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Li T, Chen J, Zhao B, Chen H, Yuan C, Garden GA, Giovanello KS, Wu G, Zhu H. The Interaction Effects of Age, Sex, APOE and Common Health Risk Factors on Human Brain Functions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.05.24311482. [PMID: 39148839 PMCID: PMC11326347 DOI: 10.1101/2024.08.05.24311482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Recent studies have shed light on the complex nonlinear changes in brain functions across the lifespan, demonstrating the variability in the individual cognitive and neural development during aging. This variability is influenced by factors such as sex, age, genetics, and modifiable health risk factors (MHRFs), which collectively shape unique patterns of brain functional connectivities (FCs) across different regions. However, their joint effects and underlying mechanisms remain unclear. We conduct a comprehensive analysis to jointly examine the association of common risk factors with brain functional measures, using data from 36,630 UK Biobank participants aged 44-81. Participants were assessed for age, sex, Apolipoprotein E ( APOE ) genotypes, ten common MHRFs, and brain FCs measured via resting-state functional magnetic resonance imaging. Using the fine-grained HCP-MMP parcellation and Ji-12 network atlases, we identified 91 associations with network functional connectivity (NFC) and 102 associations with network edge strength (NES) measures. Hypertension, BMI, and education emerged as the top three influential factors across networks. Notably, a negative interaction between sex and APOE-ε4 ( APOE4 ) genotype was observed, with male APOE4 carriers showing greater reductions in NFC between the cingulo- opercular (CON) and posterior multimodal (PMN) networks. Additionally, a negative age-BMI interaction on NES between the visual and dorsal attention (DAN) networks suggested that higher BMI accelerates the decline in visual-DAN connectivity. A positive age-hypertension interaction between the frontoparietal (FPN) and default mode (DMN) networks indicated a more rapid decrease in functional segregation associated with hypertension. We also identified sex- education interactions, showing more pronounced positive effects on CON-FPN networks in females and PMN-DMN networks in males. Further interactions involving sex and other MHRFs, such as smoking, alcohol consumption, diabetes, and BMI, revealed that smoking, alcohol, and BMI had more detrimental effects in males, while diabetes had a more pronounced negative impact in females within specific networks. These findings underscore the necessity of jointly considering sex, age, genetic factors, and MHRFs to accurately delineate the multifactorial alterations in the FCs during brain aging.
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Wang B, Fan Y, Wang X, Zeng X, Zeng S, Jia H, Li Y, Dai C. Influence of lifestyle patterns on depression among adults with diabetes: a mediation effect of dietary inflammatory index. BMC Public Health 2024; 24:1779. [PMID: 38961392 PMCID: PMC11223315 DOI: 10.1186/s12889-024-19319-7] [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: 06/01/2024] [Accepted: 07/01/2024] [Indexed: 07/05/2024] Open
Abstract
BACKGROUND Lifestyle has become a crucial modulator in the management of diabetes and is intimately linked with the development and exacerbation of comorbid depression. The study aimed to analyze lifestyle patterns and their impact on depression in individuals with diabetes and to explore the role of the Dietary Inflammatory Index (DII) in the relationship between lifestyle patterns and depression. METHODS Data was attained from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2020. A latent class analysis (LCA) was performed on 3,009 diabetic adults based on lifestyle behaviors. A generalised linear model (GLM) was employed to analyse the effects of different lifestyle patterns on depression. The mediation effect model was utilised to examine the relationship between lifestyle patterns, DII and Patient Health Questionnaire-9 (PHQ-9) scores. RESULTS The cohort was divided through LCA into unhealthy lifestyle (44.53%), unhealthy but non-alcohol use (48.06%) and healthy but smoking (7.41%) groups of lifestyle behaviors, the unhealthy but non-alcohol use group was identified as a risk factor for depression (OR = 1.379, 95%CI = 1.095 ~ 1.735, P = 0.006). The DII partially mediated the relationship between the unhealthy but non-alcohol use group and PHQ-9, and fully mediated the relationship between the healthy but smoking group and PHQ-9, with effect coefficients of - 0.018 (95%CI: -0.044 ~ - 0.001) and - 0.035 (95%CI: -0.083 ~ - 0.001). CONCLUSIONS Lifestyle patterns significantly influence the occurrence of depression among diabetes patients. The dietary inflammation plays a varying mediating role between different lifestyle patterns and depression. Restricting pro-inflammatory diets or encouraging anti-inflammatory diets, combined with the promotion of healthy lifestyle practices, may be an effective method for preventing and alleviating symptoms of depression among patients with diabetes.
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Affiliation(s)
- Baoping Wang
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yuxin Fan
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Xin Wang
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Xiangru Zeng
- Department of Endocrinology, Tianjin Dongli Hospital, Tianjin, 300300, China
| | - Sha Zeng
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital Airport Hospital, Tianjin, 300000, China
| | - Hongwei Jia
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yin Li
- Dept. Maternal, Child and Adolescent Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Chenlin Dai
- Department of Endocrinology and Metabolism, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
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Li Y, Yang L, Hao D, Chen Y, Ye-Lin Y, Li CSR, Li G. Functional Networks of Reward and Punishment Processing and Their Molecular Profiles Predicting the Severity of Young Adult Drinking. Brain Sci 2024; 14:610. [PMID: 38928610 PMCID: PMC11201596 DOI: 10.3390/brainsci14060610] [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: 05/02/2024] [Revised: 06/15/2024] [Accepted: 06/16/2024] [Indexed: 06/28/2024] Open
Abstract
Alcohol misuse is associated with altered punishment and reward processing. Here, we investigated neural network responses to reward and punishment and the molecular profiles of the connectivity features predicting alcohol use severity in young adults. We curated the Human Connectome Project data and employed connectome-based predictive modeling (CPM) to examine how functional connectivity (FC) features during wins and losses are associated with alcohol use severity, quantified by Semi-Structured Assessment for the Genetics of Alcoholism, in 981 young adults. We combined the CPM findings and the JuSpace toolbox to characterize the molecular profiles of the network connectivity features of alcohol use severity. The connectomics predicting alcohol use severity appeared specific, comprising less than 0.12% of all features, including medial frontal, motor/sensory, and cerebellum/brainstem networks during punishment processing and medial frontal, fronto-parietal, and motor/sensory networks during reward processing. Spatial correlation analyses showed that these networks were associated predominantly with serotonergic and GABAa signaling. To conclude, a distinct pattern of network connectivity predicted alcohol use severity in young adult drinkers. These "neural fingerprints" elucidate how alcohol misuse impacts the brain and provide evidence of new targets for future intervention.
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Affiliation(s)
- Yashuang Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
| | - Lin Yang
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
| | - Dongmei Hao
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
| | - Yu Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA (C.-S.R.L.)
| | - Yiyao Ye-Lin
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022 Valencia, Spain
| | - Chiang-Shan Ray Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, USA (C.-S.R.L.)
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06511, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06511, USA
| | - Guangfei Li
- Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, 100 Pingleyuan, Beijing 100124, China; (Y.L.)
- Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing 100124, China
- BJUT-UPV Joint Research Laboratory in Biomedical Engineering, 46022 Valencia, Spain
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Wang K, Fu Y, Li L, Zhang L, Huang M, Yan W, Shan X, Yan Z, Lu Y. Gut Microbiota Moderates Multimodal Brain Structure-Function Integration and Behavioral Cognition in Growth Hormone Deficient Children. Neuroendocrinology 2024; 114:698-708. [PMID: 38679006 DOI: 10.1159/000539097] [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: 01/30/2024] [Accepted: 04/23/2024] [Indexed: 05/01/2024]
Abstract
INTRODUCTION Previous brain studies of growth hormone deficiency (GHD) often used single-modal neuroimaging, missing the complexity captured by multimodal data. Growth hormone affects gut microbiota and metabolism in GHD. However, from a gut-brain axis (GBA) perspective, the relationship between abnormal GHD brain development and microbiota alterations remains unclear. The ultimate goal is to uncover the manifestations underlying GBA abnormalities in GHD and idiopathic short stature (ISS). METHODS Participants included 23 GHD and 25 ISS children. The fusion independent component analysis was applied to integrate multimodal brain data (high-resolution structural, diffusion tensor, and resting-state functional MRI) covering regional homogeneity (ReHo), amplitude of low frequency fluctuations (ALFF), and white matter fractional anisotropy (FA). Gut microbiome diversity and metabolites were analyzed using 16S sequencing and proton nuclear magnetic resonance (1H-NMR). Associations between multimodal neuroimaging and cognition were assessed using moderation analysis. RESULTS Six independent components (IC) of ReHo, ALFF, and FA differed significantly between GHD and ISS patients, with three functional components linked to the processing speed index. GHD individuals showed higher levels of acetate, nicotinate, and lysine in microbiota metabolism. Higher alpha diversity in GHD strengthened connections between ReHo-IC1, ReHo-IC5, ALFF-IC1, and the processing speed index, while increasing agathobacter levels in ISS weakened the link between ALFF-IC1 and the speech comprehension index. CONCLUSIONS Our findings uncover differing brain structure and functional fusion in GHD, alongside microbiota metabolism of short-chain fatty acids. Additionally, microbiome influences connections between neuroimaging and cognition, offering insight into diverse GBA patterns in GHD and ISS, enhancing our understanding of the disease's pathophysiology and interventions.
