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Ballester J, Marchand WR, Philip NS. Transcranial magnetic stimulation for methamphetamine use disorder: A scoping review within the neurocircuitry model of addiction. Psychiatry Res 2024; 338:115995. [PMID: 38852478 PMCID: PMC11209858 DOI: 10.1016/j.psychres.2024.115995] [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: 03/05/2024] [Revised: 05/21/2024] [Accepted: 05/28/2024] [Indexed: 06/11/2024]
Abstract
The use of methamphetamine in the United States is increasing, contributing now to the "fourth wave" in the national opioid epidemic crisis. People who suffer from methamphetamine use disorder (MUD) have a higher risk of death. No pharmacological interventions are approved by the FDA and psychosocial interventions are only moderately effective. Transcranial Magnetic Stimulation (TMS) is a relatively novel FDA-cleared intervention for the treatment of Major Depressive Disorder (MDD) and other neuropsychiatric conditions. Several lines of research suggest that TMS could be useful for the treatment of addictive disorders, including MUD. We will review those published clinical trials that show potential effects on craving reduction of TMS when applied over the dorsolateral prefrontal cortex (DLPFC) also highlighting some limitations that affect their generalizability and applicability. We propose the use of the Koob and Volkow's neurocircuitry model of addiction as a frame to explain the brain effects of TMS in patients with MUD. We will finally discuss new venues that could lead to a more individualized and effective treatment of this complex disorder including the use of neuroimaging, the exploration of different areas of the brain such as the frontopolar cortex or the salience network and the use of biomarkers.
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Affiliation(s)
- J Ballester
- Substance Abuse Residential Rehabilitation Treatment Program, VA Salt Lake City Health Care System, 500 Foothill Drive, Salt Lake City, UT 84148, USA; Department of Psychiatry, School of Medicine, University of Utah, 501 Chipeta Way, Salt Lake City, UT 84108, USA.
| | - W R Marchand
- Department of Psychiatry, School of Medicine, University of Utah, 501 Chipeta Way, Salt Lake City, UT 84108, USA; VISN-19 Whole Health Flagship Site, VA Salt Lake City Health Care System, 500 Foothill Drive, Salt Lake City, UT 84148, USA; Animal, Dairy and Veterinary Sciences, Utah State University, 4815 Old Main Hill, Logan, UT 84322, USA
| | - N S Philip
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA; VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, USA
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Yang K, Du R, Yang Q, Zhao R, Fan F, Chen S, Luo X, Tan S, Wang Z, Yu T, Tian B, Le TM, Li CSR, Tan Y. Cortical thickness of the inferior parietal lobule as a potential predictor of relapse in men with alcohol dependence. Brain Imaging Behav 2024; 18:331-342. [PMID: 38078981 DOI: 10.1007/s11682-023-00838-7] [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] [Accepted: 12/01/2023] [Indexed: 12/26/2023]
Abstract
Alcohol dependence is a disorder with a high recurrence rate that leads to a considerable public health burden. The risk of relapse appears to be related to a complex interplay of multiple factors. Herein, we aimed to explore the potential neural predictors of relapse in Chinese male patients with alcohol dependence. This study enrolled 58 male patients with alcohol dependence who had undergone acute detoxification. General demographic information and clinical features were collected. Magnetic resonance imaging data were used to measure cortical thickness across 34 regions of the brain. Patients were followed up at six months, and 51 patients completed the follow-up visit. These patients were divided into a relapser and an abstainer group. A binary logistic regression analysis was performed to investigate the potential risk factors of relapse. Compared to abstainers, relapsers showed higher inattention and non-planning impulsivity on the 11th version of the Barratt Impulsive Scale. The cortical thicknesses of the inferior-parietal lobules were significantly higher in abstainers compared with those in relapsers. Furthermore, binary logistic regression analysis showed that the thickness of the inferior parietal lobule predicted relapse, and lower non-planning impulse was a protective factor against relapse. Relapsers show poorer impulse control than abstainers, and structural magnetic resonance imaging revealed a decreased thickness of the inferior parietal lobule in relapsers. Our results indicate the thickness of the inferior parietal lobule as a potential relapse predictor in male patients with alcohol dependence.
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Affiliation(s)
- Kebing Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Ruonan Du
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Qingyan Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Rongjiang Zhao
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Xingguang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China
| | - Thang M Le
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06519, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, 06519, USA
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital, Beijing, 100096, People's Republic of China.
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Kohler RJ, Zhornitsky S, Potenza MN, Yip SW, Worhunsky P, Angarita GA. Cocaine self-administration behavior is associated with subcortical and cortical morphometry measures in individuals with cocaine use disorder. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2024:1-12. [PMID: 38551365 DOI: 10.1080/00952990.2024.2318585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/10/2024] [Indexed: 05/24/2024]
Abstract
Background: Individual differences in gray-matter morphometry in the limbic system and frontal cortex have been linked to clinical features of cocaine use disorder (CUD). Self-administration paradigms can provide more direct measurements of the relationship between the regulation of cocaine use and gray-matter morphometry when compared to self-report assessments.Objectives: Our goal was to investigate associations with self-administration behavior in subcortical and cortical brain regions. We hypothesized the number of cocaine infusions self-administered would be correlated with gray-matter volumes (GMVs) in the striatum, amygdala, and hippocampus. Due to scarcity in human studies, we did not hypothesize subcortical directionality. In the frontal cortex, we hypothesized thickness would be negatively correlated with self-administered cocaine.Methods: We conducted an analysis of cocaine self-administration and structural MRI data from 33 (nFemales = 10) individuals with moderate-to-severe CUD. Self-administration lasted 60-minutes and cocaine (8, 16, or 32 mg/70 kg) was delivered on an FR1 schedule (5-minute lockout). Subcortical and cortical regression analyses were performed that included combined bilateral regions and age, experimental variables and use history as confounders.Results: Self-administered cocaine infusions were positively associated with caudal GMV (b = 0.18, p = 0.030) and negatively with putamenal GMV (b = -0.10, p = 0.041). In the cortical model, infusions were positively associated with insular thickness (b = 0.39, p = 0.008) and women appeared to self-administer cocaine more frequently (b = 0.23, p = 0.019).Conclusions: Brain morphometry features in the striatum and insula may contribute to cocaine consumption in CUD. These differences in morphometry may reflect consequences of prolonged use, predisposed vulnerability, or other possibilities.Clinical Trial Numbers: NCT01978431; NCT03471182.
