1
|
Liloia D, Zamfira DA, Tanaka M, Manuello J, Crocetta A, Keller R, Cozzolino M, Duca S, Cauda F, Costa T. Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research. Neurosci Biobehav Rev 2024; 164:105791. [PMID: 38960075 DOI: 10.1016/j.neubiorev.2024.105791] [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: 10/26/2023] [Revised: 05/22/2024] [Accepted: 06/27/2024] [Indexed: 07/05/2024]
Abstract
Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.
Collapse
Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Denisa Adina Zamfira
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Masaru Tanaka
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged (HUN-REN-SZTE), Danube Neuroscience Research Laboratory, Szeged, Hungary
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Annachiara Crocetta
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Mauro Cozzolino
- Department of Humanities, Philosophical and Educational Sciences, University of Salerno, Fisciano, Italy
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), Turin, Italy
| |
Collapse
|
2
|
Pavlinek A, Adhya D, Tsompanidis A, Warrier V, Vernon AC, Lancaster M, Mill J, Srivastava DP, Baron-Cohen S. Using Organoids to Model Sex Differences in the Human Brain. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100343. [PMID: 39092139 PMCID: PMC11292257 DOI: 10.1016/j.bpsgos.2024.100343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 05/08/2024] [Accepted: 05/14/2024] [Indexed: 08/04/2024] Open
Abstract
Sex differences are widespread during neurodevelopment and play a role in neuropsychiatric conditions such as autism, which is more prevalent in males than females. In humans, males have been shown to have larger brain volumes than females with development of the hippocampus and amygdala showing prominent sex differences. Mechanistically, sex steroids and sex chromosomes drive these differences in brain development, which seem to peak during prenatal and pubertal stages. Animal models have played a crucial role in understanding sex differences, but the study of human sex differences requires an experimental model that can recapitulate complex genetic traits. To fill this gap, human induced pluripotent stem cell-derived brain organoids are now being used to study how complex genetic traits influence prenatal brain development. For example, brain organoids from individuals with autism and individuals with X chromosome-linked Rett syndrome and fragile X syndrome have revealed prenatal differences in cell proliferation, a measure of brain volume differences, and excitatory-inhibitory imbalances. Brain organoids have also revealed increased neurogenesis of excitatory neurons due to androgens. However, despite growing interest in using brain organoids, several key challenges remain that affect its validity as a model system. In this review, we discuss how sex steroids and the sex chromosomes each contribute to sex differences in brain development. Then, we examine the role of X chromosome inactivation as a factor that drives sex differences. Finally, we discuss the combined challenges of modeling X chromosome inactivation and limitations of brain organoids that need to be taken into consideration when studying sex differences.
Collapse
Affiliation(s)
- Adam Pavlinek
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Dwaipayan Adhya
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
| | - Alex Tsompanidis
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Anthony C. Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | | | - Jonathan Mill
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
| | - Deepak P. Srivastava
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
3
|
Li M, Izumoto M, Wang Y, Kato Y, Iwatani Y, Hirata I, Mizuno Y, Tachibana M, Mohri I, Kagitani-Shimono K. Altered white matter connectivity of ventral language networks in autism spectrum disorder: An automated fiber quantification analysis with multi-site datasets. Neuroimage 2024; 297:120731. [PMID: 39002786 DOI: 10.1016/j.neuroimage.2024.120731] [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: 02/27/2024] [Revised: 06/28/2024] [Accepted: 07/11/2024] [Indexed: 07/15/2024] Open
Abstract
Comprehension and pragmatic deficits are prevalent in autism spectrum disorder (ASD) and are potentially linked to altered connectivity in the ventral language networks. However, previous magnetic resonance imaging studies have not sufficiently explored the microstructural abnormalities in the ventral fiber tracts underlying comprehension dysfunction in ASD. Additionally, the precise locations of white matter (WM) changes in the long tracts of patients with ASD remain poorly understood. In the current study, we applied the automated fiber-tract quantification (AFQ) method to investigate the fine-grained WM properties of the ventral language pathway and their relationships with comprehension and symptom manifestation in ASD. The analysis included diffusion/T1 weighted imaging data of 83 individuals with ASD and 83 age-matched typically developing (TD) controls. Case-control comparisons were performed on the diffusion metrics of the ventral tracts at both the global and point-wise levels. We also explored correlations between diffusion metrics, comprehension performance, and ASD traits, and conducted subgroup analyses based on age range to examine developmental moderating effects. Individuals with ASD exhibited remarkable hypoconnectivity in the ventral tracts, particularly in the temporal portions of the left inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF). These WM abnormalities were associated with poor comprehension and more severe ASD symptoms. Furthermore, WM alterations in the ventral tract and their correlation with comprehension dysfunction were more prominent in younger children with ASD than in adolescents. These findings indicate that WM disruptions in the temporal portions of the left ILF/IFOF are most notable in ASD, potentially constituting the core neurological underpinnings of comprehension and communication deficits in autism. Moreover, impaired WM connectivity and comprehension ability in patients with ASD appear to improve with age.
Collapse
Affiliation(s)
- Min Li
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Maya Izumoto
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yide Wang
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoko Kato
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshiko Iwatani
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Hirata
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Yoshifumi Mizuno
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
| | - Masaya Tachibana
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Ikuko Mohri
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan
| | - Kuriko Kagitani-Shimono
- Osaka University, Department of Child Development, United Graduate School of Child Development, Suita, Osaka, Japan.
| |
Collapse
|
4
|
Mohammad S, Gentreau M, Dubol M, Rukh G, Mwinyi J, Schiöth HB. Association of polygenic scores for autism with volumetric MRI phenotypes in cerebellum and brainstem in adults. Mol Autism 2024; 15:34. [PMID: 39113134 PMCID: PMC11304666 DOI: 10.1186/s13229-024-00611-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Accepted: 07/22/2024] [Indexed: 08/10/2024] Open
Abstract
Previous research on autism spectrum disorders (ASD) have showed important volumetric alterations in the cerebellum and brainstem. Most of these studies are however limited to case-control studies with small clinical samples and including mainly children or adolescents. Herein, we aimed to explore the association between the cumulative genetic load (polygenic risk score, PRS) for ASD and volumetric alterations in the cerebellum and brainstem, as well as global brain tissue volumes of the brain among adults at the population level. We utilized the latest genome-wide association study of ASD by the Psychiatric Genetics Consortium (18,381 cases, 27,969 controls) and constructed the ASD PRS in an independent cohort, the UK Biobank. Regression analyses controlled for multiple comparisons with the false-discovery rate (FDR) at 5% were performed to investigate the association between ASD PRS and forty-four brain magnetic resonance imaging (MRI) phenotypes among ~ 31,000 participants. Primary analyses included sixteen MRI phenotypes: total volumes of the brain, cerebrospinal fluid (CSF), grey matter (GM), white matter (WM), GM of whole cerebellum, brainstem, and ten regions of the cerebellum (I_IV, V, VI, VIIb, VIIIa, VIIIb, IX, X, CrusI and CrusII). Secondary analyses included twenty-eight MRI phenotypes: the sub-regional volumes of cerebellum including the GM of the vermis and both left and right lobules of each cerebellar region. ASD PRS were significantly associated with the volumes of seven brain areas, whereby higher PRS were associated to reduced volumes of the whole brain, WM, brainstem, and cerebellar regions I-IV, IX, and X, and an increased volume of the CSF. Three sub-regional volumes including the left cerebellar lobule I-IV, cerebellar vermes VIIIb, and X were significantly and negatively associated with ASD PRS. The study highlights a substantial connection between susceptibility to ASD, its underlying genetic etiology, and neuroanatomical alterations of the adult brain.
Collapse
Affiliation(s)
- Salahuddin Mohammad
- Functional Pharmacology and Neuroscience Unit, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Mélissa Gentreau
- Functional Pharmacology and Neuroscience Unit, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Manon Dubol
- Department of Women's and Children's Health, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Gull Rukh
- Functional Pharmacology and Neuroscience Unit, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Jessica Mwinyi
- Functional Pharmacology and Neuroscience Unit, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Helgi B Schiöth
- Functional Pharmacology and Neuroscience Unit, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
| |
Collapse
|
5
|
Zhao Z, Okada N, Yagishita S, Yahata N, Nitta N, Shibata S, Abe Y, Morita S, Kumagai E, Tanaka KF, Suhara T, Takumi T, Kasai K, Jinde S. Correlations of brain structure with the social behavior of 15q11-13 duplication mice, an animal model of autism. Neurosci Res 2024:S0168-0102(24)00100-7. [PMID: 39097003 DOI: 10.1016/j.neures.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 06/07/2024] [Accepted: 07/31/2024] [Indexed: 08/05/2024]
Abstract
Duplication of chromosome 15q11-13 has been reported to be one of the most frequent cytogenetic copy number variations in autism spectrum disorder (ASD), and a mouse model of paternal 15q11-13 duplication was generated, termed 15q dup mice. While previous studies have replicated some of the behavioral and brain structural phenotypes of ASD separately, the relationship between brain structure and behavior has rarely been examined. In this study, we performed behavioral experiments related to anxiety and social behaviors and magnetic resonance imaging (MRI) using the same set of 15q dup and wild-type mice. 15q dup mice showed increased anxiety and a tendency toward alterations in social behaviors, as reported previously, as well as variability in terms of sociability. MRI analysis revealed that a lower sociability index was correlated with a smaller gray matter volume in the right medial entorhinal cortex. These results may help to understand how variability in behavioral phenotypes of ASD arises even in individuals with the same genetic background and to determine the individual differences in neurodevelopmental trajectory correlated with specific brain structures that underlie these phenotypes.
Collapse
Affiliation(s)
- Zhilei Zhao
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan; International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan; International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Sho Yagishita
- International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan; Laboratory of Structural Physiology, Center for Disease Biology and Integrative Medicine, Faculty of Medicine, Faculty of Medicine Bldg, The University of Tokyo, 1 #NC207, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Noriaki Yahata
- National Institutes for Quantum Sciences and Technology, Anagawa 4-9-1, Inage-ku, Chiba 263-8555, Japan
| | - Nobuhiro Nitta
- National Institutes for Quantum Sciences and Technology, Anagawa 4-9-1, Inage-ku, Chiba 263-8555, Japan; Central Institute for Experimental Animals, 3-25-12 Tonomachi, Kawasaki Ward, Kawasaki, Kanagawa 210-0821, Japan
| | - Sayaka Shibata
- National Institutes for Quantum Sciences and Technology, Anagawa 4-9-1, Inage-ku, Chiba 263-8555, Japan
| | - Yoshifumi Abe
- Division of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo 160-8582, Japan
| | - Susumu Morita
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Eureka Kumagai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan
| | - Kenji F Tanaka
- Division of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo 160-8582, Japan
| | - Tetsuya Suhara
- National Institutes for Quantum Sciences and Technology, Anagawa 4-9-1, Inage-ku, Chiba 263-8555, Japan
| | - Toru Takumi
- Department of Physiology and Cell Biology, Kobe University School of Medicine, 7-5-1 Kusunoki-cho, Chuo, Kobe 650-0017, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan; International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Seiichiro Jinde
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo 113-8655, Japan.
| |
Collapse
|
6
|
Asad Z, Fakheir Y, Abukhaled Y, Khalil R. Implications of altered pyramidal cell morphology on clinical symptoms of neurodevelopmental disorders. Eur J Neurosci 2024. [PMID: 39054743 DOI: 10.1111/ejn.16484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/26/2024] [Accepted: 07/13/2024] [Indexed: 07/27/2024]
Abstract
The prevalence of pyramidal cells (PCs) in the mammalian cerebral cortex underscore their value as they play a crucial role in various brain functions, ranging from cognition, sensory processing, to motor output. PC morphology significantly influences brain connectivity and plays a critical role in maintaining normal brain function. Pathological alterations to PC morphology are thought to contribute to the aetiology of neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. This review explores the relationship between abnormalities in PC morphology in key cortical areas and the clinical manifestations in schizophrenia and ASD. We focus largely on human postmortem studies and provide evidence that dendritic segment length, complexity and spine density are differentially affected in these disorders. These morphological alterations can lead to disruptions in cortical connectivity, potentially contributing to the cognitive and behavioural deficits observed in these disorders. Furthermore, we highlight the importance of investigating the functional and structural characteristics of PCs in these disorders to illuminate the underlying pathogenesis and stimulate further research in this area.
