Poster No:
558
Submission Type:
Abstract Submission
Authors:
YI-HSUAN LIU1, Kun-Hsien Chou1,2, Pei-Lin Lee3, Chia-Chun Hung4,5, Li-Hung Chang1, Marc Potenza6,7,8,9,10, Chiang-Shan Li6, Tony Szu-Hsien Lee11,5,12, Ching-Po Lin1,3,13,14
Institutions:
1Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan, 3Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan, 4Continuing Education Master's Program of Addiction Prevention and Treatment, National Taiwan Normal, Taipei, Taiwan, 5Center for Addiction Prevention and Policy Research, National Taiwan Normal University, Taipei, Taiwan, 6Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, 7The Child Study Center, School of Medicine, Yale University, New Haven, CT, 8Department of Neuroscience and the The Wu Tsai Institute, Yale University, New Haven, CT, 9The Connecticut Council on Problem Gambling, Wethersfield, CT, 10The Connecticut Mental Health Center, New Haven, CT, 11Department of Health Promotion and Health Education, National Taiwan Normal University, Taipei, Taiwan, 12Continuing Education Master's Program of Addiction Prevention and Treatment, National Taiwan Normal University, Taipei, Taiwan, 13Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, 14Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
First Author:
YI-HSUAN LIU
Institute of Neuroscience, National Yang Ming Chiao Tung University
Taipei, Taiwan
Co-Author(s):
Kun-Hsien Chou
Institute of Neuroscience, National Yang Ming Chiao Tung University|Brain Research Center, National Yang Ming Chiao Tung University
Taipei, Taiwan|Taipei, Taiwan
Pei-Lin Lee
Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University
Taipei, Taiwan
Chia-Chun Hung
Continuing Education Master's Program of Addiction Prevention and Treatment, National Taiwan Normal|Center for Addiction Prevention and Policy Research, National Taiwan Normal University
Taipei, Taiwan|Taipei, Taiwan
Li-Hung Chang
Institute of Neuroscience, National Yang Ming Chiao Tung University
Taipei, Taiwan
Marc Potenza
Department of Psychiatry, School of Medicine, Yale University|The Child Study Center, School of Medicine, Yale University|Department of Neuroscience and the The Wu Tsai Institute, Yale University|The Connecticut Council on Problem Gambling|The Connecticut Mental Health Center
New Haven, CT|New Haven, CT|New Haven, CT|Wethersfield, CT|New Haven, CT
Chiang-Shan Li
Department of Psychiatry, School of Medicine, Yale University
New Haven, CT
Tony Szu-Hsien Lee
Department of Health Promotion and Health Education, National Taiwan Normal University|Center for Addiction Prevention and Policy Research, National Taiwan Normal University|Continuing Education Master's Program of Addiction Prevention and Treatment, National Taiwan Normal University
Taipei, Taiwan|Taipei, Taiwan|Taipei, Taiwan
Ching-Po Lin
Institute of Neuroscience, National Yang Ming Chiao Tung University|Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University|Department of Education and Research, Taipei City Hospital|Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes
Taipei, Taiwan|Taipei, Taiwan|Taipei, Taiwan|Miaoli, Taiwan
Introduction:
The engagement in recreational substance use during youth can exert significant and enduring effects on brain development. Among the array of recreational substances in Taiwan, ketamine stands out as particularly prevalent among young individuals, due to its affordability, easy accessibility, and relatively minor legal consequences [1]. Although our comprehension of the neurobiological alterations associated with ketamine abuse has advanced considerably [2,3], there exists a notable gap in knowledge concerning brain changes resulting from early, non-medical exposure to ketamine. To address this gap, we recruited participants with early ketamine exposure from the community. Given the distinctive characteristics of these individuals, it is crucial to emphasize individual brain structure alterations to elucidate the impact of early-stage ketamine use. Hence, in this study, we employ a personalized analytical approach with structural T1-weighted MRI anatomical scans to pinpoint subtle yet significant changes in gray matter volume among a cohort of young adults with early exposure to recreational ketamine use.
Methods:
Participants consisted of 174 individuals from Taiwan, including 53 ketamine use (KU) and 121 healthy controls (HC) [Table 1]. T1-weighted MRI anatomical scans were preprocessed using the VBM pipeline [4]. We extract regional gray matter volume (GMV) from 1060 brain areas and map them into nine corresponded large-scale brain networks [5,6,7]. For individual-level analyses, we employed a w-score approach to identify extreme regional GMV changes for each participant [8]. A general linear model was constructed using healthy controls to obtain beta coefficient estimates of GMV for each ROI, incorporating covariates such as age, sex, and education. This model was applied to individuals with ketamine use further, wherein we calculated residuals for the 1060 brain regions per participant and transformed them into corresponding W-scores. To provide a summary of individual variation in KU, w-scores were summarized by counting how many subjects had an extreme deviation (extreme deviation defined as p< 0.001, |z| > 3.29) at a given ROI, and then dividing by the group size to show the frequency of individuals with extreme deviations at that brain area. For group-level analyses, we employed an ANCOVA model to identify brain regions with significant between-group difference in GMV using the same statistic threshold (p< 0.001) as in the individual analysis. Subsequently, to control for the varying number of regions within networks, we divided the number of significantly different areas to the total within each.

·Table 1: Demographics.
Results:
Upon examination of individual-level w-scores, our analysis uncovered that KU exhibits more extensive alterations in regional GMV, a phenomenon potentially obscured by conventional case-control group-level analysis (Fig 1. (a)). The most substantial impact is also observed in the frontoparietal, somatomotor, visual, dorsal attention, and default networks (Fig 1. (b)).

·Fig 1
Conclusions:
In our investigation, we have identified morphometric heterogeneity throughout the brains of individuals with early exposure to ketamine. Remarkably, the networks involved deviate from the conventional findings associated with addiction, particularly those related to reward networks. This discovery suggests that employing individual-level analysis might unveil subtle yet significant anatomical changes among a cohort of young adults with early exposure to recreational ketamine use. These initial findings provide a glimpse into the potential nuanced direct impact of ketamine or the possibility of serving as an early biomarker for the essential brain networks associated with addiction. Further research is indispensable to validate and gain deeper insights into the implications of these preliminary observations.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Emotion, Motivation and Social Neuroscience:
Social Neuroscience Other
Lifespan Development:
Early life, Adolescence, Aging
Modeling and Analysis Methods:
Methods Development 2
Keywords:
Addictions
Data analysis
Morphometrics
MRI
STRUCTURAL MRI
Other - ketamine
1|2Indicates the priority used for review
Provide references using author date format
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[3] Strous, J. F., Weeland, C. J., van der Draai, F. A., Daams, J. G., Denys, D., Lok, A., ... & Figee, M. (2022), 'Brain changes associated with long-term ketamine abuse, a systematic review', Frontiers in neuroanatomy, vol. 8.
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[6] Tian, Y., Margulies, D. S., Breakspear, M., & Zalesky, A. (2020), 'Topographic organization of the human subcortex unveiled with functional connectivity gradients', Nature neuroscience, vol. 23, no. 11, pp. 1421-1432.
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