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Affiliation(s)
- Robert J Kohler
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Simon Zhornitsky
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Connecticut Mental Health Center, New Haven, CT, USA
| | - Marc N Potenza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Connecticut Mental Health Center, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Connecticut Council on Problem Gambling, Wethersfield, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | - Sarah W Yip
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Patrick Worhunsky
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
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Boer OD, El Marroun H, Muetzel RL. Adolescent substance use initiation and long-term neurobiological outcomes: insights, challenges and opportunities. Mol Psychiatry 2024:10.1038/s41380-024-02471-2. [PMID: 38409597 DOI: 10.1038/s41380-024-02471-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 01/15/2024] [Accepted: 01/30/2024] [Indexed: 02/28/2024]
Abstract
The increased frequency of risk taking behavior combined with marked neuromaturation has positioned adolescence as a focal point of research into the neural causes and consequences of substance use. However, little work has provided a summary of the links between adolescent initiated substance use and longer-term brain outcomes. Here we review studies exploring the long-term effects of adolescent-initiated substance use with structural and microstructural neuroimaging. A quarter of all studies reviewed conducted repeated neuroimaging assessments. Long-term alcohol use, as well as tobacco use were consistently associated with smaller frontal cortices and altered white matter microstructure. This association was mostly observed in the ACC, insula and subcortical regions in alcohol users, and for the OFC in tobacco users. Long-term cannabis use was mostly related to altered frontal cortices and hippocampal volumes. Interestingly, cannabis users scanned more years after use initiation tended to show smaller measures of these regions, whereas those with fewer years since initiation showed larger measures. Long-term stimulant use tended to show a similar trend as cannabis in terms of years since initiation in measures of the putamen, insula and frontal cortex. Long-term opioid use was mostly associated with smaller subcortical and insular volumes. Of note, null findings were reported in all substance use categories, most often in cannabis use studies. In the context of the large variety in study designs, substance use assessment, methods, and sample characteristics, we provide recommendations on how to interpret these findings, and considerations for future studies.
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Affiliation(s)
- Olga D Boer
- Department of Psychology, Education and Child Studies - Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Hanan El Marroun
- Department of Psychology, Education and Child Studies - Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center - Sophia Children's Hospital, Rotterdam, The Netherlands.
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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Sun D, Wang R, Du Q, Zhang Y, Chen H, Shi Z, Wang X, Zhou H. Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study. J Transl Med 2024; 22:83. [PMID: 38245759 PMCID: PMC10800041 DOI: 10.1186/s12967-024-04892-7] [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: 06/29/2023] [Accepted: 01/13/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent. OBJECTIVE We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure. METHODS MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis. RESULTS After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) = - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology. CONCLUSION Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.
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Affiliation(s)
- Dongren Sun
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Rui Wang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Qin Du
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Ying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Hongxi Chen
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Ziyan Shi
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China
| | - Xiaofei Wang
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China.
| | - Hongyu Zhou
- Department of Neurology, West China Hospital, Sichuan University, Guo Xuexiang #37, Chengdu, 610041, China.
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Wang HA, Liang HJ, Ernst TM, Nakama H, Cunningham E, Chang L. Independent and combined effects of methamphetamine use disorders and APOEε4 allele on cognitive performance and brain morphometry. Addiction 2023; 118:2384-2396. [PMID: 37563863 PMCID: PMC10840926 DOI: 10.1111/add.16309] [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: 12/18/2022] [Accepted: 06/19/2023] [Indexed: 08/12/2023]
Abstract
AIMS Prior studies showed that methamphetamine (METH) users had greater than normal age-related brain atrophy; whether having the apolipoprotein E (APOE)-ε4 allele may be a contributory factor has not been evaluated. We aimed to determine the independent and combined effects of chronic heavy METH use and having at least one copy of the APOE-ε4 allele (APOE-ε4+) on brain morphometry and cognition, especially in relation to aging. METHODS We compared brain morphometry and cognitive performance in 77 individuals with chronic heavy METH use (26 APOE-ε4+, 51 APOE-ε4-) and 226 Non-METH users (66 APOE-ε4+, 160 APOE-ε4-), using a 2 × 2 design (two-way analysis of co-variance). Vertex-wise cortical volumes, thickness and seven subcortical volumes, were automatically measured using FreeSurfer. Linear regression between regional brain measures, and cognitive scores that showed group differences were evaluated. Group differences in age-related decline in brain and cognitive measures were also explored. RESULTS Regardless of APOE-ε4 genotype, METH users had lower Motor Z-scores (P = 0.005), thinner right lateral-orbitofrontal cortices (P < 0.001), smaller left pars-triangularis gyrus volumes (P = 0.004), but larger pallida, hippocampi and amygdalae (P = 0.004-0.006) than nonusers. Across groups, APOE-ε4+ METH users had the smallest volumes of superior frontal cortical gyri bilaterally, and of the smallest volume in left rostral-middle frontal gyri (all P-values <0.001). Smaller right superior-frontal gyrus predicted poorer motor function only in APOE-ε4+ participants (interaction-P < 0.001). Cortical volumes and thickness declined with age similarly across all participants; however, APOE-ε4-carriers showed thinner right inferior parietal cortices than noncarriers at younger age (interaction-P < 0.001). CONCLUSIONS Chronic heavy use and having at least one copy of the APOE-ε4 allele may have synergistic effects on brain atrophy, particularly in frontal cortices, which may contribute to their poorer cognitive function. However, the enlarged subcortical volumes in METH users replicated prior studies, and are likely due to METH-mediated neuroinflammation.
