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Common gray matter atrophy in individuals with different behavioral addictions: a voxel-wise meta-analysis1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 2Department of Psychology, School of Public Administration, Sichuan University, Chengdu, China
Synopsis
In order to figure out the common structural alterations in behavioral addicts among various publications and to find a biomarker for future improvement of diagnostic category, we searched for voxel based morphometry studies compared between patients and healthy controls and pooled them together in a meta-analytic way by using AES-SDM. 22 studies comprising 5 different addictive behaviors were included. 576 patients showed GM reduction in the left ACC, right striatum and right SMA compared with 635 HCs. In summary, our findings revealed common GM decreases in frontostriatal circuitry, consistent with previous multimodal neuroimaging findings in addiction.
Introduction
With the improvement of psychiatric classification system in recent years, especially the release of DSM-V1, behavioral addiction (BHA) as a newly established diagnosis has developed rapidly promoting considerable amounts of publications. Part of them focused on gray matter (GM) abnormalities through voxel based morphometry (VBM), but few of the results were replicated and different types of BHAs varied further. The aim of this study was to figure out whether different addictive behaviors suggest a common GM abnormalities and whether structural changes are consistent with previous functional disruption found in addiction2.Methods
We performed a comprehensive and exhaustive search in the PubMed, Web of Science, Cochrane Library and ScienceDirect databases for studies up to May 2018 that reported VBM results on BHA. The reference lists of enrolled studies and a few high-quality reviews were also investigated manually in case of omission. Missing information such as peak coordinates or whole-brain results was obtained by contacting authors. Studies were excluded if (1)the methodology wasn't VBM; (2)participants weren't compared on a group-level; (3)whole-brain results or peak coordinates were absent after contacting; (4) papers were published in a non-English journal; (5) datasets partially duplicated among several publications; (6) thresholds within different regions were employed inconsistently. We chose anisotropic effect-size signed differential mapping (AES-SDM) to perform pooled analysis. Meanwhile, we also calculated the results of Jackknife analysis, subgroup and meta-regression for further analysis.Results
Totally, 22 studies were included comprising 576 behavioral addicts and 635 healthy controls (HCs).11 of 22 studies were concerned on internet gaming disorder (IGD); 7 reported comparisons between pathological gamblers (PG) and HCs; the 4 remaining studies centered on internet addiction (IA), problematic hypersexual behavior (PHB) and mobile phone dependence (MPD). Individuals with BHA showed significant GM decreases in the left anterior cingulate cortex (ACC) extending to paracingulate gyri, right striatum and right supplementary motor area (SMA). Results of IGD subgroup remained substantially consistent with that of the entire group apart from the extra reduction in the right middle frontal gyrus (MFG). However, PGs only indicated a smaller GMV in the left MFG. Studies using corrected p value for multiple comparison showed smaller GMV in the left ACC, right striatum, right SMA and right inferior frontal gyrus (IFG). Studies with pure male addicts showed decreased GMV in the left superior frontal gyrus (SFG) and right striatum. For the jackknife analysis, GM changes in the left ACC were always duplicated. Moreover, the right striatum survived in 19 of 22 datasets; the right SMA disappeared in only 1 of 22 datasets. Meta-regression revealed that severer patients were identified to develop a greater GMV in the left ACC and right SMA. A positive association was discovered between GMV in the left ACC and BIS-11 score as well.Discussion
As far as we know, our current study is the first transdiagnostic meta-analysis to reveal the common trait of structural anomalies among various behavioral addictions. In line with our previous prediction, the frontostriatal circuit dominated the ultimate results, which was also consistent with the neural fundamental of substance addiction3.Multimodal neuroimaging researches also identified the same regional abnormalities in behavioral addicts as our results4-6. IGD subgroup successfully replicated the main finding demonstrating the stability. In contrast to IGDs, PG subgroup seemed to be inconsistent, which might result from the limited included studies and numerous comorbidities. Pure male subgroup findings indicated the right IFG and right striatum might be related to addictive susceptibility of specific behaviors in males (e.g. internet gaming, exercise, gambling), which required pure female studies to make a contrast in the future. In view of the findings of meta-regression, ACC volume might be an indicator of clinical severity and even further predict individual addictive impulsiveness. We inferred that impulsive individuals might have stronger neuron activities in ACC resulting in the enlargement. As far as we knew, emotional and impulse control was one of the functions of ACC and abnormalities in SMA suggested the maladjustment of internally voluntary movement which was also one of the features of behavioral addicts7,8. So the association between function of ACC and SMA explained why these two regions together could reflect severity of addicts.Conclusion
In summary, our current meta-analysis revealed that the overlapped robust GM reduction of behavioral addicts in the frontostriatal circuitry consistent with previous prefrontal-striatal models in substance-related disorder. Severity and impulsivity were also demonstrated to be related to regional structural anomalies. In view of the absence of several types of behaviors, future large-scale and high-quality studies across multimodal methods was required to discover similarities and differences between various behavioral addictions.Acknowledgements
This study was supported by the National Natural Science Foundation (Grant Nos. 81771718, 81761128023, 81621003), Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT, Grant No. IRT16R52) of China.References
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