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Lyu K, Li J, Chen M, Li W, Zhang W, Hu M, Zhang Y, Feng X. A bibliometric analysis of autism spectrum disorder signaling pathways research in the past decade. Front Psychiatry 2024; 15:1304916. [PMID: 38410675 PMCID: PMC10895046 DOI: 10.3389/fpsyt.2024.1304916] [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: 09/30/2023] [Accepted: 01/29/2024] [Indexed: 02/28/2024] Open
Abstract
Background This study employs bibliometric methods to comprehensively understand the fundamental structure of research about Autism Spectrum Disorder (ASD) Signaling Pathways by examining key indicators such as nations, institutions, journals, authors, and keywords. Methodology We utilized the WoScc database to retrieve literature relevant to ASD Signaling Pathways published between 2013 and 2023. Through visual analysis and tools like CiteSpace and VosViewer, we explored nations, institutions, journals, authors, and keywords, thereby constructing relevant networks. Results 26 The study encompasses 1,396 articles, revealing a consistent increase in publications. The United States, China, and Germany are leading nations in this literature. Regarding research institutions, the University of California system and Eric Klann have garnered significant attention due to their substantial contributions to the field of ASD Signaling Pathways. Most relevant research is published in the journal "Molecular Autism." Research interests are concentrated across various themes, including "elevating neuronal β-catenin levels," "Tunisian children," "Fmr1 knockout (KO) mice," "de novo mutations," "autistic children," "local translation," "propionic acid-induced mouse models," "neurosystems," "glucose metabolism," and "neuronal migration." Future research may emphasize exploring aspects such as gut microbiota, genes, stress, maternal immune activation, memory, and neurodevelopmental disorders of ASD. Conclusion This study, through bibliometric analysis of key indicators such as nations, institutions, journals, authors, and keywords, provides a comprehensive overview of the current state of research on ASD Signaling Pathways. These investigations predominantly focus on molecular mechanisms, animal model studies, population-based research, and the structure and function of neurosystems. Future research directions are also clearly proposed. First, in-depth research on the genes and neurodevelopmental disorders associated with ASD will continue to reveal the genetic basis and provide support for precise treatments. At the same time, attention to the gut microbiota will help explore its association with ASD, which may provide clues for new treatments. In addition, the relationship between stress and ASD will become the focus of research to understand better the emotional and behavioral characteristics of ASD patients in stressful situations. Maternal immune activation will also be further studied to explore how environmental factors influence the risk and development of ASD. Finally, a deeper understanding of the cognitive functions of patients with ASD, especially memory and learning, will help develop individualized treatment strategies to improve patients' quality of life. These directions will work together and are expected to provide a more comprehensive understanding of Signaling Pathways research in ASD and provide new ideas and opportunities for future intervention and treatment.
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Affiliation(s)
- Kaifeng Lyu
- Faculty of Chinese Medicine, Macau University of Science and Technology, Macau, China
| | - Jiangshan Li
- College of Acupuncture, Moxibustion, Massage, and Rehabilitation, Hunan University of Traditional Chinese Medicine, Changsha, China
| | - Min Chen
- Faculty of Chinese Medicine and State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau, China
| | - Wu Li
- College of Acupuncture, Moxibustion, Massage, and Rehabilitation, Hunan University of Traditional Chinese Medicine, Changsha, China
| | - Wei Zhang
- Pediatrics One, The First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, China
| | - Meichao Hu
- Rehabilitation Department, Chifeng Obstetrics and Gynecology Hospitalal, Chifeng, China
| | - Yuxing Zhang
- College of Acupuncture, Moxibustion, Massage, and Rehabilitation, Hunan University of Traditional Chinese Medicine, Changsha, China
| | - Xiang Feng
- College of Acupuncture, Moxibustion, Massage, and Rehabilitation, Hunan University of Traditional Chinese Medicine, Changsha, China
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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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Lin Q, Shi Y, Huang H, Jiao B, Kuang C, Chen J, Rao Y, Zhu Y, Liu W, Huang R, Lin J, Ma L. Functional brain network alterations in the co-occurrence of autism spectrum disorder and attention deficit hyperactivity disorder. Eur Child Adolesc Psychiatry 2024; 33:369-380. [PMID: 36800038 DOI: 10.1007/s00787-023-02165-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 02/05/2023] [Indexed: 02/18/2023]
Abstract
Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are two highly prevalent and commonly co-occurring neurodevelopmental disorders. The neural mechanisms underpinning the comorbidity of ASD and ADHD (ASD + ADHD) remain unclear. We focused on the topological organization and functional connectivity of brain networks in ASD + ADHD patients versus ASD patients without ADHD (ASD-only). Resting-state functional magnetic resonance imaging (rs-fMRI) data from 114 ASD and 161 typically developing (TD) individuals were obtained from the Autism Brain Imaging Data Exchange II. The ASD patients comprised 40 ASD + ADHD and 74 ASD-only individuals. We constructed functional brain networks for each group and performed graph-theory and network-based statistic (NBS) analyses. Group differences between ASD + ADHD and ASD-only were analyzed at three levels: nodal, global, and connectivity. At the nodal level, ASD + ADHD exhibited topological disorganization in the temporal and occipital regions, compared with ASD-only. At the global level, ASD + ADHD and ASD-only displayed no significant differences. At the connectivity level, the NBS analysis revealed that ASD + ADHD showed enhanced functional connectivity between the prefrontal and frontoparietal regions, as well as between the orbitofrontal and occipital regions, compared with ASD-only. The hippocampus was the shared region in aberrant functional connectivity patterns in ASD + ADHD and ASD-only compared with TD. These findings suggests that ASD + ADHD displays altered topology and functional connectivity in the brain regions that undertake social cognition, language processing, and sensory processing.
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Affiliation(s)
- Qiwen Lin
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Yafei Shi
- School of Fundamental Medical Science, Guangzhou University of Chinese Medicine, Guangzhou, 510006, People's Republic of China
| | - Huiyuan Huang
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Bingqing Jiao
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Changyi Kuang
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Jiawen Chen
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Yuyang Rao
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Yunpeng Zhu
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Wenting Liu
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China
| | - Ruiwang Huang
- Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, School of Psychology, South China Normal University, Guangzhou, 510631, People's Republic of China
| | - Jiabao Lin
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China.
- Institut Des Sciences Cognitives Marc Jeannerod, CNRS UMR 5229, Université Claude Bernard, Lyon 1, Lyon, France.
| | - Lijun Ma
- School of Public Health and Management, Guangzhou University of Chinese Medicine, University Town, No.232, Huandong Road, Guangzhou, 510006, People's Republic of China.
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Liu J, Liu QR, Wu ZM, Chen QR, Chen J, Wang Y, Cao XL, Dai MX, Dong C, Liu Q, Zhu J, Zhang LL, Li Y, Wang YF, Liu L, Yang BR. Specific brain imaging alterations underlying autistic traits in children with attention-deficit/hyperactivity disorder. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2023; 19:20. [PMID: 37986005 PMCID: PMC10658985 DOI: 10.1186/s12993-023-00222-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 11/07/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND Autistic traits (ATs) are frequently reported in children with Attention-Deficit/Hyperactivity Disorder (ADHD). This study aimed to examine ATs in children with ADHD from both behavioral and neuroimaging perspectives. METHODS We used the Autism Spectrum Screening Questionnaire (ASSQ) to assess and define subjects with and without ATs. For behavioral analyses, 67 children with ADHD and ATs (ADHD + ATs), 105 children with ADHD but without ATs (ADHD - ATs), and 44 typically developing healthy controls without ATs (HC - ATs) were recruited. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data and analyzed the mean amplitude of low-frequency fluctuation (mALFF) values (an approach used to depict different spontaneous brain activities) in a sub-sample. The imaging features that were shared between ATs and ADHD symptoms or that were unique to one or the other set of symptoms were illustrated as a way to explore the "brain-behavior" relationship. RESULTS Compared to ADHD-ATs, the ADHD + ATs group showed more global impairment in all aspects of autistic symptoms and higher hyperactivity/impulsivity (HI). Partial-correlation analysis indicated that HI was significantly positively correlated with all aspects of ATs in ADHD. Imaging analyses indicated that mALFF values in the left middle occipital gyrus (MOG), left parietal lobe (PL)/precuneus, and left middle temporal gyrus (MTG) might be specifically related to ADHD, while those in the right MTG might be more closely associated with ATs. Furthermore, altered mALFF in the right PL/precuneus correlated with both ADHD and ATs, albeit in diverse directions. CONCLUSIONS The co-occurrence of ATs in children with ADHD manifested as different behavioral characteristics and specific brain functional alterations. Assessing ATs in children with ADHD could help us understand the heterogeneity of ADHD, further explore its pathogenesis, and promote clinical interventions.
