1
|
Zhang M, Niu X, Dang J, Sun J, Tao Q, Wang W, Han S, Cheng J, Zhang Y. Neuroanatomical subtypes of tobacco use disorder and relationship with clinical and molecular features. Prog Neuropsychopharmacol Biol Psychiatry 2024; 136:111235. [PMID: 39732318 DOI: 10.1016/j.pnpbp.2024.111235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 12/05/2024] [Accepted: 12/21/2024] [Indexed: 12/30/2024]
Abstract
BACKGROUND Individual neurobiological heterogeneity among patients with tobacco use disorder (TUD) hampers the identification of neuroimaging phenotypes. METHODS The current study recruited 122 TUD individuals and 57 healthy controls, and obtained their 3D-T1 images. Heterogeneity through discriminative analysis (HYDRA) was applied to uncover the potential subtype of TUD where regional gray matter volume (GMV) was treated as the feature. Then we examined the clinical, neuroimaging and molecular characteristics of subtypes. RESULTS Two distinct neuroanatomical subtypes were found. In subtype 1, TUD individuals showed decreased GMV in right orbitofrontal cortex (OFC), while subtype 2 exhibited distributed pattern of widely GMV increase. Moreover, subtype 1 showed older initial smoking age, longer duration of smoking than Subtype 2. Persistent smoking behavior in subtype 1 is more likely caused by substance dependence/addiction rather than psychosocial factors. GMV correlated negatively with cumulative tobacco exposure in Subtype 1 but not in Subtype 2. Besides, neuroanatomical aberrance in subtype 1 was mainly associated with dopamine system, while neuroanatomical abnormalities in subtype 2 were primarily associated with GABAa. CONCLUSIONS Overall, our results revealed two opposite neuroanatomical subtypes of TUD, which largely overlapped with their clinical and molecular features respectively. TUD subtypes taxonomy based on objective anatomy could help to facilitate the development of individualized treatment for TUD.
Collapse
Affiliation(s)
- Mengzhe Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China.
| |
Collapse
|
2
|
Chen X, Long K, Liu S, Cai Y, Cheng L, Chen W, Lin F, Lei H. Repeated exposure to high-dose nicotine induces prefrontal gray matter atrophy in adolescent male rats. Neuroscience 2024:S0306-4522(24)00650-X. [PMID: 39631662 DOI: 10.1016/j.neuroscience.2024.11.059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 11/07/2024] [Accepted: 11/24/2024] [Indexed: 12/07/2024]
Abstract
Incidences of seizure after e-cigarette use in adolescents and young adults have been reported, raising the concern about the risk of nicotine overconsumption. Few previous studies have investigated the effects of nicotine at high doses on brain and behavior in adolescent animals. In this study, the effects of a 15-day repeated nicotine treatment at a daily dose of 2 mg/kg body weight were investigated in adolescent and adult male rats. Nicotine treatment abolished body weight gain in the adults, but did not affect the body weight significantly in the adolescents. Only the nicotine-treated adolescents showed significant changes in brain anatomy 1 day post-treatment, which manifested as a significant reduction of whole-brain gray matter (GM) volume, a further reduction of regional GM volume in the medial prefrontal cortex (mPFC) and altered GM volume covariations between the mPFC and a number of brain regions. The mPFC of nicotine-treated adolescent rats did not exhibit evident signs of neuronal degeneration and reactive astrocytosis, but showed a significantly decreased expression of presynaptic marker synaptophysin (SYN), along with a significantly increased oxidative stress and a significantly elevated expressions of microglial marker ionized calcium binding adaptor molecule 1 (IBA1). Together, these results suggested that repeated nicotine overdosing may shift regional redox, modulate microglia-mediated pruning, and give rise to structural/connectivity deficits in the mPFC of adolescent male rats.
