functional network configuration and the mechanism underlying clinical improvement are still unclear. In this study, we examined the alternations of functional connectivity induced by rTMS using resting-state electroencephalogram (EEG) in children with ASD. Resting-state EEG was obtained from 24 children with ASD before and after rTMS intervention and from 24 age- and gender-matched typically developing (TD) children. The rTMS intervention course consisted of five 5-s trains at 15 Hz, with 10-min inter-train intervals, on the left parietal lobe each consecutive weekday for 3 weeks (15 sessions in total). Children with ASD showed significantly hypo-connected networks and sub-optimal network properties at both global and local levels, compared with TD peers. After rTMS intervention, long-range intra- and inter-hemispheric connections were significantly promoted, especially those within the alpha band. Meanwhile, network properties at both local and global levels were greatly promoted in the delta, theta, and alpha bands. Consistent with the changes in the network connectivities and properties, the core symptoms in ASD were also relieved measured by clinical scales after treatment. The findings of this study demonstrate that high-frequency rTMS over the parietal lobe is potentially an effective strategy to improve core symptoms by enhancing long-range connectivity reorganization in ASD.
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Cohen AL, Kroeck MR, Wall J, McManus P, Ovchinnikova A, Sahin M, Krueger DA, Bebin EM, Northrup H, Wu JY, Warfield SK, Peters JM, Fox MD. Tubers Affecting the Fusiform Face Area Are Associated with Autism Diagnosis. Ann Neurol 2023; 93:577-590. [PMID: 36394118 PMCID: PMC9974824 DOI: 10.1002/ana.26551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 11/11/2022] [Accepted: 11/13/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Tuberous sclerosis complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms. METHODS We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at 8 regions of interest derived from the ASD neuroimaging literature, including the anterior cingulate, orbitofrontal and posterior parietal cortices, inferior frontal and fusiform gyri, superior temporal sulcus, amygdala, and supplemental motor area. Next, we performed an unbiased data-driven voxelwise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses. RESULTS There were no significant ASD-related differences in tuber burden across the whole brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis, we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD. INTERPRETATION Although TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. ANN NEUROL 2023;93:577-590.
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Affiliation(s)
- Alexander L Cohen
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mallory R Kroeck
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Juliana Wall
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter McManus
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Arina Ovchinnikova
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Darcy A Krueger
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - E Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School at University of Texas Health Science Center at Houston and Children's Memorial Hermann Hospital, Houston, TX, USA
| | - Joyce Y Wu
- Division of Neurology & Epilepsy, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jurriaan M Peters
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
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8
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Neuraxial analgesia in labour and the fetus. Best Pract Res Clin Anaesthesiol 2023. [DOI: 10.1016/j.bpa.2023.02.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
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Arnatkeviciute A, Markello RD, Fulcher BD, Misic B, Fornito A. Toward Best Practices for Imaging Transcriptomics of the Human Brain. Biol Psychiatry 2023; 93:391-404. [PMID: 36725139 DOI: 10.1016/j.biopsych.2022.10.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/03/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022]
Abstract
Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.
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Affiliation(s)
- Aurina Arnatkeviciute
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia.
| | - Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Ben D Fulcher
- School of Physics, The University of Sydney, Sydney, New South Wales, Australia
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia
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Wang H, Wu X, Chen Y, Hou F, Zhu K, Jiang Q, Xiao P, Zhang Q, Xiang Z, Fan Y, Xie X, Li L, Song R. Combining multi-omics approaches to prioritize the variant-regulated functional long non-coding RNAs in autism spectrum disorder. Asian J Psychiatr 2023; 80:103357. [PMID: 36462391 DOI: 10.1016/j.ajp.2022.103357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/14/2022] [Accepted: 11/25/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Rising evidence has indicated that long non-coding RNA (lncRNA) may play an essential role in the development of autism spectrum disorder (ASD). However, identifying the lncRNAs associated with ASD and the risk loci on them remains a major challenge. This study aims to identify potential causative variants and explore the related mechanisms. METHODS By leveraging differential expression analysis, WGCNA analysis and cis-expression quantitative analysis, our study mined functional SNPs with the regulated long non-coding RNA genes in brain tissues. We recruited 611 ASD children and 645 healthy children in the case-control study. RESULTS Total 68 different expressed lncRNAs were validated by calculating the brain tissue-specific expression using RNA-seq data. By the WGCNA method, 9 functional lncRNAs classified as e-lncRNA were found to interact with 976 ASD risk genes. Furthermore, we mined functional SNPs regulated long non-coding RNAs in brain tissues. We analyzed the association between candidate SNPs and ASD risks in Chinese children, which showed BDNF-AS rs1565228 allele G to C reduced the risk of ASD (OR = 0.81, 95%CI: 0.66-0.98). Further bioinformatics analysis showed that the variant rs1565228 C>G with the low binding affinity of transcription factor SRF caused the decreased expression of lncRNA BDNF-AS. Our study revealed that rs2295412 in the non-coding sequence of the lncRNA gene region was significantly associated with the risk of ASD. DISCUSSION These findings suggested that the SNPs in the non-coding region of lncRNA may play important roles in the genetic susceptibility of ASD, which may facilitate the early screening of ASD.
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Affiliation(s)
- Haoxue Wang
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xvfang Wu
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yanlin Chen
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen 518019, China
| | - Fang Hou
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen 518019, China
| | - Kaiheng Zhu
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qi Jiang
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Pei Xiao
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Quan Zhang
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhen Xiang
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yixi Fan
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xinyan Xie
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Li Li
- Maternity and Children Health Care Hospital of Luohu District, Shenzhen 518019, China.
| | - Ranran Song
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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Klöbl M, Prillinger K, Diehm R, Doganay K, Lanzenberger R, Poustka L, Plener P, Konicar L. Individual brain regulation as learned via neurofeedback is related to affective changes in adolescents with autism spectrum disorder. Child Adolesc Psychiatry Ment Health 2023; 17:6. [PMID: 36635760 PMCID: PMC9837918 DOI: 10.1186/s13034-022-00549-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/18/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND Emotions often play a role in neurofeedback (NF) regulation strategies. However, investigations of the relationship between the induced neuronal changes and improvements in affective domains are scarce in electroencephalography-based studies. Thus, we extended the findings of the first study on slow cortical potential (SCP) NF in autism spectrum disorder (ASD) by linking affective changes to whole-brain activity during rest and regulation. METHODS Forty-one male adolescents with ASD were scanned twice at rest using functional magnetic resonance imaging. Between scans, half underwent NF training, whereas the other half received treatment as usual. Furthermore, parents reported on their child's affective characteristics at each measurement. The NF group had to alternatingly produce negative and positive SCP shifts during training and was additionally scanned using functional magnetic resonance imaging while applying their developed regulation strategies. RESULTS No significant treatment group-by-time interactions in affective or resting-state measures were found. However, we found increases of resting activity in the anterior cingulate cortex and right inferior temporal gyrus as well as improvements in affective characteristics over both groups. Activation corresponding to SCP differentiation in these regions correlated with the affective improvements. A further correlation was found for Rolandic operculum activation corresponding to positive SCP shifts. There were no significant correlations with the respective achieved SCP regulation during NF training. CONCLUSION SCP NF in ASD did not lead to superior improvements in neuronal or affective functioning compared to treatment as usual. However, the affective changes might be related to the individual strategies and their corresponding activation patterns as indicated by significant correlations on the whole-brain level. Trial registration This clinical trial was registered at drks.de (DRKS00012339) on 20th April, 2017.
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Affiliation(s)
- Manfred Klöbl
- Department of Psychiatry & Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Karin Prillinger
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
| | - Robert Diehm
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Kamer Doganay
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry & Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry, Medical University of Göttingen, Göttingen, Germany
| | - Paul Plener
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Ulm, Ulm, Germany
| | - Lilian Konicar
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria.
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Ippolito G, Bertaccini R, Tarasi L, Di Gregorio F, Trajkovic J, Battaglia S, Romei V. The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research. Biomedicines 2022; 10:biomedicines10123189. [PMID: 36551945 PMCID: PMC9775381 DOI: 10.3390/biomedicines10123189] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/03/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.
