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Liu J, Wang L, Zhang L, Ding Y, Zhang X, Hu Z, Zhao X. Abnormal amygdala volume moderates parenting and anxiety symptoms in children and adolescents with anxiety disorder. J Psychiatr Res 2024; 175:316-322. [PMID: 38759497 DOI: 10.1016/j.jpsychires.2024.05.012] [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: 12/06/2023] [Revised: 04/25/2024] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
Anxiety disorders (AD) usually onset in childhood or adolescence and are related to brain development and early experiences during this period. As the hub of the fear circuit, the amygdala plays a crucial role in the development of emotional processing, and abnormalities in its structure and function are associated with anxiety disorders. We aim to uncover the amygdala volume's moderation between parenting and anxiety severity in children and adolescents with AD. 129 children and adolescents with anxiety and 135 age- and sex-matched Health controls (HC) using the publicly available Healthy Brain Network (HBN) dataset were included. Anxiety severity was measured using the Screen for Child Anxiety Related Disorders Self-report (SCARED-SR) and parenting was measured using the Alabama Parenting Questionnaire Self-Report (APQ-SR). We investigated age-related differences in amygdala volume in children and adolescents with anxiety disorders. Further, we examined the role of amygdala volume in moderating the association between parental involvement, particularly the maternal involvement, and anxiety symptoms in this population. We found larger bilateral amygdala in the AD group compared with the HC among the age range of 7-12. And increases in amygdala volume tended to negatively moderate the linear relationships between maternal involvement and anxiety symptoms in the AD group. These findings provide new evidence of abnormal brain alteration in children and adolescents with anxiety and may reflect proactive adaptations of adolescent brain development.
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Affiliation(s)
- Jingjing Liu
- Department of Psychosomatic Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Lu Wang
- Department of Psychosomatic Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China
| | - Lei Zhang
- School of Government, Shanghai University of Political Science and Law, Shanghai, 201701, China
| | - Yue Ding
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xiaochen Zhang
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Zhishan Hu
- Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | - Xudong Zhao
- Department of Psychosomatic Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 200120, China; Pudong New Area Mental Health Centre Affiliated to Tongji University, Shanghai, 200124, China.
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Ysbæk-Nielsen AT. Exploring volumetric abnormalities in subcortical L-HPA axis structures in pediatric generalized anxiety disorder. Nord J Psychiatry 2024:1-9. [PMID: 38573199 DOI: 10.1080/08039488.2024.2335980] [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: 05/15/2023] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Pediatric generalized anxiety disorder (GAD) is debilitating and increasingly prevalent, yet its etiology remains unclear. Some believe the disorder to be propagated by chronic dysregulation of the limbic-hypothalamic-pituitary-adrenal (L-HPA) axis, but morphometric studies of implicated subcortical areas have been largely inconclusive. Recognizing that certain subcortical subdivisions are more directly involved in L-HPA axis functioning, this study aims to detect specific abnormalities in these critical areas. METHODS Thirty-eight MRI scans of preschool children with (n = 15) and without (n = 23) GAD underwent segmentation and between-group volumetric comparisons of the basolateral amygdala (BLA), ventral hippocampal subiculum (vSC), and mediodorsal medial magnocellular (MDm) area of the thalamus. RESULTS Children with GAD displayed significantly larger vSC compared to healthy peers, F(1, 31) = 6.50, pFDR = .048. On average, children with GAD presented with larger BLA and MDm, Fs(1, 31) ≥ 4.86, psFDR ≤ .054. Exploratory analyses revealed right-hemispheric lateralization of all measures, most notably the MDm, F(1, 31) = 8.13, pFDR = .024, the size of which scaled with symptom severity, r = .83, pFDR = .033. CONCLUSION The BLA, vSC, and MDm are believed to be involved in the regulation of anxiety and stress, both individually and collectively through the excitation and inhibition of the L-HPA axis. All were found to be enlarged in children with GAD, perhaps reflecting hypertrophy related to hyperexcitability, or early neuronal overgrowth. Longitudinal studies should investigate the relationship between these early morphological differences and the long-term subcortical atrophy previously observed.
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Cardoner N, Andero R, Cano M, Marin-Blasco I, Porta-Casteràs D, Serra-Blasco M, Via E, Vicent-Gil M, Portella MJ. Impact of Stress on Brain Morphology: Insights into Structural Biomarkers of Stress-related Disorders. Curr Neuropharmacol 2024; 22:935-962. [PMID: 37403395 PMCID: PMC10845094 DOI: 10.2174/1570159x21666230703091435] [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: 11/01/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 07/06/2023] Open
Abstract
Exposure to acute and chronic stress has a broad range of structural effects on the brain. The brain areas commonly targeted in the stress response models include the hippocampus, the amygdala, and the prefrontal cortex. Studies in patients suffering from the so-called stress-related disorders -embracing post-traumatic stress, major depressive and anxiety disorders- have fairly replicated animal models of stress response -particularly the neuroendocrine and the inflammatory models- by finding alterations in different brain areas, even in the early neurodevelopment. Therefore, this narrative review aims to provide an overview of structural neuroimaging findings and to discuss how these studies have contributed to our knowledge of variability in response to stress and the ulterior development of stress-related disorders. There are a gross number of studies available but neuroimaging research of stress-related disorders as a single category is still in its infancy. Although the available studies point at particular brain circuitries involved in stress and emotion regulation, the pathophysiology of these abnormalities -involving genetics, epigenetics and molecular pathways-, their relation to intraindividual stress responses -including personality characteristics, self-perception of stress conditions…-, and their potential involvement as biomarkers in diagnosis, treatment prescription and prognosis are discussed.
