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Guo B, Liu T, Choi S, Mao H, Wang W, Xi K, Jones C, Hartley ND, Feng D, Chen Q, Liu Y, Wimmer RD, Xie Y, Zhao N, Ou J, Arias-Garcia MA, Malhotra D, Liu Y, Lee S, Pasqualoni S, Kast RJ, Fleishman M, Halassa MM, Wu S, Fu Z. Restoring thalamocortical circuit dysfunction by correcting HCN channelopathy in Shank3 mutant mice. Cell Rep Med 2024; 5:101534. [PMID: 38670100 PMCID: PMC11149412 DOI: 10.1016/j.xcrm.2024.101534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 12/11/2023] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
Thalamocortical (TC) circuits are essential for sensory information processing. Clinical and preclinical studies of autism spectrum disorders (ASDs) have highlighted abnormal thalamic development and TC circuit dysfunction. However, mechanistic understanding of how TC dysfunction contributes to behavioral abnormalities in ASDs is limited. Here, our study on a Shank3 mouse model of ASD reveals TC neuron hyperexcitability with excessive burst firing and a temporal mismatch relationship with slow cortical rhythms during sleep. These TC electrophysiological alterations and the consequent sensory hypersensitivity and sleep fragmentation in Shank3 mutant mice are causally linked to HCN2 channelopathy. Restoring HCN2 function early in postnatal development via a viral approach or lamotrigine (LTG) ameliorates sensory and sleep problems. A retrospective case series also supports beneficial effects of LTG treatment on sensory behavior in ASD patients. Our study identifies a clinically relevant circuit mechanism and proposes a targeted molecular intervention for ASD-related behavioral impairments.
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Affiliation(s)
- Baolin Guo
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tiaotiao Liu
- School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China
| | - Soonwook Choi
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Honghui Mao
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Wenting Wang
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Kaiwen Xi
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Carter Jones
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nolan D Hartley
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Dayun Feng
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Qian Chen
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Yingying Liu
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Ralf D Wimmer
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Yuqiao Xie
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Ningxia Zhao
- Xi'an TCM Hospital of Encephalopathy, Shaanxi University of Chinese Medicine, Xi'an 710032, China
| | - Jianjun Ou
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, National Clinical Research Center for Mental Disorders, Changsha 410011, China
| | - Mario A Arias-Garcia
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Diya Malhotra
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yang Liu
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China
| | - Sihak Lee
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sammuel Pasqualoni
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ryan J Kast
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Morgan Fleishman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michael M Halassa
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Shengxi Wu
- Department of Neurobiology, School of Basic Medicine, Fourth Military Medical University, Xi'an 710032, China.
| | - Zhanyan Fu
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA.
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2
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Nagai Y, Kirino E, Tanaka S, Usui C, Inami R, Inoue R, Hattori A, Uchida W, Kamagata K, Aoki S. Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI. Cereb Cortex 2024; 34:129-145. [PMID: 38012112 PMCID: PMC11065111 DOI: 10.1093/cercor/bhad451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.
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Affiliation(s)
- Yasuhito Nagai
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, 1129 Nagaoka Izunokuni-shi Shizuoka 410-2295, Japan
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Shoji Tanaka
- Department of Information and Communication Sciences, Sophia University, 7-1 Kioi-cho Chiyoda-ku Tokyo 102-8554, Japan
| | - Chie Usui
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Rie Inami
- Department of Psychiatry, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Reiichi Inoue
- Juntendo Institute of Mental Health, 700-1 Fukuroyama Koshigaya-shi Saitama 343-0032, Japan
| | - Aki Hattori
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo Bunkyo-ku Tokyo 113-8421, Japan
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode Urayasu-shi Chiba 279-0013, Japan
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Li X, Zhao H, Wang M, Li L, Wang X, Ma Z, Du H, Li R. Thalamic segmentation based on diffusion tensor imaging in patients with trigeminal neuralgia. Brain Res 2024; 1830:148832. [PMID: 38412884 DOI: 10.1016/j.brainres.2024.148832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 11/29/2023] [Accepted: 02/24/2024] [Indexed: 02/29/2024]
Abstract
Classical trigeminal neuralgia (CTN) refers to episodic pain that is strictly confined to the trigeminal distribution area, and the thalamus is an important component of the trigeminal sensory pathway. Probabilistic tracking imaging algorithm was used to identify specific connections between the thalamus and the cortex, in order to identify structural changes in the thalamus of patients with CTN and perform thalamic segmentation. A total of 32 patients with CTN and 32 healthy controls underwent DTI-MRI scanning (3.0 T). Differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) between the groups were studied. Correlation analysis was performed with clinical course and pain level. Compared to the healthy controls, patients in the CTN group had significantly reduced FA, increased AD, RD and MD in somatosensory subregion of the bilateral thalamus, increased RD in frontal subregion, increased RD and MD in motor subregion. Correlation analysis showed that patient history was positively correlated with pain grading, and that medical history was positively correlated with significantly reduced FA in somatosensory subregion, negatively correlated with increased RD and MD in motor subregion. We used DTI-based probabilistic fiber tracking to discover altered structural connectivity between the thalamus and cerebral cortex in patients with CTN and to obtain a thalamic segmentation atlas, which will help to further understand the pathophysiology of CTN and serve as a future reference for thalamic deep brain stimulation electrode implantation for the treatment of intractable pain.
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Affiliation(s)
- Xinyi Li
- Department of Radiological Image, Jining Medical University, Jining 272011, China
| | - Hang Zhao
- Department of Radiology, Jining No. 1 People's Hospital, Jining 272011, China
| | - Min Wang
- Department of Radiology, Jining No. 1 People's Hospital, Jining 272011, China
| | - Li Li
- Department of Radiological Image, Jining Medical University, Jining 272011, China
| | - Xiulin Wang
- Stem Cell Clinical Research Center, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China
| | - Zitang Ma
- Department of Radiology, Jining No. 1 People's Hospital, Jining 272011, China
| | - Hai Du
- Department of Radiology, Ordos Central Hospital, Ordos 017000, China.
| | - Rui Li
- Department of Radiology, Jining No. 1 People's Hospital, Jining 272011, China.
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4
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Huang AS, Kang K, Vandekar S, Rogers BP, Heckers S, Woodward ND. Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling. Neuropsychopharmacology 2024:10.1038/s41386-024-01837-y. [PMID: 38480909 DOI: 10.1038/s41386-024-01837-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 02/13/2024] [Accepted: 02/21/2024] [Indexed: 03/18/2024]
Abstract
Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.
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Affiliation(s)
- Anna S Huang
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Kaidi Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Baxter P Rogers
- Vanderbilt University Institute of Imaging Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Stephan Heckers
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Neil D Woodward
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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5
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Shin D, Kim CN, Ross J, Hennick KM, Wu SR, Paranjape N, Leonard R, Wang JC, Keefe MG, Pavlovic BJ, Donohue KC, Moreau C, Wigdor EM, Larson HH, Allen DE, Cadwell CR, Bhaduri A, Popova G, Bearden CE, Pollen AA, Jacquemont S, Sanders SJ, Haussler D, Wiita AP, Frost NA, Sohal VS, Nowakowski TJ. Thalamocortical organoids enable in vitro modeling of 22q11.2 microdeletion associated with neuropsychiatric disorders. Cell Stem Cell 2024; 31:421-432.e8. [PMID: 38382530 PMCID: PMC10939828 DOI: 10.1016/j.stem.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 12/14/2023] [Accepted: 01/25/2024] [Indexed: 02/23/2024]
Abstract
Thalamic dysfunction has been implicated in multiple psychiatric disorders. We sought to study the mechanisms by which abnormalities emerge in the context of the 22q11.2 microdeletion, which confers significant genetic risk for psychiatric disorders. We investigated early stages of human thalamus development using human pluripotent stem cell-derived organoids and show that the 22q11.2 microdeletion underlies widespread transcriptional dysregulation associated with psychiatric disorders in thalamic neurons and glia, including elevated expression of FOXP2. Using an organoid co-culture model, we demonstrate that the 22q11.2 microdeletion mediates an overgrowth of thalamic axons in a FOXP2-dependent manner. Finally, we identify ROBO2 as a candidate molecular mediator of the effects of FOXP2 overexpression on thalamic axon overgrowth. Together, our study suggests that early steps in thalamic development are dysregulated in a model of genetic risk for schizophrenia and contribute to neural phenotypes in 22q11.2 deletion syndrome.
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Affiliation(s)
- David Shin
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Chang N Kim
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jayden Ross
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kelsey M Hennick
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Sih-Rong Wu
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Neha Paranjape
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94107, USA
| | - Rachel Leonard
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jerrick C Wang
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Matthew G Keefe
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Bryan J Pavlovic
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Kevin C Donohue
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Clara Moreau
- Sainte Justine Research Center, University of Montréal, 3175 Chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 1C5, Canada; Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Emilie M Wigdor
- Institute of Developmental and Regenerative Medicine, University of Oxford, Headington, Oxford OX3 7TY, UK
| | - H Hanh Larson
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Denise E Allen
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Cathryn R Cadwell
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pathology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Aparna Bhaduri
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Galina Popova
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Carrie E Bearden
- Integrative Center for Neurogenetics, Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, University of California, Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Alex A Pollen
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Sebastien Jacquemont
- Sainte Justine Research Center, University of Montréal, 3175 Chemin de la Côte-Sainte-Catherine, Montréal, QC H3T 1C5, Canada
| | - Stephan J Sanders
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Institute of Developmental and Regenerative Medicine, University of Oxford, Headington, Oxford OX3 7TY, UK
| | - David Haussler
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95060, USA; Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA; Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Arun P Wiita
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94107, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158
| | - Nicholas A Frost
- Department of Neurology, University of Utah, Salt Lake City, UT 84108, USA
| | - Vikaas S Sohal
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Tomasz J Nowakowski
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94158, USA; Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94158, USA.
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6
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Leyva-Díaz E, Wilson ES, López-Bendito G. Development has the answer: Unraveling psychiatric disorders via thalamocortical organoids. Cell Stem Cell 2024; 31:283-284. [PMID: 38458174 DOI: 10.1016/j.stem.2024.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 03/10/2024]
Abstract
Dissecting the role of the thalamus in neuropsychiatric disorders requires new models to analyze complex genetic interactions. In this issue of Cell Stem Cell, Shin et al. use patient-derived thalamocortical organoids to investigate 22q11.2 microdeletion impact on thalamic development, revealing significant transcriptional dysregulation linked to psychiatric disorders.
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Affiliation(s)
- Eduardo Leyva-Díaz
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), San Juan de Alicante, Alicante, Spain
| | - Emily S Wilson
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), San Juan de Alicante, Alicante, Spain
| | - Guillermina López-Bendito
- Instituto de Neurociencias de Alicante, Universidad Miguel Hernández-Consejo Superior de Investigaciones Científicas (UMH-CSIC), San Juan de Alicante, Alicante, Spain.