Collapse
Affiliation(s)
- Xi Chen
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Kehong Long
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Sijie Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Yue Cai
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Linlin Cheng
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, PR China
| | - Wei Chen
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Fuchun Lin
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China
| | - Hao Lei
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei, PR China; University of Chinese Academy of Sciences, Beijing, PR China; Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei, PR China.
| |
Collapse
|
3
|
Anderson NE, Maurer JM, Stephenson D, Harenski K, Caldwell M, Van Rybroek G, Kiehl KA. Striatal brain volume linked to severity of substance use in high-risk incarcerated youth. Dev Psychopathol 2024:1-10. [PMID: 38738358 DOI: 10.1017/s0954579424000804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Abstract
Substance use disorders among juveniles are a major public health concern and are often intertwined with other psychosocial risk factors including antisocial behavior. Identifying etiological risks and mechanisms promoting substance use disorders remains a high priority for informing more focused interventions in high-risk populations. The present study examined brain gray matter structure in relation to substance use severity among n = 152 high-risk, incarcerated boys (aged 14-20). Substance use severity was positively associated with gray matter volume across several frontal/striatal brain regions including amygdala, pallidum, putamen, insula, and orbitofrontal cortex. Effects were apparent when using voxel-based-morphometric analysis, as well as in whole-brain, data-driven, network-based approaches (source-based morphometry). These findings support the hypothesis that elevated gray matter volume in striatal reward circuits may be an endogenous marker for vulnerability to severe substance use behaviors among youth.
Collapse
Affiliation(s)
| | | | | | | | - Michael Caldwell
- Mendota Mental Health Institute, Madison, WI, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Greg Van Rybroek
- Mendota Mental Health Institute, Madison, WI, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Kent A Kiehl
- The Mind Research Network, Albuquerque, NM, USA
- Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| |
Collapse
|
4
|
Weidler C, Gramegna C, Müller D, Schrickel M, Habel U. Resting-state functional connectivity and structural differences between smokers and healthy non-smokers. Sci Rep 2024; 14:6878. [PMID: 38519565 PMCID: PMC10960011 DOI: 10.1038/s41598-024-57510-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 03/19/2024] [Indexed: 03/25/2024] Open
Abstract
Previous studies have shown an association between cigarette use and altered resting-state functional connectivity (rsFC) in many large-scale networks, sometimes complemented by measures of cortical atrophy. In this study, we aimed to further explore the neural differences between smokers and healthy non-smokers through the integration of functional and structural analyses. Imaging data of fifty-two smokers and forty-five non-smokers were analyzed through an independent component analysis for group differences in rsFC. Smokers showed lower rsFC within the dorsal attention network (DAN) in the left superior and middle frontal gyrus and left superior division of the lateral occipital cortex compared to non-smokers; moreover, cigarette use was found to be associated with reduced grey matter volume in the left superior and middle frontal gyrus and right orbitofrontal cortex, partly overlapping with functional findings. Within smokers, daily cigarette consumption was positively associated with increased rsFC within the cerebellar network and the default mode network and decreased rsFC within the visual network and the salience network, while carbon monoxide level showed a positive association with increased rsFC within the sensorimotor network. Our results suggest that smoking negatively impacts rsFC within the DAN and that changes within this network might serve as a circuit-based biomarker for structural deficits.
Collapse
Affiliation(s)
- Carmen Weidler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
| | - Chiara Gramegna
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany.
- PhD Program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
- Department of Psychology, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, 20126, Milan, Italy.
| | - Dario Müller
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany
| | - Maike Schrickel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany
| | - Ute Habel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Germany
- Institute of Neuroscience and Medicine, JARA-Institute Brain Structure Function Relationship (INM 10), Research Center Jülich, Jülich, Germany
| |
Collapse
|
5
|
Wang W, Kang Y, Niu X, Zhang Z, Li S, Gao X, Zhang M, Cheng J, Zhang Y. Connectome-based predictive modeling of smoking severity using individualized structural covariance network in smokers. Front Neurosci 2023; 17:1227422. [PMID: 37547147 PMCID: PMC10400777 DOI: 10.3389/fnins.2023.1227422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 07/04/2023] [Indexed: 08/08/2023] Open
Abstract
Introduction Abnormal interactions among distributed brain systems are implicated in the mechanisms of nicotine addiction. However, the relationship between the structural covariance network, a measure of brain connectivity, and smoking severity remains unclear. To fill this gap, this study aimed to investigate the relationship between structural covariance network and smoking severity in smokers. Methods A total of 101 male smokers and 51 male non-smokers were recruited, and they underwent a T1-weighted anatomical image scan. First, an individualized structural covariance network was derived via a jackknife-bias estimation procedure for each participant. Then, a data-driven machine learning method called connectome-based predictive modeling (CPM) was conducted to infer smoking severity measured with Fagerström Test for Nicotine Dependence (FTND) scores using an individualized structural covariance network. The performance of CPM was evaluated using the leave-one-out cross-validation and a permutation testing. Results As a result, CPM identified the smoking severity-related structural covariance network, as indicated by a significant correlation between predicted and actual FTND scores (r = 0.23, permutation p = 0.020). Identified networks comprised of edges mainly located between the subcortical-cerebellum network and networks including the frontoparietal default model and motor and visual networks. Discussion These results identified smoking severity-related structural covariance networks and provided a new insight into the neural underpinnings of smoking severity.