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Affiliation(s)
- Narcís Cardoner
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Raül Andero
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- Departament de Psicobiologia i de Metodologia de les Ciències de la Salut, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Marta Cano
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Ignacio Marin-Blasco
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Daniel Porta-Casteràs
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Maria Serra-Blasco
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Programa eHealth ICOnnecta't, Institut Català d'Oncologia, Barcelona, Spain
| | - Esther Via
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Muriel Vicent-Gil
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Maria J. Portella
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
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Liu H, Hao Z, Qiu S, Wang Q, Zhan L, Huang L, Shao Y, Wang Q, Su C, Cao Y, Sun J, Wang C, Lv Y, Li M, Shen W, Li H, Jia X. Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis. Brain Imaging Behav 2023:10.1007/s11682-023-00842-x. [PMID: 38150133 DOI: 10.1007/s11682-023-00842-x] [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] [Accepted: 12/07/2023] [Indexed: 12/28/2023]
Abstract
Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.
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Affiliation(s)
- Han Liu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Shasha Qiu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qianqian Wang
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- School of Western Languages, Heilongjiang University, Heilongjiang, China
| | - Lina Huang
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Youbin Shao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qing Wang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Chang Su
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Yikang Cao
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Chunjie Wang
- Institute of Brain Science, Department of Psychology, School of Education, Hangzhou Normal University, Hangzhou, China
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Yating Lv
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Wenbin Shen
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Huayun Li
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
| | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
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5
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Zugman A, Jett L, Antonacci C, Winkler AM, Pine DS. A systematic review and meta-analysis of resting-state fMRI in anxiety disorders: Need for data sharing to move the field forward. J Anxiety Disord 2023; 99:102773. [PMID: 37741177 PMCID: PMC10753861 DOI: 10.1016/j.janxdis.2023.102773] [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: 08/31/2022] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/25/2023]
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders. Neuroimaging findings remain uncertain, and resting state functional magnetic resonance (rs-fMRI) connectivity is of particular interest since it is a scalable functional imaging modality. Given heterogeneous past findings for rs-fMRI in anxious individuals, we characterize patterns across anxiety disorders by conducting a systematic review and meta-analysis. Studies were included if they contained at the time of scanning both a healthy group and a patient group. Due to insufficient study numbers, the quantitative meta-analysis only included seed-based studies. We performed an activation likelihood estimation (ALE) analysis that compared patients and healthy volunteers. All analyses were corrected for family-wise error with a cluster-level threshold of p < .05. Patients exhibited hypo-connectivity between the amygdala and the medial frontal gyrus, anterior cingulate cortex, and cingulate gyrus. This finding, however, was not robust to potential file-drawer effects. Though limited by strict inclusion criteria, our results highlight the heterogeneous nature of reported findings. This underscores the need for data sharing when attempting to detect reliable patterns of disruption in brain activity across anxiety disorders.
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Affiliation(s)
- André Zugman
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
| | - Laura Jett
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Child Emotion Lab, University of Wisconsin, Madison, Madison, WI, United States.
| | - Chase Antonacci
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Department of Psychology, Stanford University, Stanford, CA, United States.
| | - Anderson M Winkler
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Division of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, Texas, United States.
| | - Daniel S Pine
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
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6
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Yoo C, Kim MJ. Topographical similarity of cortical thickness represents generalized anxiety symptoms in adolescence. Brain Res Bull 2023; 202:110728. [PMID: 37558098 DOI: 10.1016/j.brainresbull.2023.110728] [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: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/05/2023] [Indexed: 08/11/2023]
Abstract
Generalized anxiety disorder (GAD) is a common condition characterized by excessive and uncontrollable worry, along with its high comorbidity rates. Despite increasing efforts to identify the neural underpinnings of GAD, neuroimaging research using cortical thickness have yielded largely inconsistent results. To address this, we adopted an inter-subject representational similarity analysis framework to explore a potential nonlinear relationship between vertex-wise cortical thickness and generalized anxiety symptom severity. We utilized a sample of 120 adolescents (13-18 years of age) from the Healthy Brain Network dataset. Here, we found greater topographical resemblance among participants with heightened generalized anxiety symptoms in the left caudal anterior cingulate and pericalcarine cortex. These results were not driven by the effects of age, sex, ADHD diagnosis, and GAD diagnosis. Such associations were not observed when including a group of younger participants (11-12 years of age) for analyses, highlighting the importance of age range selection when considering the link between cortical thickness and anxiety. Our findings reveal a novel cortical thickness topography that represents generalized anxiety in adolescents, which is embedded within the shared geometries between generalized anxiety symptoms and cortical thickness.
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Affiliation(s)
- Chaebin Yoo
- Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, South Korea
| | - M Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, South Korea.
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7
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Steinhäuser JL, Teed AR, Al-Zoubi O, Hurlemann R, Chen G, Khalsa SS. Reduced vmPFC-insula functional connectivity in generalized anxiety disorder: a Bayesian confirmation study. Sci Rep 2023; 13:9626. [PMID: 37316518 DOI: 10.1038/s41598-023-35939-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/26/2023] [Indexed: 06/16/2023] Open
Abstract
Differences in the correlated activity of networked brain regions have been reported in individuals with generalized anxiety disorder (GAD) but an overreliance on null-hypothesis significance testing (NHST) limits the identification of disorder-relevant relationships. In this preregistered study, we applied both a Bayesian statistical framework and NHST to the analysis of resting-state fMRI scans from females with GAD and matched healthy comparison females. Eleven a-priori hypotheses about functional connectivity (FC) were evaluated using Bayesian (multilevel model) and frequentist (t-test) inference. Reduced FC between the ventromedial prefrontal cortex (vmPFC) and the posterior-mid insula (PMI) was confirmed by both statistical approaches and was associated with anxiety sensitivity. FC between the vmPFC-anterior insula, the amygdala-PMI, and the amygdala-dorsolateral prefrontal cortex (dlPFC) region pairs did not survive multiple comparison correction using the frequentist approach. However, the Bayesian model provided evidence for these region pairs having decreased FC in the GAD group. Leveraging Bayesian modeling, we demonstrate decreased FC of the vmPFC, insula, amygdala, and dlPFC in females with GAD. Exploiting the Bayesian framework revealed FC abnormalities between region pairs excluded by the frequentist analysis and other previously undescribed regions in GAD, demonstrating the value of applying this approach to resting-state FC data in clinical investigations.
