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Wang Y, Ma L, Wang J, Ding Y, Liu N, Men W, Tan S, Gao JH, Qin S, He Y, Dong Q, Tao S. The neural and genetic underpinnings of different developmental trajectories of Attention-Deficit/Hyperactivity Symptoms in children and adolescents. BMC Med 2024; 22:223. [PMID: 38831366 PMCID: PMC11149188 DOI: 10.1186/s12916-024-03449-1] [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: 09/13/2023] [Accepted: 05/28/2024] [Indexed: 06/05/2024] Open
Abstract
BACKGROUND The trajectory of attention-deficit hyperactivity disorder (ADHD) symptoms in children and adolescents, encompassing descending, stable, and ascending patterns, delineates their ADHD status as remission, persistence or late onset. However, the neural and genetic underpinnings governing the trajectory of ADHD remain inadequately elucidated. METHODS In this study, we employed neuroimaging techniques, behavioral assessments, and genetic analyses on a cohort of 487 children aged 6-15 from the Children School Functions and Brain Development project at baseline and two follow-up tests for 1 year each (interval 1: 1.14 ± 0.32 years; interval 2: 1.14 ± 0.30 years). We applied a Latent class mixed model (LCMM) to identify the developmental trajectory of ADHD symptoms in children and adolescents, while investigating the neural correlates through gray matter volume (GMV) analysis and exploring the genetic underpinnings using polygenic risk scores (PRS). RESULTS This study identified three distinct trajectories (ascending-high, stable-low, and descending-medium) of ADHD symptoms from childhood through adolescence. Utilizing the linear mixed-effects (LME) model, we discovered that attention hub regions served as the neural basis for these three developmental trajectories. These regions encompassed the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), responsible for inhibitory control; the right inferior parietal lobule (IPL), which facilitated conscious focus on exogenous stimuli; and the bilateral middle frontal gyrus/precentral gyrus (MFG/PCG), accountable for regulating both dorsal and ventral attention networks while playing a crucial role in flexible modulation of endogenous and extrinsic attention. Furthermore, our findings revealed that individuals in the ascending-high group exhibited the highest PRS for ADHD, followed by those in the descending-medium group, with individuals in the stable-low group displaying the lowest PRS. Notably, both ascending-high and descending-medium groups had significantly higher PRS compared to the stable-low group. CONCLUSIONS The developmental trajectory of ADHD symptoms in the general population throughout childhood and adolescence can be reliably classified into ascending-high, stable-low, and descending-medium groups. The bilateral MFG/PCG, left ACC/mPFC, and right IPL may serve as crucial brain regions involved in attention processing, potentially determining these trajectories. Furthermore, the ascending-high pattern of ADHD symptoms exhibited the highest PRS for ADHD.
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Affiliation(s)
- Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Shuping Tan
- Psychiatry Research Center, Beijing HuiLongGuan Hospital, Peking University, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
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Marrero K, Aruljothi K, Delgadillo C, Kabbara S, Swatch L, Zagha E. Goal-Directed Learning is Multidimensional and Accompanied by Diverse and Widespread Changes in Neocortical Signaling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.02.13.528412. [PMID: 36824924 PMCID: PMC9948952 DOI: 10.1101/2023.02.13.528412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
New tasks are often learned in stages with each stage reflecting a different learning challenge. Accordingly, each learning stage is likely mediated by distinct neuronal processes. And yet, most rodent studies of the neuronal correlates of goal-directed learning focus on individual outcome measures and individual brain regions. Here, we longitudinally studied mice from naïve to expert performance in a head-fixed, operant conditioning whisker discrimination task. In addition to tracking the primary behavioral outcome of stimulus discrimination, we tracked and compared an array of object-based and temporal-based behavioral measures. These behavioral analyses identify multiple, partially overlapping learning stages in this task, consistent with initial response implementation, early stimulus-response generalization, and late response inhibition. To begin to understand the neuronal foundations of these learning processes, we performed widefield Ca2+ imaging of dorsal neocortex throughout learning and correlated behavioral measures with neuronal activity. We found distinct and widespread correlations between neocortical activation patterns and various behavioral measures. For example, improvements in sensory discrimination correlated with target stimulus evoked activations of licking-related cortices along with distractor stimulus evoked global cortical suppression. Our study reveals multidimensional learning for a simple goal-directed learning task and generates hypotheses for the neuronal modulations underlying these various learning processes.
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Affiliation(s)
- Krista Marrero
- Neuroscience Graduate Program, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
| | - Krithiga Aruljothi
- Department of Psychology, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
| | - Christian Delgadillo
- Division of Biomedical Sciences, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
| | - Sarah Kabbara
- Neuroscience Graduate Program, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
| | - Lovleen Swatch
- College of Natural & Agricultural Sciences, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
| | - Edward Zagha
- Neuroscience Graduate Program, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
- Department of Psychology, University of California, Riverside 900 University Avenue, Riverside CA 92521 USA
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Wang X, Guo Y, Xu J, Xiao Y, Fu Y. Decreased gray matter volume in the anterior cerebellar of attention deficit/hyperactivity disorder comorbid oppositional defiant disorder children with associated cerebellar-cerebral hyperconnectivity: insights from a combined structural MRI and resting-state fMRI study. Int J Dev Neurosci 2024. [PMID: 38795021 DOI: 10.1002/jdn.10349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 05/06/2024] [Accepted: 05/13/2024] [Indexed: 05/27/2024] Open
Abstract
Attention deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) are highly comorbid. Many prior investigations have found that ADHD relates to anatomical abnormalities in gray matter. The abnormal gray matter of ADHD comorbid ODD is still poorly understood. This study aimed to explore the effect of comorbid ODD on gray matter volume (GMV) and functional alterations in ADHD. All data were provided by the ADHD-200 Preprocessed Repository, including 27 ADHD-only children, 27 ADHD + ODD children, and 27 healthy controls aged 9-14 years. Voxel-based morphometry (VBM) and functional connectivity (FC) of resting-state functional magnetic resonance imaging (fMRI) were used to compare the difference in GMV and FC between ADHD + ODD, ADHD-only, and healthy children. The results showed that ADHD children with comorbid ODD had a more significant reduction in cerebellar volume, mainly in the anterior regions of the cerebellum (Cerebellum_4_5). The Cerebellum_4_5 showed increased functional connectivity with multiple cortical regions. These brain regions include numerous executive functioning (EF) and brain default mode network (DMN) nodes. The GMV abnormalities and excessive connectivity between brain regions may further exacerbate the emotional and cognitive deficits associated with ADHD.
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Affiliation(s)
- Xin Wang
- Department of Radiology, The First People's Hospital of Yancheng, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, People's Republic of China
| | - Yan Guo
- Department of Neurology, The First People's Hospital of Yancheng, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, People's Republic of China
| | - Jin Xu
- Department of Radiology, The First People's Hospital of Yancheng, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, People's Republic of China
| | - Yong Xiao
- Department of Radiology, The First People's Hospital of Yancheng, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, People's Republic of China
| | - Yigang Fu
- Department of Radiology, The First People's Hospital of Yancheng, The Yancheng Clinical College of Xuzhou Medical University, Yancheng, People's Republic of China
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4
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Wang Y, Ma L, Wang J, Ding Y, Men W, Tan S, Gao JH, Qin S, He Y, Dong Q, Tao S. Connections Between the Middle Frontal Gyrus and the Dorsoventral Attention Network Are Associated With the Development of Attentional Symptoms. Biol Psychiatry 2024:S0006-3223(24)01291-5. [PMID: 38718879 DOI: 10.1016/j.biopsych.2024.04.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/24/2024] [Accepted: 04/29/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND The right middle frontal gyrus (MFG) has been proposed as a convergence site for the dorsal attention network (DAN) and ventral attention network (VAN), regulating both networks and enabling flexible modulation of attention. However, it is unclear whether the connections between the right MFG and these networks can predict changes in attention-deficit/hyperactivity disorder (ADHD) symptoms. METHODS This study used data from the Children School Functions and Brain Development project (N = 713, 56.2% boys). Resting-state functional magnetic resonance imaging was employed to analyze the connections of the right MFG with the DAN/VAN; connectome-based predictive modeling was applied for longitudinal prediction, and ADHD polygenic risk scores were used for genetic analysis. RESULTS ADHD symptoms were associated with the connections between the right MFG and DAN subregion, including the frontal eye field, as well as the VAN subregions, namely the inferior parietal lobule and inferior frontal gyrus. Furthermore, these connections of the right MFG with the frontal eye field, the inferior parietal lobule, and the inferior frontal gyrus could significantly predict changes in ADHD symptoms over 1 year and mediate the prediction of ADHD symptom changes by polygenic risk scores for ADHD. Finally, the validation samples confirmed that the functional connectivity between the right MFG and the frontal eye field/inferior parietal lobule in patients with ADHD was significantly weaker than that in typically developing control participants, and this difference disappeared after medication. CONCLUSIONS The connection of the right MFG with the DAN and VAN can serve as a predictive indicator for changes in ADHD symptoms over the following year, while also mediating the prediction of ADHD symptom changes by a polygenic risk score for ADHD. These findings hold promise as potential biomarkers for early identification of children who are at risk of developing ADHD.