Collapse
|
6
|
von Deneen KM, Hussain H, Waheed J, Xinwen W, Yu D, Yuan K. Comparison of frontostriatal circuits in adolescent nicotine addiction and internet gaming disorder. J Behav Addict 2022; 11:26-39. [PMID: 35049521 PMCID: PMC9109629 DOI: 10.1556/2006.2021.00086] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/08/2021] [Accepted: 12/16/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Recently, there has been significantly increased participation in online gaming and other addictive behaviors particularly in adolescents. Tendencies to avoid social interaction and become more involved in technology-based activities pose the danger of creating unhealthy addictions. Thus, the presence of relatively immature cognitive control and high risk-taking properties makes adolescence a period of major changes leading to an increased rate of emotional disorders and addiction. AIMS The critical roles of frontostriatal circuits in addiction have become the primary focus associated with reward in the striatum and cognitive control in the PFC. Internet gaming disorder (IGD) and nicotine addiction are currently becoming more and more serious. METHODS In the light of neuroimaging, the similarity between brain mechanisms causing substance use disorder (SUD) and IGD have been described in previous literature. RESULTS In particular, two distinct brain systems affect the way we act accounting for uncharacteristic neural function in addiction: the affective system comprises of the striatum driven by emotional, reward-related, and internal stimuli, and a cognitive system consisting of the prefrontal cortex (PFC) supporting the ventral affective system's actions via inhibitory control. DISCUSSION AND CONCLUSION Therefore, as a novel concept, we focused on the implication of frontostriatal circuits in nicotine addiction and IGD by reviewing the main findings from our studies compared to those of others. We hope that all of these neuroimaging findings can lead to effective intervention and treatment for addiction especially during this critical period.
Collapse
Affiliation(s)
- Karen M. von Deneen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China,Corresponding authors. E-mail: (), ,
| | - Hadi Hussain
- Xi'an Jiaotong University, 74 Yanta Street, Yanta District, Xi'an, Shaanxi 710001, Peoples R China
| | - Junaid Waheed
- Xi'an Jiaotong University, 74 Yanta Street, Yanta District, Xi'an, Shaanxi 710001, Peoples R China
| | - Wen Xinwen
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, Peoples R China,Corresponding authors. E-mail: (), ,
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, Peoples R China,Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia 014010, Peoples R China,Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi'an, Shaanxi, 710071, Peoples R China,Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710126, Peoples R China,Corresponding authors. E-mail: (), ,
| |
Collapse
|
7
|
Zhang M, Gao X, Yang Z, Wen M, Huang H, Zheng R, Wang W, Wei Y, Cheng J, Han S, Zhang Y. Shared gray matter alterations in subtypes of addiction: a voxel-wise meta-analysis. Psychopharmacology (Berl) 2021; 238:2365-2379. [PMID: 34313804 DOI: 10.1007/s00213-021-05920-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 07/05/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND Numerous studies based on voxel-based morphometry (VBM) have revealed gray matter (GM) alterations in multiple brain regions for addiction. However, findings are poorly replicated, and it remains elusive whether distinct diagnoses of addiction are underpinned by shared abnormalities. Our aim was to conduct a quantitative meta-analysis of structural neuroimaging studies investigating GM abnormalities in two main categories of addiction: substance use disorders (SUD) and behavioral addictions (BA). METHOD A systematic database search was conducted in several databases from Jan 1, 2010, to Oct 23, 2020, to identify eligible VBM studies. Meta-analysis was performed with the seed-based d mapping software package to compare alternations between individuals with addiction-related disorders and healthy controls (HC). RESULTS A total of 59 VBM studies including 2096 individuals with addiction-related disorders and 2637 HC met the inclusion criteria. Individuals with addiction-related disorders showed shared GM volume decrease in bilateral prefrontal cortex, bilateral insula, bilateral rolandic operculum, left superior temporal gyrus, and right Heschl gyrus and GM increase in right lingual gyrus and right fusiform gyrus comparing with HC (p < 0.005). Subgroup analysis found heterogeneity between SUD and BA mainly in left inferior occipital gyrus and right striatum (p < 0.005). Meta-regression revealed that GM atrophy in right anterior cingulate (r = 0.541, p = 0.03 (uncorrected)) and left inferior frontal gyrus (r = 0.595, p = 0.015) were positively correlated with higher impulsivity. CONCLUSIONS This meta-analysis identified a concordance across subtypes of addiction in terms of the brain structural changes in prefrontal and insula areas, which may relate to higher impulsivity observed across addiction diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates in addiction.