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Affiliation(s)
- Keren Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yuchuan Fu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lan Li
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lingfeng Zhang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Mei Huang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Weihao Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaoou Shan
- Department of Pediatric Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
- Key Laboratory of Structural Malformations in Children of Zhejiang Province, Wenzhou, China
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, China
| | - Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
- Key Laboratory of Structural Malformations in Children of Zhejiang Province, Wenzhou, China
- Wenzhou Key Laboratory of Structural and Functional Imaging, Wenzhou, China
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Zhang R, Yan W, Manza P, Shokri-Kojori E, Demiral SB, Schwandt M, Vines L, Sotelo D, Tomasi D, Giddens NT, Wang GJ, Diazgranados N, Momenan R, Volkow ND. Disrupted brain state dynamics in opioid and alcohol use disorder: attenuation by nicotine use. Neuropsychopharmacology 2024; 49:876-884. [PMID: 37935861 PMCID: PMC10948795 DOI: 10.1038/s41386-023-01750-w] [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: 07/06/2023] [Revised: 09/10/2023] [Accepted: 09/29/2023] [Indexed: 11/09/2023]
Abstract
Substance use disorder (SUD) is a chronic relapsing disorder with long-lasting changes in brain intrinsic networks. While most research to date has focused on static functional connectivity, less is known about the effect of chronic drug use on dynamics of brain networks. Here we investigated brain state dynamics in individuals with opioid use (OUD) and alcohol use disorder (AUD) and assessed how concomitant nicotine use, which is frequent among individuals with OUD and AUD, affects brain dynamics. Resting-state functional magnetic resonance imaging data of 27 OUD, 107 AUD, and 137 healthy participants were included in the analyses. To identify recurrent brain states and their dynamics, we applied a data-driven clustering approach that determines brain states at a single time frame. We found that OUD and AUD non-smokers displayed similar changes in brain state dynamics including decreased fractional occupancy or dwell time in default mode network (DMN)-dominated brain states and increased appearance rate in visual network (VIS)-dominated brain states, which were also reflected in transition probabilities of related brain states. Interestingly, co-use of nicotine affected brain states in an opposite manner by lowering VIS-dominated and enhancing DMN-dominated brain states in both OUD and AUD participants. Our finding revealed a similar pattern of brain state dynamics in OUD and AUD participants that differed from controls, with an opposite effect for nicotine use suggesting distinct effects of various drugs on brain state dynamics. Different strategies for treating SUD may need to be implemented based on patterns of co-morbid drug use.
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Affiliation(s)
- Rui Zhang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Weizheng Yan
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Peter Manza
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Ehsan Shokri-Kojori
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Sukru Baris Demiral
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Melanie Schwandt
- Office of Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892-1108, USA
| | - Leah Vines
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Diana Sotelo
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Dardo Tomasi
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Natasha T Giddens
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
- Department of Psychiatry, University of Wisconsin, Madison, WI, USA
| | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Nancy Diazgranados
- Office of Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892-1108, USA
| | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892-1108, USA
| | - Nora D Volkow
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA.
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Frie JA, McCunn P, Eed A, Hassan A, Luciani KR, Chen C, Tyndale RF, Khokhar JY. Factors influencing JUUL e-cigarette nicotine vapour-induced reward, withdrawal, pharmacokinetics and brain connectivity in rats: sex matters. Neuropsychopharmacology 2024; 49:782-795. [PMID: 38057369 PMCID: PMC10948865 DOI: 10.1038/s41386-023-01773-3] [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: 05/21/2023] [Revised: 11/05/2023] [Accepted: 11/14/2023] [Indexed: 12/08/2023]
Abstract
Though vaping likely represents a safer alternative to smoking, it is not without risks, many of which are not well understood, especially for vulnerable populations. Here we evaluate the sex- and age-dependent effects of JUUL nicotine vapour in rats. Following passive nicotine vapour exposures (from 59 mg/ml JUUL nicotine pods), rats were evaluated for reward-like behaviour, locomotion, and precipitated withdrawal. Pharmacokinetics of nicotine and its metabolites in brain and plasma and the long-term impact of nicotine vapour exposure on functional magnetic resonance imaging-based brain connectivity were assessed. Adult female rats acquired conditioned place preference (CPP) at a high dose (600 s of exposure) of nicotine vapour while female adolescents, as well as male adults and adolescents did not. Adult and adolescent male rats displayed nicotine vapour-induced precipitated withdrawal and hyperlocomotion, while both adult and adolescent female rats did not. Adult females showed higher venous and arterial plasma and brain nicotine and nicotine metabolite concentrations compared to adult males and adolescent females. Adolescent females showed higher brain nicotine concentration compared to adolescent males. Both network-based statistics and between-component group connectivity analyses uncovered reduced connectivity in nicotine-exposed rats, with a significant group by sex interaction observed in both analyses. The short- and long-term effects of nicotine vapour are affected by sex and age, with distinct behavioural, pharmacokinetic, and altered network connectivity outcomes dependent on these variables.
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Affiliation(s)
- Jude A Frie
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Patrick McCunn
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Amr Eed
- Department of Medical Biophysics and Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Ahmad Hassan
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Karling R Luciani
- Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Chuyun Chen
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Rachel F Tyndale
- Departments of Psychiatry, and Pharmacology & Toxicology, University of Toronto, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Jibran Y Khokhar
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
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Lee PH, Tervo-Clemmens B, Liu RT, Gersten MB, Jung JY, Janes AC, Gilman J. Use of Tobacco Products and Suicide Attempts Among Elementary School-Aged Children. JAMA Netw Open 2024; 7:e240376. [PMID: 38407905 PMCID: PMC10897745 DOI: 10.1001/jamanetworkopen.2024.0376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/27/2024] Open
Abstract
Importance The use of tobacco products, including e-cigarettes and vaping, has rapidly increased among children. However, despite consistent associations found between smoking cigarettes and suicidal behaviors among adolescents and adults, there are limited data on associations between emerging tobacco products and suicidal behaviors, especially among preadolescent children. Objective To examine whether the use of tobacco products is associated with nonsuicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SAs) among preadolescent children. Design, Setting, and Participants This cohort study, conducted from September 1, 2022, to September 5, 2023, included participants in the Adolescent Brain Cognitive Development study, a population-based cohort of 11 868 US children enrolled at 9 and 10 years of age. The cross-sectional investigation focused on 3-year periods starting from the baseline to year 2 of follow-up. Statistical analysis was performed from October 1, 2022, to June 30, 2023. Main Outcomes and Measures Children's use of tobacco products was assessed based on youth reports, including lifetime experiences of various nicotine-related products, supplemented with hair toxicologic tests. Main outcomes were children's lifetime experiences of NSSI, SI, and SAs, assessed using the K-SADS-5 (Kiddie Schedule for Affective Disorders and Schizophrenia for the DSM-5). Multivariate logistic regression was conducted to examine the associations of the use of tobacco products with NSSI, SI, and SAs among the study participants. Sociodemographic, familial, and children's behavioral, temperamental, and clinical outcomes were adjusted in the analyses. Results Of 8988 unrelated study participants (median age, 9.8 years [range, 8.9-11.0 years]; 4301 girls [47.9%]), 101 children (1.1%) and 151 children (1.7%) acknowledged lifetime use of tobacco products at baseline and at 18-month follow-up, respectively. After accounting for various suicide risk factors and potential confounders, children reporting use of tobacco products were at a 3 to 5 times increased risk of SAs (baseline: n = 153 [adjusted odds ratio (OR), 4.67; 95% CI, 2.35-9.28; false discovery rate (FDR)-corrected P < .001]; year 1: n = 227 [adjusted OR, 4.25; 95% CI, 2.33-7.74; FDR-corrected P < .001]; and year 2: n = 321 [adjusted OR, 2.85; 95% CI, 1.58-5.13; FDR-corrected P = .001]). Of all facets of impulsivity measures that were significant correlates of use of tobacco products, negative urgency was the only independent risk factor for SAs (adjusted OR, 1.52 [95% CI, 1.31-1.78]; FDR-corrected P < .001). In contrast, children's alcohol, cannabis, and prescription drug use were not associated with SAs. Conclusions and Relevance This study of US children suggests that the increased risk of SAs, consistently reported for adolescents and adults who smoke cigarettes, extends to a range of emerging tobacco products and manifests among elementary school-aged children. Further investigations are imperative to clarify the underlying mechanisms and to implement effective preventive policies for children.
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Affiliation(s)
- Phil H Lee
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston
- Center for Genomic Medicine, Massachusetts General Hospital, Boston
| | - Brenden Tervo-Clemmens
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis
- Center for Addiction Medicine, Massachusetts General Hospital, Boston
| | - Richard T Liu
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston
- Depression Clinical and Research Program, Massachusetts General Hospital, Boston
| | - Maia B Gersten
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston
- Division of Neuropsychiatry, Massachusetts General Hospital, Boston
| | - Jae-Yoon Jung
- Department of Pediatrics, Stanford University, Stanford, California
| | - Amy C Janes
- Cognitive and Pharmacological Neuroimaging Unit, National Institute on Drug Abuse, Biomedical Research Center, Baltimore, Maryland
| | - Jodi Gilman
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston
- Center for Addiction Medicine, Massachusetts General Hospital, Boston
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Jordan T, Apostol MR, Nomi J, Petersen N. Unraveling Neural Complexity: Exploring Brain Entropy to Yield Mechanistic Insight in Neuromodulation Therapies for Tobacco Use Disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.12.557465. [PMID: 37745351 PMCID: PMC10515846 DOI: 10.1101/2023.09.12.557465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Neuromodulation therapies, such as repetitive transcranial magnetic stimulation (rTMS), have shown promise as treatments for tobacco use disorder (TUD). However, the underlying mechanisms of these therapies remain unclear, which may hamper optimization and personalization efforts. In this study, we investigated alteration of brain entropy as a potential mechanism underlying the neural effects of noninvasive brain stimulation by rTMS in people with TUD. We employed sample entropy (SampEn) to quantify the complexity and predictability of brain activity measured using resting-state fMRI data. Our study design included a randomized single-blind study with 42 participants who underwent 2 data collection sessions. During each session, participants received high-frequency (10Hz) stimulation to the dorsolateral prefrontal cortex (dlPFC) or a control region (visual cortex), and resting-state fMRI scans were acquired before and after rTMS. Our findings revealed that individuals who smoke exhibited higher baseline SampEn throughout the brain as compared to previously-published SampEn measurements in control participants. Furthermore, high-frequency rTMS to the dlPFC but not the control region reduced SampEn in the insula and dlPFC, regions implicated in TUD, and also reduced self-reported cigarette craving. These results suggest that brain entropy may serve as a potential biomarker for effects of rTMS, and provide insight into the neural mechanisms underlying rTMS effects on smoking cessation. Our study contributes to the growing understanding of brain-based interventions for TUD by highlighting the relevance of brain entropy in characterizing neural activity patterns associated with smoking. The observed reductions in entropy following dlPFC-targeted rTMS suggest a potential mechanism for the therapeutic effects of this intervention. These findings support the use of neuroimaging techniques to investigate the use of neuromodulation therapies for TUD.