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Affiliation(s)
- Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jiali Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yuyin Ding
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Shuping Tan
- Psychiatry Research Center, Beijing HuiLongGuan Hospital, Peking University, Beijing, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
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Kawata NYS, Nishitani S, Yao A, Takiguchi S, Mizuno Y, Mizushima S, Makita K, Hamamura S, Saito DN, Okazawa H, Fujisawa TX, Tomoda A. Brain structures and functional connectivity in neglected children with no other types of maltreatment. Neuroimage 2024; 292:120589. [PMID: 38575041 DOI: 10.1016/j.neuroimage.2024.120589] [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: 04/19/2023] [Revised: 03/11/2024] [Accepted: 03/25/2024] [Indexed: 04/06/2024] Open
Abstract
Child maltreatment can adversely affect brain development, leading to vulnerabilities in brain structure and function and various psychiatric disorders. Among the various types of child maltreatment, neglect has the highest incidence rate (76.0%); however, data on its sole adverse influence on the brain remain limited. This case-control brain magnetic resonance imaging (MRI) study identified the changes in gray matter structure and function that distinguish neglected children with no other type of maltreatment (Neglect group, n = 23) from typically developing children (TD group, n = 140), and investigated the association between these structural and functional differences and specific psychosocial phenotypes observed in neglected children. Our results showed that the Neglect group had a larger right and left anterior cingulate cortex (R/L.ACC) and smaller left angular gyrus (L.AG) gray matter volume. The larger R/L.ACC was associated with hyperactivity and inattention. Resting-state functional analysis showed increased functional connectivity (FC) between the left supramarginal gyrus (L.SMG) in the salience network (SN) and the right middle frontal gyrus (R.MFG) simultaneously with a decrease in FC with the L.ACC for the same seed. The increased FC for the R.MFG was associated with difficulty in peer problems and depressive symptoms; a mediating effect was evident for depressive symptoms. These results suggest that the structural atypicality of the R/L.ACC indirectly contributes to the disturbed FCs within the SN, thereby exacerbating depressive symptoms in neglected children. In conclusion, exposure to neglect in childhood may lead to maladaptive brain development, particularly neural changes associated with depressive symptoms.
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Affiliation(s)
- Natasha Y S Kawata
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan
| | - Shota Nishitani
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Life Science Innovation Center, University of Fukui, Fukui 910-8507, Japan.
| | - Akiko Yao
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan
| | - Shinichiro Takiguchi
- Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Life Science Innovation Center, University of Fukui, Fukui 910-8507, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui 910-1193, Japan
| | - Yoshifumi Mizuno
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui 910-1193, Japan
| | - Sakae Mizushima
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan
| | - Kai Makita
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan
| | - Shoko Hamamura
- Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui 910-1193, Japan
| | - Daisuke N Saito
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan
| | - Hidehiko Okazawa
- Life Science Innovation Center, University of Fukui, Fukui 910-8507, Japan; Biomedical Imaging Research Center, University of Fukui, Fukui 910-1193, Japan
| | - Takashi X Fujisawa
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Life Science Innovation Center, University of Fukui, Fukui 910-8507, Japan
| | - Akemi Tomoda
- Research Center for Child Mental Development, University of Fukui, 23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Fukui 910-1193, Japan; Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui 910-1193, Japan; Life Science Innovation Center, University of Fukui, Fukui 910-8507, Japan; Department of Child and Adolescent Psychological Medicine, University of Fukui Hospital, Fukui 910-1193, Japan.
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Adams RA, Zor C, Mihalik A, Tsirlis K, Brudfors M, Chapman J, Ashburner J, Paulus MP, Mourão-Miranda J. Voxelwise Multivariate Analysis of Brain-Psychosocial Associations in Adolescents Reveals 6 Latent Dimensions of Cognition and Psychopathology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00085-5. [PMID: 38588854 DOI: 10.1016/j.bpsc.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 03/15/2024] [Accepted: 03/28/2024] [Indexed: 04/10/2024]
Abstract
BACKGROUND Adolescence heralds the onset of considerable psychopathology, which may be conceptualized as an emergence of altered covariation between symptoms and brain measures. Multivariate methods can detect such modes of covariation or latent dimensions, but none specifically relating to psychopathology have yet been found using population-level structural brain data. Using voxelwise (instead of parcellated) brain data may strengthen latent dimensions' brain-psychosocial relationships, but this creates computational challenges. METHODS We obtained voxelwise gray matter density and psychosocial variables from the baseline (ages 9-10 years) Adolescent Brain Cognitive Development (ABCD) Study cohort (N = 11,288) and employed a state-of-the-art segmentation method, sparse partial least squares, and a rigorous machine learning framework to prevent overfitting. RESULTS We found 6 latent dimensions, 4 of which pertain specifically to mental health. The mental health dimensions were related to overeating, anorexia/internalizing, oppositional symptoms (all ps < .002) and attention-deficit/hyperactivity disorder symptoms (p = .03). Attention-deficit/hyperactivity disorder was related to increased and internalizing symptoms related to decreased gray matter density in dopaminergic and serotonergic midbrain areas, whereas oppositional symptoms were related to increased gray matter in a noradrenergic nucleus. Internalizing symptoms were related to increased and oppositional symptoms to reduced gray matter density in the insular, cingulate, and auditory cortices. Striatal regions featured strongly, with reduced caudate nucleus gray matter in attention-deficit/hyperactivity disorder and reduced putamen gray matter in oppositional/conduct problems. Voxelwise gray matter density generated stronger brain-psychosocial correlations than brain parcellations. CONCLUSIONS Voxelwise brain data strengthen latent dimensions of brain-psychosocial covariation, and sparse multivariate methods increase their psychopathological specificity. Internalizing and externalizing symptoms are associated with opposite gray matter changes in similar cortical and subcortical areas.
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Affiliation(s)
- Rick A Adams
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
| | - Cemre Zor
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Agoston Mihalik
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Konstantinos Tsirlis
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
| | - Mikael Brudfors
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - James Chapman
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
| | - John Ashburner
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | | | - Janaina Mourão-Miranda
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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7
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Abbott N, Love T. Bridging the Divide: Brain and Behavior in Developmental Language Disorder. Brain Sci 2023; 13:1606. [PMID: 38002565 PMCID: PMC10670267 DOI: 10.3390/brainsci13111606] [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: 09/15/2023] [Revised: 11/14/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
Developmental language disorder (DLD) is a heterogenous neurodevelopmental disorder that affects a child's ability to comprehend and/or produce spoken and/or written language, yet it cannot be attributed to hearing loss or overt neurological damage. It is widely believed that some combination of genetic, biological, and environmental factors influences brain and language development in this population, but it has been difficult to bridge theoretical accounts of DLD with neuroimaging findings, due to heterogeneity in language impairment profiles across individuals and inconsistent neuroimaging findings. Therefore, the purpose of this overview is two-fold: (1) to summarize the neuroimaging literature (while drawing on findings from other language-impaired populations, where appropriate); and (2) to briefly review the theoretical accounts of language impairment patterns in DLD, with the goal of bridging the disparate findings. As will be demonstrated with this overview, the current state of the field suggests that children with DLD have atypical brain volume, laterality, and activation/connectivity patterns in key language regions that likely contribute to language difficulties. However, the precise nature of these differences and the underlying neural mechanisms contributing to them remain an open area of investigation.