Collapse
Affiliation(s)
- Mengzhe Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xinyu Gao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhengui Yang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mengmeng Wen
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huiyu Huang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ruiping Zheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weijian Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yarui Wei
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Shaoqiang Han
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Yong Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| |
Collapse
|
8
|
Li Y, Zhang L, Zhang R, Xu T, Feng T. The Neural Basis Linking Achievement Motivation With Procrastination: Left Precuneus Connectivity With Right Anterior Cingulate Cortex. PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN 2021; 48:1382-1392. [PMID: 34407664 DOI: 10.1177/01461672211040677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Procrastination adversely affects individual's learning, working, health, and well-being, which troubles many people around the world. Previous studies have indicated that people with higher achievement motivation tend to have less procrastination. However, how achievement motivation is linked with procrastination at the neural level is still poorly understood. Here, we adopted the voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) methods to study this issue. The VBM analysis revealed that higher achievement motivation was correlated with larger gray matter volumes in left precuneus (lPre). Furthermore, the RSFC results showed that the functional connectivity between lPre and right anterior cingulate cortex (rACC) was positively associated with achievement motivation and negatively correlated with procrastination. More importantly, a mediation analysis demonstrated that achievement motivation fully mediated the relation between lPre-rACC connectivity and procrastination. These findings suggested that lPre-rACC coupling might be the neural correlate underlying the association between achievement motivation and procrastination.
Collapse
Affiliation(s)
- Yuhua Li
- Southwest University, Chongqing, China
| | | | | | - Ting Xu
- Southwest University, Chongqing, China
| | - Tingyong Feng
- Southwest University, Chongqing, China.,Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China
| |
Collapse
|
9
|
Pando-Naude V, Toxto S, Fernandez-Lozano S, Parsons CE, Alcauter S, Garza-Villarreal EA. Gray and white matter morphology in substance use disorders: a neuroimaging systematic review and meta-analysis. Transl Psychiatry 2021; 11:29. [PMID: 33431833 PMCID: PMC7801701 DOI: 10.1038/s41398-020-01128-2] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 11/10/2020] [Accepted: 11/20/2020] [Indexed: 12/16/2022] Open
Abstract
Substance use disorders (SUDs) are characterized by a compulsion to seek and consume one or more substances of abuse, with a perceived loss of control and a negative emotional state. Prolonged substance use seems to be associated with morphological changes of multiple neural circuits, in particular the frontal-striatal and limbic pathways. Such neuroadaptations are evident across several substance disorders, but may vary depending on the type of substance, consumption severity and/or other unknown factors. We therefore identified studies investigating the effects of SUDs using volumetric whole-brain voxel-based morphometry (VBM) in gray (GM) and white matter (WM). We performed a systematic review and meta-analysis of VBM studies using the anatomic likelihood estimation (ALE) method implemented in GingerALE (PROSPERO pre-registration CRD42017071222 ). Sixty studies met inclusion criteria and were included in the final quantitative meta-analysis, with a total of 614 foci, 94 experiments and 4938 participants. We found convergence and divergence in brain regions and volume effects (higher vs. lower volume) in GM and WM depending on the severity of the consumption pattern and type of substance used. Convergent pathology was evident across substances in GM of the insula, anterior cingulate cortex, putamen, and thalamus, and in WM of the thalamic radiation and internal capsule bundle. Divergent pathology between occasional use (cortical pathology) and addiction (cortical-subcortical pathology) provides evidence of a possible top-down neuroadaptation. Our findings indicate particular brain morphometry alterations in SUDs, which may inform our understanding of disease progression and ultimately therapeutic approaches.