Collapse
Affiliation(s)
- Zummar Asad
- School of Medicine, Royal College of Surgeons in Ireland (RCSI), Dublin, Ireland
| | - Yara Fakheir
- College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Yara Abukhaled
- College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Reem Khalil
- Department of Biology, Chemistry and Environmental Sciences, American University of Sharjah, Sharjah, United Arab Emirates
| |
Collapse
|
7
|
Yeung MK, Bai J, Mak KL. Longitudinal changes in executive function in autism spectrum disorder: A systematic review and meta-analyses. Autism Res 2024. [PMID: 38975618 DOI: 10.1002/aur.3196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 06/23/2024] [Indexed: 07/09/2024]
Abstract
Individuals with an autism spectrum disorder (ASD) diagnosis show impairment in executive function (EF). However, findings are mixed regarding differences in the age effect on EF between autistic individuals and persons with typical development (TD). Questions remain regarding whether the age-related trajectories of EF in ASD are the same as or different from those in TD. To bridge this knowledge gap, we conducted a systematic review and meta-analyses of longitudinal studies that compared age-related changes in EF between ASD and TD groups (preregistration: osf.io/j5764). A literature search was conducted using PubMed, PsycINFO, and Web of Science on January 29, 2024. After screening by two independent reviewers, 14 longitudinal studies were included. Random-effects meta-analyses of studies involving a maximum total of 518 autistic and 3558 TD children and adolescents (mean baseline ages: 5.7-12.0 years) showed that ASD had significantly poorer EF than TD at both baseline and follow-up. However, there was no significant group difference in the age-related change in EF across domains, including working memory, inhibition, shifting, and planning. Robust Bayesian meta-analyses also provided substantial evidence in favor of the null hypothesis that ASD and TD groups showed similar changes over time for most EF processes. Limitations of the literature included the limited number of longitudinal studies and a narrow range of developmental stages and EF constructs analyzed across studies. Altogether, these findings suggest that autistic children and adolescents generally can improve in EF over time similarly to their neurotypical peers. This has important implications for parents and educators, encouraging appropriate EF training and intervention for autistic children and adolescents at an early stage.
Collapse
Affiliation(s)
- Michael K Yeung
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
- University Research Facility of Human Behavioral Neuroscience, The Education University of Hong Kong, Hong Kong, China
| | - Jieru Bai
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - Kwai-Lai Mak
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| |
Collapse
|
8
|
Megari K, Frantzezou CK, Polyzopoulou ZA, Tzouni SK. Neurocognitive features in childhood & adulthood in autism spectrum disorder: A neurodiversity approach. Int J Dev Neurosci 2024. [PMID: 38953464 DOI: 10.1002/jdn.10356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 05/30/2024] [Accepted: 06/10/2024] [Indexed: 07/04/2024] Open
Abstract
OBJECTIVES Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a diverse profile of cognitive functions. Heterogeneity is observed among both baseline and comorbid features concerning the diversity of neuropathology in autism. Symptoms vary depending on the developmental stage, level of severity, or comorbidity with other medical or psychiatric diagnoses such as intellectual disability, epilepsy, and anxiety disorders. METHOD The neurodiversity movement does not face variations in neurological and cognitive development in ASD as deficits but as normal non-pathological human variations. Thus, ASD is not identified as a neurocognitive pathological disorder that deviates from the typical, but as a neuro-individuality, a normal manifestation of a neurobiological variation within the population. RESULTS In this light, neurodiversity is described as equivalent to any other human variation, such as ethnicity, gender, or sexual orientation. This review will provide insights about the neurodiversity approach in children and adults with ASD. Using a neurodiversity approach can be helpful when working with children who have autism spectrum disorder (ASD). DISCUSSION This method acknowledges and values the various ways that people with ASD interact with one another and experience the world in order to embrace the neurodiversity approach when working with children with ASD.
Collapse
Affiliation(s)
- Kalliopi Megari
- Department of Psychology, CITY College, University of York, Europe Campus, Thessaloniki, Greece
| | | | - Zoi A Polyzopoulou
- Department of Psychology, University of Western Macedonia, Florina, Greece
| | - Stella K Tzouni
- Department of Psychology, University of Western Macedonia, Florina, Greece
| |
Collapse
|
9
|
Saha P. Eigenvector Centrality Characterization on fMRI Data: Gender and Node Differences in Normal and ASD Subjects : Author name. J Autism Dev Disord 2024; 54:2757-2768. [PMID: 37142901 DOI: 10.1007/s10803-023-05922-x] [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] [Accepted: 02/05/2023] [Indexed: 05/06/2023]
Abstract
With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging (fMRI) offer region wise network representations through fMRI diagnostic maps. The article investigates the suitability of network node centrality values to discriminate ASD subject groups compared to typically developing controls following a boxplot formalism and a classification and regression tree model. Region wise differences between normal and ASD subjects primarily belong to the frontoparietal, limbic, ventral attention, default mode and visual networks. The reduced number of regions-of-interests (ROI) clearly suggests the benefit of automated supervised machine learning algorithm over the manual classification method.
Collapse
Affiliation(s)
- Papri Saha
- Department of Computer Science, Derozio Memorial College, Rajarhat Road, P.O. - R- Gopalpur, Kolkata, 700136, India.
| |
Collapse
|
10
|
Sun L, Zhao T, Liang X, Xia M, Li Q, Liao X, Gong G, Wang Q, Pang C, Yu Q, Bi Y, Chen P, Chen R, Chen Y, Chen T, Cheng J, Cheng Y, Cui Z, Dai Z, Deng Y, Ding Y, Dong Q, Duan D, Gao JH, Gong Q, Han Y, Han Z, Huang CC, Huang R, Huo R, Li L, Lin CP, Lin Q, Liu B, Liu C, Liu N, Liu Y, Liu Y, Lu J, Ma L, Men W, Qin S, Qiu J, Qiu S, Si T, Tan S, Tang Y, Tao S, Wang D, Wang F, Wang J, Wang P, Wang X, Wang Y, Wei D, Wu Y, Xie P, Xu X, Xu Y, Xu Z, Yang L, Yuan H, Zeng Z, Zhang H, Zhang X, Zhao G, Zheng Y, Zhong S, He Y. Functional connectome through the human life span. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.12.557193. [PMID: 37745373 PMCID: PMC10515818 DOI: 10.1101/2023.09.12.557193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimer's disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.
Collapse
Affiliation(s)
- Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Qian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chenxuan Pang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qian Yu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Pindong Chen
- Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Rui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, China
| | - Zhengjia Dai
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yao Deng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ruiwang Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ran Huo
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Lingjiang Li
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, China
- Department of Education and Research, Taipei City Hospital, Taipei, China
| | - Qixiang Lin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bangshan Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
- Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, China
| | - Chao Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Yong Liu
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Jing Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji’nan, China
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin University, Tianjin, China
| | - Xiaoqin Wang
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dongtao Wei
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Department of Psychology, Southwest University, Chongqing, China
| | - Yankun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, China
| | - Peng Xie
- Chongqing Key Laboratory of Neurobiology, Chongqing, China
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiufeng Xu
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuehua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Huishu Yuan
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Haibo Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yanting Zheng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Suyu Zhong
- Center for Artificial Intelligence in Medical Imaging, School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | | | | | | | | | | | | | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| |
Collapse
|
11
|
Xie X, Zhou R, Fang Z, Zhang Y, Wang Q, Liu X. Seeing beyond words: Visualizing autism spectrum disorder biomarker insights. Heliyon 2024; 10:e30420. [PMID: 38694128 PMCID: PMC11061761 DOI: 10.1016/j.heliyon.2024.e30420] [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: 10/07/2023] [Revised: 04/24/2024] [Accepted: 04/25/2024] [Indexed: 05/04/2024] Open
Abstract
Objective This study employs bibliometric and visual analysis to elucidate global research trends in Autism Spectrum Disorder (ASD) biomarkers, identify critical research focal points, and discuss the potential integration of diverse biomarker modalities for precise ASD assessment. Methods A comprehensive bibliometric analysis was conducted using data from the Web of Science Core Collection database until December 31, 2022. Visualization tools, including R, VOSviewer, CiteSpace, and gCLUTO, were utilized to examine collaborative networks, co-citation patterns, and keyword associations among countries, institutions, authors, journals, documents, and keywords. Results ASD biomarker research emerged in 2004, accumulating a corpus of 4348 documents by December 31, 2022. The United States, with 1574 publications and an H-index of 213, emerged as the most prolific and influential country. The University of California, Davis, contributed significantly with 346 publications and an H-index of 69, making it the leading institution. Concerning journals, the Journal of Autism and Developmental Disorders, Autism Research, and PLOS ONE were the top three publishers of ASD biomarker-related articles among a total of 1140 academic journals. Co-citation and keyword analyses revealed research hotspots in genetics, imaging, oxidative stress, neuroinflammation, gut microbiota, and eye tracking. Emerging topics included "DNA methylation," "eye tracking," "metabolomics," and "resting-state fMRI." Conclusion The field of ASD biomarker research is dynamically evolving. Future endeavors should prioritize individual stratification, methodological standardization, the harmonious integration of biomarker modalities, and longitudinal studies to advance the precision of ASD diagnosis and treatment.
Collapse
Affiliation(s)
- Xinyue Xie
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Rongyi Zhou
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Zihan Fang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Yongting Zhang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Qirong Wang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Xiaomian Liu
- Henan University of Chinese Medicine, School of Medicine, Zhengzhou, Henan, 450046, China
| |
Collapse
|
12
|
Wen J, Antoniades M, Yang Z, Hwang G, Skampardoni I, Wang R, Davatzikos C. Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning. Biol Psychiatry 2024:S0006-3223(24)01286-1. [PMID: 38718880 DOI: 10.1016/j.biopsych.2024.04.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/29/2024] [Accepted: 04/22/2024] [Indexed: 05/21/2024]
Abstract
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes with different brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal magnetic resonance imaging to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, and multiple sclerosis, as well as their potential in a transdiagnostic framework, where neuroanatomical and neurobiological commonalities were assessed across diagnostic boundaries. Subsequently, we summarize relevant machine learning methodologies and their clinical interpretability. We discuss the potential clinical implications of the current findings and envision future research avenues. Finally, we discuss an emerging paradigm called dimensional neuroimaging endophenotypes. Dimensional neuroimaging endophenotypes dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into low-dimensional yet informative, quantitative brain phenotypic representations, serving as robust intermediate phenotypes (i.e., endophenotypes), presumably reflecting the interplay of underlying genetic, lifestyle, and environmental processes associated with disease etiology.
Collapse
Affiliation(s)
- Junhao Wen
- Laboratory of AI and Biomedical Science, University of Southern California, Los Angeles, California.
| | - Mathilde Antoniades
- Artificial Intelligence in Biomedical Imaging Laboratory, Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zhijian Yang
- Artificial Intelligence in Biomedical Imaging Laboratory, Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Gyujoon Hwang
- Psychiatry and Behavioral Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Ioanna Skampardoni
- Artificial Intelligence in Biomedical Imaging Laboratory, Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Rongguang Wang
- Artificial Intelligence in Biomedical Imaging Laboratory, Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Christos Davatzikos
- Artificial Intelligence in Biomedical Imaging Laboratory, Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
| |
Collapse
|
13
|
Du L, Ye F, Gao W, Yang A, Luan J, Xu M, Lv K, Hu P, Liu B, Yu H, Wang Y, Huang W, Shu N, Ouyang G, Yin Q, Shmuel A, Wang Y, Zhang Q, Xu P, Ma G. Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder. Cereb Cortex 2024; 34:63-71. [PMID: 38696609 DOI: 10.1093/cercor/bhae081] [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: 10/30/2023] [Revised: 01/24/2024] [Accepted: 02/12/2024] [Indexed: 05/04/2024] Open
Abstract
To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.
