1
|
Lautarescu A, Bonthrone AF, Bos B, Barratt B, Counsell SJ. Advances in fetal and neonatal neuroimaging and everyday exposures. Pediatr Res 2024:10.1038/s41390-024-03294-1. [PMID: 38877283 DOI: 10.1038/s41390-024-03294-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 06/16/2024]
Abstract
The complex, tightly regulated process of prenatal brain development may be adversely affected by "everyday exposures" such as stress and environmental pollutants. Researchers are only just beginning to understand the neural sequelae of such exposures, with advances in fetal and neonatal neuroimaging elucidating structural, microstructural, and functional correlates in the developing brain. This narrative review discusses the wide-ranging literature investigating the influence of parental stress on fetal and neonatal brain development as well as emerging literature assessing the impact of exposure to environmental toxicants such as lead and air pollution. These 'everyday exposures' can co-occur with other stressors such as social and financial deprivation, and therefore we include a brief discussion of neuroimaging studies assessing the effect of social disadvantage. Increased exposure to prenatal stressors is associated with alterations in the brain structure, microstructure and function, with some evidence these associations are moderated by factors such as infant sex. However, most studies examine only single exposures and the literature on the relationship between in utero exposure to pollutants and fetal or neonatal brain development is sparse. Large cohort studies are required that include evaluation of multiple co-occurring exposures in order to fully characterize their impact on early brain development. IMPACT: Increased prenatal exposure to parental stress and is associated with altered functional, macro and microstructural fetal and neonatal brain development. Exposure to air pollution and lead may also alter brain development in the fetal and neonatal period. Further research is needed to investigate the effect of multiple co-occurring exposures, including stress, environmental toxicants, and socioeconomic deprivation on early brain development.
Collapse
Affiliation(s)
- Alexandra Lautarescu
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alexandra F Bonthrone
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Brendan Bos
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Ben Barratt
- MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Serena J Counsell
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| |
Collapse
|
2
|
Arichi T. Characterizing Large-Scale Human Circuit Development with In Vivo Neuroimaging. Cold Spring Harb Perspect Biol 2024; 16:a041496. [PMID: 38438187 PMCID: PMC11146311 DOI: 10.1101/cshperspect.a041496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Large-scale coordinated patterns of neural activity are crucial for the integration of information in the human brain and to enable complex and flexible human behavior across the life span. Through recent advances in noninvasive functional magnetic resonance imaging (fMRI) methods, it is now possible to study this activity and how it emerges in the living fetal brain across the second half of human gestation. This work has demonstrated that functional activity in the fetal brain has several features in keeping with highly organized networks of activity, which are undergoing a highly programmed and rapid sequence of development before birth, in which long-range connections emerge and core features of the mature functional connectome (such as hub regions and a gradient organization) are established. In this review, the findings of these studies are summarized, their relationship to the known changes in developmental neurobiology is considered, and considerations for future work in the context of limitations to the fMRI approach are presented.
Collapse
Affiliation(s)
- Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College London, New Hunt's House, Guy's Campus, London SE1 1UL, United Kingdom
- Children's Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London SE1 7EH, United Kingdom
| |
Collapse
|
3
|
Whelan TP, Daly E, Puts NA, Malievskaia E, Murphy DGM, McAlonan GM. Editorial Perspective: Bridging the translational neuroscience gap in autism - development of the 'shiftability' paradigm. J Child Psychol Psychiatry 2024; 65:862-865. [PMID: 38130022 DOI: 10.1111/jcpp.13940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/08/2023] [Indexed: 12/23/2023]
Abstract
Clinical trials of pharmacological candidates targeting the core features of autism have largely failed. This is despite evidence linking differences in multiple neurochemical systems to brain function in autism. While this has in part been explained by the heterogeneity of the autistic population, the field has largely relied upon association studies to link brain chemistry to function. The only way to directly establish that a neurotransmitter or neuromodulator is involved in a candidate brain function is to change it and observe a shift in that function. This experimental approach dominates preclinical neuroscience, but not human studies. There is little direct experimental evidence describing how neurochemical systems modulate information processing in the living human brain. Thus, our understanding of how neurochemical differences contribute to neurodiversity is limited, impeding our ability to translate findings from animal studies into humans. Here, we introduce our 'shiftability' paradigm, an approach to bridge the translational gap in autism research. We provide an overview of the guiding principles and methodologies we use to directly test the hypothesis that neurochemical systems function differently in autistic and non-autistic individuals.
Collapse
Affiliation(s)
- Tobias P Whelan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- COMPASS Pathfinder Ltd, London, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicolaas A Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | | | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR-Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Grainne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR-Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| |
Collapse
|
4
|
Damera SR, De Asis-Cruz J, Cook KM, Kapse K, Spoehr E, Murnick J, Basu S, Andescavage N, Limperopoulos C. Regional homogeneity as a marker of sensory cortex dysmaturity in preterm infants. iScience 2024; 27:109662. [PMID: 38665205 PMCID: PMC11043889 DOI: 10.1016/j.isci.2024.109662] [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: 09/07/2023] [Revised: 01/23/2024] [Accepted: 04/01/2024] [Indexed: 04/28/2024] Open
Abstract
Atypical perinatal sensory experience in preterm infants is thought to increase their risk of neurodevelopmental disabilities by altering the development of the sensory cortices. Here, we used resting-state fMRI data from preterm and term-born infants scanned between 32 and 48 weeks post-menstrual age to assess the effect of early ex-utero exposure on sensory cortex development. Specifically, we utilized a measure of local correlated-ness called regional homogeneity (ReHo). First, we demonstrated that the brain-wide distribution of ReHo mirrors the known gradient of cortical maturation. Next, we showed that preterm birth differentially reduces ReHo across the primary sensory cortices. Finally, exploratory analyses showed that the reduction of ReHo in the primary auditory cortex of preterm infants is related to increased risk of autism at 18 months. In sum, we show that local connectivity within sensory cortices has different developmental trajectories, is differentially affected by preterm birth, and may be associated with later neurodevelopment.
