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Fu Z, Sui J, Iraji A, Liu J, Calhoun VD. Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population. Mol Psychiatry 2024:10.1038/s41380-024-02683-6. [PMID: 39085394 DOI: 10.1038/s41380-024-02683-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 07/16/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024]
Abstract
Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.
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Affiliation(s)
- Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
- Department of Computer Science, Georgia State University, Atlanta, GA, USA.
| | - Jing Sui
- IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Yan J, Bai H, Sun Y, Sun X, Hu Z, Liu B, He C, Zhang X. Frontoparietal Response to Working Memory Load Mediates the Association between Sleep Duration and Cognitive Function in Children. Brain Sci 2024; 14:706. [PMID: 39061446 PMCID: PMC11274878 DOI: 10.3390/brainsci14070706] [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: 06/14/2024] [Revised: 07/07/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
Lack of sleep has been found to be associated with cognitive impairment in children, yet the neural mechanism underlying this relationship remains poorly understood. To address this issue, this study utilized the data from the Adolescent Brain Cognitive Development (ABCD) study (n = 4930, aged 9-10), involving their sleep assessments, cognitive measures, and functional magnetic resonance imaging (fMRI) during an emotional n-back task. Using partial correlations analysis, we found that the out-of-scanner cognitive performance was positively correlated with sleep duration. Additionally, the activation of regions of interest (ROIs) in frontal and parietal cortices for the 2-back versus 0-back contrast was positively correlated with both sleep duration and cognitive performance. Mediation analysis revealed that this activation significantly mediated the relationship between sleep duration and cognitive function at both individual ROI level and network level. After performing analyses separately for different sexes, it was revealed that the mediation effect of the task-related activation was present in girls (n = 2546). These findings suggest that short sleep duration may lead to deficit in cognitive function of children, particularly in girls, through the modulation of frontoparietal activation during working memory load.
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Affiliation(s)
- Jie Yan
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
| | - Haolei Bai
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
| | - Yuqing Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Xueqi Sun
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
| | - Zhian Hu
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Chao He
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
| | - Xiaolong Zhang
- Department of Physiology, Institute of Brain and Intelligence, Third Military Medical University, Chongqing 400038, China
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Turan O, Garner J, Chang L, Isaiah A. Accuracy of parent-reported sleep duration among adolescents assessed using accelerometry. Pediatr Res 2024:10.1038/s41390-024-03393-z. [PMID: 38961167 DOI: 10.1038/s41390-024-03393-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 05/30/2024] [Accepted: 06/25/2024] [Indexed: 07/05/2024]
Abstract
IMPACT Parent-reported children's sleep duration is a primary outcome measure in population-level studies, and is the primary driver of pharmacotherapy such as melatonin. Accelerometry using the Fitbit suggests that few adolescents sleep for the optimal 9-12 h as recommended by the American Academy of Sleep Medicine, and most parent reports grossly overestimate average nightly sleep duration. Parent reports of adolescent sleep duration are unreliable, and quantitative assessment of children's sleep duration should be considered when a significant step such as pharmacotherapy is undertaken for sleep.
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Affiliation(s)
- Ozerk Turan
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jonathan Garner
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Amal Isaiah
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Maryland School of Medicine, Baltimore, MD, USA.
- Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA.
- Institute for Health Computing, University of Maryland, Bethesda, USA.
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Yu M, Jiang Y, Gong X, Gao X. Relationship Between Sleep Duration and Cognitive Function in Older Adults: Analysis of NHANES and UK Biobank GWAS Data. Biol Res Nurs 2024; 26:399-409. [PMID: 38302190 DOI: 10.1177/10998004241230325] [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] [Indexed: 02/03/2024]
Abstract
OBJECTIVES To explore the relationship between sleep duration and cognitive functions in older adults using NHANES, a national US population study dataset, and to explore the causal association with Mendelian randomization (MR) using the UK Biobank. METHODS First, an observational study was conducted with the NHANES database with participants ≥60 years. Sleep duration was measured with accelerometers for 7 consecutive days. Participants were divided into habitual short sleep (<7 h) and long sleep (>9 h) groups. Cognitive functions were measured with the CERAD Word Learning sub-set, Animal Fluency, and Digit Symbol Substitution test (DSST). Multivariate regression models were used to explore relationships between sleep duration and cognitive functions. Second, bidirectional MR was conducted with data for self-reported sleep duration, which came from a genome-wide association study (GWAS) comprising 446,118 adults from the UK Biobank, and general cognitive performance, which was obtained from a recent GWAS study (N = 257,841). Inverse-variance weighted (IVW) was used as the primary estimation of the outcome. RESULTS In the observational study, 2687 participants were included. Sleep duration was associated with cognitive functions in a non-linear way. Habitual long sleep (>9°h) was associated with lower scores on DSST (OR = 0.01, p = .003) in the fully-adjusted model. The association between habitual short sleep and cognitive functions was insignificant. For the MR, genetically predicted lower general cognitive performance was causally associated with a higher prevalence of habitual short sleep (OR = 0.97, p = 5.1 × 10-7) and long sleep (OR = 0.97, p = 8.87 × 10-16). DISCUSSION Short and long sleep duration might be both causally associated with worse outcomes of cognitive functions in older adults, highlighting the importance of maintaining sleep health.
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Affiliation(s)
- Min Yu
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, China
- Center for Oral Therapy of Sleep Apnea, Peking University Hospital of Stomatology, Beijing, China
- National Center for Stomatology, Beijing, China
| | - Yang Jiang
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, China
- Center for Oral Therapy of Sleep Apnea, Peking University Hospital of Stomatology, Beijing, China
- National Center for Stomatology, Beijing, China
| | - Xu Gong
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, China
- Center for Oral Therapy of Sleep Apnea, Peking University Hospital of Stomatology, Beijing, China
- National Center for Stomatology, Beijing, China
| | - Xuemei Gao
- Department of Orthodontics, Peking University School and Hospital of Stomatology, Beijing, China
- Center for Oral Therapy of Sleep Apnea, Peking University Hospital of Stomatology, Beijing, China
- National Center for Stomatology, Beijing, China
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Wang Q, Liu T, Zhou Y. Association between sleep problems and impulsivity mediated through regional homogeneity abnormalities in male methamphetamine abstainers. Brain Imaging Behav 2024:10.1007/s11682-024-00900-y. [PMID: 38914808 DOI: 10.1007/s11682-024-00900-y] [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: 05/24/2024] [Indexed: 06/26/2024]
Abstract
Sleep problems and impulsivity frequently occur in methamphetamine (MA) abstainers and are linked to aberrant brain function. However, the interplay between these factors remains poorly understood. This study aimed to investigate the relationship between sleep, impulsivity, and regional homogeneity (ReHo) through mediation analysis in MA abstainers. 46 MA abstainers and 44 healthy controls were included. Impulsivity and sleep problems were evaluated using the Barratt Impulsivity Scale and the Pittsburgh Sleep Quality Scale, respectively. ReHo, indicative of local brain spontaneous neural activity, was assessed using resting-state functional magnetic resonance imaging. Results unveiled correlations between different dimensions of impulsivity and ReHo values in specific brain regions. Motor impulsivity correlated with ReHo values in the left postcentral gyrus and left precentral gyrus, while non-planning impulsivity was only associated with ReHo values in the left precentral gyrus. Additionally, the need for sleep medications correlated with ReHo values in the left precentral gyrus and bilateral postcentral gyrus. Also, the need for sleep medications was positively correlated with cognitive impulsivity and motor impulsivity. Mediation analysis indicated that reduced ReHo values in the left precentral gyrus mediated the association between impulsivity and the need for sleep medications. These findings imply that addressing sleep problems, especially the need for sleep medications, might augment spontaneous neural activity in specific brain regions linked to impulsivity among MA abstainers. This underscores the importance of integrating sleep interventions into comprehensive treatment strategies for MA abstainers.
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Affiliation(s)
- Qianjin Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
- Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China.
| | - Tieqiao Liu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Yanan Zhou
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
- Department of Psychiatry, Hunan Brain Hospital (Hunan Second People's Hospital), Changsha, China.
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Huang CH, Wong LC, Chu YJ, Hsu CJ, Wang HP, Tsai WC, Lee WT. The sleep problems in individuals with Rett syndrome and their caregivers. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2024:13623613241254620. [PMID: 38853381 DOI: 10.1177/13623613241254620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
LAY ABSTRACT Sleep problems are common and impactful among individuals with Rett syndrome (RTT) and their caregivers. We examined the sleep patterns of 29 RTT patients and their primary caregivers using various assessment tools. The study found that a majority of the patients experienced sleep disturbances, with younger patients showing more sleep difficulties. Caregivers also reported poor sleep quality. The findings emphasize the need to address sleep problems in RTT management, as improving sleep quality can positively impact the well-being of individuals with RTT and their caregivers.
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Affiliation(s)
- Cheng-Hsien Huang
- Department of Pediatrics, Sleep Center, Yang-Ming Branch, Taipei City Hospital, Taipei, Taiwan
- University of Taipei, Taiwan
| | - Lee-Chin Wong
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Yen-Ju Chu
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
| | - Chia-Jui Hsu
- Department of Pediatrics, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
| | - Hsin-Pei Wang
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Pediatrics, National Taiwan University Hospital YunLin Branch, Yun-Lin, Taiwan
| | - Wen-Che Tsai
- Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan
| | - Wang-Tso Lee
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
- Department of Pediatrics, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Brain and Mind Sciences, National Taiwan University Children's Hospital, Taipei, Taiwan
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Monti MM. The subcortical basis of subjective sleep quality. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.29.596530. [PMID: 38854024 PMCID: PMC11160773 DOI: 10.1101/2024.05.29.596530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Study objectives To assess the association between self-reported sleep quality and cortical and subcortical local morphometry. Methods Sleep and neuroanatomical data from the full release of the young adult Human Connectome Project dataset were analyzed. Sleep quality was operationalized with the Pittsburgh Sleep Quality Index (PSQI). Local cortical and subcortical morphometry was measured with subject-specific segmentations resulting in voxelwise thickness measurements for cortex and relative (i.e., cross-sectional) local atrophy measurements for subcortical regions. Results Relative atrophy across several subcortical regions, including bilateral pallidum, striatum, and thalamus, was negatively associated with both global PSQI score and sub-components of the index related to sleep duration, efficiency, and quality. Conversely, we found no association between cortical morphometric measurements and self-reported sleep quality. Conclusions This work shows that subcortical regions such as the bilateral pallidum, thalamus, and striatum, might be interventional targets to ameliorate self-reported sleep quality.
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Affiliation(s)
- Martin M. Monti
- Department of Psychology, University of California Los Angeles, 502 Portola Plaza, Los Angeles, 90095, CA, USA
- Brain Injury Research Center (BIRC), Department of Neurosurgery, University of California Los Angeles, 300 Stein Plaza Driveway, Los Angeles, 90095, CA, USA
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Zhi D, Jiang R, Pearlson G, Fu Z, Qi S, Yan W, Feng A, Xu M, Calhoun V, Sui J. Triple Interactions Between the Environment, Brain, and Behavior in Children: An ABCD Study. Biol Psychiatry 2024; 95:828-838. [PMID: 38151182 PMCID: PMC11006588 DOI: 10.1016/j.biopsych.2023.12.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Environmental exposures play a crucial role in shaping children's behavioral development. However, the mechanisms by which these exposures interact with brain functional connectivity and influence behavior remain unexplored. METHODS We investigated the comprehensive environment-brain-behavior triple interactions through rigorous association, prediction, and mediation analyses, while adjusting for multiple confounders. Particularly, we examined the predictive power of brain functional network connectivity (FNC) and 41 environmental exposures for 23 behaviors related to cognitive ability and mental health in 7655 children selected from the Adolescent Brain Cognitive Development (ABCD) Study at both baseline and follow-up. RESULTS FNC demonstrated more predictability for cognitive abilities than for mental health, with cross-validation from the UK Biobank study (N = 20,852), highlighting the importance of thalamus and hippocampus in longitudinal prediction, while FNC+environment demonstrated more predictive power than FNC in both cross-sectional and longitudinal prediction of all behaviors, especially for mental health (r = 0.32-0.63). We found that family and neighborhood exposures were common critical environmental influencers on cognitive ability and mental health, which can be mediated by FNC significantly. Healthy perinatal development was a unique protective factor for higher cognitive ability, whereas sleep problems, family conflicts, and adverse school environments specifically increased risk of poor mental health. CONCLUSIONS This work revealed comprehensive environment-brain-behavior triple interactions based on the ABCD Study, identified cognitive control and default mode networks as the most predictive functional networks for a wide repertoire of behaviors, and underscored the long-lasting impact of critical environmental exposures on childhood development, in which sleep problems were the most prominent factors affecting mental health.