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Affiliation(s)
- Hannah A. Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hua-Jun Liang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Thomas M. Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Eric Cunningham
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
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Li G, Li Y, Zhang Z, Chen Y, Li B, Hao D, Yang L, Yang Y, Li X, Li CSR. Sex differences in externalizing and internalizing traits and ventral striatal responses to monetary loss. J Psychiatr Res 2023; 162:11-20. [PMID: 37062201 PMCID: PMC10225357 DOI: 10.1016/j.jpsychires.2023.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 02/26/2023] [Accepted: 04/08/2023] [Indexed: 04/18/2023]
Abstract
Ventral striatum (VS) processes rewarding and punishing stimuli. Women and men vary in externalizing and internalizing traits, which may influence neural responses to reward and punishment. To investigate sex differences in how individual traits influence VS responses to reward and punishment, we curated the data of the Human Connectome Project and identified 981 (473 men) subjects evaluated by the Achenbach Adult Self-Report Syndrome Scales. We processed the imaging data with published routines and extracted VS response (β) to win and to loss vs. baseline in a gambling task for correlation with externalizing and internalizing symptom severity. Men vs. women showed more severe externalizing symptoms and higher VS response to monetary losses (VS-loss β) but not to wins. Men but not women showed a significant, positive correlation between VS-loss β and externalizing traits, and the sex difference was confirmed by a slope test. The correlations of VS-loss vs. externalizing and of VS-win vs. externalizing and those of VS-loss vs. externalizing and of VS-loss vs. internalizing traits both differed significantly in slope, confirming its specificity, in men. Further, the sex-specific relationship between VS-loss β and externalizing trait did not extend to activities during exposure to negative emotion in the face matching task. To conclude, VS responses to loss but not to win and their correlation with externalizing rather than internalizing symptom severity showed sex differences in young adults. The findings highlight the relationship of externalizing traits and VS response to monetary loss and may have implications for psychological models of externalizing behaviors in men.
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Affiliation(s)
- Guangfei Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China; Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China.
| | - Yashuang Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Zhao Zhang
- Department of Biomedical Engineering, School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Yu Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Bao Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Dongmei Hao
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China; Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Lin Yang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China; Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Yimin Yang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China; Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Xuwen Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China; Beijing International Science and Technology Cooperation Base for Intelligent Physiological Measurement and Clinical Transformation, Beijing, China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA; Wu Tsai Institute, Yale University, New Haven, CT, USA.
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Yang K, Du R, Yang Q, Zhao R, Fan F, Chen S, Luo X, Tan S, Wang Z, Yu T, Tian B, Le TM, Li CSR, Tan Y. Cortical thickness of the inferior parietal lobule as a potential predictor of relapse in men with alcohol dependence. RESEARCH SQUARE 2023:rs.3.rs-2628081. [PMID: 36945425 PMCID: PMC10029073 DOI: 10.21203/rs.3.rs-2628081/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
Background Alcohol dependence (AD) is a disorder with a high recurrence rate that leads to a considerable public health burden. The risk of relapse appears to be related to a complex interplay of multiple factors. Herein, we aimed to explore the potential neural predictors of relapse in Chinese male patients with AD. Methods This study enrolled 58 male patients with AD who had undergone acute detoxification. General demographic information and clinical features were collected. Magnetic resonance imaging (MRI) data were used to measure cortical thickness across 34 regions of the brain. Patients were followed up at 6 months, and 51 patients completed the follow-up visit. These patients were divided into a relapser and an abstainer group. A binary logistic regression analysis was performed to investigate the potential risk factors of relapse. Results Compared to abstainers, relapsers showed higher inattention and non-planning impulsivity on the 11th version of the Barratt Impulsive Scale. The cortical thicknesses of the inferior-parietal lobule were significantly greater in abstainers compared with those in relapsers. Furthermore, binary logistic regression analysis showed that the thickness of the inferior parietal lobule predicted relapse. Conclusions Relapsers show poorer impulse control than abstainers, and MRI imaging shows a decreased thickness of the inferior parietal lobule in relapsers. Our results indicate the thickness of the inferior parietal lobule as a potential relapse predictor in male patients with AD.
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Affiliation(s)
- Kebing Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Ruonan Du
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Qingyan Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Rongjiang Zhao
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Song Chen
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | | | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Ting Yu
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | - Baopeng Tian
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
| | | | | | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing Huilongguan Hospital
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Robinson EA, Gleeson J, Arun AH, Clemente A, Gaillard A, Rossetti MG, Brambilla P, Bellani M, Crisanti C, Curran HV, Lorenzetti V. Measuring white matter microstructure in 1,457 cannabis users and 1,441 controls: A systematic review of diffusion-weighted MRI studies. FRONTIERS IN NEUROIMAGING 2023; 2:1129587. [PMID: 37554654 PMCID: PMC10406316 DOI: 10.3389/fnimg.2023.1129587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/09/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Cannabis is the most widely used regulated substance by youth and adults. Cannabis use has been associated with psychosocial problems, which have been partly ascribed to neurobiological changes. Emerging evidence to date from diffusion-MRI studies shows that cannabis users compared to controls show poorer integrity of white matter fibre tracts, which structurally connect distinct brain regions to facilitate neural communication. However, the most recent evidence from diffusion-MRI studies thus far has yet to be integrated. Therefore, it is unclear if white matter differences in cannabis users are evident consistently in selected locations, in specific diffusion-MRI metrics, and whether these differences in metrics are associated with cannabis exposure levels. METHODS We systematically reviewed the results from diffusion-MRI imaging studies that compared white matter differences between cannabis users and controls. We also examined the associations between cannabis exposure and other behavioral variables due to changes in white matter. Our review was pre-registered in PROSPERO (ID: 258250; https://www.crd.york.ac.uk/prospero/). RESULTS We identified 30 diffusion-MRI studies including 1,457 cannabis users and 1,441 controls aged 16-to-45 years. All but 6 studies reported group differences in white matter integrity. The most consistent differences between cannabis users and controls were lower fractional anisotropy within the arcuate/superior longitudinal fasciculus (7 studies), and lower fractional anisotropy of the corpus callosum (6 studies) as well as higher mean diffusivity and trace (4 studies). Differences in fractional anisotropy were associated with cannabis use onset (4 studies), especially in the corpus callosum (3 studies). DISCUSSION The mechanisms underscoring white matter differences are unclear, and they may include effects of cannabis use onset during youth, neurotoxic effects or neuro adaptations from regular exposure to tetrahydrocannabinol (THC), which exerts its effects by binding to brain receptors, or a neurobiological vulnerability predating the onset of cannabis use. Future multimodal neuroimaging studies, including recently developed advanced diffusion-MRI metrics, can be used to track cannabis users over time and to define with precision when and which region of the brain the white matter changes commence in youth cannabis users, and whether cessation of use recovers white matter differences. SYSTEMATIC REVIEW REGISTRATION www.crd.york.ac.uk/prospero/, identifier: 258250.