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Affiliation(s)
- Giuseppe Ippolito
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Riccardo Bertaccini
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Francesco Di Gregorio
- UO Medicina Riabilitativa e Neuroriabilitazione, Azienda Unità Sanitaria Locale, 40133 Bologna, Italy
| | - Jelena Trajkovic
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Simone Battaglia
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Dipartimento di Psicologia, Università di Torino, 10124 Torino, Italy
| | - Vincenzo Romei
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Correspondence:
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Kang J, Li X, Casanova MF, Sokhadze EM, Geng X. Impact of repetitive transcranial magnetic stimulation on the directed connectivity of autism EEG signals: a pilot study. Med Biol Eng Comput 2022; 60:3655-3664. [DOI: 10.1007/s11517-022-02693-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 10/06/2022] [Indexed: 11/11/2022]
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Wei L, Zhang Y, Zhai W, Wang H, Zhang J, Jin H, Feng J, Qin Q, Xu H, Li B, Liu J. Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders. Front Neurosci 2022; 16:987248. [PMID: 36523439 PMCID: PMC9745118 DOI: 10.3389/fnins.2022.987248] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/07/2022] [Indexed: 11/29/2023] Open
Abstract
INTRODUCTION Understanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effective connectivity which measures the causal interactions of these networks is also impaired in these patients remains unclear. OBJECTS The main purpose of this study was to investigate the effective connectivity of large-scale brain networks in patients with ASD during resting state. MATERIALS AND METHODS The subjects were 42 autistic children and 127 age-matched normal children from the ABIDE II dataset. We investigated effective connectivity of 7 large-scale brain networks including visual network (VN), default mode network (DMN), cerebellum, sensorimotor network (SMN), auditory network (AN), salience network (SN), frontoparietal network (FPN), with spectral dynamic causality model (spDCM). Parametric empirical Bayesian (PEB) was used to perform second-level group analysis and furnished group commonalities and differences in effective connectivity. Furthermore, we analyzed the correlation between the strength of effective connectivity and patients' clinical characteristics. RESULTS For both groups, SMN acted like a hub network which demonstrated dense effective connectivity with other large-scale brain network. We also observed significant causal interactions within the "triple networks" system, including DMN, SN and FPN. Compared with healthy controls, children with ASD showed decreased effective connectivity among some large-scale brain networks. These brain networks included VN, DMN, cerebellum, SMN, and FPN. In addition, we also found significant negative correlation between the strength of the effective connectivity from right angular gyrus (ANG_R) of DMN to left precentral gyrus (PreCG_L) of SMN and ADOS-G or ADOS-2 module 4 stereotyped behaviors and restricted interest total (ADOS_G_STEREO_BEHAV) scores. CONCLUSION Our research provides new evidence for the pathogenesis of children with ASD from the perspective of effective connections within and between large-scale brain networks. The attenuated effective connectivity of brain networks may be a clinical neurobiological feature of ASD. Changes in effective connectivity of brain network in children with ASD may provide useful information for the diagnosis and treatment of the disease.
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Affiliation(s)
- Lei Wei
- Network Center, Air Force Medical University, Xi’an, China
| | - Yao Zhang
- Military Medical Center, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Wensheng Zhai
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Air Force Medical University, Xi’an, China
| | - Junchao Zhang
- Network Center, Air Force Medical University, Xi’an, China
| | - Haojie Jin
- Network Center, Air Force Medical University, Xi’an, China
| | - Jianfei Feng
- Network Center, Air Force Medical University, Xi’an, China
| | - Qin Qin
- Network Center, Air Force Medical University, Xi’an, China
| | - Hao Xu
- Network Center, Air Force Medical University, Xi’an, China
| | - Baojuan Li
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Jian Liu
- Network Center, Air Force Medical University, Xi’an, China
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Fu L, Zhao J, Sun J, Yan Y, Ma M, Chen Q, Qiu J, Yang W. Everyday Creativity is Associated with Increased Frontal Electroencephalography Alpha Activity During Creative Ideation. Neuroscience 2022; 503:107-117. [PMID: 36115516 DOI: 10.1016/j.neuroscience.2022.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 09/02/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022]
Abstract
Everyday creativity is the basic ability of human survival and penetrates every aspect of life. Nevertheless, the neural mechanisms underlying everyday creativity was largely unexplored. In this study, seventy-five participants completed the creative behaviour inventory, a tool for assessing creative behaviour in daily life. The participants also completed the alternate uses task (AUT) during an electroencephalography (EEG) assessment to evaluate creative thinking. Alpha power was used to quantify neural oscillations during the creative process, while alpha coherence was used to quantify information communication between frontal regions and other sites during creative ideation. Moreover, these two task-related quantitative measures were combined to investigate the relationship between individual differences in everyday creativity and EEG alpha activity during creative idea generation. Compared with the reference period, increased alpha power was observed in the frontal cortex of the right hemisphere and increased functional coupling was observed between frontal and parietal/temporal regions during the activation period. Interestingly, individual differences in everyday creativity were associated with distinct patterns of EEG alpha activity. Specifically, individuals with higher everyday creativity had increased alpha power in the frontal cortex, and increased changes in coherence in frontal-temporal regions of the right hemisphere while performing the AUT. It might indicate that individuals with higher everyday creativity had an enhanced ability to focus on internal information processing and control bottom-up stimuli, as well as better selection of novel semantic information when performing creative ideation tasks.
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Affiliation(s)
- Lei Fu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Jia Zhao
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Jiangzhou Sun
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Yuchi Yan
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Mujie Ma
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Qunlin Chen
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China.
| | - Wenjing Yang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University (SWU), Chongqing 400715, China.
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16
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Cai Y, Zhao J, Wang L, Xie Y, Fan X. Altered topological properties of white matter structural network in adults with autism spectrum disorder. Asian J Psychiatr 2022; 75:103211. [PMID: 35907341 DOI: 10.1016/j.ajp.2022.103211] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex developmental disability and is currently viewed as a disorder of brain connectivity in which white matter abnormalities. However, the majority of the research to date has focused on children with ASD. Understanding the topological organization of the white matter structural network in adults may help uncover the nature of ASD pathology in adulthood. METHOD This study investigated the topological properties of white matter structural network using diffusion tensor imaging and graph theory analysis in a sample of 32 adults with ASD compared to 35 matched typically developing (TD) controls. Group differences in global and nodal topological metrics were compared. The relationships between the altered network metrics and the severity of clinical symptoms were calculated. RESULTS Compared to TD controls, ASD patients exhibited decreased small-worldness and increased global efficiency. In addition, the reduced nodal efficiency and increased nodal degree were found in the frontal (e.g., the inferior frontal gyrus) and parietal (e.g., postcentral gyrus) regions. Furthermore, the altered topological metrics (e.g., increased global efficiency and reduced nodal efficiency) were correlated with the severity of ASD symptoms. CONCLUSION These results indicated that the complicatedly topological organization of the white matter structural network was abnormal and may play an essential role in the underlying pathological mechanism of ASD in adults.
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Affiliation(s)
- Yun Cai
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Jinghui Zhao
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Lian Wang
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Yuanjun Xie
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710030, China.
| | - Xiaotang Fan
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China.
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17
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Li M, Wang Y, Tachibana M, Rahman S, Kagitani-Shimono K. Atypical structural connectivity of language networks in autism spectrum disorder: A meta-analysis of diffusion tensor imaging studies. Autism Res 2022; 15:1585-1602. [PMID: 35962721 PMCID: PMC9546367 DOI: 10.1002/aur.2789] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 07/25/2022] [Indexed: 11/20/2022]
Abstract
Patients with autism spectrum disorder (ASD) often show pervasive and complex language impairments that are closely associated with aberrant structural connectivity of language networks. However, the characteristics of white matter connectivity in ASD have remained inconclusive in previous diffusion tensor imaging (DTI) studies. The current meta‐analysis aimed to comprehensively elucidate the abnormality in language‐related white matter connectivity in individuals with ASD. We searched PubMed, Web of Science, Scopus, and Medline databases to identify relevant studies. The standardized mean difference was calculated to measure the pooled difference in DTI metrics in each tract between the ASD and typically developing (TD) groups. The moderating effects of age, sex, language ability, and symptom severity were investigated using subgroup and meta‐regression analysis. Thirty‐three DTI studies involving 831 individuals with ASD and 836 TD controls were included in the meta‐analysis. ASD subjects showed significantly lower fractional anisotropy or higher mean diffusivity across language‐associated tracts than TD controls. These abnormalities tended to be more prominent in the left language networks than in the right. In addition, children with ASD exhibit more pronounced and pervasive disturbances in white matter connectivity than adults. These results support the under‐connectivity hypothesis and demonstrate the widespread abnormal microstructure of language‐related tracts in patients with ASD. Otherwise, white matter abnormalities in the autistic brain could vary depending on the developmental stage and hemisphere.
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Affiliation(s)
- Min Li
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Yide Wang
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Masaya Tachibana
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
| | - Shafiur Rahman
- Department of Child Development, United Graduate School of Child Development, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu, Shizuoka, Japan.,Research Center for Child Mental Development, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu, Shizuoka, Japan
| | - Kuriko Kagitani-Shimono
- Department of Child Development, United Graduate School of Child Development, Osaka University, Suita, Osaka, Japan
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Ursino M, Serra M, Tarasi L, Ricci G, Magosso E, Romei V. Bottom-up vs. top-down connectivity imbalance in individuals with high-autistic traits: An electroencephalographic study. Front Syst Neurosci 2022; 16:932128. [PMID: 36032324 PMCID: PMC9412751 DOI: 10.3389/fnsys.2022.932128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/27/2022] [Indexed: 11/25/2022] Open
Abstract
Brain connectivity is often altered in autism spectrum disorder (ASD). However, there is little consensus on the nature of these alterations, with studies pointing to either increased or decreased connectivity strength across the broad autism spectrum. An important confound in the interpretation of these contradictory results is the lack of information about the directionality of the tested connections. Here, we aimed at disambiguating these confounds by measuring differences in directed connectivity using EEG resting-state recordings in individuals with low and high autistic traits. Brain connectivity was estimated using temporal Granger Causality applied to cortical signals reconstructed from EEG. Between-group differences were summarized using centrality indices taken from graph theory (in degree, out degree, authority, and hubness). Results demonstrate that individuals with higher autistic traits exhibited a significant increase in authority and in degree in frontal regions involved in high-level mechanisms (emotional regulation, decision-making, and social cognition), suggesting that anterior areas mostly receive information from more posterior areas. Moreover, the same individuals exhibited a significant increase in the hubness and out degree over occipital regions (especially the left and right pericalcarine regions, where the primary visual cortex is located), suggesting that these areas mostly send information to more anterior regions. Hubness and authority appeared to be more sensitive indices than the in degree and out degree. The observed brain connectivity differences suggest that, in individual with higher autistic traits, bottom-up signaling overcomes top-down channeled flow. This imbalance may contribute to some behavioral alterations observed in ASD.