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Affiliation(s)
- Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Godfrey Pearlson
- Department of Psychiatry and Neurobiology, Yale School of Medicine, New Haven, Connecticut
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Emory University, and Georgia State University, Atlanta, Georgia
| | - Shile Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Weizheng Yan
- National Institute on Alcohol Abuse and Alcoholism, Lab of Neuroimaging, National Institutes of Health, Bethesda, Maryland
| | - Aichen Feng
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Ming Xu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Emory University, and Georgia State University, Atlanta, Georgia.
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia Institute of Technology, Emory University, and Georgia State University, Atlanta, Georgia.
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Li L, Zhang Y, Fan M, Cao B. Sleep and mental health among Chinese adolescents: the chain-mediating role of physical health perception and school adjustment. BMC Psychol 2024; 12:228. [PMID: 38659039 PMCID: PMC11044529 DOI: 10.1186/s40359-024-01719-4] [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: 06/13/2023] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
OBJECTIVE Sleep problems and their detrimental effects on adolescents' physical and mental health have received substantial attention. Prior studies have focused mainly on the direct association between sleep and mental health; however, little is known about the underlying mediating mechanism. To address this gap, the present study constructed a chain mediation model to examine the association between sleep deficiency and mental health status in adolescents, by introducing two mediating variables-physical health perception and school adjustment. METHODS A sample of 7530 senior high school students completed a battery of self-report questionnaires measuring their sleep duration, mental health status, physical health perception, and school adjustment. Data were collected from the Database of Youth Health at Shandong University. All the measures showed good reliability and validity in the present study. Data were analyzed using SPSS 25.0 and the SPSS PROCESS. RESULTS The results were as follows: (1) Sleep duration was significantly associated with physical health perception and mental health. (2) Physical health perception partially mediated the association between sleep and mental health. (3) Physical health perception and school adjustment played a chain mediating role between sleep and mental health. In conclusion, sleep not only directly associated with mental health among adolescents, but also influences mental health by the chain mediating effect of perception of physical health and school adjustment. CONCLUSION These findings in the present study contribute to understanding the mechanisms underlying the association between sleep and mental health and have important implications for interventions aimed at improving mental health status among adolescents in China. Our results indicated that promoting adequate sleep duration and improving sleep quality are possible key mental health promotion strategies for adolescents.
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Affiliation(s)
- Liangliang Li
- Chongqing Three Gorges Medical College, 366 Tianxing Road, 404120, Wanzhou, Chongqing, P. R. China
| | - Yueying Zhang
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Ministry of Education, Southwest University, 400715, Chongqing, P. R. China
| | - Mingyue Fan
- Chongqing Three Gorges Medical College, 366 Tianxing Road, 404120, Wanzhou, Chongqing, P. R. China.
| | - Bing Cao
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Ministry of Education, Southwest University, 400715, Chongqing, P. R. China.
- National Demonstration Center for Experimental Psychology Education, Southwest University, 400715, Chongqing, P. R. China.
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Tian Y, Wang YL. Resilience provides mediating effect of resilience between fear of progression and sleep quality in patients with hematological malignancies. World J Psychiatry 2024; 14:541-552. [PMID: 38659599 PMCID: PMC11036458 DOI: 10.5498/wjp.v14.i4.541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 02/19/2024] [Accepted: 03/28/2024] [Indexed: 04/17/2024] Open
Abstract
BACKGROUND Hematological tumors are common malignant tumors, with high morbidity and mortality rates. Most patients with hematological malignancies develop sleep disorders that seriously affect their life and health because of acute onset of disease, rapid progression, high recurrence rates, complex treatment methods, and treatment costs. AIM To explore the mediating effect of resilience on fear of disease progression and sleep quality in patients with hematological malignancies. METHODS A cross-sectional analysis of 100 patients with hematological malignancies, treated in the First Affiliated Hospital of Jinzhou Medical University between August 2022 and August 2023, was conducted. Patients were assessed using a general data survey, a simplified scale for the fear of progression (FoP) of disease, a resilience scale, and the Pittsburgh Sleep Quality Index. Statistical analysis was conducted to determine the relationship between various patient characteristics and FoP, resilience, and sleep quality. Spearman's correlation analysis was used to examine the correlations between mental resilience, FoP, and sleep quality. RESULTS The total FoP score mean value in patients with hematological malignancies was 38.09 ± 5.16; the total resilience score mean value was 40.73 ± 7.04; and the Pittsburgh Sleep Quality Index score mean value was 10.72 ± 1.90. FoP, resilience, and sleep quality of the patients were associated with family per capita monthly income and patient education level (P < 0.05). Spearman correlation analysis revealed that FoP was negatively correlated with resilience and sleep quality scores (r = -0.560, -0.537, P < 0.01), respectively, and resilience was significantly associated with sleep quality scores (r = 0.688, P < 0.01). Mediation analysis showed that the mediating effect of resilience between FoP and sleep quality in patients with hematological malignancies was -0.100 and accounted for 50.51% of the total effect. This indicated that FoP directly and indirectly affected sleep quality through the mesomeric effect of resilience. CONCLUSION Resilience is an intermediary variable between FoP and sleep quality in patients with hematological malignancies. Medical staff should evaluate and follow-up FoP and resilience to implement measures to improve sleep quality.
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Affiliation(s)
- Yuan Tian
- Department of Hematology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121000, Liaoning Province, China
| | - Ying-Li Wang
- Department of Cardiology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou 121000, Liaoning Province, China
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Chandler-Mather N, Crichton A, Shelton D, Harris K, Donovan C, Dawe S. Carer-reported sleep disturbance and carer- and teacher-rated executive functioning in children with prenatal alcohol exposure and Fetal Alcohol Spectrum Disorder. Child Neuropsychol 2024:1-22. [PMID: 38607688 DOI: 10.1080/09297049.2024.2337715] [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: 10/06/2023] [Accepted: 03/24/2024] [Indexed: 04/14/2024]
Abstract
Children with prenatal alcohol exposure (PAE) and Fetal Alcohol Spectrum Disorder (FASD) have high rates of sleep disturbance and marked difficulties with executive functioning (EF). Sleep disturbance has been associated with poorer EF across development in typically developing children. The contribution of insomnia symptoms and nightmares to EF difficulties in children with PAE and FASD is unclear. The current study examined whether caregiver-reported insomnia symptoms and nightmares predicted difficulties with EF in children with PAE who were assessed at FASD diagnostic clinics. Archival data on 116 children with PAE assessed at FASD diagnostic clinics were extracted from databases. Children were assigned to a preschool-age group (3.1 to 5.9 years, n = 40) and a school-age group (5.9 to 10.9 years, n = 76). Insomnia symptoms and nightmares were measured using items extracted from the Child Behavior Checklist (CBCL) while EF was measured using the caregiver and teacher Behavior Rating Inventory of Executive Function (BRIEF) rating forms. Bootstrapped regression models were used examine the effects of insomnia symptoms and nightmares on domains of EF in each group while adjusting for potential confounds. For preschool children, insomnia symptoms were associated with greater daytime tiredness while nightmares were associated with greater difficulties with Emergent Metacognition according to their teachers. For school-age children, insomnia symptoms predicted greater EF difficulties across most domains according to their caregivers but not teachers. Sleep disturbance may compound EF impairments in children with PAE and should be screened for as part of FASD diagnostic assessment.
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Affiliation(s)
| | - Ali Crichton
- Victorian Fetal Alcohol Service, Monash Children's Hospital, Clayton, Australia
- Department of Paediatrics, Monash University, Melbourne, Australia
| | - Doug Shelton
- Gold Coast University Hospital, Southport, Australia
| | - Katrina Harris
- Victorian Fetal Alcohol Service, Monash Children's Hospital, Clayton, Australia
| | - Caroline Donovan
- School of Applied Psychology, Griffith University, Brisbane, Australia
| | - Sharon Dawe
- School of Applied Psychology, Griffith University, Brisbane, Australia
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Zhang B, Rolls ET, Wang X, Xie C, Cheng W, Feng J. Roles of the medial and lateral orbitofrontal cortex in major depression and its treatment. Mol Psychiatry 2024; 29:914-928. [PMID: 38212376 DOI: 10.1038/s41380-023-02380-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 01/13/2024]
Abstract
We describe evidence for dissociable roles of the medial and lateral orbitofrontal cortex (OFC) in major depressive disorder (MDD) from structure, functional activation, functional connectivity, metabolism, and neurochemical systems. The reward-related medial orbitofrontal cortex has lower connectivity and less reward sensitivity in MDD associated with anhedonia symptoms; and the non-reward related lateral OFC has higher functional connectivity and more sensitivity to non-reward/aversive stimuli in MDD associated with negative bias symptoms. Importantly, we propose that conventional antidepressants act to normalize the hyperactive lateral (but not medial) OFC to reduce negative bias in MDD; while other treatments are needed to operate on the medial OFC to reduce anhedonia, with emerging evidence suggesting that ketamine may act in this way. The orbitofrontal cortex is the key cortical region in emotion and reward, and the current review presents much new evidence about the different ways that the medial and lateral OFC are involved in MDD.
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Affiliation(s)
- Bei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
| | - Edmund T Rolls
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
- Oxford Centre for Computational Neuroscience, Oxford, UK.
- Department of Computer Science, University of Warwick, Coventry, UK.
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, PR China
- Medical Psychological Institute, Central South University, Changsha, PR China
- China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, PR China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, PR China.
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, PR China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, PR China.
- Department of Computer Science, University of Warwick, Coventry, UK.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, PR China.
- Zhangjiang Fudan International Innovation Center, Shanghai, PR China.
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13
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Ji W, Li G, Hu Y, Zhang W, Wang J, Jiang F, Zhang Y, Wu F, Wei X, Li Y, Gao X, Manza P, Volkow ND, Wang GJ, Zhang Y. Associations among birthweight, adrenarche, brain morphometry and cognitive function in preterm children aged 9-11 years. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00063-6. [PMID: 38417787 DOI: 10.1016/j.bpsc.2024.02.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/26/2024] [Accepted: 02/20/2024] [Indexed: 03/01/2024]
Abstract
BACKGROUND Preterm infants with low birthweight are at heightened risk of developmental sequelae, including neurological and cognitive dysfunction that can persist into adolescence or adulthood. In addition, preterm birth and low birthweight can provoke changes in endocrine and metabolic processes that likely impact brain health throughout development. However, few studies have examined associations among birthweight, pubertal endocrine process, long-term neurological and cognitive development. METHODS We investigated the associations between birthweight and brain morphometry, cognitive function, and onset of adrenarche assessed 9 to 11 years later in 3571 preterm and full-term children using the Adolescent Brain Cognitive Development dataset. RESULTS The preterm children showed lower birthweight and early adrenarche, as expected. Birthweight was positively associated with cognitive function (all︱Cohen's d︱> 0.154, P < 0.005), global brain volumes (all︱Cohen's d︱> 0.170, P < 0.008) and regional volumes in frontal, temporal, and parietal cortices in preterm and full-term children (all︱Cohen's d︱> 0.170, P < 0.0007); and cortical volume in the lateral orbitofrontal cortex (lOFC) partially mediated the effect of low birthweight on cognitive function in preterm children. In addition, adrenal score and cortical volume in the lOFC mediated the associations between birthweight and cognitive function only in preterm children. CONCLUSIONS These findings highlight the impact of low birthweight on long-term brain structural and cognitive function development, and showed important associations with early onset of adrenarche during the puberty. This understanding may help with prevention and treatment.
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Affiliation(s)
- Weibin Ji
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Guanya Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yang Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Wenchao Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Jia Wang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Fukun Jiang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yaqi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Feifei Wu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Xiaorong Wei
- Kindergarten affiliated to Air Force Medical University, Xi'an, Shaanxi, 710032, China
| | - Yuefeng Li
- Department of Neonatology, Shenzhen Luohu Maternity and Child Health Hospital, Shenzhen 518103, China
| | - Xinbo Gao
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute for Brain: a journal of neurology and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA.
| | - Yi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China; International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China.
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14
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Newson JJ, Bala J, Giedd JN, Maxwell B, Thiagarajan TC. Leveraging big data for causal understanding in mental health: a research framework. Front Psychiatry 2024; 15:1337740. [PMID: 38439791 PMCID: PMC10910083 DOI: 10.3389/fpsyt.2024.1337740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 02/01/2024] [Indexed: 03/06/2024] Open
Abstract
Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause.