Collapse
Affiliation(s)
- Srikanth R. Damera
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kevin M. Cook
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Kushal Kapse
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Emma Spoehr
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Jon Murnick
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Sudeepta Basu
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Children’s National, 111 Michigan Avenue NW, Washington, DC 20010, USA
| |
Collapse
|
5
|
Tsang T, Green SA, Liu J, Lawrence K, Jeste S, Bookheimer SY, Dapretto M. Salience network connectivity is altered in 6-week-old infants at heightened likelihood for developing autism. Commun Biol 2024; 7:485. [PMID: 38649483 PMCID: PMC11035613 DOI: 10.1038/s42003-024-06016-9] [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: 03/20/2023] [Accepted: 03/06/2024] [Indexed: 04/25/2024] Open
Abstract
Converging evidence implicates disrupted brain connectivity in autism spectrum disorder (ASD); however, the mechanisms linking altered connectivity early in development to the emergence of ASD symptomatology remain poorly understood. Here we examined whether atypicalities in the Salience Network - an early-emerging neural network involved in orienting attention to the most salient aspects of one's internal and external environment - may predict the development of ASD symptoms such as reduced social attention and atypical sensory processing. Six-week-old infants at high likelihood of developing ASD based on family history exhibited stronger Salience Network connectivity with sensorimotor regions; infants at typical likelihood of developing ASD demonstrated stronger Salience Network connectivity with prefrontal regions involved in social attention. Infants with higher connectivity with sensorimotor regions had lower connectivity with prefrontal regions, suggesting a direct tradeoff between attention to basic sensory versus socially-relevant information. Early alterations in Salience Network connectivity predicted subsequent ASD symptomatology, providing a plausible mechanistic account for the unfolding of atypical developmental trajectories associated with vulnerability to ASD.
Collapse
Affiliation(s)
| | - Shulamite A Green
- Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Cognitive Neuroscience, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Katherine Lawrence
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Shafali Jeste
- Children's Hospital Los Angeles, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Center for Cognitive Neuroscience, University of California, Los Angeles, Los Angeles, CA, USA
| | - Mirella Dapretto
- Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA.
- Semel Institute of Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| |
Collapse
|
6
|
Kang E, Heo DW, Lee J, Suk HI. A Learnable Counter-Condition Analysis Framework for Functional Connectivity-Based Neurological Disorder Diagnosis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:1377-1387. [PMID: 38019623 DOI: 10.1109/tmi.2023.3337074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
To understand the biological characteristics of neurological disorders with functional connectivity (FC), recent studies have widely utilized deep learning-based models to identify the disease and conducted post-hoc analyses via explainable models to discover disease-related biomarkers. Most existing frameworks consist of three stages, namely, feature selection, feature extraction for classification, and analysis, where each stage is implemented separately. However, if the results at each stage lack reliability, it can cause misdiagnosis and incorrect analysis in afterward stages. In this study, we propose a novel unified framework that systemically integrates diagnoses (i.e., feature selection and feature extraction) and explanations. Notably, we devised an adaptive attention network as a feature selection approach to identify individual-specific disease-related connections. We also propose a functional network relational encoder that summarizes the global topological properties of FC by learning the inter-network relations without pre-defined edges between functional networks. Last but not least, our framework provides a novel explanatory power for neuroscientific interpretation, also termed counter-condition analysis. We simulated the FC that reverses the diagnostic information (i.e., counter-condition FC): converting a normal brain to be abnormal and vice versa. We validated the effectiveness of our framework by using two large resting-state functional magnetic resonance imaging (fMRI) datasets, Autism Brain Imaging Data Exchange (ABIDE) and REST-meta-MDD, and demonstrated that our framework outperforms other competing methods for disease identification. Furthermore, we analyzed the disease-related neurological patterns based on counter-condition analysis.
Collapse
|
7
|
França LGS, Ciarrusta J, Gale-Grant O, Fenn-Moltu S, Fitzgibbon S, Chew A, Falconer S, Dimitrova R, Cordero-Grande L, Price AN, Hughes E, O'Muircheartaigh J, Duff E, Tuulari JJ, Deco G, Counsell SJ, Hajnal JV, Nosarti C, Arichi T, Edwards AD, McAlonan G, Batalle D. Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment. Nat Commun 2024; 15:16. [PMID: 38331941 PMCID: PMC10853532 DOI: 10.1038/s41467-023-44050-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 11/28/2023] [Indexed: 02/10/2024] Open
Abstract
Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.
Collapse
Affiliation(s)
- Lucas G S França
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Computer and Information Sciences, Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Sean Fitzgibbon
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Eugene Duff
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK
- Department of Brain Sciences, Imperial College London, London, W12 0BZ, UK
- UK Dementia Research Institute at Imperial College London, London, W12 0BZ, UK
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, 20500, Turku, Finland
- Turku Collegium for Science and Medicine and Technology, University of Turku, 20500, Turku, Finland
- Department of Psychiatry, University of Turku and Turku University Hospital, 20500, Turku, Finland
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Pompeu Fabra University, 08002, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, 08010, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103, Leipzig, Germany
- School of Psychological Sciences, Monash University, Melbourne, VIC, 3010, Australia
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
- Department of Paediatric Neurosciences, Evelina London Children's Hospital, Guy's and St Thomas' NHS Foundation Trust, London, SE1 7EH, UK
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, UK
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, SE1 1UL, UK
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK.
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, UK.
| |
Collapse
|
8
|
Huang Q, Velthuis H, Pereira AC, Ahmad J, Cooke SF, Ellis CL, Ponteduro FM, Puts NAJ, Dimitrov M, Batalle D, Wong NML, Kowalewski L, Ivin G, Daly E, Murphy DGM, McAlonan GM. Exploratory evidence for differences in GABAergic regulation of auditory processing in autism spectrum disorder. Transl Psychiatry 2023; 13:320. [PMID: 37852957 PMCID: PMC10584846 DOI: 10.1038/s41398-023-02619-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 09/28/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023] Open
Abstract
Altered reactivity and responses to auditory input are core to the diagnosis of autism spectrum disorder (ASD). Preclinical models implicate ϒ-aminobutyric acid (GABA) in this process. However, the link between GABA and auditory processing in humans (with or without ASD) is largely correlational. As part of a study of potential biosignatures of GABA function in ASD to inform future clinical trials, we evaluated the role of GABA in auditory repetition suppression in 66 adults (n = 28 with ASD). Neurophysiological responses (temporal and frequency domains) to repetitive standard tones and novel deviants presented in an oddball paradigm were compared after double-blind, randomized administration of placebo, 15 or 30 mg of arbaclofen (STX209), a GABA type B (GABAB) receptor agonist. We first established that temporal mismatch negativity was comparable between participants with ASD and those with typical development (TD). Next, we showed that temporal and spectral responses to repetitive standards were suppressed relative to responses to deviants in the two groups, but suppression was significantly weaker in individuals with ASD at baseline. Arbaclofen reversed weaker suppression of spectral responses in ASD but disrupted suppression in TD. A post hoc analysis showed that arbaclofen-elicited shift in suppression was correlated with autistic symptomatology measured using the Autism Quotient across the entire group, though not in the smaller sample of the ASD and TD group when examined separately. Thus, our results confirm: GABAergic dysfunction contributes to the neurophysiology of auditory sensory processing alterations in ASD, and can be modulated by targeting GABAB activity. These GABA-dependent sensory differences may be upstream of more complex autistic phenotypes.