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Affiliation(s)
- Mauro Ursino
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy
- *Correspondence: Mauro Ursino,
| | - Michele Serra
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, Cesena, Italy
| | - Giulia Ricci
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy
| | - Elisa Magosso
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy
| | - Vincenzo Romei
- Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Santa Lucia, Rome, Italy
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Talebi N, Motie Nasrabadi A. Investigating the discrimination of linear and nonlinear effective connectivity patterns of EEG signals in children with Attention-Deficit/Hyperactivity Disorder and Typically Developing children. Comput Biol Med 2022; 148:105791. [PMID: 35863245 DOI: 10.1016/j.compbiomed.2022.105791] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/06/2022] [Accepted: 06/26/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Analysis of effective connectivity among brain regions is an important key to decipher the mechanisms underlying neural disorders such as Attention Deficit Hyperactivity Disorder (ADHD). We previously introduced a new method, called nCREANN (nonlinear Causal Relationship Estimation by Artificial Neural Network), for estimating linear and nonlinear components of effective connectivity, and provided novel findings about effective connectivity of EEG signals of children with autism. Using the nCREANN method in the present study, we assessed effective connectivity patterns of ADHD children based on their EEG signals recorded during a visual attention task, and compared them with the aged-matched Typically Developing (TD) subjects. METHOD In addition to the nCREANN method for estimating linear and nonlinear aspects of effective connectivity, the direct Directed Transfer Function (dDTF) was utilized to extract the spectral information of connectivity patterns. RESULTS The dDTF results did not suggest a specific frequency band for distinguishing between the two groups, and different patterns of effective connectivity were observed in all bands. Both nCREANN and dDTF methods showed decreased connectivity between temporal/frontal and temporal/occipital regions, and increased connection between frontal/parietal regions in ADHDs than TDs. Furthermore, the nCREANN results showed more left-lateralized connections in ADHDs compared to the symmetric bilateral inter-hemispheric interactions in TDs. In addition, by fusion of linear and nonlinear connectivity measures of nCREANN method, we achieved an accuracy of 99% in classification of the two groups. CONCLUSION These findings emphasize the capability of nCREANN method to investigate the brain functioning of neural disorders and its strength in preciously distinguish between healthy and disordered subjects.
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Affiliation(s)
- Nasibeh Talebi
- Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.
| | - Ali Motie Nasrabadi
- Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.
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Chaudry S, Vasudevan N. mTOR-Dependent Spine Dynamics in Autism. Front Mol Neurosci 2022; 15:877609. [PMID: 35782388 PMCID: PMC9241970 DOI: 10.3389/fnmol.2022.877609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 04/25/2022] [Indexed: 12/12/2022] Open
Abstract
Autism Spectrum Conditions (ASC) are a group of neurodevelopmental disorders characterized by deficits in social communication and interaction as well as repetitive behaviors and restricted range of interests. ASC are complex genetic disorders with moderate to high heritability, and associated with atypical patterns of neural connectivity. Many of the genes implicated in ASC are involved in dendritic spine pruning and spine development, both of which can be mediated by the mammalian target of rapamycin (mTOR) signaling pathway. Consistent with this idea, human postmortem studies have shown increased spine density in ASC compared to controls suggesting that the balance between autophagy and spinogenesis is altered in ASC. However, murine models of ASC have shown inconsistent results for spine morphology, which may underlie functional connectivity. This review seeks to establish the relevance of changes in dendritic spines in ASC using data gathered from rodent models. Using a literature survey, we identify 20 genes that are linked to dendritic spine pruning or development in rodents that are also strongly implicated in ASC in humans. Furthermore, we show that all 20 genes are linked to the mTOR pathway and propose that the mTOR pathway regulating spine dynamics is a potential mechanism underlying the ASC signaling pathway in ASC. We show here that the direction of change in spine density was mostly correlated to the upstream positive or negative regulation of the mTOR pathway and most rodent models of mutant mTOR regulators show increases in immature spines, based on morphological analyses. We further explore the idea that these mutations in these genes result in aberrant social behavior in rodent models that is due to these altered spine dynamics. This review should therefore pave the way for further research on the specific genes outlined, their effect on spine morphology or density with an emphasis on understanding the functional role of these changes in ASC.
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Traut N, Heuer K, Lemaître G, Beggiato A, Germanaud D, Elmaleh M, Bethegnies A, Bonnasse-Gahot L, Cai W, Chambon S, Cliquet F, Ghriss A, Guigui N, de Pierrefeu A, Wang M, Zantedeschi V, Boucaud A, van den Bossche J, Kegl B, Delorme R, Bourgeron T, Toro R, Varoquaux G. Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery. Neuroimage 2022; 255:119171. [PMID: 35413445 DOI: 10.1016/j.neuroimage.2022.119171] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 02/16/2022] [Accepted: 03/30/2022] [Indexed: 12/23/2022] Open
Abstract
MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, undisclosed, analytic choices. We conducted an international challenge to predict ASD diagnosis from MRI data, where we provided preprocessed anatomical and functional MRI data from > 2,000 individuals. Evaluation of the predictions was rigorously blinded. 146 challengers submitted prediction algorithms, which were evaluated at the end of the challenge using unseen data and an additional acquisition site. On the best algorithms, we studied the importance of MRI modalities, brain regions, and sample size. We found evidence that MRI could predict ASD diagnosis: the 10 best algorithms reliably predicted diagnosis with AUC∼0.80 - far superior to what can be currently obtained using genotyping data in cohorts 20-times larger. We observed that functional MRI was more important for prediction than anatomical MRI, and that increasing sample size steadily increased prediction accuracy, providing an efficient strategy to improve biomarkers. We also observed that despite a strong incentive to generalise to unseen data, model development on a given dataset faces the risk of overfitting: performing well in cross-validation on the data at hand, but not generalising. Finally, we were able to predict ASD diagnosis on an external sample added after the end of the challenge (EU-AIMS), although with a lower prediction accuracy (AUC=0.72). This indicates that despite being based on a large multisite cohort, our challenge still produced biomarkers fragile in the face of dataset shifts.
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Affiliation(s)
- Nicolas Traut
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Katja Heuer
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Guillaume Lemaître
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | - Anita Beggiato
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Child and Adolescent Psychiatry Department, Robert Debré, APHP, Paris, France
| | | | | | | | | | - Weidong Cai
- Stanford University School of Medicine, Palo Alto, US
| | | | - Freddy Cliquet
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | | | | | | | - Meng Wang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Valentina Zantedeschi
- Univ Lyon, UJM-Saint-Etienne, CNRS, Institut d'Optique Graduate School, Laboratoire Hubert Curien UMR 5516, F-42023, Saint-Etienne, France
| | - Alexandre Boucaud
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | - Joris van den Bossche
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | | | - Richard Delorme
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Child and Adolescent Psychiatry Department, Robert Debré, APHP, Paris, France
| | - Thomas Bourgeron
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | - Roberto Toro
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | - Gaël Varoquaux
- Parietal, Inria, Saclay, France; Soda, Inria, Saclay, France.
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22
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Han YMY, Chan MC, Chan MMY, Yeung MK, Chan AS. Effects of working memory load on frontal connectivity in children with autism spectrum disorder: a fNIRS study. Sci Rep 2022; 12:1522. [PMID: 35087126 PMCID: PMC8795357 DOI: 10.1038/s41598-022-05432-3] [Citation(s) in RCA: 5] [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: 08/29/2021] [Accepted: 01/12/2022] [Indexed: 01/29/2023] Open
Abstract
Individuals with autism spectrum disorder (ASD) perform poorly in working memory (WM) tasks, with some literature suggesting that their impaired performance is modulated by WM load. While some neuroimaging and neurophysiological studies have reported altered functional connectivity during WM processing in individuals with autism, it remains largely unclear whether such alterations are moderated by WM load. The present study aimed to examine the effect of WM load on functional connectivity within the prefrontal cortex (PFC) in ASD using functional near-infrared spectroscopy (fNIRS). Twenty-two children with high-functioning ASD aged 8-12 years and 24 age-, intelligent quotient (IQ)-, sex- and handedness-matched typically developing (TD) children performed a number n-back task with three WM loads (0-back, 1-back, and 2-back). Hemodynamic changes in the bilateral lateral and medial PFC during task performance were monitored using a multichannel NIRS device. Children with ASD demonstrated slower reaction times, specifically during the "low load" condition, than TD children. In addition, the ASD and TD groups exhibited differential load-dependent functional connectivity changes in the lateral and medial PFC of the right but not the left hemisphere. These findings indicate that WM impairment in high-functioning ASD is paralleled by load-dependent alterations in right, but not left, intrahemispheric connectivity during WM processing in children with ASD. A disruption of functional neural connections that support different cognitive processes may underlie poor performance in WM tasks in ASD.
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Affiliation(s)
- Yvonne M Y Han
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, People's Republic of China.