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7
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Presto P, Sehar U, Kopel J, Reddy PH. Mechanisms of pain in aging and age-related conditions: Focus on caregivers. Ageing Res Rev 2024; 95:102249. [PMID: 38417712 DOI: 10.1016/j.arr.2024.102249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 02/13/2024] [Accepted: 02/22/2024] [Indexed: 03/01/2024]
Abstract
Pain is a complex, subjective experience that can significantly impact quality of life, particularly in aging individuals, by adversely affecting physical and emotional well-being. Whereas acute pain usually serves a protective function, chronic pain is a persistent pathological condition that contributes to functional deficits, cognitive decline, and emotional disturbances in the elderly. Despite substantial progress that has been made in characterizing age-related changes in pain, complete mechanistic details of pain processing mechanisms in the aging patient remain unknown. Pain is particularly under-recognized and under-managed in the elderly, especially among patients with Alzheimer's disease (AD), Alzheimer's disease-related dementias (ADRD), and other age-related conditions. Furthermore, difficulties in assessing pain in patients with AD/ADRD and other age-related conditions may contribute to the familial caregiver burden. The purpose of this article is to discuss the mechanisms and risk factors for chronic pain development and persistence, with a particular focus on age-related changes. Our article also highlights the importance of caregivers working with aging chronic pain patients, and emphasizes the urgent need for increased legislative awareness and improved pain management in these populations to substantially alleviate caregiver burden.
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Affiliation(s)
- Peyton Presto
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Ujala Sehar
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - Jonathan Kopel
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA
| | - P Hemachandra Reddy
- Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Nutritional Sciences Department, College of Human Sciences, Texas Tech University, Lubbock, TX 79409, USA; Department of Speech, Language and Hearing Sciences, School Health Professions, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Public Health, School of Population and Public Health, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Neurology, Departments of School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX 79430, USA; Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
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8
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Yoo S, Jang Y, Hong SJ, Park H, Valk SL, Bernhardt BC, Park BY. Whole-brain structural connectome asymmetry in autism. Neuroimage 2024; 288:120534. [PMID: 38340881 DOI: 10.1016/j.neuroimage.2024.120534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/28/2024] [Accepted: 02/07/2024] [Indexed: 02/12/2024] Open
Abstract
Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.
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Affiliation(s)
- Seulki Yoo
- Convergence Research Institute, Sungkyunkwan University, Suwon, Republic of Korea
| | - Yurim Jang
- Artificial Intelligence Convergence Research Center, Inha University, Incheon, Republic of Korea
| | - Seok-Jun Hong
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Hyunjin Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Sofie L Valk
- Forschungszentrum Julich, Germany; Max Planck Institute for Cognitive and Brain Sciences, Leipzig, Germany; Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Data Science, Inha University, Incheon, Republic of Korea; Department of Statistics and Data Science, Inha University, Incheon, Republic of Korea.
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9
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Song Y, Hupfeld KE, Davies-Jenkins CW, Zöllner HJ, Murali-Manohar S, Mumuni AN, Crocetti D, Yedavalli V, Oeltzschner G, Alessi N, Batschelett MA, Puts NA, Mostofsky SH, Edden RA. Brain glutathione and GABA+ levels in autistic children. Autism Res 2024; 17:512-528. [PMID: 38279628 PMCID: PMC10963146 DOI: 10.1002/aur.3097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/28/2023] [Indexed: 01/28/2024]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.
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Affiliation(s)
- Yulu Song
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kathleen E. Hupfeld
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Christopher W. Davies-Jenkins
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Helge J. Zöllner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Saipavitra Murali-Manohar
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Deana Crocetti
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Vivek Yedavalli
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Georg Oeltzschner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Natalie Alessi
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Mitchell A. Batschelett
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Nicolaas A.J. Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
- MRC Center for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Stewart H. Mostofsky
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Richard A.E. Edden
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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10
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Zhan L, Gao Y, Huang L, Zhang H, Huang G, Wang Y, Sun J, Xie Z, Li M, Jia X, Cheng L, Yu Y. Brain functional connectivity alterations of Wernicke's area in individuals with autism spectrum conditions in multi-frequency bands: A mega-analysis. Heliyon 2024; 10:e26198. [PMID: 38404781 PMCID: PMC10884452 DOI: 10.1016/j.heliyon.2024.e26198] [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: 08/06/2023] [Revised: 02/05/2024] [Accepted: 02/08/2024] [Indexed: 02/27/2024] Open
Abstract
Characterized by severe deficits in communication, most individuals with autism spectrum conditions (ASC) experience significant language dysfunctions, thereby impacting their overall quality of life. Wernicke's area, a classical and traditional brain region associated with language processing, plays a substantial role in the manifestation of language impairments. The current study carried out a mega-analysis to attain a comprehensive understanding of the neural mechanisms underpinning ASC, particularly in the context of language processing. The study employed the Autism Brain Image Data Exchange (ABIDE) dataset, which encompasses data from 443 typically developing (TD) individuals and 362 individuals with ASC. The objective was to detect abnormal functional connectivity (FC) between Wernicke's area and other language-related functional regions, and identify frequency-specific altered FC using Wernicke's area as the seed region in ASC. The findings revealed that increased FC in individuals with ASC has frequency-specific characteristics. Further, in the conventional frequency band (0.01-0.08 Hz), individuals with ASC exhibited increased FC between Wernicke's area and the right thalamus compared with TD individuals. In the slow-5 frequency band (0.01-0.027 Hz), increased FC values were observed in the left cerebellum Crus II and the right lenticular nucleus, pallidum. These results provide novel insights into the potential neural mechanisms underlying communication deficits in ASC from the perspective of language impairments.
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Affiliation(s)
- Linlin Zhan
- School of Western Studies, Heilongjiang University, Harbin, China
| | - Yanyan Gao
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Lina Huang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Hongqiang Zhang
- Department of Radiology, Changshu No. 2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Guofeng Huang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yadan Wang
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Zhou Xie
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Mengting Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Lulu Cheng
- School of Foreign Studies, China University of Petroleum (East China), Qingdao, China
- Shanghai Center for Research in English Language Education, Shanghai International Studies University, Shanghai, China
| | - Yang Yu
- Psychiatry Department, The Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang, Hangzhou, China
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11
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Ding N, Fu L, Qian L, Sun B, Li C, Gao H, Lei T, Ke X. The correlation between brain structure characteristics and emotion regulation ability in children at high risk of autism spectrum disorder. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02369-y. [PMID: 38402375 DOI: 10.1007/s00787-024-02369-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 01/08/2024] [Indexed: 02/26/2024]
Abstract
As indicated by longitudinal observation, autism has difficulty controlling emotions to a certain extent in early childhood, and most children's emotional and behavioral problems are further aggravated with the growth of age. This study aimed at exploring the correlation between white matter and white matter fiber bundle connectivity characteristics and their emotional regulation ability in children with autism using machine learning methods, which can lay an empirical basis for early clinical intervention of autism. Fifty-five high risk of autism spectrum disorder (HR-ASD) children and 52 typical development (TD) children were selected to complete the skull 3D-T1 structure and diffusion tensor imaging (DTI). The emotional regulation ability of the two groups was compared using the still-face paradigm (SFP). The classification and regression models of white matter characteristics and white matter fiber bundle connections of emotion regulation ability in the HR-ASD group were built based on the machine learning method. The volume of the right amygdala (R2 = 0.245) and the volume of the right hippocampus (R2 = 0.197) affected constructive emotion regulation strategies. FA (R2 = 0.32) and MD (R2 = 0.34) had the predictive effect on self-stimulating behaviour. White matter fiber bundle connection predicted constructive regulation strategies (positive edging R2 = 0.333, negative edging R2 = 0.334) and mother-seeking behaviors (positive edging R2 = 0.667, negative edging R2 = 0.363). The emotional regulation ability of HR-ASD children is significantly correlated with the connections of multiple white matter fiber bundles, which is a potential neuro-biomarker of emotional regulation ability.
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Affiliation(s)
- Ning Ding
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
- Qingdao Women and Children' s Hospital, Qingdao University, Qingdao, 266011, China
| | - Linyan Fu
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Lu Qian
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Bei Sun
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Chunyan Li
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Huiyun Gao
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Tianyu Lei
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Xiaoyan Ke
- Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China.
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12
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Jang Y, Choi H, Yoo S, Park H, Park BY. Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:2. [PMID: 38267953 PMCID: PMC10807082 DOI: 10.1186/s12993-024-00228-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 01/10/2024] [Indexed: 01/26/2024]
Abstract
Autism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.
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Affiliation(s)
- Yurim Jang
- Artificial Intelligence Convergence Research Center, Inha University, Incheon, Republic of Korea
| | - Hyoungshin Choi
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Seulki Yoo
- Convergence Research Institute, Sungkyunkwan University, Suwon, Republic of Korea
| | - Hyunjin Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- School of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
- Department of Data Science, Inha University, Incheon, Republic of Korea.
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13
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Talvio K, Castrén ML. Astrocytes in fragile X syndrome. Front Cell Neurosci 2024; 17:1322541. [PMID: 38259499 PMCID: PMC10800791 DOI: 10.3389/fncel.2023.1322541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/11/2023] [Indexed: 01/24/2024] Open
Abstract
Astrocytes have an important role in neuronal maturation and synapse function in the brain. The interplay between astrocytes and neurons is found to be altered in many neurodevelopmental disorders, including fragile X syndrome (FXS) that is the most common inherited cause of intellectual disability and autism spectrum disorder. Transcriptional, functional, and metabolic alterations in Fmr1 knockout mouse astrocytes, human FXS stem cell-derived astrocytes as well as in in vivo models suggest autonomous effects of astrocytes in the neurobiology of FXS. Abnormalities associated with FXS astrocytes include differentiation of central nervous system cell populations, maturation and regulation of synapses, and synaptic glutamate balance. Recently, FXS-specific changes were found more widely in astrocyte functioning, such as regulation of inflammatory pathways and maintenance of lipid homeostasis. Changes of FXS astrocytes impact the brain homeostasis and function both during development and in the adult brain and offer opportunities for novel types of approaches for intervention.
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Affiliation(s)
| | - Maija L. Castrén
- Department of Physiology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
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14
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Zarate-Lopez D, Torres-Chávez AL, Gálvez-Contreras AY, Gonzalez-Perez O. Three Decades of Valproate: A Current Model for Studying Autism Spectrum Disorder. Curr Neuropharmacol 2024; 22:260-289. [PMID: 37873949 PMCID: PMC10788883 DOI: 10.2174/1570159x22666231003121513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 08/30/2023] [Accepted: 08/30/2023] [Indexed: 10/25/2023] Open
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increased prevalence and incidence in recent decades. Its etiology remains largely unclear, but it seems to involve a strong genetic component and environmental factors that, in turn, induce epigenetic changes during embryonic and postnatal brain development. In recent decades, clinical studies have shown that inutero exposure to valproic acid (VPA), a commonly prescribed antiepileptic drug, is an environmental factor associated with an increased risk of ASD. Subsequently, prenatal VPA exposure in rodents has been established as a reliable translational model to study the pathophysiology of ASD, which has helped demonstrate neurobiological changes in rodents, non-human primates, and brain organoids from human pluripotent stem cells. This evidence supports the notion that prenatal VPA exposure is a valid and current model to replicate an idiopathic ASD-like disorder in experimental animals. This review summarizes and describes the current features reported with this animal model of autism and the main neurobiological findings and correlates that help elucidate the pathophysiology of ASD. Finally, we discuss the general framework of the VPA model in comparison to other environmental and genetic ASD models.