Collapse
Affiliation(s)
- Qiyun Huang
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Research Center for Brain-Computer Interface, Pazhou Lab, Guangzhou, China.
| | - Hester Velthuis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andreia C Pereira
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Nuclear Sciences Applied to Health (ICNAS), Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Coimbra, Portugal
| | - Jumana Ahmad
- School of Human Sciences, University of Greenwich, London, UK
| | - Samuel F Cooke
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Claire L Ellis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Francesca M Ponteduro
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicolaas A J Puts
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Mihail Dimitrov
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nichol M L Wong
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - Lukasz Kowalewski
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Glynis Ivin
- South London and Maudsley NHS Foundation Trust Pharmacy, London, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
| | - Gráinne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
| |
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Fenn-Moltu S, Fitzgibbon SP, Ciarrusta J, Eyre M, Cordero-Grande L, Chew A, Falconer S, Gale-Grant O, Harper N, Dimitrova R, Vecchiato K, Fenchel D, Javed A, Earl M, Price AN, Hughes E, Duff EP, O’Muircheartaigh J, Nosarti C, Arichi T, Rueckert D, Counsell S, Hajnal JV, Edwards AD, McAlonan G, Batalle D. Development of neonatal brain functional centrality and alterations associated with preterm birth. Cereb Cortex 2023; 33:5585-5596. [PMID: 36408638 PMCID: PMC10152096 DOI: 10.1093/cercor/bhac444] [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: 06/02/2022] [Revised: 09/21/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022] Open
Abstract
Formation of the functional connectome in early life underpins future learning and behavior. However, our understanding of how the functional organization of brain regions into interconnected hubs (centrality) matures in the early postnatal period is limited, especially in response to factors associated with adverse neurodevelopmental outcomes such as preterm birth. We characterized voxel-wise functional centrality (weighted degree) in 366 neonates from the Developing Human Connectome Project. We tested the hypothesis that functional centrality matures with age at scan in term-born babies and is disrupted by preterm birth. Finally, we asked whether neonatal functional centrality predicts general neurodevelopmental outcomes at 18 months. We report an age-related increase in functional centrality predominantly within visual regions and a decrease within the motor and auditory regions in term-born infants. Preterm-born infants scanned at term equivalent age had higher functional centrality predominantly within visual regions and lower measures in motor regions. Functional centrality was not related to outcome at 18 months old. Thus, preterm birth appears to affect functional centrality in regions undergoing substantial development during the perinatal period. Our work raises the question of whether these alterations are adaptive or disruptive and whether they predict neurodevelopmental characteristics that are more subtle or emerge later in life.
Collapse
Affiliation(s)
- Sunniva Fenn-Moltu
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Sean P Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Judit Ciarrusta
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Michael Eyre
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, 28040, Spain
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Oliver Gale-Grant
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Nicholas Harper
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Katy Vecchiato
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Daphna Fenchel
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Ayesha Javed
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Megan Earl
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Paediatric Liver, GI and Nutrition Centre and MowatLabs, King’s College London, London, SE5 9RS, United Kingdom
| | - Anthony N Price
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Emer Hughes
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Eugene P Duff
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford, OX3 9DU, United Kingdom
- Department of Paediatrics, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Jonathan O’Muircheartaigh
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
- Paediatric Neurosciences, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, SE1 7EH, United Kingdom
- Department of Bioengineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Imperial College London, London, SW7 2AZ, United Kingdom
- Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, 81675, Germany
| | - Serena Counsell
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| | - A David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Grainne McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, SE1 1UL, United Kingdom
| | - Dafnis Batalle
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, SE5 8AF, United Kingdom
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE1 7EH, United Kingdom
| |
Collapse
|
11
|
Xu S, Zhang Z, Li L, Zhou Y, Lin D, Zhang M, Zhang L, Huang G, Liu X, Becker B, Liang Z. Functional connectivity profiles of the default mode and visual networks reflect temporal accumulative effects of sustained naturalistic emotional experience. Neuroimage 2023; 269:119941. [PMID: 36791897 DOI: 10.1016/j.neuroimage.2023.119941] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 01/30/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023] Open
Abstract
Determining and decoding emotional brain processes under ecologically valid conditions remains a key challenge in affective neuroscience. The current functional Magnetic Resonance Imaging (fMRI) based emotion decoding studies are mainly based on brief and isolated episodes of emotion induction, while sustained emotional experience in naturalistic environments that mirror daily life experiences are scarce. Here we used 12 different 10-minute movie clips as ecologically valid emotion-evoking procedures in n = 52 individuals to explore emotion-specific fMRI functional connectivity (FC) profiles on the whole-brain level at high spatial resolution (432 parcellations including cortical and subcortical structures). Employing machine-learning based decoding and cross validation procedures allowed to investigate FC profiles contributing to classification that can accurately distinguish sustained happiness and sadness and that generalize across subjects, movie clips, and parcellations. Both functional brain network-based and subnetwork-based emotion classification results suggested that emotion manifests as distributed representation of multiple networks, rather than a single functional network or subnetwork. Further, the results showed that the Visual Network (VN) and Default Mode Network (DMN) associated functional networks, especially VN-DMN, exhibited a strong contribution to emotion classification. To further estimate the temporal accumulative effect of naturalistic long-term movie-based video-evoking emotions, we divided the 10-min episode into three stages: early stimulation (1∼200 s), middle stimulation (201∼400 s), and late stimulation (401∼600 s) and examined the emotion classification performance at different stimulation stages. We found that the late stimulation contributes most to the classification (accuracy=85.32%, F1-score=85.62%) compared to early and middle stimulation stages, implying that continuous exposure to emotional stimulation can lead to more intense emotions and further enhance emotion-specific distinguishable representations. The present work demonstrated that sustained happiness and sadness under naturalistic conditions are presented in emotion-specific network profiles and these expressions may play different roles in the generation and modulation of emotions. These findings elucidated the importance of network level adaptations for sustained emotional experiences during naturalistic contexts and open new venues for imaging network level contributions under naturalistic conditions.