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, People's Republic of China.
| | - Ming-Chung Chan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, People's Republic of China
| | - Melody M Y Chan
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, People's Republic of China
| | - Michael K Yeung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, People's Republic of China
- University Research Facility in Behavioral and Systems Neuroscience (UBSN), The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, People's Republic of China
| | - Agnes S Chan
- Department of Psychology, The Chinese University of Hong Kong, Kowloon, Hong Kong SAR, People's Republic of China
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23
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Multi-Region Local Field Potential Signatures in Response to the Formalin-induced Inflammatory Stimulus in Male Rats. Brain Res 2022; 1778:147779. [PMID: 35007546 DOI: 10.1016/j.brainres.2022.147779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 12/31/2021] [Accepted: 01/03/2022] [Indexed: 11/22/2022]
Abstract
Pain can be ignited by noxious chemical (e.g., acid), mechanical (e.g., pressure), and thermal (e.g., heat) stimuli and generated by the activation of sensory neurons and their axonal terminals called nociceptors in the periphery. Nociceptive information transmitted from the periphery is projected to the central nervous system (thalamus, somatosensory cortex, insular, anterior cingulate cortex, amygdala, periaqueductal grey, prefrontal cortex, etc.) to generate a unified experience of pain. Local field potential (LFP) recording is one of the neurophysiological tools to investigate the combined neuronal activity, ranging from several hundred micrometers to a few millimeters (radius), located around the embedded electrode. The advantage of recording LFP is that it provides stable simultaneous activities in various brain regions in response to external stimuli. In this study, differential LFP activities from the contralateral anterior cingulate cortex (ACC), ventral tegmental area (VTA), and bilateral amygdala in response to peripheral noxious formalin injection were recorded in anesthetized male rats. The results indicated increased power of delta, theta, alpha, beta, and gamma bands in the ACC and amygdala but no change of gamma-band in the right amygdala. Within the VTA, intensities of the delta, theta, and beta bands were only enhanced significantly after formalin injection. It was found that the connectivity (i.t. the coherence) among these brain regions reduced significantly under the formalin-induced nociception, which suggests a significant interruption within the brain. With further study, it will sort out the key combination of structures that will serve as the signature for pain state.
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24
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Hubbard RJ, Zadeh I, Jones AP, Robert B, Bryant NB, Clark VP, Pilly PK. Brain connectivity alterations during sleep by closed-loop transcranial neurostimulation predict metamemory sensitivity. Netw Neurosci 2021; 5:734-756. [PMID: 34746625 PMCID: PMC8567828 DOI: 10.1162/netn_a_00201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 05/15/2021] [Indexed: 12/23/2022] Open
Abstract
Metamemory involves the ability to correctly judge the accuracy of our memories. The retrieval of memories can be improved using transcranial electrical stimulation (tES) during sleep, but evidence for improvements to metamemory sensitivity is limited. Applying tES can enhance sleep-dependent memory consolidation, which along with metamemory requires the coordination of activity across distributed neural systems, suggesting that examining functional connectivity is important for understanding these processes. Nevertheless, little research has examined how functional connectivity modulations relate to overnight changes in metamemory sensitivity. Here, we developed a closed-loop short-duration tES method, time-locked to up-states of ongoing slow-wave oscillations, to cue specific memory replays in humans. We measured electroencephalographic (EEG) coherence changes following stimulation pulses, and characterized network alterations with graph theoretic metrics. Using machine learning techniques, we show that pulsed tES elicited network changes in multiple frequency bands, including increased connectivity in the theta band and increased efficiency in the spindle band. Additionally, stimulation-induced changes in beta-band path length were predictive of overnight changes in metamemory sensitivity. These findings add new insights into the growing literature investigating increases in memory performance through brain stimulation during sleep, and highlight the importance of examining functional connectivity to explain its effects. Numerous studies have demonstrated a clear link between sleep and memory—namely, memories are consolidated during sleep, leading to more stable and long-lasting representations. We have previously shown that tagging episodes with specific patterns of brain stimulation during encoding and replaying those patterns during sleep can enhance this consolidation process to improve confidence and decision-making of memories (metamemory). Here, we extend this work to examine network-level brain changes that occur following stimulation during sleep that predict metamemory improvements. Using graph theoretic and machine-learning methods, we found that stimulation-induced changes in beta-band path length predicted overnight improvements in metamemory. This novel finding sheds new light on the neural mechanisms of memory consolidation and suggests potential applications for improving metamemory.
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Affiliation(s)
- Ryan J Hubbard
- Center for Human-Machine Collaboration, Information and Systems Sciences Laboratory, HRL Laboratories, LLC, Malibu, CA, USA
| | - Iman Zadeh
- Center for Human-Machine Collaboration, Information and Systems Sciences Laboratory, HRL Laboratories, LLC, Malibu, CA, USA
| | - Aaron P Jones
- Psychology Clinical Neuroscience Center, Department of Psychology, The University of New Mexico, Albuquerque, NM, USA
| | - Bradley Robert
- Psychology Clinical Neuroscience Center, Department of Psychology, The University of New Mexico, Albuquerque, NM, USA
| | - Natalie B Bryant
- Psychology Clinical Neuroscience Center, Department of Psychology, The University of New Mexico, Albuquerque, NM, USA
| | - Vincent P Clark
- Psychology Clinical Neuroscience Center, Department of Psychology, The University of New Mexico, Albuquerque, NM, USA
| | - Praveen K Pilly
- Center for Human-Machine Collaboration, Information and Systems Sciences Laboratory, HRL Laboratories, LLC, Malibu, CA, USA
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25
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Estimating brain effective connectivity from EEG signals of patients with autism disorder and healthy individuals by reducing volume conduction effect. Cogn Neurodyn 2021; 16:519-529. [DOI: 10.1007/s11571-021-09730-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 09/26/2021] [Accepted: 10/02/2021] [Indexed: 10/19/2022] Open
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26
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Wakatsuki S, Araki T. Novel Molecular Basis for Synapse Formation: Small Non-coding Vault RNA Functions as a Riboregulator of MEK1 to Modulate Synaptogenesis. Front Mol Neurosci 2021; 14:748721. [PMID: 34630040 PMCID: PMC8498202 DOI: 10.3389/fnmol.2021.748721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Small non-coding vault RNAs (vtRNAs) have been described as a component of the vault complex, a hollow-and-barrel-shaped ribonucleoprotein complex found in most eukaryotes. It has been suggested that the function of vtRNAs might not be limited to simply maintaining the structure of the vault complex. Despite the increasing research on vtRNAs, little is known about their physiological functions. Recently, we have shown that murine vtRNA (mvtRNA) up-regulates synaptogenesis by activating the mitogen activated protein kinase (MAPK) signaling pathway. mvtRNA binds to and activates mitogen activated protein kinase 1 (MEK1), and thereby enhances MEK1-mediated extracellular signal-regulated kinase activation. Here, we introduce the regulatory mechanism of MAPK signaling in synaptogenesis by vtRNAs and discuss the possibility as a novel molecular basis for synapse formation.
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Affiliation(s)
- Shuji Wakatsuki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Toshiyuki Araki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
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27
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Wakatsuki S, Takahashi Y, Shibata M, Adachi N, Numakawa T, Kunugi H, Araki T. Small noncoding vault RNA modulates synapse formation by amplifying MAPK signaling. J Cell Biol 2021; 220:211679. [PMID: 33439240 PMCID: PMC7809882 DOI: 10.1083/jcb.201911078] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 09/04/2020] [Accepted: 12/02/2020] [Indexed: 12/30/2022] Open
Abstract
The small noncoding vault RNA (vtRNA) is a component of the vault complex, a ribonucleoprotein complex found in most eukaryotes. Emerging evidence suggests that vtRNAs may be involved in the regulation of a variety of cellular functions when unassociated with the vault complex. Here, we demonstrate a novel role for vtRNA in synaptogenesis. Using an in vitro synapse formation model, we show that murine vtRNA (mvtRNA) promotes synapse formation by modulating the MAPK signaling pathway. mvtRNA is transported to the distal region of neurites as part of the vault complex. Interestingly, mvtRNA is released from the vault complex in the neurite by a mitotic kinase Aurora-A–dependent phosphorylation of MVP, a major protein component of the vault complex. mvtRNA binds to and activates MEK1 and thereby enhances MEK1-mediated ERK activation in neurites. These results suggest the existence of a regulatory mechanism of the MAPK signaling pathway by vtRNAs as a new molecular basis for synapse formation.
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Affiliation(s)
- Shuji Wakatsuki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Yoko Takahashi
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Megumi Shibata
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Naoki Adachi
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan.,Department of Biomedical Chemistry, School of Science and Technology, Kwansei Gakuin University, Hyogo, Japan
| | - Tadahiro Numakawa
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan.,Department of Cell Modulation, Institute of Molecular Embryology and Genetics, Kumamoto University, Kumamoto, Japan
| | - Hiroshi Kunugi
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Toshiyuki Araki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
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28
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Chen YC, Chen C, Martínez RM, Fan YT, Liu CC, Chen CY, Cheng Y. An amygdala-centered hyper-connectivity signature of threatening face processing predicts anxiety in youths with autism spectrum conditions. Autism Res 2021; 14:2287-2299. [PMID: 34423915 DOI: 10.1002/aur.2595] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/17/2021] [Accepted: 08/06/2021] [Indexed: 11/06/2022]
Abstract
Anxiety is exceedingly prevalent among individuals with an autism spectrum condition (ASC). While recent literature postulates anxiety as a mechanism encompassing an underlying amygdala-related elevated baseline level of arousal even to nonthreatening cues, whether this same mechanism contributes to anxiety in those with an ASC and supports the transdiagnostic nature of anxiety remains elusive. In this case-control study of 51 youths (26 ASC), we assessed autism and anxiety via the Autism-Spectrum Quotient and the State-Trait Anxiety Inventory, respectively. Hemodynamic responses, including amygdala reactivity, to explicit and implicit (backwardly masked) perception of threatening faces were acquired using functional Magnetic Resonance Imaging (fMRI). For explicit fear, ASC individuals showed significantly greater negative correlations between the amygdala and the attentional deployment-parietal network. For implicit fear, ASC individuals showed significantly stronger correlations of the amygdala with the prefrontal networks, temporal pole, and hippocampus. Additionally, an fMRI-based neurologic signature for anxiety in ASCs was identified via the LibSVM machine learning model using amygdala-centered functional connectivity during the emotional processing of explicit and implicit stimuli. Hypervigilance to implicit threat in ASCs comorbid with anxiety might exacerbate explicit threat reactivity; hence the use of attentional avoidance patterns to restrict affective hyperarousal for explicitly perceived socioemotional stimuli. Consequently, developing an attention-independent behavioral/neural marker identifying anxiety in ASCs is highly warranted. LAY SUMMARY: This study identifies a dissociation of amygdala reactivity dependent on explicit and implicit threat processing. Implicit anxiety in individuals with an autism spectrum condition (ASC) could outweigh explicitly induced threat. When explicitly perceiving socioemotional stimuli, ASC individuals with anxiety might use attentional avoidance patterns to restrict affective hyperarousal.