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Affiliation(s)
| | - Jerzy Bala
- Sapien Labs, Arlington, VA, United States
| | - Jay N. Giedd
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Benjamin Maxwell
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
- Rady Children’s Hospital – San Diego, San Diego, CA, United States
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15
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Thieux M, Zhang M, Guignard‐Perret A, Mazza S, Plancoulaine S, Guyon A, Franco P. Does the brain sleep differently depending on intellectual abilities? CNS Neurosci Ther 2024; 30:e14378. [PMID: 37485816 PMCID: PMC10848103 DOI: 10.1111/cns.14378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 06/05/2023] [Accepted: 07/12/2023] [Indexed: 07/25/2023] Open
Abstract
AIMS To compare the children's sleep electroencephalogram according to their intellectual profile. METHODS Children were grouped according to their Wechsler Intelligence Scale for Children (WISC) scores (17 with normal intelligence quotient [IQ, NIQ] and 24 with high IQ [HIQ]). Comparisons of spectral power between groups and its relationship with WISC scores were assessed using analyses of variance and linear regression models, adjusted for age and sex. RESULTS Children with HIQ had more rapid eye movement (REM) sleep, especially late at night, and more power in slow-frequency bands during REM sleep than those with NIQ. There were also positive associations between the processing speed index and the spectral power in β bands in NREM sleep, and with the spectral power in α, σ, β, and γ bands in REM sleep, with different associations between groups. CONCLUSION The enhanced power in slow bands during REM sleep in children with HIQ overlaps with that of typical REM sleep oscillations thought to be involved in emotional memory consolidation. The dissimilar relationships between spectral power and WISC scores in NIQ and HIQ groups may underlie functional differences in brain activity related to cognitive efficiency, questioning the direction of the relationship between sleep and cognitive functioning.
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Affiliation(s)
- Marine Thieux
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
| | - Min Zhang
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
| | - Anne Guignard‐Perret
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
| | - Stéphanie Mazza
- Research on Healthcare Performance RESHAPE, INSERM U1290Université Claude Bernard Lyon 1LyonFrance
| | - Sabine Plancoulaine
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
- Inserm, INRAE, Center for Research in Epidemiology and Statistics (CRESS)Université Paris Cité and Université Sorbonne Paris NordParisFrance
| | - Aurore Guyon
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
| | - Patricia Franco
- INSERM U1028, CNRS UMR5292Lyon Neuroscience Research CenterLyonFrance
- Pediatric Sleep Unit, Department of Pediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, Hôpital Femme Mère EnfantHospices Civils de LyonLyonFrance
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16
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Fu Z, Sui J, Iraji A, Liu J, Calhoun V. Cognitive and Psychiatric Relevance of Dynamic Functional Connectivity States in a Large (N>10,000) Children Population. RESEARCH SQUARE 2024:rs.3.rs-3586731. [PMID: 38260417 PMCID: PMC10802706 DOI: 10.21203/rs.3.rs-3586731/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9 ~ 11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a sparsely connected state. The composite cognitive score and the ADHD score were the most significantly correlated with the DFC states. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.
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Affiliation(s)
- Zening Fu
- Georgia Institute of Technology, Emory University and Georgia State University
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17
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Liu Z, Wei Y, Yang Y, Kong L. Unveiling a novel clinical risk assessment model for identifying non-suicidal self-injury risks in depressed Chinese adolescents amidst the COVID-19 pandemic: insights from low self-esteem, internet use, and sleep disturbance. Front Psychiatry 2024; 14:1259909. [PMID: 38250260 PMCID: PMC10797052 DOI: 10.3389/fpsyt.2023.1259909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024] Open
Abstract
Background Non-suicidal self-injury (NSSI) is a highly prevalent behavioral problem among depression adolescent patients that can result in numerous adverse outcomes. This study endeavors to bridge this knowledge gap by creating a comprehensive model that incorporates multiple aspects of NSSI to accurately evaluate its risk in adolescents with depression, thereby enhancing our ability to prevent and address this challenging issue. Method Using a cross-sectional design, we recruited 302 adolescents with depressive disorders who visited or were hospitalized at Shandong Mental Health Center from December 2021 to June 2022. The participants completed several self-report questionnaires, including the Chinese version of the Internet Addiction Test, the Pittsburgh Sleep Quality Index questionnaire, the Defeat Scale, the Social Avoidance and Distress Scale and the Children's Depression Inventory. Logistic regression analysis was performed to identify the diagnostic factors, which were further used to establish clinical risk assessment models. A receiver operating characteristic curve (ROC) to identify the best model. An external validating team was introduced to verify the assessing efficiency. Results Based on a logistic regression analysis, three variables have been identified as significant risk factors. Specifically, adolescents with depression who experience low self-esteem, internet use, or suffer from sleep disturbance face an increased risk of NSSI. An integrated risk index for NSSI exhibits excellent accuracy in identifying depressed adolescents at risk of NSSI (area under the curve = 0.86, sensitivity = 0.88, specificity = 0.69). In the validation cohort, the identification performance remains strong (area under the curve = 0.84, sensitivity = 0.72, specificity = 0.81). Conclusion This study highlighted the role of self-esteem, internet use and sleep disturbance in the development of NSSI. The risk index diagnosing NSSI onset may help to guide the design and application of novel interventions to minimize this risky behavior in future depressed adolescents.
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Affiliation(s)
- Zhongyi Liu
- Department of Psychiatry, School of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, China
- Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, China
| | - Yuhuan Wei
- Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, China
- School of Mental Health, Jining Medical University, Jining, China
| | - Ying Yang
- Department of Psychiatry, School of Clinical Medicine, Cheeloo College of Medicine, Shandong University, Jinan, China
- Childhood Psychiatry Unit, Shandong Mental Health Center, Jinan, China
- School of Mental Health, Jining Medical University, Jining, China
| | - Linghua Kong
- School of Nursing and Rehabilitation, Cheeloo College of Medicine, Shandong University, Jinan, China
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18
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Ji W, Li G, Jiang F, Zhang Y, Wu F, Zhang W, Hu Y, Wang J, Wei X, Li Y, Manza P, Tomasi D, Gao X, Wang GJ, Zhang Y, Volkow ND. Preterm birth associated alterations in brain structure, cognitive functioning and behavior in children from the ABCD dataset. Psychol Med 2024; 54:409-418. [PMID: 37365781 DOI: 10.1017/s0033291723001757] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/28/2023]
Abstract
BACKGROUND Preterm birth is a global health problem and associated with increased risk of long-term developmental impairments, but findings on the adverse outcomes of prematurity have been inconsistent. METHODS Data were obtained from the baseline session of the ongoing longitudinal Adolescent Brain and Cognitive Development (ABCD) Study. We identified 1706 preterm children and 1865 matched individuals as Control group and compared brain structure (MRI data), cognitive function and mental health symptoms. RESULTS Results showed that preterm children had higher psychopathological risk and lower cognitive function scores compared to controls. Structural MRI analysis indicated that preterm children had higher cortical thickness in the medial orbitofrontal cortex, parahippocampal gyrus, temporal and occipital gyrus; smaller volumes in the temporal and parietal gyrus, cerebellum, insula and thalamus; and smaller fiber tract volumes in the fornix and parahippocampal-cingulum bundle. Partial correlation analyses showed that gestational age and birth weight were associated with ADHD symptoms, picvocab, flanker, reading, fluid cognition composite, crystallized cognition composite and total cognition composite scores, and measures of brain structure in regions involved with emotional regulation, attention and cognition. CONCLUSIONS These findings suggest a complex interplay between psychopathological risk and cognitive deficits in preterm children that is associated with changes in regional brain volumes, cortical thickness, and structural connectivity among cortical and limbic brain regions critical for cognition and emotional well-being.
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Affiliation(s)
- Weibin Ji
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Guanya Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Fukun Jiang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yaqi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Feifei Wu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Wenchao Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yang Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Jia Wang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Xiaorong Wei
- Kindergarten affiliated to Air Force Medical University, Xi'an, Shaanxi 710032, China
| | - Yuefeng Li
- Department of Neonatology, Shenzhen Luohu Maternity and Child Health Hospital, Shenzhen 518103, China
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Dardo Tomasi
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Xinbo Gao
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
- Chongqing Institute for Brain: a journal of neurology and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Yi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
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19
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Cameron S, Donnelly A, Broderick C, Arichi T, Bartsch U, Dazzan P, Elberling J, Godfrey E, Gringras P, Heathcote LC, Joseph D, Wood TC, Pariante C, Rubia K, Flohr C. Mind and skin: Exploring the links between inflammation, sleep disturbance and neurocognitive function in patients with atopic dermatitis. Allergy 2024; 79:26-36. [PMID: 37469218 DOI: 10.1111/all.15818] [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: 03/03/2023] [Revised: 06/06/2023] [Accepted: 07/02/2023] [Indexed: 07/21/2023]
Abstract
Atopic dermatitis (AD) is a chronic, pruritic and inflammatory, dry skin condition with many known comorbidities. These include airway disease, food allergies, atopic eye disease and autoimmune conditions. Furthermore, there is often significant sleep disturbance as well as increased psychological distress and mental health problems. Severe AD therefore often has a significant impact on the quality of life of both patients and their families. In this review we discuss recent findings on the putative links between AD, its association with itch, sleep disturbance and neuropsychiatric morbidity, including the role of inflammation in these conditions. Itch was thought to predominantly drive sleep disruption in AD. We now understand changes in sleep influence immune cell distribution and the associated inflammatory cytokines, which suggests a bidirectional relationship between AD and sleep. We also increasingly recognize inflammation as a key driver in psychological symptoms and disorders. The link between cutaneous, systemic and possible brain inflammation could at least in part be driven by the sleep deprivation and itch-driven neuronal proliferation seen in AD.
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Affiliation(s)
- Shona Cameron
- St John's Institute of Dermatology, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Ali Donnelly
- St John's Institute of Dermatology, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Conor Broderick
- St John's Institute of Dermatology, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Ullrich Bartsch
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
- UK Dementia Research Institute, Care Research & Technology Centre, Imperial College London and University of Surrey, Guildford, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Jesper Elberling
- Depart of Dermatology and Allergy, Herlev and Gentofte Hospital, Copenhagen, Denmark
| | - Emma Godfrey
- Health Psychology Section, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paul Gringras
- Paediatric Sleep Department, Evelina Children's Hospital, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Lauren C Heathcote
- Health Psychology Section, Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Desaline Joseph
- Paediatric Sleep Department, Evelina Children's Hospital, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Tobias C Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Carmine Pariante
- UK Dementia Research Institute, Care Research & Technology Centre, Imperial College London and University of Surrey, Guildford, UK
| | - Katya Rubia
- UK Dementia Research Institute, Care Research & Technology Centre, Imperial College London and University of Surrey, Guildford, UK
| | - Carsten Flohr
- St John's Institute of Dermatology, King's College London and Guy's and St Thomas' NHS Foundation Trust, London, UK
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20
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Keenan L, Bramham J, Downes M. Parent-Report Sleep Disturbances and Everyday Executive Functioning Difficulties in Children with Tourette Syndrome. Dev Neuropsychol 2024; 49:39-60. [PMID: 38224316 DOI: 10.1080/87565641.2023.2300428] [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: 07/25/2023] [Accepted: 12/22/2023] [Indexed: 01/16/2024]
Abstract
There is an increasing need to identify and treat sleep disturbances in Tourette syndrome (TS), a neurodevelopmental condition characterized by tics. This study explored sleep, tics, and executive functioning in children with TS (n=136) and neurotypical controls (n=101) through parent-report scales and open-ended questions. 85% of children with TS scored in the clinical range for a sleep disorder. Higher tic severity predicted increased sleep disturbances and executive difficulties. Qualitative insights indicated a bidirectional link between sleep and tics, which warrants consideration in clinical settings. Further research is needed to explore causal links.
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Affiliation(s)
- Lisa Keenan
- School of Psychology, University College Dublin, Dublin, Ireland
| | - Jessica Bramham
- School of Psychology, University College Dublin, Dublin, Ireland
| | - Michelle Downes
- School of Psychology, University College Dublin, Dublin, Ireland
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21
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Zhang L, Sasser J, Doane LD, Peltz J, Oshri A. Latent Profiles of Sleep Patterns in Early Adolescence: Associations With Behavioral Health Risk. J Adolesc Health 2024; 74:177-185. [PMID: 37815759 PMCID: PMC10841331 DOI: 10.1016/j.jadohealth.2023.08.021] [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: 02/10/2023] [Revised: 08/10/2023] [Accepted: 08/10/2023] [Indexed: 10/11/2023]
Abstract
PURPOSE The present study characterized sleep profiles in a national longitudinal sample of early adolescents and examined whether profiles predicted later behavioral problems. METHODS Three waves of data (2016-2021) were obtained from the Adolescent Behavior and Cognitive Development study, including 3,326 participants with both weekday and weekend sleep data measured by Fitbit wearables (age range 10.58-13.67 years; 49.3% female). Latent profile analysis was utilized to identify sleep profiles using multiple sleep indicators (duration, latency, efficiency, wake minutes, wake counts, and midpoint). We then explored whether demographic predictors predicted profile membership and tested the latent sleep profiles' predictive utility of internalizing and externalizing symptoms. RESULTS Four profiles were identified: average sleep (40.39%), high duration & high wakefulness (28.58%), high efficiency, low duration &low wakefulness (16.86%), and low duration & low efficiency (14.17%). Participants with older age, males, higher body mass index, and advanced pubertal status were more likely to be classified in the low duration & low efficiency profile than the average group. Participants with lower income, minority identification, older age, and higher body mass index were more likely to be classified in the high efficiency, low duration &low wakefulness than the average group. Participants with lower parental education and males were more likely to be in the high sleep duration & high wakefulness than the average group. The low duration & low efficiency group had the highest attention problems, social problems, and rule-breaking behaviors. DISCUSSION Our findings highlight unique sleep patterns in early adolescence and their prospective links with internalizing and externalizing problems.