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Affiliation(s)
- Noelle Abbott
- School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA 92182, USA;
- San Diego State University/University of California San Diego Joint Doctoral Program in Language and Communicative Disorders, San Diego, CA 92182, USA
| | - Tracy Love
- School of Speech, Language, and Hearing Sciences, San Diego State University, San Diego, CA 92182, USA;
- San Diego State University/University of California San Diego Joint Doctoral Program in Language and Communicative Disorders, San Diego, CA 92182, USA
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Suleri A, Cecil C, Rommel AS, Hillegers M, White T, de Witte LD, Muetzel RL, Bergink V. Long-term effects of prenatal infection on the human brain: a prospective multimodal neuroimaging study. Transl Psychiatry 2023; 13:306. [PMID: 37789021 PMCID: PMC10547711 DOI: 10.1038/s41398-023-02597-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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 09/15/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023] Open
Abstract
There is convincing evidence from rodent studies suggesting that prenatal infections affect the offspring's brain, but evidence in humans is limited. Here, we assessed the occurrence of common infections during each trimester of pregnancy and examined associations with brain outcomes in adolescent offspring. Our study was embedded in the Generation R Study, a large-scale sociodemographically diverse prospective birth cohort. We included 1094 mother-child dyads and investigated brain morphology (structural MRI), white matter microstructure (DTI), and functional connectivity (functional MRI), as outcomes at the age of 14. We focused on both global and focal regions. To define prenatal infections, we composed a score based on the number and type of infections during each trimester of pregnancy. Models were adjusted for several confounders. We found that prenatal infection was negatively associated with cerebral white matter volume (B = -0.069, 95% CI -0.123 to -0.015, p = 0.011), and we found an association between higher prenatal infection scores and smaller volumes of several frontotemporal regions of the brain. After multiple testing correction, we only observed an association between prenatal infections and the caudal anterior cingulate volume (B = -0.104, 95% CI -0.164 to -0.045, p < 0.001). We did not observe effects of prenatal infection on other measures of adolescent brain morphology, white matter microstructure, or functional connectivity, which is reassuring. Our results show potential regions of interest in the brain for future studies; data on the effect of severe prenatal infections on the offspring's brain in humans are needed.
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Affiliation(s)
- Anna Suleri
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Charlotte Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Anna-Sophie Rommel
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Manon Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Tonya White
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, Bethesda, MD, USA
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Veerle Bergink
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA.
- Department of Psychiatry, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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Zdorovtsova N, Jones J, Akarca D, Benhamou E, The Calm Team, Astle DE. Exploring neural heterogeneity in inattention and hyperactivity. Cortex 2023; 164:90-111. [PMID: 37207412 DOI: 10.1016/j.cortex.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 02/21/2023] [Accepted: 04/04/2023] [Indexed: 05/21/2023]
Abstract
Inattention and hyperactivity are cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD). These characteristics have also been observed across a range of other neurodevelopmental conditions, such as autism and dyspraxia, suggesting that they might best be studied across diagnostic categories. Here, we evaluated the associations between inattention and hyperactivity behaviours and features of the structural brain network (connectome) in a large transdiagnostic sample of children (Centre for Attention, Learning, and Memory; n = 383). In our sample, we found that a single latent factor explains 77.6% of variance in scores across multiple questionnaires measuring inattention and hyperactivity. Partial Least-Squares (PLS) regression revealed that variability in this latent factor could not be explained by a linear component representing nodewise properties of connectomes. We then investigated the type and extent of neural heterogeneity in a subset of our sample with clinically-elevated levels of inattention and hyperactivity. Multidimensional scaling combined with k-means clustering revealed two neural subtypes in children with elevated levels of inattention and hyperactivity (n = 232), differentiated primarily by nodal communicability-a measure which demarcates the extent to which neural signals propagate through specific brain regions. These different clusters had similar behavioural profiles, which included high levels of inattention and hyperactivity. However, one of the clusters scored higher on multiple cognitive assessment measures of executive function. We conclude that inattention and hyperactivity are so common in children with neurodevelopmental difficulties because they emerge through multiple different trajectories of brain development. In our own data, we can identify two of these possible trajectories, which are reflected by measures of structural brain network topology and cognition.
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Affiliation(s)
- Natalia Zdorovtsova
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Jonathan Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Danyal Akarca
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Elia Benhamou
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - The Calm Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK
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10
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Abdolalizadeh A, Moradi K, Dabbagh Ohadi MA, Mirfazeli FS, Rajimehr R. Larger left hippocampal presubiculum is associated with lower risk of antisocial behavior in healthy adults with childhood conduct history. Sci Rep 2023; 13:6148. [PMID: 37061611 PMCID: PMC10105780 DOI: 10.1038/s41598-023-33198-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 04/08/2023] [Indexed: 04/17/2023] Open
Abstract
Conduct Disorder (CD) is defined as aggressive, antisocial, and rule-breaking behavior during childhood. It is a major risk factor for developing antisocial personality disorder (ASPD) in adulthood. However, nearly half the CDs do not develop ASPD. Identification of reversion factors seems crucial for proper interventions. We identified 40 subjects with childhood history of CD (CC) and 1166 control subjects (HC) from Human Connectome Project. Their psychiatric, emotional, impulsivity, and personality traits were extracted. An emotion recognition task-fMRI analysis was done. We also did subregion analysis of hippocampus and amygdala in 35 CC and 69 demographically matched HCs. CC subjects scored significantly higher in antisocial-related evaluations. No differences in task-fMRI activation of amygdala and hippocampus were observed. CCs had larger subfields of the left hippocampus: presubiculum, CA3, CA4, and dentate gyrus. Further, an interaction model revealed a significant presubiculum volume × group association with antisocial, aggression, and agreeableness scores. Our study shows that healthy young adults with a prior history of CD still exhibit some forms of antisocial-like behavior with larger left hippocampal subfields, including presubiculum that also explains the variability in antisocial behavior. These larger left hippocampal subfield volumes may play a protective role against CD to ASPD conversion.
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Affiliation(s)
- AmirHussein Abdolalizadeh
- Biological Psychology, Department of Psychology, School of Medicine and Health Sciences, Carl Von Ossietzky Universität Oldenburg, Oldenburg, Germany
- Interdisciplinary Neuroscience Research Program, Tehran University of Medical Sciences, Tehran, Iran
- Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kamyar Moradi
- Interdisciplinary Neuroscience Research Program, Tehran University of Medical Sciences, Tehran, Iran
- Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Amin Dabbagh Ohadi
- Interdisciplinary Neuroscience Research Program, Tehran University of Medical Sciences, Tehran, Iran
- Students' Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Sadat Mirfazeli
- Mental Health Research Center, Psychosocial Health Research Institute, Department of Psychiatry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
| | - Reza Rajimehr
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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11
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Gidziela A, Ahmadzadeh YI, Michelini G, Allegrini AG, Agnew-Blais J, Lau LY, Duret M, Procopio F, Daly E, Ronald A, Rimfeld K, Malanchini M. A meta-analysis of genetic effects associated with neurodevelopmental disorders and co-occurring conditions. Nat Hum Behav 2023; 7:642-656. [PMID: 36806400 PMCID: PMC10129867 DOI: 10.1038/s41562-023-01530-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 01/16/2023] [Indexed: 02/22/2023]
Abstract
A systematic understanding of the aetiology of neurodevelopmental disorders (NDDs) and their co-occurrence with other conditions during childhood and adolescence remains incomplete. In the current meta-analysis, we synthesized the literature on (1) the contribution of genetic and environmental factors to NDDs, (2) the genetic and environmental overlap between different NDDs, and (3) the co-occurrence between NDDs and disruptive, impulse control and conduct disorders (DICCs). Searches were conducted across three platforms: Web of Science, Ovid Medline and Ovid Embase. Studies were included only if 75% or more of the sample consisted of children and/or adolescents and the studies had measured the aetiology of NDDs and DICCs using single-generation family designs or genomic methods. Studies that had selected participants on the basis of unrelated diagnoses or injuries were excluded. We performed multilevel, random-effects meta-analyses on 296 independent studies, including over four million (partly overlapping) individuals. We further explored developmental trajectories and the moderating roles of gender, measurement, geography and ancestry. We found all NDDs to be substantially heritable (family-based heritability, 0.66 (s.e. = 0.03); SNP heritability, 0.19 (s.e. = 0.03)). Meta-analytic genetic correlations between NDDs were moderate (grand family-based genetic correlation, 0.36 (s.e. = 0.12); grand SNP-based genetic correlation, 0.39 (s.e. = 0.19)) but differed substantially between pairs of disorders. The genetic overlap between NDDs and DICCs was strong (grand family-based genetic correlation, 0.62 (s.e. = 0.20)). While our work provides evidence to inform and potentially guide clinical and educational diagnostic procedures and practice, it also highlights the imbalance in the research effort that has characterized developmental genetics research.