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Affiliation(s)
- Yu-Chun Chen
- Department of Physical Medicine & Rehabilitation, National Yang Ming Chiao Tung University Hospital, Yilan, Taiwan.,Department of Physical Education, National Taiwan University of Sport, Taichung, Taiwan
| | - Chenyi Chen
- Graduate Institute of Injury Prevention and Control, College of Public Health, Taipei Medical University, Taipei, Taiwan.,Brain and Consciousness Research Center, Shuang-Ho Hospital, Taipei Medical University, New Taipei City, Taiwan.,Graduate Institute of Mind, Brain and Consciousness, College of Humanities and Social Sciences, Taipei Medical University, Taipei, Taiwan.,Psychiatric Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Róger Marcelo Martínez
- Graduate Institute of Injury Prevention and Control, College of Public Health, Taipei Medical University, Taipei, Taiwan.,School of Psychological Sciences, National Autonomous University of Honduras, Tegucigalpa, Honduras
| | - Yang-Tang Fan
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan, Taiwan
| | - Chia-Chien Liu
- Department of Psychiatry, Taichung Veterans General Hospital, Taichung, Taiwan.,Institute of Neuroscience and Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chin-Yau Chen
- Department of Surgery, National Yang Ming Chiao Tung University Hospital, Yilan, Taiwan
| | - Yawei Cheng
- Department of Physical Medicine & Rehabilitation, National Yang Ming Chiao Tung University Hospital, Yilan, Taiwan.,Institute of Neuroscience and Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Department of Education and Research, Taipei City Hospital, Taipei, Taiwan
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29
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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] [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 Transplantation, University of Milan, Via Festa del Perdono, 7, 20122 Milan, Italy
| | - Guido Nosari
- Department of Pathophysiology and Transplantation, University of Milan, Via Festa del Perdono, 7, 20122 Milan, Italy
| | - Riccardo Marin
- Department of Informatics, University of Verona, Verona, Italy
| | | | - Marcella Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Carolina Bonivento
- IRCCS "E. Medea", Polo Friuli Venezia Giulia, San Vito al Tagliamento (PN), Italy
| | - Franco Fabbro
- Department of Medicine, University of Udine, Udine, Italy
| | - Massimo Molteni
- IRCCS "E. Medea", Polo Friuli Venezia Giulia, San Vito al Tagliamento (PN), Italy
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Via Festa del Perdono, 7, 20122 Milan, Italy.,Department of Neurosciences and Mental Health Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via Francesco Sforza 28, 20122 Milan, Italy
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30
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Loomba N, Beckerson ME, Ammons CJ, Maximo JO, Kana RK. Corpus callosum size and homotopic connectivity in Autism spectrum disorder. Psychiatry Res Neuroimaging 2021; 313:111301. [PMID: 34022542 DOI: 10.1016/j.pscychresns.2021.111301] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Revised: 04/28/2021] [Accepted: 05/07/2021] [Indexed: 12/14/2022]
Abstract
By examining how morphology of the corpus callosum (CC) in autism spectrum disorder (ASD) may affect functional communication across hemispheres, we hope to provide new insights into the structure-function relationship in the brain. We used a sample of 94 participants from the Autism Brain Imaging Data Exchange (ABIDE) database (55 typically-developing (TD) and 39 with ASD). The CC was segmented into five sub-regions (anterior, mid-anterior, central, mid-posterior, posterior) using FreeSurfer software, which were further examined for group differences. The total volume and specific sub-region volumes of the CC, and interhemispheric (homotopic) functional connectivity were calculated, along with the relationship between volume and connectivity. These measures were correlated with social ability assessed by the Social Responsiveness Scale (SRS). The central sub-region of CC was significantly smaller in ASD, although there was no group difference in total CC volume. ASD participants also showed stronger homotopic connectivity in the superior frontal gyrus. SRS scores were negatively correlated with the CC central sub-region volumes in ASD. The findings of this study add to the body of research showing morphological differences in the CC in ASD as well as connectivity differences. The absence of a significant relationship between structure and homotopic functional connectivity aligns with previous findings.
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Affiliation(s)
- Niharika Loomba
- Interdisciplinary Graduate Program, Vanderbilt University, Nashville, TN, United States
| | - Meagan E Beckerson
- Department of Psychology, University of Alabama, Tuscaloosa, AL, United States; Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, AL, United States
| | - Carla J Ammons
- Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, United States
| | - Jose O Maximo
- Department of Psychiatry & Behavior Neurobiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Rajesh K Kana
- Department of Psychology, University of Alabama, Tuscaloosa, AL, United States; Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, AL, United States.
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31
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Barile B, Marzullo A, Stamile C, Durand-Dubief F, Sappey-Marinier D. Data augmentation using generative adversarial neural networks on brain structural connectivity in multiple sclerosis. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 206:106113. [PMID: 34004501 DOI: 10.1016/j.cmpb.2021.106113] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 04/07/2021] [Indexed: 05/23/2023]
Abstract
BACKGROUND AND OBJECTIVE Machine learning frameworks have demonstrated their potentials in dealing with complex data structures, achieving remarkable results in many areas, including brain imaging. However, a large collection of data is needed to train these models. This is particularly challenging in the biomedical domain since, due to acquisition accessibility, costs and pathology related variability, available datasets are limited and usually imbalanced. To overcome this challenge, generative models can be used to generate new data. METHODS In this study, a framework based on generative adversarial network is proposed to create synthetic structural brain networks in Multiple Sclerosis (MS). The dataset consists of 29 relapsing-remitting and 19 secondary-progressive MS patients. T1 and diffusion tensor imaging (DTI) acquisitions were used to obtain the structural brain network for each subject. Evaluation of the quality of newly generated brain networks is performed by (i) analysing their structural properties and (ii) studying their impact on classification performance. RESULTS We demonstrate that advanced generative models could be directly applied to the structural brain networks. We quantitatively and qualitatively show that newly generated data do not present significant differences compared to the real ones. In addition, augmenting the existing dataset with generated samples leads to an improvement of the classification performance (F1score 81%) with respect to the baseline approach (F1score 66%). CONCLUSIONS Our approach defines a new tool for biomedical application when connectome-based data augmentation is needed, providing a valid alternative to usual image-based data augmentation techniques.
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Affiliation(s)
- Berardino Barile
- CREATIS (UMR 5220 CNRS & U1206 INSERM), Université Claude Bernard Lyon 1, Université de Lyon, Villeurbanne, France.
| | - Aldo Marzullo
- Department of Mathematics and Computer Science, University of Calabria, Rende, Italy.
| | | | - Françoise Durand-Dubief
- CREATIS (UMR 5220 CNRS & U1206 INSERM), Université Claude Bernard Lyon 1, Université de Lyon, Villeurbanne, France; Hôpital Neurologique, Service de Neurologie A, Hôpital Civils de Lyon, Bron, France.
| | - Dominique Sappey-Marinier
- CREATIS (UMR 5220 CNRS & U1206 INSERM), Université Claude Bernard Lyon 1, Université de Lyon, Villeurbanne, France; CERMEP - Imagerie du Vivant, Université de Lyon, Bron, France.
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32
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Alotaibi N, Maharatna K. Classification of Autism Spectrum Disorder From EEG-Based Functional Brain Connectivity Analysis. Neural Comput 2021; 33:1914-1941. [PMID: 34411269 DOI: 10.1162/neco_a_01394] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 02/04/2021] [Indexed: 11/04/2022]
Abstract
Autism is a psychiatric condition that is typically diagnosed with behavioral assessment methods. Recent years have seen a rise in the number of children with autism. Since this could have serious health and socioeconomic consequences, it is imperative to investigate how to develop strategies for an early diagnosis that might pave the way to an adequate intervention. In this study, the phase-based functional brain connectivity derived from electroencephalogram (EEG) in a machine learning framework was used to classify the children with autism and typical children in an experimentally obtained data set of 12 autism spectrum disorder (ASD) and 12 typical children. Specifically, the functional brain connectivity networks have quantitatively been characterized by graph-theoretic parameters computed from three proposed approaches based on a standard phase-locking value, which were used as the features in a machine learning environment. Our study was successfully classified between two groups with approximately 95.8% accuracy, 100% sensitivity, and 92% specificity through the trial-averaged phase-locking value (PLV) approach and cubic support vector machine (SVM). This work has also shown that significant changes in functional brain connectivity in ASD children have been revealed at theta band using the aggregated graph-theoretic features. Therefore, the findings from this study offer insight into the potential use of functional brain connectivity as a tool for classifying ASD children.
