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Soumier A, Lio G, Demily C. Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders. Mol Psychiatry 2024:10.1038/s41380-024-02487-8. [PMID: 38443634 DOI: 10.1038/s41380-024-02487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.
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Affiliation(s)
- Amelie Soumier
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France.
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France.
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France.
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France.
| | - Guillaume Lio
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
| | - Caroline Demily
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France
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Zhang J, Zhang Z, Sun H, Ma Y, Yang J, Chen K, Yu X, Qin T, Zhao T, Zhang J, Chu C, Wang J. Personalized functional network mapping for autism spectrum disorder and attention-deficit/hyperactivity disorder. Transl Psychiatry 2024; 14:92. [PMID: 38346949 PMCID: PMC10861462 DOI: 10.1038/s41398-024-02797-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 01/11/2024] [Accepted: 01/22/2024] [Indexed: 02/15/2024] Open
Abstract
Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are two typical neurodevelopmental disorders that have a long-term impact on physical and mental health. ASD is usually comorbid with ADHD and thus shares highly overlapping clinical symptoms. Delineating the shared and distinct neurophysiological profiles is important to uncover the neurobiological mechanisms to guide better therapy. In this study, we aimed to establish the behaviors, functional connectome, and network properties differences between ASD, ADHD-Combined, and ADHD-Inattentive using resting-state functional magnetic resonance imaging. We used the non-negative matrix fraction method to define personalized large-scale functional networks for each participant. The individual large-scale functional network connectivity (FNC) and graph-theory-based complex network analyses were executed and identified shared and disorder-specific differences in FNCs and network attributes. In addition, edge-wise functional connectivity analysis revealed abnormal edge co-fluctuation amplitude and number of transitions among different groups. Taken together, our study revealed disorder-specific and -shared regional and edge-wise functional connectivity and network differences for ASD and ADHD using an individual-level functional network mapping approach, which provides new evidence for the brain functional abnormalities in ASD and ADHD and facilitates understanding the neurobiological basis for both disorders.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Zhiwei Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hui Sun
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Jia Yang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Kexuan Chen
- Medical School, Kunming University of Science and Technology, Kunming, China
| | - Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Tianwei Qin
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianyu Zhao
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Jingyue Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Congying Chu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China.
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Huang Z, Zhang X, Yang X, Ding S, Cai J. Aberrant brain intra- and internetwork functional connectivity in children with Prader-Willi syndrome. Neuroradiology 2024; 66:135-144. [PMID: 38001311 PMCID: PMC10761436 DOI: 10.1007/s00234-023-03259-x] [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: 04/26/2023] [Accepted: 11/18/2023] [Indexed: 11/26/2023]
Abstract
PURPOSE Prader-Willi syndrome (PWS) suffers from brain functional reorganization and developmental delays during childhood, but the underlying neurodevelopmental mechanism is unclear. This paper aims to investigate the intra- and internetwork functional connectivity (FC) changes, and their relationships with developmental delays in PWS children. METHODS Resting-state functional magnetic resonance imaging datasets of PWS children and healthy controls (HCs) were acquired. Independent component analysis was used to acquire core resting-state networks (RSNs). The intra- and internetwork FC patterns were then investigated. RESULTS In terms of intranetwork FC, children with PWS had lower FC in the dorsal attention network, the auditory network, the medial visual network (VN) and the sensorimotor network (SMN) than HCs (FWE-corrected, p < 0.05). In terms of internetwork FC, PWS children had decreased FC between the following pairs of regions: posterior default mode network (DMN) and anterior DMN; posterior DMN and SMN; SMN and posterior VN and salience network and medial VN (FDR-corrected, p < 0.05). Partial correlation analyses revealed that the intranetwork FC patterns were positively correlated with developmental quotients in PWS children, while the internetwork FC patterns were completely opposite (p < 0.05). Intranetwork FC patterns showed an area under the receiver operating characteristic curve of 0.947, with a sensitivity of 96.15% and a specificity of 81.25% for differentiating between PWS and HCs. CONCLUSION Impaired intra- and internetwork FC patterns in PWS children are associated with developmental delays, which may result from neural pathway dysfunctions. Intranetwork FC reorganization patterns can discriminate PWS children from HCs. REGISTRATION NUMBER ON THE CHINESE CLINICAL TRAIL REGISTRY ChiCTR2100046551.
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Affiliation(s)
- Zhongxin Huang
- Department of Radiology, Children's Hospital of Chongqing Medical University, No. 136, Zhongshan Second Road 400014, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China
- Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Chongqing, 400014, China
| | - Xiangmin Zhang
- Department of Radiology, Children's Hospital of Chongqing Medical University, No. 136, Zhongshan Second Road 400014, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China
- Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Chongqing, 400014, China
| | - Xinyi Yang
- Department of Radiology, Children's Hospital of Chongqing Medical University, No. 136, Zhongshan Second Road 400014, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China
- Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Chongqing, 400014, China
| | - Shuang Ding
- Department of Radiology, Children's Hospital of Chongqing Medical University, No. 136, Zhongshan Second Road 400014, Chongqing, China
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China
- Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Chongqing, 400014, China
| | - Jinhua Cai
- Department of Radiology, Children's Hospital of Chongqing Medical University, No. 136, Zhongshan Second Road 400014, Chongqing, China.