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Affiliation(s)
- Agnieszka Gidziela
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK. .,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
| | - Yasmin I Ahmadzadeh
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Giorgia Michelini
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.,UCLA Semel Institute for Neuroscience, Division of Child and Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.,Division of Psychology and Language Sciences, University College London, London, UK
| | - Jessica Agnew-Blais
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Lok Yan Lau
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Megan Duret
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Francesca Procopio
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Emily Daly
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Angelica Ronald
- Department of Psychological Sciences, Birkbeck University of London, London, UK
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.,Department of Psychology, Royal Holloway University of London, Egham, UK
| | - Margherita Malanchini
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK. .,Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
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12
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Sun Y, Jia T, Barker ED, Chen D, Zhang Z, Xu J, Chang S, Zhou G, Liu Y, Tay N, Luo Q, Chang X, Banaschewski T, Bokde ALW, Flor H, Grigis A, Garavan H, Heinz A, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Lu L, Shi J, Schumann G, Desrivières S. Associations of DNA Methylation With Behavioral Problems, Gray Matter Volumes, and Negative Life Events Across Adolescence: Evidence From the Longitudinal IMAGEN Study. Biol Psychiatry 2023; 93:342-351. [PMID: 36241462 DOI: 10.1016/j.biopsych.2022.06.012] [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: 10/11/2021] [Revised: 05/17/2022] [Accepted: 06/05/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND Negative life events (NLEs) increase the risk for externalizing behaviors (EBs) and internalizing behaviors (IBs) in adolescence and adult psychopathology. DNA methylation associated with behavioral problems may reflect this risk and long-lasting effects of NLEs. METHODS To identify consistent associations between blood DNA methylation and EBs or IBs across adolescence, we conducted longitudinal epigenome-wide association studies (EWASs) using data from the IMAGEN cohort, collected at ages 14 and 19 years (n = 506). Significant findings were validated in a separate subsample (n = 823). Methylation risk scores were generated by 10-fold cross-validation and further tested for their associations with gray matter volumes and NLEs. RESULTS No significant findings were obtained for the IB-EWAS. The EB-EWAS identified a genome-wide significant locus in a gene linked to attention-deficit/hyperactivity disorder (ADHD) (IQSEC1, cg01460382; p = 1.26 × 10-8). Other most significant CpG sites were near ADHD-related genes and enriched for genes regulating tumor necrosis factor and interferon-γ signaling, highlighting the relevance of EB-EWAS findings for ADHD. Analyses with the EB methylation risk scores suggested that it partly reflected comorbidity with IBs in late adolescence. Specific to EBs, EB methylation risk scores correlated with smaller gray matter volumes in medial orbitofrontal and anterior/middle cingulate cortices, brain regions known to associate with ADHD and conduct problems. Longitudinal mediation analyses indicated that EB-related DNA methylation were more likely the outcomes of problematic behaviors accentuated by NLEs, and less likely the epigenetic bases of such behaviors. CONCLUSIONS Our findings suggest that novel epigenetic mechanisms through which NLEs exert short and longer-term effects on behavior may contribute to ADHD.
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Affiliation(s)
- Yan Sun
- National Institute on Drug Dependence, Peking University Hospital, Beijing, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and Research and Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Edward D Barker
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom; Developmental Psychopathology Laboratory, Department of Psychology, King's College London, London, United Kingdom
| | - Di Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and Research and Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China
| | - Zuo Zhang
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Jiayuan Xu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China; Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Suhua Chang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No.2018RU006), Beijing, China
| | - Guangdong Zhou
- Faculty of Psychology, Tianjin Normal University, Tianjin, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Yun Liu
- Department of Biochemistry and Molecular Biology, Ministry of Education-Singapore Key Laboratory of Metabolism and Molecular Medicine, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Nicole Tay
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and Research and Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China; State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and Research and Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin-Commissariat à L'énergie Atomique et Aux Energies Alternatives, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Trajectoires développementales en psychiatrie," Université Paris-Saclay, École Normale supérieure Paris-Saclay, Centre National de la Recherche Scientifique, Centre Borelli, Paris, France; Assistance Publique-Hôpitaux de Paris, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Sorbonne Université, Paris, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Trajectoires développementales en psychiatrie," Université Paris-Saclay, École Normale supérieure Paris-Saclay, Centre National de la Recherche Scientifique, Centre Borelli, Paris, France; Department of Psychiatry 91G16, Orsay Hospital, Orsay, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging and Psychiatry", University Paris Sud, University Paris Descartes, Sorbonne Paris Cité, Orsay, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | - Dimitri Papadopoulos Orfanos
- NeuroSpin-Commissariat à L'énergie Atomique et Aux Energies Alternatives, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Tomáš Paus
- Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- Global Brain Health Institute and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Lin Lu
- National Institute on Drug Dependence, Peking University Hospital, Beijing, China; Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Research Unit of Diagnosis and Treatment of Mood Cognitive Disorder, Chinese Academy of Medical Sciences (No.2018RU006), Beijing, China
| | - Jie Shi
- National Institute on Drug Dependence, Peking University Hospital, Beijing, China
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and Research and Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, China; PONS Centre, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Berlin, Germany
| | - Sylvane Desrivières
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.
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13
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Meyer GP, da Silva BS, Bandeira CE, Tavares MEA, Cupertino RB, Oliveira EP, Müller D, Kappel DB, Teche SP, Vitola ES, Rohde LA, Rovaris DL, Grevet EH, Bau CHD. Dissecting the cross-trait effects of the FOXP2 GWAS hit on clinical and brain phenotypes in adults with ADHD. Eur Arch Psychiatry Clin Neurosci 2023; 273:15-24. [PMID: 35279744 DOI: 10.1007/s00406-022-01388-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 02/01/2022] [Indexed: 11/03/2022]
Abstract
The Forkhead box P2 (FOXP2) encodes for a transcription factor with a broad role in embryonic development. It is especially represented among GWAS hits for neurodevelopmental disorders and related traits, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, neuroticism, and risk-taking behaviors. While several functional studies are underway to understand the consequences of FOXP2 variation, this study aims to expand previous findings to clinically and genetically related phenotypes and neuroanatomical features among subjects with ADHD. The sample included 407 adults with ADHD and 463 controls. Genotyping was performed on the Infinium PsychArray-24 BeadChip, and the FOXP2 gene region was extracted. A gene-wide approach was adopted to evaluate the combined effects of FOXP2 variants (n = 311) on ADHD status, severity, comorbidities, and personality traits. Independent risk variants presenting potential functional effects were further tested for association with cortical surface areas in a subsample of cases (n = 87). The gene-wide analyses within the ADHD sample showed a significant association of the FOXP2 gene with harm avoidance (P = 0.001; PFDR = 0.015) and nominal associations with hyperactivity symptoms (P = 0.026; PFDR = 0.130) and antisocial personality disorder (P = 0.026; PFDR = 0.130). An insertion/deletion variant (rs79622555) located downstream of FOXP2 was associated with the three outcomes and nominally with the surface area of superior parietal and anterior cingulate cortices. Our results extend and refine previous GWAS findings pointing to a role of FOXP2 in several neurodevelopment-related phenotypes, mainly those involving underlying symptomatic domains of self-regulation and inhibitory control. Taken together, the available evidence may constitute promising insights into the puzzle of the FOXP2-related pathophysiology.