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Affiliation(s)
- Noura Alotaibi
- Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
| | - Koushik Maharatna
- Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK
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33
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Cross-sectional investigation of insulin resistance in youths with autism spectrum disorder. Any role for reduced brain glucose metabolism? Transl Psychiatry 2021; 11:229. [PMID: 33879765 PMCID: PMC8058067 DOI: 10.1038/s41398-021-01345-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 03/18/2021] [Accepted: 03/29/2021] [Indexed: 12/14/2022] Open
Abstract
The autism spectrum disorder (ASD) is an etiologically heterogeneous disorder. Dysfunctions of the intermediate metabolism have been described in some patients. We speculate these metabolic abnormalities are associated with brain insulin resistance (IR), i.e., the reduced glucose metabolism at the level of the nervous central system. The Homeostasis model assessment of insulin resistance (HOMA-IR) is very often used in population studies as estimate of peripheral IR and it has been recently recognized as proxy of brain IR. We investigated HOMA-IR in 60 ASD patients aged 4-18 years and 240 healthy controls, also aged 4-18 years, but unmatched for age, sex, body weight, or body mass index (BMI). At multivariable linear regression model, the HOMA-IR was 0.31 unit higher in ASD individuals than in controls, after having adjusted for sex, age, BMI z-score category, and lipids that are factors known to influence HOMA-IR. Findings of this preliminary study suggest it is worth investigating brain glucose metabolism in larger population of patients with ASD by using gold standard technique. The recognition of a reduced glucose metabolism in some areas of the brain as marker of autism might have tremendous impact on our understanding of the pathogenic mechanisms of the disease and in terms of public health.
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34
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Li C, Li Y, Fu L, Wang Y, Cheng X, Cui X, Jiang J, Xiao T, Ke X, Fang H. The relationships between the topological properties of the whole-brain white matter network and the severity of autism spectrum disorder: A study from monozygotic twins. Neuroscience 2021; 465:60-70. [PMID: 33887385 DOI: 10.1016/j.neuroscience.2021.04.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
Twins provide a valuable perspective for exploring the pathological mechanism of autism spectrum disorder (ASD). We aim to analyze differences in the topological properties of the white matter (WM) network between monozygotic twins with ASD (MZCo-ASD) and children with typical development (TD). We enrolled 67 subjects aged 2-9 years. Twenty-three pairs of MZCo-ASD and 21 singleton children with TD completed clinical assessments and diffusion tensor imaging (DTI). Graph theory was used to compare the topological properties of the WM network between the two groups, and analyzed their correlations with the severity of clinical symptoms. We found that the global efficiency (Eg) of MZCo-ASD is weaker than that of TD children, while the shortest path length (Lp) of MZCo-ASD is longer than that of TD children, and MZCo-ASD have three unique hubs (the bilateral dorsolateral superior frontal gyrus and right insula). Eg and Lp were both correlated with the repetitive behavior scores of the Autism Diagnostic Interview-Revised (ADI-R) in the MZCo-ASD group, and the nodal efficiency of the dorsal superior frontal gyrus (SFGdor) was correlated with the ADI-R scores of repetitive behaviors. Left SFGdor nodal efficiency was correlated with Repetitive Behavior and Communication, two core symptoms of autism. The results implicated that MZCo-ASD had atypical brain structural network attributes and node distributions. Using MZCo-ASD, we found that the WM topological properties that correlate with the severity of ASD core symptoms were Eg, Lp, and the nodal efficiency of the SFGdor.
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Affiliation(s)
- Chunyan Li
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Yun Li
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Linyan Fu
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Yue Wang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xin Cheng
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xiwen Cui
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Jiying Jiang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Ting Xiao
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xiaoyan Ke
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China.
| | - Hui Fang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China.
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35
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Abstract
The small non-coding vault RNA (vtRNA) is a component of the vault complex, a ribonucleoprotein complex found in most eukaryotes. vtRNAs regulate a variety of cellular functions when unassociated with the vault complex. Human has four vtRNA paralogs (hvtRNA1-1, hvtRNA1-2, hvtRNA1-3, hvtRNA2-1), which are highly similar and differ only slightly in primary and secondary structure. Despite the increasing research on vtRNAs, a feature that distinguishes one hvtRNA from the others has not been recognized. Recently, we demonstrated that murine vtRNA (mvtRNA) promotes synapse formation by modulating the MAPK signaling pathway. Here we showed that expression ofhvtRNA1-1, but not hvtRNA2-1 increases the expression of synaptic marker proteins, ERK phosphorylation and the number of PSD95 and Synapsin I double positive puncta to an extent similar to that of mvtRNA, suggesting that hvtRNA1-1 may enhance synapse formation. This finding opens new perspectives to uncover the function of the different vtRNA paralogs.
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Affiliation(s)
- Shuji Wakatsuki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Moeka Ohno
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Toshiyuki Araki
- Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
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36
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Esposito CM, Buoli M, Ciappolino V, Agostoni C, Brambilla P. The Role of Cholesterol and Fatty Acids in the Etiology and Diagnosis of Autism Spectrum Disorders. Int J Mol Sci 2021; 22:ijms22073550. [PMID: 33805572 PMCID: PMC8036564 DOI: 10.3390/ijms22073550] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 03/17/2021] [Accepted: 03/25/2021] [Indexed: 02/07/2023] Open
Abstract
Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders whose pathogenesis seems to be related to an imbalance of excitatory and inhibitory synapses, which leads to disrupted connectivity during brain development. Among the various biomarkers that have been evaluated in the last years, metabolic factors represent a bridge between genetic vulnerability and environmental aspects. In particular, cholesterol homeostasis and circulating fatty acids seem to be involved in the pathogenesis of ASDs, both through the contribute in the stabilization of cell membranes and the modulation of inflammatory factors. The purpose of the present review is to summarize the available data about the role of cholesterol and fatty acids, mainly long-chain ones, in the onset of ASDs. A bibliographic research on the main databases was performed and 36 studies were included in our review. Most of the studies document a correlation between ASDs and hypocholesterolemia, while the results concerning circulating fatty acids are less univocal. Even though further studies are necessary to confirm the available data, the metabolic biomarkers open to new treatment options such as the modulation of the lipid pattern through the diet.
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Affiliation(s)
- Cecilia Maria Esposito
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; (C.M.E.); (M.B.); (V.C.); (P.B.)
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
| | - Massimiliano Buoli
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; (C.M.E.); (M.B.); (V.C.); (P.B.)
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
| | - Valentina Ciappolino
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; (C.M.E.); (M.B.); (V.C.); (P.B.)
| | - Carlo Agostoni
- Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy
- Pediatric Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
- Correspondence:
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122 Milan, Italy; (C.M.E.); (M.B.); (V.C.); (P.B.)
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy
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37
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Ayub R, Sun KL, Flores RE, Lam VT, Jo B, Saggar M, Fung LK. Thalamocortical connectivity is associated with autism symptoms in high-functioning adults with autism and typically developing adults. Transl Psychiatry 2021; 11:93. [PMID: 33536431 PMCID: PMC7859407 DOI: 10.1038/s41398-021-01221-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 01/07/2021] [Accepted: 01/15/2021] [Indexed: 01/30/2023] Open
Abstract
Alterations in sensorimotor functions are common in individuals with autism spectrum disorder (ASD). Such aberrations suggest the involvement of the thalamus due to its key role in modulating sensorimotor signaling in the cortex. Although previous research has linked atypical thalamocortical connectivity with ASD, investigations of this association in high-functioning adults with autism spectrum disorder (HFASD) are lacking. Here, for the first time, we investigated the resting-state functional connectivity of the thalamus, medial prefrontal, posterior cingulate, and left dorsolateral prefrontal cortices and its association with symptom severity in two matched cohorts of HFASD. The principal cohort consisted of 23 HFASD (mean[SD] 27.1[8.9] years, 39.1% female) and 20 age- and sex-matched typically developing controls (25.1[7.2] years, 30.0% female). The secondary cohort was a subset of the ABIDE database consisting of 58 HFASD (25.4[7.8] years, 37.9% female) and 51 typically developing controls (24.4[6.7] years, 39.2% female). Using seed-based connectivity analysis, between-group differences were revealed as hyperconnectivity in HFASD in the principal cohort between the right thalamus and bilateral precentral/postcentral gyri and between the right thalamus and the right superior parietal lobule. The former was associated with autism-spectrum quotient in a sex-specific manner, and was further validated in the secondary ABIDE cohort. Altogether, we present converging evidence for thalamocortical hyperconnectivity in HFASD that is associated with symptom severity. Our results fill an important knowledge gap regarding atypical thalamocortical connectivity in HFASD, previously only reported in younger cohorts.