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Affiliation(s)
- Linhao Zhang
- Department of Human Development and Family Science, University of Georgia, Athens, Georgia.
| | - Jeri Sasser
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Leah D Doane
- Department of Psychology, Arizona State University, Tempe, Arizona
| | - Jack Peltz
- Department of Psychology, SUNY Brockport, Brockport, New York
| | - Assaf Oshri
- Department of Human Development and Family Science, University of Georgia, Athens, Georgia
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22
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Li W, Sun L, Yue L, Xiao S. Associations between afternoon napping, left amygdala volume and cognitive performance in elderly with normal cognitive function. Sleep Med 2024; 113:232-237. [PMID: 38064794 DOI: 10.1016/j.sleep.2023.11.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 11/19/2023] [Accepted: 11/21/2023] [Indexed: 01/07/2024]
Abstract
BACKGROUND The relationship between afternoon napping and cognitive function in the elderly is very complex and the mechanism is unknown. METHODS In the current study, 194 community elders with normal cognitive functions were included. All subjects completed baseline clinical assessment, baseline neuropsychological test as well as baseline structural MRI. Based on their napping status, these 194 participants were divided into the napping group (n = 88) and the non-napping group (n = 106). We then compared the differences in cognitive performance and structural magnetic resonance between the two groups. RESULTS In the intergroup analysis, we found that the nappers showed poorer cognitive performance on both overall cognitive function and domain specific cognitive function; while on the whole sample, we found a significant negative association (F = 20.27, p<0.001) between afternoon napping and left amygdala volume. However, we did not find any effect of night sleep length or napping frequency on cognitive performance or left amygdala volume. CONCLUSIONS In community elders with normal cognitive functions, afternoon napping is associated with cognitive performance, and left amygdala may play an important role in this process.
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Affiliation(s)
- Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Lin Sun
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
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23
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Mewton L, Davies S, Sunderland M, Champion K, Hoy N, Newton N, Teesson M, Squeglia LM. Longitudinal relationships between lifestyle risk factors and neurodevelopment in early adolescence. Health Psychol 2023; 42:904-912. [PMID: 37616102 PMCID: PMC10840638 DOI: 10.1037/hea0001248] [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] [Indexed: 08/25/2023]
Abstract
OBJECTIVE The goal of this study is to investigate the cross-sectional and longitudinal relationships between clustered lifestyle risk factors (sleep, physical activity, body mass index [BMI], and screen time) and neurodevelopment over the early adolescent period. METHOD Data from the ABCD Study Data Release 3.0 consisted of 11,878 participants (aged 9-10 years) at baseline and 6,571 participants (aged 11-12 years) at 2-year follow-up. The interrelationships between lifestyle risk factors and brain structure were analyzed using bivariate multiple indicator latent change score models. Using confirmatory factor analysis, a single lifestyle risk factor domain (measured by sleep, physical activity, BMI, and screen time) was shown to fit the data well. Using exploratory and confirmatory factor analysis, seven brain structure domains were extracted and labeled as temporal-parietal, frontotemporal, occipital, orbitofrontal, temporal, cingulate, parietal, and cuneus domains. All bivariate latent change score models accounted for age, sex at birth, race/ethnicity, parental education, and marital status. RESULTS Higher lifestyle risk was associated with smaller brain volume at baseline. Higher baseline lifestyle risk was also associated with a greater rate of change (i.e., greater decreases) in brain volume for the temporal-parietal, frontotemporal, orbitofrontal, parietal, and cuneus domains. Effects were not reciprocal; baseline brain volume did not predict changes in lifestyle behaviors over time. CONCLUSION These findings are important for understanding the biological mechanisms underpinning health risk factors and can be used to target interventions and improve brain health during this critical developmental phase. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Louise Mewton
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Sarah Davies
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Matthew Sunderland
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Katrina Champion
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Nicholas Hoy
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Nicola Newton
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Maree Teesson
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Lindsay M. Squeglia
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina
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24
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McCarthy MJ, Brumback T, Thomas ML, Meruelo AD. The relations between chronotype, stressful life events, and impulsivity in the Adolescent Brain Cognitive Development (ABCD) study. J Psychiatr Res 2023; 167:119-124. [PMID: 37866325 DOI: 10.1016/j.jpsychires.2023.10.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 10/04/2023] [Accepted: 10/14/2023] [Indexed: 10/24/2023]
Abstract
Circadian rhythm disturbances, especially circadian phase delays are associated with impulsive behaviors and have been implicated in psychiatric disorders. Chronotype is a developmentally regulated proxy measure of circadian phase. Past studies have investigated the relationship between chronotype and trauma and found that trauma is associated with evening chronotypes, suggesting the course of chronotype development may be affected by adverse childhood experiences (ACEs). However, the relationships among chronotype, impulsivity and ACEs have largely been studied in a pairwise manner using small, cross-sectional cohorts. We hypothesized that in a cohort of high-risk youth, childhood trauma would be associated with later chronotype, and later chronotype would be associated with higher rates of impulsivity. We analyzed a cross-sectional sample (n = 966) from Year 2 of adolescents at high risk for psychiatric disorders from the ABCD study who were characterized for chronotype, stressful life events, and impulsivity. We used a hierarchical regression model to examine the relationship between chronotype, stressful life events, and impulsivity using the Munich Chronotype Questionnaire (MCTQ), the Life Events Scale, Urgency, Premeditation, Perseverance and Sensation Seeking (UPPS) Impulsive Behavior scale. We found associations between eveningness, stressful life events, and all dimensions of impulsivity. Increased eveningness was associated with a higher number of stressful life events and increased impulsivity. Understanding the role of stressful life events and impulsivity in those predisposed towards eveningness is useful because it may improve our understanding of the biological mechanisms that contribute to psychiatric disorders, and lead to better prevention and treatment efforts using interventions such as increased lifestyle regularity and daytime light exposure.
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Affiliation(s)
- Michael J McCarthy
- University of California, San Diego, VA San Diego Healthcare System, 3350 La Jolla Village Dr, San Diego, CA, 92161, USA.
| | - Ty Brumback
- Northern Kentucky University, 1 Louie B Nunn Dr, Highland Heights, KY, 41099, USA.
| | - Michael L Thomas
- Colorado State University, 1876 Campus Delivery, Fort Collins, CO, 80523-1876, USA.
| | - Alejandro D Meruelo
- University of California, San Diego, 9500 Gilman Dr, La Jolla, CA, 92093, USA.
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25
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Waters AM, Gibson L, Sluis RA, Modecki KL. Using Nightly Sleep Guidelines to Address Links Between Adolescents' Self-Reported Weekly Sleep Patterns and Anxiety and Depression Symptoms. Child Psychiatry Hum Dev 2023:10.1007/s10578-023-01610-0. [PMID: 37823958 DOI: 10.1007/s10578-023-01610-0] [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] [Accepted: 09/12/2023] [Indexed: 10/13/2023]
Abstract
Short and long nightly sleep durations are associated with anxiety and depression symptoms among adolescents. However, studies have not used recommended hours of nightly sleep or focused on sleep patterns across weekdays and weekends in examining links with anxiety and depression symptoms. The present study included 709 adolescents in Grade 11 (402 females; 307 males) who self-reported hours of sleep on weeknights and weekends and anxiety and depression symptoms. Using the recommended 8-10 h to define average nightly sleep for adolescents, sleep patterns across weekdays and weekends were categorised into seven classes: short stable, short increasing, average decreasing, average stable, average increasing, long decreasing, and long stable. Relative to average stable sleepers, short stable, short increasing, and long stable sleepers had significantly higher anxiety and depression. Adolescents require 8-10 h of sleep on weeknights, regardless of weekends, for optimal emotional wellbeing.
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Affiliation(s)
- Allison M Waters
- School of Applied Psychology and Centre for Mental Health, Griffith University, Mount Gravatt Campus, Brisbane, Australia.
| | - Lily Gibson
- School of Applied Psychology and Centre for Mental Health, Griffith University, Mount Gravatt Campus, Brisbane, Australia
| | - Rachel A Sluis
- School of Applied Psychology and Centre for Mental Health, Griffith University, Mount Gravatt Campus, Brisbane, Australia
| | - Kathryn L Modecki
- School of Applied Psychology and Centre for Mental Health, Griffith University, Mount Gravatt Campus, Brisbane, Australia
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26
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Petit D, Touchette E, Pennestri MH, Paquet J, Côté S, Tremblay RE, Boivin M, Montplaisir JY. Nocturnal sleep duration trajectories in early childhood and school performance at age 10 years. J Sleep Res 2023; 32:e13893. [PMID: 36973015 DOI: 10.1111/jsr.13893] [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: 11/24/2022] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 03/29/2023]
Abstract
Sleep plays a fundamental role in brain development and resultant functions. The aim was to verify whether nocturnal sleep duration during early childhood has long-term associations with academic achievement at age 10 years. The present study is part of the Quebec Longitudinal Study of Child Development, a representative cohort of infants born in 1997-1998 in the province of Quebec, Canada. Children with known neurological conditions were excluded from this cohort. Four trajectories of parent-reported nocturnal sleep duration at ages 2.5, 3, 4, 5 and 6 years were determined using a SAS procedure named PROC TRAJ. Sleep duration at age 10 years was also reported. Teachers provided data on academic performance when the children were age 10 years. These data were available for 910 children (430 boys, 480 girls; 96.6% Caucasians). Univariate and multivariable logistic regressions were performed using SPSS. Children who slept less than 8 hr per night at 2.5 years but normalized later on (Traj1) had three-five times the odds of having grades below the class average in reading, writing, mathematics and science compared with children who slept sufficiently (Traj3-4: 10-11 hr per night). Children who slept about 9 hr per night throughout childhood (Traj2) had two-three times the odds of being below the class average in mathematics and science. Sleep duration at age 10 years was not correlated with the academic performance. These results point to the presence of a very important early period during which sufficient sleep is needed to fine-tune the functions necessary for academic achievement later on.
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Affiliation(s)
- Dominique Petit
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
- Department of Psychiatry, Université de Montréal, Montreal, Quebec, Canada
| | - Evelyne Touchette
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
- Department of Psychoeducation, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada
- Research Unit on Children's Psychosocial Maladjustment, Laval University, Quebec City, Quebec, Canada
| | - Marie-Hélène Pennestri
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
- Department of Educational and Counselling Psychology, McGill University, Montreal, Quebec, Canada
- Hôpital en Santé Mentale Rivière-des-Prairies, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
| | - Jean Paquet
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
- Department of Psychiatry, Université de Montréal, Montreal, Quebec, Canada
| | - Sylvana Côté
- Department of Social and Preventive Medicine, Université de Montréal, Montreal, Quebec, Canada
- Research Unit on Children's Psychosocial Maladjustment, Université de Montréal, Montreal, Quebec, Canada
| | - Richard E Tremblay
- Department of Psychiatry, Université de Montréal, Montreal, Quebec, Canada
- Research Unit on Children's Psychosocial Maladjustment, Université de Montréal, Montreal, Quebec, Canada
- School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland
| | - Michel Boivin
- Research Unit on Children's Psychosocial Maladjustment, Laval University, Quebec City, Quebec, Canada
| | - Jacques Y Montplaisir
- Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, CIUSSS du Nord-de-I'lle-de-Montréal, Montreal, Quebec, Canada
- Department of Psychiatry, Université de Montréal, Montreal, Quebec, Canada
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27
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Gao X, Wei T, Xu S, Sun W, Zhang B, Li C, Sui R, Fei N, Li Y, Xu W, Han D. Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study. Sleep Med 2023; 110:243-253. [PMID: 37657176 DOI: 10.1016/j.sleep.2023.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/14/2023] [Accepted: 08/13/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure. METHODS We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness. RESULTS At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5). CONCLUSIONS We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.
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Affiliation(s)
- Xiang Gao
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Tao Wei
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, 100053, People's Republic of China
| | - Shenglong Xu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Wei Sun
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, 100053, People's Republic of China
| | - Bowen Zhang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Cancan Li
- Department of Epidemiology and Health Statistics, School of Public Halth, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Rongcui Sui
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Nanxi Fei
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Yanru Li
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China.
| | - Wen Xu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Demin Han
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China.