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Affiliation(s)
- Gabriela Pessin Meyer
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Bruna Santos da Silva
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Cibele Edom Bandeira
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Maria Eduarda Araujo Tavares
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Eduarda Pereira Oliveira
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Diana Müller
- ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Djenifer B Kappel
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, Wales
| | - Stefania Pigatto Teche
- ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Psychiatry, School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Eduardo Schneider Vitola
- ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Psychiatry, School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Luis Augusto Rohde
- ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
| | - Diego Luiz Rovaris
- Departamento de Fisiologia e Biofisica, Universidade de Sao Paulo Instituto de Ciencias Biomedicas, São Paulo, Brazil
| | - Eugenio Horacio Grevet
- ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.,Department of Psychiatry, School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Claiton Henrique Dotto Bau
- Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. .,ADHD Outpatient Program, Clinical Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil. .,Developmental Psychiatry Program, Experimental Research Center, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil. .,Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
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14
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The computational psychiatry of antisocial behaviour and psychopathy. Neurosci Biobehav Rev 2023; 145:104995. [PMID: 36535376 DOI: 10.1016/j.neubiorev.2022.104995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 11/21/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022]
Abstract
Antisocial behaviours such as disobedience, lying, stealing, destruction of property, and aggression towards others are common to multiple disorders of childhood and adulthood, including conduct disorder, oppositional defiant disorder, psychopathy, and antisocial personality disorder. These disorders have a significant negative impact for individuals and for society, but whether they represent clinically different phenomena, or simply different approaches to diagnosing the same underlying psychopathology is highly debated. Computational psychiatry, with its dual focus on identifying different classes of disorder and health (data-driven) and latent cognitive and neurobiological mechanisms (theory-driven), is well placed to address these questions. The elucidation of mechanisms that might characterise latent processes across different disorders of antisocial behaviour can also provide important advances. In this review, we critically discuss the contribution of computational research to our understanding of various antisocial behaviour disorders, and highlight suggestions for how computational psychiatry can address important clinical and scientific questions about these disorders in the future.
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15
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Lin X, Huang L, Huang H, Ke Z, Chen Y. Disturbed relationship between glucocorticoid receptor and 5-HT1AR/5-HT2AR in ADHD rats: A correlation study. Front Neurosci 2023; 16:1064369. [PMID: 36699537 PMCID: PMC9869156 DOI: 10.3389/fnins.2022.1064369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 12/16/2022] [Indexed: 01/12/2023] Open
Abstract
Objective This work is to investigate the alterations of the central 5-hydroxytryptamine (5-HT) system in spontaneously hypertensive rats (SHR) and the correlation with the behaviors of SHR, and to explore the effects of glucocorticoid intervention on the central 5-HT system and SHR behaviors. Materials and methods Three weeks old SHR were chosen as the attention-deficit hyperactivity disorder (ADHD) model and treated with glucocorticoid receptor (GR) agonist or inhibitor, whereas Wista Kyoto rats (WKY) were chosen as the normal control group. Open-field test and Làt maze test were used to evaluate the spontaneous activities and non-selective attention. The levels of 5-HT in the extracellular fluid specimens of the prefrontal cortex of rats were analyzed by high-performance liquid chromatography. The expressions of GR, 5-HT1A receptor (5-HT1AR), and 5-HT2A receptor (5-HT2AR) in the prefrontal cortex were analyzed through immunohistochemistry. Results Our study demonstrated that the 5-HT level was lower in the prefrontal cortex of SHR compared to that of WKY. The Open-field test and Làt maze test showed that GR agonist (dexamethasone, DEX) intervention ameliorated attention deficit and hyperactive behavior, whereas GR inhibitor (RU486) aggravated the disorders. With DEX, the expression levels of 5-HT and 5-HT2AR in the prefrontal cortex of SHR were significantly higher than those in the control group, whereas the expression level of 5-HT1AR was lower. However, the expression levels of 5-HT and 5-HT2AR were significantly decreased after the intervention with RU486, while the expression level of 5-HT1AR increased. Results showed that glucocorticoid was negatively correlated with 5-HT1AR and positively correlated with 5-HT2AR. Conclusion In the prefrontal cortex of ADHD rats, the down-regulation of 5-HT and 5-HT2AR expressions and the up-regulation of 5-HT1AR, compared with WYK rats, suggested a dysfunctional central 5-HT system in ADHD rats. The GR agonist can upregulate the expression of 5-HT and 5-HT2AR and downregulate the expression of 5-HT1AR in the prefrontal cortex of SHR as well as reduce the hyperactivity and attention deficit behavior in SHR, while the opposite was true for the GR inhibitor. It is suggested that the dysfunction of the 5-HT system in ADHD rats is closely related to glucocorticoid receptor activity.
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16
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Kristanto D, Liu X, Sommer W, Hildebrandt A, Zhou C. What do neuroanatomical networks reveal about the ontology of human cognitive abilities? iScience 2022; 25:104706. [PMID: 35865139 PMCID: PMC9293763 DOI: 10.1016/j.isci.2022.104706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/15/2022] [Accepted: 06/28/2022] [Indexed: 11/18/2022] Open
Abstract
Over the last decades, cognitive psychology has come to a fair consensus about the human intelligence ontological structure. However, it remains an open question whether anatomical properties of the brain support the same ontology. The present study explored the ontological structure derived from neuroanatomical networks associated with performance on 15 cognitive tasks indicating various abilities. Results suggest that the brain-derived (neurometric) ontology partly agrees with the cognitive performance-derived (psychometric) ontology complemented with interpretable differences. Moreover, the cortical areas associated with different inferred abilities are segregated, with little or no overlap. Nevertheless, these spatially segregated cortical areas are integrated via denser white matter structural connections as compared with the general brain connectome. The integration of ability-related cortical networks constitutes a neural counterpart to the psychometric construct of general intelligence, while the consistency and difference between psychometric and neurometric ontologies represent crucial pieces of knowledge for theory building, clinical diagnostics, and treatment. Psychometric and neurometric cognitive ontologies are partly equivalent Ability-related brain areas are ontologically segregated with little to no overlap However, ability-related brain areas are densely interconnected by fiber tracts
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17
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The neurobiology of antisocial behavior in adolescence current knowledge and relevance for youth forensic clinical practice. Curr Opin Psychol 2022; 47:101356. [DOI: 10.1016/j.copsyc.2022.101356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 03/28/2022] [Accepted: 05/04/2022] [Indexed: 11/23/2022]
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18
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Teeuw J, Klein M, Mota NR, Brouwer RM, van ‘t Ent D, Al-Hassaan Z, Franke B, Boomsma DI, Hulshoff Pol HE. Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample. Int J Mol Sci 2022; 23:ijms23063176. [PMID: 35328598 PMCID: PMC8949114 DOI: 10.3390/ijms23063176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/10/2022] [Accepted: 03/10/2022] [Indexed: 12/10/2022] Open
Abstract
Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to −0.20), with sizeable genetic correlations (FA ra up to +0.42; MD ra up to −0.33). The cortical gray matter (CGM; rph up to −0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.