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Affiliation(s)
- Jonas L Steinhäuser
- Laureate Institute for Brain Research, Tulsa, OK, USA.
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
| | - Adam R Teed
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Obada Al-Zoubi
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Department of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - René Hurlemann
- Department of Psychiatry, School of Medicine & Health Sciences, University of Oldenburg, Oldenburg, Germany
- Research Center Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Gang Chen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, MD, USA
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, USA.
- Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, USA.
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Tian YE, Di Biase MA, Mosley PE, Lupton MK, Xia Y, Fripp J, Breakspear M, Cropley V, Zalesky A. Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders. JAMA Psychiatry 2023; 80:567-576. [PMID: 37099313 PMCID: PMC10134046 DOI: 10.1001/jamapsychiatry.2023.0791] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/15/2023] [Indexed: 04/27/2023]
Abstract
Importance Physical health and chronic medical comorbidities are underestimated, inadequately treated, and often overlooked in psychiatry. A multiorgan, systemwide characterization of brain and body health in neuropsychiatric disorders may enable systematic evaluation of brain-body health status in patients and potentially identify new therapeutic targets. Objective To evaluate the health status of the brain and 7 body systems across common neuropsychiatric disorders. Design, Setting, and Participants Brain imaging phenotypes, physiological measures, and blood- and urine-based markers were harmonized across multiple population-based neuroimaging biobanks in the US, UK, and Australia, including UK Biobank; Australian Schizophrenia Research Bank; Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative; Prospective Imaging Study of Ageing; Human Connectome Project-Young Adult; and Human Connectome Project-Aging. Cross-sectional data acquired between March 2006 and December 2020 were used to study organ health. Data were analyzed from October 18, 2021, to July 21, 2022. Adults aged 18 to 95 years with a lifetime diagnosis of 1 or more common neuropsychiatric disorders, including schizophrenia, bipolar disorder, depression, generalized anxiety disorder, and a healthy comparison group were included. Main Outcomes and Measures Deviations from normative reference ranges for composite health scores indexing the health and function of the brain and 7 body systems. Secondary outcomes included accuracy of classifying diagnoses (disease vs control) and differentiating between diagnoses (disease vs disease), measured using the area under the receiver operating characteristic curve (AUC). Results There were 85 748 participants with preselected neuropsychiatric disorders (36 324 male) and 87 420 healthy control individuals (40 560 male) included in this study. Body health, especially scores indexing metabolic, hepatic, and immune health, deviated from normative reference ranges for all 4 neuropsychiatric disorders studied. Poor body health was a more pronounced illness manifestation compared to brain changes in schizophrenia (AUC for body = 0.81 [95% CI, 0.79-0.82]; AUC for brain = 0.79 [95% CI, 0.79-0.79]), bipolar disorder (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.57-0.58]), depression (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.58-0.58]), and anxiety (AUC for body = 0.63 [95% CI, 0.63-0.63]; AUC for brain = 0.57 [95% CI, 0.57-0.58]). However, brain health enabled more accurate differentiation between distinct neuropsychiatric diagnoses than body health (schizophrenia-other: mean AUC for body = 0.70 [95% CI, 0.70-0.71] and mean AUC for brain = 0.79 [95% CI, 0.79-0.80]; bipolar disorder-other: mean AUC for body = 0.60 [95% CI, 0.59-0.60] and mean AUC for brain = 0.65 [95% CI, 0.65-0.65]; depression-other: mean AUC for body = 0.61 [95% CI, 0.60-0.63] and mean AUC for brain = 0.65 [95% CI, 0.65-0.66]; anxiety-other: mean AUC for body = 0.63 [95% CI, 0.62-0.63] and mean AUC for brain = 0.66 [95% CI, 0.65-0.66). Conclusions and Relevance In this cross-sectional study, neuropsychiatric disorders shared a substantial and largely overlapping imprint of poor body health. Routinely monitoring body health and integrated physical and mental health care may help reduce the adverse effect of physical comorbidity in people with mental illness.