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28
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You Y, Liu J, Yao Z, Zhang S, Chen K, Ma X. Neural mechanisms of long-term exercise intervention on cognitive performance among short-sleep young adults: A hemodynamic study. Sleep Med 2023; 110:7-16. [PMID: 37517285 DOI: 10.1016/j.sleep.2023.07.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 07/02/2023] [Accepted: 07/20/2023] [Indexed: 08/01/2023]
Abstract
OBJECTIVES Short-sleep is becoming increasingly common and may negatively affect brain function including cognitive ability. Physical exercise has been proved to improve cognitive function while intensity matters. This study was conducted to examine the effects of 12-week exercise interventions on cognitive performance and prefrontal cortex activation related to task performance in short-sleep young adults. METHODS A total of 50 subjects (23.62 ± 5.28 years and 24 men) with regular short-sleep conditions (<7 h per night) participated in this study and were divided into three groups: control, moderate-intensity continuous training (MICT), and high-intensity interval training (HIIT) group. As task performance (congruent and incongruent Stroop) was monitored, changes in prefrontal oxygenated hemoglobin (oxyHb), an indicator of cortical activation, were measured using functional near-infrared spectroscopy (fNIRS) to explore the hemodynamics mechanism. RESULTS Post 12-week intervention, significant differences in reaction time for congruent [β (95%CI): -0.045 (-0.088, -0.002), p = 0.039] and incongruent Stroop tests [β (95%CI): -0.058 (-0.113, -0.003), p = 0.038] were found only in the MICT intervention group. However, HIIT did not show significant improvements in cognitive function. Left middle frontal gyrus (Frontal Mid L) and right dorsolateral superior frontal gyrus (Frontal Sup R) were both stimulated by MICT and HIIT. Moreover, left dorsolateral superior frontal gyrus (Frontal Sup L) was stimulated by MICT. CONCLUSION The findings indicated that 12-week MICT improved cognition by significantly increasing cortical activity across more brain regions. Thus, we suggested that maintaining moderate-intensity exercise could benefit cognitive function despite short sleep.
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Affiliation(s)
- Yanwei You
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China
| | - Jianxiu Liu
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China; Vanke School of Public Health, Tsinghua University, Beijing, 100084, China
| | - Zhengbang Yao
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21218, USA
| | - Shiqi Zhang
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China
| | - Keshuo Chen
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China
| | - Xindong Ma
- Division of Sports Science & Physical Education, Tsinghua University, Beijing, 100084, China; IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China.
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29
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Cui J, Li G, Zhang M, Xu J, Qi H, Ji W, Wu F, Zhang Y, Jiang F, Hu Y, Zhang W, Wei X, Manza P, Volkow ND, Gao X, Wang GJ, Zhang Y. Associations between body mass index, sleep-disordered breathing, brain structure, and behavior in healthy children. Cereb Cortex 2023; 33:10087-10097. [PMID: 37522299 PMCID: PMC10656948 DOI: 10.1093/cercor/bhad267] [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: 03/21/2023] [Revised: 06/30/2023] [Accepted: 07/01/2023] [Indexed: 08/01/2023] Open
Abstract
Pediatric overweight/obesity can lead to sleep-disordered breathing (SDB), abnormal neurological and cognitive development, and psychiatric problems, but the associations and interactions between these factors have not been fully explored. Therefore, we investigated the associations between body mass index (BMI), SDB, psychiatric and cognitive measures, and brain morphometry in 8484 children 9-11 years old using the Adolescent Brain Cognitive Development dataset. BMI was positively associated with SDB, and both were negatively correlated with cortical thickness in lingual gyrus and lateral orbitofrontal cortex, and cortical volumes in postcentral gyrus, precentral gyrus, precuneus, superior parietal lobule, and insula. Mediation analysis showed that SDB partially mediated the effect of overweight/obesity on these brain regions. Dimensional psychopathology (including aggressive behavior and externalizing problem) and cognitive function were correlated with BMI and SDB. SDB and cortical volumes in precentral gyrus and insula mediated the correlations between BMI and externalizing problem and matrix reasoning ability. Comparisons by sex showed that obesity and SDB had a greater impact on brain measures, cognitive function, and mental health in girls than in boys. These findings suggest that preventing childhood obesity will help decrease SDB symptom burden, abnormal neurological and cognitive development, and psychiatric problems.
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Affiliation(s)
- Jianqi Cui
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Guanya Li
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Minmin Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Jiayu Xu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Haowen Qi
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Weibin Ji
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Feifei Wu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yaqi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Fukun Jiang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Yang Hu
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Wenchao Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
| | - Xiaorong Wei
- Kindergarten, Air Force Medical University, Xi'an, Shaanxi 710032, China
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Xinbo Gao
- Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
- Chongqing Institute for Brain, Guangyang Bay Laboratory, Chongqing 400064, China
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Yi Zhang
- Center for Brain Imaging, School of Life Science and Technology, Xidian University & Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, Xi'an, Shaanxi 710126, China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, China
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30
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Lai M, Gao Y, Lu L, Huang X, Gong Q, Li J, Jiang P. Functional connectivity of the left inferior parietal lobule mediates the impact of anxiety and depression symptoms on sleep quality in healthy adults. Cereb Cortex 2023; 33:9908-9916. [PMID: 37429833 DOI: 10.1093/cercor/bhad253] [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: 03/08/2023] [Revised: 06/14/2023] [Accepted: 06/15/2023] [Indexed: 07/12/2023] Open
Abstract
Individuals with anxiety and depression symptoms are vulnerable to sleep disturbances. The current study aimed to explore the shared neuro-mechanisms underlying the effect of anxiety and depression symptoms on sleep quality. We recruited a cohort of 92 healthy adults who underwent functional magnetic resonance imaging scanning. We measured anxiety and depression symptoms using the Zung Self-rating Anxiety/Depression Scales and sleep quality using the Pittsburgh Sleep Quality Index. Independent component analysis was used to explore the functional connectivity (FC) of brain networks. Whole-brain linear regression analysis showed that poor sleep quality was associated with increased FC in the left inferior parietal lobule (IPL) within the anterior default mode network. Next, we extracted the covariance of anxiety and depression symptoms using principal component analysis to represent participants' emotional features. Mediation analysis revealed that the intra-network FC of the left IPL mediated the association between the covariance of anxiety and depression symptoms and sleep quality. To conclude, the FC of the left IPL may be a potential neural substrate in the association between the covariance of anxiety and depression symptoms and poor sleep quality, and may serve as a potential intervention target for the treatment of sleep disturbance in the future.
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Affiliation(s)
- Mingfeng Lai
- Mental Health Center, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, 610041 Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, 610041 Chengdu, China
| | - Lu Lu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, 610041 Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, 610041 Chengdu, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, 610041 Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, 610041 Chengdu, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, 610041 Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, 610041 Chengdu, China
| | - Jing Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ping Jiang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, 610041 Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, 610041 Chengdu, China
- West China Medical Publishers, West China Hospital, Sichuan University, 610041 Chengdu, China
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31
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Jiang R, Wu J, Rosenblatt M, Dai W, Rodriguez RX, Sui J, Qi S, Liang Q, Xu B, Meng Q, Calhoun VD, Scheinost D. Elevated C-reactive protein mediates the liver-brain axis: a preliminary study. EBioMedicine 2023; 93:104679. [PMID: 37356206 PMCID: PMC10320521 DOI: 10.1016/j.ebiom.2023.104679] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Revised: 06/10/2023] [Accepted: 06/11/2023] [Indexed: 06/27/2023] Open
Abstract
BACKGROUND Chronic liver diseases of all etiologies exist along a spectrum with varying degrees of hepatic fibrosis. Despite accumulating evidence implying associations between liver fibrosis and cognitive functioning, there is limited research exploring the underlying neurobiological factors and the possible mediating role of inflammation on the liver-brain axis. METHODS Using data from the UK Biobank, we examined the cross-sectional association of liver fibrosis (as measured by Fibrosis-4 score) with cognitive functioning and regional grey matter volumes (GMVs) while adjusting for numerous covariates and multiple comparisons. We further performed post-hoc preliminary analysis to investigate the mediating effect of C-reactive protein (CRP) on the association between liver fibrosis and both cognitive functioning and GMVs. FINDINGS We analysed behaviour from up to 447,626 participants (N ranged from 45,055 to 447,533 per specific cognitive metric) 37 years and older. 38,244 participants (age range 44-82 years) had GMV data collected at a median 9-year follow-up. Liver fibrosis showed significant associations with cognitive performance in reasoning, working memory, visual memory, prospective memory, executive function, and processing speed. Subgroup analysis indicated larger effects sizes for symbol digital substitution but smaller effect sizes for trail making in middle-aged people than their old counterparts. Neuroimaging analyses revealed significant associations between liver fibrosis and reduced regional GMVs, primarily in the hippocampus, thalamus, ventral striatum, parahippocampal gyrus, brain stem, and cerebellum. CRP levels were significantly higher in adults with advanced liver fibrosis than those without, indicating an elevated systemic inflammation. Moreover, the serum CRP significantly mediated the effect of liver fibrosis on most cognitive measures and regional GMVs in the hippocampus and brain stem. INTERPRETATION This study provides a well-powered characterization of associations between liver fibrosis, cognitive impairment, and grey matter atrophy. It also highlights the possibly mediating role of systemic inflammation on the liver-brain axis. Early surveillance and prevention of liver diseases may reduce cognitive decline and brain GMV loss. FUNDING National Science Foundation, and National Institutes of Health.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA.
| | - Jing Wu
- Second Department of Liver Disease Center, Youan Hospital, Capital Medical University, Beijing, 100069, China
| | - Matthew Rosenblatt
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Wei Dai
- Department of Biostatistics, Yale University, New Haven, CT 06520, USA
| | - Raimundo X Rodriguez
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520, USA
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100088, China
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Qinghao Liang
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA
| | - Bin Xu
- Second Department of Liver Disease Center, Youan Hospital, Capital Medical University, Beijing, 100069, China.
| | - Qinghua Meng
- Department of Medical Oncology, Beijing You-An Hospital, Capital Medical University, Beijing, 100069, China
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520, USA; Department of Statistics & Data Science, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA; Wu Tsai Institute, Yale University, 100 College Street, New Haven, CT 06510, USA.
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32
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Cao L, Feng R, Gao Y, Bao W, Zhou Z, Liang K, Hu X, Li H, Zhang L, Li Y, Zhuo L, Huang G, Huang X. Suprachiasmatic nucleus functional connectivity related to insomnia symptoms in adolescents with major depressive disorder. Front Psychiatry 2023; 14:1154095. [PMID: 37260759 PMCID: PMC10228684 DOI: 10.3389/fpsyt.2023.1154095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 04/21/2023] [Indexed: 06/02/2023] Open
Abstract
Background Insomnia is a commonly seen symptom in adolescents with major depressive disorder (MDD). The suprachiasmatic nucleus (SCN), which is the circadian rhythm regulation center, plays a crucial role in the regulation of sleep-wake circulation. Nevertheless, how SCN function contributes to the exact neural mechanisms underlying the associations between insomnia and depressive symptoms has not been explored in adolescents. In the current study, we aimed to explore the relationship between SCN functional connectivity (FC) and insomnia symptoms in adolescents with MDD using a seed-based FC method. Methods In the current study, we recruited sixty-eight first-episode drug-naïve adolescents with MDD and classified them into high insomnia (MDD-HI) and low insomnia (MDD-LI) groups according to the sleep disturbance subscale of the Hamilton Depression Rating Scale (HAMD-S). Forty-three age/gender-matched healthy controls (HCs) were also recruited. SCN FC maps were generally for all subjects and compared among three groups using one-way ANOVA with age, gender and adjusted HAMD score as covariates. We used partial correlations to explore associations between altered FC and clinical symptoms, including sleep quality scores. Results Adolescents with MDD showed worse sleep quality, which positively correlated with the severity of depression. Compared to MDD-LI and HCs, MDD-HI adolescents demonstrated significantly decreased FC between the right SCN and bilateral precuneus, and there was no significant difference between the MDD-LI and HC groups. The HAMD-S scores were negatively correlated with bilateral SCN-precuneus connectivity, and the retardation factor score of HAMD was negatively correlated with right SCN-precuneus connectivity. Conclusion The altered FC between the SCN and precuneus may underline the neural mechanism of sleep-related symptoms in depressive adolescents and provide potential targets for personalized treatment strategies.
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Affiliation(s)
- Lingling Cao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Department of Radiology, Sichuan Mianyang 404 Hospital, Mianyang, China
| | - Ruohan Feng
- Department of Radiology, Sichuan Mental Health Center, The Third Hospital of Mianyang, Mianyang, China
| | - Yingxue Gao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Weijie Bao
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Zilin Zhou
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Kaili Liang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xinyue Hu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hailong Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Lianqing Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yang Li
- Department of Psychiatry, Sichuan Mental Health Center, The Third Hospital of Mianyang, Mianyang, China
| | - Lihua Zhuo
- Department of Radiology, Sichuan Mental Health Center, The Third Hospital of Mianyang, Mianyang, China
| | - Guoping Huang
- Department of Psychiatry, Sichuan Mental Health Center, The Third Hospital of Mianyang, Mianyang, China
| | - Xiaoqi Huang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
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Cao X. Sleep Time and Depression Symptoms as Predictors of Cognitive Development Among Adolescents: A Cross-Lagged Study From China. Psychol Rep 2023:332941231175833. [PMID: 37164938 DOI: 10.1177/00332941231175833] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Sleep time and depression symptoms are important factors affecting cognitive development in adolescents. Based on the China Education Panel Survey (CEPS) database, this study used a two-wave cross-lagged model to examine the bidirectional relationship between sleep time, depression symptoms, and cognitive development. Descriptive statistics showed that Chinese adolescents' cognitive development increased significantly from 7th to 8th grade in junior high school, but unfortunately, their depression level and average sleep time per night demonstrated a slightly deteriorating trend. Correlation analysis showed that there was a relatively stable negative correlation between cognitive development, sleep time, and depression symptoms. Moreover, the cross-lagged model revealed that there was a bidirectional relationship between cognitive development and sleep time, a bidirectional relationship between depression symptoms and sleep time, and a unidirectional relationship between depression symptoms and cognitive development. Male adolescents in the subgroup were consistent with the total sample. Among female adolescents, only cognitive development and sleep time have a bidirectional relationship, while depression symptoms and cognitive development, and depression symptoms and sleep time have a unidirectional relationship. Therefore, it is of significance to take targeted action to promote cognitive development and healthy growth in adolescents worldwide.