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Affiliation(s)
- Rafi Ayub
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Kevin L Sun
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- School of Medicine, Stanford University, Stanford, CA, USA
| | - Ryan E Flores
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Vicky T Lam
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Booil Jo
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Manish Saggar
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Lawrence K Fung
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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38
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Ranti D, Valliani AAA, Costa A, Oermann EK. Artificial intelligence as applied to clinical neurological conditions. Artif Intell Med 2021. [DOI: 10.1016/b978-0-12-821259-2.00020-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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39
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Agastinose Ronicko JF, Thomas J, Thangavel P, Koneru V, Langs G, Dauwels J. Diagnostic classification of autism using resting-state fMRI data improves with full correlation functional brain connectivity compared to partial correlation. J Neurosci Methods 2020; 345:108884. [PMID: 32730918 DOI: 10.1016/j.jneumeth.2020.108884] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/23/2020] [Accepted: 07/24/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Autism Spectrum Disorder (ASD) is a neurodevelopmental disability with altered connectivity in brain networks. NEW METHOD In this study, brain connections in Resting-state functional Magnetic Resonance Imaging (Rs-fMRI) of ASD and Typical Developing (TD) are analyzed by partial and full correlation methods such as Gaussian Graphical Least Absolute Shrinkage and Selection Operator (GLASSO), Max-Det Matrix Completion (MDMC), and Pearson Correlation Co-Efficient (PCCE). We investigated Functional Connectivity (FC) of ASD and TD brain from 238 functionally defined regions of interest. Furthermore, we constructed a series of feature sets by applying conditional random forests and conditional permutation importance. We built classifier models by Random Forest (RF), Oblique RF (ORF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) for each feature set. FC features are ranked based on p-value and we analyzed the top 20 FC features. RESULTS We achieved a single-trial test accuracy of 72.5 %, though MDMC-SVM and PCCE-CNN pipelines. Further, PCCE-CNN pipeline gives better average test accuracy (70.31 %) and area under the curve (0.73) compared to other pipelines. We found that top-20 PCCE based FC features are from networks such as Dorsal Attention (DA), Cingulo-Opercular Task Control (COTC), somatosensory motor hand and subcortical. In addition, among top 20 PCCE features, many FC links are found between COTC and DA (4 connections) which helped to discriminate the ASD and TD. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS The generalized classifier models built in our study for highly heterogeneous participants perform better than previous studies with similar data sets and diagnostic groups.
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Affiliation(s)
- Jac Fredo Agastinose Ronicko
- School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore.
| | - John Thomas
- School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore.
| | - Prasanth Thangavel
- School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore.
| | - Vineetha Koneru
- School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore.
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090, Vienna, Austria.
| | - Justin Dauwels
- School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639 798, Singapore.
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40
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Fertan E, Wong AA, Purdon MK, Weaver ICG, Brown RE. The effect of background strain on the behavioral phenotypes of the MDGA2 +/- mouse model of autism spectrum disorder. GENES BRAIN AND BEHAVIOR 2020; 20:e12696. [PMID: 32808443 DOI: 10.1111/gbb.12696] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/27/2020] [Accepted: 08/14/2020] [Indexed: 12/26/2022]
Abstract
The membrane-associated mucin (MAM) domain containing glycosylphosphatidylinositol anchor 2 protein single knock-out mice (MDGA2+/- ) are models of ASD. We examined the behavioral phenotypes of male and female MDGA2+/- and wildtype mice on C57BL6/NJ and C57BL6/N backgrounds at 2 months of age and measured MDGA2, neuroligin 1 and neuroligin 2 levels at 7 months. Mice on the C57BL6/NJ background performed better than those on the C57BL6/N background in visual ability and in learning and memory performance in the Morris water maze and differed in measures of motor behavior and anxiety. Mice with the MDGA2+/- genotype differed from WT mice in motor, social and repetitive behavior and anxiety, but most of these effects involved interactions between MDGA2+/- genotype and background strain. The background strain also influenced MDGA2 levels and NLGN2 association in MDGA2+/- mice. Our findings emphasize the importance of the background strain used in studies of genetically modified mice.
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Affiliation(s)
- Emre Fertan
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Aimée A Wong
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Michaela K Purdon
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Ian C G Weaver
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada.,Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.,Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada.,Brain Repair Centre, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Richard E Brown
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada.,Brain Repair Centre, Dalhousie University, Halifax, Nova Scotia, Canada
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41
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Trujillo Villarreal LA, Cárdenas-Tueme M, Maldonado-Ruiz R, Reséndez-Pérez D, Camacho-Morales A. Potential role of primed microglia during obesity on the mesocorticolimbic circuit in autism spectrum disorder. J Neurochem 2020; 156:415-434. [PMID: 32902852 DOI: 10.1111/jnc.15141] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 07/12/2020] [Accepted: 07/27/2020] [Indexed: 12/19/2022]
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disease which involves functional and structural defects in selective central nervous system (CNS) regions that harm function and individual ability to process and respond to external stimuli. Individuals with ASD spend less time engaging in social interaction compared to non-affected subjects. Studies employing structural and functional magnetic resonance imaging reported morphological and functional abnormalities in the connectivity of the mesocorticolimbic reward pathway between the nucleus accumbens and the ventral tegmental area (VTA) in response to social stimuli, as well as diminished medial prefrontal cortex in response to visual cues, whereas stronger reward system responses for the non-social realm (e.g., video games) than social rewards (e.g., approval), associated with caudate nucleus responsiveness in ASD children. Defects in the mesocorticolimbic reward pathway have been modulated in transgenic murine models using D2 dopamine receptor heterozygous (D2+/-) or dopamine transporter knockout mice, which exhibit sociability deficits and repetitive behaviors observed in ASD phenotypes. Notably, the mesocorticolimbic reward pathway is modulated by systemic and central inflammation, such as primed microglia, which occurs during obesity or maternal overnutrition. Therefore, we propose that a positive energy balance during obesity/maternal overnutrition coordinates a systemic and central inflammatory crosstalk that modulates the dopaminergic neurotransmission in selective brain areas of the mesocorticolimbic reward pathway. Here, we will describe how obesity/maternal overnutrition may prime microglia, causing abnormalities in dopamine neurotransmission of the mesocorticolimbic reward pathway, postulating a possible immune role in the development of ASD.
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Affiliation(s)
- Luis A- Trujillo Villarreal
- Departamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México.,Unidad de Neurometabolismo, Centro de Investigación y Desarrollo en Ciencias de la Salud, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Marcela Cárdenas-Tueme
- Departamento de Biología Celular y Genética, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Roger Maldonado-Ruiz
- Departamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México.,Unidad de Neurometabolismo, Centro de Investigación y Desarrollo en Ciencias de la Salud, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Diana Reséndez-Pérez
- Departamento de Biología Celular y Genética, Facultad de Ciencias Biológicas, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
| | - Alberto Camacho-Morales
- Departamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México.,Unidad de Neurometabolismo, Centro de Investigación y Desarrollo en Ciencias de la Salud, Universidad Autónoma de Nuevo León, San Nicolas de los Garza, México
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42
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Ghahari S, Salehi F, Farahani N, Coben R, Motie Nasrabadi A. Representing Temporal Network based on dDTF of EEG signals in Children with Autism and Healthy Children. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.102139] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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43
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Samanta D. An Updated Review of Tuberous Sclerosis Complex-Associated Autism Spectrum Disorder. Pediatr Neurol 2020; 109:4-11. [PMID: 32563542 DOI: 10.1016/j.pediatrneurol.2020.03.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/01/2020] [Accepted: 03/03/2020] [Indexed: 01/30/2023]
Abstract
Tuberous sclerosis complex (TSC) is a neurocutaneous disorder caused by mutations of either the TSC1 or TSC2 gene. Various neuropsychiatric features, including autism, are prevalent in TSC. Recently, significant progress has been possible with the prospective calculation of the prevalence of autism in TSC, identification of early clinical and neurophysiological biomarkers to predict autism, and investigation of different therapies to prevent autism in this high-risk population. The author provides a narrative review of recent findings related to biomarkers for diagnosis of autism in TSC, as well as recent studies related to the management of TSC-associated autism. Further sophisticated modeling and analysis are required to understand the role of different models-tuber models, seizures and related neurophysiological factors models, genotype models, and brain connectivity models-to unravel the neurobiological basis of autism in TSC. Early neuropsychologic assessments may be beneficial in this high-risk group. Targeted intervention to improve visual skill, cognition, and fine motor skills with later addition of social skill training can be helpful. Multicenter, prospective studies are ongoing to identify if presymptomatic treatment with vigabatrin in patients with TSC can improve outcomes, including autism. Several studies indicated reasonable safety of everolimus in young children, and its potential application in high-risk infants with TSC, before the closure of the temporal window of permanent changes, maybe undertaken shortly.
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Affiliation(s)
- Debopam Samanta
- Child Neurology Section, Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
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44
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Morphofunctional Alterations of the Hypothalamus and Social Behavior in Autism Spectrum Disorders. Brain Sci 2020; 10:brainsci10070435. [PMID: 32650534 PMCID: PMC7408098 DOI: 10.3390/brainsci10070435] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 06/21/2020] [Accepted: 07/03/2020] [Indexed: 12/15/2022] Open
Abstract
An accumulating body of evidence indicates a tight relationship between the endocrine system and abnormal social behavior. Two evolutionarily conserved hypothalamic peptides, oxytocin and arginine-vasopressin, because of their extensively documented function in supporting and regulating affiliative and socio-emotional responses, have attracted great interest for their critical implications for autism spectrum disorders (ASD). A large number of controlled trials demonstrated that exogenous oxytocin or arginine-vasopressin administration can mitigate social behavior impairment in ASD. Furthermore, there exists long-standing evidence of severe socioemotional dysfunctions after hypothalamic lesions in animals and humans. However, despite the major role of the hypothalamus for the synthesis and release of oxytocin and vasopressin, and the evident hypothalamic implication in affiliative behavior in animals and humans, a rather small number of neuroimaging studies showed an association between this region and socioemotional responses in ASD. This review aims to provide a critical synthesis of evidences linking alterations of the hypothalamus with impaired social cognition and behavior in ASD by integrating results of both anatomical and functional studies in individuals with ASD as well as in healthy carriers of oxytocin receptor (OXTR) genetic risk variant for ASD. Current findings, although limited, indicate that morphofunctional anomalies are implicated in the pathophysiology of ASD and call for further investigations aiming to elucidate anatomical and functional properties of hypothalamic nuclei underlying atypical socioemotional behavior in ASD.