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Affiliation(s)
- Timothy Jordan
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Michael R. Apostol
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Jason Nomi
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
| | - Nicole Petersen
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles CA
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Upton S, Brown AA, Golzy M, Garland EL, Froeliger B. Right inferior frontal gyrus theta-burst stimulation reduces smoking behaviors and strengthens fronto-striatal-limbic resting-state functional connectivity: a randomized crossover trial. Front Psychiatry 2023; 14:1166912. [PMID: 37457779 PMCID: PMC10338839 DOI: 10.3389/fpsyt.2023.1166912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/22/2023] [Indexed: 07/18/2023] Open
Abstract
Introduction Functional and anatomical irregularities in the right inferior frontal gyrus (rIFG), a ventrolateral prefrontal region that mediates top-down inhibitory control over prepotent behavioral responding, are implicated in the ongoing maintenance of nicotine dependence (ND). However, there is little research on the effects of neuromodulation of the rIFG on smoking behavior, inhibitory control, and resting-state functional connectivity (rsFC) among individuals with ND. Methods In this double-blind, crossover, theta-burst stimulation (TBS) study, adults with ND (N = 31; female: n = 15) completed a baseline session and were then randomized to two counterbalanced sessions of functionally neuronavigated TBS to the rIFG: continuous TBS (cTBS) on 1 day and intermittent TBS (iTBS) on another. Differences in cigarette cravings, smoking, and fronto-striatal-limbic rsFC were assessed. Results Relative to baseline, cTBS significantly reduced appetitive and withdrawal cravings immediately after treatment. The effects of cTBS on withdrawal craving persisted for 24 h, as well as produced a reduction in smoking. Furthermore, cTBS significantly strengthened rsFC between the rIFG pars opercularis and subcallosal cingulate (fronto-striatal circuit), and between the rIFG pars opercularis and the right posterior parahippocampal gyrus (fronto-limbic circuit). At post-24 h, cTBS-induced increase in fronto-striatal rsFC was significantly associated with less appetitive craving, while the increase in fronto-limbic rsFC was significantly associated with less withdrawal craving and smoking. Discussion These findings warrant further investigation into the potential value of rIFG cTBS to attenuate smoking behavior among individuals with ND.
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Affiliation(s)
- Spencer Upton
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
| | - Alexander A. Brown
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
- Department of Psychiatry, School of Medicine, University of Missouri, Columbia, MO, United States
- Cognitive Neuroscience Systems Core Facility, University of Missouri, Columbia, MO, United States
| | - Mojgan Golzy
- Biostatistics Unit, Department of Family and Community Medicine, School of Medicine, University of Missouri, Columbia, MO, United States
| | - Eric L. Garland
- Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City, UT, United States
| | - Brett Froeliger
- Department of Psychological Sciences, University of Missouri, Columbia, MO, United States
- Department of Psychiatry, School of Medicine, University of Missouri, Columbia, MO, United States
- Cognitive Neuroscience Systems Core Facility, University of Missouri, Columbia, MO, United States
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10
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Lorenzetti V, Gaillard A, Beyer E, Kowalczyk M, Kamboj SK, Manning V, Gleeson J. Do mindfulness-based interventions change brain function in people with substance dependence? A systematic review of the fMRI evidence. BMC Psychiatry 2023; 23:407. [PMID: 37286936 DOI: 10.1186/s12888-023-04789-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 04/14/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Substance use disorders (SUDs) affect ~ 35 million people globally and are associated with strong cravings, stress, and brain alterations. Mindfulness-based interventions (MBIs) can mitigate the adverse psychosocial outcomes of SUDs, but the underlying neurobiology is unclear. Emerging findings were systematically synthesised from fMRI studies about MBI-associated changes in brain function in SUDs and their associations with mindfulness, drug quantity, and craving. METHODS PsycINFO, Medline, CINAHL, PubMed, Scopus, and Web of Science were searched. Seven studies met inclusion criteria. RESULTS Group by time effects indicated that MBIs in SUDs (6 tobacco and 1 opioid) were associated with changes in the function of brain pathways implicated in mindfulness and addiction (e.g., anterior cingulate cortex and striatum), which correlated with greater mindfulness, lower craving and drug quantity. CONCLUSIONS The evidence for fMRI-related changes with MBI in SUD is currently limited. More fMRI studies are required to identify how MBIs mitigate and facilitate recovery from aberrant brain functioning in SUDs.
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Affiliation(s)
- Valentina Lorenzetti
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Level 5 Daniel Mannix Building, 115 Victoria Parade, Fitzroy, VIC, 3065, Australia.
| | - Alexandra Gaillard
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Level 5 Daniel Mannix Building, 115 Victoria Parade, Fitzroy, VIC, 3065, Australia
- Centre for Mental Health, Swinburne University of Technology, Hawthorn, Australia
| | - Emillie Beyer
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Level 5 Daniel Mannix Building, 115 Victoria Parade, Fitzroy, VIC, 3065, Australia
| | - Magdalena Kowalczyk
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Level 5 Daniel Mannix Building, 115 Victoria Parade, Fitzroy, VIC, 3065, Australia
| | - Sunjeev K Kamboj
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Victoria Manning
- Monash Addiction Research Centre, Eastern Health Clinical School, Monash University, Melbourne, Australia
- Turning Point, Eastern Health, Monash University, Melbourne, Australia
| | - John Gleeson
- Digital Innovations in Mental Health and Well-being Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
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Carrette LLG, Kimbrough A, Davoudian PA, Kwan AC, Collazo A, George O. Hyperconnectivity of Two Separate Long-Range Cholinergic Systems Contributes to the Reorganization of the Brain Functional Connectivity during Nicotine Withdrawal in Male Mice. eNeuro 2023; 10:ENEURO.0019-23.2023. [PMID: 37295945 PMCID: PMC10306126 DOI: 10.1523/eneuro.0019-23.2023] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/13/2023] [Accepted: 04/25/2023] [Indexed: 06/12/2023] Open
Abstract
Chronic nicotine results in dependence with withdrawal symptoms on discontinuation of use, through desensitization of nicotinic acetylcholine receptors and altered cholinergic neurotransmission. Nicotine withdrawal is associated with increased whole-brain functional connectivity and decreased network modularity; however, the role of cholinergic neurons in those changes is unknown. To identify the contribution of nicotinic receptors and cholinergic regions to changes in the functional network, we analyzed the contribution of the main cholinergic regions to brain-wide activation of the immediate early-gene Fos during withdrawal in male mice and correlated these changes with the expression of nicotinic receptor mRNA throughout the brain. We show that the main functional connectivity modules included the main long-range cholinergic regions, which were highly synchronized with the rest of the brain. However, despite this hyperconnectivity, they were organized into two anticorrelated networks that were separated into basal forebrain-projecting and brainstem-thalamic-projecting cholinergic regions, validating a long-standing hypothesis of the organization of the brain cholinergic systems. Moreover, baseline (without nicotine) expression of Chrna2, Chrna3, Chrna10, and Chrnd mRNA of each brain region correlated with withdrawal-induced changes in Fos expression. Finally, by mining the Allen Brain mRNA expression database, we were able to identify 1755 gene candidates and three pathways (Sox2-Oct4-Nanog, JAK-STAT, and MeCP2-GABA) that may contribute to nicotine withdrawal-induced Fos expression. These results identify the dual contribution of the basal forebrain and brainstem-thalamic cholinergic systems to whole-brain functional connectivity during withdrawal; and identify nicotinic receptors and novel cellular pathways that may be critical for the transition to nicotine dependence.
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Affiliation(s)
| | - Adam Kimbrough
- Department of Psychiatry, UC San Diego, California 92093
| | - Pasha A Davoudian
- Medical Scientist Training Program, Yale University School of Medicine, New Haven, Connecticut 06511
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, Connecticut 06511
| | - Alex C Kwan
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14853
| | - Andres Collazo
- Beckman Institute, California Institute of Technology, Pasadena, California 91125
| | - Olivier George
- Department of Psychiatry, UC San Diego, California 92093
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12
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Rolls ET, Feng R, Feng J. Lifestyle risks associated with brain functional connectivity and structure. Hum Brain Mapp 2023; 44:2479-2492. [PMID: 36799566 PMCID: PMC10028639 DOI: 10.1002/hbm.26225] [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: 10/05/2022] [Revised: 01/16/2023] [Accepted: 01/23/2023] [Indexed: 02/18/2023] Open
Abstract
Some lifestyle factors are related to health and brain function and structure, but the brain systems involved are incompletely understood. A general linear model was used to test the associations of the combined and separate lifestyle risk measures of alcohol use, smoking, diet, amounts of physical activity, leisure activity, and mobile phone use, with brain functional connectivity with the high resolution Human Connectome Project (HCP) atlas in 19,415 participants aged 45-78 from the UK Biobank, with replication with HCP data. Higher combined lifestyle risk scores were associated with lower functional connectivity across the whole brain, but especially of three brain systems. Low physical, and leisure and social, activity were associated with low connectivities of the somatosensory/motor cortical regions and of hippocampal memory-related regions. Low mobile phone use, perhaps indicative of poor social communication channels, was associated with low functional connectivity of brain regions in and related to the superior temporal sulcus that are involved in social behavior and face processing. Smoking was associated with lower functional connectivity of especially frontal regions involved in attention. Lower cortical thickness in some of these regions, and also lower subcortical volume of the hippocampus, amygdala, and globus pallidus, were also associated with the sum of the poor lifestyle scores. This very large scale analysis emphasizes how the lifestyle of humans relates to their brain structure and function, and provides a foundation for understanding the causalities that relate to the differences found here in the brains of different individuals.