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Affiliation(s)
- David Zarate-Lopez
- Laboratory of Neuroscience, School of Psychology, University of Colima, Colima 28040, México
- Physiological Science Ph.D. Program, School of Medicine, University of Colima, Colima 28040, Mexico
| | - Ana Laura Torres-Chávez
- Laboratory of Neuroscience, School of Psychology, University of Colima, Colima 28040, México
- Physiological Science Ph.D. Program, School of Medicine, University of Colima, Colima 28040, Mexico
| | - Alma Yadira Gálvez-Contreras
- Department of Neuroscience, Centro Universitario de Ciencias de la Salud, University of Guadalajara, Guadalajara 44340, México
| | - Oscar Gonzalez-Perez
- Laboratory of Neuroscience, School of Psychology, University of Colima, Colima 28040, México
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15
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Persichetti AS, Shao J, Gotts SJ, Martin A. A functional parcellation of the whole brain in individuals with autism spectrum disorder reveals atypical patterns of network organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.15.571854. [PMID: 38168156 PMCID: PMC10760210 DOI: 10.1101/2023.12.15.571854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
BACKGROUND Researchers studying autism spectrum disorder (ASD) lack a comprehensive map of the functional network topography in the ASD brain. We used high-quality resting state functional MRI (rs-fMRI) connectivity data and a robust parcellation routine to provide a whole-brain map of functional networks in a group of seventy individuals with ASD and a group of seventy typically developing (TD) individuals. METHODS The rs-fMRI data were collected using an imaging sequence optimized to achieve high temporal signal-to-noise ratio (tSNR) across the whole-brain. We identified functional networks using a parcellation routine that intrinsically incorporates stability and replicability of the networks by keeping only network distinctions that agree across halves of the data over multiple random iterations in each group. The groups were tightly matched on tSNR, in-scanner motion, age, and IQ. RESULTS We compared the maps from each group and found that functional networks in the ASD group are atypical in three seemingly related ways: 1) whole-brain connectivity patterns are less stable across voxels within multiple functional networks, 2) the cerebellum, subcortex, and hippocampus show weaker differentiation of functional subnetworks, and 3) subcortical structures and the hippocampus are atypically integrated with the neocortex. CONCLUSIONS These results were statistically robust and suggest that patterns of network connectivity between the neocortex and the cerebellum, subcortical structures, and hippocampus are atypical in ASD individuals.
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Affiliation(s)
- Andrew S Persichetti
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Jiayu Shao
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Stephen J Gotts
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
| | - Alex Martin
- Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892
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16
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Karavallil Achuthan S, Stavrinos D, Argueta P, Vanderburgh C, Holm HB, Kana RK. Thalamic functional connectivity and sensorimotor processing in neurodevelopmental disorders. Front Neurosci 2023; 17:1279909. [PMID: 38161799 PMCID: PMC10755010 DOI: 10.3389/fnins.2023.1279909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 11/08/2023] [Indexed: 01/03/2024] Open
Abstract
One of the earliest neurobiological findings in autism has been the differences in the thalamocortical pathway connectivity, suggesting the vital role thalamus plays in human experience. The present functional MRI study investigated resting-state functional connectivity of the thalamus in 49 (autistic, ADHD, and neurotypical) young adults. All participants underwent structural MRI and eyes-open resting state functional MRI scans. After preprocessing the imaging data using Conn's connectivity toolbox, a seed-based functional connectivity analysis was conducted using bilateral thalamus as primary seeds. Autistic participants showed stronger thalamic connectivity, relative to ADHD and neurotypical participants, between the right thalamus and right precentral gyrus, right pars opercularis-BA44, right postcentral gyrus, and the right superior parietal lobule (RSPL). Autistic participants also showed significantly increased connectivity between the left thalamus and the right precentral gyrus. Furthermore, regression analyses revealed a significant relationship between autistic traits and left thalamic-precentral connectivity (R2 = 0.1113), as well as between autistic traits and right postcentral gyrus and RSPL connectivity (R2 = 0.1204) in autistic participants compared to ADHD. These findings provide significant insights into the role of thalamus in coordinating neural information processing and its alterations in neurodevelopmental disorders.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Despina Stavrinos
- Department of Psychology and the Institute of Social Science Research, The University of Alabama, Tuscaloosa, AL, United States
| | - Paula Argueta
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Caroline Vanderburgh
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
| | - Haley B. Holm
- Children’s Hospital of Atlanta, Atlanta, GA, United States
| | - Rajesh K. Kana
- Department of Psychology and the Center for Innovative Research in Autism, The University of Alabama, Tuscaloosa, AL, United States
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17
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Kiral FR, Choe M, Park IH. Diencephalic organoids - A key to unraveling development, connectivity, and pathology of the human diencephalon. Front Cell Neurosci 2023; 17:1308479. [PMID: 38130869 PMCID: PMC10733522 DOI: 10.3389/fncel.2023.1308479] [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: 10/06/2023] [Accepted: 11/20/2023] [Indexed: 12/23/2023] Open
Abstract
The diencephalon, an integral component of the forebrain, governs a spectrum of crucial functions, ranging from sensory processing to emotional regulation. Yet, unraveling its unique development, intricate connectivity, and its role in neurodevelopmental disorders has long been hampered by the scarcity of human brain tissue and ethical constraints. Recent advancements in stem cell technology, particularly the emergence of brain organoids, have heralded a new era in neuroscience research. Although most brain organoid methodologies have hitherto concentrated on directing stem cells toward telencephalic fates, novel techniques now permit the generation of region-specific brain organoids that faithfully replicate precise diencephalic identities. These models mirror the complexity of the human diencephalon, providing unprecedented opportunities for investigating diencephalic development, functionality, connectivity, and pathophysiology in vitro. This review summarizes the development, function, and connectivity of diencephalic structures and touches upon developmental brain disorders linked to diencephalic abnormalities. Furthermore, it presents current diencephalic organoid models and their applications in unraveling the intricacies of diencephalic development, function, and pathology in humans. Lastly, it highlights thalamocortical assembloid models, adept at capturing human-specific aspects of thalamocortical connections, along with their relevance in neurodevelopmental disorders.
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Affiliation(s)
| | | | - In-Hyun Park
- Interdepartmental Neuroscience Program, Department of Genetics, Yale Stem Cell Center, Yale Child Study Center, Wu Tsai Institute, Yale School of Medicine, New Haven, CT, United States
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18
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Kim CN, Shin D, Wang A, Nowakowski TJ. Spatiotemporal molecular dynamics of the developing human thalamus. Science 2023; 382:eadf9941. [PMID: 37824646 PMCID: PMC10758299 DOI: 10.1126/science.adf9941] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 09/15/2023] [Indexed: 10/14/2023]
Abstract
The thalamus plays a central coordinating role in the brain. Thalamic neurons are organized into spatially distinct nuclei, but the molecular architecture of thalamic development is poorly understood, especially in humans. To begin to delineate the molecular trajectories of cell fate specification and organization in the developing human thalamus, we used single-cell and multiplexed spatial transcriptomics. We show that molecularly defined thalamic neurons differentiate in the second trimester of human development and that these neurons organize into spatially and molecularly distinct nuclei. We identified major subtypes of glutamatergic neuron subtypes that are differentially enriched in anatomically distinct nuclei and six subtypes of γ-aminobutyric acid-mediated (GABAergic) neurons that are shared and distinct across thalamic nuclei.
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Affiliation(s)
- Chang N Kim
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - David Shin
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Albert Wang
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA 94143, USA
- Department of Anatomy, University of California, San Francisco, CA 94143, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
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19
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Schwartz S, Wang L, Uribe S, Shinn-Cunningham B, Tager-Flusberg H. Auditory evoked potentials in adolescents with autism: An investigation of brain development, intellectual impairment, and neural encoding. Autism Res 2023; 16:1859-1876. [PMID: 37735966 PMCID: PMC10676753 DOI: 10.1002/aur.3003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 07/21/2023] [Indexed: 09/23/2023]
Abstract
Limited research has evaluated neural encoding of sounds from a developmental perspective in individuals with autism (ASD), especially among those with intellectual disability. We compared auditory evoked potentials (AEPs) in autistic adolescents with a wide range of intellectual abilities (n = 40, NVIQ 30-160) to both age-matched cognitively able neurotypical adolescent controls (NT-A, n = 37) and younger neurotypical children (NT-C, n = 27) to assess potential developmental delays. In addition to a classic measure of peak amplitude, we calculated a continuous measure of intra-class correlation (ICC) between each adolescent participant's AEP and the age-normative, average AEP waveforms calculated from NT-C and NT-A to study differences in signal morphology. We found that peak amplitudes of neural responses were significantly smaller in autistic adolescents compared to NT-A. We also found that the AEP morphology of autistic adolescents looked more like NT-A peers than NT-C but was still significantly different from NT-A AEP waveforms. Results suggest that AEPs of autistic adolescents present differently from NTs, regardless of age, and differences cannot be accounted for by developmental delay. Nonverbal intelligence significantly predicted how closely each adolescent's AEP resembled the age-normed waveform. These results support an evolving theory that the degree of disruption in early neural responses to low-level inputs is reflected in the severity of intellectual impairments in autism.
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Affiliation(s)
- Sophie Schwartz
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Le Wang
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Sofia Uribe
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Department of Psychology, Southern Methodist University, Dallas, TX, USA
| | | | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
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20
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Song Y, Hupfeld KE, Davies-Jenkins CW, Zöllner HJ, Murali-Manohar S, Mumuni AN, Crocetti D, Yedavalli V, Oeltzschner G, Alessi N, Batschelett MA, Puts NAJ, Mostofsky SH, Edden RAE. Brain Glutathione and GABA+ levels in autistic children. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.28.559718. [PMID: 37808813 PMCID: PMC10557661 DOI: 10.1101/2023.09.28.559718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a large cohort of children aged 8-12 years with ASD (n=52) and typically developing children (TDC, n=49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.
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Affiliation(s)
- Yulu Song
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kathleen E Hupfeld
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Christopher W Davies-Jenkins
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Helge J Zöllner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Saipavitra Murali-Manohar
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | | | - Deana Crocetti
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Vivek Yedavalli
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Georg Oeltzschner
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Natalie Alessi
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Mitchell A Batschelett
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom
- MRC Center for Neurodevelopmental Disorders, King's College London, London, United Kingdom
| | - Stewart H Mostofsky
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Richard A E Edden
- The Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
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21
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MacDonald DN, Bedford SA, Olafson E, Park MTM, Devenyi GA, Tullo S, Patel R, Anagnostou E, Baron-Cohen S, Bullmore ET, Chura LR, Craig MC, Ecker C, Floris DL, Holt RJ, Lenroot R, Lerch JP, Lombardo MV, Murphy DGM, Raznahan A, Ruigrok ANV, Smith E, Shinohara RT, Spencer MD, Suckling J, Taylor MJ, Thurm A, Lai MC, Chakravarty MM. Characterizing Subcortical Structural Heterogeneity in Autism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.28.554882. [PMID: 37693556 PMCID: PMC10491091 DOI: 10.1101/2023.08.28.554882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Autism presents with significant phenotypic and neuroanatomical heterogeneity, and neuroimaging studies of the thalamus, globus pallidus and striatum in autism have produced inconsistent and contradictory results. These structures are critical mediators of functions known to be atypical in autism, including sensory gating and motor function. We examined both volumetric and fine-grained localized shape differences in autism using a large (n=3145, 1045-1318 after strict quality control), cross-sectional dataset of T1-weighted structural MRI scans from 32 sites, including both males and females (assigned-at-birth). We investigated three potentially important sources of neuroanatomical heterogeneity: sex, age, and intelligence quotient (IQ), using a meta-analytic technique after strict quality control to minimize non-biological sources of variation. We observed no volumetric differences in the thalamus, globus pallidus, or striatum in autism. Rather, we identified a variety of localized shape differences in all three structures. Including age, but not sex or IQ, in the statistical model improved the fit for both the pallidum and striatum, but not for the thalamus. Age-centered shape analysis indicated a variety of age-dependent regional differences. Overall, our findings help confirm that the neurodevelopment of the striatum, globus pallidus and thalamus are atypical in autism, in a subtle location-dependent manner that is not reflected in overall structure volumes, and that is highly non-uniform across the lifespan.