Collapse
Affiliation(s)
- Lei Du
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, No. 52 Fucheng Road, Haidian, Beijing 100142, China
| | - Fang Ye
- Department of Pediatrics, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Wenwen Gao
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
- Department of Radiology, the Sixth Medical Center of People's Liberation Army (PLA) General Hospital, No. 6 Fucheng Road, Haidian, Beijing 100048, China
| | - Aocai Yang
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Jixin Luan
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Manxi Xu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Kuan Lv
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Pianpian Hu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Bing Liu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Hongwei Yu
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Yuli Wang
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Road, Haidian, Beijing 100875, China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Road, Haidian, Beijing 100875, China
| | - Gaoxiang Ouyang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Road, Haidian, Beijing 100875, China
| | - Qian Yin
- School of Artificial Intelligence, Beijing Normal University, No. 19 Xinjiekouwai Road, Haidian, Beijing 100875, China
| | - Amir Shmuel
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 45 Sherbrooke St W, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, Physiology, and Biomedical Engineering, McGill University, 45 Sherbrooke St W, Montreal, QC, Canada
| | - Yunfeng Wang
- Department of Pediatrics, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Qi Zhang
- Department of Pediatrics, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Pengfei Xu
- Department of Pediatrics, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| | - Guolin Ma
- Department of Radiology, China-Japan Friendship Hospital, No. 2 East Yinghua Road, Chaoyang, Beijing 100029, China
| |
Collapse
|
14
|
Lyu TJ, Ma J, Zhang XY, Xie GG, Liu C, Du J, Xu YN, Yang DC, Cen C, Wang MY, Lyu NY, Wang Y, Zhang HQ. Deficiency of FRMD5 results in neurodevelopmental dysfunction and autistic-like behavior in mice. Mol Psychiatry 2024; 29:1253-1264. [PMID: 38228891 DOI: 10.1038/s41380-024-02407-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 12/17/2023] [Accepted: 01/02/2024] [Indexed: 01/18/2024]
Abstract
The pathophysiology of autism spectrum disorders (ASDs) is causally linked to postsynaptic scaffolding proteins, as evidenced by numerous large-scale genomic studies [1, 2] and in vitro and in vivo neurobiological studies of mutations in animal models [3, 4]. However, due to the distinct phenotypic and genetic heterogeneity observed in ASD patients, individual mutation genes account for only a small proportion (<2%) of cases [1, 5]. Recently, a human genetic study revealed a correlation between de novo variants in FERM domain-containing-5 (FRMD5) and neurodevelopmental abnormalities [6]. In this study, we demonstrate that deficiency of the scaffolding protein FRMD5 leads to neurodevelopmental dysfunction and ASD-like behavior in mice. FRMD5 deficiency results in morphological abnormalities in neurons and synaptic dysfunction in mice. Frmd5-deficient mice display learning and memory dysfunction, impaired social function, and increased repetitive stereotyped behavior. Mechanistically, tandem mass tag (TMT)-labeled quantitative proteomics revealed that FRMD5 deletion affects the distribution of synaptic proteins involved in the pathological process of ASD. Collectively, our findings delineate the critical role of FRMD5 in neurodevelopment and ASD pathophysiology, suggesting potential therapeutic implications for the treatment of ASD.
Collapse
Affiliation(s)
- Tian-Jie Lyu
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Ji Ma
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China
| | - Xi-Yin Zhang
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Guo-Guang Xie
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Cheng Liu
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China
| | - Juan Du
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China
| | - Yi-Nuo Xu
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - De-Cao Yang
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China
| | - Cheng Cen
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Meng-Yuan Wang
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China
| | - Na-Yun Lyu
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China
| | - Yun Wang
- Neuroscience Research Institute and Department of Neurobiology, School of Basic Medical Sciences, Key Laboratory for Neuroscience, Ministry of Education/National Health Commission, National Health Commission and State Key Laboratory of Natural and Biomimetic Drugs, Peking University, 100191, Beijing, China.
- PKU-IDG/McGovern Institute for Brain Research, Peking University, 100871, Beijing, China.
| | - Hong-Quan Zhang
- Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, State Key Laboratory of Molecular Oncology and International Cancer Institute, Peking University Health Science Center, 100191, Beijing, China.
| |
Collapse
|
15
|
Bamford RA, Zuko A, Eve M, Sprengers JJ, Post H, Taggenbrock RLRE, Fäβler D, Mehr A, Jones OJR, Kudzinskas A, Gandawijaya J, Müller UC, Kas MJH, Burbach JPH, Oguro-Ando A. CNTN4 modulates neural elongation through interplay with APP. Open Biol 2024; 14:240018. [PMID: 38745463 PMCID: PMC11293442 DOI: 10.1098/rsob.240018] [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: 01/23/2024] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 05/16/2024] Open
Abstract
The neuronal cell adhesion molecule contactin-4 (CNTN4) is genetically associated with autism spectrum disorder (ASD) and other psychiatric disorders. Cntn4-deficient mouse models have previously shown that CNTN4 plays important roles in axon guidance and synaptic plasticity in the hippocampus. However, the pathogenesis and functional role of CNTN4 in the cortex has not yet been investigated. Our study found a reduction in cortical thickness in the motor cortex of Cntn4 -/- mice, but cortical cell migration and differentiation were unaffected. Significant morphological changes were observed in neurons in the M1 region of the motor cortex, indicating that CNTN4 is also involved in the morphology and spine density of neurons in the motor cortex. Furthermore, mass spectrometry analysis identified an interaction partner for CNTN4, confirming an interaction between CNTN4 and amyloid-precursor protein (APP). Knockout human cells for CNTN4 and/or APP revealed a relationship between CNTN4 and APP. This study demonstrates that CNTN4 contributes to cortical development and that binding and interplay with APP controls neural elongation. This is an important finding for understanding the physiological function of APP, a key protein for Alzheimer's disease. The binding between CNTN4 and APP, which is involved in neurodevelopment, is essential for healthy nerve outgrowth.
Collapse
Affiliation(s)
- Rosemary A. Bamford
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
| | - Amila Zuko
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, The Netherlands
| | - Madeline Eve
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
| | - Jan J. Sprengers
- Department of Translational Neuroscience, UMC Utrecht Brain Center, UMC Utrecht, Utrecht3508 AB, The Netherlands
| | - Harm Post
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht, Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
- Netherlands Proteomics Centre, Utrecht, The Netherlands
| | - Renske L. R. E. Taggenbrock
- Department of Translational Neuroscience, UMC Utrecht Brain Center, UMC Utrecht, Utrecht3508 AB, The Netherlands
| | - Dominique Fäβler
- Institute for Pharmacy and Molecular Biotechnology (IPMB), Functional Genomics, University of Heidelberg, Heidelberg69120, Germany
| | - Annika Mehr
- Institute for Pharmacy and Molecular Biotechnology (IPMB), Functional Genomics, University of Heidelberg, Heidelberg69120, Germany
| | - Owen J. R. Jones
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
| | - Aurimas Kudzinskas
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
| | - Josan Gandawijaya
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
| | - Ulrike C. Müller
- Institute for Pharmacy and Molecular Biotechnology (IPMB), Functional Genomics, University of Heidelberg, Heidelberg69120, Germany
| | - Martien J. H. Kas
- Department of Translational Neuroscience, UMC Utrecht Brain Center, UMC Utrecht, Utrecht3508 AB, The Netherlands
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands
| | - J. Peter H. Burbach
- Department of Translational Neuroscience, UMC Utrecht Brain Center, UMC Utrecht, Utrecht3508 AB, The Netherlands
| | - Asami Oguro-Ando
- University of Exeter Medical School, University of Exeter, ExeterEX2 5DW, UK
- Department of Pharmacy, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Noda, Chiba, Japan
- Research Institute for Science and Technology, Tokyo University of Science, Tokyo, Japan
| |
Collapse
|
16
|
Işıklar S, Sağlam D. Volumetric analysis of age- and sex-related changes in the corpus striatum and thalamus in the 1-18 age group: a retrospective magnetic resonance imaging study. Cereb Cortex 2024; 34:bhae142. [PMID: 38602741 DOI: 10.1093/cercor/bhae142] [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: 01/25/2024] [Revised: 03/16/2024] [Accepted: 03/17/2024] [Indexed: 04/12/2024] Open
Abstract
Studies of the development and asymmetry of the corpus striatum and thalamus in early childhood are rare. Studies investigating these structures across the lifespan have not presented their changes during childhood and adolescence in detail. For these reasons, this study investigated the effect of age and sex factors on the development and asymmetry of the corpus striatum and thalamus in the 1-18 age group. In this retrospective study, we included 652 individuals [362 (56%) males] aged 1-18 years with normal brain MRI between 2012 and 2021. Absolute and relative volumes of the corpus striatum and thalamus were obtained by segmentation of three-dimensional T1-weighted MRIs with volBrain1.0. We created age-specific volume data and month-based development models with the help of SPSS (ver.28). The corpus striatum and thalamus had cubic absolute volumetric developmental models. The relative volume of the caudate and thalamus (only males) is consistent with the decreasing "growth" model, the others with the decreasing cubic model. The absolute volumes of the males' bilateral corpus striatum and thalamus and the relative volumes of the caudate and thalamus of the females were significantly larger (P < 0.05). The caudate showed right > left lateralization; putamen, globus pallidus, and thalamus showed left > right lateralization.
Collapse
Affiliation(s)
- Sefa Işıklar
- Medical Imaging Techniques Program, Vocational School of Health Services, Bursa Uludag University, Bursa 16059, Turkey
| | - Dilek Sağlam
- Department of Radiology, Faculty of Medicine, Bursa Uludag University, Bursa 16059, Turkey
| |
Collapse
|
17
|
Friedel EBN, Tebartz van Elst L, Schäfer M, Maier S, Runge K, Küchlin S, Reich M, Lagrèze WA, Kornmeier J, Ebert D, Endres D, Domschke K, Nickel K. Retinal Thinning in Adults with Autism Spectrum Disorder. J Autism Dev Disord 2024; 54:1143-1156. [PMID: 36550331 PMCID: PMC10907434 DOI: 10.1007/s10803-022-05882-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
Since the retina shares its embryological origin with the central nervous system, optical coherence tomography (OCT), an imaging technique frequently employed in ophthalmology to analyze the macula and intraretinal layer thicknesses and volumes, has recently become increasingly important in psychiatric research. We examined 34 autistic and 31 neurotypical adults (NT) using OCT. Autistic adults had reduced overall macular and outer nuclear layer (ONL) thickness and volume compared to NT. Both macular and ONL thickness showed significant inverse associations with the severity of autistic symptoms measured with the Social Responsiveness Scale 2 (SRS-2). Longitudinal studies across different age groups are required to clarify whether retinal changes may represent a possible trait marker.
Collapse
Affiliation(s)
- Evelyn B N Friedel
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Eye Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Mirjam Schäfer
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Simon Maier
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Kimon Runge
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Sebastian Küchlin
- Eye Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michael Reich
- Eye Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Wolf A Lagrèze
- Eye Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Kornmeier
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Institute for Frontier Areas of Psychology and Mental Health, Freiburg, Germany
| | - Dieter Ebert
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dominique Endres
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Katharina Domschke
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Kathrin Nickel
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
| |
Collapse
|
18
|
Davidson TL, Stevenson RJ. Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction. Int J Mol Sci 2024; 25:1991. [PMID: 38396670 PMCID: PMC10888241 DOI: 10.3390/ijms25041991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 01/25/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.
Collapse
Affiliation(s)
- Terry L. Davidson
- Department of Neuroscience, Center for Neuroscience and Behavior, American University, 4400 Massachusetts Avenue, NW, Washington, DC 20016, USA
| | | |
Collapse
|
19
|
Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Li Q, Xu Z, Men W, Wang Y, Tan S, Gao JH, Qin S, Tao S, Dong Q, Zhao T, He Y. Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence. Nat Commun 2024; 15:784. [PMID: 38278807 PMCID: PMC10817914 DOI: 10.1038/s41467-024-44863-6] [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: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.
Collapse
Affiliation(s)
- Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
| |
Collapse
|
20
|
Quatrosi G, Genovese D, Galliano G, Zoppé H, Amodio E, Bonnet-Brilhault F, Tripi G. Cranio-Facial Characteristics in Autism Spectrum Disorder: A Scoping Review. J Clin Med 2024; 13:729. [PMID: 38337423 PMCID: PMC10856091 DOI: 10.3390/jcm13030729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024] Open
Abstract
Autism spectrum disorders (ASD) consist of a complex group of neurodevelopmental disorders characterised by qualitative impairments of social interactions, communication abilities, and a limited, stereotyped, and repetitive selection of interests and activities. In light of the imperative to identify a possible biomarker for ASD, it has been determined that craniofacial anomalies serve as significant risk factors for neurodevelopmental disorders. The aim of this scoping review is to deepen the knowledge of the scientific literature related to cranio-facial characteristics in individuals with ASD, with a particular focus on recent research advancements. The review was performed by employing the search strings (("Autism Spectrum Disorder" OR autism OR ASD OR "Autism Spectrum") AND ("facial morphology" OR "facial phenotype")) on the databases PubMed/MEDLINE, Scopus, and ERIC as of March 9, 2023. The review comprised seven studies whose findings were obtained through quantitative analysis of Euclidean distances between anatomical landmarks. The examination of facial abnormalities represents a possible reliable diagnostic biomarker that could aid in the timely identification of ASD. Phenotypic characteristics that may serve as predictive indicators of the severity of autistic symptoms can be observed in certain individuals with ASD by applying anthropometric and instrumental measurements. The presence of a phenotype characterised by an increased intercanthal distance and a reduced facial midline height appears to be associated with a higher degree of severity in autistic symptoms. In addition, it is worth noting that facial asymmetry and facial masculinity can be considered reliable indicators for predicting a more severe manifestation of symptoms.