Collapse
Affiliation(s)
- Shuyue Xu
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Zhiguo Zhang
- Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China; Peng Cheng Laboratory, Shenzhen 518055, China; Marshall Laboratory of Biomedical Engineering, Shenzhen 518060, China
| | - Linling Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Yongjie Zhou
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, Shenzhen, China
| | - Danyi Lin
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Min Zhang
- Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China
| | - Li Zhang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Gan Huang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Xiqin Liu
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, MOE Key Laboratory for Neuroinformation, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Benjamin Becker
- Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, MOE Key Laboratory for Neuroinformation, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Zhen Liang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China; Marshall Laboratory of Biomedical Engineering, Shenzhen 518060, China.
| |
Collapse
|
12
|
Liu Y, Yu Q, Cheng L, Chen J, Gao J, Liu Y, Lin X, Wang X, Hou Z. The parcellation of cingulate cortex in neonatal period based on resting-state functional MRI. Cereb Cortex 2023; 33:2548-2558. [PMID: 35689654 DOI: 10.1093/cercor/bhac225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 11/14/2022] Open
Abstract
The human cingulate cortex (CC) is a complex region that is characterized by heterogeneous cytoarchitecture, connectivity, and function, and it is associated with various cognitive functions. The adult CC has been divided into various subregions, and this subdivision is highly consistent with its functional differentiation. However, only a few studies have focused on the function of neonatal CC. The aim of this study was to describe the cingulate segregation and the functional connectivity of each subdivision in full-term neonates (n = 60) based on resting-state functional magnetic resonance imaging. The neonatal CC was divided into three subregions, and each subregion showed specific connectivity patterns. The anterior cingulate cortex was mainly correlated with brain regions related to the salience (affected) network and default mode network (DMN), the midcingulate cortex was related to motor areas, and the posterior cingulate cortex was coupled with DMN. Moreover, we found that the cingulate subregions showed distinct functional profiles with major brain networks, which were defined using independent component analysis, and exhibited functional lateralization. This study provided new insights into the understanding of the functional specialization of neonatal CC, and these findings may have significant clinical implications, especially in predicting neurological disorder.
Collapse
Affiliation(s)
- Yanyan Liu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250014, China
| | - Luqi Cheng
- School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China
| | - Jinge Chen
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
| | - Jie Gao
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
| | - Yujia Liu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
| | - Xiangtao Lin
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250014, China
| | - Ximing Wang
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250014, China
| | - Zhongyu Hou
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Jinan, Shandong 250014, China
- Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250014, China
| |
Collapse
|
13
|
Zhang F, Moerman F, Niu H, Warreyn P, Roeyers H. Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life. Autism Res 2022; 15:2223-2237. [PMID: 36193817 DOI: 10.1002/aur.2827] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/20/2022] [Indexed: 12/15/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10 months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.
Collapse
Affiliation(s)
- Fen Zhang
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
- ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Floor Moerman
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Haijing Niu
- State Key Lab. of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Petra Warreyn
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Herbert Roeyers
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| |
Collapse
|
14
|
Scheinost D, Chang J, Lacadie C, Brennan-Wydra E, Foster R, Boxberger A, Macari S, Vernetti A, Constable RT, Ment LR, Chawarska K. Hypoconnectivity between anterior insula and amygdala associates with future vulnerabilities in social development in a neurodiverse sample of neonates. Sci Rep 2022; 12:16230. [PMID: 36171268 PMCID: PMC9517994 DOI: 10.1038/s41598-022-20617-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 09/15/2022] [Indexed: 11/25/2022] Open
Abstract
Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD = 1.5) who due to family history have high likelihood (HL) for developing autism (n = 12) and in controls (n = 41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M = 17.3 months, SD = 2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -0.561, p = .003) and this association remained robust when maternal mental health factors were considered. Considering that a subsample of LL participants (n = 14/41) underwent brain imaging during the fetal period at PMA 31 and 34 weeks, in an exploratory analysis, we evaluated prospectively development of the LaINS-Lamy connectivity and found that the two areas strongly coactivate throughout the third trimester of pregnancy. The study identifies left lateralized anterior insula-amygdala connectivity as a potential target of further investigation into neural circuitry that enhances likelihood of future onset of social behaviors associated with autism during neonatal and potentially prenatal periods.
Collapse
Affiliation(s)
- Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Joseph Chang
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA
| | - Cheryl Lacadie
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | | | - Rachel Foster
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | | | - Suzanne Macari
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Angelina Vernetti
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA
| | - R Todd Constable
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Laura R Ment
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, 06510, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Katarzyna Chawarska
- Department of Statistics and Data Science, Yale University, New Haven, CT, 06520, USA.
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, 06510, USA.
- Yale Child Study Center, Yale School of Medicine, 300 George Street, Suite 900, New Haven, CT, 06510, USA.
| |
Collapse
|
15
|
Kardan O, Kaplan S, Wheelock MD, Feczko E, Day TKM, Miranda-Domínguez Ó, Meyer D, Eggebrecht AT, Moore LA, Sung S, Chamberlain TA, Earl E, Snider K, Graham A, Berman MG, Uğurbil K, Yacoub E, Elison JT, Smyser CD, Fair DA, Rosenberg MD. Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds. Dev Cogn Neurosci 2022; 56:101123. [PMID: 35751994 PMCID: PMC9234342 DOI: 10.1016/j.dcn.2022.101123] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 05/20/2022] [Accepted: 06/13/2022] [Indexed: 11/23/2022] Open
Abstract
Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler's connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants' age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network-i.e. within-network connections-predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.
Collapse
Affiliation(s)
| | - Sydney Kaplan
- Washington University in St. Louis School of Medicine, USA
| | | | | | | | | | | | | | | | | | | | - Eric Earl
- Oregon Health & Science University, USA
| | | | | | | | | | | | | | | | | | | |
Collapse
|
16
|
Sobotka D, Ebner M, Schwartz E, Nenning KH, Taymourtash A, Vercauteren T, Ourselin S, Kasprian G, Prayer D, Langs G, Licandro R. Motion correction and volumetric reconstruction for fetal functional magnetic resonance imaging data. Neuroimage 2022; 255:119213. [PMID: 35430359 DOI: 10.1016/j.neuroimage.2022.119213] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 10/18/2022] Open
Abstract
Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose a single 3D volume from a specific acquisition timepoint with least motion artefacts as reference volume, and perform interpolation for the reconstruction of the motion corrected time series. The results can suffer, if no low-motion frame is available, and if reconstruction does not exploit any assumptions about the continuity of the fMRI signal. Here, we propose a novel framework, which estimates a high-resolution reference volume by using outlier-robust motion correction, and by utilizing Huber L2 regularization for intra-stack volumetric reconstruction of the motion-corrected fetal brain fMRI. We performed an extensive parameter study to investigate the effectiveness of motion estimation and present in this work benchmark metrics to quantify the effect of motion correction and regularised volumetric reconstruction approaches on functional connectivity computations. We demonstrate the proposed framework's ability to improve functional connectivity estimates, reproducibility and signal interpretability, which is clinically highly desirable for the establishment of prognostic noninvasive imaging biomarkers. The motion correction and volumetric reconstruction framework is made available as an open-source package of NiftyMIC.