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45
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Nunes AS, Vakorin VA, Kozhemiako N, Peatfield N, Ribary U, Doesburg SM. Atypical age-related changes in cortical thickness in autism spectrum disorder. Sci Rep 2020; 10:11067. [PMID: 32632150 PMCID: PMC7338512 DOI: 10.1038/s41598-020-67507-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 06/08/2020] [Indexed: 01/17/2023] Open
Abstract
Recent longitudinal neuroimaging and neurophysiological studies have shown that tracking relative age-related changes in neural signals, rather than a static snapshot of a neural measure, could offer higher sensitivity for discriminating typically developing (TD) individuals from those with autism spectrum disorder (ASD). It is not clear, however, which aspects of age-related changes (trajectories) would be optimal for identifying atypical brain development in ASD. Using a large cross-sectional data set (Autism Brain Imaging Data Exchange [ABIDE] repository; releases I and II), we aimed to explore age-related changes in cortical thickness (CT) in TD and ASD populations (age range 6–30 years old). Cortical thickness was estimated from T1-weighted MRI images at three scales of spatial coarseness (three parcellations with different numbers of regions of interest). For each parcellation, three polynomial models of age-related changes in CT were tested. Specifically, to characterize alterations in CT trajectories, we compared the linear slope, curvature, and aberrancy of CT trajectories across experimental groups, which was estimated using linear, quadratic, and cubic polynomial models, respectively. Also, we explored associations between age-related changes with ASD symptomatology quantified as the Autism Diagnostic Observation Schedule (ADOS) scores. While no overall group differences in cortical thickness were observed across the entire age range, ASD and TD populations were different in terms of age-related changes, which were located primarily in frontal and tempo-parietal areas. These atypical age-related changes were also associated with ADOS scores in the ASD group and used to predict ASD from TD development. These results indicate that the curvature is the most reliable feature for localizing brain areas developmentally atypical in ASD with a more pronounced effect with symptomatology and is the most sensitive in predicting ASD development.
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Affiliation(s)
- Adonay S Nunes
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada.
| | - Vasily A Vakorin
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada.,Behavioral & Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, Canada
| | - Nataliia Kozhemiako
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada
| | - Nicholas Peatfield
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada
| | - Urs Ribary
- Behavioral & Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, Canada.,Department Pediatrics and Psychiatry, University of British Columbia, Vancouver, Canada.,B.C. Children's Hospital Research Institute, Vancouver, Canada.,Department Psychology, Simon Fraser University, Burnaby, Canada
| | - Sam M Doesburg
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, 8888 University Dr, Burnaby, BC, V5A 1S6, Canada.,Behavioral & Cognitive Neuroscience Institute, Simon Fraser University, Burnaby, Canada
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Abstract
Since the initial psychological report by Leo Kanner in 1943, relatively little formal biochemical/neurological research on the cause of autism, other than peripheral searches for genomic mutations, had been carried until the end of the 20th century. As a result of studies on twin sets and the conclusion that autism was largely a hereditary defect, numerous investigations have sought various genetic faults in particular. However, such studies were able to reveal a plausible etiology for this malady in only a small percentage of instances. Key bio-molecular characteristics of this syndrome have been uncovered when the potential roles of the glia were studied in depth. Findings related to biochemical deficiencies appearing early in the newborn, such as depressed IGF-1 (insulin-like growth factor #1) in neurogenesis/myelination, are becoming emphasized in many laboratories. Progress leading to timely diagnoses and subsequent prevention of central nervous system dysconnectivity now seems plausible. The tendency for an infant to develop autism may currently be determinable and preventable before irreversible psychosocial disturbances become established. These discussions about glial function will be inter-spersed with comments about their apparent relevance to autism. The concluding portion of this presentation will be a detailed review and summation of this diagnosis and prevention proposition.
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Affiliation(s)
- Gary Steinman
- Visiting Researcher, Department of Obstetrics & Gynecology, Hadassah Hospital-Hebrew University, Ein Kerem, Jerusalem, Israel.
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47
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Comparing different EEG connectivity methods in young males with ASD. Behav Brain Res 2020; 383:112482. [PMID: 31972185 DOI: 10.1016/j.bbr.2020.112482] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 12/24/2019] [Accepted: 01/13/2020] [Indexed: 12/27/2022]
Abstract
Although EEG connectivity data are often used to build models of the association between overt behavioural signs of Autism Spectrum Disorder (ASD) and underlying brain connectivity indices, use of a large number of possible connectivity methods across studies has produced a fairly inconsistent set of results regarding this association. To explore the level of agreement between results from five commonly-used EEG connectivity models (i.e., Coherence, Weighted Phased Lag Index- Debiased, Phase Locking Value, Phase Slope Index, Granger Causality), a sample of 41 young males with ASD provided EEG data under eyes-opened and eyes-closed conditions. There were relatively few statistically significant and/or meaningful correlations between the results obtained from the five connectivity methods, arguing for a re-estimation of the methodology used in such studies so that specific connectivity methods may be matched to particular research questions regarding the links between neural connectivity and overt behaviour within this population.
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48
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Sarmukadam K, Sharpley CF, Bitsika V, McMillan MME, Agnew LL. A review of the use of EEG connectivity to measure the neurological characteristics of the sensory features in young people with autism. Rev Neurosci 2020; 30:497-510. [PMID: 30269108 DOI: 10.1515/revneuro-2018-0070] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 08/03/2018] [Indexed: 11/15/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition affecting about 1 in 100 children and is currently incurable. ASD represents a challenge to traditional methods of assessment and diagnosis, and it has been suggested that direct measures of brain activity and connectivity between brain regions during demanding tasks represents a potential pathway to building more accurate models of underlying brain function and ASD. One of the key behavioural diagnostic indicators of ASD consists of sensory features (SF), often characterised by over- or under-reactivity to environmental stimuli. SF are associated with behavioural difficulties that impede social and education success in these children as well as anxiety and depression. This review examines the previous literature on the measurement of EEG connectivity and SF observed in individuals with ASD.
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Affiliation(s)
- Kimaya Sarmukadam
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
| | - Christopher F Sharpley
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
| | - Vicki Bitsika
- Centre for Autism Spectrum Disorder, Bond University, Gold Coast 4229, Queensland, Australia
| | - Mary M E McMillan
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
| | - Linda L Agnew
- Brain-Behaviour Research Group, University of New England, Armidale 2350, New South Wales, Australia
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Egorova O, Myte R, Schneede J, Hägglöf B, Bölte S, Domellöf E, Ivars A'roch B, Elgh F, Ueland PM, Silfverdal SA. Maternal blood folate status during early pregnancy and occurrence of autism spectrum disorder in offspring: a study of 62 serum biomarkers. Mol Autism 2020; 11:7. [PMID: 32131900 PMCID: PMC6964211 DOI: 10.1186/s13229-020-0315-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 01/02/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) evolves from an interplay between genetic and environmental factors during prenatal development. Since identifying maternal biomarkers associated with ASD risk in offspring during early pregnancy might result in new strategies for intervention, we investigated maternal metabolic biomarkers in relation to occurrence of ASD in offspring using both univariate logistic regression and multivariate network analysis. METHODS Serum samples from 100 women with an offspring diagnosed with ASD and 100 matched control women with typically developing offspring were collected at week 14 of pregnancy. Concentrations of 62 metabolic biomarkers were determined, including amino acids, vitamins (A, B, D, E, and K), and biomarkers related to folate (vitamin B9) metabolism, lifestyle factors, as well as C-reactive protein (CRP), the kynurenine-tryptophan ratio (KTR), and neopterin as markers of inflammation and immune activation. RESULTS We found weak evidence for a positive association between higher maternal serum concentrations of folate and increased occurrence of ASD (OR per 1 SD increase: 1.70, 95% CI 1.22-2.37, FDR adjusted P = 0.07). Multivariate network analysis confirmed expected internal biochemical relations between the biomarkers. Neither inflammation markers nor vitamin D3 levels, all hypothesized to be involved in ASD etiology, displayed associations with ASD occurrence in the offspring. CONCLUSIONS Our findings suggest that high maternal serum folate status during early pregnancy may be associated with the occurrence of ASD in offspring. No inference about physiological mechanisms behind this observation can be made at the present time because blood folate levels may have complex relations with nutritional intake, the cellular folate status and status of other B-vitamins. Therefore, further investigations, which may clarify the potential role and mechanisms of maternal blood folate status in ASD risk and the interplay with other potential risk factors, in larger materials are warranted.
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Affiliation(s)
- Olga Egorova
- Department of Clinical Sciences, Pediatrics, Umeå University, Umeå, Sweden.
| | - Robin Myte
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Jörn Schneede
- Department of Clinical Pharmacology, Pharmacology and Clinical Neurosciences, Umeå University, Umeå, Sweden
| | - Bruno Hägglöf
- Department of Child and Adolescent Psychiatry, Umea University, Umeå, Sweden
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Stockholm, Sweden.,Department of Women's and Children's Health, Karolinska Institutet & Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, WA, Australia
| | - Erik Domellöf
- Department of Psychology, Umeå University, Umeå, Sweden
| | - Barbro Ivars A'roch
- Department of Child and Adolescent Psychiatry, Umea University, Umeå, Sweden
| | - Fredrik Elgh
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Per Magne Ueland
- Bevital AS, Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Medical Biochemistry and Pharmacology, Haukeland University Hospital, Bergen, Norway
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50
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Rasheed W, Tang TB. Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM. IEEE Trans Neural Syst Rehabil Eng 2020; 28:83-93. [DOI: 10.1109/tnsre.2019.2948798] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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