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Affiliation(s)
- Edmund T Rolls
- Department of Computer Science, University of Warwick, Coventry, UK
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- Oxford Centre for Computational Neuroscience, Oxford, UK
| | - Ruiqing Feng
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry, UK
- 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
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13
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Carrette LL, Kimbrough A, Davoudian PA, Kwan AC, Collazo A, George O. Hyperconnectivity of two separate long-range cholinergic systems contributes to the reorganization of the brain functional connectivity during nicotine withdrawal in male mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.29.534836. [PMID: 37034602 PMCID: PMC10081261 DOI: 10.1101/2023.03.29.534836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Chronic nicotine results in dependence with withdrawal symptoms upon discontinuation of use, through desensitization of nicotinic acetylcholine receptors and altered cholinergic neurotransmission. Nicotine withdrawal is associated with increased whole-brain functional connectivity and decreased network modularity, however, the role of cholinergic neurons in those changes is unknown. To identify the contribution of nicotinic receptors and cholinergic regions to changes in the functional network, we analyzed the contribution of the main cholinergic regions to brain-wide activation of the immediate early-gene FOS during withdrawal in male mice and correlated these changes with the expression of nicotinic receptor mRNA throughout the brain. We show that the main functional connectivity modules included the main long-range cholinergic regions, which were highly synchronized with the rest of the brain. However, despite this hyperconnectivity they were organized into two anticorrelated networks that were separated into basal forebrain projecting and brainstem-thalamic projecting cholinergic regions, validating a long-standing hypothesis of the organization of the brain cholinergic systems. Moreover, baseline (without nicotine) expression of Chrna2 , Chrna3 , Chrna10 , and Chrnd mRNA of each brain region correlated with withdrawal-induced changes in FOS expression. Finally, by mining the Allen Brain mRNA expression database, we were able to identify 1755 gene candidates and three pathways (Sox2-Oct4-Nanog, JAK-STAT, and MeCP2-GABA) that may contribute to nicotine withdrawal-induced FOS expression. These results identify the dual contribution of the basal forebrain and brainstem-thalamic cholinergic systems to whole-brain functional connectivity during withdrawal; and identify nicotinic receptors and novel cellular pathways that may be critical for the transition to nicotine dependence. Significance Statement Discontinuation of nicotine use in dependent users is associated with increased whole-brain activation and functional connectivity and leads to withdrawal symptoms. Here we investigated the contribution of the nicotinic cholinergic receptors and main cholinergic projecting brain areas in the whole-brain changes associated with withdrawal. This not only allowed us to visualize and confirm the previously described duality of the cholinergic brain system using this novel methodology, but also identify nicotinic receptors together with 1751 other genes that contribute, and could thus be targets for treatments against, nicotine withdrawal and dependence.
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Affiliation(s)
| | - Adam Kimbrough
- Department of Psychiatry, UC San Diego, La Jolla, CA, 92032, United States
| | - Pasha A. Davoudian
- Medical Scientist Training Program, Yale University School of Medicine, New Haven, CT, 06511, United States
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, 06511, United States
| | - Alex C. Kwan
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, 14853, United States
| | - Andres Collazo
- Beckman Institute, CalTech, Pasadena, CA, 91125, United States
| | - Olivier George
- Department of Psychiatry, UC San Diego, La Jolla, CA, 92032, United States
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14
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Liu Q, Leng P, Gu Y, Shang X, Zhou Y, Zhang H, Zuo L, Mei G, Xiong C, Wu T, Li H. The dose-effect relationships of cigarette and alcohol consumption with depressive symptoms: a multiple-center, cross-sectional study in 5965 Chinese middle-aged and elderly men. BMC Psychiatry 2022; 22:657. [PMID: 36284280 PMCID: PMC9594935 DOI: 10.1186/s12888-022-04316-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 10/13/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Although association of depressive symptoms with cigarette or alcohol is well documented, the dose-response relationship between them is rarely studied. This study aims to evaluate dose-response relationships of cigarette and alcohol consumption with depressive symptoms in Chinese middle-aged and elderly men, providing evidence to guide cigarette and alcohol control. METHODS This multiple-center, cross-sectional study including 5965 Chinese men aged 40-79 years was conducted in 2013-2016 in China. Depressive symptoms were evaluated by Beck Depression Inventory-Short Form. History of cigarette smoking and alcohol drinking were collected with a structured questionnaire. Prevalence of depressive symptoms was compared depending on cigarette and alcohol consumption. Adjusted odds ratios (OR) and 95% confidence interval (CI) were estimated by binary logistic regression. Interpolation analysis was applied to test dose-effect relationships. RESULTS A parabolic-shaped relationship was observed between cigarette consumption and depressive symptoms. Compared to never smokers, 59.0% (OR = 1.59, 95% CI 1.30-1.94) and 29.0% (OR = 1.29, 95% CI 1.08-1.54) higher odds of depressive symptoms were observed in men smoking < 10 cigarettes/day and 10-20 cigarettes/day, whereas, similar odds of depressive symptoms among men smoking > 20 cigarettes/day (P = 0.092). An inverted J-shaped relationship was observed between alcohol consumption and depressive symptoms. Compared to never drinkers, a tendency of higher prevalence of depressive symptoms (OR = 1.16, 95% CI 0.99-1.36) was observed in men drinking < 140 g/week, and similar prevalence was observed in those drinking 140-280 g/week (P = 0.920), whereas, 29.4% (OR = 0.71, 95% CI 0.57-0.88) lower odds in men drinking > 280 g/week. CONCLUSIONS Associations of cigarette smoking and alcohol drinking with depressive symptoms differ with consumption in middle-aged and elderly men. Health-care providers should exercise great caution on depressive symptoms in conducting cigarette and alcohol control.
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Affiliation(s)
- Qian Liu
- grid.33199.310000 0004 0368 7223Center for Reproductive Medicine, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000 China ,grid.33199.310000 0004 0368 7223Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030 China
| | - Pei Leng
- grid.33199.310000 0004 0368 7223Center for Reproductive Medicine, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000 China
| | - Yiqun Gu
- grid.453135.50000 0004 1769 3691National Health and Family Planning Key Laboratory of Male Reproductive Health, National Research Institute for Family Planning, Beijing, 100000 China
| | - Xuejun Shang
- Department of Andrology, School of Medicine, Jinling Hospital, Nanjing University, Nanjing, 210093 China
| | - Yuanzhong Zhou
- grid.417409.f0000 0001 0240 6969School of Public Health, Zunyi Medical University, Zunyi, 563000 Guizhou China
| | - Huiping Zhang
- grid.33199.310000 0004 0368 7223Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030 China ,Wuhan Tongji Reproductive Medicine Hospital, Wuhan, 563000 China
| | - Liandong Zuo
- grid.413428.80000 0004 1757 8466Guangzhou Women and Children’s Medical Center, Guangzhou, 510000 China
| | - Guangan Mei
- Technical Guidance Institute of Shanxi Province Family Planning Commission, Xi’an, 710000 China
| | - Chengliang Xiong
- grid.33199.310000 0004 0368 7223Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030 China ,Wuhan Tongji Reproductive Medicine Hospital, Wuhan, 563000 China
| | - Tianpeng Wu
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
| | - Honggang Li
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. .,Wuhan Tongji Reproductive Medicine Hospital, Wuhan, 563000, China.
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15
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Tang J, Xia Y, Liu N, Li L, Zou P, Zhu P, Shan X, Lui S, Lu Y, Yan Z. Growth hormone deficiency interferes with dynamic brain networks in short children. Psychoneuroendocrinology 2022; 142:105786. [PMID: 35552090 DOI: 10.1016/j.psyneuen.2022.105786] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/10/2022] [Accepted: 04/26/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE This study aimed to explore the disparities in dynamic brain networks between children with growth hormone deficiency (GHD) and idiopathic short stature (ISS, non-growth hormone deficiency). METHODS This study enrolled 65 children with GHD and 60 sex- and age-matched children with ISS. Resting-state functional magnetic resonance imaging (rs-fMRI) was performed for all participants to obtain information on dynamic regional homogeneity (dReHo) and functional connectivity (FC) in dynamic (dFC) or static (sFC) state. The rs-fMRI metrics were subsequently compared between the GHD and ISS groups. RESULTS Compared to the ISS group, the GHD group showed significant dynamic abnormalities in intra-networks of the central executive and cerebellar networks and in inter-networks of the central executive network to attentional, sensorimotor, and visual networks, as well as cerebellar network to default mode, sensorimotor, and visual networks. In addition, FC changes in the dynamic state were different from those in the static state. CONCLUSIONS The abnormal dynamics in intra- and inter-networks involved in cognitive, emotional, and motor functions in children with GHD extend the knowledge on brain functional alterations in children with GHD as reflected by dynamic changes in macroscopic neural activity patterns. These findings may help explain how GHD leads to various behavioral and cognitive deficits in children with short stature.
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Affiliation(s)
- Jing Tang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Yikai Xia
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Naici Liu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Lan Li
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Pinfa Zou
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Pingyi Zhu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Xiaoou Shan
- Children's Department of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China.
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China.
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Chen D, Jia T, Cheng W, Cao M, Banaschewski T, Barker GJ, Bokde ALW, Bromberg U, Büchel C, Desrivières S, Flor H, Grigis A, Garavan H, Gowland PA, Heinz A, Ittermann B, Martinot JL, Paillère Martinot ML, Nees F, Orfanos DP, Paus T, Poustka L, Fröhner JH, Smolka MN, Walter H, Whelan R, Robbins TW, Sahakian BJ, Schumann G, Feng J. Brain Signatures During Reward Anticipation Predict Persistent Attention-Deficit/Hyperactivity Disorder Symptoms. J Am Acad Child Adolesc Psychiatry 2022; 61:1050-1061. [PMID: 34954028 DOI: 10.1016/j.jaac.2021.11.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 10/23/2021] [Accepted: 12/15/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Children experiencing attention-deficit/hyperactivity disorder (ADHD) symptoms may retain symptoms into adulthood, but little is known about the underlying mechanism. METHOD To identify biomarkers of persistent ADHD symptom development, we carried out whole-brain analyses of neuroimaging data during the anticipation phase of the Monetary-Incentive-Delay (MID) task in 1,368 adolescents recruited by the IMAGEN Consortium at age 14 years, whose behavioral measurements were followed up longitudinally at age 16. In particular, we focused on comparing individuals with persistent high ADHD symptoms at both ages 14 and 16 years to unaffected control individuals, but also exploring which individuals demonstrating symptom remission (with high ADHD symptoms at age 14 but much reduced at age 16). RESULTS We identified reduced activations in the medial frontal cortex and the thalamus during reward anticipation as neuro-biomarkers for persistent ADHD symptoms across time. The genetic relevance of the above findings was further supported by the associations of the polygenic risk scores of ADHD with both the persistent and control status and the activations of both brain regions. Furthermore, in an exploratory analysis, the thalamic activation might also help to distinguish persons with persistent ADHD from those remitted in both an exploratory sample (odds ratio = 9.43, p < .001) and an independent generalization sample (odds ratio = 4.64, p = .003). CONCLUSION Using a well-established and widely applied functional magnetic resonance imaging task, we have identified neural biomarkers that could discriminate ADHD symptoms that persist throughout adolescence from controls and potentially those likely to remit during adolescent development as well.