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Affiliation(s)
- Xiaojie Cao
- Graduate School of Education, Peking University, Beijing, China
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34
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Fung H, Yeo BTT, Chen C, Lo JC, Chee MWL, Ong JL. Adherence to 24-Hour Movement Recommendations and Health Indicators in Early Adolescence: Cross-Sectional and Longitudinal Associations in the Adolescent Brain Cognitive Development Study. J Adolesc Health 2023; 72:460-470. [PMID: 36528521 DOI: 10.1016/j.jadohealth.2022.10.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 09/12/2022] [Accepted: 10/13/2022] [Indexed: 12/23/2022]
Abstract
PURPOSE Adherence to 24-hour movement guidelines of ≥60 minutes of physical activity, ≤2 hours of screen time, and 9-11 hours of sleep has been shown to benefit cognitive, physical, and psychosocial health in children and young adolescents aged 5-13 years. However, these findings have mostly been based on cross-sectional studies or relatively small samples and the associations between adherence to guidelines and brain structure remain to be evaluated. METHODS Data from the Adolescent Brain Cognitive Development℠ (ABCD) study of 10,574 early adolescents aged 9-14 years from September 2016 to January 2021 were used to examine whether adherence to 24-hour movement guidelines benefits cognition (general cognitive ability, executive function, and learning/memory assessed by the National Institutes of Health Toolbox neurocognitive battery), body mass index, psychosocial health (internalizing, externalizing, and total problems from the parent-reported Child Behavior Checklist), and magnetic resonance imaging-derived brain morphometric measures at baseline (T1), ∼2 years later (T2), and longitudinally from T1 to T2 (T2-T1). Multivariable linear mixed models were used, with adjustments for sociodemographic confounders. Time elapsed and T1 outcome measures were also controlled for in longitudinal models. RESULTS Better cognitive scores, fewer behavioral problems, lower adiposity levels, and greater gray matter volumes were observed in those who met both sleep and screen time recommendations compared to those who met none. Longitudinal follow-up further supports these findings; participants who met both recommendations at T1 and T2 evidenced better outcome measures than those who met none. DISCUSSION These findings support consideration of integrated rather than isolated movement recommendations across the day in early adolescence for better cognitive, physical and psychosocial health. Although the associations between physical activity and health indicators were less consistent in this study, the significant findings from sleep and screen time demonstrate the importance of considering movement recommendations in an integrated rather than isolated manner for adolescent health. It is recommended that movement behaviors be simultaneously targeted for better developmental outcomes.
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Affiliation(s)
- Hoki Fung
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Meditation Research Group, Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, Massachusetts
| | - B T Thomas Yeo
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Electrical and Computer Engineering, National University of Singapore, Singapore; Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, Singapore; N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Christina Chen
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - June C Lo
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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35
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Zhao Y, Yang X, Cheng S, Li C, He D, Cai Q, Wei W, Qin X, Zhang N, Shi S, Chu X, Meng P, Zhang F. Assessing the effect of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes. Cereb Cortex 2023:7030864. [PMID: 36750265 DOI: 10.1093/cercor/bhac526] [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: 10/11/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 02/09/2023] Open
Abstract
Longitudinal changes in brain structure and lifestyle can affect sleep phenotypes. However, the influence of the interaction between longitudinal changes in brain structure and lifestyle on sleep phenotypes remains unclear. Genome-wide association study dataset of longitudinal changes in brain structure was obtained from published study. Phenotypic data of lifestyles and sleep phenotypes were obtained from UK Biobank cohort. Using genotype data from UK Biobank, we calculated polygenetic risk scores of longitudinal changes in brain structure phenotypes. Linear/logistic regression analysis was conducted to evaluate interactions between longitudinal changes in brain structure and lifestyles on sleep duration, chronotype, insomnia, snoring and daytime dozing. Multiple lifestyle × longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activity×caudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 × 10-3) in total samples, coffee intake×cerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 × 10-4) in females. Besides, we found 4 overlapping interactions in different sleep phenotypes. We conducted sex stratification analysis and identified one overlapping interaction between female and male. Our results support the moderate effects of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes, and deepen our understanding of the pathogenesis of sleep disorders.
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Affiliation(s)
- Yijing Zhao
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Qingqing Cai
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Sirong Shi
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xiaoge Chu
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
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Fu Z, Abbott CC, Miller J, Deng ZD, McClintock SM, Sendi MSE, Sui J, Calhoun VD. Cerebro-cerebellar functional neuroplasticity mediates the effect of electric field on electroconvulsive therapy outcomes. Transl Psychiatry 2023; 13:43. [PMID: 36746924 PMCID: PMC9902462 DOI: 10.1038/s41398-023-02312-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 01/04/2023] [Accepted: 01/06/2023] [Indexed: 02/08/2023] Open
Abstract
Electroconvulsive therapy (ECT) is the most effective treatment for severe depression and works by applying an electric current through the brain. The applied current generates an electric field (E-field) and seizure activity, changing the brain's functional organization. The E-field, which is determined by electrode placement (right unilateral or bitemporal) and pulse amplitude (600, 700, or 800 milliamperes), is associated with the ECT response. However, the neural mechanisms underlying the relationship between E-field, functional brain changes, and clinical outcomes of ECT are not well understood. Here, we investigated the relationships between whole-brain E-field (Ebrain, the 90th percentile of E-field magnitude in the brain), cerebro-cerebellar functional network connectivity (FNC), and clinical outcomes (cognitive performance and depression severity). A fully automated independent component analysis framework determined the FNC between the cerebro-cerebellar networks. We found a linear relationship between Ebrain and cognitive outcomes. The mediation analysis showed that the cerebellum to middle occipital gyrus (MOG)/posterior cingulate cortex (PCC) FNC mediated the effects of Ebrain on cognitive performance. In addition, there is a mediation effect through the cerebellum to parietal lobule FNC between Ebrain and antidepressant outcomes. The pair-wise t-tests further demonstrated that a larger Ebrain was associated with increased FNC between cerebellum and MOG and decreased FNC between cerebellum and PCC, which were linked with decreased cognitive performance. This study implies that an optimal E-field balancing the antidepressant and cognitive outcomes should be considered in relation to cerebro-cerebellar functional neuroplasticity.
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Affiliation(s)
- Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
| | | | - Jeremy Miller
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA
| | - Zhi-De Deng
- Computational Neurostimulation Research Program, Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Shawn M McClintock
- Division of Psychology, Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Mohammad S E Sendi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Sleep and Mental Health Problems in Children and Adolescents. Sleep Med Clin 2023; 18:245-254. [PMID: 37120167 DOI: 10.1016/j.jsmc.2023.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
Abstract
Previous reviews have described the links between sleep and mental health extensively. In this narrative review, we focus on literature published during the last decade investigating the links between sleep and mental health difficulties in childhood and adolescence. More specifically, we focus on the mental health disorders listed in the most recent edition of the Diagnostic and Statistical Manual of Mental Disorders. We also discuss possible mechanisms underlying these associations. The review ends with a discussion of possible future lines of enquiry.
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Petrican R, Paine AL, Escott-Price V, Shelton KH. Overlapping brain correlates of superior cognition among children at genetic risk for Alzheimer's disease and/or major depressive disorder. Sci Rep 2023; 13:984. [PMID: 36653486 PMCID: PMC9849214 DOI: 10.1038/s41598-023-28057-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Early life adversity (ELA) tends to accelerate neurobiological ageing, which, in turn, is thought to heighten vulnerability to both major depressive disorder (MDD) and Alzheimer's disease (AD). The two conditions are putatively related, with MDD representing either a risk factor or early symptom of AD. Given the substantial environmental susceptibility of both disorders, timely identification of their neurocognitive markers could facilitate interventions to prevent clinical onset. To this end, we analysed multimodal data from the Adolescent Brain and Cognitive Development study (ages 9-10 years). To disentangle genetic from correlated genetic-environmental influences, while also probing gene-adversity interactions, we compared adoptees, a group generally exposed to substantial ELA, with children raised by their biological families via genetic risk scores (GRS) from genome-wide association studies. AD and MDD GRSs predicted overlapping and widespread neurodevelopmental alterations associated with superior fluid cognition. Specifically, among adoptees only, greater AD GRS were related to accelerated structural maturation (i.e., cortical thinning) and higher MDD GRS were linked to delayed functional neurodevelopment, as reflected in compensatory brain activation on an inhibitory control task. Our study identifies compensatory mechanisms linked to MDD risk and highlights the potential cognitive benefits of accelerated maturation linked to AD vulnerability in late childhood.
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Affiliation(s)
- Raluca Petrican
- Institute of Population Health, Department of Psychology, University of Liverpool, Bedford Street South, Liverpool, L69 7ZA, UK.
| | - Amy L Paine
- School of Psychology, Cardiff University, 70 Park Place, Cardiff, CF10 3AT, UK
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Katherine H Shelton
- School of Psychology, Cardiff University, 70 Park Place, Cardiff, CF10 3AT, UK
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Zhang G, Liu T, Wei W, Zhang R, Wang H, Wang M. Evaluation of altered brain activity in type 2 diabetes using various indices of brain function: A resting-state functional magnetic resonance imaging study. Front Hum Neurosci 2023; 16:1032264. [PMID: 36699964 PMCID: PMC9870028 DOI: 10.3389/fnhum.2022.1032264] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/05/2022] [Indexed: 01/11/2023] Open
Abstract
Background Type 2 diabetes mellitus (T2DM) has been identified as a risk factor that increases the rate of cognitive decline. Previous studies showed that patients with T2DM had brain function alterations based on a single index of resting-state functional magnetic resonance imaging (rs-fMRI). The present study aimed to explore spontaneous brain activity in patients with T2DM by comparing various rs-fMRI indices, and to determine the relationship between these changes and cognitive dysfunction. Methods A total of 52 patients with T2DM and age- and sex-matched control participants were included in this study. The amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) values were calculated to represent the status of spontaneous neural activity. The Montreal Cognitive Assessment (MoCA) was used for the rapid evaluation of cognition in all subjects. Pearson correlation and mediation analyses were conducted to investigate the relationship between rs-fMRI indices and clinical parameters such as fasting glucose, disease duration, and MoCA. Results Patients with T2DM had alterations of concordant spontaneous brain activity in brain areas including the bilateral cerebellum posterior lobe, the left inferior temporal gyrus (ITG.L), the parahippocampal gyrus, and the left supplementary motor area (SMA.L). The indices were significantly correlated to each other in most of the detected brain areas. Positive correlations were observed between fasting glucose and neural activity in the surrounding areas of the left insula and the inferior frontal gyrus. MoCA scores were negatively correlated with the ReHo values extracted from the left anterior occipital lobe and the superior cerebellar cortex and were positively correlated with VMHC values extracted from the left caudate and the precentral gyrus (PreCG). No significant mediation effect of abnormal brain activity was found in the relationship between clinical parameters and MoCA scores. Conclusion The current study demonstrated the functional concordance of abnormal brain activities in patients with T2DM by comparing ALFF, ReHo, and VMHC measurements. Widespread abnormalities mainly involved in motor and sensory processing functions may provide insight into examining T2DM-related neurological pathophysiology.