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China.
- Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Chongqing, 400014, China.
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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.
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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.)
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Helmy E, Elnakib A, ElNakieb Y, Khudri M, Abdelrahim M, Yousaf J, Ghazal M, Contractor S, Barnes GN, El-Baz A. Role of Artificial Intelligence for Autism Diagnosis Using DTI and fMRI: A Survey. Biomedicines 2023; 11:1858. [PMID: 37509498 PMCID: PMC10376963 DOI: 10.3390/biomedicines11071858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 06/22/2023] [Accepted: 06/27/2023] [Indexed: 07/30/2023] Open
Abstract
Autism spectrum disorder (ASD) is a wide range of diseases characterized by difficulties with social skills, repetitive activities, speech, and nonverbal communication. The Centers for Disease Control (CDC) estimates that 1 in 44 American children currently suffer from ASD. The current gold standard for ASD diagnosis is based on behavior observational tests by clinicians, which suffer from being subjective and time-consuming and afford only late detection (a child must have a mental age of at least two to apply for an observation report). Alternatively, brain imaging-more specifically, magnetic resonance imaging (MRI)-has proven its ability to assist in fast, objective, and early ASD diagnosis and detection. With the recent advances in artificial intelligence (AI) and machine learning (ML) techniques, sufficient tools have been developed for both automated ASD diagnosis and early detection. More recently, the development of deep learning (DL), a young subfield of AI based on artificial neural networks (ANNs), has successfully enabled the processing of brain MRI data with improved ASD diagnostic abilities. This survey focuses on the role of AI in autism diagnostics and detection based on two basic MRI modalities: diffusion tensor imaging (DTI) and functional MRI (fMRI). In addition, the survey outlines the basic findings of DTI and fMRI in autism. Furthermore, recent techniques for ASD detection using DTI and fMRI are summarized and discussed. Finally, emerging tendencies are described. The results of this study show how useful AI is for early, subjective ASD detection and diagnosis. More AI solutions that have the potential to be used in healthcare settings will be introduced in the future.
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Affiliation(s)
- Eman Helmy
- Department of Diagnostic Radiology, Faculty of Medicine, Mansoura University, Elgomheryia Street, Mansoura 3512, Egypt;
| | - Ahmed Elnakib
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (A.E.); (Y.E.); (M.K.); (M.A.)
| | - Yaser ElNakieb
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (A.E.); (Y.E.); (M.K.); (M.A.)
| | - Mohamed Khudri
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (A.E.); (Y.E.); (M.K.); (M.A.)
| | - Mostafa Abdelrahim
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (A.E.); (Y.E.); (M.K.); (M.A.)
| | - Jawad Yousaf
- Electrical, Computer, and Biomedical Engineering Department, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates; (J.Y.); (M.G.)
| | - Mohammed Ghazal
- Electrical, Computer, and Biomedical Engineering Department, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates; (J.Y.); (M.G.)
| | - Sohail Contractor
- Department of Radiology, University of Louisville, Louisville, KY 40202, USA;
| | - Gregory Neal Barnes
- Department of Neurology, Pediatric Research Institute, University of Louisville, Louisville, KY 40202, USA;
| | - Ayman El-Baz
- Bioengineering Department, University of Louisville, Louisville, KY 40292, USA; (A.E.); (Y.E.); (M.K.); (M.A.)
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6
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Luo L, Chen J, Wu Q, Yuan B, Hu C, Yang T, Wei H, Li T. Prenatally VPA exposure is likely to cause autistic-like behavior in the rats offspring via TREM2 down-regulation to affect the microglial activation and synapse alterations. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2023; 99:104090. [PMID: 36870407 DOI: 10.1016/j.etap.2023.104090] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/17/2023] [Accepted: 02/23/2023] [Indexed: 06/18/2023]
Abstract
Microglial dysfunction has been reported in the valproic acid (VPA)-induced autism spectrum disorder (ASD) rat models. However, how does prenatal VPA exposure affect microglia remains to be elucidated. The triggering receptor expressed on myeloid cells 2 (TREM2) is revealed to be implicated in a range of microglia functions. However, reports on the association between TREM2 and VPA-induced ASD rat models are scarce. Our results showed that prenatal VPA exposure induced autistic-like behaviors, downregulated the levels of TREM2, up-regulated microglial activation, dysregulated microglial polarization, and altered synapse in offspring. TREM2 overexpression partly ameliorated microglia dysfunction and autistic-like behaviors in prenatal VPA-exposed rats. Our findings demonstrated that prenatally VPA exposure is likely to cause autistic-like behavior in the rat offspring via TREM2 down-regulation to affect the microglial activation, microglial polarization and synaptic pruning of microglia for the first time.
