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Ren T, Zhang L, Liu Y, Zhang Q, Sun Y, Zhou W, Huang L, Wang M, Pu Y, Huang R, Chen J, He H, Zhu T, Wang S, Chen W, Zhang Q, Du W, Luo Q, Li F. Sex-specific associations of adolescent motherhood with cognitive function, behavioral problems, and autistic-like traits in offspring and the mediating roles of family conflict and altered brain structure. BMC Med 2024; 22:226. [PMID: 38840198 PMCID: PMC11155128 DOI: 10.1186/s12916-024-03442-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 05/24/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Previous studies have linked adolescent motherhood to adverse neurodevelopmental outcomes in offspring, yet the sex-specific effect and underlying mechanisms remain unclear. METHODS This study included 6952 children aged 9-11 from the Adolescent Brain Cognitive Development study. The exposed group consisted of children of mothers < 20 years at the time of birth, while the unexposed group was composed of children of mothers aged 20-35 at birth. We employed a generalized linear mixed model to investigate the associations of adolescent motherhood with cognitive, behavioral, and autistic-like traits in offspring. We applied an inverse-probability-weighted marginal structural model to examine the potential mediating factors including adverse perinatal outcomes, family conflict, and brain structure alterations. RESULTS Our results revealed that children of adolescent mothers had significantly lower cognitive scores (β, - 2.11, 95% CI, - 2.90 to - 1.31), increased externalizing problems in male offspring (mean ratio, 1.28, 95% CI, 1.08 to 1.52), and elevated internalizing problems (mean ratio, 1.14, 95% CI, 0.99 to 1.33) and autistic-like traits (mean ratio, 1.22, 95% CI, 1.01 to 1.47) in female. A stressful family environment mediated ~ 70% of the association with internalizing problems in females, ~ 30% with autistic-like traits in females, and ~ 20% with externalizing problems in males. Despite observable brain morphometric changes related to adolescent motherhood, these did not act as mediating factors in our analysis, after adjusting for family environment. No elevated rate of adverse perinatal outcomes was observed in the offspring of adolescent mothers in this study. CONCLUSIONS Our results reveal distinct sex-specific neurodevelopmental outcomes impacts of being born to adolescent mothers, with a substantial mediating effect of family environment on behavioral outcomes. These findings highlight the importance of developing sex-tailored interventions and support the hypothesis that family environment significantly impacts the neurodevelopmental consequences of adolescent motherhood.
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Affiliation(s)
- Tai Ren
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Lingli Zhang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Yongjie Liu
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Qingli Zhang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Yunjun Sun
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Wei Zhou
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Like Huang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Ming Wang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Yiwei Pu
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Runqi Huang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Jingyu Chen
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Hua He
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Tailin Zhu
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Susu Wang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Weiran Chen
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Qianlong Zhang
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China
| | - Wenchong Du
- NTU Psychology, School of Social Sciences, Nottingham Trent University, 50 Shakespeare Street, Nottingham, NG1 4FQ, UK.
| | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, Ministry of Education-Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, 220 Handan Road, Shanghai, 200433, China.
| | - Fei Li
- Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health & Department of Developmental and Behavioural Paediatric & Child Primary Care, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 1665 Kongjiang Road, Shanghai, 200092, China.
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2
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Muhetaer P, Leng J, Hu P. Deficiency in Self-Control: Unraveling Psychological and Behavioral Risk Factors for Obsessive-Compulsive Symptoms in College Students. Psychol Res Behav Manag 2024; 17:1329-1338. [PMID: 38524290 PMCID: PMC10961077 DOI: 10.2147/prbm.s456685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 03/15/2024] [Indexed: 03/26/2024] Open
Abstract
Objective Obsessive-compulsive disorder (OCD) is a complex mental disorder to treat. However, there are some deficiencies in research performed to date about the psychological and behavioral factors that may trigger obsessive-compulsive symptoms (OCS). Based on the Psychopathology of Self-Control Theory which states that deficits in self-control underpin psychiatric symptoms, this study investigated the factors influencing OCS among college students. Methods A total of 5599 non-clinical Chinese college students were recruited to complete the Chinese version of the Self-Control Scale, Aitken Procrastination Inventory, and Symptom Checklist-90. Pearson's correlation analyses and the bootstrap method were performed to test our hypothesis. Results The following results were obtained: (a) There were significant correlations among self-control, procrastination, anxiety, and OCS. (b) When controlling for the effects of age and sex, self-control remained a significant negative predictor of OCS. (c) The mediating roles of procrastination and anxiety, and the chain mediating role of procrastination and anxiety were the three predicted pathways linking self-control and OCS. Conclusion This study highlights the significance of self-control deficiencies in OCS. It provides new insights into the psychological and behavioral factors that increase the risk of OCS with important practical implications for early intervention in OCD.