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Affiliation(s)
- Ge Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China
| | - Taiyuan Liu
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Rui Zhang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China
| | - Huilin Wang
- Department of Radiology, Bethune International Peace Hospital, Shijiazhuang, China,*Correspondence: Huilin Wang ✉
| | - Meiyun Wang
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, China,Laboratory of Brian Science and Brain-Like Intelligence Technology, Institute for Integrated Medical Science and Engineering, Henan Academy of Sciences, Zhengzhou, China,Meiyun Wang ✉
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Soehner AM, Hayes RA, Franzen PL, Goldstein TR, Hasler BP, Buysse DJ, Siegle GJ, Dahl RE, Forbes EE, Ladouceur CD, McMakin DL, Ryan ND, Silk JS, Jalbrzikowski M. Naturalistic Sleep Patterns are Linked to Global Structural Brain Aging in Adolescence. J Adolesc Health 2023; 72:96-104. [PMID: 36270890 PMCID: PMC9881228 DOI: 10.1016/j.jadohealth.2022.08.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 08/17/2022] [Accepted: 08/17/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE We examined whether interindividual differences in naturalistic sleep patterns correlate with any deviations from typical brain aging. METHODS Our sample consisted of 251 participants without current psychiatric diagnoses (9-25 years; mean [standard deviation] = 17.4 ± 4.52 yr; 58% female) drawn from the Neuroimaging and Pediatric Sleep Databank. Participants completed a T1-weighted structural magnetic resonance imaging scan and 5-7 days of wrist actigraphy to assess naturalistic sleep patterns (duration, timing, continuity, and regularity). We estimated brain age from extracted structural magnetic resonance imaging indices and calculated brain age gap (estimated brain age-chronological age). Robust regressions tested cross-sectional associations between brain age gap and sleep patterns. Exploratory models investigated moderating effects of age and biological gender and, in a subset of the sample, links between sleep, brain age gap, and depression severity (Patient-Reported Outcomes Measurement Information System Depression). RESULTS Later sleep timing (midsleep) was associated with more advanced brain aging (larger brain age gap), β = 0.1575, puncorr = .0042, pfdr = .0167. Exploratory models suggested that this effect may be driven by males, although the interaction of gender and brain age gap did not survive multiple comparison correction (β = 0.2459, puncorr = .0336, pfdr = .1061). Sleep duration, continuity, and regularity were not significantly associated with brain age gap. Age did not moderate any brain age gap-sleep relationships. In this psychiatrically healthy sample, depression severity was also not associated with brain age gap or sleep. DISCUSSION Later midsleep may be one behavioral cause or correlate of more advanced brain aging, particularly among males. Future studies should examine whether advanced brain aging and individual differences in sleep precede the onset of suboptimal cognitive-emotional outcomes in adolescents.
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Affiliation(s)
- Adriane M Soehner
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Rebecca A Hayes
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts
| | - Peter L Franzen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Tina R Goldstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Brant P Hasler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Greg J Siegle
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Ronald E Dahl
- School of Public Health, University of California, Berkeley, Berkeley, California
| | - Erika E Forbes
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Cecile D Ladouceur
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Dana L McMakin
- Department of Psychology, Florida International University, Miami, Florida
| | - Neal D Ryan
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jennifer S Silk
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Maria Jalbrzikowski
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts.
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Chen Z, Jiang T, Yin X, Li B, Tan Z, Guo J. The increased functional connectivity between the locus coeruleus and supramarginal gyrus in insomnia disorder with acupuncture modulation. Front Neurosci 2023; 17:1131916. [PMID: 37152608 PMCID: PMC10157050 DOI: 10.3389/fnins.2023.1131916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 03/31/2023] [Indexed: 05/09/2023] Open
Abstract
Background Insomnia disorder (ID) seriously affects the quality of people's daily life, and acupuncture is an effective therapy for it. As an essential component of the upward activation system, the locus coeruleus (LC) plays a crucial role in sleep-wake regulation, its aberrant functional connectivity (FC) is found to be involved in ID. The purpose of this study was to explore the modulation effect of acupuncture on the resting state FC of LC in ID patients. Methods 60 ID patients were recruited and randomly assigned to real acupuncture (RA) or sham acupuncture (SA) treatment. Resting-state functional magnetic resonance imaging (fMRI) data were collected before and after the treatment. With LC as the region of interest, the FC method was adopted to examine acupuncture-related modulation of intrinsic connectivity in ID patients. The Pittsburgh Sleep Quality Index (PSQI), Hyperarousal Scale (HAS), and actigraphy were used to assess sleep quality and cortical hyperarousal states. Associations between clinical outcomes and FC features were calculated using Pearson's correlation analysis. Results The improvement in sleep quality and hyperarousal in the RA group was greater than that in the SA group. After treatment, the FC between the LC and left inferior frontal gyrus (IFG) decreased in the RA group. The FC between the LC and left insula and supramarginal gyrus (SMG) was higher in the RA group. The change of LC FC values with the SMG was negatively associated with the change in PSQI scores. Conclusion Acupuncture can modulate FC between the LC and IFG, insular gyrus, and SMG. This may imply the potential mechanism of acupuncture treatment for insomnia.
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Affiliation(s)
- Zhaoyi Chen
- Beijing Key Laboratory of Acupuncture Neuromodulation, Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Tongfei Jiang
- Beijing Key Laboratory of Acupuncture Neuromodulation, Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Xuejiao Yin
- Beijing Key Laboratory of Acupuncture Neuromodulation, Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Bin Li
- Beijing Key Laboratory of Acupuncture Neuromodulation, Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
| | - Zhongjian Tan
- Department of Radiology, Dong Zhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Jing Guo
- Beijing Key Laboratory of Acupuncture Neuromodulation, Department of Acupuncture and Moxibustion, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China
- *Correspondence: Jing Guo,
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Pan R, Zhang Y, Xu Z, Yi W, Zhao F, Song J, Sun Q, Du P, Fang J, Cheng J, Liu Y, Chen C, Lu Y, Li T, Su H, Shi X. Exposure to fine particulate matter constituents and cognitive function performance, potential mediation by sleep quality: A multicenter study among Chinese adults aged 40-89 years. ENVIRONMENT INTERNATIONAL 2022; 170:107566. [PMID: 36219911 DOI: 10.1016/j.envint.2022.107566] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 06/16/2023]
Abstract
Although exposure to fine particulate matter (PM2.5) has been associated with cognitive decline, little is known about which PM2.5 constituents are more harmful. Recent study on the association between PM2.5 and sleep quality prompted us to propose that sleep quality may mediate the adverse effects of PM2.5 components on cognitive decline. Understanding the association between PM2.5 constituents and cognitive function, as well as the mediating role of sleep quality provides a future intervention target for improving cognitive function. Using data involving 1834 participants from a multicenter cross-sectional study in nine cities of the Beijing-Tianjin-Hebei (BTH) region in China, we undertook multivariable linear regression analyses to quantify the association of annual moving-average PM2.5 and its chemical constituents with cognitive function and to assess the modifying role of exposure characteristic in this association. Besides, we examined the extent to which this association of PM2.5 constituents with cognitive function was mediated via sleep quality by a mediation analysis. We observed significantly negative associations between an increase of one interquartile range increase in PM2.5 [-0.876 (95 % CI: -1.205, -0.548)], organic carbon [-0.481 (95 % CI: -0.744, -0.219)], potassium [-0.344 (95 % CI: -0.530, -0.157)], iron [-0.468 (95 % CI: -0.646, -0.291)], and ammonium ion [-0.125 (95 % CI: -0.197, -0.052)] and cognitive decline. However, we didn't find any individual components more harmful than PM2.5. Poor sleep quality partially mediated the estimated associations, which were explained ranging from 2.28 % to 11.99 %. Stratification analyses showed that people living in areas with lower greenspace were more susceptible to specific PM2.5 components. Our study suggests that the adverse effect of suffering from PM2.5 components is more pronounced among individuals with poor sleep quality, amplifying environmental inequalities in health. Besides reducing environmental pollution, improving sleep quality may be another measure worth considering to improve cognition if our research is confirmed in the future.
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Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Qinghua Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Peng Du
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yingchun Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yifu Lu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
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Ho TC, Shah R, Mishra J, May AC, Tapert SF. Multi-level predictors of depression symptoms in the Adolescent Brain Cognitive Development (ABCD) study. J Child Psychol Psychiatry 2022; 63:1523-1533. [PMID: 35307818 PMCID: PMC9489813 DOI: 10.1111/jcpp.13608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/25/2022] [Indexed: 01/09/2023]
Abstract
BACKGROUND While identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study. METHODS A total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up. RESULTS Both linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2 = 0.156; GBT: MAE = 3.761; R2 = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2 = 0.103; GBT: MAE = 4.262; R2 = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints. CONCLUSIONS Consistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.
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Affiliation(s)
- Tiffany C. Ho
- Department of Psychiatry & Behavioral Sciences; Weill Institute of Neurosciences; University of California, San Francisco, San Francisco, CA
| | - Rutvik Shah
- Department of Psychiatry & Behavioral Sciences; Weill Institute of Neurosciences; University of California, San Francisco, San Francisco, CA
- Department of Psychiatry, University of California, San Diego, San Diego, CA
| | - Jyoti Mishra
- Department of Psychiatry, University of California, San Diego, San Diego, CA
| | - April C. May
- Department of Psychiatry, University of California, San Diego, San Diego, CA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA
| | - Susan F. Tapert
- Department of Psychiatry, University of California, San Diego, San Diego, CA
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Ma Q, Wang H, Rolls ET, Xiang S, Li J, Li Y, Zhou Q, Cheng W, Li F. Lower gestational age is associated with lower cortical volume and cognitive and educational performance in adolescence. BMC Med 2022; 20:424. [PMID: 36329481 PMCID: PMC9635194 DOI: 10.1186/s12916-022-02627-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Gestational age (GA) is associated with later cognition and behavior. However, it is unclear how specific cognitive domains and brain structural development varies with the stepwise change of gestational duration. METHODS This large-scale longitudinal cohort study analyzed 11,878 early adolescents' brain volume maps at 9-10 years (baseline) and 5685 at 11-12 years (a 2-year follow-up) from the Adolescent Brain Cognitive Development (ABCD) study. According to gestational age, adolescents were divided into five categorical groups: ≤ 33 weeks, 34-35 weeks, 36 weeks, 37-39 weeks, and ≥ 40 weeks. The NIH Toolbox was used to estimate neurocognitive performance, including crystallized and fluid intelligence, which was measured for 11,878 adolescents at baseline with crystallized intelligence and relevant subscales obtained at 2-year follow-up (with participant numbers ranging from 6185 to 6310 depending on the cognitive domain). An additional large population-based cohort of 618,070 middle adolescents at ninth-grade (15-16 years) from the Danish national register was utilized to validate the association between gestational age and academic achievements. A linear mixed model was used to examine the group differences between gestational age and neurocognitive performance, school achievements, and grey matter volume. A mediation analysis was performed to examine whether brain structural volumes mediated the association between GA and neurocognition, followed with a longitudinal analysis to track the changes. RESULTS Significant group differences were found in all neurocognitive scores, school achievements, and twenty-five cortical regional volumes (P < 0.05, Bonferroni corrected). Specifically, lower gestational ages were associated with graded lower cognition and school achievements and with smaller brain volumes of the fronto-parieto-temporal, fusiform, cingulate, insula, postcentral, hippocampal, thalamic, and pallidal regions. These lower brain volumes mediated the association between gestational age and cognitive function (P = 1 × 10-8, β = 0.017, 95% CI: 0.007-0.028). Longitudinal analysis showed that compared to full term adolescents, preterm adolescents still had smaller brain volumes and crystallized intelligence scores at 11-12 years. CONCLUSIONS These results emphasize the relationships between gestational age at birth and adolescents' lower brain volume, and lower cognitive and educational performance, measured many years later when 9-10 and 11-12 years old. The study indicates the importance of early screening and close follow-up for neurocognitive and behavioral development for children and adolescents born with gestational ages that are even a little lower than full term.
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Affiliation(s)
- Qing Ma
- Department of Neurology, Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China
| | - Hui Wang
- Department of Developmental and Behavioral Pediatric & Child Primary Care/MOE-Shanghai Key Laboratory of Children's Environmental Health, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200082, China
| | - Edmund T Rolls
- Department of Neurology, Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.,Department of Computer Science, University of Warwick, Coventry CV4 7AL, Conventry, UK.,Oxford Centre for Computational Neuroscience, Oxford, UK
| | - Shitong Xiang
- Department of Neurology, Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China
| | - Jiong Li
- Department of Clinical Medicine, Aarhus University, Aarhus, 8000, Denmark
| | - Yuzhu Li
- Department of Neurology, Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China.,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China
| | - Qiongjie Zhou
- Obstetrics and Gynecology Hospital of Fudan University, Shanghai, 200011, China.,Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Shanghai, 200011, China
| | - Wei Cheng
- Department of Neurology, Huashan Hospital, Institute of Science and Technology for Brain-Inspired Intelligence, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, 200433, China. .,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China. .,Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, 321004, China. .,Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, 200032, China.
| | - Fei Li
- Department of Developmental and Behavioral Pediatric & Child Primary Care/MOE-Shanghai Key Laboratory of Children's Environmental Health, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200082, China.