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Affiliation(s)
- Lijuan Luo
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Jie Chen
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Qionghui Wu
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Binlin Yuan
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Chaoqun Hu
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Ting Yang
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
| | - Hua Wei
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China; Department of Child Health Care, Children's Hospital of Chongqing Medical University, Chongqing, China.
| | - Tingyu Li
- Children's Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing Key Laboratory of Child Nutrition and Health, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China; Department of Child Health Care, Children's Hospital of Chongqing Medical University, Chongqing, China.
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Kim JI, Bang S, Yang JJ, Kwon H, Jang S, Roh S, Kim SH, Kim MJ, Lee HJ, Lee JM, Kim BN. Classification of Preschoolers with Low-Functioning Autism Spectrum Disorder Using Multimodal MRI Data. J Autism Dev Disord 2023; 53:25-37. [PMID: 34984638 DOI: 10.1007/s10803-021-05368-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/05/2021] [Indexed: 02/03/2023]
Abstract
Multimodal imaging studies targeting preschoolers and low-functioning autism spectrum disorder (ASD) patients are scarce. We applied machine learning classifiers to parameters from T1-weighted MRI and DTI data of 58 children with ASD (age 3-6 years) and 48 typically developing controls (TDC). Classification performance reached an accuracy, sensitivity, and specificity of 88.8%, 93.0%, and 83.8%, respectively. The most prominent features were the cortical thickness of the right inferior occipital gyrus, mean diffusivity of the middle cerebellar peduncle, and nodal efficiency of the left posterior cingulate gyrus. Machine learning-based analysis of MRI data was useful in distinguishing low-functioning ASD preschoolers from TDCs. Combination of T1 and DTI improved classification accuracy about 10%, and large-scale multi-modal MRI studies are warranted for external validation.
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Affiliation(s)
- Johanna Inhyang Kim
- Department of Psychiatry, Hanyang University Medical Center, 222-1 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
| | - Sungkyu Bang
- Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
| | - Jin-Ju Yang
- Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
| | - Heejin Kwon
- Department of Psychology, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 02722, Republic of Korea
| | - Soomin Jang
- Department of Psychiatry, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Sungwon Roh
- Department of Psychiatry, Hanyang University Medical Center, 222-1 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
- Department of Psychiatry, Hanyang University College of Medicine, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
| | - Seok Hyeon Kim
- Department of Psychiatry, Hanyang University Medical Center, 222-1 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
- Department of Psychiatry, Hanyang University College of Medicine, 222 Wangsimni-ro, Seongdong-gu, Seoul, 04763, Republic of Korea
| | - Mi Jung Kim
- Department of Rehabilitation Medicine, Hanyang University College of Medicine, 222 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, 222 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, 222 Wangsimni-ro, Sungdong-gu, Seoul, 04763, Republic of Korea.
| | - Bung-Nyun Kim
- Department of Psychiatry, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, 101 Daehak-no, Chongno-gu, Seoul, 03080, Republic of Korea.
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Cui W, Wang S, Chen B, Fan G. White matter structural network alterations in congenital bilateral profound sensorineural hearing loss children: A graph theory analysis. Hear Res 2022; 422:108521. [PMID: 35660126 DOI: 10.1016/j.heares.2022.108521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 03/22/2022] [Accepted: 05/14/2022] [Indexed: 11/25/2022]
Abstract
Functional magnetic resonance imaging (fMRI) studies have revealed a functional reorganization in patients with sensorineural hearing loss (SNHL). The structural basement of functional changes has also been investigated recently. Graph theory analysis brings a new understanding of the structural connectome and topological features in central neural system diseases. However, little is known about the structural network connectome changes in SNHL patients, especially in children. We explored the differences in topologic organization, rich-club organization, and structural connection between children with congenital bilateral profound SNHL and normal hearing under the age of three using graph theory analysis and probabilistic tractography. Compared with the normal-hearing (NH) group, the SNHL group showed no difference in global and nodal topological parameters. Increased structural connection strength were found in the right cortico-striatal-thalamus-cortical circuity. Decreased cross-hemisphere connections were found between the right precuneus and the left auditory cortex as well as the left subcortical regions. Rich-club organization analysis found increased local connection in the SNHL group. These results revealed structural organizations after hearing deprivation in congenital bilateral profound SNHL children.
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Affiliation(s)
- Wenzhuo Cui
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, LN, China
| | - Shanshan Wang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, LN, China
| | - Boyu Chen
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, LN, China
| | - Guoguang Fan
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, LN, China.