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Affiliation(s)
- Emily Anne Robinson
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - John Gleeson
- Digital Innovation 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
| | - Arush Honnedevasthana Arun
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Adam Clemente
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
| | - Alexandra Gaillard
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Maria Gloria Rossetti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Marcella Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Verona, Italy
| | - Camilla Crisanti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - H. Valerie Curran
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
- Clinical Psychopharmacology Unit, University College London, London, United Kingdom
| | - Valentina Lorenzetti
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC, Australia
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10
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Zhao Y, Yang X, Cheng S, Li C, He D, Cai Q, Wei W, Qin X, Zhang N, Shi S, Chu X, Meng P, Zhang F. Assessing the effect of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes. Cereb Cortex 2023:7030864. [PMID: 36750265 DOI: 10.1093/cercor/bhac526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 02/09/2023] Open
Abstract
Longitudinal changes in brain structure and lifestyle can affect sleep phenotypes. However, the influence of the interaction between longitudinal changes in brain structure and lifestyle on sleep phenotypes remains unclear. Genome-wide association study dataset of longitudinal changes in brain structure was obtained from published study. Phenotypic data of lifestyles and sleep phenotypes were obtained from UK Biobank cohort. Using genotype data from UK Biobank, we calculated polygenetic risk scores of longitudinal changes in brain structure phenotypes. Linear/logistic regression analysis was conducted to evaluate interactions between longitudinal changes in brain structure and lifestyles on sleep duration, chronotype, insomnia, snoring and daytime dozing. Multiple lifestyle × longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activity×caudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 × 10-3) in total samples, coffee intake×cerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 × 10-4) in females. Besides, we found 4 overlapping interactions in different sleep phenotypes. We conducted sex stratification analysis and identified one overlapping interaction between female and male. Our results support the moderate effects of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes, and deepen our understanding of the pathogenesis of sleep disorders.
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Affiliation(s)
- Yijing Zhao
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xuena Yang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Shiqiang Cheng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Chun'e Li
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Dan He
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Qingqing Cai
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Wenming Wei
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xiaoyue Qin
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Na Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Sirong Shi
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Xiaoge Chu
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Peilin Meng
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
| | - Feng Zhang
- Key Laboratory of Trace Elements and Endemic Diseases, Collaborative Innovation Center of Endemic Disease and Health Promotion for Silk Road Region, School of Public Health, Health Science Center, Xi'an Jiaotong University, No. 76 Yan Ta West Road, Xi'an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases of Ministry of Education of China, Health Science Center, Xi'an Jiaotong University, Xi'an 710061, China
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11
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Lorenzetti V, Kowalczyk M, Duehlmeyer L, Greenwood LM, Chye Y, Yücel M, Whittle S, Roberts CA. Brain Anatomical Alterations in Young Cannabis Users: Is it All Hype? A Meta-Analysis of Structural Neuroimaging Studies. Cannabis Cannabinoid Res 2023; 8:184-196. [PMID: 35443799 DOI: 10.1089/can.2021.0099] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Introduction: Cannabis use has a high prevalence in young youth and is associated with poor psychosocial outcomes. Such outcomes have been ascribed to the impact of cannabis exposure on the developing brain. However, findings from individual studies of volumetry in youth cannabis users are equivocal. Objectives: Our primary objective was to systematically review the evidence on brain volume differences between young cannabis users and nonusers aged 12-26 where profound neuromaturation occurs, accounting for the role of global brain volumes (GBVs). Our secondary objective was to systematically integrate the findings on the association between youth age and volumetry in youth cannabis users. Finally, we aimed to evaluate the quality of the evidence. Materials and Methods: A systematic search was run in three databases (PubMed, Scopus, and PsycINFO) and was reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We run meta-analyses (with and without controlling for GBV) of brain volume differences between young cannabis users and nonusers. We conducted metaregressions to explore the role of age on volumetric differences. Results: Sixteen studies were included. The reviewed samples included 830 people with mean age 22.5 years (range 14-26 years). Of these, 386 were cannabis users (with cannabis use onset at 15-19 years) and 444 were controls. We found no detectable group differences in any of the GBVs (intracranium, total brain, total white matter, and total gray matter) and regional brain volumes (i.e., hippocampus, amygdala, orbitofrontal cortex, and total cerebellum). Age and cannabis use level did not predict (standardized mean) volume group differences in metaregression. We found little evidence of publication bias (Egger's test p>0.1). Conclusions: Contrary to evidence in adult samples (or in samples mixing adults and youth), previous single studies in young cannabis users, and meta-analyses of brain function in young cannabis users, this early evidence suggests nonsignificant volume differences between young cannabis users and nonusers. While prolonged and long-term exposure to heavy cannabis use may be required to detect gross volume alterations, more studies in young cannabis users are needed to map in detail cannabis-related neuroanatomical changes.
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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, Fitzroy, 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, Fitzroy, Australia
| | - Leonie Duehlmeyer
- 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, Fitzroy, Australia
| | - Lisa-Marie Greenwood
- Research School of Psychology, The Australian National University, Canberra, Australia
| | - Yann Chye
- BrainPark, The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Clayton, Australia
| | - Murat Yücel
- BrainPark, The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Clayton, Australia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton, Australia
| | - Carl A Roberts
- Department of Psychology, University of Liverpool, Liverpool, United Kingdom
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12
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Hill-Bowen LD, Riedel MC, Salo T, Flannery JS, Poudel R, Laird AR, Sutherland MT. Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies. Drug Alcohol Depend 2022; 240:109625. [PMID: 36115222 DOI: 10.1016/j.drugalcdep.2022.109625] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/01/2022] [Accepted: 09/06/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact. METHODS We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks. RESULTS Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal). CONCLUSIONS These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.
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Affiliation(s)
- Lauren D Hill-Bowen
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Michael C Riedel
- Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Jessica S Flannery
- Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, United States
| | - Ranjita Poudel
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Angela R Laird
- Department of Physics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States
| | - Matthew T Sutherland
- Department of Psychology, Florida International University, 11200 SW 8th Street, Miami, FL 33199, United States.
