Reduced cortical thickness in behavioral addictions
Poster No:
574
Submission Type:
Abstract Submission
Authors:
Hongsheng Xie1,2, Fei Zhu2,3, Qiyong Gong2,3, Zhiyun Jia1,2
Institutions:
1Department of Nuclear Medicine, Sichuan University West China Hospital, Chengdu, China, 2Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China, 3Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
First Author:
Hongsheng Xie
Department of Nuclear Medicine, Sichuan University West China Hospital|Research Unit of Psychoradiology, Chinese Academy of Medical Sciences
Chengdu, China|Chengdu, China
Department of Nuclear Medicine, Sichuan University West China Hospital|Research Unit of Psychoradiology, Chinese Academy of Medical Sciences
Chengdu, China|Chengdu, China
Co-Author(s):
Fei Zhu
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences|Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University
Chengdu, China|Chengdu, China
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences|Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University
Chengdu, China|Chengdu, China
Qiyong Gong
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences|Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University
Chengdu, China|Chengdu, China
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences|Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University
Chengdu, China|Chengdu, China
Zhiyun Jia
Department of Nuclear Medicine, Sichuan University West China Hospital|Research Unit of Psychoradiology, Chinese Academy of Medical Sciences
Chengdu, China|Chengdu, China
Department of Nuclear Medicine, Sichuan University West China Hospital|Research Unit of Psychoradiology, Chinese Academy of Medical Sciences
Chengdu, China|Chengdu, China
Introduction:
Behavioral addictions (BAs) are disorders similar to substance addiction, which are characterized by excessive and uncontrollable engagement in specific activities instead of a psychoactive drug. BAs include gambling disorder, internet gaming disorder, and smartphone addiction 1. Individuals with BAs can display a variety of symptoms, including cravings, a lack of control, and withdrawal symptoms. Currently, many neuroimaging studies have found structural brain alterations in BAs, such as decreased grey matter volume in the orbitofrontal cortex (OFC), putamen, and supplementary motor area 2,3. However, these findings are often not consistent, thus, a meta-analysis is needed to confirm and extend previous findings.
This study aimed to investigate the altered cortical thickness (CTh) pattern in BAs. We hypothesized that altered CTh could be found in key brain regions involved in reward, executive, and/or affective function.
This study aimed to investigate the altered cortical thickness (CTh) pattern in BAs. We hypothesized that altered CTh could be found in key brain regions involved in reward, executive, and/or affective function.
Methods:
Search strategy and selection criteria
This study followed the PRISMA guideline, and the protocol was registered on PROSPERO (CRD42023421271) 4. We searched five databases (PubMed, Embase, Web of Science, PsychINFO, and CNKI) from inception to May 1, 2023 for CTh studies. The key search words were as follows: (behavioral addiction OR gambling disorder OR internet gaming disorder OR phone addiction) AND (cortical thickness OR surface-based morphometry). More details can be found on PROSPERO.
Meta-analyses
We used the SDM-PSI to investigate the altered CTh in the BAs group 5. Briefly, the peak coordinates with t-scores from primary studies were used to create the combined effect-size signed map. A p-value of 0.005 was used to generate significant clusters with peak MNI coordinates 6. Additionally, meta-regression was conducted to explore the association between addiction severity and CTh alterations.
Control analyses
Potential sources of heterogeneity were analyzed, including age, male proportion, and education. Reproducibility and publication bias were assessed by Jack-knife sensitivity analysis and Egger's test, respectively 7.
This study followed the PRISMA guideline, and the protocol was registered on PROSPERO (CRD42023421271) 4. We searched five databases (PubMed, Embase, Web of Science, PsychINFO, and CNKI) from inception to May 1, 2023 for CTh studies. The key search words were as follows: (behavioral addiction OR gambling disorder OR internet gaming disorder OR phone addiction) AND (cortical thickness OR surface-based morphometry). More details can be found on PROSPERO.
Meta-analyses
We used the SDM-PSI to investigate the altered CTh in the BAs group 5. Briefly, the peak coordinates with t-scores from primary studies were used to create the combined effect-size signed map. A p-value of 0.005 was used to generate significant clusters with peak MNI coordinates 6. Additionally, meta-regression was conducted to explore the association between addiction severity and CTh alterations.
Control analyses
Potential sources of heterogeneity were analyzed, including age, male proportion, and education. Reproducibility and publication bias were assessed by Jack-knife sensitivity analysis and Egger's test, respectively 7.