Collapse
Affiliation(s)
- Victor Pando-Naude
- Department of Clinical Medicine, Center for Music in the Brain, University of Aarhus, Aarhus, Denmark
| | - Sebastian Toxto
- Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM) campus Juriquilla, Queretaro, Mexico
- Instituto Nacional de Psiquiatría "Ramón de la Fuente Muñiz", Mexico City, Mexico
- Facultad de Medicina, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | - Sofia Fernandez-Lozano
- Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM) campus Juriquilla, Queretaro, Mexico
- Facultad de Psicología, Universidad Nacional Autónoma de México (UNAM), Mexico City, Mexico
| | - Christine E Parsons
- Department of Clinical Medicine, Interacting Minds Center, University of Aarhus, Aarhus, Denmark
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM) campus Juriquilla, Queretaro, Mexico
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM) campus Juriquilla, Queretaro, Mexico.
- Department of Clinical Medicine, Center of Functionally Integrative Neuroscience, University of Aarhus, Aarhus, Denmark.
| |
Collapse
|
10
|
Yang Z, Zhang Y, Cheng J, Zheng R. Meta-analysis of brain gray matter changes in chronic smokers. Eur J Radiol 2020; 132:109300. [PMID: 33010686 DOI: 10.1016/j.ejrad.2020.109300] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 09/11/2020] [Accepted: 09/13/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND Previous studies based on voxel-based morphometry (VBM) had revealed brain gray matter (GM) changes in chronic smokers relative to nonsmokers. However, not all studies reported entirely consistent findings, or even opposite. The aim of this study was to conduct a quantitative meta-analysis of VBM studies of chronic smokers. METHOD A systematic database search was conducted in PubMed and Web of Knowledge from January 1, 2000 to January 31, 2020 to identify eligible VBM studies. Meta-analysis was performed with the Seed-based d Mapping software package to compare alternations between chronic cigarette smokers and nonsmokers. In addition, meta-regression analysis were performed to examine the influences of cigarette per day, smoking history and FTND. RESULTS A total of 17 VBM studies including 905 smokers and 1344 nonsmokers met the inclusion criteria. The results of this meta-analysis showed that the chronic smokers showed a robust GM volume decrease in bilateral prefrontal cortex and left insular and a GM increase in the right lingual cortex and left occipital cortex. Moreover, meta-regression analysis showed that cigarette per day, smoking history and FTND were partly associated with GM changes in chronic smokers. CONCLUSIONS This meta-analysis indicated that chronic cigarette smokers had significant and robust brain GM alternations compared with nonsmokers. Longitudinal studies should be performed in the future to explore whether these brain regions could be used as potential therapeutic neuro-target for nicotine dependence.
Collapse
Affiliation(s)
- Zhengui Yang
- First Affiliated Hospital of Zhengzhou University 450002, Zhengzhou, China
| | - Yong Zhang
- First Affiliated Hospital of Zhengzhou University 450002, Zhengzhou, China.
| | - Jingliang Cheng
- First Affiliated Hospital of Zhengzhou University 450002, Zhengzhou, China
| | - Ruiping Zheng
- First Affiliated Hospital of Zhengzhou University 450002, Zhengzhou, China
| |
Collapse
|
11
|
Xue T, Dong F, Huang R, Tao Z, Tang J, Cheng Y, Zhou M, Hu Y, Li X, Yu D, Ju H, Yuan K. Dynamic Neuroimaging Biomarkers of Smoking in Young Smokers. Front Psychiatry 2020; 11:663. [PMID: 32754067 PMCID: PMC7367415 DOI: 10.3389/fpsyt.2020.00663] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 06/26/2020] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE To examine potential changes in the dynamic characteristics of regional neural activity in young smokers and to detect whether the changes were associated with smoking behavior. METHODS The dynamic regional homogeneity (dReHo) and dynamic amplitude of low-frequency fluctuations (dALFF) in 40 young smokers and 42 nonsmokers were compared. Correlation analyses were also performed between dReHo and dALFF in areas showing group differences and smoking behavior [e.g., the Fagerström Test for Nicotine dependence (FTND) scores and pack-years]. RESULTS Significantly differences in dReHo variability were observed in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), medial frontal gyrus (MFG), insula, cuneus, postcentral gyrus, inferior semi-lunar lobule, orbitofrontal gyrus, and inferior temporal gyrus (ITG). Young smokers also showed significantly increased dALFF variability in the anterior cingulate cortex (ACC) and ITG. Furthermore, a significant positive correlation was found between dALFF variability in the ACC and the pack-years; whereas a significant negative correlation between dReHo variability in the IFG and the FTND scores was found in young smokers. CONCLUSION The pattern of resting state regional neural activity variability was different between young smokers and nonsmokers. Dynamic regional indexes might be a novel neuroimaging biomarker of smoking behavior in young smokers.