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Affiliation(s)
- Di Chen
- 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, China
| | - Tianye Jia
- 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, China; Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
| | - Wei Cheng
- 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, China
| | - Miao Cao
- 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, China
| | | | - Gareth J Barker
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | | | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | | | - Sylvane Desrivières
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Herta Flor
- Heidelberg University, Mannheim, Germany; University of Mannheim, Mannheim, Germany
| | | | | | | | | | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale (INSERM) and the Université Paris-Saclay, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale (INSERM) and the Université Paris-Saclay, Gif-sur-Yvette, France; Sorbonne Université, Paris, France
| | - Frauke Nees
- Heidelberg University, Mannheim, Germany; University Medical Centre Schleswig-Holstein, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Centre Hospitalier Universitaire Sainte -Justine, University of Montreal, Quebec, Canada
| | - Luise Poustka
- University Medical Centre Göttingen, Göttingen, Germany
| | | | | | | | | | - T W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; University of Cambridge, United Kingdom
| | - Barbara J Sahakian
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; University of Cambridge, United Kingdom
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Charité - Universitätsmedizin Berlin, Germany
| | - Jianfeng Feng
- 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, China; University of Warwick, Coventry, United Kingdom; Zhangjiang Fudan International Innovation Center, Shanghai, China
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Antón-Toro LF, Bruña R, Del Cerro-León A, Shpakivska D, Mateos-Gordo P, Porras-Truque C, García-Gómez R, Maestú F, García-Moreno LM. Electrophysiological resting-state hyperconnectivity and poorer behavioural regulation as predisposing profiles of adolescent binge drinking. Addict Biol 2022; 27:e13199. [PMID: 35754100 PMCID: PMC9286401 DOI: 10.1111/adb.13199] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/29/2022] [Accepted: 06/02/2022] [Indexed: 11/30/2022]
Abstract
Adolescent Binge Drinking (BD) has become an increasing health and social concern, with detrimental consequences for brain development and functional integrity. However, research on neurophysiological and neuropsychological traits predisposing to BD are limited at this time. In this work, we conducted a 2‐year longitudinal magnetoencephalography (MEG) study over a cohort of initially alcohol‐naïve adolescents with the purpose of exploring anomalies in resting‐state electrophysiological networks, impulsivity, sensation‐seeking, and dysexecutive behaviour able to predict future BD patterns. In a sample of 67 alcohol‐naïve adolescents (age = 14.5 ± 0.9), we measured resting‐state activity using MEG. Additionally, we evaluated their neuropsychological traits using self‐report ecological scales (BIS‐11, SSS‐V, BDEFS, BRIEF‐SR and DEX). In a second evaluation, 2 years later, we measured participant's alcohol consumption, sub‐dividing the original sample in two groups: future binge drinkers (22 individuals, age 14.6 ± 0.8; eight females) and future light/no drinkers (17 individuals, age 14.5 ± 0.8; eight females). Then, we searched for differences predating alcohol BD intake. We found abnormalities in MEG resting state, in a form of gamma band hyperconnectivity, in those adolescents who transitioned into BD years later. Furthermore, they showed higher impulsivity, dysexecutive behaviours and sensation seeking, positively correlated with functional connectivity (FC). Sensation seeking and impulsivity mainly predicted BD severity in the future, while the relationship between dysexecutive trait and FC with future BD was mediated by sensation seeking. These findings shed light to electrophysiological and neuropsychological traits of vulnerability towards alcohol consumption. We hypothesise that these differences may rely on divergent neurobiological development of inhibitory neurotransmission pathways and executive prefrontal circuits.
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Affiliation(s)
- Luis F Antón-Toro
- Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Ricardo Bruña
- Department of Radiology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Alberto Del Cerro-León
- Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Danylyna Shpakivska
- Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Patricia Mateos-Gordo
- Department of Psychobiology and Methodology in Behavioral Sciences, Complutense University of Madrid (UCM), Madrid, Spain
| | - Claudia Porras-Truque
- Department of Psychobiology and Methodology in Behavioral Sciences, Complutense University of Madrid (UCM), Madrid, Spain
| | - Raquel García-Gómez
- Department of Psychobiology and Methodology in Behavioral Sciences, Complutense University of Madrid (UCM), Madrid, Spain
| | - Fernando Maestú
- Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Luis Miguel García-Moreno
- Department of Psychobiology and Methodology in Behavioral Sciences, Complutense University of Madrid (UCM), Madrid, Spain
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18
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Mori K, Haruno M. Resting functional connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction reflects the social network size for active interactions. Hum Brain Mapp 2022; 43:2869-2879. [PMID: 35261111 PMCID: PMC9120559 DOI: 10.1002/hbm.25822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/03/2022] [Accepted: 02/16/2022] [Indexed: 11/08/2022] Open
Abstract
The size of an individual active social network is a key parameter of human social behavior and is correlated with subjective well-being. However, it remains unknown how the social network size of active interactions is represented in the brain. Here, we examined whether resting-state functional magnetic resonance imaging (fMRI) connectivity is associated with the social network size of active interactions using behavioral data of a large sample (N = 222) on Twitter. Region of interest (ROI)-to-ROI analysis, graph theory analysis, seed-based analysis, and decoding analysis together provided compelling evidence that people who have a large social network size of active interactions, as measured by "reply," show higher fMRI connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction, which represents the core of the theory of mind network. These results demonstrated that people who have a large social network size of active interactions maintain activity of the identified functional connectivity in daily life, possibly providing a mechanism for efficient information transmission between the brain networks related to language and theory-of-mind.
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Affiliation(s)
- Kazuma Mori
- Center for Information and Neural Networks, National Institute of Information and Communications Technology (NICT), Suita, Osaka, Japan.,Graduate School of Information Science and Technology, Osaka University, Suita, Osaka, Japan
| | - Masahiko Haruno
- Center for Information and Neural Networks, National Institute of Information and Communications Technology (NICT), Suita, Osaka, Japan.,Grauduate School of Frontier Biosciences, Osaka University, Suita, Osaka, Japan
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19
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Rolls ET, Wan Z, Cheng W, Feng J. Risk-taking in humans and the medial orbitofrontal cortex reward system. Neuroimage 2022; 249:118893. [PMID: 35007715 DOI: 10.1016/j.neuroimage.2022.118893] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/28/2021] [Accepted: 01/06/2022] [Indexed: 11/29/2022] Open
Abstract
Risk-taking differs between humans, and is associated with the personality measures of impulsivity and sensation-seeking. To analyse the brain systems involved, self-report risk-taking, resting state functional connectivity, and related behavioral measures were analyzed in 18,740 participants of both sexes from the UK Biobank. Functional connectivities of the medial orbitofrontal cortex, ventromedial prefrontal cortex (VMPFC), and the parahippocampal areas were significantly higher in the risk-taking group (p < 0.001, FDR corrected). The risk-taking measure was validated in that it was significantly associated with alcohol drinking amount (r = 0.08, p = 5.1×10-28), cannabis use (r = 0.12, p = 6.0×10-66), and anxious feelings (r = -0.12, p = 7.6×-98). The functional connectivity findings were cross-validated in two independent datasets. The higher functional connectivity of the medial orbitofrontal cortex and VMPFC included higher connectivity with the anterior cingulate cortex, which provides a route for these reward-related regions to have a greater influence on action in risk-taking individuals. In conclusion, the medial orbitofrontal cortex, which is involved in reward value and pleasure, was found to be related to risk-taking, which is associated with impulsivity. An implication is that risk-taking is driven by specific orbitofrontal cortex reward systems, and is different for different rewards which are represented differently in the brains of different individuals. This is an advance in understanding the bases and mechanisms of risk-taking in humans, given that the orbitofrontal cortex, VMPFC and anterior cingulate cortex are highly developed in humans, and that risk-taking can be reported in humans.
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Affiliation(s)
- Edmund T Rolls
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Oxford Centre for Computational Neuroscience, Oxford, UK.
| | - Zhuo Wan
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
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20
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Wen M, Yang Z, Wei Y, Huang H, Zheng R, Wang W, Gao X, Zhang M, Fang K, Zhang Y, Cheng J, Han S. More than just statics: Temporal dynamic changes of intrinsic brain activity in cigarette smoking. Addict Biol 2021; 26:e13050. [PMID: 34085358 DOI: 10.1111/adb.13050] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 03/30/2021] [Accepted: 04/27/2021] [Indexed: 01/15/2023]
Abstract
Smoking is companied with altered intrinsic activity of the brain measured by amplitude of low-frequency fluctuation. Evidence has revealed that human brain activity is a highly dynamic and rapidly changing system. How exactly cigarette smoking affect temporal dynamic intrinsic brain activity is not fully understood nor is it clear how smoking severity influences spontaneous brain activity. Dynamic amplitude of low-frequency fluctuation (dALFF) was used to examine the dynamic temporal variability in 93 participants (63 smokers, 30 nonsmokers). We further divided smokers into light and heavy smokers. The temporal variability in intrinsic brain activity among these groups was compared. Correlation analyses were performed between dALFF in areas showing group differences and smoking behaviour (e.g., the Fagerström Test for Nicotine Dependence [FTND] scores and pack-years). Smokers showed significantly increased dALFF in the left inferior/middle frontal gyrus, right orbitofrontal gyrus, right insula, left superior/medial frontal gyrus and right middle frontal gyrus than nonsmokers. Light smokers showed increased dALFF variability in the left prefrontal cortex. Heavy smokers showed increased dynamics in specific brain regions, including the right postcentral gyrus, right insula and left precentral gyrus. Furthermore, the temporal variability in dALFF in the left superior/medial frontal gyrus, left superior/middle frontal gyrus, right middle frontal gyrus and right insula was positively correlated with pack-years or FTND. Combined, these results suggest that smokers increase stable and persistent spontaneous brain activity in prefrontal cortex, involved impaired gold-directed action and value-based decision-making. In addition, individuals with heavier smoking severity show increased perturbance on spontaneous brain activity of perception and sensorimotor, related to increased reliance.