Collapse
Affiliation(s)
- Giuseppe Quatrosi
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy;
| | - Dario Genovese
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Via del Vespro, 133, 90127 Palermo, Italy; (G.G.); (E.A.); (G.T.)
| | - Giuseppe Galliano
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Via del Vespro, 133, 90127 Palermo, Italy; (G.G.); (E.A.); (G.T.)
| | - Hugo Zoppé
- UMR 1253 iBrain, Inserm, Université de Tours, 37020 Tours, France; (H.Z.); (F.B.-B.)
- Excellence Center for Autism and Neurodevelopmental Disorders, CHRU de Tours, 37000 Tours, France
| | - Emanuele Amodio
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Via del Vespro, 133, 90127 Palermo, Italy; (G.G.); (E.A.); (G.T.)
| | - Fréderique Bonnet-Brilhault
- UMR 1253 iBrain, Inserm, Université de Tours, 37020 Tours, France; (H.Z.); (F.B.-B.)
- Excellence Center for Autism and Neurodevelopmental Disorders, CHRU de Tours, 37000 Tours, France
| | - Gabriele Tripi
- Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (PROMISE), University of Palermo, Via del Vespro, 133, 90127 Palermo, Italy; (G.G.); (E.A.); (G.T.)
- Department of Child and Adolescent Psychiatry, EPSM du Loiret/Centre Hospitalier Universitaire d’Orléans, Université d’Orléans, 45100 Orléans, France
| |
Collapse
|
21
|
Haaf R, Brandi ML, Albantakis L, Lahnakoski JM, Henco L, Schilbach L. Peripheral oxytocin levels are linked to hypothalamic gray matter volume in autistic adults: a cross-sectional secondary data analysis. Sci Rep 2024; 14:1380. [PMID: 38228703 PMCID: PMC10791615 DOI: 10.1038/s41598-023-50770-5] [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: 04/13/2023] [Accepted: 12/25/2023] [Indexed: 01/18/2024] Open
Abstract
Oxytocin (OXT) is known to modulate social behavior and cognition and has been discussed as pathophysiological and therapeutic factor for autism spectrum disorder (ASD). An accumulating body of evidence indicates the hypothalamus to be of particular importance with regard to the underlying neurobiology. Here we used a region of interest voxel-based morphometry (VBM) approach to investigate hypothalamic gray matter volume (GMV) in autistic (n = 29, age 36.03 ± 11.0) and non-autistic adults (n = 27, age 30.96 ± 11.2). Peripheral plasma OXT levels and the autism spectrum quotient (AQ) were used for correlation analyses. Results showed no differences in hypothalamic GMV in autistic compared to non-autistic adults but suggested a differential association between hypothalamic GMV and OXT levels, such that a positive association was found for the ASD group. In addition, hypothalamic GMV showed a positive association with autistic traits in the ASD group. Bearing in mind the limitations such as a relatively small sample size, a wide age range and a high rate of psychopharmacological treatment in the ASD sample, these results provide new preliminary evidence for a potentially important role of the HTH in ASD and its relationship to the OXT system, but also point towards the importance of interindividual differences.
Collapse
Affiliation(s)
- Raoul Haaf
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany.
- Graduate School, Technical University of Munich, Munich, Germany.
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany.
| | - Marie-Luise Brandi
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
| | - Laura Albantakis
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- Outpatient and Day Clinic for Disorders of Social Interaction, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Juha M Lahnakoski
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Neurosciences and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Lara Henco
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- Graduate School of Systemic Neurosciences, Munich, Germany
| | - Leonhard Schilbach
- Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
- Outpatient and Day Clinic for Disorders of Social Interaction, Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry, Munich, Germany
- Graduate School of Systemic Neurosciences, Munich, Germany
- Ludwig-Maximilians-Universität München, Munich, Germany
| |
Collapse
|
22
|
Gros G, Miranda Marcos R, Latrille A, Saitovitch A, Gollier-Briant F, Fossati P, Schmidt L, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Hohmann S, Holz N, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Lemaitre H, Vulser H. Whole-brain gray matter maturation trajectories associated with autistic traits from adolescence to early adulthood. Brain Struct Funct 2024; 229:15-29. [PMID: 37819410 PMCID: PMC10827811 DOI: 10.1007/s00429-023-02710-2] [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: 05/15/2023] [Accepted: 09/03/2023] [Indexed: 10/13/2023]
Abstract
A growing number of evidence supports a continued distribution of autistic traits in the general population. However, brain maturation trajectories of autistic traits as well as the influence of sex on these trajectories remain largely unknown. We investigated the association of autistic traits in the general population, with longitudinal gray matter (GM) maturation trajectories during the critical period of adolescence. We assessed 709 community-based adolescents (54.7% women) at age 14 and 22. After testing the effect of sex, we used whole-brain voxel-based morphometry to measure longitudinal GM volumes changes associated with autistic traits measured by the Social Responsiveness Scale (SRS) total and sub-scores. In women, we observed that the SRS was associated with slower GM volume decrease globally and in the left parahippocampus and middle temporal gyrus. The social communication sub-score correlated with slower GM volume decrease in the left parahippocampal, superior temporal gyrus, and pallidum; and the social cognition sub-score correlated with slower GM volume decrease in the left middle temporal gyrus, the right ventromedial prefrontal and orbitofrontal cortex. No longitudinal association was found in men. Autistic traits in young women were found to be associated with specific brain trajectories in regions of the social brain and the reward circuit known to be involved in Autism Spectrum Disorder. These findings support both the hypothesis of an earlier GM maturation associated with autistic traits in adolescence and of protective mechanisms in women. They advocate for further studies on brain trajectories associated with autistic traits in women.
Collapse
Affiliation(s)
- Guillaume Gros
- Control-Interoception-Attention Team, Hôpital Pitié-Salpêtrière Paris, Brain Institute, Inserm/CNRS/Sorbonne University, UMR 7225/U1127, Paris, France
- Department of Adult Psychiatry, Centre du Neurodéveloppement Adulte, AP-HP.Sorbonne Université, Pitié-Salpêtrière Hospital, 47-83 Boulevard de L'Hôpital, 75013, Paris, France
| | - Ruben Miranda Marcos
- Control-Interoception-Attention Team, Hôpital Pitié-Salpêtrière Paris, Brain Institute, Inserm/CNRS/Sorbonne University, UMR 7225/U1127, Paris, France
- Department of Adult Psychiatry, Centre du Neurodéveloppement Adulte, AP-HP.Sorbonne Université, Pitié-Salpêtrière Hospital, 47-83 Boulevard de L'Hôpital, 75013, Paris, France
| | - Anthony Latrille
- Institut Des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, 33076, Bordeaux, France
| | - Ana Saitovitch
- Department of Pediatric Radiology, Necker-Enfants Malades Hospital, AP-HP, Université Paris Cité, Imagine Institute, INSERM U1299, UMR 1163, Paris, France
| | - Fanny Gollier-Briant
- Unité Diagnostique Autisme Ados-Jeunes Adultes (UD3A), CHU and Universite de Nantes, Fondation FondaMental, Nantes, Créteil, France
| | - Philippe Fossati
- Control-Interoception-Attention Team, Hôpital Pitié-Salpêtrière Paris, Brain Institute, Inserm/CNRS/Sorbonne University, UMR 7225/U1127, Paris, France
- Department of Adult Psychiatry, Centre du Neurodéveloppement Adulte, AP-HP.Sorbonne Université, Pitié-Salpêtrière Hospital, 47-83 Boulevard de L'Hôpital, 75013, Paris, France
| | - Liane Schmidt
- Control-Interoception-Attention Team, Hôpital Pitié-Salpêtrière Paris, Brain Institute, Inserm/CNRS/Sorbonne University, UMR 7225/U1127, Paris, France
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-Sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM U 1299 "Trajectoires Développementales and Psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-Sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM U 1299 "Trajectoires Développementales and Psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-Sur-Yvette, France
- Department of Child and Adolescent Psychiatry, AP-HP. Sorbonne University, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de La Santé Et de La Recherche Médicale, INSERM U 1299 "Trajectoires Développementales and Psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-Sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Hervé Lemaitre
- Institut Des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, 33076, Bordeaux, France
| | - Hélène Vulser
- Control-Interoception-Attention Team, Hôpital Pitié-Salpêtrière Paris, Brain Institute, Inserm/CNRS/Sorbonne University, UMR 7225/U1127, Paris, France.
- Department of Adult Psychiatry, Centre du Neurodéveloppement Adulte, AP-HP.Sorbonne Université, Pitié-Salpêtrière Hospital, 47-83 Boulevard de L'Hôpital, 75013, Paris, France.
| |
Collapse
|
23
|
Xiaoyan H, Zhaoxi Y, Lingli Z, Jinyuan C, Wen Q. Taurine Improved Autism-Like Behaviours and Defective Neurogenesis of the Hippocampus in BTBR Mice through the PTEN/mTOR/AKT Signalling Pathway. Folia Biol (Praha) 2024; 70:45-52. [PMID: 38830122 DOI: 10.14712/fb2024070010045] [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] [Indexed: 06/05/2024]
Abstract
Effective treatment of patients with autism spectrum disorder (ASD) is still absent so far. Taurine exhibits therapeutic effects towards the autism-like behaviour in ASD model animals. Here, we determined the mechanism of taurine effect on hippocampal neurogenesis in genetically inbred BTBR T+ tf/J (BTBR) mice, a proposed model of ASD. In this ASD mouse model, we explored the effect of oral taurine supplementation on ASD-like behaviours in an open field test, elevated plus maze, marble burying test, self-grooming test, and three-chamber test. The mice were divided into four groups of normal controls (WT) and models (BTBR), who did or did not receive 6-week taurine supplementation in water (WT, WT+ Taurine, BTBR, and BTBR+Taurine). Neurogenesis-related effects were determined by Ki67 immunofluorescence staining. Western blot analysis was performed to detect the expression of phosphatase and tensin homologue deleted from chromosome 10 (PTEN)/mTOR/AKT pathway-associated proteins. Our results showed that taurine improved the autism-like behaviour, increased the proliferation of hippocampal cells, promoted PTEN expression, and reduced phosphorylation of mTOR and AKT in hippocampal tissue of the BTBR mice. In conclusion, taurine reduced the autism-like behaviour in partially inherited autism model mice, which may be associa-ted with improving the defective neural precursor cell proliferation and enhancing the PTEN-associated pathway in hippocampal tissue.
Collapse
Affiliation(s)
- Huang Xiaoyan
- Department of Child Health, Shenzhen Guangming Women and Child Healthcare Hospital, Shenzhen, China.
| | - Yang Zhaoxi
- Department of Child Health, Shenzhen Guangming Women and Child Healthcare Hospital, Shenzhen, China
| | - Zhang Lingli
- Department of Child Health, Shenzhen Guangming Women and Child Healthcare Hospital, Shenzhen, China
| | - Chen Jinyuan
- Department of Child Health, Shenzhen Guangming Women and Child Healthcare Hospital, Shenzhen, China
| | - Qin Wen
- Department of Child Health, Shenzhen Guangming Women and Child Healthcare Hospital, Shenzhen, China
| |
Collapse
|
24
|
Shen L, Zhang J, Fan S, Ping L, Yu H, Xu F, Cheng Y, Xu X, Yang C, Zhou C. Cortical thickness abnormalities in autism spectrum disorder. Eur Child Adolesc Psychiatry 2024; 33:65-77. [PMID: 36542200 DOI: 10.1007/s00787-022-02133-0] [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] [Received: 09/22/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022]
Abstract
The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.