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Affiliation(s)
- Juan Liu
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Qian-Rong Liu
- Peking University Sixth Hospital/Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Zhao-Min Wu
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Qiao-Ru Chen
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Jing Chen
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Yuan Wang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Xiao-Lan Cao
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Mei-Xia Dai
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Chao Dong
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Qiao Liu
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Jun Zhu
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Lin-Lin Zhang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Ying Li
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China
| | - Yu-Feng Wang
- Peking University Sixth Hospital/Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
| | - Bin-Rang Yang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen, Guangdong, China.
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Chou HC, Lin HC, Huang KH, Chang YC. Associations between neonatal jaundice and autism spectrum disorder or attention deficit hyperactivity disorder: Nationwide population based cohort study. J Formos Med Assoc 2023; 122:1150-1157. [PMID: 37225632 DOI: 10.1016/j.jfma.2023.05.010] [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: 01/06/2023] [Revised: 05/01/2023] [Accepted: 05/10/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND/PURPOSE Neonatal jaundice might result brain insults. Both autistic spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are developmental disorders, which might result from early brain injury at neonatal period. We aimed to explore the association between neonatal jaundice treated with phototherapy and the ASD or ADHD. METHODS This retrospective nationwide population cohort study was based on a nationally representative database of Taiwan, and neonates born from 2004 to 2010 were enrolled. All eligible infants were divided into 4 groups, without jaundice, jaundice with no treatment, jaundice with simple phototherapy only and jaundice with intensive phototherapy or blood exchange transfusion (BET). Each infant was follow-up until the date of incident primary outcomes, death, or 7-year-old, whichever occurred first. Primary outcomes were ASD, ADHD. Using cox proportional hazard model to analyze their associations. RESULTS In total, 118,222 infants with neonatal jaundice were enrolled, including diagnosed only (7260), simple phototherapy (82,990), intensive phototherapy or BET (27,972 infants). The cumulative incidences of ASD in each group was 0.57%, 0.81%, 0.77%, and 0.83%, respectively. The cumulative incidences of ADHD in each group was 2.83%, 4.04%, 3.52% and 3.48%, respectively. Jaundice groups were significantly associated with ASD, ADHD, or either one, even after all other extraneous maternal and neonatal variables were adjusted. After stratification, the associations were still existed in subgroup with birth weights ≥2500 grams and in male subgroup. CONCLUSION Neonatal jaundice correlated with the ASD and ADHD. The associations were significant in infants of both sexes and with birth weights larger than 2500 grams.
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Affiliation(s)
- Hung-Chieh Chou
- Department of Pediatrics, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Pediatrics, National Taiwan University Hospital, Yun-Lin Branch, Yun-Lin, Taiwan
| | - Hung-Chih Lin
- Division of Neonatology, China Medical University Children's Hospital, Taichung, Taiwan; School of Chinese Medicine, China Medical University, Taichung, Taiwan; Asia University Hospital, Asia University, Taichung, Taiwan
| | - Kuang-Hua Huang
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Yu-Chia Chang
- Department of Long Term Care, College of Health and Nursing, National Quemoy University, Kinmen County, Taiwan; Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan.