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Affiliation(s)
- David N. MacDonald
- Integrated Program in Neuroscience, McGill University
- Cerebral Imaging Centre, Douglas Mental Health University Institute
| | - Saashi A. Bedford
- Integrated Program in Neuroscience, McGill University
- Cerebral Imaging Centre, Douglas Mental Health University Institute
- Autism Research Centre, Department of Psychiatry, University of Cambridge
| | - Emily Olafson
- Cerebral Imaging Centre, Douglas Mental Health University Institute
- Department of Neuroscience, Weill Cornell Graduate School of Medical Sciences
| | - Min Tae M. Park
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto
| | - Gabriel A. Devenyi
- Cerebral Imaging Centre, Douglas Mental Health University Institute
- Department of Psychiatry, McGill University
| | - Stephanie Tullo
- Integrated Program in Neuroscience, McGill University
- Cerebral Imaging Centre, Douglas Mental Health University Institute
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health University Institute
- Department of Biological and Biomedical Engineering, McGill University
| | | | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge
| | | | - Lindsay R. Chura
- Autism Research Centre, Department of Psychiatry, University of Cambridge
| | - Michael C. Craig
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London
- National Autism Unit, Bethlem Royal Hospital, London, UK
| | - Christine Ecker
- Institute of Psychiatry, Psychology and Neuroscience, King’s College London
- Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, GoetheUniversity
| | - Dorothea L. Floris
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich,Switzerland
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands
| | - Rosemary J. Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge
| | - Rhoshel Lenroot
- Dept.of Psychiatry and Behavioral Sciences, University of New Mexico
| | - Jason P. Lerch
- Program in Neurosciences and Mental Health, The Hospital for Sick Children
- Department of Medical Biophysics, University of Toronto
- Wellcome Centre for Integrative Neuroimaging, University of Oxford
| | - Michael V. Lombardo
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia
| | | | - Armin Raznahan
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of MentalHealth
| | - Amber N. V. Ruigrok
- Autism Research Centre, Department of Psychiatry, University of Cambridge
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester
| | - Elizabeth Smith
- Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children’s Hospital
| | - Russell T. Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Michael D. Spencer
- Autism Research Centre, Department of Psychiatry, University of Cambridge
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge
| | - Margot J. Taylor
- Program in Neurosciences and Mental Health, The Hospital for Sick Children
- Diagnostic Imaging, The Hospital for Sick Children
| | - Audrey Thurm
- Section on Behavioral Pediatrics, National Institute of Mental Health
| | | | - Meng-Chuan Lai
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto
- Autism Research Centre, Department of Psychiatry, University of Cambridge
- Program in Neurosciences and Mental Health, The Hospital for Sick Children
- The Margaret and Wallace McCain Centre for Child, Youth & Family Mental Health and Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine
| | - M. Mallar Chakravarty
- Integrated Program in Neuroscience, McGill University
- Cerebral Imaging Centre, Douglas Mental Health University Institute
- Department of Psychiatry, McGill University
- Department of Biological and Biomedical Engineering, McGill University
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22
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Badke D’Andrea C, Marek S, Van AN, Miller RL, Earl EA, Stewart SB, Dosenbach NUF, Schlaggar BL, Laumann TO, Fair DA, Gordon EM, Greene DJ. Thalamo-cortical and cerebello-cortical functional connectivity in development. Cereb Cortex 2023; 33:9250-9262. [PMID: 37293735 PMCID: PMC10492576 DOI: 10.1093/cercor/bhad198] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 05/09/2023] [Accepted: 05/17/2023] [Indexed: 06/10/2023] Open
Abstract
The thalamus is a critical relay center for neural pathways involving sensory, motor, and cognitive functions, including cortico-striato-thalamo-cortical and cortico-ponto-cerebello-thalamo-cortical loops. Despite the importance of these circuits, their development has been understudied. One way to investigate these pathways in human development in vivo is with functional connectivity MRI, yet few studies have examined thalamo-cortical and cerebello-cortical functional connectivity in development. Here, we used resting-state functional connectivity to measure functional connectivity in the thalamus and cerebellum with previously defined cortical functional networks in 2 separate data sets of children (7-12 years old) and adults (19-40 years old). In both data sets, we found stronger functional connectivity between the ventral thalamus and the somatomotor face cortical functional network in children compared with adults, extending previous cortico-striatal functional connectivity findings. In addition, there was more cortical network integration (i.e. strongest functional connectivity with multiple networks) in the thalamus in children than in adults. We found no developmental differences in cerebello-cortical functional connectivity. Together, these results suggest different maturation patterns in cortico-striato-thalamo-cortical and cortico-ponto-cerebellar-thalamo-cortical pathways.
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Affiliation(s)
- Carolina Badke D’Andrea
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Scott Marek
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Ryland L Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Eric A Earl
- Data Science and Sharing Team, National Institute of Mental Health, NIH, DHHS, Bethesda, MD 20899, United States
| | - Stephanie B Stewart
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, CO 80045, United States
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
| | | | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Damien A Fair
- Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455, United States
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, United States
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55455, United States
| | - Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, United States
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23
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Correa S, Nichols ES, Mueller ME, de Vrijer B, Eagleson R, McKenzie CA, de Ribaupierre S, Duerden EG. Default mode network functional connectivity strength in utero and the association with fetal subcortical development. Cereb Cortex 2023; 33:9144-9153. [PMID: 37259175 PMCID: PMC10350815 DOI: 10.1093/cercor/bhad190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/02/2023] Open
Abstract
The default mode network is essential for higher-order cognitive processes and is composed of an extensive network of functional and structural connections. Early in fetal life, the default mode network shows strong connectivity with other functional networks; however, the association with structural development is not well understood. In this study, resting-state functional magnetic resonance imaging and anatomical images were acquired in 30 pregnant women with singleton pregnancies. Participants completed 1 or 2 MR imaging sessions, on average 3 weeks apart (43 data sets), between 28- and 39-weeks postconceptional ages. Subcortical volumes were automatically segmented. Activation time courses from resting-state functional magnetic resonance imaging were extracted from the default mode network, medial temporal lobe network, and thalamocortical network. Generalized estimating equations were used to examine the association between functional connectivity strength between default mode network-medial temporal lobe, default mode network-thalamocortical network, and subcortical volumes, respectively. Increased functional connectivity strength in the default mode network-medial temporal lobe network was associated with smaller right hippocampal, left thalamic, and right caudate nucleus volumes, but larger volumes of the left caudate. Increased functional connectivity strength in the default mode network-thalamocortical network was associated with smaller left thalamic volumes. The strong associations seen among the default mode network functional connectivity networks and regionally specific subcortical volume development indicate the emergence of short-range connectivity in the third trimester.
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Affiliation(s)
- Susana Correa
- Neuroscience Program, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
| | - Emily S Nichols
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
| | - Megan E Mueller
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
| | - Barbra de Vrijer
- Obstetrics & Gynaecology, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Roy Eagleson
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Biomedical Engineering, Western University, London, ON N6A 3K7, Canada
- Electrical and Computer Engineering, Western University, London, ON N6A 3K7, Canada
| | - Charles A McKenzie
- Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Sandrine de Ribaupierre
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Biomedical Engineering, Western University, London, ON N6A 3K7, Canada
- Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Clinical Neurological Sciences, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
- Anatomy and Cell Biology, Schulich School of Medicine & Dentistry, Western University, London, ON N6A 3K7, Canada
| | - Emma G Duerden
- Western Institute for Neuroscience, Western University, London, ON N6A 3K7, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON N6A 3K7, Canada
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24
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Wagner L, Banchik M, Okada NJ, McDonald N, Jeste SS, Bookheimer SY, Green SA, Dapretto M. Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD. Cereb Cortex 2023; 33:8075-8086. [PMID: 37005061 PMCID: PMC10267628 DOI: 10.1093/cercor/bhad100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 04/04/2023] Open
Abstract
Despite growing evidence implicating thalamic functional connectivity atypicalities in autism spectrum disorder (ASD), it remains unclear how such alterations emerge early in human development. Because the thalamus plays a critical role in sensory processing and neocortical organization early in life, its connectivity with other cortical regions could be key for studying the early onset of core ASD symptoms. Here, we investigated emerging thalamocortical functional connectivity in infants at high (HL) and typical (TL) familial likelihood for ASD in early and late infancy. We report significant thalamo-limbic hyperconnectivity in 1.5-month-old HL infants, and thalamo-cortical hypoconnectivity in prefrontal and motor regions in 9-month-old HL infants. Importantly, early sensory over-responsivity (SOR) symptoms in HL infants predicted a direct trade-off in thalamic connectivity whereby stronger thalamic connectivity with primary sensory regions and basal ganglia was inversely related to connectivity with higher order cortices. This trade-off suggests that ASD may be characterized by early differences in thalamic gating. The patterns reported here could directly underlie atypical sensory processing and attention to social vs. nonsocial stimuli observed in ASD. These findings lend support to a theoretical framework of ASD whereby early disruptions in sensorimotor processing and attentional biases early in life may cascade into core ASD symptomatology.
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Affiliation(s)
- Lauren Wagner
- Neuroscience Interdepartmental Program, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Megan Banchik
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Nana J Okada
- Department of Psychology, Harvard Medical School, Boston, MA 02138, United States
| | - Nicole McDonald
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Shafali S Jeste
- Division of Neurology, Children’s Hospital Los Angeles, Los Angeles, CA 90027, United States
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Shulamite A Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, United States
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25
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Gandhi T, Canepa CR, Adeyelu TT, Adeniyi PA, Lee CC. Neuroanatomical Alterations in the CNTNAP2 Mouse Model of Autism Spectrum Disorder. Brain Sci 2023; 13:891. [PMID: 37371370 DOI: 10.3390/brainsci13060891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 05/23/2023] [Accepted: 05/29/2023] [Indexed: 06/29/2023] Open
Abstract
Autism spectrum disorder (ASD) is associated with neurodevelopmental alterations, including atypical forebrain cellular organization. Mutations in several ASD-related genes often result in cerebral cortical anomalies, such as the abnormal developmental migration of excitatory pyramidal cells and the malformation of inhibitory neuronal circuitry. Notably here, mutations in the CNTNAP2 gene result in ectopic superficial cortical neurons stalled in lower cortical layers and alterations to the balance of cortical excitation and inhibition. However, the broader circuit-level implications of these findings have not been previously investigated. Therefore, we assessed whether ectopic cortical neurons in CNTNAP2 mutant mice form aberrant connections with higher-order thalamic nuclei, potentially accounting for some autistic behaviors, such as repetitive and hyperactive behaviors. Furthermore, we assessed whether the development of parvalbumin-positive (PV) cortical interneurons and their specialized matrix support structures, called perineuronal nets (PNNs), were altered in these mutant mice. We found alterations in both ectopic neuronal connectivity and in the development of PNNs, PV neurons and PNNs enwrapping PV neurons in various sensory cortical regions and at different postnatal ages in the CNTNAP2 mutant mice, which likely lead to some of the cortical excitation/inhibition (E/I) imbalance associated with ASD. These findings suggest neuroanatomical alterations in cortical regions that underlie the emergence of ASD-related behaviors in this mouse model of the disorder.