Collapse
Affiliation(s)
- Ting Xue
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ruoyan Huang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Zhanlong Tao
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
| | - Jun Tang
- School of Science, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yongxin Cheng
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Mi Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yiting Hu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xiaojian Li
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Haitao Ju
- Department of Neurosurgery, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
- Life Sciences Research Center, School of Life Science and Technology, Xidian University, Xi’an, China
| |
Collapse
|
12
|
Liu C, Dong F, Li Y, Ren Y, Xie D, Wang X, Xue T, Zhang M, Ren G, von Deneen KM, Yuan K, Yu D. 12 h Abstinence-Induced ERP Changes in Young Smokers: Electrophysiological Evidence From a Go/NoGo Study. Front Psychol 2019; 10:1814. [PMID: 31474901 PMCID: PMC6703154 DOI: 10.3389/fpsyg.2019.01814] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 07/22/2019] [Indexed: 11/13/2022] Open
Abstract
Decreased inhibition control ability and increased craving may be the most important causes of relapsing in smoking. Although inhibition control defects in young smokers were investigated, the effects of short-term abstinence on inhibition control in young smokers were still unclear. Thirty young smokers participated in the present study. The EEG signals during the Go/NoGo task were recorded in both satiety and 12 h abstinence conditions. The task performances were observed and compared between the two conditions. Event-related potential (ERP) analysis was used to investigate changes in N200 and P300 amplitude and latency induced by 12 h of abstinence. After 12 h of abstinence, the latency of N200 was prolonged in young smokers. No significant changes were found in the number of NoGo errors and the response time of Go in young smokers after 12 h of abstinence. Correlation analysis showed that the N200 latency of abstinence condition was significantly correlated with the number of NoGo errors and the response time of Go in the abstinence condition. The present findings may improve the understanding of the effect of short-term abstinence in young smokers. We suggested that the latency of N200 may be associated with inefficient inhibitory control of the abstinence condition in young smokers. Our results may contribute new insights into the neural mechanism of nicotine abstinence in young smokers.
Collapse
Affiliation(s)
- Chang Liu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Yangding Li
- Guangxi Key Laboratory of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, China
| | - Yan Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Dongdong Xie
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Xianfu Wang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ming Zhang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | - Guoyin Ren
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| | | | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
- Guangxi Key Laboratory of Multi-Source Information Mining and Security, Guangxi Normal University, Guilin, China
- School of Life Sciences and Technology, Xidian University, Xi’an, China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, China
| |
Collapse
|
13
|
Lin F, Wu G, Zhu L, Lei H. Region-Specific Changes of Insular Cortical Thickness in Heavy Smokers. Front Hum Neurosci 2019; 13:265. [PMID: 31417384 PMCID: PMC6685069 DOI: 10.3389/fnhum.2019.00265] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 07/16/2019] [Indexed: 11/13/2022] Open
Abstract
Insula plays an essential role in maintaining the addiction to cigarette smoking and smoking-related alterations on the insular volume and density have been reported in smokers. However, less is known about the effects of chronic cigarette smoking on the insular cortical thickness. In this study, we explored the region-specific changes of insular cortical thickness in heavy smokers and their relations with smoking-related variables. 37 heavy smokers (29 males, mean age 47.19 ± 7.22 years) and 37 non-smoking healthy controls (29 males, mean age 46.95 ± 8.45 years) participated in the study. Subregional insular cortical thickness was evaluated and compared between the two groups. Correlation analysis was performed to investigate relationships between the insular cortical thickness and clinical characteristics in heavy smokers. There was no statistical difference on the cortical thickness in the left insula (p = 0.536) between the two groups while heavy smokers had a slightly thinner cortical thickness in the right insula (p = 0.048). In addition, heavy smokers showed a greater cortical thinning in the anterior (p = 0.0084) and superior (p = 0.0054) segment of the circular sulcus of the right insula as well as the inferior (p = 0.012) segment of the circular sulcus of the left insula. Moreover, the cortical thickness of the superior segment of the circular sulcus of the left insula was correlated negatively with nicotine severity (r = −0.423; p = 0.009) and the longer cigarette exposure was associated with the cortical thinning in the long insular gyrus and central sulcus of the right insula (r = −0.475; p = 0.003). Our findings indicate that chronic cigarette use is associated with region-specific insular thinning, which has the potential to improve our understanding of the specific roles of insular subregions in nicotine addiction.