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Affiliation(s)
- Palizhati Muhetaer
- Department of Psychology, Renmin University of China, Beijing, People’s Republic of China
| | - Jie Leng
- Department of Psychology, Renmin University of China, Beijing, People’s Republic of China
| | - Ping Hu
- Department of Psychology, Renmin University of China, Beijing, People’s Republic of China
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3
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Lv Q, Zeljic K, Zhao S, Zhang J, Zhang J, Wang Z. Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning. Neurosci Bull 2023; 39:1309-1326. [PMID: 37093448 PMCID: PMC10387015 DOI: 10.1007/s12264-023-01057-2] [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: 09/02/2022] [Accepted: 02/17/2023] [Indexed: 04/25/2023] Open
Abstract
Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.
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Affiliation(s)
- Qian Lv
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
| | - Kristina Zeljic
- School of Health and Psychological Sciences, City, University of London, London, EC1V 0HB, UK
| | - Shaoling Zhao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Jiangtao Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Jianmin Zhang
- Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou, 310012, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
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4
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Haghshomar M, Mirghaderi SP, Shobeiri P, James A, Zarei M. White matter abnormalities in paediatric obsessive-compulsive disorder: a systematic review of diffusion tensor imaging studies. Brain Imaging Behav 2023; 17:343-366. [PMID: 36935464 DOI: 10.1007/s11682-023-00761-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/13/2023] [Indexed: 03/21/2023]
Abstract
Microstructural alterations in white matter are evident in obsessive-compulsive disorder (OCD) both in adult and paediatric populations. Paediatric patients go through the process of maturation and thus may undergo different pathophysiology than adult OCD. Findings from studies in paediatric obsessive-compulsive disorder have been inconsistent, possibly due to their small sample size or heterogeneous populations. The aim of this review is to provide a comprehensive overview of white matter structures in paediatric obsessive-compulsive disorder and their correlation with clinical features. Based on PRISMA guidelines, we performed a systematic search on diffusion tensor imaging studies that reported fractional anisotropy, mean diffusivity, radial diffusivity, or axial diffusivity alterations between paediatric patients with obsessive-compulsive disorder and healthy controls using voxel-based analysis, or tract-based spatial statistics. We identified fifteen relevant studies. Most studies reported changes predominantly in the corpus callosum, cingulum, arcuate fasciculus, uncinate fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, forceps minor and major, and the cerebellum in paediatric obsessive-compulsive disorder. These alterations included increased and decreased fractional anisotropy and radial diffusivity, and increased mean and axial diffusivity in different white matter tracts. These changes were associated with obsessive-compulsive disorder symptoms. Moreover, specific genetic polymorphisms were linked with cerebellar white matter changes in paediatric obsessive-compulsive disorder. White matter changes are widespread in paediatric OCD patients. These changes are often associated with symptoms however there are controversies in the direction of changes in some tracts.
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Affiliation(s)
- Maryam Haghshomar
- The Medical School, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Parnian Shobeiri
- The Medical School, Tehran University of Medical Sciences, Tehran, Iran
| | - Anthony James
- Highfield Family and Adolescent Unit, Warneford Hospital, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran. .,Departments of Neurology, Odense University Hospital, Odense, Denmark. .,Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
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5
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Becker H, Liu Y, Hanna GL, Bilek E, Block SR, Hardee JE, Heitzeg MM, Pagliaccio D, Marsh R, Fitzgerald KD. Error-related brain activity associated with obsessive-compulsive symptoms in youth. Brain Behav 2023; 13:e2941. [PMID: 36919195 PMCID: PMC10097091 DOI: 10.1002/brb3.2941] [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: 07/23/2022] [Revised: 02/04/2023] [Accepted: 02/14/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Subclinical obsessive-compulsive symptoms (OCS) are common in children, and increase risk for later onset of obsessive-compulsive disorder (OCD). In pediatric patients with OCD, neuroimaging research implicates altered neural mechanisms for error-processing, but whether abnormal brain response occurs with subclinical OCS remains poorly understood. METHODS Using functional magnetic resonance imaging (fMRI), 113 youth (8-18 years; 45 female) from a community sample were scanned during an error-eliciting Go/No-Go task. OCS were assessed dimensionally using the obsessive-compulsive subscale of the Child Behavior Checklist. The association between OCS scores and error-related brain activity was examined at the whole-brain level. RESULTS Lower OCS scores associated with stronger response to errors in dorsal anterior cingulate cortex (dACC), caudate, putamen, thalamus, and occipital cortex. Additionally, lower OCS related to higher capacity for inhibitory control, as indexed by greater accuracy on No-Go trials during fMRI scanning. The relationship between lower OCS and better accuracy on No-Go trials was mediated by greater error-related dACC activity. CONCLUSIONS The inverse relationship between OCS and error-related activity in the dACC and extended cortical-striatal-thalamic circuitry may index an adaptive process by which subclinical OCS are minimized in youth. Further, these results identify an observable pattern of brain activity that tracks with subclinical OCS severity. Understanding the link between neural networks for error processing and the normal to abnormal range of OCS may pave the way for brain-based strategies to identify children who are more likely to develop OCD and enable the targeting of preventive strategies to reduce risk.