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Affiliation(s)
- Tanya Gandhi
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70806, USA
| | - Cade R Canepa
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70806, USA
| | - Tolulope T Adeyelu
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70806, USA
| | - Philip A Adeniyi
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70806, USA
| | - Charles C Lee
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70806, USA
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26
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Openshaw RL, Thomson DM, Bristow GC, Mitchell EJ, Pratt JA, Morris BJ, Dawson N. 16p11.2 deletion mice exhibit compromised fronto-temporal connectivity, GABAergic dysfunction, and enhanced attentional ability. Commun Biol 2023; 6:557. [PMID: 37225770 DOI: 10.1038/s42003-023-04891-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 05/01/2023] [Indexed: 05/26/2023] Open
Abstract
Autism spectrum disorders are more common in males, and have a substantial genetic component. Chromosomal 16p11.2 deletions in particular carry strong genetic risk for autism, yet their neurobiological impact is poorly characterised, particularly at the integrated systems level. Here we show that mice reproducing this deletion (16p11.2 DEL mice) have reduced GABAergic interneuron gene expression (decreased parvalbumin mRNA in orbitofrontal cortex, and male-specific decreases in Gad67 mRNA in parietal and insular cortex and medial septum). Metabolic activity was increased in medial septum, and in its efferent targets: mammillary body and (males only) subiculum. Functional connectivity was altered between orbitofrontal, insular and auditory cortex, and between septum and hippocampus/subiculum. Consistent with this circuit dysfunction, 16p11.2 DEL mice showed reduced prepulse inhibition, but enhanced performance in the continuous performance test of attentional ability. Level 1 autistic individuals show similarly heightened performance in the equivalent human test, also associated with parietal, insular-orbitofrontal and septo-subicular dysfunction. The data implicate cortical and septal GABAergic dysfunction, and resulting connectivity changes, as the cause of pre-attentional and attentional changes in autism.
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Affiliation(s)
- Rebecca L Openshaw
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK
| | - David M Thomson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Greg C Bristow
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, BD7 1DP, UK
| | - Emma J Mitchell
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Judith A Pratt
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Brian J Morris
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK.
| | - Neil Dawson
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK.
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27
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Leisman G, Melillo R, Melillo T. Prefrontal Functional Connectivities in Autism Spectrum Disorders: A Connectopathic Disorder Affecting Movement, Interoception, and Cognition. Brain Res Bull 2023; 198:65-76. [PMID: 37087061 DOI: 10.1016/j.brainresbull.2023.04.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/05/2023] [Accepted: 04/17/2023] [Indexed: 04/24/2023]
Abstract
The prefrontal cortex is included in a neuronal system that includes the basal ganglia, the thalamus, and the cerebellum. Most of the higher and more complex motor, cognitive, and emotional behavioral functions are thought to be found primarily in the frontal lobes. Insufficient connectivity between the medial prefrontal cortex (mPFC) and other regions of the brain that are distant from each other involved in top-down information processing rely on the global integration of data from multiple input sources and enhance low level perception processes (bottom-up information processing). The reduced deactivation in mPFC and in the rest of the Default Network during global task processing is consistent with the integrative modulatory role served by the mPFC. We stress the importance of understanding the degree to which sensory and movement anomalies in individuals with autism spectrum disorder (ASD) can contribute to social impairment. Further investigation on the neurobiological basis of sensory symptoms and its relationship to other clinical features found in ASD is required Treatment perhaps should not be first behaviorally based but rather based on facilitating sensory motor development.
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Affiliation(s)
- Gerry Leisman
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel; University of the Medical Sciences of Havana, Department of Clinical Neurophysiology, Institute of Neurology and Neurosurgery, Havana, Cuba.
| | - Robert Melillo
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
| | - Ty Melillo
- Northeast College of the Health Sciencs, Seneca Falls, NY USA
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28
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Wilson S, Pietsch M, Cordero-Grande L, Christiaens D, Uus A, Karolis VR, Kyriakopoulou V, Colford K, Price AN, Hutter J, Rutherford MA, Hughes EJ, Counsell SJ, Tournier JD, Hajnal JV, Edwards AD, O’Muircheartaigh J, Arichi T. Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain. eLife 2023; 12:e83727. [PMID: 37010273 PMCID: PMC10125021 DOI: 10.7554/elife.83727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 03/31/2023] [Indexed: 04/04/2023] Open
Abstract
The development of connectivity between the thalamus and maturing cortex is a fundamental process in the second half of human gestation, establishing the neural circuits that are the basis for several important brain functions. In this study, we acquired high-resolution in utero diffusion magnetic resonance imaging (MRI) from 140 fetuses as part of the Developing Human Connectome Project, to examine the emergence of thalamocortical white matter over the second to third trimester. We delineate developing thalamocortical pathways and parcellate the fetal thalamus according to its cortical connectivity using diffusion tractography. We then quantify microstructural tissue components along the tracts in fetal compartments that are critical substrates for white matter maturation, such as the subplate and intermediate zone. We identify patterns of change in the diffusion metrics that reflect critical neurobiological transitions occurring in the second to third trimester, such as the disassembly of radial glial scaffolding and the lamination of the cortical plate. These maturational trajectories of MR signal in transient fetal compartments provide a normative reference to complement histological knowledge, facilitating future studies to establish how developmental disruptions in these regions contribute to pathophysiology.
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Affiliation(s)
- Siân Wilson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Maximilian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de MadridMadridSpain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)MadridSpain
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Department of Electrical Engineering (ESAT/PSI), Katholieke Universiteit LeuvenLeuvenBelgium
| | - Alena Uus
- Department of Biomedical Engineering, School Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas' HospitalLondonUnited Kingdom
| | - Vyacheslav R Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Emer J Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Department of Forensic and Neurodevelopmental Sciences, King’s College LondonLondonUnited Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College LondonLondonUnited Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College LondonLondonUnited Kingdom
- Centre for Neurodevelopmental Disorders, King’s College LondonLondonUnited Kingdom
- Children’s Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation TrustLondonUnited Kingdom
- Department of Bioengineering, Imperial College LondonLondonUnited Kingdom
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29
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Jaramillo V, Schoch SF, Markovic A, Kohler M, Huber R, Lustenberger C, Kurth S. An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy. Neuroimage 2023; 269:119924. [PMID: 36739104 DOI: 10.1016/j.neuroimage.2023.119924] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 01/24/2023] [Accepted: 02/01/2023] [Indexed: 02/05/2023] Open
Abstract
Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Spindles are often subdivided into slow (11.0-13.0 Hz) and fast (13.5-16.0 Hz) frequencies, for which not only different functions have been proposed, but for which also distinctive developmental trajectories have been reported across the first years of life. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants' EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas slow and fast spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, fast spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, fast spindle density in central and frontocentral regions at age 6 months predicts overall developmental status at age 12 months, and motor skills at age 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict later behavioral development. We further identified spindle frequency as a determinant of slow and fast spindle density, which accordingly, also predicts motor skills at 24 months. Our results propose fast spindle density, or alternatively spindle frequency, as early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are in support of a role of sleep spindles in sensorimotor microcircuitry development. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.
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Affiliation(s)
- Valeria Jaramillo
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Surrey Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom; Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Sarah F Schoch
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, NL
| | - Andjela Markovic
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Department of Psychology, University of Fribourg, Fribourg, CH
| | - Malcolm Kohler
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH
| | - Reto Huber
- Child Development Center, University Children's Hospital Zurich, Zurich, CH; Children's Research Center, University Children's Hospital Zurich, University of Zurich (UZH), Zürich, Switzerland; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, CH
| | - Caroline Lustenberger
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
| | - Salome Kurth
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Department of Psychology, University of Fribourg, Fribourg, CH.
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30
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Hong SJ, Mottron L, Park BY, Benkarim O, Valk SL, Paquola C, Larivière S, Vos de Wael R, Degré-Pelletier J, Soulieres I, Ramphal B, Margolis A, Milham M, Di Martino A, Bernhardt BC. A convergent structure-function substrate of cognitive imbalances in autism. Cereb Cortex 2023; 33:1566-1580. [PMID: 35552620 PMCID: PMC9977381 DOI: 10.1093/cercor/bhac156] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 03/28/2022] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain. METHODS To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging. RESULTS IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas. CONCLUSION Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.
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Affiliation(s)
- Seok-Jun Hong
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea.,Department of Biomedical Engineering, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea.,Center for the Developing Brain, Child Mind Institute, 101 East 56th Street, New York, NY 10022, United States
| | - Laurent Mottron
- Centre de Recherche du CIUSSSNIM and Department of Psychiatry and Addictology, Université de Montréal, 7070 boulevard Perras, Montréal, Quebec H1E 1A4, Canada
| | - Bo-Yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Seobu-ro 2066, Jangan-gu, Suwon 16419, South Korea.,Department of Data Science, Inha Univerisity, Incheon 22212, South Korea
| | - Oualid Benkarim
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Sofie L Valk
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Otto Hahn group Cognitive neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraβe 1A. Leipzig D-04103, Germany.,Institute of Neuroscience and Medicine, Research Centre Wilhelm-Johnen-Strasse, Jülich 52425, Germany.,Institute of Systems Neuroscience, Heinrich Heine University, Moorenstr. 5, Düsseldorf 40225, Germany
| | - Casey Paquola
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Institute of Neuroscience and Medicine, Research Centre Wilhelm-Johnen-Strasse, Jülich 52425, Germany
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
| | - Janie Degré-Pelletier
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada.,Department of Psychology, Université du Québec à Montréal, 100 rue Sherbrooke Ouest, Montréal, Québec H2X 3P2, Canada
| | - Isabelle Soulieres
- Department of Psychology, Université du Québec à Montréal, 100 rue Sherbrooke Ouest, Montréal, Québec H2X 3P2, Canada
| | - Bruce Ramphal
- Department of Psychiatry, The New York State Psychiatric Institute and the College of Physicians Surgeons, Columbia University, 1051 Riverside Drive, New York, NY 10032, United States
| | - Amy Margolis
- Department of Psychiatry, The New York State Psychiatric Institute and the College of Physicians Surgeons, Columbia University, 1051 Riverside Drive, New York, NY 10032, United States
| | - Michael Milham
- Center for the Developing Brain, Child Mind Institute, 101 East 56th Street, New York, NY 10022, United States.,Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY 10962, United States
| | - Adriana Di Martino
- Autism Center, Child Mind Institute, 101 East 56th Street, New York, NY 10022, United States
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Department of Neurology and Neurosurgery and Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, Quebec H3A2B4, Canada
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31
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Baran B, Trang Huong Nguyen Q, Mylonas D, Santangelo SL, Manoach DS. Increased resting-state thalamocortical functional connectivity in children and young adults with autism spectrum disorder. Autism Res 2023; 16:271-279. [PMID: 36546577 PMCID: PMC10619334 DOI: 10.1002/aur.2875] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022]
Abstract
There is converging evidence that abnormal thalamocortical interactions contribute to attention deficits and sensory sensitivities in autism spectrum disorder (ASD). However, previous functional MRI studies of thalamocortical connectivity in ASD have produced inconsistent findings in terms of both the direction (hyper vs. hypoconnectivity) and location of group differences. This may reflect, in part, the confounding effects of head motion during scans. In the present study, we investigated resting-state thalamocortical functional connectivity in 8-25 year-olds with ASD and their typically developing (TD) peers. We used pre-scan training, on-line motion correction, and rigorous data quality assurance protocols to minimize motion confounds. ASD participants showed increased thalamic connectivity with temporal cortex relative to TD. Both groups showed similar age-related decreases in thalamic connectivity with occipital cortex, consistent with a process of circuit refinement. Findings of thalamocortical hyperconnectivity in ASD are consistent with other evidence that decreased thalamic inhibition leads to increase and less filtered sensory information reaching the cortex where it disrupts attention and contributes to sensory sensitivity. This literature motivates studies of mechanisms, functional consequences, and treatment of thalamocortical circuit dysfunction in ASD.