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Affiliation(s)
- Ye Ella Tian
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Maria A. Di Biase
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Philip E. Mosley
- Clinical Brain Networks Group, Queensland Institute of Medical Research Berghofer Medical Institute, Brisbane, Queensland, Australia
- Queensland Brain Institute, Brisbane, Queensland, Australia
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Michelle K. Lupton
- Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ying Xia
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Jurgen Fripp
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Michael Breakspear
- Discipline of Psychiatry, College of Health, Medicine and Wellbeing, the University of Newcastle, Newcastle, New South Wales, Australia
- School of Psychological Sciences, College of Engineering, Science and Environment, the University of Newcastle, Newcastle, New South Wales, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Andrew Zalesky
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, Faculty of Engineering and Information Technology, the University of Melbourne, Melbourne, Victoria, Australia
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9
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Hou J, Liu S, van Wingen G. Increased subcortical brain activity in anxious but not depressed individuals. J Psychiatr Res 2023; 160:38-46. [PMID: 36773346 DOI: 10.1016/j.jpsychires.2023.02.013] [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: 08/22/2022] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 02/10/2023]
Abstract
BACKGROUND Anxiety and depressive symptoms usually co-occur. Neuroimaging abnormalities in patients with depression and anxiety disorders are therefore related to a combination of symptoms. Here, we used a large population study to select individuals with anxiety, depressive, or both anxiety and depressive symptoms to identify whether neuroimaging differences are unique or shared between anxiety and depressive symptoms. METHODS We selected four groups of 200 individuals (anxiety, depression, anxiety and depression, controls) from the UK Biobank, matched for age, sex, intelligence, and educational attainment (total N = 800). We extracted the amplitude of low frequency fluctuations (ALFF) from resting-state functional magnetic resonance imaging data, which indexes spontaneous neuronal activity. Group differences were assessed using permutation testing to correct for multiple comparisons, with age, sex, IQ, and head motion as covariates. RESULTS Compared to controls, anxious individuals had higher ALFF values in many subcortical brain regions including the striatum, thalamus, medial temporal lobe, midbrain, pons, as well as the cerebellum. Anxious individuals also showed higher ALFF in the hippocampus, parahippocampal gyrus, cerebellum, and pons compared to individuals with depressive symptoms. No significant differences were found for the depression and combined anxiety/depression groups. Post-hoc tests with largest possible samples showed comparable results in the anxiety group and in the combined group, but still no significant differences for the depression group. CONCLUSIONS Anxiety but not depressive symptoms were associated with increased subcortical activity during rest. This suggest that anxiety symptoms may have the largest contribution to the neuroimaging differences in individuals with depression and anxiety disorders.
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Affiliation(s)
- Jiangyun Hou
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Shu Liu
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Guido van Wingen
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands.
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10
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Rojczyk P, Seitz-Holland J, Kaufmann E, Sydnor VJ, Kim CL, Umminger LF, Wiegand TLT, Guenette JP, Zhang F, Rathi Y, Bouix S, Pasternak O, Fortier CB, Salat D, Hinds SR, Heinen F, O’Donnell LJ, Milberg WP, McGlinchey RE, Shenton ME, Koerte IK. Sleep Quality Disturbances Are Associated with White Matter Alterations in Veterans with Post-Traumatic Stress Disorder and Mild Traumatic Brain Injury. J Clin Med 2023; 12:2079. [PMID: 36902865 PMCID: PMC10004675 DOI: 10.3390/jcm12052079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/09/2023] Open
Abstract
Sleep disturbances are strongly associated with mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). PTSD and mTBI have been linked to alterations in white matter (WM) microstructure, but whether poor sleep quality has a compounding effect on WM remains largely unknown. We evaluated sleep and diffusion magnetic resonance imaging (dMRI) data from 180 male post-9/11 veterans diagnosed with (1) PTSD (n = 38), (2) mTBI (n = 25), (3) comorbid PTSD+mTBI (n = 94), and (4) a control group with neither PTSD nor mTBI (n = 23). We compared sleep quality (Pittsburgh Sleep Quality Index, PSQI) between groups using ANCOVAs and calculated regression and mediation models to assess associations between PTSD, mTBI, sleep quality, and WM. Veterans with PTSD and comorbid PTSD+mTBI reported poorer sleep quality than those with mTBI or no history of PTSD or mTBI (p = 0.012 to <0.001). Poor sleep quality was associated with abnormal WM microstructure in veterans with comorbid PTSD+mTBI (p < 0.001). Most importantly, poor sleep quality fully mediated the association between greater PTSD symptom severity and impaired WM microstructure (p < 0.001). Our findings highlight the significant impact of sleep disturbances on brain health in veterans with PTSD+mTBI, calling for sleep-targeted interventions.
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Affiliation(s)
- Philine Rojczyk
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
| | - Johanna Seitz-Holland
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Elisabeth Kaufmann
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
- Department of Neurology, Ludwig-Maximilians-University, 81377 Munich, Germany
| | - Valerie J. Sydnor
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
| | - Cara L. Kim
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
| | - Lisa F. Umminger
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
| | - Tim L. T. Wiegand
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
| | - Jeffrey P. Guenette
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Software Engineering and IT, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Catherine B. Fortier
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
| | - David Salat
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, USA
- Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, 02115 MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Boston, MA 02129, USA
| | - Sidney R. Hinds
- Department of Neurology, Uniformed Services University, Bethesda, MD 20814, USA
| | - Florian Heinen
- Department of Pediatric Neurology and Developmental Medicine and LMU Center for Children with Medical Complexity, Dr. von Hauner Children’s Hospital, Ludwig-Maximilians-University, 80337 Munich, Germany
| | - Lauren J. O’Donnell
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - William P. Milberg
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, 02115 MA, USA
| | - Regina E. McGlinchey
- Translational Research Center for TBI and Stress Disorders (TRACTS) and Geriatric Research, Education and Clinical Center (GRECC), VA Boston Healthcare System, Boston, MA 02130, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- Neuroimaging Research for Veterans (NeRVe) Center, VA Boston Healthcare System, Boston, 02115 MA, USA
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Inga K. Koerte
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02145, USA
- cBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-University, 80336 Munich, Germany
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-University, 82152 Munich, Germany
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11
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Groenewold NA, Bas-Hoogendam JM, Amod AR, Laansma MA, Van Velzen LS, Aghajani M, Hilbert K, Oh H, Salas R, Jackowski AP, Pan PM, Salum GA, Blair JR, Blair KS, Hirsch J, Pantazatos SP, Schneier FR, Talati A, Roelofs K, Volman I, Blanco-Hinojo L, Cardoner N, Pujol J, Beesdo-Baum K, Ching CRK, Thomopoulos SI, Jansen A, Kircher T, Krug A, Nenadić I, Stein F, Dannlowski U, Grotegerd D, Lemke H, Meinert S, Winter A, Erb M, Kreifelts B, Gong Q, Lui S, Zhu F, Mwangi B, Soares JC, Wu MJ, Bayram A, Canli M, Tükel R, Westenberg PM, Heeren A, Cremers HR, Hofmann D, Straube T, Doruyter AGG, Lochner C, Peterburs J, Van Tol MJ, Gur RE, Kaczkurkin AN, Larsen B, Satterthwaite TD, Filippi CA, Gold AL, Harrewijn A, Zugman A, Bülow R, Grabe HJ, Völzke H, Wittfeld K, Böhnlein J, Dohm K, Kugel H, Schrammen E, Zwanzger P, Leehr EJ, Sindermann L, Ball TM, Fonzo GA, Paulus MP, Simmons A, Stein MB, Klumpp H, Phan KL, Furmark T, Månsson KNT, Manzouri A, Avery SN, Blackford JU, Clauss JA, Feola B, Harper JC, Sylvester CM, Lueken U, Veltman DJ, Winkler AM, Jahanshad N, Pine DS, Thompson PM, Stein DJ, Van der Wee NJA. Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group. Mol Psychiatry 2023; 28:1079-1089. [PMID: 36653677 PMCID: PMC10804423 DOI: 10.1038/s41380-022-01933-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 10/31/2022] [Accepted: 12/15/2022] [Indexed: 01/20/2023]
Abstract
There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE < 0.001; right: d = -0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.