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9
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Cai Y, Zhao J, Wang L, Xie Y, Fan X. Altered topological properties of white matter structural network in adults with autism spectrum disorder. Asian J Psychiatr 2022; 75:103211. [PMID: 35907341 DOI: 10.1016/j.ajp.2022.103211] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/10/2022] [Accepted: 07/12/2022] [Indexed: 12/27/2022]
Abstract
BACKGROUND Autism spectrum disorder (ASD) is a complex developmental disability and is currently viewed as a disorder of brain connectivity in which white matter abnormalities. However, the majority of the research to date has focused on children with ASD. Understanding the topological organization of the white matter structural network in adults may help uncover the nature of ASD pathology in adulthood. METHOD This study investigated the topological properties of white matter structural network using diffusion tensor imaging and graph theory analysis in a sample of 32 adults with ASD compared to 35 matched typically developing (TD) controls. Group differences in global and nodal topological metrics were compared. The relationships between the altered network metrics and the severity of clinical symptoms were calculated. RESULTS Compared to TD controls, ASD patients exhibited decreased small-worldness and increased global efficiency. In addition, the reduced nodal efficiency and increased nodal degree were found in the frontal (e.g., the inferior frontal gyrus) and parietal (e.g., postcentral gyrus) regions. Furthermore, the altered topological metrics (e.g., increased global efficiency and reduced nodal efficiency) were correlated with the severity of ASD symptoms. CONCLUSION These results indicated that the complicatedly topological organization of the white matter structural network was abnormal and may play an essential role in the underlying pathological mechanism of ASD in adults.
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Affiliation(s)
- Yun Cai
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Jinghui Zhao
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Lian Wang
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China
| | - Yuanjun Xie
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710030, China.
| | - Xiaotang Fan
- Department of Developmental Neuropsychology, School of Psychology, Army Medical University, Chongqing 400038, China.
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10
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Peterson BS, Liu J, Dantec L, Newman C, Sawardekar S, Goh S, Bansal R. Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder. J Child Psychol Psychiatry 2022; 63:855-870. [PMID: 34762311 PMCID: PMC9091058 DOI: 10.1111/jcpp.13531] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/08/2021] [Indexed: 01/11/2023]
Abstract
BACKGROUND Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management. METHODS We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively. RESULTS Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants. CONCLUSIONS Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.
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Affiliation(s)
- Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
| | - Jiaqi Liu
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | - Louis Dantec
- École Polytechnique Universitaire de Marseille, France
| | | | - Siddhant Sawardekar
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027
| | | | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA 90027;,Keck School of Medicine at the University of Southern California, Los Angeles, CA 90033
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11
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Zhang Y, Qin B, Wang L, Zhang K, Song C, Chen J, Cai J, Li T. Corpus Callosum Volumes in Children with Autism Spectrum Disorders: Sex-Associated Differences. J Autism Dev Disord 2022; 53:2421-2429. [PMID: 35352234 DOI: 10.1007/s10803-022-05538-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/16/2022] [Indexed: 11/27/2022]
Abstract
This study aimed to analyze the relationship between sex and corpus callosum (CC) volume in children with autism spectrum disorders (ASD) aged 2-4 years. This prospective study included 50 children with ASD and 50 typically developing (TD) children aged 2-4 years. Midsagittal slices of the CCs of the participants were divided into five subregions using FreeSurfer software. The PMCC, AMCC and TCC volumes were significantly higher in ASD participants than in TD participants, and results were significant in females with ASD rather than in males with ASD (all P < 0.05). In toddlers with ASD, the CC volumes were increased and more pronounced in females than in males. This could be due to overgrowth of axons or/and axonal pruning disorders.
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Affiliation(s)
- Yun Zhang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
- Chongqing Engineering Research Center for Clinical Big-Data and Drug Evaluation, Medical Data Science, Academy of Chongqing Medical University, Chongqing, 400014, China
| | - Bin Qin
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
- Chongqing Engineering Research Center for Clinical Big-Data and Drug Evaluation, Medical Data Science, Academy of Chongqing Medical University, Chongqing, 400014, China
| | - Longlun Wang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
| | - Ke Zhang
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
| | - Cui Song
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
- Department of Endocrinology and Genetic Metabolic Disease, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Jie Chen
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
- Children Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Jinhua Cai
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China.
| | - Tingyu Li
- National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing, 400014, China.
- Children Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing, China.
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12
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Qin B, Wang L, Cai J, Li T, Zhang Y. Functional Brain Networks in Preschool Children With Autism Spectrum Disorders. Front Psychiatry 2022; 13:896388. [PMID: 35859600 PMCID: PMC9289162 DOI: 10.3389/fpsyt.2022.896388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE The present study aims to investigate the functional brain network characteristics of preschool children with autism spectrum disorder (ASD) through functional connectivity (FC) calculations using resting-state functional MRI (rs-fMRI) and graph theory analysis to better understand the pathogenesis of ASD and provide imaging evidence for the early assessment of this condition. METHODS A prospective study of preschool children including 32 with ASD (ASD group) and 22 healthy controls (HC)group was conducted in which all subjects underwent rs-fMRI scans, and then the differences in FC between the two groups was calculated, followed by graph-theoretic analysis to obtain the FC properties of the network. RESULTS In the calculation of FC, compared with the children in the HC group, significant increases or decreases in subnetwork connectivity was found in the ASD group. There were 25 groups of subnetworks with enhanced FC, of which the medial prefrontal and posterior cingulate gyrus and angular gyrus were all important components of the default mode network (DMN). There were 11 groups of subnetworks with weakened FC, including the hippocampus, parahippocampal gyrus, superior frontal gyrus, inferior temporal gyrus, precuneus, amygdala, and perirhinal cortex, with the hippocampus and parahippocampal gyrus predominating. In the network properties determined by graph theory, the clustering coefficient and local efficiency of the functional network was increased in the ASD group; specifically, compared with those in the HC group, nodes in the left subinsular frontal gyrus and the right middle temporal gyrus had increased efficiency, and nodes in the left perisylvian cortex, the left lingual gyrus, and the right hippocampus had decreased efficiency. CONCLUSION Alterations in functional brain networks are evident in preschool children with ASD and can be detected with sleep rs-fMRI, which is important for understanding the pathogenesis of ASD and assessing this condition early.