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21
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Qi S, Schumann G, Bustillo J, Turner JA, Jiang R, Zhi D, Fu Z, Mayer AR, Vergara VM, Silva RF, Iraji A, Chen J, Damaraju E, Ma X, Yang X, Stevens M, Mathalon DH, Ford JM, Voyvodic J, Mueller BA, Belger A, Potkin SG, Preda A, Zhuo C, Xu Y, Chu C, Banaschewski T, Barker GJ, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Orfanos DP, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Calhoun VD, Sui J. Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker. Biol Psychiatry 2021; 90:529-539. [PMID: 33875230 PMCID: PMC8322149 DOI: 10.1016/j.biopsych.2021.01.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/28/2020] [Accepted: 01/04/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.
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Affiliation(s)
- Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Juan Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico
| | - Jessica A Turner
- Department of Psychology, Georgia State University, Atlanta, Georgia
| | - Rongtao Jiang
- University of Chinese Academy of Sciences, Beijing, China; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Dongmei Zhi
- University of Chinese Academy of Sciences, Beijing, China; Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Andrew R Mayer
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico
| | - Victor M Vergara
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Rogers F Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Armin Iraji
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Jiayu Chen
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Eswar Damaraju
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia
| | - Xiaohong Ma
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xiao Yang
- Psychiatric Laboratory and Mental Health Center, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | | | - Daniel H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, California
| | - Judith M Ford
- Department of Psychiatry, University of California San Francisco, San Francisco, California
| | - James Voyvodic
- Department of Radiology, Duke University, Durham, North Carolina
| | - Bryon A Mueller
- Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Steven G Potkin
- Department of Psychiatry, University of California Irvine, Irvine, California
| | - Adrian Preda
- Department of Psychiatry, University of California Irvine, Irvine, California
| | - Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory, Nankai University Affiliated Anding Hospital, Tianjin, China
| | - Yong Xu
- Department of Humanities and Social Science, Shanxi Medical University, Taiyuan, China
| | - Congying Chu
- Centre for Population Neuroscience and Stratified Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Stratified Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Stratified Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Herta Flor
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, Vermont
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Charité Mitte, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry," University Paris-Saclay, Paris, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry," University Paris-Saclay, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry," University Paris-Saclay, Paris, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Charité Mitte, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Berlin, Germany
| | - Robert Whelan
- PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Humboldt University, Berlin, Germany
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; Department of Psychology, Georgia State University, Atlanta, Georgia.
| | - Jing Sui
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute Technology, and Emory University, Atlanta, Georgia; University of Chinese Academy of Sciences, Beijing, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
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Ventral striatal resting-state functional connectivity in adolescents is associated with earlier onset of binge drinking. Drug Alcohol Depend 2021; 227:109010. [PMID: 34488072 PMCID: PMC8464521 DOI: 10.1016/j.drugalcdep.2021.109010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Earlier engagement in heavy drinking during adolescence is a risk factor for the development of alcohol use disorders later in life. Longitudinal studies in adolescents have linked brain structure and task-evoked function to future alcohol use; however, less is known about how intrinsic network-level interactions relate to future substance use during this developmental period. METHODS In this prospective longitudinal study, resting-state functional connectivity of the ventral striatum, risky decision making, and sensation seeking were measured in 73 adolescents at baseline. Participants were between the ages of 14 and 15 and had no substantial history of substance use upon study entry. Follow-up interviews were conducted approximately every 3 months to assess the initiation of binge drinking (≥ 5 or ≥ 4 drinks per occasion for males or females, respectively). RESULTS Adolescents who began binge drinking sooner exhibited greater connectivity of the ventral striatum to the left precuneus, left angular gyrus, and the left superior frontal gyrus. Greater connectivity of the ventral striatum to the right insula/putamen was associated with longer duration to the onset of binge drinking. Resting-state functional connectivity in these regions was not associated with baseline assessments of risky decision making or sensation seeking. CONCLUSIONS Findings provide novel information about potential risk factors for early initiation of heavy alcohol use. Interventions that target relevant resting-state networks may enhance prevention efforts to decrease adolescent substance use by prolonging onset to heavier levels of alcohol consumption.
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23
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Tuo J, He W, Yang S, Liu L, Liu X, Liu H, Wang Y, Tang T, Xia J, Liao W, Liu Y, Huang Q. Disrupted Topological Organization of Functional Networks in Asymptomatic Carotid Plaque Without Significant Carotid Stenosis: A Resting-State fMRI Study. Front Hum Neurosci 2021; 15:685763. [PMID: 34421560 PMCID: PMC8375554 DOI: 10.3389/fnhum.2021.685763] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/05/2021] [Indexed: 11/16/2022] Open
Abstract
Purpose: Previous studies have found that there are significant changes in functional network properties for patients with moderate to severe carotid artery stenosis. Our study aimed to explore the topology properties of brain functional network in asymptomatic patients with carotid plaque without significant stenosis. Methods: A total of 61 asymptomatic patients with carotid plaque (mean age 61.79 ± 7.35 years) and 25 healthy control subjects (HC; 58.12 ± 6.79 years) were recruited. General data collection, carotid ultrasound examination and resting state functional magnetic resonance imaging were performed on all subjects. Graph-theory was applied to examine the differences in the brain functional network topological properties between two groups. Results: In the plaque group, Eloc(P = 0.03), γ (P = 0.01), and σ (P = 0.01) were significantly higher than in the HC group. The degree centrality of left middle frontal gyrus and the nodal efficiency of left middle frontal gyrus and right inferior parietal angular gyrus were significantly higher in the plaque group than in HC. The degree centrality and betweenness centrality of right middle temporal gyrus, as well as the nodal efficiency of right middle temporal gyrus, were significantly lower in the plaque group than in HC. Conclusions: The brain functional networks of patients with carotid plaques differ from those of healthy controls. Asymptomatic patients with carotid plaques exhibit increased local and global connectivity, which may reflect subtle reorganizations in response to early brain damage.
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Affiliation(s)
- Jia Tuo
- Department of Neurology, Chenzhou No.1 People's Hospital, Chenzhou, China.,Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Wei He
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Emergency, Xiangya Hospital, Central South University, Changsha, China
| | - Shuai Yang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Lihui Liu
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaojuan Liu
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hui Liu
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Yang Wang
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Integrated Traditional and Western, Xiangya Hospital, Central South University, Changsha, China
| | - Tao Tang
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Integrated Traditional and Western, Xiangya Hospital, Central South University, Changsha, China
| | - Jian Xia
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Weihua Liao
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Yunhai Liu
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qing Huang
- Hunan Clinical Research Center for Cerebrovascular Disease, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
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24
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Dynamic weighted “small-world” graphical network establishment for fNIRS time-varying brain function analysis. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102902] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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25
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Linli Z, Huang X, Liu Z, Guo S, Sariah A. A multivariate pattern analysis of resting-state functional MRI data in Naïve and chronic betel quid chewers. Brain Imaging Behav 2021; 15:1222-1234. [PMID: 32712800 DOI: 10.1007/s11682-020-00322-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Betel quid (BQ) is the fourth most commonly consumed psychoactive substance in the world. However, comprehensive functional magnetic resonance imaging (fMRI) studies exploring the neurophysiological mechanism of BQ addiction are lacking. Betel-quid-dependent (BQD) individuals (n = 24) and age-matched healthy controls (HC) (n = 26) underwent fMRI before and after chewing BQ. Multivariate pattern analysis (MVPA) was used to explore the acute effects of BQ-chewing in both groups. A cross-sectional comparison was conducted to explore the chronic effects of BQ-chewing. Regression analysis was used to investigate the relationship between altered circuits of BQD individuals and the severity of BQ addiction. MVPA achieved classification accuracies of up to 90% in both groups for acute BQ-chewing. Suppression of the default-mode network was the most prominent feature. BQD showed more extensive and intensive within- and between-network dysconnectivity of the default, frontal-parietal, and occipital regions associated with high-order brain functions such as self-awareness, inhibitory control, and decision-making. In contrast, the chronic effects of BQ on the brain function were mild, but impaired circuits were predominately located in the default and frontal-parietal networks which might be associated with compulsive drug use. Simultaneously quantifying the effects of both chronic and acute BQ exposure provides a possible neuroimaging-based BQ addiction foci. Results from this study may help us understand the neural mechanisms involved in BQ-chewing and BQ dependence.
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Affiliation(s)
- Zeqiang Linli
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, People's Republic of China
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, People's Republic of China
| | - Xiaojun Huang
- Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Zhening Liu
- Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China
| | - Shuixia Guo
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, People's Republic of China.
- Key Laboratory of Applied Statistics and Data Science, Hunan Normal University, College of Hunan Province, Changsha, People's Republic of China.
| | - Adellah Sariah
- Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
- Department of Mental Health and Psychiatric Nursing, Hubert Kairuki Memorial University, Dar es Salaam, Tanzania.
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26
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Chen D, Jia T, Zhang Y, Cao M, Loth E, Lo CYZ, Cheng W, Liu Z, Gong W, Sahakian BJ, Feng J. Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals. Front Hum Neurosci 2021; 15:657857. [PMID: 34025376 PMCID: PMC8134539 DOI: 10.3389/fnhum.2021.657857] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 03/11/2021] [Indexed: 01/01/2023] Open
Abstract
Several previous studies have reported atypicality in resting-state functional connectivity (FC) in autism spectrum disorder (ASD), yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis (CCA) and hierarchical clustering were used to partition the high-functioning ASD group (i.e., the ASD discovery group) into subgroups. A support vector machine (SVM) model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule (ADOS) scores within the ASD discovery group (r = 0.30, P < 0.001, n = 260), which was further validated in an independent sample (i.e., the ASD validation group) (r = 0.35, P = 0.031, n = 29). The neuroimage-based partition derived two subgroups representing severe versus mild autistic patients. We identified FCs that show graded changes in strength from ASD-severe, through ASD-mild, to controls, while the same pattern cannot be observed in partitions based on ADOS score. We also identified FCs that are specific for ASD-mild, similar to a partition based on ADOS score. The current study provided multiple pieces of evidence with replication to show that resting-state functional magnetic resonance imaging (rsfMRI) FCs could serve as neural biomarkers in partitioning high-functioning autistic individuals based on their symptom severity and showing advantages over traditional partition based on ADOS score. Our results also indicate a compensatory role for a frontocortical network in patients with mild ASD, indicating potential targets for future clinical treatments.