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Affiliation(s)
- Nynke A Groenewold
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
- South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa.
| | - Janna Marie Bas-Hoogendam
- Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | - Alyssa R Amod
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Laura S Van Velzen
- Orygen & Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Moji Aghajani
- Leiden University, Institute of Education & Child Studies, Section Forensic Family & Youth Care, Leiden, Netherlands
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Hyuntaek Oh
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
- Michael E DeBakey VA Medical Center, Center for Translational Research on Inflammatory Diseases, Houston, TX, USA
| | - Andrea P Jackowski
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Pedro M Pan
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Giovanni A Salum
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - James R Blair
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, Copenhagen, Denmark
| | - Karina S Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Joy Hirsch
- Departments of Psychiatry & Neurobiology, Yale School of Medicine, New Haven, CT, USA
| | - Spiro P Pantazatos
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Franklin R Schneier
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Ardesheer Talati
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Karin Roelofs
- Donders Institute for Brain, Cognition and Behavior, Radboud University Behavioral Science Institute, Radboud University, Nijmegen, Netherlands
| | - Inge Volman
- Wellcome Centre for Integrative Neuroimaging Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK
| | - Laura Blanco-Hinojo
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Narcís Cardoner
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Jesus Pujol
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Katja Beesdo-Baum
- Behavioral Epidemiology, Institute of Clinical Psycholog and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Andreas Jansen
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry, University of Marburg, Marburg, Germany
- Department of Psychiatry, University Hospital of Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Michael Erb
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Benjamin Kreifelts
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Fei Zhu
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Benson Mwangi
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jair C Soares
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mon-Ju Wu
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ali Bayram
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Mesut Canli
- Department of Physiology, Istanbul University, Istanbul, Turkey
| | - Raşit Tükel
- Department of Psychiatry, Istanbul University, Istanbul, Turkey
| | - P Michiel Westenberg
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | - Alexandre Heeren
- Psychological Science Research Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Henk R Cremers
- Department of Clinical Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | | | - Christine Lochner
- SA-MRC Unit on Risk and Resilience in Mental Disorders, Stellenbosch University, Stellenbosch, South Africa
| | - Jutta Peterburs
- Institute of Systems Medicine and Faculty of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
| | - Marie-José Van Tol
- Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bart Larsen
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Andrea L Gold
- Department of Psychiatry and Human Behavior, Brown University Warren Alpert Medical School, Providence, RI, USA
| | - Anita Harrewijn
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - André Zugman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Joscha Böhnlein
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Harald Kugel
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Elisabeth Schrammen
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Peter Zwanzger
- KBO-Inn-Salzach-Klinikum, Munich, Germany
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University of Munich, Munich, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lisa Sindermann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Tali M Ball
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Gregory A Fonzo
- Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | | | - Alan Simmons
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Murray B Stein
- Departments of Psychiatry & School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Heide Klumpp
- Departments of Psychology & Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry & Behavioral Health, the Ohio State University, Columbus, OH, USA
| | - Tomas Furmark
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | | | | | - Suzanne N Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Brandee Feola
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Chad M Sylvester
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC location VUMC, Amsterdam, Netherlands
| | - Anderson M Winkler
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dan J Stein
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SA-MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
| | - Nic J A Van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
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12
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Yang X, Cheng B, Yang J, Cheng S, Pan C, Zhao Y, Zhang H, Liu L, Meng P, Zhang J, Zhang Z, Li C, Chen Y, He D, Wen Y, Jia Y, Liu H, Zhang F. Assessing the interaction effects of brain structure longitudinal changes and life environmental factors on depression and anxiety. Hum Brain Mapp 2023; 44:1227-1238. [PMID: 36416531 PMCID: PMC9875931 DOI: 10.1002/hbm.26153] [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: 07/10/2022] [Revised: 10/16/2022] [Accepted: 11/07/2022] [Indexed: 11/25/2022] Open
Abstract
Disrupted brain structures and several life environmental factors have been shown to influence depression and anxiety, but their interactions with anxiety and depression remain elusive. Genome-wide association study datasets of 15 brain structure longitudinal changes (N = 15,640) were obtained from the published study. Genotype and phenotype-related data of depression, anxiety, and life environmental factors (including smoking, alcohol drinking, coffee intake, maternal smoking, physical activity, vitamin D, insomnia, sleep duration, and family satisfaction) were collected from UK Biobank. We calculated the polygenic risk scores (PRS) of 15 brain structure changes and then conducted linear regression analyses to explore the interactions of brain structure changes and life environmental factors on depression and anxiety using 15 brain structure change-related PRS, life environmental factors and interactions of them as instrumental variables, and depression score or anxiety score as outcomes. Sex stratification in all analyses was performed to reveal sex-specific differences in the interactions. We found 14 shared interactions related to both depression and anxiety in total sample, such as alcohol drinking × cerebellum white matter 3 (WM; beta = -.003, p = .018 for depression; beta = -003, p = .008 for anxiety) and maternal smoking × nucleus accumbens 2 (beta = .088, p = .002 for depression; beta = .070, p = .008 for anxiety). We also observed sex-specific differences in the interactions, for instance, alcohol drinking × cerebellum WM 3 was negatively associated with depression and anxiety in males (beta = -.004, p = .020 for depression; beta = -.005, p = .002 for anxiety). Our study results reveal the important interactions between brain structure changes and several life environmental factors on depression and anxiety, which may help to explore the pathogenesis of depression and anxiety.