Collapse
Affiliation(s)
- Liancheng Shen
- Department of Psychiatry, Shandong Daizhuang Hospital, Jining, China
| | - Junqing Zhang
- Department of Pharmacy, Shandong Daizhuang Hospital, Jining, China
| | - Shiran Fan
- School of Mental Health, Jining Medical University, Jining, China
| | - Liangliang Ping
- Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, China
| | - Hao Yu
- School of Mental Health, Jining Medical University, Jining, China
| | - Fangfang Xu
- School of Mental Health, Jining Medical University, Jining, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Chunyan Yang
- School of Rehabilitation Medicine, Jining Medical University, Jining, China.
| | - Cong Zhou
- School of Mental Health, Jining Medical University, Jining, China.
- Department of Psychology, Affiliated Hospital of Jining Medical University, Jining, China.
| |
Collapse
|
25
|
Lu H, Wang S, Xue Z, Liu J, Niu X, Gao L, Guo X. Decreased functional concordance in male children with autism spectrum disorder. Autism Res 2023; 16:2263-2274. [PMID: 37787080 DOI: 10.1002/aur.3035] [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: 04/03/2023] [Accepted: 09/10/2023] [Indexed: 10/04/2023]
Abstract
Autism spectrum disorder (ASD) is an early-onset neurodevelopmental condition with altered function of the brain. At present, a variety of functional metrics from neuroimaging techniques have been used to explore ASD neurological mechanisms. However, the concordance of these functional metrics in ASD is still unclear. This study used resting-state functional magnetic resonance imaging data, which were obtained from the open-access Autism Brain Imaging Data Exchange database, including 105 children with ASD and 102 demographically matched typically developing (TD) children. Both voxel-wise and volume-wise functional concordance were calculated by combining the dynamic amplitude of low-frequency fluctuations, dynamic regional homogeneity, and dynamic global signal correlation. Furthermore, a two-sample t-test was performed to compare the functional concordance between ASD and TD groups. Finally, the relationship between voxel-wise functional concordance and Autism Diagnostic Observation Schedule subscores was analyzed using the multivariate support vector regression in the ASD group. Compared with the TD group, we found that ASD showed decreased voxel-wise functional concordance in the left superior temporal pole (STGp), right amygdala, and left opercular part of the inferior frontal gyrus (IFGoper). Moreover, decreased functional concordance was associated with restricted and repetitive behaviors in ASD. Our results found altered brain function in the left STGp, right amygdala, and left IFGoper in ASD by functional concordance, indicating that functional concordance may provide new insights into the neurological mechanisms of ASD.
Collapse
Affiliation(s)
- Huibin Lu
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Sha Wang
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Zaifa Xue
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Jing Liu
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Xiaoxia Niu
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Le Gao
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| |
Collapse
|
26
|
Weber CF, Lake EMR, Haider SP, Mozayan A, Bobba PS, Mukherjee P, Scheinost D, Constable RT, Ment L, Payabvash S. Autism spectrum disorder-specific changes in white matter connectome edge density based on functionally defined nodes. Front Neurosci 2023; 17:1285396. [PMID: 38075286 PMCID: PMC10702224 DOI: 10.3389/fnins.2023.1285396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 10/30/2023] [Indexed: 02/12/2024] Open
Abstract
Introduction Autism spectrum disorder (ASD) is associated with both functional and microstructural connectome disruptions. We deployed a novel methodology using functionally defined nodes to guide white matter (WM) tractography and identify ASD-related microstructural connectome changes across the lifespan. Methods We used diffusion tensor imaging and clinical data from four studies in the national database for autism research (NDAR) including 155 infants, 102 toddlers, 230 adolescents, and 96 young adults - of whom 264 (45%) were diagnosed with ASD. We applied cortical nodes from a prior fMRI study identifying regions related to symptom severity scores and used these seeds to construct WM fiber tracts as connectome Edge Density (ED) maps. Resulting ED maps were assessed for between-group differences using voxel-wise and tract-based analysis. We then examined the association of ASD diagnosis with ED driven from functional nodes generated from different sensitivity thresholds. Results In ED derived from functionally guided tractography, we identified ASD-related changes in infants (pFDR ≤ 0.001-0.483). Overall, more wide-spread ASD-related differences were detectable in ED based on functional nodes with positive symptom correlation than negative correlation to ASD, and stricter thresholds for functional nodes resulted in stronger correlation with ASD among infants (z = -6.413 to 6.666, pFDR ≤ 0.001-0.968). Voxel-wise analysis revealed wide-spread ED reductions in central WM tracts of toddlers, adolescents, and adults. Discussion We detected early changes of aberrant WM development in infants developing ASD when generating microstructural connectome ED map with cortical nodes defined by functional imaging. These were not evident when applying structurally defined nodes, suggesting that functionally guided DTI-based tractography can help identify early ASD-related WM disruptions between cortical regions exhibiting abnormal connectivity patterns later in life. Furthermore, our results suggest a benefit of involving functionally informed nodes in diffusion imaging-based probabilistic tractography, and underline that different age cohorts can benefit from age- and brain development-adapted image processing protocols.
Collapse
Affiliation(s)
- Clara F Weber
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
- Social Neuroscience Lab, Department of Psychiatry and Psychotherapy, Lübeck University, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), Lübeck University, Lübeck, Germany
| | - Evelyn M R Lake
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| | - Stefan P Haider
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
- Department of Otorhinolaryngology, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Ali Mozayan
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| | - Pratheek S Bobba
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Dustin Scheinost
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| | - Robert T Constable
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| | - Laura Ment
- Yale University School of Medicine, Department of Pediatrics and Neurology, New Haven, CT, United States
| | - Seyedmehdi Payabvash
- Yale University School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, United States
| |
Collapse
|
27
|
Walter C, Balouchzadeh R, Garcia KE, Kroenke CD, Pathak A, Bayly PV. Multi-scale measurement of stiffness in the developing ferret brain. Sci Rep 2023; 13:20583. [PMID: 37996465 PMCID: PMC10667369 DOI: 10.1038/s41598-023-47900-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 11/20/2023] [Indexed: 11/25/2023] Open
Abstract
Cortical folding is an important process during brain development, and aberrant folding is linked to disorders such as autism and schizophrenia. Changes in cell numbers, size, and morphology have been proposed to exert forces that control the folding process, but these changes may also influence the mechanical properties of developing brain tissue. Currently, the changes in tissue stiffness during brain folding are unknown. Here, we report stiffness in the developing ferret brain across multiple length scales, emphasizing changes in folding cortical tissue. Using rheometry to measure the bulk properties of brain tissue, we found that overall brain stiffness increases with age over the period of cortical folding. Using atomic force microscopy to target the cortical plate, we found that the occipital cortex increases in stiffness as well as stiffness heterogeneity over the course of development and folding. These findings can help to elucidate the mechanics of the cortical folding process by clarifying the concurrent evolution of tissue properties.
Collapse
Affiliation(s)
- Christopher Walter
- Mechanical Engineering and Materials Science, Washington University, St. Louis, USA.
| | - Ramin Balouchzadeh
- Mechanical Engineering and Materials Science, Washington University, St. Louis, USA
| | - Kara E Garcia
- Radiology and Imaging Sciences, Indiana University School of Medicine, Evansville, IN, USA
| | - Christopher D Kroenke
- Advanced Imaging Research Center and Oregon National Primate Research Center Division of Neuroscience, Oregon Health and Science University, Portland, OR, USA
| | - Amit Pathak
- Mechanical Engineering and Materials Science, Washington University, St. Louis, USA
| | - Philip V Bayly
- Mechanical Engineering and Materials Science, Washington University, St. Louis, USA.
| |
Collapse
|
28
|
Razzak R, Li J, He S, Sokhadze E. Investigating Sex-Based Neural Differences in Autism and Their Extended Reality Intervention Implications. Brain Sci 2023; 13:1571. [PMID: 38002531 PMCID: PMC10670246 DOI: 10.3390/brainsci13111571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 10/27/2023] [Accepted: 11/02/2023] [Indexed: 11/26/2023] Open
Abstract
Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, and there is growing interest in the use of extended reality (XR) technologies for intervention. Despite the promising potential of XR interventions, there remain gaps in our understanding of the neurobiological mechanisms underlying ASD, particularly in relation to sex-based differences. This scoping review synthesizes the current research on brain activity patterns in ASD, emphasizing the implications for XR interventions and neurofeedback therapy. We examine the brain regions commonly affected by ASD, the potential benefits and drawbacks of XR technologies, and the implications of sex-specific differences for designing effective interventions. Our findings underscore the need for ongoing research into the neurobiological underpinnings of ASD and sex-based differences, as well as the importance of developing tailored interventions that consider the unique needs and experiences of autistic individuals.
Collapse
Affiliation(s)
- Rehma Razzak
- Department of Computer Science, Kennesaw State University, Marietta, GA 30060, USA; (R.R.); (S.H.)
| | - Joy Li
- Department of Software Engineering and Game Development, Kennesaw State University, Marietta, GA 30060, USA;
| | - Selena He
- Department of Computer Science, Kennesaw State University, Marietta, GA 30060, USA; (R.R.); (S.H.)
| | - Estate Sokhadze
- Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| |
Collapse
|
29
|
Mei T, Forde NJ, Floris DL, Dell'Acqua F, Stones R, Ilioska I, Durston S, Moessnang C, Banaschewski T, Holt RJ, Baron-Cohen S, Rausch A, Loth E, Oakley B, Charman T, Ecker C, Murphy DGM, Beckmann CF, Llera A, Buitelaar JK. Autism Is Associated With Interindividual Variations of Gray and White Matter Morphology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1084-1093. [PMID: 36075529 DOI: 10.1016/j.bpsc.2022.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 08/06/2022] [Accepted: 08/24/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. METHODS We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6-30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions-A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants' GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. RESULTS One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. CONCLUSIONS Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.
Collapse
Affiliation(s)
- Ting Mei
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
| | - Natalie J Forde
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands; Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Flavio Dell'Acqua
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Richard Stones
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Iva Ilioska
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Sarah Durston
- University Medical Center Utrecht, Utrecht, the Netherlands
| | - Carolin Moessnang
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; Department of Applied Psychology, SRH University, Heidelberg, Germany
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rosemary J Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Annika Rausch
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Declan G M Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands; Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom
| | - Alberto Llera
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands.
| |
Collapse
|
30
|
Liloia D, Cauda F, Uddin LQ, Manuello J, Mancuso L, Keller R, Nani A, Costa T. Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1075-1083. [PMID: 35131520 DOI: 10.1016/j.bpsc.2022.01.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 12/30/2021] [Accepted: 01/24/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies. METHODS Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD. RESULTS We found that specific brain areas exhibit a >90% probability of gray matter alteration selectivity for ASD: the bilateral precuneus (Brodmann area 7), right inferior occipital gyrus (Brodmann area 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network. CONCLUSIONS The identification of these spatial gray matter alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD and opens attractive prospects for future neuroimaging-based interventions.
Collapse
Affiliation(s)
- Donato Liloia
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Franco Cauda
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy
| | - Lucina Q Uddin
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California
| | - Jordi Manuello
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Roberto Keller
- Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy
| | - Andrea Nani
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy
| |
Collapse
|
31
|
Berg LM, Gurr C, Leyhausen J, Seelemeyer H, Bletsch A, Schaefer T, Pretzsch CM, Oakley B, Loth E, Floris DL, Buitelaar JK, Beckmann CF, Banaschewski T, Charman T, Jones EJH, Tillmann J, Chatham CH, Bourgeron T, Murphy DG, Ecker C. The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings. Mol Autism 2023; 14:36. [PMID: 37794485 PMCID: PMC10552404 DOI: 10.1186/s13229-023-00568-z] [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] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 09/19/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings. METHODS We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings. RESULTS In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD-but not for ADHD-related genes. LIMITATIONS Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting. CONCLUSION Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.
Collapse
Affiliation(s)
- Lisa M Berg
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany.
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany.