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Affiliation(s)
- Di Chen
- 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
| | - Tianye Jia
- 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
- Centre for Population Neuroscience and Precision Medicine, MRC SGDP Centre, IoPPN, King’s College London, London, United Kingdom
| | - Yuning Zhang
- Centre for Population Neuroscience and Precision Medicine, MRC SGDP Centre, IoPPN, King’s College London, London, United Kingdom
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- School of Psychology, University of Southampton, Southampton, United Kingdom
| | - Miao Cao
- 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
| | - Eva Loth
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Sciences, IoPPN, King’s College London, London, United Kingdom
| | - Chun-Yi Zac Lo
- 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
| | - Wei Cheng
- 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
| | - Zhaowen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Weikang Gong
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Barbara Jacquelyn Sahakian
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Jianfeng Feng
- 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
- School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, United Kingdom
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27
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Tepfer LJ, Alloy LB, Smith DV. Family history of depression is associated with alterations in task-dependent connectivity between the cerebellum and ventromedial prefrontal cortex. Depress Anxiety 2021; 38:508-520. [PMID: 33666313 PMCID: PMC8085134 DOI: 10.1002/da.23143] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 01/18/2021] [Accepted: 02/12/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND A family history of major depressive disorder (MDD) increases the likelihood of a future depressive episode, which itself poses a significant risk for disruptions in reward processing and social cognition. However, it is unclear whether a family history of MDD is associated with alterations in the neural circuitry underlying reward processing and social cognition. METHODS We subdivided 279 participants from the Human Connectome Project into three groups: 71 with a lifetime history of MDD, 103 with a family history (FH) of MDD, and 105 healthy controls (HCs). We then evaluated task-based functional magnetic resonance imaging data on a social cognition and a reward processing task and found a region of the ventromedial prefrontal cortex (vmPFC) that responded to both tasks, independent of the group. To investigate whether the vmPFC shows alterations in functional connectivity between groups, we conducted psychophysiological interaction analyses using the vmPFC as a seed region. RESULTS We found that FH (relative to HC) was associated with increased sadness scores, and MDD (relative to both FH and HC) was associated with increased sadness and MDD symptoms. Additionally, the FH group had increased vmPFC functional connectivity within the nucleus accumbens, left dorsolateral PFC, and subregions of the cerebellum relative to HC during the social cognition task. CONCLUSIONS These findings suggest that aberrant neural mechanisms among those with a familial risk of MDD may underlie vulnerability to altered social cognition.
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Affiliation(s)
| | | | - David V. Smith
- Corresponding Author: David V. Smith, Ph.D., Assistant Professor of Psychology, Temple University, Weiss Hall, Room 825, 1701 North 13th Street Philadelphia, PA 19122, Office Phone: 215-204-1552,
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28
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Jia T, Xie C, Banaschewski T, Barker GJ, Bokde ALW, Büchel C, Quinlan EB, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Poustka L, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Robbins TW, Feng J. Neural network involving medial orbitofrontal cortex and dorsal periaqueductal gray regulation in human alcohol abuse. SCIENCE ADVANCES 2021; 7:eabd4074. [PMID: 33536210 PMCID: PMC7857680 DOI: 10.1126/sciadv.abd4074] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 12/16/2020] [Indexed: 05/26/2023]
Abstract
Prompted by recent evidence of neural circuitry in rodent models, functional magnetic resonance imaging and functional connectivity analyses were conducted for a large adolescent population at two ages, together with alcohol abuse measures, to characterize a neural network that may underlie the onset of alcoholism. A network centered on the medial orbitofrontal cortex (mOFC), as well as including the dorsal periaqueductal gray (dPAG), central nucleus of the amygdala, and nucleus accumbens, was identified, consistent with the rodent models, with evidence of both inhibitory and excitatory coregulation by the mOFC over the dPAG. Furthermore, significant relationships were detected between raised baseline excitatory coregulation in this network and impulsivity measures, supporting a role for negative urgency in alcohol dependence.
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Affiliation(s)
- Tianye Jia
- 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
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London SE5 8AF, UK
| | - Chao Xie
- 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
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Christian Büchel
- University Medical Centre Hamburg-Eppendorf, Martinistr. 52, Hamburg, Germany
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London SE5 8AF, UK
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London SE5 8AF, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, C.E.A., Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT 05405, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie," Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie," Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
- AP-HP.Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Kiel University, Kiel, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- PONS-Research Group, Charité Mental Health, Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Berlin, Germany
- Department of Sports and Health Sciences, University of Potsdam, Potsdam, Germany
- PONS Centre, Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Trevor W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Jianfeng Feng
- 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
- School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
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29
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Zhu J, Zhou Y, Ma S, Chen R, Xie S, Liu Z, Li X, Wei W. The association between anxiety and esophageal cancer: A nationwide population-based study. Psychooncology 2020; 30:321-330. [PMID: 33098157 DOI: 10.1002/pon.5580] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 10/06/2020] [Accepted: 10/18/2020] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Research on generalized anxiety disorder (GAD) and its association with esophageal cancer (EC) is sparse. The study aimed to explore the association between GAD and EC. METHODS A multicenter, population-based study in high-risk regions for EC (ECHRRs) was conducted from 2017 to 2019. All participants received free endoscopy screening. If the esophageal endoscopy results were suspicious, the pathological biopsy was performed to confirm normal, esophagitis, low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and EC. Information on participants' exposure to risk factors was collected. GAD was assessed with Generalized Anxiety Disorder Scale-7. RESULTS With esophageal endoscopy, 25,650 participants in ECHRRs were examined, 9586 of whom were suspicious and confirmed by esophageal pathology. The detection rate of EC and precancerous lesions was 6.83% (1751/25,650), with 1377 LGIN (5.37%), 272 HGIN (1.06%), and 102 EC (0.40%) cases. The overall mean GAD score (95% CI) and prevalence among 25,650 participants with endoscopy were 1.96 (1.93-1.99) and 16.90%, respectively. The mean GAD score and prevalence among 9586 participants with pathology were 1.96 (1.91-2.02) and 17.98%, respectively. The mean GAD scores of patients confirmed with normal, esophagitis, LGIN, HGIN, and EC were 1.73 (1.62-1.85), 1.91 (1.85-1.97), 1.94 (1.80-2.08), 3.98 (3.73-4.23). and 2.97 (2.49-3.45), respectively (p < 0.001). The corresponding prevalence of GAD were 5.21%, 18.72%, 17.72%, 43.75%, and 36.27%, respectively (p < 0.001). The age- and gender-adjusted odds ratios (ORs) between GAD and each esophageal lesion type were 1.02 (0.99-1.04), 1.01 (0.98-1.04), 1.27 (1.21-1.33), and 1.16 (1.08-1.24), respectively. The ORs (95% CIs) of the positive associations were 1.08 (1.05-1.12), 1.03 (0.99-1.07), 1.35 (1.29-1.42), and 1.19 (1.10-1.29) after further adjustment for potential confounders (all p < 0.001). Sensitivity analysis showed that the positive association persisted. CONCLUSIONS GAD was significantly higher in patients with EC and precancerous lesions. Focusing on and alleviating anxiety in high-risk groups (including patients with HGIN and EC) may be an effective strategy for EC prevention and control. Further prospective studies are warranted to validate the results.
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Affiliation(s)
- Juan Zhu
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
| | - Yueyue Zhou
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Shanrui Ma
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
| | - Ru Chen
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
| | - Shuanghua Xie
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
| | - Zhengkui Liu
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Xinqing Li
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
| | - Wenqiang Wei
- Cancer Registry Office, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, People's Republic of China
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30
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Klugah-Brown B, Di X, Zweerings J, Mathiak K, Becker B, Biswal B. Common and separable neural alterations in substance use disorders: A coordinate-based meta-analyses of functional neuroimaging studies in humans. Hum Brain Mapp 2020; 41:4459-4477. [PMID: 32964613 PMCID: PMC7555084 DOI: 10.1002/hbm.25085] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 05/18/2020] [Accepted: 05/20/2020] [Indexed: 12/12/2022] Open
Abstract
Delineating common and separable neural alterations in substance use disorders (SUD) is imperative to understand the neurobiological basis of the addictive process and to inform substance‐specific treatment strategies. Given numerous functional MRI (fMRI) studies in different SUDs, a meta‐analysis could provide an opportunity to determine robust shared and substance‐specific alterations. The present study employed a coordinate‐based meta‐analysis covering fMRI studies in individuals with addictive cocaine, cannabis, alcohol, and nicotine use. The primary meta‐analysis demonstrated common alterations in primary dorsal striatal, and frontal circuits engaged in reward/salience processing, habit formation, and executive control across different substances and task‐paradigms. Subsequent sub‐analyses revealed substance‐specific alterations in frontal and limbic regions, with marked frontal and insula‐thalamic alterations in alcohol and nicotine use disorders respectively. Examining task‐specific alterations across substances revealed pronounced frontal alterations during cognitive processes yet stronger striatal alterations during reward‐related processes. Finally, an exploratory meta‐analysis revealed that neurofunctional alterations in striatal and frontal reward processing regions can already be determined with a high probability in studies with subjects with comparably short durations of use. Together the findings emphasize the role of dysregulations in frontostriatal circuits and dissociable contributions of these systems in the domains of reward‐related and cognitive processes which may contribute to substance‐specific behavioral alterations.