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Affiliation(s)
- Hannah Becker
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - Yanni Liu
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Gregory L Hanna
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily Bilek
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
| | | | - Jillian E Hardee
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA.,Addiction Research Center, University of Michigan, Ann Arbor, Michigan, USA
| | - Mary M Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA.,Addiction Research Center, University of Michigan, Ann Arbor, Michigan, USA
| | - David Pagliaccio
- New York State Psychiatric Institute, Columbia University, New York, New York, USA
| | - Rachel Marsh
- New York State Psychiatric Institute, Columbia University, New York, New York, USA
| | - Kate D Fitzgerald
- New York State Psychiatric Institute, Columbia University, New York, New York, USA
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6
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Alexander-Bloch AF, Sood R, Shinohara RT, Moore TM, Calkins ME, Chertavian C, Wolf DH, Gur RC, Satterthwaite TD, Gur RE, Barzilay R. Connectome-wide Functional Connectivity Abnormalities in Youth With Obsessive-Compulsive Symptoms. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:1068-1077. [PMID: 34375730 PMCID: PMC8821731 DOI: 10.1016/j.bpsc.2021.07.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 07/16/2021] [Accepted: 07/29/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Obsessive-compulsive symptomatology (OCS) is common in adolescence but usually does not meet the diagnostic threshold for obsessive-compulsive disorder. Nevertheless, both obsessive-compulsive disorder and subthreshold OCS are associated with increased likelihood of experiencing other serious psychiatric conditions, including depression and suicidal ideation. Unfortunately, there is limited information on the neurobiology of OCS. METHODS Here, we undertook one of the first brain imaging studies of OCS in a large adolescent sample (analyzed n = 832) from the Philadelphia Neurodevelopmental Cohort. We investigated resting-state functional magnetic resonance imaging functional connectivity using complementary analytic approaches that focus on different neuroanatomical scales, from known functional systems to connectome-wide tests. RESULTS We found a robust pattern of connectome-wide, OCS-related differences, as well as evidence of specific abnormalities involving known functional systems, including dorsal and ventral attention, frontoparietal, and default mode systems. Analysis of cerebral perfusion imaging and high-resolution structural imaging did not show OCS-related differences, consistent with domain specificity to functional connectivity. CONCLUSIONS The brain connectomic associations with OCS reported here, together with early studies of its clinical relevance, support the potential for OCS as an early marker of psychiatric risk that may enhance our understanding of mechanisms underlying the onset of adolescent psychopathology.
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Affiliation(s)
- Aaron F Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Rahul Sood
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Tyler M Moore
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Monica E Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Casey Chertavian
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Daniel H Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Raquel E Gur
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ran Barzilay
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; CHOP/Penn Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
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7
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Lawrence KE, Abaryan Z, Laltoo E, Hernandez LM, Gandal MJ, McCracken JT, Thompson PM. White matter microstructure shows sex differences in late childhood: Evidence from 6797 children. Hum Brain Mapp 2022; 44:535-548. [PMID: 36177528 PMCID: PMC9842921 DOI: 10.1002/hbm.26079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/29/2022] [Accepted: 08/19/2022] [Indexed: 02/01/2023] Open
Abstract
Sex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion-weighted magnetic resonance imaging approaches. However, sex differences in white matter microstructure prior to adulthood remain poorly understood; previous developmental work focused on conventional microstructure metrics and yielded mixed results. Here, we rigorously characterized sex differences in white matter microstructure among over 6000 children from the Adolescent Brain Cognitive Development study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model-diffusion tensor imaging (DTI)-and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. Sex differences in FA were regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.