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Affiliation(s)
- Bin Qin
- Department of Radiology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.,Chongqing Engineering Research Center for Clinical Big Data and Drug Evaluation, Medical Data Science, Academy of Chongqing Medical University, Chongqing, China
| | - Longlun Wang
- Department of Radiology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Jinhua Cai
- Department of Radiology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Tingyu Li
- Children Nutrition Research Center, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Yun Zhang
- Department of Radiology, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Translational Medical Research in Cognitive Development and Learning and Memory Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.,Chongqing Engineering Research Center for Clinical Big Data and Drug Evaluation, Medical Data Science, Academy of Chongqing Medical University, Chongqing, China
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13
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Kim D, Lee JY, Jeong BC, Ahn JH, Kim JI, Lee ES, Kim H, Lee HJ, Han CE. Overconnectivity of the right Heschl's and inferior temporal gyrus correlates with symptom severity in preschoolers with autism spectrum disorder. Autism Res 2021; 14:2314-2329. [PMID: 34529363 PMCID: PMC9292809 DOI: 10.1002/aur.2609] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/26/2021] [Accepted: 08/30/2021] [Indexed: 01/12/2023]
Abstract
Previous studies have reported varying findings regarding the association of brain connectivity in autism spectrum disorder (ASD) with overconnectivity, underconnectivity, or both. Despite the emerging understanding that ASD is a developmental disconnection syndrome, very little is known about structural brain networks in preschool‐aged children with low‐functioning ASD. We aimed to investigate the structural brain connectivity of low‐functioning ASD using diffusion magnetic resonance imaging and graph theory to examine alterations in different brain network topologies and identify any correlations with the clinical severity of ASD in preschool‐aged children. Fifty‐two preschool‐aged children (28 with ASD and 24 with typical development) were included in the analysis. Graph‐based network analysis was performed to examine the global and local structural brain networks. Nodal network measures exhibited increased nodal strength in the right Heschl's gyrus, which was positively associated with all autistic clinical symptoms (Autism Diagnostic Observation Schedule and Childhood Autism Rating Scale [CARS]). The nodal strength of the right inferior temporal gyrus showed a moderate correlation with the CARS score. Using network‐based statistics, we identified a subnetwork with increased connections encompassing the right Heschl's gyrus and the right inferior temporal gyrus in preschool‐aged children with ASD. The asymmetric value in the inferior temporal gyrus exhibited right dominance of nodal strength in children with ASD compared to that in typically developing children. Our findings support the theory of aberrant brain growth and overconnectivity as the underlying mechanism of ASD and provides new insights into potential regional biomarkers that can detect low‐functioning ASD in preschool‐aged children.