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Affiliation(s)
- Benjamin Klugah-Brown
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Jana Zweerings
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany.,JARA Translational Brain Medicine, RWTH Aachen, Aachen, Germany
| | - Klaus Mathiak
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Aachen, Germany.,JARA Translational Brain Medicine, RWTH Aachen, Aachen, Germany
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
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31
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Vatansever D, Karapanagiotidis T, Margulies DS, Jefferies E, Smallwood J. Distinct patterns of thought mediate the link between brain functional connectomes and well-being. Netw Neurosci 2020; 4:637-657. [PMID: 32885119 PMCID: PMC7462429 DOI: 10.1162/netn_a_00137] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 03/04/2020] [Indexed: 12/29/2022] Open
Abstract
Ongoing thought patterns constitute important aspects of both healthy and abnormal human cognition. However, the neural mechanisms behind these daily experiences and their contribution to well-being remain a matter of debate. Here, using resting-state fMRI and retrospective thought sampling in a large neurotypical cohort (n = 211), we identified two distinct patterns of thought, broadly describing the participants' current concerns and future plans, that significantly explained variability in the individual functional connectomes. Consistent with the view that ongoing thoughts are an emergent property of multiple neural systems, network-based analysis highlighted the central importance of both unimodal and transmodal cortices in the generation of these experiences. Importantly, while state-dependent current concerns predicted better psychological health, mediating the effect of functional connectomes, trait-level future plans were related to better social health, yet with no mediatory influence. Collectively, we show that ongoing thoughts can influence the link between brain physiology and well-being.
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Affiliation(s)
- Deniz Vatansever
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | | | - Daniel S Margulies
- Brain and Spine Institute, French National Centre for Scientific Research, Paris, France
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32
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Voon V, Grodin E, Mandali A, Morris L, Doñamayor N, Weidacker K, Kwako L, Goldman D, Koob GF, Momenan R. Addictions NeuroImaging Assessment (ANIA): Towards an integrative framework for alcohol use disorder. Neurosci Biobehav Rev 2020; 113:492-506. [PMID: 32298710 DOI: 10.1016/j.neubiorev.2020.04.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 03/30/2020] [Accepted: 04/05/2020] [Indexed: 02/08/2023]
Abstract
Alcohol misuse and addiction are major international public health issues. Addiction can be characterized as a disorder of aberrant neurocircuitry interacting with environmental, genetic and social factors. Neuroimaging in alcohol misuse can thus provide a critical window into underlying neural mechanisms, highlighting possible treatment targets and acting as clinical biomarkers for predicting risk and treatment outcomes. This neuroimaging review on alcohol misuse in humans follows the Addictions Neuroclinical Assessment (ANA) that proposes incorporating three functional neuroscience domains integral to the neurocircuitry of addiction: incentive salience and habits, negative emotional states, and executive function within the context of the addiction cycle. Here we review and integrate multiple imaging modalities focusing on underlying cognitive processes such as reward anticipation, negative emotionality, cue reactivity, impulsivity, compulsivity and executive function. We highlight limitations in the literature and propose a model forward in the use of neuroimaging as a tool to understanding underlying mechanisms and potential clinical applicability for phenotyping of heterogeneity and predicting risk and treatment outcomes.
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Affiliation(s)
- Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Behavioural and Clinical Neurosciences Institute, Cambridge, UK; Cambridgeshire and Peterborough NHS Trust, Cambridge, UK.
| | - Erica Grodin
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - Alekhya Mandali
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Laurel Morris
- Behavioural and Clinical Neurosciences Institute, Cambridge, UK; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Nuria Doñamayor
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Laura Kwako
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - David Goldman
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - George F Koob
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
| | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, UK
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33
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Wan Z, Rolls ET, Cheng W, Feng J. Sensation-seeking is related to functional connectivities of the medial orbitofrontal cortex with the anterior cingulate cortex. Neuroimage 2020; 215:116845. [PMID: 32289458 DOI: 10.1016/j.neuroimage.2020.116845] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/03/2020] [Accepted: 04/06/2020] [Indexed: 10/24/2022] Open
Abstract
Sensation-seeking is a multifaceted personality trait with components that include experience-seeking, thrill and adventure seeking, disinhibition, and susceptibility to boredom, and is an aspect of impulsiveness. We analysed brain regions involved in sensation-seeking in a large-scale study with 414 participants and showed that the sensation-seeking score could be optimally predicted from the functional connectivity with typically (in different participants) 18 links between brain areas (measured in the resting state with fMRI) with correlation r = 0.34 (p = 7.3 × 10-13) between the predicted and actual sensation-seeking score across all participants. Interestingly, 8 of the 11 links that were common for all participants were between the medial orbitofrontal cortex and the anterior cingulate cortex and yielded a prediction accuracy r = 0.30 (p = 4.8 × 10-10). We propose that this important aspect of personality, sensation-seeking, reflects a strong effect of reward (in which the medial orbitofrontal cortex is implicated) on promoting actions to obtain rewards (in which the anterior cingulate cortex is implicated). Risk-taking was found to have a moderate correlation with sensation-seeking (r = 0.49, p = 3.9 × 10-26), and three of these functional connectivities were significantly correlated (p < 0.05) with the overall risk-taking score. This discovery helps to show how the medial orbitofrontal and anterior cingulate cortices influence behaviour and personality, and indicate that sensation-seeking can involve in part the medial orbitofrontal cortex reward system, which can thereby become associated with risk-taking and a type of impulsiveness.
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Affiliation(s)
- Zhuo Wan
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
| | - Edmund T Rolls
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK; Oxford Centre for Computational Neuroscience, Oxford, UK.
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK; School of Mathematical Sciences, School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, 200433, PR China.
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Kashyap R, Bhattacharjee S, Yeo BTT, Chen SHA. Maximizing dissimilarity in resting state detects heterogeneous subtypes in healthy population associated with high substance use and problems in antisocial personality. Hum Brain Mapp 2020; 41:1261-1273. [PMID: 31773817 PMCID: PMC7267929 DOI: 10.1002/hbm.24873] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 11/05/2019] [Accepted: 11/12/2019] [Indexed: 01/08/2023] Open
Abstract
Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRI's are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying common-and-orthogonal-basis-extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component is specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n = 107) with maximal-COBE-dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found six behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether the findings suggested that subtypes exist even in healthy control population, and comparison studies (case vs. control) need to be mindful of it.
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Affiliation(s)
- Rajan Kashyap
- Centre for Research and Development in Learning (CRADLE)Nanyang Technological UniversitySingaporeSingapore
- Department of Electrical and Computer EngineeringCentre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of SingaporeSingapore
| | - Sagarika Bhattacharjee
- Psychology, School of Social Sciences (SSS)Nanyang Technological UniversitySingaporeSingapore
| | - B. T. Thomas Yeo
- Department of Electrical and Computer EngineeringCentre for Sleep and Cognition, Clinical Imaging Research Centre, N.1 Institute for Health, National University of SingaporeSingapore
- Centre for Cognitive Neuroscience, Neuroscience and Behavioral Disorders ProgramDuke‐NUS Medical SchoolSingaporeSingapore
- Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownMassachusetts
- NUS Graduate School for Integrative Sciences and EngineeringNational University of SingaporeSingaporeSingapore
| | - S. H. Annabel Chen
- Centre for Research and Development in Learning (CRADLE)Nanyang Technological UniversitySingaporeSingapore
- Psychology, School of Social Sciences (SSS)Nanyang Technological UniversitySingaporeSingapore
- Lee Kong Chian School of Medicine (LKC Medicine)Nanyang Technological UniversitySingaporeSingapore
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Cheng W, Rolls ET, Robbins TW, Gong W, Liu Z, Lv W, Du J, Wen H, Ma L, Quinlan EB, Garavan H, Artiges E, Papadopoulos Orfanos D, Smolka MN, Schumann G, Kendrick K, Feng J. Decreased brain connectivity in smoking contrasts with increased connectivity in drinking. eLife 2019; 8:e40765. [PMID: 30616717 PMCID: PMC6336408 DOI: 10.7554/elife.40765] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Accepted: 12/20/2018] [Indexed: 01/01/2023] Open
Abstract
In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors.
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Affiliation(s)
- Wei Cheng
- Institute of Science and Technology for Brain-inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
- Department of Computer ScienceUniversity of WarwickCoventryUnited Kingdom
| | - Edmund T Rolls
- Institute of Science and Technology for Brain-inspired IntelligenceFudan UniversityShanghaiChina
- Department of Computer ScienceUniversity of WarwickCoventryUnited Kingdom
- Oxford Centre for Computational NeuroscienceOxfordUnited Kingdom
| | - Trevor W Robbins
- Behavioural and Clinical Neuroscience InstituteUniversity of CambridgeCambridgeUnited Kingdom
- Department of PsychologyUniversity of CambridgeCambridgeUnited Kingdom
| | - Weikang Gong
- Institute of Science and Technology for Brain-inspired IntelligenceFudan UniversityShanghaiChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhaowen Liu
- School of Computer Science and TechnologyXidian UniversityXi’anChina
| | - Wujun Lv
- School of MathematicsShanghai University Finance and EconomicsShanghaiChina
| | - Jingnan Du
- Institute of Science and Technology for Brain-inspired IntelligenceFudan UniversityShanghaiChina
| | - Hongkai Wen
- Department of Computer ScienceUniversity of WarwickCoventryUnited Kingdom
| | - Liang Ma
- Beijing Institute of Genomics, Chinese Academy of SciencesBeijingChina
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUnited Kingdom
| | - Hugh Garavan
- Department of PsychiatryUniversity of VermontVermontUnited States
- Department of Psychiatry PsychologyUniversity of VermontVermontUnited States
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 'Neuroimaging & Psychiatry', University Paris Sud – Paris Saclay, University Paris Descartes, Service Hospitalier Frédéric Joliot and GH Nord Essonne Psychiatry Department 91G16OrsayFrance
| | | | - Michael N Smolka
- Department of Psychiatry and Neuroimaging CenterTechnische Universität DresdenDresdenGermany
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUnited Kingdom
| | - Keith Kendrick
- Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, Center for Information in MedicineUniversity of Electronic Science and Technology of ChinaChengduChina
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University)Ministry of EducationShanghaiChina
- Department of Computer ScienceUniversity of WarwickCoventryUnited Kingdom
- School of Mathematical Sciences and Centre for Computational Systems BiologyFudan UniversityShanghaiChina
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