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Affiliation(s)
- Katherine E. Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Zvart Abaryan
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Emily Laltoo
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Leanna M. Hernandez
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Michael J. Gandal
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA,Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCaliforniaUSA,Department of Human Genetics, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - James T. McCracken
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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8
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Grazioplene RG, DeYoung CG, Hampson M, Anticevic A, Pittenger C. Obsessive compulsive symptom dimensions are linked to altered white-matter microstructure in a community sample of youth. Transl Psychiatry 2022; 12:328. [PMID: 35948535 PMCID: PMC9365814 DOI: 10.1038/s41398-022-02013-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 05/05/2022] [Accepted: 05/30/2022] [Indexed: 11/17/2022] Open
Abstract
Obsessive-compulsive symptoms (OCS) are common in school-aged children and predict the development of obsessive compulsive disorder (OCD). White-matter abnormalities have been described in OCD, but the white matter correlates of OCS in the developing brain are unclear. Some correlates of OCS (or a diagnosis of OCD) may reflect correlates of a transdiagnostic or even general psychopathology factor. We examined these questions in a large sample of typically developing youth (N = 1208), using a hierarchical analysis of fixel-based white matter measures in relation to OCS and general psychopathology. General psychopathology was associated with abnormalities in the posterior corpus callosum and forceps major in an age-dependent manner, suggesting altered maturation (specifically, hypermaturation in younger subjects). A unidimensional measure of OCS did not associate with any white-matter abnormalities, but analysis of separate OCS dimensions (derived from factor analysis within this sample) revealed the 'Bad Thoughts' dimension to associate with white-matter abnormalities in dorsal parietal white-matter and descending corticospinal tracts, and the 'Symmetry' dimension to associate with abnormalities in the anterior corpus callosum. Repetition/checking and Symmetry OCS were additionally associated with posterior abnormalities overlapping with the correlates of general psychopathology. Contamination symptoms had no white-matter correlates. Secondary analysis of fractional anisotropy (FA) revealed distinct white-matter abnormalities, suggesting that fixel-based and FA analyses identify distinct features of white matter relevant to psychopathology. These findings suggest that OCS dimensions correlate with dissociable abnormalities in white matter, implicating separable networks. Future studies should examine these white-matter signatures in a longitudinal framework.
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Affiliation(s)
| | - Colin G DeYoung
- University of Minnesota, Department of Psychology, Minneapolis, MN, USA
| | - Michelle Hampson
- Yale University, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
| | - Alan Anticevic
- Yale University, Department of Psychiatry, New Haven, CT, USA
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9
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Weeland CJ, van den Heuvel OA, White T, Tiemeier H, Vriend C. Obsessive-compulsive symptoms and resting-state functional characteristics in pre-adolescent children from the general population. Brain Imaging Behav 2022; 16:2715-2724. [PMID: 36319909 PMCID: PMC9712396 DOI: 10.1007/s11682-022-00732-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 09/17/2022] [Accepted: 10/05/2022] [Indexed: 12/04/2022]
Abstract
While functional brain characteristics of obsessive-compulsive disorder have been extensively studied, literature on network topology and subnetwork connectivity related to obsessive-compulsive symptoms (OCS) is sparse. Here we investigated the functional brain characteristics of OCS in children from the general population using a multiscale approach. Since we previously observed OCS-related differences in thalamus morphology, we also focused on the network participation of thalamic subregions. The study included 1701 participants (9-12 years) from the population-based Generation R study. OCS were measured using the Short Obsessive-Compulsive Disorder Screener. We studied the brain network at multiple scales: global network topology, subnetwork connectivity and network participation of thalamic nodes (pre-registration: https://osf.io/azr9c ). Modularity, small-worldness and average participation coefficient were calculated on the global scale. We used a data-driven consensus community approach to extract a partition of five subnetworks involving thalamic subregions and calculate the within- and between-subnetwork functional connectivity and topology. Multiple linear regression models were fitted to model the relationship between OCS and functional brain measures. No significant associations were found when using our preregistered definition of probable OCS. However, post-hoc analyses showed that children endorsing at least one OCS (compared with controls) had higher modularity, lower connectivity between frontoparietal, limbic and visual networks as well as altered participation of the lateral prefrontal thalamus node. Our results suggest that network characteristics of OCS in children from the general population are partly symptom-specific and severity-dependent. Thorough assessment of symptom dimensions can deepen our understanding of OCS-related brain networks.
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Affiliation(s)
- Cees J Weeland
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands.
- Dept. Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Wytemaweg 8, 3015 GD, Rotterdam, the Netherlands.
- The Generation R Study Group, Erasmus Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands.
| | - Odile A van den Heuvel
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands
| | - T White
- Dept. Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Wytemaweg 8, 3015 GD, Rotterdam, the Netherlands
| | - H Tiemeier
- Harvard TH Chan School of Public Health, 677 Huntington Ave, 02115, Boston, MA, USA
| | - C Vriend
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands
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