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Wu X, Yu G, Zhang K, Feng J, Zhang J, Sahakian BJ, Robbins TW. Symptom-Based Profiling and Multimodal Neuroimaging of a Large Preteenage Population Identifies Distinct Obsessive-Compulsive Disorder-like Subtypes With Neurocognitive Differences. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:1078-1089. [PMID: 34224907 DOI: 10.1016/j.bpsc.2021.06.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/06/2021] [Accepted: 06/21/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) is characterized by both internalizing (anxiety) and externalizing (compulsivity) symptoms. Currently, little is known about their interrelationships and their relative contributions to disease heterogeneity. Our goal is to resolve affective and cognitive symptom heterogeneity related to internalized and externalized symptom dimensions by determining subtypes of children with OCD symptoms, and to identify any corresponding neural differences. METHODS A total of 1269 children with OCD symptoms screened using the Child Behavior Checklist Obsessive-Compulsive Symptom scale and 3987 matched control subjects were obtained from the Adolescent Brain Cognitive Development (ABCD) Study. Consensus hierarchical clustering was used to cluster children with OCD symptoms into distinct subtypes. Ten neurocognitive task scores and 20 Child Behavior Checklist syndrome scales were used to characterize cognitive/behavioral differences. Gray matter volume, fractional anisotropy of major white matter fiber tracts, and functional connectivity among networks were used in case-control studies. RESULTS We identified two subgroups with contrasting patterns in internalized and externalized dimensions. Group 1 showed compulsive thoughts and repeated acts but relatively low anxiety symptoms, whereas group 2 exhibited higher anxiety and perfectionism and relatively low repetitive behavior. Only group 1 had significant cognitive impairments and gray matter volume reductions in the bilateral inferior parietal lobe, precentral gyrus, and precuneus gyrus, and had white matter tract fractional anisotropy reductions in the corticostriatal fasciculus. CONCLUSIONS Children with OCD symptoms are heterogeneous at the level of symptom clustering and its underlying neural basis. Two subgroups represent distinct patterns of externalizing and internalizing symptoms, suggesting that anxiety is not its major predisposing factor. These results may have implications for the nosology and treatment of preteenage OCD.
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Affiliation(s)
- Xinran Wu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Gechang Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Kai Zhang
- School of Computer Science and Technology, East China Normal University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Sciences, Shanghai, China; Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, United Kingdom
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
| | - Barbara J Sahakian
- Departments of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Trevor W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Psychology, University of Cambridge, Cambridge, United Kingdom; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
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46
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Shared brain and genetic architectures between mental health and physical activity. Transl Psychiatry 2022; 12:428. [PMID: 36192376 PMCID: PMC9530213 DOI: 10.1038/s41398-022-02172-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 11/15/2022] Open
Abstract
Physical activity is correlated with, and effectively treats various forms of psychopathology. However, whether biological correlates of physical activity and psychopathology are shared remains unclear. Here, we examined the extent to which the neural and genetic architecture of physical activity and mental health are shared. Using data from the UK Biobank (N = 6389), we applied canonical correlation analysis to estimate associations between the amplitude and connectivity strength of subnetworks of three major neurocognitive networks (default mode, DMN; salience, SN; central executive networks, CEN) with accelerometer-derived measures of physical activity and self-reported mental health measures (primarily of depression, anxiety disorders, neuroticism, subjective well-being, and risk-taking behaviors). We estimated the genetic correlation between mental health and physical activity measures, as well as putative causal relationships by applying linkage disequilibrium score regression, genomic structural equational modeling, and latent causal variable analysis to genome-wide association summary statistics (GWAS N = 91,105-500,199). Physical activity and mental health were associated with connectivity strength and amplitude of the DMN, SN, and CEN (r's ≥ 0.12, p's < 0.048). These neural correlates exhibited highly similar loading patterns across mental health and physical activity models even when accounting for their shared variance. This suggests a largely shared brain network architecture between mental health and physical activity. Mental health and physical activity (including sleep) were also genetically correlated (|rg| = 0.085-0.121), but we found no evidence for causal relationships between them. Collectively, our findings provide empirical evidence that mental health and physical activity have shared brain and genetic architectures and suggest potential candidate subnetworks for future studies on brain mechanisms underlying beneficial effects of physical activity on mental health.
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47
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Yang FN, Xie W, Wang Z. Effects of sleep duration on neurocognitive development in early adolescents in the USA: a propensity score matched, longitudinal, observational study. THE LANCET. CHILD & ADOLESCENT HEALTH 2022; 6:705-712. [PMID: 35914537 PMCID: PMC9482948 DOI: 10.1016/s2352-4642(22)00188-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/24/2022] [Accepted: 05/27/2022] [Indexed: 05/07/2023]
Abstract
BACKGROUND Although the American Academy of Sleep Medicine suggests at least 9 h of sleep per day for 6-12-year-olds, children in recent generations often report sleeping less than this amount. Because early adolescence is a crucial period for neurocognitive development, we aimed to investigate how insufficient sleep affects children's mental health, cognition, brain function, and brain structure over 2 years. METHODS In this propensity score matched, longitudinal, observational cohort study, we obtained data from a population-based sample of 9-10-year-olds from 21 US study sites in the ongoing Adolescent Brain Cognitive Development (ABCD) study. Participants were categorised as having sufficient sleep or insufficient sleep on the basis of a cutoff of 9 h sleep per day. Using propensity score matching, we matched these two groups of participants on 11 key covariates, including sex, socioeconomic status, and puberty status. Participants were excluded from our analysis if they did not pass a baseline resting-state functional MRI quality check or had missing data for the covariates involved in propensity score matching. Outcome measures retrieved from the ABCD study were behavioural problems, mental health, cognition, and structural and resting-state functional brain measures, assessed at baseline and at 2-year follow-up. We examined group differences on these outcomes over those 2 years among all eligible participants. We then did mediation analyses of the neural correlates of behavioural changes induced by insufficient sleep. FINDINGS Between Sept 1, 2016, and Oct 15, 2018, 11 878 individuals had baseline data collected for the ABCD study, of whom 8323 were eligible and included in this study (4142 participants in the sufficient sleep group and 4181 in the insufficient sleep group). Follow-up data were collected from July 30, 2018, to Jan 15, 2020. We identified 3021 matched sufficient sleep-insufficient sleep pairs at baseline and 749 matched pairs at 2-year follow-up, and observed similar differences between the groups in behaviour and neural measures at both timepoints; the effect sizes of between-group differences in behavioural measures at these two timepoints were significantly correlated with each other (r=0·85, 95% CI 0·73-0·92; p<0·0001). A similar pattern was observed in resting-state functional connectivity (r=0·54, 0·45-0·61; p<0·0001) and in structural measures (eg, in grey matter volume r=0·61, 0·51-0·69; p<0·0001). We found that cortico-basal ganglia functional connections mediate the effects of insufficient sleep on depression, thought problems, and crystallised intelligence, and that structural properties of the anterior temporal lobe mediate the effect of insufficient sleep on crystallised intelligence. INTERPRETATION These results provide population-level evidence for the long-lasting effect of insufficient sleep on neurocognitive development in early adolescence. These findings highlight the value of early sleep intervention to improve early adolescents' long-term developmental outcomes. FUNDING National Institutes of Health.
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Affiliation(s)
- Fan Nils Yang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Weizhen Xie
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
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48
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Jiang R, Westwater ML, Noble S, Rosenblatt M, Dai W, Qi S, Sui J, Calhoun VD, Scheinost D. Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank. BMC Med 2022; 20:286. [PMID: 36076200 PMCID: PMC9461129 DOI: 10.1186/s12916-022-02490-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/20/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Grip strength is a widely used and well-validated measure of overall health that is increasingly understood to index risk for psychiatric illness and neurodegeneration in older adults. However, existing work has not examined how grip strength relates to a comprehensive set of mental health outcomes, which can detect early signs of cognitive decline. Furthermore, whether brain structure mediates associations between grip strength and cognition remains unknown. METHODS Based on cross-sectional and longitudinal data from over 40,000 participants in the UK Biobank, this study investigated the behavioral and neural correlates of handgrip strength using a linear mixed effect model and mediation analysis. RESULTS In cross-sectional analysis, we found that greater grip strength was associated with better cognitive functioning, higher life satisfaction, greater subjective well-being, and reduced depression and anxiety symptoms while controlling for numerous demographic, anthropometric, and socioeconomic confounders. Further, grip strength of females showed stronger associations with most behavioral outcomes than males. In longitudinal analysis, baseline grip strength was related to cognitive performance at ~9 years follow-up, while the reverse effect was much weaker. Further, baseline neuroticism, health, and financial satisfaction were longitudinally associated with subsequent grip strength. The results revealed widespread associations between stronger grip strength and increased grey matter volume, especially in subcortical regions and temporal cortices. Moreover, grey matter volume of these regions also correlated with better mental health and considerably mediated their relationship with grip strength. CONCLUSIONS Overall, using the largest population-scale neuroimaging dataset currently available, our findings provide the most well-powered characterization of interplay between grip strength, mental health, and brain structure, which may facilitate the discovery of possible interventions to mitigate cognitive decline during aging.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.
| | - Margaret L Westwater
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA
| | - Matthew Rosenblatt
- Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA
| | - Wei Dai
- Department of Biostatistics, Yale University, New Haven, CT, 06520, USA
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA
| | - Jing Sui
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, USA.
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, 06520, USA.
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA.
- Child Study Center, Yale School of Medicine, New Haven, CT, 06510, USA.
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Fucà E, Costanzo F, Ursumando L, Celestini L, Scoppola V, Mancini S, Valentini D, Villani A, Vicari S. Sleep and behavioral problems in preschool-age children with Down syndrome. Front Psychol 2022; 13:943516. [PMID: 35923741 PMCID: PMC9342601 DOI: 10.3389/fpsyg.2022.943516] [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: 05/13/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Sleep is a major concern, especially in people with Down Syndrome (DS). Beyond Obstructive Sleep Apnea, a number of other sleep difficulties have been reported in children with DS, such as delayed sleep onset, night-time awakenings, and early morning awakenings. The detrimental effect of sleep difficulties seems to contribute to and exacerbate the cognitive and behavioral outcomes of DS. Although the screening for sleep disorders is recommended early in age in DS, only a few studies have evaluated the sleep profile in preschool-age children with DS. The aim of the current study was to assess the association between sleep disturbances and behavioral problems in a group of preschool-age children with DS, by means of a feasible and easy-to-administer parent-report questionnaires. Seventy-one preschool-age children with DS, ranging in age from 3 to 5.11 years, were included in this retrospective study. Sleep disturbances were evaluated by means of the Sleep Disturbance Scale for Children, while emotional and behavioral problems by means of the Child Behavior Checklist. Sleep breathing disorders were the most frequent sleep difficulties reported by parents. Moreover, children with clinical scores in total sleep problems exhibited elevation of psychopathological symptoms, namely Total problems, Affective problems, Anxiety problems, Pervasive Developmental Problems, and Attention Deficit/Hyperactivity Problems. The identification of the broader connection between sleep difficulties and emotional and behavioral problems in preschool-age children with DS leads to important considerations for intervention.
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Affiliation(s)
- Elisa Fucà
- Child and Adolescent Neuropsychiatry Unit, Department of Neuroscience, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Floriana Costanzo
- Child and Adolescent Neuropsychiatry Unit, Department of Neuroscience, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
- *Correspondence: Floriana Costanzo,
| | - Luciana Ursumando
- Child and Adolescent Neuropsychiatry Unit, Department of Neuroscience, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
| | - Laura Celestini
- Pediatric Unit, Department of Pediatric Emergency (DEA), Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | | | - Silvia Mancini
- Department of Human Sciences, European University of Rome, Rome, Italy
| | - Diletta Valentini
- Pediatric Unit, Department of Pediatric Emergency (DEA), Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Alberto Villani
- Pediatric Unit, Department of Pediatric Emergency (DEA), Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Stefano Vicari
- Child and Adolescent Neuropsychiatry Unit, Department of Neuroscience, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
- Department of Life Science and Public Health, Catholic University of the Sacred Heart, Rome, Italy
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50
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Kristanto D, Liu X, Sommer W, Hildebrandt A, Zhou C. What do neuroanatomical networks reveal about the ontology of human cognitive abilities? iScience 2022; 25:104706. [PMID: 35865139 PMCID: PMC9293763 DOI: 10.1016/j.isci.2022.104706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 05/15/2022] [Accepted: 06/28/2022] [Indexed: 11/18/2022] Open
Abstract
Over the last decades, cognitive psychology has come to a fair consensus about the human intelligence ontological structure. However, it remains an open question whether anatomical properties of the brain support the same ontology. The present study explored the ontological structure derived from neuroanatomical networks associated with performance on 15 cognitive tasks indicating various abilities. Results suggest that the brain-derived (neurometric) ontology partly agrees with the cognitive performance-derived (psychometric) ontology complemented with interpretable differences. Moreover, the cortical areas associated with different inferred abilities are segregated, with little or no overlap. Nevertheless, these spatially segregated cortical areas are integrated via denser white matter structural connections as compared with the general brain connectome. The integration of ability-related cortical networks constitutes a neural counterpart to the psychometric construct of general intelligence, while the consistency and difference between psychometric and neurometric ontologies represent crucial pieces of knowledge for theory building, clinical diagnostics, and treatment. Psychometric and neurometric cognitive ontologies are partly equivalent Ability-related brain areas are ontologically segregated with little to no overlap However, ability-related brain areas are densely interconnected by fiber tracts
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