Collapse
Affiliation(s)
- Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Ebner
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
| |
Collapse
|
17
|
Casingal CR, Descant KD, Anton ES. Coordinating cerebral cortical construction and connectivity: Unifying influence of radial progenitors. Neuron 2022; 110:1100-1115. [PMID: 35216663 PMCID: PMC8989671 DOI: 10.1016/j.neuron.2022.01.034] [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: 07/26/2021] [Revised: 10/15/2021] [Accepted: 01/26/2022] [Indexed: 01/02/2023]
Abstract
Radial progenitor development and function lay the foundation for the construction of the cerebral cortex. Radial glial scaffold, through its functions as a source of neurogenic progenitors and neuronal migration guide, is thought to provide a template for the formation of the cerebral cortex. Emerging evidence is challenging this limited view. Intriguingly, radial glial scaffold may also play a role in axonal growth, guidance, and neuronal connectivity. Radial glial cells not only facilitate the generation, placement, and allocation of neurons in the cortex but also regulate how they wire up. The organization and function of radial glial cells may thus be a unifying feature of the developing cortex that helps to precisely coordinate the right patterns of neurogenesis, neuronal placement, and connectivity necessary for the emergence of a functional cerebral cortex. This perspective critically explores this emerging view and its impact in the context of human brain development and disorders.
Collapse
Affiliation(s)
- Cristine R Casingal
- UNC Neuroscience Center, the Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - Katherine D Descant
- UNC Neuroscience Center, the Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
| | - E S Anton
- UNC Neuroscience Center, the Department of Cell Biology and Physiology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA.
| |
Collapse
|
18
|
Ouyang M, Peng Y, Sotardi S, Hu D, Zhu T, Cheng H, Huang H. Flattened Structural Network Changes and Association of Hyperconnectivity With Symptom Severity in 2-7-Year-Old Children With Autism. Front Neurosci 2022; 15:757838. [PMID: 35237118 PMCID: PMC8882907 DOI: 10.3389/fnins.2021.757838] [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: 08/12/2021] [Accepted: 12/21/2021] [Indexed: 01/17/2023] Open
Abstract
Understanding the brain differences present at the earliest possible diagnostic age for autism spectrum disorder (ASD) is crucial for delineating the underlying neuropathology of the disorder. However, knowledge of brain structural network changes in the early important developmental period between 2 and 7 years of age is limited in children with ASD. In this study, we aimed to fill the knowledge gap by characterizing age-related brain structural network changes in ASD from 2 to 7 years of age, and identify sensitive network-based imaging biomarkers that are significantly correlated with the symptom severity. Diffusion MRI was acquired in 30 children with ASD and 21 typically developmental (TD) children. With diffusion MRI and quantified clinical assessment, we conducted network-based analysis and correlation between graph-theory-based measurements and symptom severity. Significant age-by-group interaction was found in global network measures and nodal efficiencies during the developmental period of 2-7 years old. Compared with significant age-related growth of the structural network in TD, relatively flattened maturational trends were observed in ASD. Hyper-connectivity in the structural network with higher global efficiency, global network strength, and nodal efficiency were observed in children with ASD. Network edge strength in ASD also demonstrated hyper-connectivity in widespread anatomical connections, including those in default-mode, frontoparietal, and sensorimotor networks. Importantly, identified higher nodal efficiencies and higher network edge strengths were significantly correlated with symptom severity in ASD. Collectively, structural networks in ASD during this early developmental period of 2-7 years of age are characterized by hyper-connectivity and slower maturation, with aberrant hyper-connectivity significantly correlated with symptom severity. These aberrant network measures may serve as imaging biomarkers for ASD from 2 to 7 years of age.
Collapse
Affiliation(s)
- Minhui Ouyang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Yun Peng
- Department of Radiology, Beijing Children’s Hospital, Capital Medical University, Beijing, China,*Correspondence: Yun Peng,
| | - Susan Sotardi
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Di Hu
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Department of Radiology, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Tianjia Zhu
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
| | - Hua Cheng
- Department of Radiology, Beijing Children’s Hospital, Capital Medical University, Beijing, China
| | - Hao Huang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States,Hao Huang,
| |
Collapse
|
19
|
Huang Q, Pereira AC, Velthuis H, Wong NML, Ellis CL, Ponteduro FM, Dimitrov M, Kowalewski L, Lythgoe DJ, Rotaru D, Edden RAE, Leonard A, Ivin G, Ahmad J, Pretzsch CM, Daly E, Murphy DGM, McAlonan GM. GABA B receptor modulation of visual sensory processing in adults with and without autism spectrum disorder. Sci Transl Med 2022; 14:eabg7859. [PMID: 34985973 DOI: 10.1126/scitranslmed.abg7859] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
[Figure: see text].