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Affiliation(s)
- Daegyeom Kim
- Department of Electronics and Information Engineering, Korea University, Sejong, Republic of Korea
| | - Joo Young Lee
- Clinical Research Institute of Developmental Medicine, Seoul Hanyang University Hospital, Seoul, Republic of Korea
| | - Byeong Chang Jeong
- Department of Electronics and Information Engineering, Korea University, Sejong, Republic of Korea.,Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong, Republic of Korea
| | - Ja-Hye Ahn
- Department of Pediatrics, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Johanna Inhyang Kim
- Clinical Research Institute of Developmental Medicine, Seoul Hanyang University Hospital, Seoul, Republic of Korea.,Department of Child and Adolescent Psychiatry, Department of Psychiatry, Seoul Hanyang University Hospital, Seoul, Republic of Korea
| | - Eun Soo Lee
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Hyuna Kim
- Department of Child Psychotherapy, Hanyang University Graduate School of Medicine, Seoul, Republic of Korea
| | - Hyun Ju Lee
- Clinical Research Institute of Developmental Medicine, Seoul Hanyang University Hospital, Seoul, Republic of Korea.,Department of Pediatrics, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Cheol E Han
- Department of Electronics and Information Engineering, Korea University, Sejong, Republic of Korea.,Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology, Korea University, Sejong, Republic of Korea
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14
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Biagi L, Lenzi S, Cipriano E, Fiori S, Bosco P, Cristofani P, Astrea G, Pini A, Cioni G, Mercuri E, Tosetti M, Battini R. Neural substrates of neuropsychological profiles in dystrophynopathies: A pilot study of diffusion tractography imaging. PLoS One 2021; 16:e0250420. [PMID: 33939732 PMCID: PMC8092766 DOI: 10.1371/journal.pone.0250420] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 04/06/2021] [Indexed: 11/18/2022] Open
Abstract
Introduction Cognitive difficulties and neuropsychological alterations in Duchenne and Becker muscular dystrophy (DMD, BMD) boys are not yet sufficiently explored, although this topic could have a relevant impact, finding novel biomarkers of disease both at genetics and neuroimaging point of view. The current study aims to: 1) analyze the neuropsychological profile of a group of DMD and BMD boys without cognitive impairment with an assessment of their executive functions; 2) explore the structural connectivity in DMD, BMD, and age-matched controls focusing on cortico-subcortical tracts that connect frontal cortex, basal ganglia, and cerebellum via the thalamus; 3) explore possible correlations between altered structural connectivity and clinical neuropsychological measures. Materials and methods This pilot study included 15 boys (5 DMD subjects, 5 BMD subjects, and 5 age-matched typically developing, TD). They were assessed using a neuropsychological assessment protocol including cognitive and executive functioning assessment and performed a 1.5T MRI brain exam including advance Diffusion Weighted Imaging (DWI) method for tractography. Structural connectivity measurements were extracted along three specific tracts: Cortico-Ponto-Cerebellar Tract (CPCT), Cerebellar-Thalamic Tract (CTT), and Superior Longitudinal Fasciculus (SLF). Cortical-Spinal Tract (CST) was selected for reference, as control tract. Results Regarding intellectual functioning, a major impairment in executive functions compared to the general intellectual functioning was observed both for DMD (mean score = 86.20; SD = 11.54) and for BMD children (mean score = 88; SD = 3.67). Mean FA resulted tendentially always lower in DMD compared to both BMD and TD groups for all the examined tracts. The differences in FA were statistically significant for the right CTT (DMD vs BMD, p = 0.002, and DMD vs TD, p = 0.0015) and the right CPCT (DMD vs TD, p = 0.008). Concerning DMD, significant correlations emerged between FA-R-CTT and intellectual quotients (FIQ, p = 0.044; ρs = 0.821), and executive functions (Denomination Total, p = 0.044, ρs = 0.821; Inhibition Total, p = 0.019, ρs = 0.900). BMD showed a significant correlation between FA-R-CPCT and working memory index (p = 0.007; ρs = 0.949). Discussion and conclusion In this pilot study, despite the limitation of sample size, the findings support the hypothesis of the involvement of a cerebellar-thalamo-cortical loop for the neuropsychological profile of DMD, as the CTT and the CPCT are involved in the network and the related brain structures are known to be implied in executive functions. Our results suggest that altered WM connectivity and reduced fibre organization in cerebellar tracts, probably due to the lack of dystrophin in the brain, may render less efficient some neuropsychological functions in children affected by dystrophinopathies. The wider multicentric study could help to better establish the role of cerebellar connectivity in neuropsychological profile for dystrophinopathies, identifying possible novel diagnostic and prognostic biomarkers.
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Affiliation(s)
- Laura Biagi
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Calambrone, Pisa, Italy
| | - Sara Lenzi
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
| | - Emilio Cipriano
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Calambrone, Pisa, Italy
- Department of Physics, University of Pisa, Pisa, Italy
| | - Simona Fiori
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
| | - Paolo Bosco
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Calambrone, Pisa, Italy
| | - Paola Cristofani
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
| | - Guia Astrea
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
| | - Antonella Pini
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
| | - Giovanni Cioni
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eugenio Mercuri
- Pediatric Neurology Unit, Catholic University and Nemo Center, Policlinico Universitario Gemelli, Rome, Italy
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Fondazione Stella Maris, Calambrone, Pisa, Italy
| | - Roberta Battini
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
- * E-mail:
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15
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Li C, Li Y, Fu L, Wang Y, Cheng X, Cui X, Jiang J, Xiao T, Ke X, Fang H. The relationships between the topological properties of the whole-brain white matter network and the severity of autism spectrum disorder: A study from monozygotic twins. Neuroscience 2021; 465:60-70. [PMID: 33887385 DOI: 10.1016/j.neuroscience.2021.04.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
Twins provide a valuable perspective for exploring the pathological mechanism of autism spectrum disorder (ASD). We aim to analyze differences in the topological properties of the white matter (WM) network between monozygotic twins with ASD (MZCo-ASD) and children with typical development (TD). We enrolled 67 subjects aged 2-9 years. Twenty-three pairs of MZCo-ASD and 21 singleton children with TD completed clinical assessments and diffusion tensor imaging (DTI). Graph theory was used to compare the topological properties of the WM network between the two groups, and analyzed their correlations with the severity of clinical symptoms. We found that the global efficiency (Eg) of MZCo-ASD is weaker than that of TD children, while the shortest path length (Lp) of MZCo-ASD is longer than that of TD children, and MZCo-ASD have three unique hubs (the bilateral dorsolateral superior frontal gyrus and right insula). Eg and Lp were both correlated with the repetitive behavior scores of the Autism Diagnostic Interview-Revised (ADI-R) in the MZCo-ASD group, and the nodal efficiency of the dorsal superior frontal gyrus (SFGdor) was correlated with the ADI-R scores of repetitive behaviors. Left SFGdor nodal efficiency was correlated with Repetitive Behavior and Communication, two core symptoms of autism. The results implicated that MZCo-ASD had atypical brain structural network attributes and node distributions. Using MZCo-ASD, we found that the WM topological properties that correlate with the severity of ASD core symptoms were Eg, Lp, and the nodal efficiency of the SFGdor.