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Affiliation(s)
- Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Bolun Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Jian Yang
- Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Chuyu Pan
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yijing Zhao
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Huijie Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Li Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Jingxi Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Zhen Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yujing Chen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yan Wen
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Yumeng Jia
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Huan Liu
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.,Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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13
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The neurobiology of irritable bowel syndrome. Mol Psychiatry 2023; 28:1451-1465. [PMID: 36732586 DOI: 10.1038/s41380-023-01972-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/06/2023] [Accepted: 01/17/2023] [Indexed: 02/04/2023]
Abstract
Irritable bowel syndrome (IBS) is the most prevalent disorder of brain-gut interactions that affects between 5 and 10% of the general population worldwide. The current symptom criteria restrict the diagnosis to recurrent abdominal pain associated with altered bowel habits, but the majority of patients also report non-painful abdominal discomfort, associated psychiatric conditions (anxiety and depression), as well as other visceral and somatic pain-related symptoms. For decades, IBS was considered an intestinal motility disorder, and more recently a gut disorder. However, based on an extensive body of reported information about central, peripheral mechanisms and genetic factors involved in the pathophysiology of IBS symptoms, a comprehensive disease model of brain-gut-microbiome interactions has emerged, which can explain altered bowel habits, chronic abdominal pain, and psychiatric comorbidities. In this review, we will first describe novel insights into several key components of brain-gut microbiome interactions, starting with reported alterations in the gut connectome and enteric nervous system, and a list of distinct functional and structural brain signatures, and comparing them to the proposed brain alterations in anxiety disorders. We will then point out the emerging correlations between the brain networks with the genomic, gastrointestinal, immune, and gut microbiome-related parameters. We will incorporate this new information into a systems-based disease model of IBS. Finally, we will discuss the implications of such a model for the improved understanding of the disorder and the development of more effective treatment approaches in the future.
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14
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Sambuco N, Bradley MM, Lang PJ. Hippocampal and amygdala volumes vary with transdiagnostic psychopathological dimensions of distress, anxious arousal, and trauma. Biol Psychol 2023; 177:108501. [PMID: 36646300 DOI: 10.1016/j.biopsycho.2023.108501] [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: 07/01/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 01/15/2023]
Abstract
Reduced hippocampal and/or amygdala volumes have been reported in patients with a variety of different anxiety diagnoses, suggesting that structural alterations may vary transdiagnostically across the internalizing disorders. The current study measured hippocampal and amygdala volumes in anxiety and mood disorder patients assessing differences that vary dimensionally with transdiagnostic factors of distress, anxious arousal, and trauma, based on a principal components analysis of questionnaires relating to symptomology. High-resolution structural images were collected in a sample of 165 patients, and volumes extracted from the hippocampal formation (including CA1, CA2/3, CA4/DG, subiculum, and molecular layer) and the amygdala. Transdiagnostically, increasing distress was associated with reduced hippocampal CA1 volume, increasing anxious arousal was associated with reduced hippocampal CA4/DG volume, and increasing trauma severity was associated with reduced amygdala volume in women. Taken together, the data indicate that subcortical brain volumes decrease as the severity of transdiagnostic psychopathological symptomology increases.
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Affiliation(s)
- Nicola Sambuco
- Center for the Study of Emotion and Attention, University of Florida, Gainesville, FL, USA.