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Affiliation(s)
- Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA
| | | | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Susan L. Santangelo
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Maine Medical Center Research Institute, Scarborough, ME
- Tufts University School of Medicine, Department of Psychiatry, Boston, MA
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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32
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Li C, Chen W, Li X, Li T, Chen Y, Zhang C, Ning M, Wang X. Gray matter asymmetry atypical patterns in subgrouping minors with autism based on core symptoms. Front Neurosci 2023; 16:1077908. [PMID: 36760800 PMCID: PMC9905125 DOI: 10.3389/fnins.2022.1077908] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 12/30/2022] [Indexed: 01/26/2023] Open
Abstract
Abnormal gray matter (GM) asymmetry has been verified in autism spectrum disorder (ASD), which is characterized by high heterogeneity. ASD is distinguished by three core symptom domains. Previous neuroimaging studies have offered support for divergent neural substrates of different core symptom domains in ASD. However, no previous study has explored GM asymmetry alterations underlying different core symptom domains. This study sought to clarify atypical GM asymmetry patterns underlying three core symptom domains in ASD with a large sample of 230 minors with ASD (ages 7-18 years) and 274 matched TD controls from the Autism Brain Imaging Data Exchange I (ABIDE I) repository. To this end, the scores of the revised autism diagnostic interview (ADI-R) subscales were normalized for grouping ASD into three core-symptom-defined subgroups: social interaction (SI), verbal communication (VA), and restricted repetitive behaviors (RRB). We investigated core-symptom-related GM asymmetry alterations in ASD resulting from advanced voxel-based morphometry (VBM) by general linear models. We also examined the relationship between GM asymmetry and age and between GM asymmetry and symptom severity assessed by the Autism Diagnostic Observation Schedule (ADOS). We found unique GM asymmetry alterations underlying three core-symptom-defined subgroups in ASD: more rightward asymmetry in the thalamus for SI, less rightward asymmetry in the superior temporal gyrus, anterior cingulate and caudate for VA, and less rightward asymmetry in the middle and inferior frontal gyrus for RRB. Furthermore, the asymmetry indexes in the thalamus were negatively associated with ADOS_SOCIAL scores in the general ASD group. We also showed significant correlations between GM asymmetry and age in ASD and TD individuals. Our results support the theory that each core symptom domain of ASD may have independent etiological and neurobiological underpinnings, which is essential for the interpretation of heterogeneity and the future diagnosis and treatment of ASD.
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Affiliation(s)
- Cuicui Li
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Wenxiong Chen
- Guangzhou Women and Children’s Medical Center, Guangzhou, China
| | - Xiaojing Li
- Guangzhou Women and Children’s Medical Center, Guangzhou, China
| | - Tong Li
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Ying Chen
- Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Chunling Zhang
- Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Mingmin Ning
- Guangzhou Women and Children’s Medical Center, Guangzhou, China,*Correspondence: Mingmin Ning,
| | - Ximing Wang
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China,Ximing Wang,
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33
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Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy. J Neurosci 2023; 43:559-570. [PMID: 36639904 PMCID: PMC9888512 DOI: 10.1523/jneurosci.0874-22.2022] [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: 05/08/2022] [Revised: 10/19/2022] [Accepted: 11/26/2022] [Indexed: 12/12/2022] Open
Abstract
Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.
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34
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Koevoet D, Deschamps PKH, Kenemans JL. Catecholaminergic and cholinergic neuromodulation in autism spectrum disorder: A comparison to attention-deficit hyperactivity disorder. Front Neurosci 2023; 16:1078586. [PMID: 36685234 PMCID: PMC9853424 DOI: 10.3389/fnins.2022.1078586] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/15/2022] [Indexed: 01/09/2023] Open
Abstract
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by social impairments and restricted, repetitive behaviors. Treatment of ASD is notoriously difficult and might benefit from identification of underlying mechanisms that overlap with those disturbed in other developmental disorders, for which treatment options are more obvious. One example of the latter is attention-deficit hyperactivity disorder (ADHD), given the efficacy of especially stimulants in treatment of ADHD. Deficiencies in catecholaminergic systems [dopamine (DA), norepinephrine (NE)] in ADHD are obvious targets for stimulant treatment. Recent findings suggest that dysfunction in catecholaminergic systems may also be a factor in at least a subgroup of ASD. In this review we scrutinize the evidence for catecholaminergic mechanisms underlying ASD symptoms, and also include in this analysis a third classic ascending arousing system, the acetylcholinergic (ACh) network. We complement this with a comprehensive review of DA-, NE-, and ACh-targeted interventions in ASD, and an exploratory search for potential treatment-response predictors (biomarkers) in ASD, genetically or otherwise. Based on this review and analysis we propose that (1) stimulant treatment may be a viable option for an ASD subcategory, possibly defined by genetic subtyping; (2) cerebellar dysfunction is pronounced for a relatively small ADHD subgroup but much more common in ASD and in both cases may point toward NE- or ACh-directed intervention; (3) deficiency of the cortical salience network is sizable in subgroups of both disorders, and biomarkers such as eye blink rate and pupillometric data may predict the efficacy of targeting this underlying deficiency via DA, NE, or ACh in both ASD and ADHD.
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Affiliation(s)
- Damian Koevoet
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands,*Correspondence: Damian Koevoet,
| | - P. K. H. Deschamps
- Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - J. L. Kenemans
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, Netherlands
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Linke AC, Chen B, Olson L, Ibarra C, Fong C, Reynolds S, Apostol M, Kinnear M, Müller RA, Fishman I. Sleep Problems in Preschoolers With Autism Spectrum Disorder Are Associated With Sensory Sensitivities and Thalamocortical Overconnectivity. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:21-31. [PMID: 34343726 PMCID: PMC9826645 DOI: 10.1016/j.bpsc.2021.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/08/2021] [Accepted: 07/21/2021] [Indexed: 01/18/2023]
Abstract
BACKGROUND Projections between the thalamus and sensory cortices are established early in development and play an important role in regulating sleep as well as in relaying sensory information to the cortex. Atypical thalamocortical functional connectivity frequently observed in children with autism spectrum disorder (ASD) might therefore be linked to sensory and sleep problems common in ASD. METHODS Here, we investigated the relationship between auditory-thalamic functional connectivity measured during natural sleep functional magnetic resonance imaging, sleep problems, and sound sensitivities in 70 toddlers and preschoolers (1.5-5 years old) with ASD compared with a matched group of 46 typically developing children. RESULTS In children with ASD, sleep problems and sensory sensitivities were positively correlated, and increased sleep latency was associated with overconnectivity between the thalamus and auditory cortex in a subsample with high-quality magnetic resonance imaging data (n = 29). In addition, auditory cortex blood oxygen level-dependent signal amplitude was elevated in children with ASD, potentially reflecting reduced sensory gating or a lack of auditory habituation during natural sleep. CONCLUSIONS These findings indicate that atypical thalamocortical functional connectivity can be detected early in development and may play a crucial role in sleep problems and sensory sensitivities in ASD.
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Affiliation(s)
- Annika Carola Linke
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California.
| | - Bosi Chen
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Lindsay Olson
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Cynthia Ibarra
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Chris Fong
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California
| | - Sarah Reynolds
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Michael Apostol
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Mikaela Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California
| | - Ralph-Axel Müller
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California; SDSU Center for Autism and Developmental Disorders, San Diego, California
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University, San Diego, California; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California; SDSU Center for Autism and Developmental Disorders, San Diego, California
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Karavallil Achuthan S, Coburn KL, Beckerson ME, Kana RK. Amplitude of low frequency fluctuations during resting state fMRI in autistic children. Autism Res 2023; 16:84-98. [PMID: 36349875 DOI: 10.1002/aur.2846] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022]
Abstract
Resting state fMRI (rs-fMRI) provides an excellent platform for examining the amplitude of low frequency fluctuations (ALFF) and fractional amplitude of low frequency fluctuations (fALFF), which are key indices of brain functioning. However, ALFF and fALFF have been used only sporadically to study autism. rs-fMRI data from 69 children (40 autistic, mean age = 8.47 ± 2.20 years; age range: 5.2 to 13.2; and 29 non-autistic, mean age = 9.02 ± 1.97 years; age range 5.9 to 12.9) were obtained from the Autism Brain Imaging Data Exchange (ABIDE II). ALFF and fALFF were measured using CONN connectivity toolbox and SPM12, at whole-brain & network-levels. A two-sampled t-test and a 2 Group (autistic, non-autistic) × 7 Networks ANOVA were conducted to test group differences in ALFF and fALFF. The whole-brain analysis identified significantly reduced ALFF values for autistic participants in left parietal opercular cortex, precuneus, and right insula. At the network level, there was a significant effect of diagnostic group and brain network on ALFF values, and only significant effect of network, not group, on fALFF values. Regression analyses indicated a significant effect of age on ALFF values of certain networks in autistic participants. Such intrinsically different network-level responses in autistic participants may have implications for task-level recruitment and synchronization of brain areas, which may in turn impact optimal cognitive functioning. Moreover, differences in low frequency fluctuations of key networks, such as the DMN and SN, may underlie alterations in brain responses in autism that are frequently reported in the literature.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Kelly L Coburn
- Department of Speech-Language Pathology & Audiology, Towson University, Towson, Maryland, USA
| | - Meagan E Beckerson
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Rajesh K Kana
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
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Weaver C, Xiao L, Lindquist MA. Single-index models with functional connectivity network predictors. Biostatistics 2022; 24:52-67. [PMID: 33948617 DOI: 10.1093/biostatistics/kxab015] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 03/22/2021] [Accepted: 03/25/2021] [Indexed: 12/16/2022] Open
Abstract
Functional connectivity is defined as the undirected association between two or more functional magnetic resonance imaging (fMRI) time series. Increasingly, subject-level functional connectivity data have been used to predict and classify clinical outcomes and subject attributes. We propose a single-index model wherein response variables and sparse functional connectivity network valued predictors are linked by an unspecified smooth function in order to accommodate potentially nonlinear relationships. We exploit the network structure of functional connectivity by imposing meaningful sparsity constraints, which lead not only to the identification of association of interactions between regions with the response but also the assessment of whether or not the functional connectivity associated with a brain region is related to the response variable. We demonstrate the effectiveness of the proposed model in simulation studies and in an application to a resting-state fMRI data set from the Human Connectome Project to model fluid intelligence and sex and to identify predictive links between brain regions.