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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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Mareva S, Akarca D, Holmes J. Transdiagnostic profiles of behaviour and communication relate to academic and socioemotional functioning and neural white matter organisation. J Child Psychol Psychiatry 2023; 64:217-233. [PMID: 36127748 PMCID: PMC10087495 DOI: 10.1111/jcpp.13685] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/07/2022] [Indexed: 01/17/2023]
Abstract
BACKGROUND Behavioural and language difficulties co-occur in multiple neurodevelopmental conditions. Our understanding of these problems has arguably been slowed by an overreliance on study designs that compare diagnostic groups and fail to capture the overlap across different neurodevelopmental disorders and the heterogeneity within them. METHODS We recruited a large transdiagnostic cohort of children with complex needs (N = 805) to identify distinct subgroups of children with common profiles of behavioural and language strengths and difficulties. We then investigated whether and how these data-driven groupings could be distinguished from a comparison sample (N = 158) on measures of academic and socioemotional functioning and patterns of global and local white matter connectome organisation. Academic skills were assessed via standardised measures of reading and maths. Socioemotional functioning was captured by the parent-rated version of the Strengths and Difficulties Questionnaire. RESULTS We identified three distinct subgroups of children, each with different levels of difficulties in structural language, pragmatic communication, and hot and cool executive functions. All three subgroups struggled with academic and socioemotional skills relative to the comparison sample, potentially representing three alternative but related developmental pathways to difficulties in these areas. The children with the weakest language skills had the most widespread difficulties with learning, whereas those with more pronounced difficulties with hot executive skills experienced the most severe difficulties in the socioemotional domain. Each data-driven subgroup could be distinguished from the comparison sample based on both shared and subgroup-unique patterns of neural white matter organisation. Children with the most pronounced deficits in language, cool executive, or hot executive function were differentiated from the comparison sample by altered connectivity in predominantly thalamocortical, temporal-parietal-occipital, and frontostriatal circuits, respectively. CONCLUSIONS These findings advance our understanding of commonly co-morbid behavioural and language problems and their relationship to behavioural outcomes and neurobiological substrates.
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Affiliation(s)
- Silvana Mareva
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Danyal Akarca
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Joni Holmes
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- School of Psychology, Faculty of Social Sciences, University of East Anglia, Norwich, UK
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Hung Y, Dallenbach NT, Green A, Gaillard S, Capella J, Hoskova B, Vater CH, Cooper E, Rudberg N, Takahashi A, Gabrieli JDE, Joshi G. Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study. Psychiatry Res 2023; 320:115039. [PMID: 36640678 DOI: 10.1016/j.psychres.2022.115039] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/25/2022] [Accepted: 12/27/2022] [Indexed: 12/29/2022]
Abstract
Attention deficit/hyperactivity disorder (ADHD), a common neurodevelopmental disorder, is the most frequent comorbid condition seen in children with autism spectrum disorder (ASD). This high comorbidity between ADHD and ASD worsens symptom manifestations and complicates disease treatment and prognosis. It remains unclear whether individuals suffering with both ADHD and ASD, compared to individuals with ADHD only, share overlapping neural correlates associated with ADHD neuropathology, or exhibit a distinct neuropathological profile. Answering this question is critical to the understanding of treatment outcomes for the challenging comorbid ADHD symptoms. To identify the shared and the differentiated neural correlates of the comorbidity mechanisms of ADHD with ASD, we use diffusion tensor imaging (DTI) to characterize white-matter microstructure integrity in youth diagnosed with ADHD+ASD and youth with ADHD-only (excluding both the diagnosis and symptoms of ASD) compared with a healthy control group. Results show that the ADHD-only cohort exhibits impaired microstructural integrity (lower fractional anisotropy, FA) in the callosal-cingulum (CC-CG) tracts compared to the control cohort. The ADHD+ASD comorbid cohort shows impaired FA in an overlapping region within the CC-CG tracts and, additionally, shows impaired FA in the frontolimbic tracts including the uncinate fasciculus and anterior thalamic radiation. Across all participants, FA in the CC-CG showed a significantly negative relationship with the degree of ADHD symptom severity. Findings of this study suggest a specific role of CC-CG underlying ADHD neuropathology and symptom manifestations, and when comorbid with ASD a shared ADHD profile with a shift toward an anterior-brain, frontal impact. Results of this study may facilitate future targeted therapeutics and assist in diagnostic precision for individuals suffering with differing levels of comorbid ADHD with ASD, and ultimately contribute to improve prognostication and outcomes for these two highly prevalent and comorbid neurodevelopmental disorders.