Collapse
Affiliation(s)
- Fuchun Lin
- National Center for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Guangyao Wu
- Department of Radiology, Zhongnan Hospital, Wuhan University, Wuhan, China.,Department of Medical Imaging, Shenzhen University General Hospital, Medical College of Shenzhen University, Shenzhen, China
| | - Ling Zhu
- Department of Radiology, Zhongnan Hospital, Wuhan University, Wuhan, China
| | - Hao Lei
- National Center for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China.,University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
14
|
Yuan K, Yu D, Bi Y, Wang R, Li M, Zhang Y, Dong M, Zhai J, Li Y, Lu X, Tian J. The left dorsolateral prefrontal cortex and caudate pathway: New evidence for cue-induced craving of smokers. Hum Brain Mapp 2017; 38:4644-4656. [PMID: 28653791 PMCID: PMC6866730 DOI: 10.1002/hbm.23690] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 06/05/2017] [Accepted: 06/09/2017] [Indexed: 01/17/2023] Open
Abstract
Although the activation of the prefrontal cortex (PFC) and the striatum had been found in smoking cue induced craving task, whether and how the functional interactions and white matter integrity between these brain regions contribute to craving processing during smoking cue exposure remains unknown. Twenty-five young male smokers and 26 age- and gender-matched nonsmokers participated in the smoking cue-reactivity task. Craving related brain activation was extracted and psychophysiological interactions (PPI) analysis was used to specify the PFC-efferent pathways contributed to smoking cue-induced craving. Diffusion tensor imaging (DTI) and probabilistic tractography was used to explore whether the fiber connectivity strength facilitated functional coupling of the circuit with the smoking cue-induced craving. The PPI analysis revealed the negative functional coupling of the left dorsolateral prefrontal cortex (DLPFC) and the caudate during smoking cue induced craving task, which positively correlated with the craving score. Neither significant activation nor functional connectivity in smoking cue exposure task was detected in nonsmokers. DTI analyses revealed that fiber tract integrity negatively correlated with functional coupling in the DLPFC-caudate pathway and activation of the caudate induced by smoking cue in smokers. Moreover, the relationship between the fiber connectivity integrity of the left DLPFC-caudate and smoking cue induced caudate activation can be fully mediated by functional coupling strength of this circuit in smokers. The present study highlighted the left DLPFC-caudate pathway in smoking cue-induced craving in smokers, which may reflect top-down prefrontal modulation of striatal reward processing in smoking cue induced craving processing. Hum Brain Mapp 38:4644-4656, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Kai Yuan
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
- School of Information EngineeringInner Mongolia University of Science and TechnologyBaotouInner Mongolia014010People's Republic of China
| | - Dahua Yu
- School of Information EngineeringInner Mongolia University of Science and TechnologyBaotouInner Mongolia014010People's Republic of China
| | - Yanzhi Bi
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
| | - Ruonan Wang
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
| | - Min Li
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
| | - Yajuan Zhang
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
| | - Minghao Dong
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
| | - Jinquan Zhai
- Department of Medical ImagingThe First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and TechnologyBaotouInner Mongolia014010People's Republic of China
| | - Yangding Li
- Guangxi Key Laboratory of Multi‐Source Information Mining and SecurityGuangxi Normal UniversityGuilinPeople's Republic of China
| | - Xiaoqi Lu
- School of Information EngineeringInner Mongolia University of Science and TechnologyBaotouInner Mongolia014010People's Republic of China
| | - Jie Tian
- School of Life Science and TechnologyXidian UniversityXi'anShaanxi710071People's Republic of China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education
- Institute of Automation, Chinese Academy of SciencesBeijing100190People's Republic of China
| |
Collapse
|