Collapse
Affiliation(s)
- Qiyun Huang
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Andreia C Pereira
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Coimbra Institute for Biomedical Imaging and Translational Research, University of Coimbra, Coimbra 3000-548, Portugal.,Institute of Nuclear Sciences Applied to Health, University of Coimbra, Coimbra 3000-548, Portugal
| | - Hester Velthuis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Nichol M L Wong
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Claire L Ellis
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Francesca M Ponteduro
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Mihail Dimitrov
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Lukasz Kowalewski
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Diana Rotaru
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Alison Leonard
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Glynis Ivin
- South London and Maudsley NHS Foundation Trust Pharmacy, London SE5 8AZ, UK
| | - Jumana Ahmad
- School of Human Sciences, University of Greenwich, London SE10 9LS, UK
| | - Charlotte M Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK
| | - Gráinne M McAlonan
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK.,MRC Centre for Neurodevelopmental Disorders, King's College London, London SE1 1UL, UK
| |
Collapse
|
20
|
Takahashi E, Allan N, Peres R, Ortug A, van der Kouwe AJW, Valli B, Ethier E, Levman J, Baumer N, Tsujimura K, Vargas-Maya NI, McCracken TA, Lee R, Maunakea AK. Integration of structural MRI and epigenetic analyses hint at linked cellular defects of the subventricular zone and insular cortex in autism: Findings from a case study. Front Neurosci 2022; 16:1023665. [PMID: 36817099 PMCID: PMC9935943 DOI: 10.3389/fnins.2022.1023665] [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: 08/20/2022] [Accepted: 12/20/2022] [Indexed: 02/05/2023] Open
Abstract
Introduction Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction, communication and repetitive, restrictive behaviors, features supported by cortical activity. Given the importance of the subventricular zone (SVZ) of the lateral ventrical to cortical development, we compared molecular, cellular, and structural differences in the SVZ and linked cortical regions in specimens of ASD cases and sex and age-matched unaffected brain. Methods We used magnetic resonance imaging (MRI) and diffusion tractography on ex vivo postmortem brain samples, which we further analyzed by Whole Genome Bisulfite Sequencing (WGBS), Flow Cytometry, and RT qPCR. Results Through MRI, we observed decreased tractography pathways from the dorsal SVZ, increased pathways from the posterior ventral SVZ to the insular cortex, and variable cortical thickness within the insular cortex in ASD diagnosed case relative to unaffected controls. Long-range tractography pathways from and to the insula were also reduced in the ASD case. FACS-based cell sorting revealed an increased population of proliferating cells in the SVZ of ASD case relative to the unaffected control. Targeted qPCR assays of SVZ tissue demonstrated significantly reduced expression levels of genes involved in differentiation and migration of neurons in ASD relative to the control counterpart. Finally, using genome-wide DNA methylation analyses, we identified 19 genes relevant to neurological development, function, and disease, 7 of which have not previously been described in ASD, that were significantly differentially methylated in autistic SVZ and insula specimens. Conclusion These findings suggest a hypothesis that epigenetic changes during neurodevelopment alter the trajectory of proliferation, migration, and differentiation in the SVZ, impacting cortical structure and function and resulting in ASD phenotypes.
Collapse
Affiliation(s)
- Emi Takahashi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nina Allan
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| | - Rafael Peres
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| | - Alpen Ortug
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Andre J W van der Kouwe
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Briana Valli
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, United States
| | - Elizabeth Ethier
- Department of Behavioral Neuroscience, Northeastern University, Boston, MA, United States
| | - Jacob Levman
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.,Department of Mathematics, Statistics and Computer Science, St. Francis Xavier University, Antigonish, NS, Canada
| | - Nicole Baumer
- Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Keita Tsujimura
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Research, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Nauru Idalia Vargas-Maya
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| | - Trevor A McCracken
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| | - Rosa Lee
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| | - Alika K Maunakea
- Epigenomics Research Program, Department of Anatomy, Institute for Biogenesis Research, Biochemistry and Physiology, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, United States
| |
Collapse
|
21
|
Chen LZ, Holmes AJ, Zuo XN, Dong Q. Neuroimaging brain growth charts: A road to mental health. PSYCHORADIOLOGY 2021; 1:272-286. [PMID: 35028568 PMCID: PMC8739332 DOI: 10.1093/psyrad/kkab022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 12/03/2021] [Accepted: 12/17/2021] [Indexed: 12/30/2022]
Abstract
Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.
Collapse
Affiliation(s)
- Li-Zhen Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, CT 06511, USA
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA
| | - Xi-Nian Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- National Basic Science Data Center, Beijing 100190, China
- Developmental Population Neuroscience Research Center, International Data Group/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Research Center for Lifespan Development of Mind and Brain, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| |
Collapse
|
22
|
Zhang Z, Gibson JR, Huber KM. Experience-dependent weakening of callosal synaptic connections in the absence of postsynaptic FMRP. eLife 2021; 10:71555. [PMID: 34617509 PMCID: PMC8526058 DOI: 10.7554/elife.71555] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 10/06/2021] [Indexed: 12/18/2022] Open
Abstract
Reduced structural and functional interhemispheric connectivity correlates with the severity of Autism Spectrum Disorder (ASD) behaviors in humans. Little is known of how ASD-risk genes regulate callosal connectivity. Here, we show that Fmr1, whose loss-of-function leads to Fragile X Syndrome (FXS), cell autonomously promotes maturation of callosal excitatory synapses between somatosensory barrel cortices in mice. Postnatal, cell-autonomous deletion of Fmr1 in postsynaptic Layer (L) 2/3 or L5 neurons results in a selective weakening of AMPA receptor- (R), but not NMDA receptor-, mediated callosal synaptic function, indicative of immature synapses. Sensory deprivation by contralateral whisker trimming normalizes callosal input strength, suggesting that experience-driven activity of postsynaptic Fmr1 KO L2/3 neurons weakens callosal synapses. In contrast to callosal inputs, synapses originating from local L4 and L2/3 circuits are normal, revealing an input-specific role for postsynaptic Fmr1 in regulation of synaptic connectivity within local and callosal neocortical circuits. These results suggest direct cell autonomous and postnatal roles for FMRP in development of specific cortical circuits and suggest a synaptic basis for long-range functional underconnectivity observed in FXS patients.