- Department of Biosciences, Goethe University Frankfurt, 60438, Frankfurt am Main, Germany.
| | - Caroline Gurr
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany
| | - Johanna Leyhausen
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany
- Department of Biosciences, Goethe University Frankfurt, 60438, Frankfurt am Main, Germany
| | - Hanna Seelemeyer
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany
| | - Anke Bletsch
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany
| | - Tim Schaefer
- Fries Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt, Germany
| | - Charlotte M Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, SE5 8AF, UK
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, SE5 8AF, UK
| | - Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, SE5 8AF, UK
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Tobias Banaschewski
- Child and Adolescent Psychiatry, Medical Faculty Mannheim, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Emily J H Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, Malet Street, London, WC1E 7JL, UK
| | - Julian Tillmann
- F. Hoffmann-La Roche, Innovation Center Basel, Basel, Switzerland
| | - Chris H Chatham
- F. Hoffmann-La Roche, Innovation Center Basel, Basel, Switzerland
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France
| | - Declan G Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, SE5 8AF, UK
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Deutschordenstrasse 50, 60528, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University, 60528, Frankfurt am Main, Germany
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, SE5 8AF, UK
| |
Collapse
|
32
|
Wang M, Xu D, Zhang L, Jiang H. Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review. Diagnostics (Basel) 2023; 13:3027. [PMID: 37835770 PMCID: PMC10571992 DOI: 10.3390/diagnostics13193027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.
Collapse
Affiliation(s)
- Miaoyan Wang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Dandan Xu
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Lili Zhang
- Department of Child Health Care, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China
| | - Haoxiang Jiang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| |
Collapse
|
33
|
de Jong JR, Dijkerman HC, Keizer A. Autistic Traits Related to the Importance of Interpersonal Touch and Appreciation of Observed Touch during COVID-19 Social Distancing. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6738. [PMID: 37754599 PMCID: PMC10531349 DOI: 10.3390/ijerph20186738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2023] [Revised: 09/04/2023] [Accepted: 09/07/2023] [Indexed: 09/28/2023]
Abstract
Studies have confirmed the significance of touch for psychological wellbeing. Social distancing regulations during the COVID-19 pandemic reduced people's ability to engage in interpersonal touch and caused increased an appreciation for observed touch, as well as a longing for touch within the neurotypical population. Yet, while the impact of social distancing and the importance of touch are evident in neurotypical individuals, it remains unclear how these factors manifest in autistic individuals. Previous research has related high levels of autistic traits to reduced levels of perceived pleasantness of touch and a reduced interest in interpersonal touch. Our study aimed to examine the differences in the appreciation of observed touch and longing for touch during social distancing between individuals with low and high levels of autistic traits. We conducted an online survey on autistic traits, the appreciation of observed CT-optimal touch and longing for touch. Consistent with our predictions, our results confirmed that individuals with high levels of autistic traits evaluated videos depicting CT-optimal touch less favorably compared to those with lower scores on autistic traits. Additionally, only the group with low levels of autistic traits exhibited a longing for touch during social distancing, whereas the group with high levels of autistic traits did not. The results provide insights in the appreciation of touch in relation to autistic traits during the unique circumstances of the COVID-19 pandemic.
Collapse
Affiliation(s)
- Jutta R. de Jong
- Experimental Psychology/Helmholtz Institute, Utrecht University, 3584 Utrecht, The Netherlands; (H.C.D.); (A.K.)
| | | | | |
Collapse
|
34
|
Karaca M, Tahtasakal R, Dana H, Sahin M, Pirencioglu SN, Tughan E, Dal F, Demirci E, Sener EF. Decreased levels of alpha synuclein in families with autism spectrum disorder and relationship between the disease severity. Brain Res 2023; 1814:148410. [PMID: 37244604 DOI: 10.1016/j.brainres.2023.148410] [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: 03/16/2023] [Revised: 04/27/2023] [Accepted: 05/15/2023] [Indexed: 05/29/2023]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorders that begin in early childhood. Mutations in α-synuclein (SNCA) gene have been shown to result in the accumulation of α-synuclein, which occurs in many neurodegenerative diseases. Our aim was to determine the changes in the expression profile and protein level of this gene by comparing the autistic children with their healthy siblings, their mothers and healthy controls in order to elucidate the possible contribution of the SNCA gene to the etiology of ASD. 50 autistic patients, their mothers, siblings and 25 healthy controls and their mothers were enrolled to determine SNCA gene expression and serum α-synuclein levels. It was determined that α-synuclein serum levels decreased in the autistic patients. Similarly, it was found that SNCA gene expression and serum α-synuclein levels were significantly decreased in the mothers of the patients. Significant negative correlation was observed between the SNCA gene and protein expression amounts in the 6-8 age of the patients. This family-based study is the first in the literature, with both gene expression and serum levels of α-synuclein. The relationship between ASD severity and α-synuclein level needs to be confirmed in larger-scale studies.
Collapse
Affiliation(s)
- Mukaddes Karaca
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey
| | - Reyhan Tahtasakal
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey
| | - Halime Dana
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey; Erciyes University Medical Faculty Department of Medical Biology, Kayseri, Turkey
| | - Murside Sahin
- Erciyes University Medical Faculty Department of Child and Adolescent Psychiatry, 38039 Kayseri, Turkey
| | - Seyda Nur Pirencioglu
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey
| | - Emre Tughan
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey
| | - Fatma Dal
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey
| | - Esra Demirci
- Erciyes University Medical Faculty Department of Child and Adolescent Psychiatry, 38039 Kayseri, Turkey
| | - Elif Funda Sener
- Erciyes University Genome and Stem Cell Center (GENKOK), Erciyes University Medical Faculty Department of Medical Biology, 38039 Kayseri, Turkey; Erciyes University Medical Faculty Department of Medical Biology, Kayseri, Turkey
| |
Collapse
|
35
|
Hu L, Wan Q, Huang L, Tang J, Huang S, Chen X, Bai X, Kong L, Deng J, Liang H, Liu G, Liu H, Lu L. MRI-based brain age prediction model for children under 3 years old using deep residual network. Brain Struct Funct 2023; 228:1771-1784. [PMID: 37603065 DOI: 10.1007/s00429-023-02686-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: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023]
Abstract
Early identification and intervention of abnormal brain development individual subjects are of great significance, especially during the earliest and most active stage of brain development in children aged under 3. Neuroimage-based brain's biological age has been associated with health, ability, and remaining life. However, the existing brain age prediction models based on neuroimage are predominantly adult-oriented. Here, we collected 658 T1-weighted MRI scans from 0 to 3 years old healthy controls and developed an accurate brain age prediction model for young children using deep learning techniques with high accuracy in capturing age-related changes. The performance of the deep learning-based model is comparable to that of the SVR-based model, showcasing remarkable precision and yielding a noteworthy correlation of 91% between the predicted brain age and the chronological age. Our results demonstrate the accuracy of convolutional neural network (CNN) brain-predicted age using raw T1-weighted MRI data with minimum preprocessing necessary. We also applied our model to children with low birth weight, premature delivery history, autism, and ADHD, and discovered that the brain age was delayed in children with extremely low birth weight (less than 1000 g) while ADHD may cause accelerated aging of the brain. Our child-specific brain age prediction model can be a valuable quantitative tool to detect abnormal brain development and can be helpful in the early identification and intervention of age-related brain disorders.
Collapse
Affiliation(s)
- Lianting Hu
- Guangzhou Women and Children's Medical Center, Guangzhou, 510623, Guangdong, China
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, Guangdong, China
| | - Qirong Wan
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, 4330060, Hubei, China
| | - Li Huang
- School of Information Management, Wuhan University, Wuhan, 430072, Hubei, China
| | - Jiajie Tang
- Guangzhou Women and Children's Medical Center, Guangzhou, 510623, Guangdong, China
- School of Information Management, Wuhan University, Wuhan, 430072, Hubei, China
| | - Shuai Huang
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, Guangdong, China
| | - Xuanhui Chen
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, Guangdong, China
| | - Xiaohe Bai
- School of Physical Sciences, University of California San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Lingcong Kong
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
| | - Jingyi Deng
- School of Information Management, Wuhan University, Wuhan, 430072, Hubei, China
| | - Huiying Liang
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, Guangdong, China
| | - Guangjian Liu
- Medical Big Data Center, Guangdong Provincial People's Hospital/Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China
- Guangdong Cardiovascular Institute, Guangzhou, 510080, Guangdong, China
| | - Hongsheng Liu
- Guangzhou Women and Children's Medical Center, Guangzhou, 510623, Guangdong, China.
| | - Long Lu
- Guangzhou Women and Children's Medical Center, Guangzhou, 510623, Guangdong, China.
- School of Information Management, Wuhan University, Wuhan, 430072, Hubei, China.
| |
Collapse
|
36
|
Morrel J, Singapuri K, Landa RJ, Reetzke R. Neural correlates and predictors of speech and language development in infants at elevated likelihood for autism: a systematic review. Front Hum Neurosci 2023; 17:1211676. [PMID: 37662636 PMCID: PMC10469683 DOI: 10.3389/fnhum.2023.1211676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/25/2023] [Indexed: 09/05/2023] Open
Abstract
Autism spectrum disorder (ASD) is an increasingly prevalent and heterogeneous neurodevelopmental condition, characterized by social communicative differences, and a combination of repetitive behaviors, focused interests, and sensory sensitivities. Early speech and language delays are characteristic of young autistic children and are one of the first concerns reported by parents; often before their child's second birthday. Elucidating the neural mechanisms underlying these delays has the potential to improve early detection and intervention efforts. To fill this gap, this systematic review aimed to synthesize evidence on early neurobiological correlates and predictors of speech and language development across different neuroimaging modalities in infants with and without a family history of autism [at an elevated (EL infants) and low likelihood (LL infants) for developing autism, respectively]. A comprehensive, systematic review identified 24 peer-reviewed articles published between 2012 and 2023, utilizing structural magnetic resonance imaging (MRI; n = 2), functional MRI (fMRI; n = 4), functional near-infrared spectroscopy (fNIRS; n = 4), and electroencephalography (EEG; n = 14). Three main themes in results emerged: compared to LL infants, EL infants exhibited (1) atypical language-related neural lateralization; (2) alterations in structural and functional connectivity; and (3) mixed profiles of neural sensitivity to speech and non-speech stimuli, with some differences detected as early as 6 weeks of age. These findings suggest that neuroimaging techniques may be sensitive to early indicators of speech and language delays well before overt behavioral delays emerge. Future research should aim to harmonize experimental paradigms both within and across neuroimaging modalities and additionally address the feasibility, acceptability, and scalability of implementing such methodologies in non-academic, community-based settings.
Collapse
Affiliation(s)
- Jessica Morrel
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Kripi Singapuri
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Rebecca J. Landa
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Rachel Reetzke
- Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, United States
- Department of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| |
Collapse
|
37
|
Pan N, Lin LZ, Wang X, Shi L, Xu XY, Jin YY, Tan S, Song XJ, Jing J, Li XH. Brain structure underlying the empathizing-systemizing difference in children with autism spectrum disorder. World J Pediatr 2023; 19:782-792. [PMID: 37273174 DOI: 10.1007/s12519-023-00732-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 05/09/2023] [Indexed: 06/06/2023]
Abstract
BACKGROUND Behavioral research has shown that children with autism spectrum disorder (ASD) have a higher empathizing-systemizing difference (D score) than normal children. However, there is no research about the neuroanatomical mechanisms of the empathizing-systemizing difference in children with ASD. METHODS Participants comprised 41 children with ASD and 39 typically developing (TD) children aged 6‒12 years. Empathizing-systemizing difference was estimated using the D score from the Chinese version of Children's Empathy Quotient and Systemizing Quotient. We quantified brain morphometry, including global and regional brain volumes and surface-based cortical measures (cortical thickness, surface area, and gyrification) via structural magnetic resonance imaging. RESULTS We found that the D score was significantly negatively associated with amygdala gray matter volume [β = -0.16; 95% confidence interval (CI): -0.30, -0.02; P value = 0.030] in children with ASD. There was a significantly negative association between D score and gyrification in the left lateral occipital cortex (LOC) in children with ASD (B = -0.10; SE = 0.03; cluster-wise P value = 0.006) and a significantly positive association between D score and gyrification in the right fusiform in TD children (B = 0.10; SE = 0.03; cluster-wise P value = 0.022). Moderation analyses demonstrated significant interactions between D score and diagnosed group in amygdala gray matter volume (β = 0.19; 95% CI 0.04, 0.35; P value = 0.013) and left LOC gyrification (β = 0.11; 95% CI 0.05, 0.17; P value = 0.001) but not in right fusiform gyrification (β = 0.08; 95% CI -0.02, 0.17; P value = 0.105). CONCLUSIONS Neuroanatomical variation in amygdala volume and gyrification of LOC could be potential biomarkers for the empathizing-systemizing difference in children with ASD but not in TD children. Large-scale neuroimaging studies are necessary to test the replicability of our findings.