| | - Margaret M Bradley
- Center for the Study of Emotion and Attention, University of Florida, Gainesville, FL, USA
| | - Peter J Lang
- Center for the Study of Emotion and Attention, University of Florida, Gainesville, FL, USA
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15
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Higher polygenic risk scores for anxiety disorders are associated with reduced area in the anterior cingulate gyrus. J Affect Disord 2023; 320:291-297. [PMID: 36150406 DOI: 10.1016/j.jad.2022.09.041] [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: 07/27/2022] [Revised: 08/27/2022] [Accepted: 09/19/2022] [Indexed: 02/02/2023]
Abstract
Anxiety disorders are heterogeneous, show a moderate genetic contribution and are associated with inconsistent cortical structure alterations. Here, we investigated whether genetic factors for anxiety disorders contribute to cortical alterations by conducting polygenic risk score (PRS) analyses. We calculated PRSs for anxiety disorders at several P value thresholds (from PT ≤ 5.0 × 10-8 to PT ≤ 1.0) based on the latest large-scale genome-wide association study of anxiety disorders from the UK biobank (25,453 cases; 58,113 controls) in an independent sample of psychiatrically and physically healthy subjects (n = 174). Using regression after adjusting for confounding factors, we tested whether these PRSs were associated with the surface area and cortical thickness in 34 bilateral brain regions extracted using FreeSurfer. A higher PRS for anxiety disorders at PT ≤ 1.0 was significantly associated with a reduced right caudal anterior cingulate area (beta = -0.25, puncorrected = 9.51 × 10-4, pcorrected = 0.032). PRSs based on more common SNPs, especially from PT ≤ 0.01 to PT ≤ 1.0, were associated with the right caudal anterior cingulate area (a maximum at PT ≤ 0.5: R2 = 0.066, beta = -0.27, puncorr = 3.81 × 10-4, pcorr = 0.013). Furthermore, individuals in the highest quartile for anxiety disorder PRS had lower surface area and volume in the right anterior cingulate gyrus than those in the lowest quartile. We suggest a shared genetic etiology between anxiety disorders and structural features of the anterior cingulate gyrus, possibly contributing to the pathogenesis of anxiety disorders via emotional dysregulations. Our findings suggest the potential usefulness of PRS to reduce pathological heterogeneity among anxiety disorders.
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16
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Liu X, Klugah-Brown B, Zhang R, Chen H, Zhang J, Becker B. Pathological fear, anxiety and negative affect exhibit distinct neurostructural signatures: evidence from psychiatric neuroimaging meta-analysis. Transl Psychiatry 2022; 12:405. [PMID: 36151073 PMCID: PMC9508096 DOI: 10.1038/s41398-022-02157-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 09/04/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
Internalizing disorders encompass anxiety, fear and depressive disorders, which exhibit overlap at both conceptual and symptom levels. Given that a neurobiological evaluation is lacking, we conducted a Seed-based D-Mapping comparative meta-analysis including coordinates as well as original statistical maps to determine common and disorder-specific gray matter volume alterations in generalized anxiety disorder (GAD), fear-related anxiety disorders (FAD, i.e., social anxiety disorder, specific phobias, panic disorder) and major depressive disorder (MDD). Results showed that GAD exhibited disorder-specific altered volumes relative to FAD including decreased volumes in left insula and lateral/medial prefrontal cortex as well as increased right putamen volume. Both GAD and MDD showed decreased prefrontal volumes compared to controls and FAD. While FAD showed less robust alterations in lingual gyrus compared to controls, this group presented intact frontal integrity. No shared structural abnormalities were found. Our study is the first to provide meta-analytic evidence for distinct neuroanatomical abnormalities underlying the pathophysiology of anxiety-, fear-related and depressive disorders. These findings may have implications for determining promising target regions for disorder-specific neuromodulation interventions (e.g. transcranial magnetic stimulation or neurofeedback).
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Affiliation(s)
- Xiqin Liu
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Benjamin Klugah-Brown
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Ran Zhang
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Huafu Chen
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Jie Zhang
- grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, 200433 Shanghai, P. R. China ,grid.8547.e0000 0001 0125 2443Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, 200433 Shanghai, P. R. China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731, Chengdu, P. R. China.
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17
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Kobayashi R, Sakurai N, Nagasaka K, Kasai S, Kodama N. Relationship between Tactile Sensation, Motor Activity, and Differential Brain Activity in Young Individuals. Brain Sci 2022; 12:brainsci12070924. [PMID: 35884731 PMCID: PMC9321563 DOI: 10.3390/brainsci12070924] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/12/2022] [Accepted: 07/13/2022] [Indexed: 02/01/2023] Open
Abstract
In this study, we compared the differences in brain activation associated with the different types of objects using functional magnetic resonance imaging (fMRI). Twenty-six participants in their 20s underwent fMRI while grasping four different types of objects. After the experiment, all of the participants completed a questionnaire based on the Likert Scale, which asked them about the sensations they experienced while grasping each object (comfort, hardness, pain, ease in grasping). We investigated the relationship between brain activity and the results of the survey; characteristic brain activity for each object was correlated with the results of the questionnaire, indicating that each object produced a different sensation response in the participants. Additionally, we observed brain activity in the primary somatosensory cortex (postcentral gyrus), the primary motor cortex (precentral gyrus), and the cerebellum exterior during the gripping task. Our study shows that gripping different objects produces activity in specific and distinct brain regions and suggests an “action appraisal” mechanism, which is considered to be the act of integrating multiple different sensory information and connecting it to actual action. To the best of our knowledge, this is the first study to observe brain activity in response to tactile stimuli and motor activity simultaneously.
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Affiliation(s)
- Ryota Kobayashi
- CLAIRVO TECHNOLOGIES, Inc., 1-4-2 Ohtemachi, Chiyoda-ku, Tokyo 100-8088, Japan
- Correspondence: (R.K.); (N.K.)
| | - Noriko Sakurai
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata 950-3198, Japan; (N.S.); (S.K.)
| | - Kazuaki Nagasaka
- Department of Physical Therapy, Faculty of Rehabilitation, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata 950-3198, Japan;
| | - Satoshi Kasai
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata 950-3198, Japan; (N.S.); (S.K.)
| | - Naoki Kodama
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, 1398 Shimami-cho, Kita-ku, Niigata 950-3198, Japan; (N.S.); (S.K.)
- Correspondence: (R.K.); (N.K.)