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Affiliation(s)
- Jalmar Teeuw
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Correspondence: ; Tel.: +31-(088)-75-53-387
| | - Marieke Klein
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Nina Roth Mota
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Rachel M. Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Dennis van ‘t Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
| | - Zyneb Al-Hassaan
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Psychology, Utrecht University, 3584 CS Utrecht, The Netherlands
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19
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Chen Y, Lei D, Cao H, Niu R, Chen F, Chen L, Zhou J, Hu X, Huang X, Guo L, Sweeney JA, Gong Q. Altered single-subject gray matter structural networks in drug-naïve attention deficit hyperactivity disorder children. Hum Brain Mapp 2021; 43:1256-1264. [PMID: 34797010 PMCID: PMC8837581 DOI: 10.1002/hbm.25718] [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: 06/18/2021] [Revised: 10/09/2021] [Accepted: 11/04/2021] [Indexed: 02/05/2023] Open
Abstract
Altered topological organization of brain structural covariance networks has been observed in attention deficit hyperactivity disorder (ADHD). However, results have been inconsistent, potentially related to confounding medication effects. In addition, since structural networks are traditionally constructed at the group level, variabilities in individual structural features remain to be well characterized. Structural brain imaging with MRI was performed on 84 drug‐naïve children with ADHD and 83 age‐matched healthy controls. Single‐subject gray matter (GM) networks were obtained based on areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared using nonparametric permutation testing. Compared with healthy subjects, GM networks in ADHD patients demonstrated significantly altered topological characteristics, including higher global and local efficiency and clustering coefficient, and shorter path length. In addition, ADHD patients exhibited abnormal centrality in corticostriatal circuitry including the superior frontal gyrus, orbitofrontal gyrus, medial superior frontal gyrus, precentral gyrus, middle temporal gyrus, and pallidum (all p < .05, false discovery rate [FDR] corrected). Altered global and nodal topological efficiencies were associated with the severity of hyperactivity symptoms and the performance on the Stroop and Wisconsin Card Sorting Test tests (all p < .05, FDR corrected). ADHD combined and inattention subtypes were differentiated by nodal attributes of amygdala (p < .05, FDR corrected). Alterations in GM network topologies were observed in drug‐naïve ADHD patients, in particular in frontostriatal loops and amygdala. These alterations may contribute to impaired cognitive functioning and impulsive behavior in ADHD.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Hengyi Cao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York, USA.,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, New York, USA.,Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Running Niu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Fuqin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Lizhou Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Jinbo Zhou
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Xinyu Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Lanting Guo
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
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20
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Nader JL, López-Vicente M, Julvez J, Guxens M, Cadman T, Elhakeem A, Järvelin MR, Rautio N, Miettunen J, El Marroun H, Melchior M, Heude B, Charles MA, Yang TC, McEachan RRC, Wright J, Polanska K, Carson J, Lin A, Rauschert S, Huang RC, Popovic M, Richiardi L, Corpeleijn E, Cardol M, Mikkola TM, Eriksson JG, Salika T, Inskip H, Vinther JL, Strandberg-Larsen K, Gürlich K, Grote V, Koletzko B, Vafeiadi M, Sunyer J, Jaddoe VWV, Harris JR. Cohort description: Measures of early-life behaviour and later psychopathology in the LifeCycle Project - EU Child Cohort Network. J Epidemiol 2021. [PMID: 34776498 PMCID: PMC10165218 DOI: 10.2188/jea.je20210241] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The EU LifeCycle Project was launched in 2017 to combine, harmonise, and analyse data from more than 250,000 participants across Europe and Australia, involving cohorts participating in the EU-funded LifeCycle Project. The purpose of this cohort description is to provide a detailed overview over the major measures within mental health domains that are available in 17 European and Australian cohorts participating in the LifeCycle Project. METHODS Data on cognitive, behavioural and psychological development has been collected on participants from birth until adulthood through questionnaire and medical data. We developed an inventory of the available data by mapping individual instruments, domain types, and age groups, providing the basis for statistical harmonization across mental health measures. RESULTS The mental health data in LifeCycle contain longitudinal and cross-sectional data for ages 0-18+ years, covering domains across a wide range of behavioural and psychopathology indicators and outcomes (including executive function, depression, ADHD and cognition). These data span a unique combination of qualitative data collected through behavioural/cognitive/mental health questionnaires and examination, as well as data from biological samples and indices in the form of brain imaging (MRI, foetal ultrasound) and DNA methylation data. Harmonized variables on a subset of mental health domains have been developed, providing statistical equivalence of measures required for longitudinal meta-analyses across instruments and cohorts. CONCLUSION Mental health data harmonized through the LifeCycle project can be used to study life course trajectories and exposure-outcome models that examine early life risk factors for mental illness and develop predictive markers for later-life disease.
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Affiliation(s)
- Johanna L Nader
- Department of Genetics and Bioinformatics, Division of Health Data and Digitalisation, Norwegian Institute of Public Health
| | - Mònica López-Vicente
- ISGlobal, Instituto de Salud Global de Barcelona.,Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam
| | - Jordi Julvez
- ISGlobal, Instituto de Salud Global de Barcelona.,Institut d'Investigació Sanitària Pere Virgili, Hospital Universitari Sant Joan de Reus
| | - Monica Guxens
- ISGlobal, Instituto de Salud Global de Barcelona.,Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam
| | - Tim Cadman
- MRC Integrative Epidemiology Unit at University of Bristol, Population Health Sciences, Bristol Medical School
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at University of Bristol, Population Health Sciences, Bristol Medical School
| | | | - Nina Rautio
- Center for Life Course Health Research, University of Oulu
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu.,Medical Research Center Oulu, Oulu University Hospital and University of Oulu
| | - Hanan El Marroun
- Department of Child and Adolescent Psychiatry, University Medical Center Rotterdam.,Department of Pediatrics, University Medical Center Rotterdam.,The Generation R Study Group
| | - Maria Melchior
- Sorbonne Université, INSERM, Institut Pierre Louis d'Épidémiologie et de Santé Publique, IPLESP
| | - Barbara Heude
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE
| | - Marie-Aline Charles
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE.,Unité mixte Inserm-Ined-EFS Elfe, INED
| | - Tiffany C Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust
| | - Rosemary R C McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust
| | - Kinga Polanska
- Department of Hygiene and Epidemiology, Medical University of Lodz
| | - Jennie Carson
- Telethon Kids Institute, University of Western Australia
| | - Ashleigh Lin
- Telethon Kids Institute, University of Western Australia
| | | | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia
| | - Maja Popovic
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO Piemonte
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and CPO Piemonte
| | - Eva Corpeleijn
- Department of Epidemiology, University Medical Center Groningen
| | - Marloes Cardol
- Department of Epidemiology, University Medical Center Groningen
| | - Tuija M Mikkola
- Folkhälsan Research Center.,Clinicum, Faculty of Medicine, University of Helsinki
| | - Johan G Eriksson
- Folkhälsan Research Center.,Public Health Promotion Unit, National Institute for Health and Welfare.,Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital.,Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research.,Department of Obstetrics & Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore
| | - Theodosia Salika
- Medical Research Council Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton
| | - Hazel Inskip
- Medical Research Council Lifecourse Epidemiology Unit, Southampton General Hospital, University of Southampton.,NIHR Southampton Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust, University of Southampton
| | | | | | - Kathrin Gürlich
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete
| | - Jordi Sunyer
- ISGlobal, Instituto de Salud Global de Barcelona
| | - Vincent W V Jaddoe
- Department of Pediatrics, University Medical Center Rotterdam.,The Generation R Study Group
| | - Jennifer R Harris
- Division of Health Data and Digitalization, Center for Fertility and Health and Department of Genetics and Bioinformatics, The Norwegian Institute of Public Health
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21
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Machine-learning-based diagnosis of drug-naive adult patients with attention-deficit hyperactivity disorder using mismatch negativity. Transl Psychiatry 2021; 11:484. [PMID: 34537812 PMCID: PMC8449778 DOI: 10.1038/s41398-021-01604-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 08/23/2021] [Accepted: 09/01/2021] [Indexed: 02/08/2023] Open
Abstract
Relatively little is investigated regarding the neurophysiology of adult attention-deficit/hyperactivity disorder (ADHD). Mismatch negativity (MMN) is an event-related potential component representing pre-attentive auditory processing, which is closely associated with cognitive status. We investigated MMN features as biomarkers to classify drug-naive adult patients with ADHD and healthy controls (HCs). Sensor-level features (amplitude and latency) and source-level features (source activation) of MMN were investigated and compared between the electroencephalograms of 34 patients with ADHD and 45 HCs using a passive auditory oddball paradigm. Correlations between MMN features and ADHD symptoms were analyzed. Finally, we applied machine learning to differentiate the two groups using sensor- and source-level features of MMN. Adult patients with ADHD showed significantly lower MMN amplitudes at the frontocentral electrodes and reduced MMN source activation in the frontal, temporal, and limbic lobes, which were closely associated with MMN generators and ADHD pathophysiology. Source activities were significantly correlated with ADHD symptoms. The best classification performance for adult ADHD patients and HCs showed an 81.01% accuracy, 82.35% sensitivity, and 80.00% specificity based on MMN source activity features. Our results suggest that abnormal MMN reflects the adult ADHD patients' pathophysiological characteristics and might serve clinically as a neuromarker of adult ADHD.