Collapse
Affiliation(s)
- Ning Pan
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China
| | - Li-Zi Lin
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Xin Wang
- Key Laboratory of Brain, Cognition and Education Science, Ministry of Education, Guangzhou, China
- Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, 510631, China
| | - Lei Shi
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, China
| | - Xiao-Yu Xu
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Yu-Ying Jin
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China
| | - Si Tan
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China
| | - Xiao-Jing Song
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China
| | - Jin Jing
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China
| | - Xiu-Hong Li
- Department of Maternal and Child Health, School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Yuexiu District, Guangzhou, 510080, China.
| |
Collapse
|
38
|
Dong Q, Li J, Ju Y, Xiao C, Li K, Shi B, Zheng W, Zhang Y. Altered Relationship between Functional Connectivity and Fiber-Bundle Structure in High-Functioning Male Adults with Autism Spectrum Disorder. Brain Sci 2023; 13:1098. [PMID: 37509029 PMCID: PMC10377258 DOI: 10.3390/brainsci13071098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/04/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterized by abnormalities in structure and function of the brain. However, how ASD affects the relationship between fiber-bundle microstructures and functional connectivity (FC) remains unclear. Here, we analyzed structural and functional images of 26 high-functioning adult males with ASD, alongside 26 age-, gender-, and full-scale IQ-matched typically developing controls (TDCs) from the BNI dataset in the ABIDE database. We utilized fixel-based analysis to extract microstructural information from fiber tracts, which was then used to predict FC using a multilinear model. Our results revealed that the structure-function relationships in both ASD and TDC cohorts were strongly aligned in the primary cortex but decoupled in the high-order cortex, and the ASD patients exhibited reduced structure-function relationships throughout the cortex compared to the TDCs. Furthermore, we observed that the disrupted relationships in ASD were primarily driven by alterations in FC rather than fiber-bundle microstructures. The structure-function relationships in the left superior parietal cortex, right precentral and inferior temporal cortices, and bilateral insula could predict individual differences in clinical symptoms of ASD patients. These findings underscore the significance of altered relationships between fiber-bundle microstructures and FC in the etiology of ASD.
Collapse
Affiliation(s)
- Qiangli Dong
- Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou 730000, China
| | - Jialong Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yumeng Ju
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Chuman Xiao
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Kangning Li
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Bin Shi
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yan Zhang
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| |
Collapse
|
39
|
Estévez-López F, Kim HH, López-Vicente M, Legerstee JS, Hillegers MHJ, Tiemeier H, Muetzel RL. Physical symptoms and brain morphology: a population neuroimaging study in 12,286 pre-adolescents. Transl Psychiatry 2023; 13:254. [PMID: 37438345 DOI: 10.1038/s41398-023-02528-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 07/14/2023] Open
Abstract
Physical symptoms, also known as somatic symptoms, are those for which medical examinations do not reveal a sufficient underlying root cause (e.g., pain and fatigue). The extant literature of the neurobiological underpinnings of physical symptoms is largely inconsistent and primarily comprises of (clinical) case-control studies with small sample sizes. In this cross-sectional study, we studied the association between dimensionally measured physical symptoms and brain morphology in pre-adolescents from two population-based cohorts; the Generation R Study (n = 2649, 10.1 ± 0.6 years old) and ABCD Study (n = 9637, 9.9 ± 0.6 years old). Physical symptoms were evaluated using continuous scores from the somatic complaints syndrome scale from the parent-reported Child Behavior Checklist (CBCL). High-resolution structural magnetic resonance imaging (MRI) was collected using 3-Tesla MRI systems. Linear regression models were fitted for global brain metrics (cortical and subcortical grey matter and total white matter volume) and surface-based vertex-wise measures (surface area and cortical thickness). Results were meta-analysed. Symptoms of anxiety/depression were studied as a contrasting comorbidity. In the meta-analyses across cohorts, we found negative associations between physical symptoms and surface area in the (i) left hemisphere; in the lateral orbitofrontal cortex and pars triangularis and (ii) right hemisphere; in the pars triangularis, the pars orbitalis, insula, middle temporal gyrus and caudal anterior cingulate cortex. However, only a subset of regions (left lateral orbitofrontal cortex and right pars triangularis) were specifically associated with physical symptoms, while others were also related to symptoms of anxiety/depression. No significant associations were observed for cortical thickness. This study in preadolescents, the most representative and well-powered to date, showed that more physical symptoms are modestly related to less surface area of the prefrontal cortex mostly. While these effects are subtle, future prospective research is warranted to understand the longitudinal relationship of physical symptoms and brain changes over time. Particularly, to elucidate whether physical symptoms are a potential cause or consequence of distinct neurodevelopmental trajectories.
Collapse
Affiliation(s)
- Fernando Estévez-López
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
- Department of Education, Faculty of Education Sciences, SPORT Research Group (CTS-1024) and CERNEP Research Center, University of Almería, Almería, Spain.
| | - Hannah H Kim
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Mónica López-Vicente
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Jeroen S Legerstee
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Manon H J Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| |
Collapse
|
40
|
Pretzsch CM, Ecker C. Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review. Front Neurosci 2023; 17:1172779. [PMID: 37457001 PMCID: PMC10347684 DOI: 10.3389/fnins.2023.1172779] [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: 02/23/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.
Collapse
Affiliation(s)
- Charlotte M. Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| |
Collapse
|
41
|
Fan Y, Xiong H, Sun G. DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification. BMC Bioinformatics 2023; 24:261. [PMID: 37349705 DOI: 10.1186/s12859-023-05378-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by difficulty communicating with society and others, behavioral difficulties, and a brain that processes information differently than normal. Genetics has a strong impact on ASD associated with early onset and distinctive signs. Currently, all known ASD risk genes are able to encode proteins, and some de novo mutations disrupting protein-coding genes have been demonstrated to cause ASD. Next-generation sequencing technology enables high-throughput identification of ASD risk RNAs. However, these efforts are time-consuming and expensive, so an efficient computational model for ASD risk gene prediction is necessary. RESULTS In this study, we propose DeepASDPerd, a predictor for ASD risk RNA based on deep learning. Firstly, we use K-mer to feature encode the RNA transcript sequences, and then fuse them with corresponding gene expression values to construct a feature matrix. After combining chi-square test and logistic regression to select the best feature subset, we input them into a binary classification prediction model constructed by convolutional neural network and long short-term memory for training and classification. The results of the tenfold cross-validation proved our method outperformed the state-of-the-art methods. Dataset and source code are available at https://github.com/Onebear-X/DeepASDPred is freely available. CONCLUSIONS Our experimental results show that DeepASDPred has outstanding performance in identifying ASD risk RNA genes.
Collapse
Affiliation(s)
- Yongxian Fan
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Hui Xiong
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Guicong Sun
- School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 541004, China.
| |
Collapse
|
42
|
Chen L, Wang Y, Wu Z, Shan Y, Li T, Hung SC, Xing L, Zhu H, Wang L, Lin W, Li G. Four-dimensional mapping of dynamic longitudinal brain subcortical development and early learning functions in infants. Nat Commun 2023; 14:3727. [PMID: 37349301 PMCID: PMC10287661 DOI: 10.1038/s41467-023-38974-9] [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] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 05/23/2023] [Indexed: 06/24/2023] Open
Abstract
Brain subcortical structures are paramount in many cognitive functions and their aberrations during infancy are predisposed to various neurodevelopmental and neuropsychiatric disorders, making it highly essential to characterize the early subcortical normative growth patterns. This study investigates the volumetric development and surface area expansion of six subcortical structures and their associations with Mullen scales of early learning by leveraging 513 high-resolution longitudinal MRI scans within the first two postnatal years. Results show that (1) each subcortical structure (except for the amygdala with an approximately linear increase) undergoes rapid nonlinear volumetric growth after birth, which slows down at a structure-specific age with bilaterally similar developmental patterns; (2) Subcortical local area expansion reveals structure-specific and spatiotemporally heterogeneous patterns; (3) Positive associations between thalamus and both receptive and expressive languages and between caudate and putamen and fine motor are revealed. This study advances our understanding of the dynamic early subcortical developmental patterns.
Collapse
Affiliation(s)
- Liangjun Chen
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Ya Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Tengfei Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Sheng-Che Hung
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Lei Xing
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, 116 Manning Rd, Chapel Hill, NC, 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, 130 Mason Farm Rd, Chapel Hill, NC, 27599, USA.
| |
Collapse
|
43
|
Chen J, Wei Z, Xu C, Peng Z, Yang J, Wan G, Chen B, Gong J, Zhou K. Social visual preference mediates the effect of cortical thickness on symptom severity in children with autism spectrum disorder. Front Psychiatry 2023; 14:1132284. [PMID: 37398604 PMCID: PMC10311909 DOI: 10.3389/fpsyt.2023.1132284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 05/29/2023] [Indexed: 07/04/2023] Open
Abstract
Background Evidence suggests that there is a robust relationship between altered neuroanatomy and autistic symptoms in individuals with autism spectrum disorder (ASD). Social visual preference, which is regulated by specific brain regions, is also related to symptom severity. However, there were a few studies explored the potential relationships among brain structure, symptom severity, and social visual preference. Methods The current study investigated relationships among brain structure, social visual preference, and symptom severity in 43 children with ASD and 26 typically developing (TD) children (aged 2-6 years). Results Significant differences were found in social visual preference and cortical morphometry between the two groups. Decreased percentage of fixation time in digital social images (%DSI) was negatively related to not only the thickness of the left fusiform gyrus (FG) and right insula, but also the Calibrated Severity Scores for the Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA-CSS). Mediation analysis showed that %DSI partially mediated the relationship between neuroanatomical alterations (specifically, thickness of the left FG and right insula) and symptom severity. Conclusion These findings offer initial evidence that atypical neuroanatomical alterations may not only result in direct effects on symptom severity but also lead to indirect effects on symptom severity through social visual preference. This finding enhances our understanding of the multiple neural mechanisms implicated in ASD.
Collapse
Affiliation(s)
- Jierong Chen
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Zhen Wei
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
- Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, China
| | - Chuangyong Xu
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Ziwen Peng
- Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou, China
| | - Junjie Yang
- Department of Child Health Care, Luohu District Maternal and Child Health Care Hospital, Shenzhen, China
| | - Guobin Wan
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Bin Chen
- Department of Child Psychiatry and Rehabilitation, Affliated Shenzhen Maternity and Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Jianhua Gong
- Department of Child Health Care, Luohu District Maternal and Child Health Care Hospital, Shenzhen, China
| | - Keying Zhou
- Department of Pediatrics, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, Guangdong, China
| |
Collapse
|
44
|
Openshaw RL, Thomson DM, Bristow GC, Mitchell EJ, Pratt JA, Morris BJ, Dawson N. 16p11.2 deletion mice exhibit compromised fronto-temporal connectivity, GABAergic dysfunction, and enhanced attentional ability. Commun Biol 2023; 6:557. [PMID: 37225770 DOI: 10.1038/s42003-023-04891-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 05/01/2023] [Indexed: 05/26/2023] Open
Abstract
Autism spectrum disorders are more common in males, and have a substantial genetic component. Chromosomal 16p11.2 deletions in particular carry strong genetic risk for autism, yet their neurobiological impact is poorly characterised, particularly at the integrated systems level. Here we show that mice reproducing this deletion (16p11.2 DEL mice) have reduced GABAergic interneuron gene expression (decreased parvalbumin mRNA in orbitofrontal cortex, and male-specific decreases in Gad67 mRNA in parietal and insular cortex and medial septum). Metabolic activity was increased in medial septum, and in its efferent targets: mammillary body and (males only) subiculum. Functional connectivity was altered between orbitofrontal, insular and auditory cortex, and between septum and hippocampus/subiculum. Consistent with this circuit dysfunction, 16p11.2 DEL mice showed reduced prepulse inhibition, but enhanced performance in the continuous performance test of attentional ability. Level 1 autistic individuals show similarly heightened performance in the equivalent human test, also associated with parietal, insular-orbitofrontal and septo-subicular dysfunction. The data implicate cortical and septal GABAergic dysfunction, and resulting connectivity changes, as the cause of pre-attentional and attentional changes in autism.