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13
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Brain Magnetic Resonance Imaging Features of Nicotine-Dependent Individuals and Its Correlation with Polymorphisms of Dopamine D Receptor Gene. CONTRAST MEDIA & MOLECULAR IMAGING 2022; 2022:2296776. [PMID: 36082055 PMCID: PMC9433208 DOI: 10.1155/2022/2296776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 07/12/2022] [Accepted: 07/15/2022] [Indexed: 11/17/2022]
Abstract
The aim of this research was developed to provide a scientific basis for individualized prevention, clinical diagnosis, and corrective treatment of nicotine addiction. The objects were 214 cases in the smoke group and 43 cases in the control group. According to the Fagerstrom Nicotine Dependence Test (FTND), the smokers were divided into mild nicotine dependence group (FTND < 6 points, 138 cases) and nicotine severe dependence group (≥6 points, 76 cases). The brain structure in long-term smokers was evaluated by using magnetic resonance imaging (MRI). The nicotine dependence was further analyzed by grouping the included individuals, and some candidate genes related to nicotine addiction were screened by combining with bioinformatics analysis. The family research strategy was adopted to detect nicotine addiction susceptibility genes and their polymorphisms. The MRI imaging results showed that the bilateral thalamus, right parietal, and left lens gram-molecule volume (GMV) were negatively correlated with smoking index and smoking years in the smoking group. The GMV of the posterior cingulate cortex in the severe nicotine dependence group was lower than that of the control group, and the GMVs of bilateral thalamus and bilateral superior limbic gyrus in the mild nicotine dependence group were lower than those of the control group. The gene polymorphism detection showed that rs6275 was highly polymorphic in the target population and the frequency of rs6275-C allele was 53.26%. Therefore, the MRI imaging characteristics suggested that the affected brain regions of smokers and people with varying degrees of nicotine dependence were mainly concentrated in response-related pathways and the limbic system and had cumulative effects on the central nervous system. In addition, the M6275 polymorphism of DRD2 gene was associated with susceptibility to nicotine addiction in Chinese population, and the M6275-C allele had a protective effect on susceptibility to nicotine addiction and smoking initiation.
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14
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Logtenberg E, Overbeek MF, Pasman JA, Abdellaoui A, Luijten M, van Holst RJ, Vink JM, Denys D, Medland SE, Verweij KJH, Treur JL. Investigating the causal nature of the relationship of subcortical brain volume with smoking and alcohol use. Br J Psychiatry 2022; 221:377-385. [PMID: 35049464 DOI: 10.1192/bjp.2021.81] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes. AIMS We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation. METHOD Mendelian randomisation uses genetic variants predictive of a certain 'exposure' as instrumental variables to test causal effects on an 'outcome'. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods. RESULTS There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects. CONCLUSIONS Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.
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Affiliation(s)
- Emma Logtenberg
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Martin F Overbeek
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Joëlle A Pasman
- Behavioural Science Institute, Radboud University Nijmegen, The Netherlands
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Maartje Luijten
- Behavioural Science Institute, Radboud University Nijmegen, The Netherlands
| | - Ruth J van Holst
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Jacqueline M Vink
- Behavioural Science Institute, Radboud University Nijmegen, The Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Sarah E Medland
- Psychiatric Genetics Group, QIMR Berghofer Medical Research Institute, Australia
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands
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15
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Hirjak D, Schmitgen MM, Werler F, Wittemann M, Kubera KM, Wolf ND, Sambataro F, Calhoun VD, Reith W, Wolf RC. Multimodal MRI data fusion reveals distinct structural, functional and neurochemical correlates of heavy cannabis use. Addict Biol 2022; 27:e13113. [PMID: 34808703 DOI: 10.1111/adb.13113] [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: 07/15/2021] [Revised: 09/24/2021] [Accepted: 10/29/2021] [Indexed: 12/19/2022]
Abstract
Heavy cannabis use (HCU) is frequently associated with a plethora of cognitive, psychopathological and sensorimotor phenomena. Although HCU is frequent, specific patterns of abnormal brain structure and function underlying HCU in individuals presenting without cannabis-use disorder or other current and life-time major mental disorders are unclear at present. This multimodal magnetic resonance imaging (MRI) study examined resting-state functional MRI (rs-fMRI) and structural MRI (sMRI) data from 24 persons with HCU and 16 controls. Parallel independent component analysis (p-ICA) was used to examine covarying components among grey matter volume (GMV) maps computed from sMRI and intrinsic neural activity (INA), as derived from amplitude of low-frequency fluctuations (ALFF) maps computed from rs-fMRI data. Further, we used JuSpace toolbox for cross-modal correlations between MRI-based modalities with nuclear imaging derived estimates, to examine specific neurotransmitter system changes underlying HCU. We identified two transmodal components, which significantly differed between the HCU and controls (GMV: p = 0.01, ALFF p = 0.03, respectively). The GMV component comprised predominantly cerebello-temporo-thalamic regions, whereas the INA component included fronto-parietal regions. Across HCU, loading parameters of both components were significantly associated with distinct HCU behavior. Finally, significant associations between GMV and the serotonergic system as well as between INA and the serotonergic, dopaminergic and μ-opioid receptor system were detected. This study provides novel multimodal neuromechanistic insights into HCU suggesting co-altered structure/function-interactions in neural systems subserving cognitive and sensorimotor functions.