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Affiliation(s)
- Yuwen Hung
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology-Harvard University, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, MA, USA.
| | - Nina T Dallenbach
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA
| | - Allison Green
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA
| | - Schuyler Gaillard
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology-Harvard University, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, MA, USA
| | - James Capella
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology-Harvard University, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, MA, USA
| | - Barbara Hoskova
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA
| | - Chloe Hutt Vater
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA
| | - Ellese Cooper
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA
| | - Nicole Rudberg
- Health Sciences, Western University, 1151 Richmond St, London, Ontario, Canada
| | - Atsushi Takahashi
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology-Harvard University, Cambridge, MA, USA
| | - John D E Gabrieli
- Athinoula A. Martinos Imaging Center at the McGovern Institute for Brain Research, Massachusetts Institute of Technology-Harvard University, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, MA, USA
| | - Gagan Joshi
- Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Kangarani-Farahani M, Izadi-Najafabadi S, Zwicker JG. How does brain structure and function on MRI differ in children with autism spectrum disorder, developmental coordination disorder, and/or attention deficit hyperactivity disorder? Int J Dev Neurosci 2022; 82:681-715. [PMID: 36084947 DOI: 10.1002/jdn.10228] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 08/22/2022] [Accepted: 09/05/2022] [Indexed: 11/09/2022] Open
Abstract
AIM The purpose of this study was to systematically review the neural similarities and differences in brain structure and function, measured by magnetic resonance imaging (MRI), in children with neurodevelopmental disorders that commonly co-occur to understand if and how they have shared neuronal characteristics. METHOD Using systematic review methodology, the following databases were comprehensively searched: MEDLINE, EMBASE, CINAHL, CENTRAL, PsycINFO, and ProQuest from the earliest record up to December 2021. Inclusion criteria were: (1) peer-reviewed studies, case reports, or theses; (2) children under 18 years of age with at least one of the following neurodevelopmental disorders: autism spectrum disorder (ASD), attention hyperactivity deficit disorder (ADHD), developmental coordination disorder (DCD), and their co-occurrence; (3) studies based on MRI modalities (i.e., structural MRI, diffusion tensor imaging (DTI), and resting-state fMRI). Thirty-one studies that met the inclusion criteria were included for quality assessment by two independent reviewers using the Appraisal tool for Cross-Sectional Studies (AXIS). RESULTS Studies compared brain structure and function of children with DCD and ADHD (n=6), DCD and ASD (n=1), ASD and ADHD (n=17), and various combinations of these co-occurring conditions (n=7). Structural neuroimaging (n=15) was the most commonly reported modality, followed by resting-state (n=8), DTI (n=5), and multi-modalities (n=3). INTERPRETATION Evidence indicated that the neural correlates of the co-occurring conditions were more widespread and distinct compared to a single diagnosis. The majority of findings (77%) suggested that each neurodevelopmental disorder had more distinct neural correlates than shared neural features, suggesting that each disorder is distinct despite commonly co-occurring with each other. As the number of papers examining the co-occurrence of ASD, DCD, and/or ADHD was limited and most findings were not corrected for multiple comparisons, these results must be interpreted with caution.
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Affiliation(s)
- Melika Kangarani-Farahani
- Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada.,BC Children's Hospital Research Institute, Vancouver, Canada
| | - Sara Izadi-Najafabadi
- Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada.,BC Children's Hospital Research Institute, Vancouver, Canada
| | - Jill G Zwicker
- BC Children's Hospital Research Institute, Vancouver, Canada.,Department of Occupational Science & Occupational Therapy, University of British Columbia, Vancouver, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, Canada.,CanChild Centre for Childhood Disability Research, Hamilton, Canada
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Bu X, Cao M, Huang X, He Y. The structural connectome in ADHD. PSYCHORADIOLOGY 2021; 1:257-271. [PMID: 38666220 PMCID: PMC10939332 DOI: 10.1093/psyrad/kkab021] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/12/2021] [Accepted: 12/13/2021] [Indexed: 02/05/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) has been conceptualized as a brain dysconnectivity disorder. In the past decade, noninvasive diffusion magnetic resonance imaging (dMRI) studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome, and that these alterations are associated with core symptoms and cognitive deficits in patients. This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-, tractography-, and network-based perspectives. Voxel- and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts, the corpus callosum, the corticospinal tracts, and the cingulum bundle in patients with ADHD. Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes. The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification. These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation. However, given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations, these ADHD-related white matter alterations are still far from informing clinical practice. Future studies with larger and more homogeneous samples are needed to validate the consistency of current results; advanced dMRI techniques can help to generate much more precise estimation of white matter pathways and assure specific fiber configurations; and finally, dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.
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Affiliation(s)
- Xuan Bu
- 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
| | - Miao Cao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai 200433, China
| | - Xiaoqi Huang
- Huaxi MR Research Center, West China Hospital of Sichuan University, Chengdu 610041, 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
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