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18
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Rook L, Mazza MC, Lefter I, Brazier F. Toward Linguistic Recognition of Generalized Anxiety Disorder. Front Digit Health 2022; 4:779039. [PMID: 35493530 PMCID: PMC9051024 DOI: 10.3389/fdgth.2022.779039] [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: 09/17/2021] [Accepted: 03/21/2022] [Indexed: 11/21/2022] Open
Abstract
Background Generalized anxiety disorder (GAD) refers to extreme, uncontrollable, and persistent worry and anxiety. The disorder is known to affect the social functioning and well-being of millions of people, but despite its prevalence and burden to society, it has proven difficult to identify unique behavioral markers. Interestingly, the worrying behavior observed in GAD is argued to stem from a verbal linguistic process. Therefore, the aim of the present study was to investigate if GAD can be predicted from the language people use to put their anxious worries into words. Given the importance of avoidance sensitivity (a higher likelihood to respond anxiously to novel or unexpected triggers) in GAD, this study also explored if prediction accuracy increases when individual differences in behavioral avoidance and approach sensitivity are taken into account. Method An expressive writing exercise was used to explore whether GAD can be predicted from linguistic characteristics of written narratives. Specifically, 144 undergraduate student participants were asked to recall an anxious experience during their university life, and describe this experience in written form. Clinically validated behavioral measures for GAD and self-reported sensitivity in behavioral avoidance/inhibition (BIS) and behavioral approach (BAS), were collected. A set of classification experiments was performed to evaluate GAD predictability based on linguistic features, BIS/BAS scores, and a concatenation of the two. Results The classification results show that GAD can, indeed, be successfully predicted from anxiety-focused written narratives. Prediction accuracy increased when differences in BIS and BAS were included, which suggests that, under those conditions, negatively valenced emotion words and words relating to social processes could be sufficient for recognition of GAD. Conclusions Undergraduate students with a high GAD score can be identified based on their written recollection of an anxious experience during university life. This insight is an important first step toward development of text-based digital health applications and technologies aimed at remote screening for GAD. Future work should investigate the extent to which these results uniquely apply to university campus populations or generalize to other demographics.
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Moore EM, Xia Y. Neurodevelopmental Trajectories Following Prenatal Alcohol Exposure. Front Hum Neurosci 2022; 15:695855. [PMID: 35058760 PMCID: PMC8763806 DOI: 10.3389/fnhum.2021.695855] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 11/29/2021] [Indexed: 12/18/2022] Open
Abstract
Prenatal alcohol exposure (PAE) interferes with neurodevelopment. The brain is particularly susceptible to the adverse consequences of prenatal alcohol exposure, and numerous studies have documented changes to brain anatomy and function, as well as consequences for cognition, behavior, and mental health. Studies in typically developing individuals have shown that the brain undergoes dynamic developmental processes over an individual’s lifespan. Furthermore, magnetic resonance imaging (MRI) studies in other neurodevelopmental and psychiatric disorders have shown that their developmental trajectories differ from the typical pattern. Therefore, to understand long-term clinical outcomes of fetal alcohol spectrum disorders (FASD), it is necessary to investigate changes in neurodevelopmental trajectories in this population. Here we review studies that have used MRI to evaluate changes in brain structure and function over time via cross-sectional or longitudinal methods in individuals with PAE. Research demonstrates that individuals with PAE have atypical cortical and white matter microstructural developmental trajectories through childhood and adolescence. More research is needed to understand how factors such as sex and postnatal experiences may further mediate these trajectories. Furthermore, nothing is known about the trajectories beyond young adulthood.
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Li S, Bai R, Yang Y, Zhao R, Upreti B, Wang X, Liu S, Cheng Y, Xu J. Abnormal cortical thickness and structural covariance networks in systemic lupus erythematosus patients without major neuropsychiatric manifestations. Arthritis Res Ther 2022; 24:259. [PMID: 36443835 PMCID: PMC9703716 DOI: 10.1186/s13075-022-02954-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/11/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) has been confirmed to have subtle changes in brain structure before the appearance of obvious neuropsychiatric symptoms. Previous literature mainly focuses on brain structure loss in non-NPSLE; however, the results are heterogeneous, and the impact of structural changes on the topological structure of patients' brain networks remains to be determined. In this study, we combined neuroimaging and network analysis methods to evaluate the changes in cortical thickness and its structural covariance networks (SCNs) in patients with non-NPSLE. METHODS We compare the cortical thickness of non-NPSLE patients (N=108) and healthy controls (HCs, N=88) using both surface-based morphometry (SBM) and regions of interest (ROI) methods, respectively. After that, we analyzed the correlation between the abnormal cortical thickness results found in the ROI method and a series of clinical features. Finally, we constructed the SCNs of two groups using the regional cortical thickness and analyzed the abnormal SCNs of non-NPSLE. RESULTS By SBM method, we found that cortical thickness of 34 clusters in the non-NPSLE group was thinner than that in the HC group. ROI method based on Destrieux atlas showed that cortical thickness of 57 regions in the non-NPSLE group was thinner than that in the HC group and related to the course of disease, autoantibodies, the cumulative amount of immunosuppressive agents, and cognitive psychological scale. In the SCN analysis, the cortical thickness SCNs of the non-NPSLE group did not follow the small-world attribute at a few densities, and the global clustering coefficient appeared to increase. The area under the curve analysis showed that there were significant differences between the two groups in clustering coefficient, degree, betweenness, and local efficiency. There are a total of seven hubs for non-NPSLE, and five hubs in HCs, the two groups do not share a common hub distribution. CONCLUSION Extensive and obvious reduction in cortical thickness and abnormal topological organization of SCNs are observed in non-NPSLE patients. The observed abnormalities may not only be the realization of brain damage caused by the disease, but also the contribution of the compensatory changes within the nervous system.
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Affiliation(s)
- Shu Li
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ru Bai
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruotong Zhao
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
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