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Affiliation(s)
- Caleb Weaver
- Department of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27606, USA
| | - Luo Xiao
- Department of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27606, USA
| | - Martin A Lindquist
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA
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Abnormal Dynamic Functional Network Connectivity in Adults with Autism Spectrum Disorder. Clin Neuroradiol 2022; 32:1087-1096. [PMID: 35543744 DOI: 10.1007/s00062-022-01173-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/12/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE This study sought to explore changes of brain dynamic functional network connectivity (dFNC) in adults with autism spectrum disorder (ASD) and investigate their relationship with clinical manifestations. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 78 adult ASD patients from autism brain imaging data exchange datasets, and 65 age-matched healthy controls subjects from the local community. Independent component analysis was conducted to evaluate dFNC patterns on the basis of 13 independent components (ICs) within 11 resting-state networks (RSN), namely, auditory network (AUDN), basal ganglia network (BGN), language network (LN), sensorimotor network (SMN), precuneus network (PUCN), salience network (SN), visuospatial network (VSN), dorsal default mode network (dDMN), high visual network (hVIS), primary visual network (pVIS), ventral default mode network (vDMN). Fraction time, mean dwell time, number of transitions, and RSN connectivity were calculated for group comparisons. Correlation analyses were performed between abnormal metrics and autism diagnostic observation schedule (ADOS) scores. RESULTS Compared with controls, ASD patients had higher fraction time and mean dwell time in state 2 (P = 0.017, P = 0.014). Reduced dFNC was found in the SMN with PUCN, SMN with hVIS, and increased dFNC was observed in the dDMN with SN in state 2 in the ASD group. Fraction time and mean dwell time was positively correlated with stereotyped behavior scores of ADOS. CONCLUSION The findings demonstrated the importance of evaluating transient alterations in specific neural networks of adult ASD patients. The abnormal metrics and connectivity may be related to symptoms such as stereotyped behavior.
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Zhang M, Hu X, Jiao J, Yuan D, Li S, Luo T, Wang M, Situ M, Sun X, Huang Y. Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study. Sci Rep 2022; 12:20151. [PMID: 36418886 PMCID: PMC9684497 DOI: 10.1038/s41598-022-21085-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Accepted: 09/22/2022] [Indexed: 11/24/2022] Open
Abstract
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.
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Affiliation(s)
- Manxue Zhang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China ,grid.412461.40000 0004 9334 6536The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiao Hu
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China ,grid.412901.f0000 0004 1770 1022West China Second Hospital of Sichuan University, Chengdu, China
| | - Jian Jiao
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Danfeng Yuan
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Sixun Li
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Tingting Luo
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Meiwen Wang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Mingjing Situ
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xueli Sun
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yi Huang
- grid.412901.f0000 0004 1770 1022Mental Health Center, West China Hospital of Sichuan University, Chengdu, China ,grid.412901.f0000 0004 1770 1022Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
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Talesh Jafadideh A, Mohammadzadeh Asl B. Topological analysis of brain dynamics in autism based on graph and persistent homology. Comput Biol Med 2022; 150:106202. [PMID: 37859293 DOI: 10.1016/j.compbiomed.2022.106202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/02/2022] [Accepted: 10/09/2022] [Indexed: 11/22/2022]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous disorder with a rapidly growing prevalence. In recent years, the dynamic functional connectivity (DFC) technique has been used to reveal the transient connectivity behavior of ASDs' brains by clustering connectivity matrices in different states. However, the states of DFC have not been yet studied from a topological point of view. In this paper, this study was performed using global metrics of the graph and persistent homology (PH) and resting-state functional magnetic resonance imaging (fMRI) data. The PH has been recently developed in topological data analysis and deals with persistent structures of data. The structural connectivity (SC) and static FC (SFC) were also studied to know which one of the SC, SFC, and DFC could provide more discriminative topological features when comparing ASDs with typical controls (TCs). Significant discriminative features were only found in states of DFC. Moreover, the best classification performance was offered by persistent homology-based metrics and in two out of four states. In these two states, some networks of ASDs compared to TCs were more segregated and isolated (showing the disruption of network integration in ASDs). The results of this study demonstrated that topological analysis of DFC states could offer discriminative features which were not discriminative in SFC and SC. Also, PH metrics can provide a promising perspective for studying ASD and finding candidate biomarkers.
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Possible Neural Mechanisms Underlying Sensory Over-Responsivity in Individuals with ASD. CURRENT DEVELOPMENTAL DISORDERS REPORTS 2022. [DOI: 10.1007/s40474-022-00257-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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From bench to bedside: The mGluR5 system in people with and without Autism Spectrum Disorder and animal model systems. Transl Psychiatry 2022; 12:395. [PMID: 36127322 PMCID: PMC9489881 DOI: 10.1038/s41398-022-02143-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 08/19/2022] [Accepted: 09/01/2022] [Indexed: 11/08/2022] Open
Abstract
The metabotropic glutamate receptor 5 (mGluR5) is a key regulator of excitatory (E) glutamate and inhibitory (I) γ-amino butyric acid (GABA) signalling in the brain. Despite the close functional ties between mGluR5 and E/I signalling, no-one has directly examined the relationship between mGluR5 and glutamate or GABA in vivo in the human brain of autistic individuals. We measured [18F] FPEB (18F-3-fluoro-5-[(pyridin-3-yl)ethynyl]benzonitrile) binding in 15 adults (6 with Autism Spectrum Disorder) using two regions of interest, the left dorsomedial prefrontal cortex and a region primarily composed of left striatum and thalamus. These two regions were mapped out using MEGA-PRESS voxels and then superimposed on reconstructed PET images. This allowed for direct comparison between mGluR5, GABA + and Glx. To better understand the molecular underpinnings of our results we used an autoradiography study of mGluR5 in three mouse models associated with ASD: Cntnap2 knockout, Shank3 knockout, and 16p11.2 deletion. Autistic individuals had significantly higher [18F] FPEB binding (t (13) = -2.86, p = 0.047) in the left striatum/thalamus region of interest as compared to controls. Within this region, there was a strong negative correlation between GABA + and mGluR5 density across the entire cohort (Pearson's correlation: r (14) = -0.763, p = 0.002). Cntnap2 KO mice had significantly higher mGlu5 receptor binding in the striatum (caudate-putamen) as compared to wild-type (WT) mice (n = 15, p = 0.03). There were no differences in mGluR5 binding for mice with the Shank3 knockout or 16p11.2 deletion. Given that Cntnap2 is associated with a specific striatal deficit of parvalbumin positive GABA interneurons and 'autistic' features, our findings suggest that an increase in mGluR5 in ASD may relate to GABAergic interneuron abnormalities.
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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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Block CL, Eroglu O, Mague SD, Smith CJ, Ceasrine AM, Sriworarat C, Blount C, Beben KA, Malacon KE, Ndubuizu N, Talbot A, Gallagher NM, Chan Jo Y, Nyangacha T, Carlson DE, Dzirasa K, Eroglu C, Bilbo SD. Prenatal environmental stressors impair postnatal microglia function and adult behavior in males. Cell Rep 2022; 40:111161. [PMID: 35926455 PMCID: PMC9438555 DOI: 10.1016/j.celrep.2022.111161] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 05/18/2022] [Accepted: 07/13/2022] [Indexed: 12/14/2022] Open
Abstract
Gestational exposure to environmental toxins and socioeconomic stressors is epidemiologically linked to neurodevelopmental disorders with strong male bias, such as autism. We model these prenatal risk factors in mice by co-exposing pregnant dams to an environmental pollutant and limited-resource stress, which robustly activates the maternal immune system. Only male offspring display long-lasting behavioral abnormalities and alterations in the activity of brain networks encoding social interactions. Cellularly, prenatal stressors diminish microglial function within the anterior cingulate cortex, a central node of the social coding network, in males during early postnatal development. Precise inhibition of microglial phagocytosis within the anterior cingulate cortex (ACC) of wild-type (WT) mice during the same critical period mimics the impact of prenatal stressors on a male-specific behavior, indicating that environmental stressors alter neural circuit formation in males via impairing microglia function during development. Block et al. show that combined exposure to air pollution and maternal stress during pregnancy activates the maternal immune system and induces male-specific impairments in social behavior and circuit connectivity in offspring. Cellularly, prenatal stressors diminish microglia phagocytic function, and inhibition of microglia phagocytosis phenocopies behavioral deficits from prenatal stressors.
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Affiliation(s)
- Carina L Block
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | - Oznur Eroglu
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Stephen D Mague
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA
| | - Caroline J Smith
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | - Alexis M Ceasrine
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | | | - Cameron Blount
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Kathleen A Beben
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | - Karen E Malacon
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | - Nkemdilim Ndubuizu
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Austin Talbot
- Department of Statistical Science, Duke University, Durham, NC 27710, USA
| | - Neil M Gallagher
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Young Chan Jo
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA
| | - Timothy Nyangacha
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - David E Carlson
- Department of Civil and Environmental Engineering, Duke University, Durham, NC 27710, USA; Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27710, USA
| | - Kafui Dzirasa
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Duke Institute for Brain Sciences, Durham, NC 27710, USA; Howard Hughes Medical Institute, Duke University, Durham, NC 27710, USA.
| | - Cagla Eroglu
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Duke Institute for Brain Sciences, Durham, NC 27710, USA; Howard Hughes Medical Institute, Duke University, Durham, NC 27710, USA.
| | - Staci D Bilbo
- Department of Psychology and Neuroscience, Trinity College of Arts and Sciences, Duke University, Durham, NC 27710, USA; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Duke Institute for Brain Sciences, Durham, NC 27710, USA; Lurie Center for Autism, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
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Bogdanova OV, Bogdanov VB, Pizano A, Bouvard M, Cazalets JR, Mellen N, Amestoy A. The Current View on the Paradox of Pain in Autism Spectrum Disorders. Front Psychiatry 2022; 13:910824. [PMID: 35935443 PMCID: PMC9352888 DOI: 10.3389/fpsyt.2022.910824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 06/17/2022] [Indexed: 01/18/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which affects 1 in 44 children and may cause severe disabilities. Besides socio-communicational difficulties and repetitive behaviors, ASD also presents as atypical sensorimotor function and pain reactivity. While chronic pain is a frequent co-morbidity in autism, pain management in this population is often insufficient because of difficulties in pain evaluation, worsening their prognosis and perhaps driving higher mortality rates. Previous observations have tended to oversimplify the experience of pain in autism as being insensitive to painful stimuli. Various findings in the past 15 years have challenged and complicated this dogma. However, a relatively small number of studies investigates the physiological correlates of pain reactivity in ASD. We explore the possibility that atypical pain perception in people with ASD is mediated by alterations in pain perception, transmission, expression and modulation, and through interactions between these processes. These complex interactions may account for the great variability and sometimes contradictory findings from the studies. A growing body of evidence is challenging the idea of alterations in pain processing in ASD due to a single factor, and calls for an integrative view. We propose a model of the pain cycle that includes the interplay between the molecular and neurophysiological pathways of pain processing and it conscious appraisal that may interfere with pain reactivity and coping in autism. The role of social factors in pain-induced response is also discussed. Pain assessment in clinical care is mostly based on subjective rather than objective measures. This review clarifies the strong need for a consistent methodology, and describes innovative tools to cope with the heterogeneity of pain expression in ASD, enabling individualized assessment. Multiple measures, including self-reporting, informant reporting, clinician-assessed, and purely physiological metrics may provide more consistent results. An integrative view on the regulation of the pain cycle offers a more robust framework to characterize the experience of pain in autism.