Collapse
Affiliation(s)
- Zhe Zhang
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
| | - Jay R Gibson
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
| | - Kimberly M Huber
- Department of Neuroscience, O'Donnell Brain Institute, University of Texas Southwestern Medical Center, Dallas, United States
| |
Collapse
|
23
|
Rajasilta O, Häkkinen S, Björnsdotter M, Scheinin NM, Lehtola SJ, Saunavaara J, Parkkola R, Lähdesmäki T, Karlsson L, Karlsson H, Tuulari JJ. Maternal pre-pregnancy BMI associates with neonate local and distal functional connectivity of the left superior frontal gyrus. Sci Rep 2021; 11:19182. [PMID: 34584134 PMCID: PMC8478954 DOI: 10.1038/s41598-021-98574-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Accepted: 09/06/2021] [Indexed: 11/09/2022] Open
Abstract
Maternal obesity/overweight during pregnancy has reached epidemic proportions and has been linked with adverse outcomes for the offspring, including cognitive impairment and increased risk for neuropsychiatric disorders. Prior neuroimaging investigations have reported widespread aberrant functional connectivity and white matter tract abnormalities in neonates born to obese mothers. Here we explored whether maternal pre-pregnancy adiposity is associated with alterations in local neuronal synchrony and distal connectivity in the neonate brain. 21 healthy mother-neonate dyads from uncomplicated pregnancies were included in this study (age at scanning 26.14 ± 6.28 days, 12 male). The neonates were scanned with a 6-min resting-state functional magnetic resonance imaging (rs-fMRI) during natural sleep. Regional homogeneity (ReHo) maps were computed from obtained rs-fMRI data. Multiple regression analysis was performed to assess the association of pre-pregnancy maternal body-mass-index (BMI) and ReHo. Seed-based connectivity analysis with multiple regression was subsequently performed with seed-ROI derived from ReHo analysis. Maternal adiposity measured by pre-pregnancy BMI was positively associated with neonate ReHo values within the left superior frontal gyrus (SFG) (FWE-corrected p < 0.005). Additionally, we found both positive and negative associations (p < 0.05, FWE-corrected) for maternal pre-pregnancy BMI and seed-based connectivity between left SFG and prefrontal, amygdalae, basal ganglia and insular regions. Our results imply that maternal pre-pregnancy BMI associates with local and distal functional connectivity within the neonate left superior frontal gyrus. These findings add to the evidence that increased maternal pre-pregnancy BMI has a programming influence on the developing neonate brain functional networks.
Collapse
Affiliation(s)
- Olli Rajasilta
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.
| | - Suvi Häkkinen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Malin Björnsdotter
- Department of Psychiatry for Affective Disorders, Sahlgrenska University Hospital, Gothenburg, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Noora M Scheinin
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
| | - Satu J Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- Department of Pediatric Neurology, Turku University Hospital and University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland.,Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Institute of Clinical Medicine, University of Turku, Lemminkäisenkatu 2, 20520, Turku, Finland.,Department of Psychiatry, University of Turku and Turku University Hospital, Turku, Finland.,Department of Psychiatry, University of Oxford, UK (Sigrid Juselius Fellowship), Oxford, UK.,Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| |
Collapse
|
24
|
Poppe T, Willers Moore J, Arichi T. Individual focused studies of functional brain development in early human infancy. Curr Opin Behav Sci 2021. [DOI: 10.1016/j.cobeha.2021.04.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
|
25
|
Eyre M, Lim M. Check your immune privilege: Is there a role for the maternal immune system in the pathogenesis of childhood tics and obsessive-compulsive disorder? Brain Behav Immun 2021; 95:19-20. [PMID: 33794314 DOI: 10.1016/j.bbi.2021.03.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 03/27/2021] [Indexed: 10/21/2022] Open
Affiliation(s)
- Michael Eyre
- School of Biomedical Engineering & Imaging Sciences, King's College London, UK; Children's Neurosciences, Evelina London Children's Hospital at Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Ming Lim
- Children's Neurosciences, Evelina London Children's Hospital at Guy's and St Thomas' NHS Foundation Trust, London, UK; Department Women and Children's Health, School of Life Course Sciences (SoLCS), King's College London, UK
| |
Collapse
|
26
|
Liu J, Chen Y, Stephens R, Cornea E, Goldman B, Gilmore JH, Gao W. Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance. Cortex 2021; 138:165-177. [PMID: 33691225 PMCID: PMC8058274 DOI: 10.1016/j.cortex.2021.02.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 11/03/2020] [Accepted: 02/05/2021] [Indexed: 02/08/2023]
Abstract
The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.
Collapse
Affiliation(s)
- Janelle Liu
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Yuanyuan Chen
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Rebecca Stephens
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Barbara Goldman
- FPG Child Development Institute and Department of Psychology & Neuroscience, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
| | - Wei Gao
- Biomedical Imaging Research Institute, Department of Biomedical Sciences, and Imaging, Cedars-Sinai Medical Center, Los Angeles, CA, USA; David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
| |
Collapse
|
27
|
Nair A, Jalal R, Liu J, Tsang T, McDonald NM, Jackson L, Ponting C, Jeste SS, Bookheimer SY, Dapretto M. Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder. Cereb Cortex 2021; 31:4191-4205. [PMID: 33866373 DOI: 10.1093/cercor/bhab078] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 03/11/2021] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.
Collapse
Affiliation(s)
- Aarti Nair
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92354, USA
| | - Rhideeta Jalal
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Janelle Liu
- Interdepartmental Neuroscience Program, University of California, Los Angeles, CA 90095, USA
| | - Tawny Tsang
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Nicole M McDonald
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Lisa Jackson
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Carolyn Ponting
- Department of Psychology, University of California, Los Angeles, CA 90095, USA
| | - Shafali S Jeste
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA 90095, USA
| |
Collapse
|
28
|
Hiremath CS, Sagar KJV, Yamini BK, Girimaji AS, Kumar R, Sravanti SL, Padmanabha H, Vykunta Raju KN, Kishore MT, Jacob P, Saini J, Bharath RD, Seshadri SP, Kumar M. Emerging behavioral and neuroimaging biomarkers for early and accurate characterization of autism spectrum disorders: a systematic review. Transl Psychiatry 2021; 11:42. [PMID: 33441539 PMCID: PMC7806884 DOI: 10.1038/s41398-020-01178-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/19/2020] [Accepted: 12/01/2020] [Indexed: 01/29/2023] Open
Abstract
The possibility of early treatment and a better outcome is the direct product of early identification and characterization of any pathological condition. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in social communication, restricted, and repetitive patterns of behavior. In recent times, various tools and methods have been developed for the early identification and characterization of ASD features as early as 6 months of age. Thorough and exhaustive research has been done to identify biomarkers in ASD using noninvasive neuroimaging and various molecular methods. By employing advanced assessment tools such as MRI and behavioral assessment methods for accurate characterization of the ASD features and may facilitate pre-emptive interventional and targeted therapy programs. However, the application of advanced quantitative MRI methods is still confined to investigational/laboratory settings, and the clinical implication of these imaging methods in personalized medicine is still in infancy. Longitudinal research studies in neurodevelopmental disorders are the need of the hour for accurate characterization of brain-behavioral changes that could be monitored over a period of time. These findings would be more reliable and consistent with translating into the clinics. This review article aims to focus on the recent advancement of early biomarkers for the characterization of ASD features at a younger age using behavioral and quantitative MRI methods.