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Affiliation(s)
- Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim Heidelberg University Mannheim Germany
| | - Mike M. Schmitgen
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Florian Werler
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Miriam Wittemann
- Department of Psychiatry and Psychotherapy Saarland University Saarbrücken Germany
| | - Katharina M. Kubera
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Nadine D. Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
| | - Fabio Sambataro
- Department of Neurosciences, Padua Neuroscience Center University of Padua Padua Italy
| | - Vince D. Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology Emory University Atlanta Georgia USA
| | - Wolfgang Reith
- Department of Neuroradiology Saarland University Saarbrücken Germany
| | - Robert Christian Wolf
- Department of General Psychiatry at the Center for Psychosocial Medicine Heidelberg University Mannheim Germany
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16
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Gutman BA, van Erp TG, Alpert K, Ching CRK, Isaev D, Ragothaman A, Jahanshad N, Saremi A, Zavaliangos‐Petropulu A, Glahn DC, Shen L, Cong S, Alnæs D, Andreassen OA, Doan NT, Westlye LT, Kochunov P, Satterthwaite TD, Wolf DH, Huang AJ, Kessler C, Weideman A, Nguyen D, Mueller BA, Faziola L, Potkin SG, Preda A, Mathalon DH, Bustillo J, Calhoun V, Ford JM, Walton E, Ehrlich S, Ducci G, Banaj N, Piras F, Piras F, Spalletta G, Canales‐Rodríguez EJ, Fuentes‐Claramonte P, Pomarol‐Clotet E, Radua J, Salvador R, Sarró S, Dickie EW, Voineskos A, Tordesillas‐Gutiérrez D, Crespo‐Facorro B, Setién‐Suero E, van Son JM, Borgwardt S, Schönborn‐Harrisberger F, Morris D, Donohoe G, Holleran L, Cannon D, McDonald C, Corvin A, Gill M, Filho GB, Rosa PGP, Serpa MH, Zanetti MV, Lebedeva I, Kaleda V, Tomyshev A, Crow T, James A, Cervenka S, Sellgren CM, Fatouros‐Bergman H, Agartz I, Howells F, Stein DJ, Temmingh H, Uhlmann A, de Zubicaray GI, McMahon KL, Wright M, Cobia D, Csernansky JG, Thompson PM, Turner JA, Wang L. A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium. Hum Brain Mapp 2022; 43:352-372. [PMID: 34498337 PMCID: PMC8675416 DOI: 10.1002/hbm.25625] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 01/06/2023] Open
Abstract
Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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Affiliation(s)
- Boris A. Gutman
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Institute for Information Transmission Problems (Kharkevich Institute)MoscowRussia
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Dmitry Isaev
- Department of Biomedical EngineeringDuke UniversityDurhamNorth CarolinaUSA
| | - Anjani Ragothaman
- Department of biomedical engineeringOregon Health and Science universityPortlandOregonUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Arvin Saremi
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Artemis Zavaliangos‐Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - David C. Glahn
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Li Shen
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shan Cong
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dag Alnæs
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Ole Andreas Andreassen
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Nhat Trung Doan
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Theodore D. Satterthwaite
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexander J. Huang
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Charles Kessler
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Andrea Weideman
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Dana Nguyen
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Lawrence Faziola
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Steven G. Potkin
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Adrian Preda
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Daniel H. Mathalon
- Department of Psychiatry and Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
| | - Juan Bustillo
- Departments of Psychiatry & NeuroscienceUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology]Emory UniversityAtlantaGeorgiaUSA
- Department of Electrical and Computer EngineeringThe University of New MexicoAlbuquerqueNew MexicoUSA
| | - Judith M. Ford
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental NeurosciencesFaculty of Medicine, TU‐DresdenDresdenGermany
| | | | - Nerisa Banaj
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Fabrizio Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Federica Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Gianfranco Spalletta
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | | | | | | | - Joaquim Radua
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
- Institut d'Investigacions Biomdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Erin W. Dickie
- Centre for Addiction and Mental Health (CAMH)TorontoCanada
| | | | | | | | | | | | - Stefan Borgwardt
- Department of PsychiatryUniversity of BaselBaselSwitzerland
- Department of Psychiatry and PsychotherapyUniversity of LübeckLübeckGermany
| | | | - Derek Morris
- Centre for Neuroimaging and Cognitive Genomics, Discipline of BiochemistryNational University of Ireland GalwayGalwayIreland
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Dara Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Geraldo Busatto Filho
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Hospital Sirio‐LibanesSao PauloSPBrazil
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Vasily Kaleda
- Department of Endogenous Mental DisordersMental Health Research CenterMoscowRussia
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Tim Crow
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Anthony James
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Simon Cervenka
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Carl M Sellgren
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden
| | - Helena Fatouros‐Bergman
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Ingrid Agartz
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Fleur Howells
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
- SA MRC Unit on Risk & Resilience in Mental DisordersUniversity of Cape TownCape TownWCSouth Africa
| | - Henk Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Department of Child and Adolescent PsychiatryTU DresdenGermany
| | - Greig I. de Zubicaray
- School of Psychology, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Katie L. McMahon
- School of Clinical SciencesQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Margie Wright
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQLDAustralia
| | - Derin Cobia
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychology and Neuroscience CenterBrigham Young UniversityProvoUtahUSA
| | - John G. Csernansky
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Lei Wang
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychiatry and Behavioral HealthOhio State University Wexner Medical CenterColumbusOhioUSA
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17
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Zhornitsky S, Chaudhary S, Le TM, Chen Y, Zhang S, Potvin S, Chao HH, van Dyck CH, Li CSR. Cognitive dysfunction and cerebral volumetric deficits in individuals with Alzheimer's disease, alcohol use disorder, and dual diagnosis. Psychiatry Res Neuroimaging 2021; 317:111380. [PMID: 34482052 PMCID: PMC8579376 DOI: 10.1016/j.pscychresns.2021.111380] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 08/22/2021] [Accepted: 08/25/2021] [Indexed: 10/20/2022]
Abstract
Epidemiological surveys suggest that excessive drinking is associated with higher risk of Alzheimer's disease (AD). The present study utilized data from the National Alzheimer's Coordinating Center to examine cognition as well as gray/white matter and ventricular volumes among participants with AD and alcohol use disorder (AD/AUD, n = 52), AD only (n = 701), AUD only (n = 67), and controls (n = 1283). AUD diagnosis was associated with higher Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) in AD than in non-AD. AD performed worse on semantic fluency and Trail Making Test A + B (TMT A + B) and showed smaller total GMV, WMV, and larger ventricular volume than non-AD. AD had smaller regional GMV in the inferior/superior parietal cortex, hippocampal formation, occipital cortex, inferior frontal gyrus, posterior cingulate cortex, and isthmus cingulate cortex than non-AD. AUD had significantly smaller somatomotor cortical GMV and showed a trend towards smaller volume in the hippocampal formation, relative to non-AUD participants. Misuse of alcohol has an additive effect on dementia severity among AD participants. Smaller hippocampal volume is a common feature of both AD and AUD. Although AD is associated with more volumetric deficits overall, AD and AUD are associated with atrophy in largely distinct brain regions.