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Affiliation(s)
- Chunyan Li
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Yun Li
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Linyan Fu
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Yue Wang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xin Cheng
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xiwen Cui
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Jiying Jiang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Ting Xiao
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China
| | - Xiaoyan Ke
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China.
| | - Hui Fang
- Children's Mental Health Research Center, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing GuangZhou Road 264, Nanjing 210029, China.
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16
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Soma D, Hirosawa T, Hasegawa C, An KM, Kameya M, Hino S, Yoshimura Y, Nobukawa S, Iwasaki S, Tanaka S, Yaoi K, Sano M, Shiota Y, Naito N, Kikuchi M. Atypical Resting State Functional Neural Network in Children With Autism Spectrum Disorder: Graph Theory Approach. Front Psychiatry 2021; 12:790234. [PMID: 34970170 PMCID: PMC8712628 DOI: 10.3389/fpsyt.2021.790234] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 11/19/2021] [Indexed: 12/17/2022] Open
Abstract
Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60-89 months old) and for 25 typically developing (TD) control children (10 girls, 60-91 months old) in a resting state while gazing at a fixation cross. After signal sources were localized onto the Desikan-Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. Children with ASD were found to have significantly lower small-worldness in the beta band (p = 0.007) than TD children had. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores (p = 0.047). Significant relations were also inferred for the Social Awareness (p = 0.008) and Social Cognition (p = 0.015) sub-scales. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD.
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Affiliation(s)
- Daiki Soma
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Tetsu Hirosawa
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Chiaki Hasegawa
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Kyung-Min An
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Masafumi Kameya
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Shoryoku Hino
- Department of Neuropsychiatry, Ishikawa Prefectural Takamatsu Hospital, Kahoku, Japan
| | - Yuko Yoshimura
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,Faculty of Education, Institute of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Sou Nobukawa
- Department of Computer Science, Chiba Institute of Technology, Narashino, Japan
| | - Sumie Iwasaki
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Sanae Tanaka
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Ken Yaoi
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Masuhiko Sano
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Yuka Shiota
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Nobushige Naito
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
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17
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Phillips NS, Kesler SR, Scoggins MA, Glass JO, Cheung YT, Liu W, Banerjee P, Ogg RJ, Srivastava D, Pui CH, Robison LL, Reddick WE, Hudson MM, Krull KR. Connectivity of the Cerebello-Thalamo-Cortical Pathway in Survivors of Childhood Leukemia Treated With Chemotherapy Only. JAMA Netw Open 2020; 3:e2025839. [PMID: 33216140 PMCID: PMC7679952 DOI: 10.1001/jamanetworkopen.2020.25839] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
IMPORTANCE Treatment with contemporary chemotherapy-only protocols is associated with risk for neurocognitive impairment among survivors of childhood acute lymphoblastic leukemia (ALL). OBJECTIVE To determine whether concurrent use of methotrexate and glucocorticoids is associated with interference with the antioxidant system of the brain and damage and disruption of glucocorticoid-sensitive regions of the cerebello-thalamo-cortical network. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study was conducted from December 2016 to July 2019 in a single pediatric cancer tertiary care center. Participants included survivors of childhood ALL who were more than 5 years from cancer diagnosis, age 8 years or older, and treated on an institutional chemotherapy-only protocol. Age-matched community members were recruited as a control group. Data were analyzed from August 2017 to August 2020. EXPOSURE ALL treatment using chemotherapy-only protocols. MAIN OUTCOMES AND MEASURES This study compared brain volumes between survivors and individuals in a community control group and examined associations among survivors of methotrexate and dexamethasone exposure with neurocognitive outcomes. Functional and effective connectivity measures were compared between survivors with and without cognitive impairment. The Rey-Osterrieth complex figure test, a neurocognitive evaluation in which individuals are asked to copy a figure and then draw the figure from memory, was scored according to published guidelines and transformed into age-adjusted z scores based on nationally representative reference data and used to measure organization and planning deficits. β values for neurocognitive tests represented the amount of change in cerebellar volume or chemotherapy exposure associated with 1 SD change in neurocognitive outcome by z score (mm3/1 SD in z score for cerebellum, mm3/[g×hr/L] for dexamethasone and methotrexate AUC, and mm3/intrathecal count for total intrathecal count). RESULTS Among 302 eligible individuals, 218 (72%) participated in the study and 176 (58%) had usable magnetic resonance imaging (MRI) results. Among these, 89 (51%) were female participants and the mean (range) age was 6.8 (1-18) years at diagnosis and 14.5 (8-27) years at evaluation. Of 100 community individuals recruited as the control group, 82 had usable MRI results; among these, 35 (43%) were female individuals and the mean (range) age was 13.8 (8-26) years at evaluation. There was no significant difference in total brain volume between survivors and individuals in the control group. Survivors of both sexes showed decreased mean (SD) cerebellar volumes compared with the control population (female: 70 568 [6465] mm3 vs 75 134 [6780] mm3; P < .001; male: 77 335 [6210] mm3 vs 79 020 [7420] mm3; P < .001). In female survivors, decreased cerebellar volume was associated with worse performance in Rey-Osterrieth complex figure test (left cerebellum: β = 55.54; SE = 25.55; P = .03; right cerebellum: β = 52.57; SE = 25.50; P = .04) and poorer dominant-hand motor processing speed (ie, grooved pegboard performance) (left cerebellum: β = 82.71; SE = 31.04; P = .009; right cerebellum: β = 91.06; SE = 30.72; P = .004). In female survivors, increased number of intrathecal treatments (ie, number of separate injections) was also associated with Worse Rey-Osterrieth test performance (β = -0.154; SE = 0.063; P = .02), as was increased dexamethasone exposure (β = -0.0014; SE = 0.0005; P = .01). Executive dysfunction was correlated with increased global efficiency between smaller brain regions (Pearson r = -0.24; P = .01) compared with individuals without dysfunction. Anatomical connectivity showed differences between impaired and nonimpaired survivors. Analysis of variance of effective-connectivity weights identified a significant interaction association (F = 3.99; P = .02) among the direction and strength of connectivity between the cerebellum and DLPFC, female sex, and executive dysfunction. Finally, no effective connectivity was found between the precuneus and DLPFC in female survivors with executive dysfunction. CONCLUSIONS AND RELEVANCE These findings suggest that dexamethasone exposure was associated with smaller cerebello-thalamo-cortical regions in survivors of ALL and that disruption of effective connectivity was associated with impairment of executive function in female survivors.
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Affiliation(s)
- Nicholas S. Phillips
- Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
- Department of Oncology, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Shelli R. Kesler
- Now with School of Nursing, University of Texas at Austin
- Department of Neuro-oncology, University of Texas MD Anderson Cancer Center, Houston
| | - Matthew A. Scoggins
- Department of Diagnostic Imaging, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - John O. Glass
- Department of Diagnostic Imaging, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Yin Ting Cheung
- School of Pharmacy, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China
| | - Wei Liu
- Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Pia Banerjee
- Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Robert J. Ogg
- Department of Diagnostic Imaging, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Deokumar Srivastava
- Department of Biostatistics, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Ching-Hon Pui
- Department of Oncology, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Leslie L. Robison
- Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Wilburn E. Reddick
- Department of Diagnostic Imaging, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Melissa M. Hudson
- Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
- Department of Oncology, St Jude Children’s Research Hospital, Memphis, Tennessee
| | - Kevin R. Krull
- Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital, Memphis, Tennessee
- Department of Psychology, St Jude Children’s Research Hospital, Memphis, Tennessee
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Kazeminejad A, Sotero RC. Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification. Front Neurosci 2019; 12:1018. [PMID: 30686984 PMCID: PMC6335365 DOI: 10.3389/fnins.2018.01018] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 12/18/2018] [Indexed: 01/16/2023] Open
Abstract
Automatic algorithms for disease diagnosis are being thoroughly researched for use in clinical settings. They usually rely on pre-identified biomarkers to highlight the existence of certain problems. However, finding such biomarkers for neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) has challenged researchers for many years. With enough data and computational power, machine learning (ML) algorithms can be used to interpret the data and extract the best biomarkers from thousands of candidates. In this study, we used the fMRI data of 816 individuals enrolled in the Autism Brain Imaging Data Exchange (ABIDE) to introduce a new biomarker extraction pipeline for ASD that relies on the use of graph theoretical metrics of fMRI-based functional connectivity to inform a support vector machine (SVM). Furthermore, we split the dataset into 5 age groups to account for the effect of aging on functional connectivity. Our methodology achieved better results than most state-of-the-art investigations on this dataset with the best model for the >30 years age group achieving an accuracy, sensitivity, and specificity of 95, 97, and 95%, respectively. Our results suggest that measures of centrality provide the highest contribution to the classification power of the models.
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Affiliation(s)
- Amirali Kazeminejad
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada
| | - Roberto C Sotero
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.,Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada.,Department of Radiology, University of Calgary, Calgary, AB, Canada
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