Collapse
Affiliation(s)
- Rebecca L Openshaw
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK
| | - David M Thomson
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Greg C Bristow
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK
- School of Pharmacy and Medical Sciences, University of Bradford, Bradford, BD7 1DP, UK
| | - Emma J Mitchell
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Judith A Pratt
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, G4 0RE, UK
| | - Brian J Morris
- School of Psychology and Neuroscience, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir James Black Building, Glasgow, G12 8QQ, UK.
| | - Neil Dawson
- Department of Biomedical and Life Sciences, Lancaster University, Lancaster, LA1 4YW, UK.
| |
Collapse
|
45
|
Abstract
Autism is often considered to reflect categorically 'different brains'. Neuropsychological research on autism spectrum disorder (ASD) however, has struggled to define this difference, or derive clear-cut boundaries between autism and non-autism. Consequently, restructuring or disbanding the ASD diagnosis is becoming increasingly advocated within research. Nonetheless, autism now exists as a salient social construction, of which 'difference' is a key facet. Clinical and educational professionals must influence this cautiously, as changes to autism's social construction may counterproductively affect the quality of life of autistic people. This paper therefore reviews ASD's value as both neuropsychological and social constructs. Although lacking neuropsychological validity, the autism label may be beneficial for autistic self-identity, reduction of stigma, and administering support. Whilst a shift away from case-control ASD research is warranted, lay notions of 'different brains' may be preserved.
Collapse
Affiliation(s)
- Daniel Crawshaw
- School of Psychology, University of Nottingham, University Park, Nottingham, UK
| |
Collapse
|
46
|
Chen L, Wu Z, Zhao F, Wang Y, Lin W, Wang L, Li G. An attention-based context-informed deep framework for infant brain subcortical segmentation. Neuroimage 2023; 269:119931. [PMID: 36746299 PMCID: PMC10241225 DOI: 10.1016/j.neuroimage.2023.119931] [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: 11/05/2022] [Revised: 01/13/2023] [Accepted: 02/03/2023] [Indexed: 02/06/2023] Open
Abstract
Precise segmentation of subcortical structures from infant brain magnetic resonance (MR) images plays an essential role in studying early subcortical structural and functional developmental patterns and diagnosis of related brain disorders. However, due to the dynamic appearance changes, low tissue contrast, and tiny subcortical size in infant brain MR images, infant subcortical segmentation is a challenging task. In this paper, we propose a context-guided, attention-based, coarse-to-fine deep framework to precisely segment the infant subcortical structures. At the coarse stage, we aim to directly predict the signed distance maps (SDMs) from multi-modal intensity images, including T1w, T2w, and the ratio of T1w and T2w images, with an SDM-Unet, which can leverage the spatial context information, including the structural position information and the shape information of the target structure, to generate high-quality SDMs. At the fine stage, the predicted SDMs, which encode spatial-context information of each subcortical structure, are integrated with the multi-modal intensity images as the input to a multi-source and multi-path attention Unet (M2A-Unet) for achieving refined segmentation. Both the 3D spatial and channel attention blocks are added to guide the M2A-Unet to focus more on the important subregions and channels. We additionally incorporate the inner and outer subcortical boundaries as extra labels to help precisely estimate the ambiguous boundaries. We validate our method on an infant MR image dataset and on an unrelated neonatal MR image dataset. Compared to eleven state-of-the-art methods, the proposed framework consistently achieves higher segmentation accuracy in both qualitative and quantitative evaluations of infant MR images and also exhibits good generalizability in the neonatal dataset.
Collapse
Affiliation(s)
- Liangjun Chen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Fenqiang Zhao
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ya Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| |
Collapse
|
47
|
Repetitive transcranial magnetic stimulation modulates long-range functional connectivity in autism spectrum disorder. J Psychiatr Res 2023; 160:187-194. [PMID: 36841084 DOI: 10.1016/j.jpsychires.2023.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/12/2023] [Accepted: 02/20/2023] [Indexed: 02/23/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is growingly applied in autism spectrum disorder (ASD) due to its potential therapeutic value, however, its effects on functional network configuration and the mechanism underlying clinical improvement are still unclear. In this study, we examined the alternations of functional connectivity induced by rTMS using resting-state electroencephalogram (EEG) in children with ASD. Resting-state EEG was obtained from 24 children with ASD before and after rTMS intervention and from 24 age- and gender-matched typically developing (TD) children. The rTMS intervention course consisted of five 5-s trains at 15 Hz, with 10-min inter-train intervals, on the left parietal lobe each consecutive weekday for 3 weeks (15 sessions in total). Children with ASD showed significantly hypo-connected networks and sub-optimal network properties at both global and local levels, compared with TD peers. After rTMS intervention, long-range intra- and inter-hemispheric connections were significantly promoted, especially those within the alpha band. Meanwhile, network properties at both local and global levels were greatly promoted in the delta, theta, and alpha bands. Consistent with the changes in the network connectivities and properties, the core symptoms in ASD were also relieved measured by clinical scales after treatment. The findings of this study demonstrate that high-frequency rTMS over the parietal lobe is potentially an effective strategy to improve core symptoms by enhancing long-range connectivity reorganization in ASD.
Collapse
|
48
|
Peterson M, Whetten C, Clark AM, Nielsen JA. No difference in extra-axial cerebrospinal fluid volumes across neurodevelopmental and psychiatric conditions in later childhood and adolescence. J Neurodev Disord 2023; 15:12. [PMID: 37005573 PMCID: PMC10068173 DOI: 10.1186/s11689-023-09477-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 02/08/2023] [Indexed: 04/04/2023] Open
Abstract
BACKGROUND While autism spectrum disorder has been associated with various organizational and developmental aberrations in the brain, an increase in extra-axial cerebrospinal fluid volume has recently garnered attention. A series of studies indicate that an increased volume between the ages of 6 months and 4 years was both predictive of the autism diagnosis and symptom severity regardless of genetic risk for the condition. However, there remains a minimal understanding regarding the specificity of an increased volume of extra-axial cerebrospinal fluid to autism. METHODS In the present study, we explored extra-axial cerebrospinal fluid volumes in children and adolescents ages 5-21 years with various neurodevelopmental and psychiatric conditions. We hypothesized that an elevated extra-axial cerebrospinal fluid volume would be found in autism compared with typical development and the other diagnostic group. We tested this hypothesis by employing a cross-sectional dataset of 446 individuals (85 autistic, 60 typically developing, and 301 other diagnosis). An analysis of covariance was used to examine differences in extra-axial cerebrospinal fluid volumes between these groups as well as a group by age interaction in extra-axial cerebrospinal fluid volumes. RESULTS Inconsistent with our hypothesis, we found no group differences in extra-axial cerebrospinal fluid volume in this cohort. However, in replication of previous work, a doubling of extra-axial cerebrospinal fluid volume across adolescence was found. Further investigation into the relationship between extra-axial cerebrospinal fluid volume and cortical thickness suggested that this increase in extra-axial cerebrospinal fluid volume may be driven by a decrease in cortical thickness. Furthermore, an exploratory analysis found no relationship between extra-axial cerebrospinal fluid volume and sleep disturbances. CONCLUSIONS These results indicate that an increased volume of extra-axial cerebrospinal fluid may be limited to autistic individuals younger than 5 years. Additionally, extra-axial cerebrospinal fluid volume does not differ between autistic, neurotypical, and other psychiatric conditions after age 4.
Collapse
Affiliation(s)
- Madeline Peterson
- Department of Psychology, Brigham Young University, Provo, UT, 84602, USA
| | | | - Anne M Clark
- Neuroscience Center, Brigham Young University, Provo, UT, 84604, USA
| | - Jared A Nielsen
- Department of Psychology, Brigham Young University, Provo, UT, 84602, USA.
- Neuroscience Center, Brigham Young University, Provo, UT, 84604, USA.
| |
Collapse
|
49
|
Guo D, Yang X, Gao M, Chen X, Tang Y, Shen L, Li K, Shi L. Deficiency of Autism-Related Gene Dock4 Leads to Impaired Spatial Memory and Hippocampal Function in Mice at Late Middle Age. Cell Mol Neurobiol 2023; 43:1129-1146. [PMID: 35635601 DOI: 10.1007/s10571-022-01233-4] [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: 02/25/2022] [Accepted: 05/12/2022] [Indexed: 11/25/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder that lasts lifelong and causes noticeably higher premature mortality. Although the core symptoms and other behavioral deficits of ASD can persist or be deteriorated from early development to old age, how aging affects the behaviors and brain anatomy in ASD is largely unknown. DOCK4 is an ASD risk gene highly expressed in the hippocampus, and Dock4 knockout (KO) mice display ASD-like behaviors in adulthood (4- to 6-month-old). In this study, we evaluated the behavioral and hippocampal pathological changes of late-middle-aged (15- to 17-month-old) Dock4 male KO mice. Aged Dock4 KO mice continuously showed similar social deficit, elevated anxiety, and disrupted object location memory as observed in the adulthood, when compared to their wild-type (WT) littermates. Notably, Dock4 KO mice displayed an age-related decline of hippocampal dependent spatial memory, showing decreased spatial memory in Barnes maze than their WT littermates at late middle age. Morphological analysis from WT and Dock4 KO littermates revealed that Dock4 deficiency led to decreased mature neurons and oligodendrocytes but increased astrocytes in the hippocampus of late-middle-aged mice. Together, we report that ASD-like behaviors mostly persist into late-middle age in Dock4 KO mice, with specific alterations of spatial memory and hippocampal anatomy by age, thus providing new evidence for understanding age differences in behavioral deficits of ASD.
Collapse
Affiliation(s)
- Daji Guo
- Clinical Neuroscience Institute, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China.
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China.
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China.
| | - Xiaoman Yang
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China
| | - Ming Gao
- Clinical Neuroscience Institute, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China
| | - Xiaoqing Chen
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China
| | - Yanping Tang
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China
| | - Lingling Shen
- Clinical Neuroscience Institute, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China
| | - Keshen Li
- Clinical Neuroscience Institute, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China.
- Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Guangzhou, 510632, Guangdong, China.
| | - Lei Shi
- JNU-HKUST Joint Laboratory for Neuroscience and Innovative Drug Research, College of Pharmacy, Jinan University, Guangzhou, 510632, Guangdong, China.
| |
Collapse
|
50
|
Cohen AL, Kroeck MR, Wall J, McManus P, Ovchinnikova A, Sahin M, Krueger DA, Bebin EM, Northrup H, Wu JY, Warfield SK, Peters JM, Fox MD. Tubers Affecting the Fusiform Face Area Are Associated with Autism Diagnosis. Ann Neurol 2023; 93:577-590. [PMID: 36394118 PMCID: PMC9974824 DOI: 10.1002/ana.26551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 11/11/2022] [Accepted: 11/13/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Tuberous sclerosis complex (TSC) is associated with focal brain "tubers" and a high incidence of autism spectrum disorder (ASD). The location of brain tubers associated with autism may provide insight into the neuroanatomical substrate of ASD symptoms. METHODS We delineated tuber locations for 115 TSC participants with ASD (n = 31) and without ASD (n = 84) from the Tuberous Sclerosis Complex Autism Center of Excellence Research Network. We tested for associations between ASD diagnosis and tuber burden within the whole brain, specific lobes, and at 8 regions of interest derived from the ASD neuroimaging literature, including the anterior cingulate, orbitofrontal and posterior parietal cortices, inferior frontal and fusiform gyri, superior temporal sulcus, amygdala, and supplemental motor area. Next, we performed an unbiased data-driven voxelwise lesion symptom mapping (VLSM) analysis. Finally, we calculated the risk of ASD associated with positive findings from the above analyses. RESULTS There were no significant ASD-related differences in tuber burden across the whole brain, within specific lobes, or within a priori regions derived from the ASD literature. However, using VLSM analysis, we found that tubers involving the right fusiform face area (FFA) were associated with a 3.7-fold increased risk of developing ASD. INTERPRETATION Although TSC is a rare cause of ASD, there is a strong association between tuber involvement of the right FFA and ASD diagnosis. This highlights a potentially causative mechanism for developing autism in TSC that may guide research into ASD symptoms more generally. ANN NEUROL 2023;93:577-590.
Collapse
Affiliation(s)
- Alexander L Cohen
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mallory R Kroeck
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Juliana Wall
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Peter McManus
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Arina Ovchinnikova
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mustafa Sahin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Rosamund Stone Zander Translational Neuroscience Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Darcy A Krueger
- Department of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - E Martina Bebin
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Hope Northrup
- Department of Pediatrics, McGovern Medical School at University of Texas Health Science Center at Houston and Children's Memorial Hermann Hospital, Houston, TX, USA
| | - Joyce Y Wu
- Division of Neurology & Epilepsy, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jurriaan M Peters
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| |
Collapse
|