Results:
Study characteristics
From 415 records, 10 studies with 11 datasets (343 individuals with BAs and 355 HCs) were eventually included (Figure 1). The mean age in the BA group was older (23.65 vs 23.57, p = 0.03), but there was no significant difference in sex (0.68 vs 0.65, p = 0.87) or education (14.91 vs 15.00, p = 0.59) between the two groups.
Meta-analyses
The BA group showed thinner CTh in the bilateral precuneus/cuneus, right superior occipital gyrus, right postcentral gyrus, right OFC, and left dorsolateral prefrontal cortex (DLPFC, Figure 2, all p < 0.005). No thicker regional CTh was found in the BA group. The meta-regression analysis showed that the right postcentral gyrus and precuneus cortex were negatively associated with standard addiction severity (both p < 0.0005).
Control analyses
Age, sex, and education showed no effects on our results. The Jackknife sensitivity analysis showed that all clusters were preserved in most combinations. The DLPFC, OFC, and postcentral gyrus were preserved in 9 out of 11 combinations. The Egger test did not show significant publication bias in all clusters (all p > 0.05).
From 415 records, 10 studies with 11 datasets (343 individuals with BAs and 355 HCs) were eventually included (Figure 1). The mean age in the BA group was older (23.65 vs 23.57, p = 0.03), but there was no significant difference in sex (0.68 vs 0.65, p = 0.87) or education (14.91 vs 15.00, p = 0.59) between the two groups.
Meta-analyses
The BA group showed thinner CTh in the bilateral precuneus/cuneus, right superior occipital gyrus, right postcentral gyrus, right OFC, and left dorsolateral prefrontal cortex (DLPFC, Figure 2, all p < 0.005). No thicker regional CTh was found in the BA group. The meta-regression analysis showed that the right postcentral gyrus and precuneus cortex were negatively associated with standard addiction severity (both p < 0.0005).
Control analyses
Age, sex, and education showed no effects on our results. The Jackknife sensitivity analysis showed that all clusters were preserved in most combinations. The DLPFC, OFC, and postcentral gyrus were preserved in 9 out of 11 combinations. The Egger test did not show significant publication bias in all clusters (all p > 0.05).
·Figure 1. Characteristics of 10 included studies.
·Figure 2. Results of meta-analyses.
Conclusions:
This meta-analysis investigated the altered CTh pattern in BAs and found reproducible reduced CTh in key brain regions within the default mode, executive control, and sensorimotor networks. More importantly, the CTh of precuneus and postcentral gyrus appear to be associated with the severity of BAs. These findings provide potential support for the addiction model of disruptions in decision-making and self-control 8,9. In conclusion, our study enhances the understanding of the neurobiological mechanisms underlying BAs and offers valuable insights into strategies for recovery from and prevention of BAs.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping 2
Keywords:
Addictions
ADULTS
Cortex
Data analysis
Meta- Analysis
MRI
Psychiatric Disorders
STRUCTURAL MRI
1|2Indicates the priority used for review
Provide references using author date format
2. Solly JE, Hook RW, Grant JE, et al., (2022), 'Structural grey matter differences in Problematic Usage of the Internet: a systematic review and meta-analysis', Molecular Psychiatry, vol. 27, no. 2, pp. 1000-1009
3. Clark L, Boileau I, Zack M, (2019), 'Neuroimaging of reward mechanisms in Gambling disorder: an integrative review', Mol Psychiatry, vol. 24, no. 5, pp. 674-693
4. Moher D, Liberati A, Tetzlaff J, et al., (2009), 'Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement', PLoS Med, vol. 6, no. 7, pp. e1000097
5. Radua J, Rubia K, Canales-RodrÃguez EJ, et al., (2014), 'Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies', Front Psychiatry, vol. 5, no. pp. 13
6. Radua J, Mataix-Cols D, Phillips ML, et al., (2012), 'A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps', European Psychiatry, vol. 27, no. 8, pp. 605-611
7. Egger M, Smith GD, Schneider M, et al., (1997), 'Bias in meta-analysis detected by a simple, graphical test', BMJ, vol. 315, no. 7109, pp. 629
8. Volkow ND, Koob GF, McLellan AT, (2016), 'Neurobiologic Advances from the Brain Disease Model of Addiction', N Engl J Med, vol. 374, no. 4, pp. 363-371
9. Groman SM, Massi B, Mathias SR, et al., (2019), 'Model-Free and Model-Based Influences in Addiction-Related Behaviors', Biol Psychiatry, vol. 85, no. 11, pp. 936-945