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22
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Vestberg T, Tedeholm PG, Ingvar M, Larsson AC, Petrovic P. Executive Functions of Swedish Counterterror Intervention Unit Applicants and Police Officer Trainees Evaluated With Design Fluency Test. Front Psychol 2021; 12:580463. [PMID: 34113276 PMCID: PMC8185326 DOI: 10.3389/fpsyg.2021.580463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 02/19/2021] [Indexed: 11/29/2022] Open
Abstract
Executive functions (EF) represent higher order top-down mechanisms regulating information processing. While suboptimal EF have been studied in various patient groups, their impact on successful behavior is still not well described. Previously, it has been suggested that design fluency (DF)-a test including several simultaneous EF components mainly related to fluency, cognitive flexibility, and creativity-predicts successful behavior in a quickly changing environment where fast and dynamic adaptions are required, such as ball sports. We hypothesized that similar behaviors are of importance in the selection process of elite police force applicants. To test this hypothesis, we compared elite police force applicants (n = 45) with a control group of police officer trainees (n = 30). Although both groups were better than the norm, the elite police force applicants had a significantly better performance in DF total correct when adjusting for sex and age [F(1,71) = 18.98, p < 0.001]. To understand how this capacity was altered by stress and tiredness, we re-tested the elite police force applicants several days during an extreme field assessment lasting 10 days. The results suggested that there was a lower than expected improvement in DF total correct and a decline in the DF3-subtest that includes a larger component of cognitive flexibility than the other subtests (DF1 and DF2). Although there was a positive correlation between the baseline session and the re-test in DF3 [r(40) = 0.49, p = 0.001], the applicants having the highest scores in the baseline test also displayed the largest percentage decline in the re-test [r(40) = -0.46, p = 0.003]. In conclusion, our result suggests that higher order EF (HEF) that include cognitive flexibility and creativity are of importance in the application for becoming an elite police officer but relatively compromised in a stressful situation. Moreover, as the decline is different between the individuals, the results suggest that applicants should be tested during baseline conditions and during stressful conditions to describe their cognitive capacity fully.
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Affiliation(s)
- Torbjörn Vestberg
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Peter G. Tedeholm
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Agneta C. Larsson
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center for Cognitive and Computational Neuropsychiatry, Karolinska Institutet, Stockholm, Sweden
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23
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Iravani B, Arshamian A, Fransson P, Kaboodvand N. Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy. Neuroimage 2021; 231:117844. [PMID: 33577937 DOI: 10.1016/j.neuroimage.2021.117844] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 01/27/2021] [Accepted: 02/04/2021] [Indexed: 01/13/2023] Open
Abstract
Recent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD group according to the level of distance of each individual's empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to parsimoniously mimic clinical neuro-stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on the key network measures derived from the simulated brain network and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.
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Affiliation(s)
- Behzad Iravani
- Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.
| | - Artin Arshamian
- Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Peter Fransson
- Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
| | - Neda Kaboodvand
- Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
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24
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Owens MM, Allgaier N, Hahn S, Yuan D, Albaugh M, Adise S, Chaarani B, Ortigara J, Juliano A, Potter A, Garavan H. Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study. Transl Psychiatry 2021; 11:64. [PMID: 33462190 PMCID: PMC7813832 DOI: 10.1038/s41398-020-01192-8] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/30/2020] [Accepted: 12/04/2020] [Indexed: 12/18/2022] Open
Abstract
Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.
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Affiliation(s)
- Max M. Owens
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Nicholas Allgaier
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Sage Hahn
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - DeKang Yuan
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Matthew Albaugh
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Shana Adise
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Bader Chaarani
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Joseph Ortigara
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Anthony Juliano
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Alexandra Potter
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Hugh Garavan
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
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25
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Mascarell Maričić L, Walter H, Rosenthal A, Ripke S, Quinlan EB, Banaschewski T, Barker GJ, Bokde ALW, Bromberg U, Büchel C, Desrivières S, Flor H, Frouin V, Garavan H, Itterman B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Smolka MN, Fröhner JH, Whelan R, Kaminski J, Schumann G, Heinz A. The IMAGEN study: a decade of imaging genetics in adolescents. Mol Psychiatry 2020; 25:2648-2671. [PMID: 32601453 PMCID: PMC7577859 DOI: 10.1038/s41380-020-0822-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Revised: 04/10/2020] [Accepted: 06/12/2020] [Indexed: 11/17/2022]
Abstract
Imaging genetics offers the possibility of detecting associations between genotype and brain structure as well as function, with effect sizes potentially exceeding correlations between genotype and behavior. However, study results are often limited due to small sample sizes and methodological differences, thus reducing the reliability of findings. The IMAGEN cohort with 2000 young adolescents assessed from the age of 14 onwards tries to eliminate some of these limitations by offering a longitudinal approach and sufficient sample size for analyzing gene-environment interactions on brain structure and function. Here, we give a systematic review of IMAGEN publications since the start of the consortium. We then focus on the specific phenotype 'drug use' to illustrate the potential of the IMAGEN approach. We describe findings with respect to frontocortical, limbic and striatal brain volume, functional activation elicited by reward anticipation, behavioral inhibition, and affective faces, and their respective associations with drug intake. In addition to describing its strengths, we also discuss limitations of the IMAGEN study. Because of the longitudinal design and related attrition, analyses are underpowered for (epi-) genome-wide approaches due to the limited sample size. Estimating the generalizability of results requires replications in independent samples. However, such densely phenotyped longitudinal studies are still rare and alternative internal cross-validation methods (e.g., leave-one out, split-half) are also warranted. In conclusion, the IMAGEN cohort is a unique, very well characterized longitudinal sample, which helped to elucidate neurobiological mechanisms involved in complex behavior and offers the possibility to further disentangle genotype × phenotype interactions.
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Affiliation(s)
- Lea Mascarell Maričić
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Annika Rosenthal
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Stephan Ripke
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Erin Burke Quinlan
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Christian Büchel
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Sylvane Desrivières
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Bernd Itterman
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging& Psychiatry", University Paris Sud, University Paris Descartes-Sorbonne Paris Cité, and Maison de Solenn, Paris, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes, Sorbonne Université, and AP-HP, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, TechnischeUniversität Dresden, Dresden, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, TechnischeUniversität Dresden, Dresden, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jakob Kaminski
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Gunter Schumann
- Department of Social Genetic & Developmental Psychiatry, Institute of Psychiatry, King's College London, London, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany.
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26
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Owens MM, Hyatt CS, Gray JC, Miller JD, Lynam DR, Hahn S, Allgaier N, Potter A, Garavan H. Neuroanatomical correlates of impulsive traits in children aged 9 to 10. JOURNAL OF ABNORMAL PSYCHOLOGY 2020; 129:831-844. [PMID: 32897083 PMCID: PMC7606639 DOI: 10.1037/abn0000627] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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Affiliation(s)
| | | | - Joshua C. Gray
- Uniformed Services University, Department of Medical and Clinical Psychology
| | | | | | - Sage Hahn
- University of Vermont, Department of Psychiatry
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27
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Floros O, Axelsson J, Almeida R, Tigerström L, Lekander M, Sundelin T, Petrovic P. Vulnerability in Executive Functions to Sleep Deprivation Is Predicted by Subclinical Attention-Deficit/Hyperactivity Disorder Symptoms. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 6:290-298. [PMID: 33341402 DOI: 10.1016/j.bpsc.2020.09.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 09/30/2020] [Accepted: 09/30/2020] [Indexed: 12/27/2022]
Abstract
BACKGROUND Sleep loss results in state instability of cognitive functioning. It is not known whether this effect is more expressed when there is an increased cognitive demand. Moreover, while vulnerability to sleep loss varies substantially among individuals, it is not known why some people are more affected than others. We hypothesized that top-down regulation was specifically affected by sleep loss and that subclinical inattention and emotional instability traits, related to attention-deficit/hyperactivity disorder symptoms, predict this vulnerability in executive function and emotion regulation, respectively. METHODS Healthy subjects (ages 17-45 years) rated trait inattention and emotional instability before being randomized to either a night of normal sleep (n = 86) or total sleep deprivation (n = 87). Thereafter, they performed a neutral and emotional computerized Stroop task, involving words and faces. Performance was characterized primarily by cognitive conflict reaction time and reaction time variability (RTV), mirroring conflict cost in top-down regulation. RESULTS Sleep loss led to increased cognitive conflict RTV. Moreover, a higher level of inattention predicted increased cognitive conflict RTV in the neutral Stroop task after sleep deprivation (r = .30, p = .0055) but not after normal sleep (r = .055, p = .65; interaction effect β = 6.19, p = .065). This association remained after controlling for cognitive conflict reaction time and emotional instability, suggesting domain specificity. Correspondingly, emotional instability predicted cognitive conflict RTV for the emotional Stroop task only after sleep deprivation, although this effect was nonsignificant after correcting for multiple comparisons. CONCLUSIONS Our findings suggest that sleep deprivation affects cognitive conflict variability and that less stable performance in executive functioning may surface after sleep loss in vulnerable individuals characterized by subclinical symptoms of inattention.