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Affiliation(s)
- Simon Zhornitsky
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA.
| | - Shefali Chaudhary
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Thang M Le
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Yu Chen
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Sheng Zhang
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Stéphane Potvin
- Centre de recherche de l'Institut, Universitaire en Santé Mentale de Montréal, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, Université de Montréal, Montréal, QC, Canada
| | - Herta H Chao
- Department of Medicine, Yale University School of Medicine, New Haven, CT 06519, USA; VA Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Christopher H van Dyck
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA; Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA; Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, USA
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18
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Nutt D, Hayes A, Fonville L, Zafar R, Palmer EO, Paterson L, Lingford-Hughes A. Alcohol and the Brain. Nutrients 2021; 13:3938. [PMID: 34836193 PMCID: PMC8625009 DOI: 10.3390/nu13113938] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/01/2021] [Accepted: 11/02/2021] [Indexed: 12/20/2022] Open
Abstract
Alcohol works on the brain to produce its desired effects, e.g., sociability and intoxication, and hence the brain is an important organ for exploring subsequent harms. These come in many different forms such as the consequences of damage during intoxication, e.g., from falls and fights, damage from withdrawal, damage from the toxicity of alcohol and its metabolites and altered brain structure and function with implications for behavioral processes such as craving and addiction. On top of that are peripheral factors that compound brain damage such as poor diet, vitamin deficiencies leading to Wernicke-Korsakoff syndrome. Prenatal alcohol exposure can also have a profound impact on brain development and lead to irremediable changes of fetal alcohol syndrome. This chapter briefly reviews aspects of these with a particular focus on recent brain imaging results. Cardiovascular effects of alcohol that lead to brain pathology are not covered as they are dealt with elsewhere in the volume.
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Affiliation(s)
- David Nutt
- Neuropsychopharmacology Unit, Division of Psychiatry, Department of Brain Sciences, Hammersmith Hospital, Imperial College London, London W12 ONN, UK; (A.H.); (L.F.); (R.Z.); (E.O.C.P.); (L.P.); (A.L.-H.)
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19
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Boelens Keun JT, van Heese EM, Laansma MA, Weeland CJ, de Joode NT, van den Heuvel OA, Gool JK, Kasprzak S, Bright JK, Vriend C, van der Werf YD. Structural assessment of thalamus morphology in brain disorders: A review and recommendation of thalamic nucleus segmentation and shape analysis. Neurosci Biobehav Rev 2021; 131:466-478. [PMID: 34587501 DOI: 10.1016/j.neubiorev.2021.09.044] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 08/25/2021] [Accepted: 09/24/2021] [Indexed: 12/30/2022]
Abstract
The thalamus is a central brain structure crucially involved in cognitive, emotional, sensory, and motor functions and is often reported to be involved in the pathophysiology of neurological and psychiatric disorders. The functional subdivision of the thalamus warrants morphological investigation on the level of individual subnuclei. In addition to volumetric measures, the investigation of other morphological features may give additional insights into thalamic morphology. For instance, shape features offer a higher spatial resolution by revealing small, regional differences that are left undetected in volumetric analyses. In this review, we discuss the benefits and limitations of recent advances in neuroimaging techniques to investigate thalamic morphology in vivo, leading to our proposed methodology. This methodology consists of available pipelines for volume and shape analysis, focussing on the morphological features of volume, thickness, and surface area. We demonstrate this combined approach in a Parkinson's disease cohort to illustrate their complementarity. Considering our findings, we recommend a combined methodology as it allows for more sensitive investigation of thalamic morphology in clinical populations.
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Affiliation(s)
- Jikke T Boelens Keun
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Eva M van Heese
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Max A Laansma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Cees J Weeland
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Niels T de Joode
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Jari K Gool
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; SEIN, Heemstede, the Netherlands; Department of Neurology, LUMC, Leiden, the Netherlands
| | - Selina Kasprzak
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Joanna K Bright
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Ysbrand D van der Werf
- Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
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20
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Muller AM, Meyerhoff DJ. Frontocerebellar gray matter plasticity in alcohol use disorder linked to abstinence. NEUROIMAGE-CLINICAL 2021; 32:102788. [PMID: 34438322 PMCID: PMC8387922 DOI: 10.1016/j.nicl.2021.102788] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/08/2021] [Accepted: 08/10/2021] [Indexed: 12/26/2022]
Abstract
GM loss in frontocerebellar circuit predicts relapse. GM recovery in AUD involves distinct neural processes. Recovery is not a reversal of any AUD-related GM damage.
Alcohol use disorder (AUD) is associated with brain-wide gray matter (GM) reduction, but the frontocerebellar circuit seems specifically affected by chronic alcohol consumption. T1 weighted MRI data from 38 AUD patients at one month of sobriety and three months later and from 25 controls were analyzed using voxel-based morphometry (VBM) and a graph theory approach (GTA). We investigated the degree to which the frontocerebellar circuit’s integration within the brain’s GM network architecture was altered by AUD-related GM volume loss. The VBM analyses did not reveal significant GM volume differences between relapsers and abstainers at either timepoint, but future relapsers at both timepoints had significantly less GM than controls in the frontocerebellar circuit. Abstainers, who at baseline also showed the most pronounced GM loss in the thalamus, showed a significant circuit-wide GM increase with inter-scan abstinence. The post-hoc GTAs revealed a persistent diffuse global atrophy in both AUD groups at follow-up relative to controls and different recovery patterns in the two AUD groups. Our findings suggest that future relapsers do not just present with a more severe expression of the same AUD consequences than abstainers, but that AUD affects the frontocerebellar circuit differently in relapsers and abstainers.
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Affiliation(s)
- Angela M Muller
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA; VA Advanced Imaging Research Center (VAARC), San Francisco VA Medical Center, San Francisco, CA, USA.
| | - Dieter J Meyerhoff
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA; VA Advanced Imaging Research Center (VAARC), San Francisco VA Medical Center, San Francisco, CA, USA
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21
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Smit DJA, Andreassen OA, Boomsma DI, Burwell SJ, Chorlian DB, de Geus EJC, Elvsåshagen T, Gordon RL, Harper J, Hegerl U, Hensch T, Iacono WG, Jawinski P, Jönsson EG, Luykx JJ, Magne CL, Malone SM, Medland SE, Meyers JL, Moberget T, Porjesz B, Sander C, Sisodiya SM, Thompson PM, van Beijsterveldt CEM, van Dellen E, Via M, Wright MJ. Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity. Brain Behav 2021; 11:e02188. [PMID: 34291596 PMCID: PMC8413828 DOI: 10.1002/brb3.2188] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 03/12/2021] [Accepted: 04/30/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND AND PURPOSE The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain. METHODS We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations. RESULTS We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters. CONCLUSION The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.