Collapse
Affiliation(s)
- Chandrakanta S Hiremath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Kommu John Vijay Sagar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - B K Yamini
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Akhila S Girimaji
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Raghavendra Kumar
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Sanivarapu Lakshmi Sravanti
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Hansashree Padmanabha
- Department of Neurology, National Institute of Mental Health and Neuroscience, Bengaluru, India
| | - K N Vykunta Raju
- Department of Pediatric Neurology, Indira Gandhi Institute of Child Health, Bengaluru, India
| | - M Thomas Kishore
- Department of Clinical Psychology, National Institute of Mental Health and Neuroscience, Bengaluru, India
| | - Preeti Jacob
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Jitender Saini
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Rose D Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Shekhar P Seshadri
- Department of Child and Adolescent Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India.
| |
Collapse
|
29
|
Emberti Gialloreti L, Enea R, Di Micco V, Di Giovanni D, Curatolo P. Clustering Analysis Supports the Detection of Biological Processes Related to Autism Spectrum Disorder. Genes (Basel) 2020; 11:genes11121476. [PMID: 33316975 PMCID: PMC7763205 DOI: 10.3390/genes11121476] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/27/2020] [Accepted: 12/07/2020] [Indexed: 12/27/2022] Open
Abstract
Genome sequencing has identified a large number of putative autism spectrum disorder (ASD) risk genes, revealing possible disrupted biological pathways; however, the genetic and environmental underpinnings of ASD remain mostly unanswered. The presented methodology aimed to identify genetically related clusters of ASD individuals. By using the VariCarta dataset, which contains data retrieved from 13,069 people with ASD, we compared patients pairwise to build “patient similarity matrices”. Hierarchical-agglomerative-clustering and heatmapping were performed, followed by enrichment analysis (EA). We analyzed whole-genome sequencing retrieved from 2062 individuals, and isolated 11,609 genetic variants shared by at least two people. The analysis yielded three clusters, composed, respectively, by 574 (27.8%), 507 (24.6%), and 650 (31.5%) individuals. Overall, 4187 variants (36.1%) were common to the three clusters. The EA revealed that the biological processes related to the shared genetic variants were mainly involved in neuron projection guidance and morphogenesis, cell junctions, synapse assembly, and in observational, imitative, and vocal learning. The study highlighted genetic networks, which were more frequent in a sample of people with ASD, compared to the overall population. We suggest that itemizing not only single variants, but also gene networks, might support ASD etiopathology research. Future work on larger databases will have to ascertain the reproducibility of this methodology.
Collapse
Affiliation(s)
- Leonardo Emberti Gialloreti
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy
- Correspondence:
| | - Roberto Enea
- IMME Research Centre, Via Giotto 43, 81100 Caserta, Italy;
| | - Valentina Di Micco
- Child Neurology and Psychiatry Unit, Systems Medicine Department, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy; (V.D.M.); (P.C.)
| | - Daniele Di Giovanni
- Department of Industrial Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy;
| | - Paolo Curatolo
- Child Neurology and Psychiatry Unit, Systems Medicine Department, University of Rome Tor Vergata, Via Montpellier 1, 00133 Rome, Italy; (V.D.M.); (P.C.)
| |
Collapse
|
30
|
Miron O, Delgado RE, Delgado CF, Simpson EA, Yu KH, Gutierrez A, Zeng G, Gerstenberger JN, Kohane IS. Prolonged Auditory Brainstem Response in Universal Hearing Screening of Newborns with Autism Spectrum Disorder. Autism Res 2020; 14:46-52. [PMID: 33140578 PMCID: PMC7894135 DOI: 10.1002/aur.2422] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 10/09/2020] [Accepted: 10/12/2020] [Indexed: 12/21/2022]
Abstract
Previous studies report prolonged auditory brainstem response (ABR) in children and adults with autism spectrum disorder (ASD). Despite its promise as a biomarker, it is unclear whether healthy newborns who later develop ASD also show ABR abnormalities. In the current study, we extracted ABR data on 139,154 newborns from their Universal Newborn Hearing Screening, including 321 newborns who were later diagnosed with ASD. We found that the ASD newborns had significant prolongations of their ABR phase and V‐negative latency compared with the non‐ASD newborns. Newborns in the ASD group also exhibited greater variance in their latencies compared to previous studies in older ASD samples, likely due in part to the low intensity of the ABR stimulus. These findings suggest that newborns display neurophysiological variation associated with ASD at birth. Future studies with higher‐intensity stimulus ABRs may allow more accurate predictions of ASD risk, which could augment the universal ABR test that currently screens millions of newborns worldwide. Lay Summary Children with autism spectrum disorder (ASD) have slow brain responses to sounds. We examined these brain responses from newborns' hearing tests and found that newborns who were later diagnosed with autism also had slower brain responses to sounds. Future studies might use these findings to better predict autism risk, with a hearing test that is already used on millions of newborns worldwide.
Collapse
Affiliation(s)
- Oren Miron
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Rafael E Delgado
- Intelligent Hearing Systems, Miami, Florida, USA.,Department of Biomedical Engineering, University of Miami, Coral Gables, Florida, USA
| | | | | | - Kun-Hsing Yu
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Anibal Gutierrez
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | - Guangyu Zeng
- Department of Psychology, University of Miami, Coral Gables, Florida, USA
| | | | - Isaac S Kohane
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
31
|
Neuroimaging Markers of Risk and Pathways to Resilience in Autism Spectrum Disorder. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 6:200-210. [PMID: 32839155 DOI: 10.1016/j.bpsc.2020.06.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 06/04/2020] [Accepted: 06/28/2020] [Indexed: 01/22/2023]
Abstract
Autism spectrum disorder is a complex, heterogeneous neurodevelopmental condition of largely unknown etiology. This heterogeneity of symptom presentation, combined with high rates of comorbidity with other developmental disorders and a lack of reliable biomarkers, makes diagnosing and evaluating life outcomes for individuals with autism spectrum disorder a challenge. We review the growing literature on neuroimaging-based biomarkers of risk for the development of autism and explore evidence for resilience in some autistic individuals. The current literature suggests that neuroimaging during early infancy, in combination with prebirth and early genetic studies, is a promising tool for identifying biomarkers of risk, while studies of gene expression and DNA methylation have provided some key insights into mechanisms of resilience. With genetics and the environment contributing to both risk for the development of autism spectrum disorder and conditions for resilience, additional studies are needed to understand how risk and resilience interact mechanistically, whereby factors of risk may engender conditions for adaptation. Future studies should prioritize longitudinal designs in global cohorts, with the involvement of the autism community as partners in research to help identify domains of functioning that hold value and importance to the community.
Collapse
|