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Affiliation(s)
- Orestis Floros
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - John Axelsson
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Stress Research Institute, Stockholm, Sweden; Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Rita Almeida
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Stockholm University Brain Imaging Center, Stockholm, Sweden
| | - Lars Tigerström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Mats Lekander
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Stress Research Institute, Stockholm, Sweden; Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Tina Sundelin
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Stress Research Institute, Stockholm, Sweden; Department of Psychology, Stockholm University, Stockholm, Sweden
| | - Predrag Petrovic
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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28
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Wang JY, Danial M, Soleymanzadeh C, Kim B, Xia Y, Kim K, Tassone F, Hagerman RJ, Rivera SM. Cortical gyrification and its relationships with molecular measures and cognition in children with the FMR1 premutation. Sci Rep 2020; 10:16059. [PMID: 32994518 PMCID: PMC7525519 DOI: 10.1038/s41598-020-73040-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 09/10/2020] [Indexed: 11/18/2022] Open
Abstract
Neurobiological basis for cognitive development and psychiatric conditions remains unexplored in children with the FMR1 premutation (PM). Knock-in mouse models of PM revealed defects in embryonic cortical development that may affect cortical folding. Cortical-folding complexity quantified using local gyrification index (LGI) was examined in 61 children (age 8–12 years, 19/14 male/female PM carriers, 15/13 male/female controls). Whole-brain vertex-wise analysis of LGI was performed for group comparisons and correlations with IQ. Individuals with aberrant gyrification in 68 cortical areas were identified using Z-scores of LGI (hyper: Z ≥ 2.58, hypo: Z ≤ − 2.58). Significant group-by-sex-by-age interaction in LGI was detected in right inferior temporal and fusiform cortices, which correlated negatively with CGG repeat length in the PM carriers. Sixteen PM boys (hyper/hypo: 7/9) and 10 PM girls (hyper/hypo: 2/5, 3 both) displayed aberrant LGI in 1–17 regions/person while 2 control boys (hyper/hypo: 0/2) and 2 control girls (hyper/hypo: 1/1) met the same criteria in only 1 region/person. LGI in the precuneus and cingulate cortices correlated positively with IQ scores in PM and control boys while negatively in PM girls and no significant correlation in control girls. These findings reveal aberrant gyrification, which may underlie cognitive performance in children with the PM.
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Affiliation(s)
- Jun Yi Wang
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA. .,MIND Institute, University of California-Davis Medical Center, Sacramento, CA, 95817, USA.
| | - Merna Danial
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA.,Department of Psychology, University of California-Davis, Davis, CA, 95616, USA
| | - Cyrus Soleymanzadeh
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA.,Department of Psychology, University of California-Davis, Davis, CA, 95616, USA
| | - Bella Kim
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA.,Department of Psychology, University of California-Davis, Davis, CA, 95616, USA
| | - Yiming Xia
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA.,Department of Psychology, University of California-Davis, Davis, CA, 95616, USA
| | - Kyoungmi Kim
- MIND Institute, University of California-Davis Medical Center, Sacramento, CA, 95817, USA.,Department of Public Health Sciences, School of Medicine, University of California-Davis, Sacramento, CA, 95817, USA
| | - Flora Tassone
- MIND Institute, University of California-Davis Medical Center, Sacramento, CA, 95817, USA.,Department of Biochemistry and Molecular Medicine, School of Medicine, University of California-Davis, Sacramento, CA, 95817, USA
| | - Randi J Hagerman
- MIND Institute, University of California-Davis Medical Center, Sacramento, CA, 95817, USA.,Department of Pediatrics, School of Medicine, University of California-Davis, Sacramento, CA, 95817, USA
| | - Susan M Rivera
- Center for Mind and Brain, University of California-Davis, 267 Cousteau Place, Davis, CA, 95618, USA.,MIND Institute, University of California-Davis Medical Center, Sacramento, CA, 95817, USA.,Department of Psychology, University of California-Davis, Davis, CA, 95616, USA
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29
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Gao Y, Jiang Y, Ming Q, Zhang J, Ma R, Wu Q, Dong D, Guo X, Liu M, Wang X, Situ W, Pauli R, Yao S. Gray Matter Changes in the Orbitofrontal-Paralimbic Cortex in Male Youths With Non-comorbid Conduct Disorder. Front Psychol 2020; 11:843. [PMID: 32435221 PMCID: PMC7218112 DOI: 10.3389/fpsyg.2020.00843] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Accepted: 04/06/2020] [Indexed: 11/29/2022] Open
Abstract
Conduct disorder is one of the most common developmental psychiatric disorders which is characterized by persistent aggressive and antisocial behaviors during childhood or adolescence. Previous neuroimaging studies have investigated the neural correlates underlying CD and demonstrated several constructive findings. However, Individuals with CD are at high risk for comorbidities, which might give rise to the inconsistencies of existed findings. It remains unclear which neuroanatomical abnormalities are specifically related to CD without comorbidities. Using structural magnetic resonance imaging (sMRI) data of 69 CD and 69 typically developing (TD) male youths (aged 14–17 years), the present study aims at investigating gray matter volume alterations of non-comorbid CD (i.e., not comorbid with attention deficit hyperactivity disorder, substance abuse disorder, anxiety or depression). We also examined how regional gray matter volumes were related to callous-unemotional (CU) traits and conduct problems in the CD group. The whole-brain analysis revealed decreased gray matter volumes in the right pre-postcentral cortex, supramarginal gyrus and right putamen in CD youths compared with TD youths. The region-of-interest analyses showed increased gray matter volumes in the superior temporal gyrus (STG) and right orbitofrontal cortex (OFC) in CD youths. Correlation analysis found that gray matter volume in the left amygdala was negatively correlated with CU traits in CD participants. These results demonstrated that gray matter volume in the orbitofrontal-paralimbic cortex, including OFC, STG and amygdala, might characterize the male youths with non-comorbid CD and might contribute to different severe forms and trajectories of CD.
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Affiliation(s)
- Yidian Gao
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Yali Jiang
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Qingsen Ming
- Department of Psychiatry, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Jibiao Zhang
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Ren Ma
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Qiong Wu
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Daifeng Dong
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Xiao Guo
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Mingli Liu
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Xiang Wang
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
| | - Weijun Situ
- Department of Radiology, Second Xiangya Hospital, Central South University, Changsha, China
| | - Ruth Pauli
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Shuqiao Yao
- Medical Psychological Center of Second Xiangya Hospital, Central South University, Changsha, China.,Medical Psychological Institute of Central South University, Changsha, China.,China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, China
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30
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Fairchild G, Hawes DJ, Frick PJ, Copeland WE, Odgers CL, Franke B, Freitag CM, De Brito SA. Conduct disorder. Nat Rev Dis Primers 2019; 5:43. [PMID: 31249310 DOI: 10.1038/s41572-019-0095-y] [Citation(s) in RCA: 158] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/17/2019] [Indexed: 02/06/2023]
Abstract
Conduct disorder (CD) is a common and highly impairing psychiatric disorder that usually emerges in childhood or adolescence and is characterized by severe antisocial and aggressive behaviour. It frequently co-occurs with attention-deficit/hyperactivity disorder (ADHD) and often leads to antisocial personality disorder in adulthood. CD affects ~3% of school-aged children and is twice as prevalent in males than in females. This disorder can be subtyped according to age at onset (childhood-onset versus adolescent-onset) and the presence or absence of callous-unemotional traits (deficits in empathy and guilt). The aetiology of CD is complex, with contributions of both genetic and environmental risk factors and different forms of interplay among the two (gene-environment interaction and correlation). In addition, CD is associated with neurocognitive impairments; smaller grey matter volume in limbic regions such as the amygdala, insula and orbitofrontal cortex, and functional abnormalities in overlapping brain circuits responsible for emotion processing, emotion regulation and reinforcement-based decision-making have been reported. Lower hypothalamic-pituitary-adrenal axis and autonomic reactivity to stress has also been reported. Management of CD primarily involves parent-based or family-based psychosocial interventions, although stimulants and atypical antipsychotics are sometimes used, especially in individuals with comorbid ADHD.
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Affiliation(s)
| | - David J Hawes
- School of Psychology, University of Sydney, Sydney, New South Wales, Australia
| | - Paul J Frick
- Department of Psychology, Louisiana State University, Baton Rouge, LA, USA and Institute for Learning Science and Teacher Education, Australian Catholic University, Brisbane, Queensland, Australia
| | | | - Candice L Odgers
- Department of Psychological Science, School of Social Ecology, University of California, Irvine, CA, USA
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Stephane A De Brito
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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