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Affiliation(s)
- Olena V. Bogdanova
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
| | - Volodymyr B. Bogdanov
- Laboratoire EA 4136 – Handicap Activité Cognition Santé HACS, Collège Science de la Sante, Institut Universitaire des Sciences de la Réadaptation, Université de Bordeaux, Bordeaux, France
| | - Adrien Pizano
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
| | - Manuel Bouvard
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
| | - Jean-Rene Cazalets
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
| | - Nicholas Mellen
- Department of Neurology, University of Louisville, Louisville, KY, United States
| | - Anouck Amestoy
- CNRS, Aquitaine Institute for Cognitive and Integrative Neuroscience, INCIA, UMR 5287, Université de Bordeaux, Bordeaux, France
- Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de l’Enfant et de l’Adolescent, Bordeaux, France
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Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on Autism Spectrum Disorder Neuroimaging. DISEASE MARKERS 2022; 2022:3372217. [PMID: 35899177 PMCID: PMC9313970 DOI: 10.1155/2022/3372217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 06/26/2022] [Accepted: 06/30/2022] [Indexed: 11/17/2022]
Abstract
Background Autism spectrum disorder (ASD) is a chronic developmental disability caused by differences in the brain. The gold standard for the diagnosis of this condition is based on behavioral science, but research on the application of neurological detection to diagnose the atypical nervous system of ASD is ongoing. ASD neuroimaging research involves the examination of the brain's structure, functional connections, and neurometabolic. However, limited medical resource and the unique heterogeneity of ASD have resulted in many challenges when neuroimaging is utilized. Objective This bibliometric study is aimed at summarizing themes and trends in research on autism spectrum disorder neuroimaging and at proposing potential directions for future inquiry. Methods Citations were downloaded from the Web of Science Core Collection database on neuroimaging published from January 1, 2012, to December 31, 2021. The retrieved information was analyzed using Bibliometric.com, CiteSpace.5.8. R3, and VOS viewer. Results A total of 1,363 papers were published across 58 regions. The United States was the leading source of publications. The League of European Research Universities published the largest number of articles (171). Burst keywords from 2018 to 2021 include identification and network. The clusters of references that continued into 2020 included graph theory, functional connectivity, and classification, which represent key research topics. Conclusions Imaging data is being used to identify neuro-network models with higher accuracy for ASD discrimination. Functional near-infrared imaging is advantageous compared to other neuroimaging. In the future, research on systematic and accurate computer-aided diagnosis technology should be encouraged. Moreover, the study of neuroimaging of ASD in different psychological and behavioral states can inspire new ideas about the diagnosis and intervention training of ASD and should be explored.
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Montenegro JTP, Seguin D, Duerden EG. Joint attention in infants at high familial risk for autism spectrum disorder and the association with thalamic and hippocampal macrostructure. Cereb Cortex Commun 2022; 3:tgac029. [PMID: 36072708 PMCID: PMC9441013 DOI: 10.1093/texcom/tgac029] [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: 04/13/2022] [Revised: 06/30/2022] [Accepted: 07/05/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder. Infants diagnosed with ASD can show impairments in spontaneous gaze-following and will seldom engage in joint attention (JA). The ability to initiate JA (IJA) can be more significantly impaired than the ability to respond to JA (RJA). In a longitudinal study, 101 infants who had a familial risk for ASD were enrolled (62% males). Participants completed magnetic resonance imaging scans at 4 or 6 months of age. Subcortical volumes (thalamus, hippocampus, amygdala, basal ganglia, ventral diencephalon, and cerebellum) were automatically extracted. Early gaze and JA behaviors were assessed with standardized measures. The majority of infants were IJA nonresponders (n = 93, 92%), and over half were RJA nonresponders (n = 50, 52%). In the nonresponder groups, models testing the association of subcortical volumes with later ASD diagnosis accounted for age, sex, and cerebral volumes. In the nonresponder IJA group, using regression method, the left hippocampus (B = −0.009, aOR = 0.991, P = 0.025), the right thalamus (B = −0.016, aOR = 0.984, P = 0.026), as well as the left thalamus (B = 0.015, aOR = 1.015, P = 0.019), predicted later ASD diagnosis. Alterations in thalamic and hippocampal macrostructure in at-risk infants who do not engage in IJA may reflect an enhanced vulnerability and may be the key predictors of later ASD development.
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Affiliation(s)
- Julia T P Montenegro
- Applied Psychology , Faculty of Education, , London, Ontario N6G1G7, Canada
- Western University, Faculty of Education Building 1137 Western Road , Faculty of Education, , London, Ontario N6G1G7, Canada
| | - Diane Seguin
- Applied Psychology , Faculty of Education, , London, Ontario N6G1G7 , Canada
- Western University, Faculty of Education Building 1137 Western Road , Faculty of Education, , London, Ontario N6G1G7 , Canada
- Physiology & Pharmacology , Schulich School of Medicine and Dentistry, , Medical Science Building, Room 216 1151 Richmond St, London, Ontario N6A5C1 , Canada
- Western University , Schulich School of Medicine and Dentistry, , Medical Science Building, Room 216 1151 Richmond St, London, Ontario N6A5C1 , Canada
| | - Emma G Duerden
- Applied Psychology , Faculty of Education, , Faculty of Education Building 1137 Western Road, London, Ontario N6G1G7 , Canada
- Western University , Faculty of Education, , Faculty of Education Building 1137 Western Road, London, Ontario N6G1G7 , Canada
- Western Institute for Neuroscience, Western University, The Brain and Mind Institute Western Interdisciplinary Research Building , Room 3190 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Biomedical Engineering , Faculty of Engineering, , Amit Chakma Engineering Building, Room 2405 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Western University , Faculty of Engineering, , Amit Chakma Engineering Building, Room 2405 1151 Richmond St, London, Ontario N6A3K7 , Canada
- Psychiatry , Schulich School of Medicine and Dentistry, , Parkwood Institute Mental Health Care Building, F4-430, London, Ontario N6C0A7 , Canada
- University of Western Ontario , Schulich School of Medicine and Dentistry, , Parkwood Institute Mental Health Care Building, F4-430, London, Ontario N6C0A7 , Canada
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Talesh Jafadideh A, Mohammadzadeh Asl B. Rest-fMRI based comparison study between autism spectrum disorder and typically control using graph frequency bands. Comput Biol Med 2022; 146:105643. [DOI: 10.1016/j.compbiomed.2022.105643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/17/2022] [Accepted: 05/14/2022] [Indexed: 01/01/2023]
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Zhou Z, Chen S, Li Y, Zhao J, Li G, Chen L, Wu Y, Zhang S, Shi X, Chen X, Xu S, Ren M, Chang S, Shan C. Comparison of Sensory Observation and Somatosensory Stimulation in Mirror Neurons and the Sensorimotor Network: A Task-Based fMRI Study. Front Neurol 2022; 13:916990. [PMID: 35847217 PMCID: PMC9279701 DOI: 10.3389/fneur.2022.916990] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 05/25/2022] [Indexed: 12/03/2022] Open
Abstract
Objective This study aimed to investigate brain plasticity by somatosensory stimulation (SS) and sensory observation (SO) based on mirror neuron and embodied cognition theory. Action observation therapy has been widely adopted for motor function improvement in post-stroke patients. However, it is uncertain whether the SO approach can also contribute to the recovery of sensorimotor function after stroke. In this study, we explored the therapeutic potential of SO for sensorimotor dysfunction and provided new evidence for neurorehabilitation. Methods Twenty-six healthy right-handed adults (12 men and 14 women), aged 18–27 (mean, 22.12; SD, 2.12) years were included. All subjects were evaluated with task-based functional magnetic resonance imaging (fMRI) to discover the characteristics and differences in brain activation between SO and SS. We adopted a block design with two conditions during fMRI scanning: observing a sensory video of brushing (task condition A, defined as SO) and brushing subjects' right forearms while they watched a nonsense string (task condition B, defined as SS). One-sample t-tests were performed to identify brain regions and voxels activated for each task condition. A paired-sample t-test and conjunction analysis were performed to explore the differences and similarities between SO and SS. Results The task-based fMRI showed that the bilateral postcentral gyrus, left precentral gyrus, bilateral middle temporal gyrus, right supramarginal gyrus, and left supplementary motor area were significantly activated during SO or SS. In addition to these brain regions, SO could also activate areas containing mirror neurons, like the left inferior parietal gyrus. Conclusion SO could activate mirror neurons and sensorimotor network-related brain regions in healthy subjects like SS. Therefore, SO may be a promising novel therapeutic approach for sensorimotor dysfunction recovery in post-stroke patients.
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Affiliation(s)
- Zhiqing Zhou
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Songmei Chen
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Rehabilitation Medicine, Shanghai No. 3 Rehabilitation Hospital, Shanghai, China
| | - Yuanli Li
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
| | - Jingjun Zhao
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Guanwu Li
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lei Chen
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yuwei Wu
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Sicong Zhang
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaolong Shi
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xixi Chen
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Shutian Xu
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
| | - Meng Ren
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Shixin Chang
- Department of Radiology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- *Correspondence: Shixin Chang
| | - Chunlei Shan
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
- Chunlei Shan
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50
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Berto S, Treacher AH, Caglayan E, Luo D, Haney JR, Gandal MJ, Geschwind DH, Montillo AA, Konopka G. Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder. Nat Commun 2022; 13:3328. [PMID: 35680911 PMCID: PMC9184501 DOI: 10.1038/s41467-022-31053-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/13/2022] [Indexed: 12/13/2022] Open
Abstract
Gene expression covaries with brain activity as measured by resting state functional magnetic resonance imaging (MRI). However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate from the ABIDE I and II imaging cohorts with datasets of gene expression in brains of neurotypical individuals and individuals with autism spectrum disorder (ASD) with regionally matched brain activity measurements from fMRI datasets. We identify genes linked with brain activity whose association is disrupted in ASD. We identified a subset of genes that showed a differential developmental trajectory in individuals with ASD compared with controls. These genes are enriched in voltage-gated ion channels and inhibitory neurons, pointing to excitation-inhibition imbalance in ASD. We further assessed differences at the regional level showing that the primary visual cortex is the most affected region in ASD. Our results link disrupted brain expression patterns of individuals with ASD to brain activity and show developmental, cell type, and regional enrichment of activity linked genes. Gene expression patterns have been associated with functional activity patterns in the brain. Here the authors determine how gene expression patterns in the human brain supports brain phenotypes obtained from resting state fMRI imaging, identifying brain regions and genes relevant to autism.
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Affiliation(s)
- Stefano Berto
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Alex H Treacher
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Emre Caglayan
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Danni Luo
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Jillian R Haney
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Michael J Gandal
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Daniel H Geschwind
- Program in Neurobehavioral Genetics, Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Program in Neurogenetics, Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Albert A Montillo
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, 75390, USA. .,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA. .,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA.
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
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