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Affiliation(s)
- Dirk J A Smit
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Scott J Burwell
- Department of Psychology, Minnesota Center for Twin and Family Research, University of Minnesota, Minneapolis, MN, USA.,Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David B Chorlian
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Reyna L Gordon
- Department of Otolaryngology, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.,Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jeremy Harper
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics, and Psychotherapy, Goethe Universität Frankfurt am Main, Frankfurt, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany.,LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,IU International University, Erfurt, Germany
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Philippe Jawinski
- LIFE - Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Erik G Jönsson
- TOP-Norment, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Jurjen J Luykx
- Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.,Outpatient Second Opinion Clinic, GGNet Mental Health, Apeldoorn, The Netherlands
| | - Cyrille L Magne
- Psychology Department, Middle Tennessee State University, Murfreesboro, TN, USA.,Literacy Studies Ph.D. Program, Middle Tennessee State University, Mufreesboro, TN, USA
| | - Stephen M Malone
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jacquelyn L Meyers
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA.,Department of Psychiatry, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Torgeir Moberget
- Department of Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, Downstate Health Sciences University, Brooklyn, NY, USA
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Chalfont Centre for Epilepsy, Chalfont-St-Peter, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Edwin van Dellen
- Department of Psychiatry, Department of Intensive Care Medicine, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Marc Via
- Brainlab-Cognitive Neuroscience Research Group, Department of Clinical Psychology and Psychobiology, and Institute of Neurosciences (UBNeuro), Universitat de Barcelona, Barcelona, Spain.,Institut de Recerca Sant Joan de Déu (IRSJD), Esplugues de Llobregat, Spain
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
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Tomasi D, Wiers CE, Manza P, Shokri-Kojori E, Michele-Vera Y, Zhang R, Kroll D, Feldman D, McPherson K, Biesecker C, Schwandt M, Diazgranados N, Koob GF, Wang GJ, Volkow ND. Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction. Cereb Cortex 2021; 31:3254-3265. [PMID: 33629726 DOI: 10.1093/cercor/bhab006] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/04/2021] [Accepted: 01/07/2021] [Indexed: 02/07/2023] Open
Abstract
Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-based classifier (MC) was developed to identify subcortical volumes that distinguished 32 healthy controls (HCs) from 33 AUD patients, who were scanned twice, during early and later withdrawal, to assess the effect of abstinence on MC-features (Discovery cohort). We validated the novel classifier in an independent Validation cohort (19 AUD patients and 20 HCs). MC-accuracy reached 80% (Discovery) and 72% (Validation). MC features included the hippocampus, amygdala, cerebellum, putamen, corpus callosum, and brain stem, which were smaller and showed stronger age-related decreases in AUD than HCs, and the ventricles and cerebrospinal fluid, which were larger in AUD and older participants. The volume of the amygdala showed a positive association with anxiety and negative urgency in AUD. Repeated imaging during the third week of detoxification revealed slightly larger subcortical volumes in AUD patients, consistent with partial recovery during abstinence. The steeper age-associated volumetric reductions in stress- and reward-related subcortical regions in AUD are consistent with accelerated aging, whereas the amygdalar associations with negative urgency and anxiety in AUD patients support its involvement in the "dark side of addiction".
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Affiliation(s)
- Dardo Tomasi
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Corinde E Wiers
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Peter Manza
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | | | - Yonga Michele-Vera
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Rui Zhang
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Danielle Kroll
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Dana Feldman
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | | | | | - Melanie Schwandt
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nancy Diazgranados
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - George F Koob
- National Institute on Drug Abuse, Bethesda, MD 21224, USA
| | - Gene-Jack Wang
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
| | - Nora D Volkow
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA
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23
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Muller AM, Pennington DL, Meyerhoff DJ. Substance-Specific and Shared Gray Matter Signatures in Alcohol, Opioid, and Polysubstance Use Disorder. Front Psychiatry 2021; 12:795299. [PMID: 35115969 PMCID: PMC8803650 DOI: 10.3389/fpsyt.2021.795299] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Substance use disorders (SUD) have been shown to be associated with gray matter (GM) loss, particularly in the frontal cortex. However, unclear is to what degree these regional GM alterations are substance-specific or shared across different substances, and if these regional GM alterations are independent of each other or the result of system-level processes at the intrinsic connectivity network level. The T1 weighted MRI data of 65 treated patients with alcohol use disorder (AUD), 27 patients with opioid use disorder (OUD) on maintenance therapy, 21 treated patients with stimulant use disorder comorbid with alcohol use disorder (polysubstance use disorder patients, PSU), and 21 healthy controls were examined via data-driven vertex-wise and voxel-wise GM analyses. Then, structural covariance analyses and open-access fMRI database analyses were used to map the cortical thinning patterns found in the three SUD groups onto intrinsic functional systems. Among AUD and OUD, we identified both common cortical thinning in right anterior brain regions as well as SUD-specific regional GM alterations that were not present in the PSU group. Furthermore, AUD patients had not only the most extended regional thinning but also significantly smaller subcortical structures and cerebellum relative to controls, OUD and PSU individuals. The system-level analyses revealed that AUD and OUD showed cortical thinning in several functional systems. In the AUD group the default mode network was clearly most affected, followed by the salience and executive control networks, whereas the salience and somatomotor network were highlighted as critical for understanding OUD. Structural brain alterations in groups with different SUDs are largely unique in their spatial extent and functional network correlates.
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Affiliation(s)
- Angela M Muller
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States.,VA Advanced Imaging Research Center (VAARC), San Francisco VA Medical Center, San Francisco, CA, United States
| | - David L Pennington
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, United States.,San Francisco Veterans Affairs Health Care System (SFVAHCS), San Francisco, CA, United States
| | - Dieter J Meyerhoff
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States.,VA Advanced Imaging Research Center (VAARC), San Francisco VA Medical Center, San Francisco, CA, United States
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