Dose-Dependent Alcohol Effects on Adult vs. Adolescent Brain Functional Connectivity in Rats
Poster No:
1778
Submission Type:
Abstract Submission
Authors:
Sung-Ho Lee1,2,3,4, Tatiana Shnitko1,2,3, LiMing Hsu1,2,3, Margaret Broadwater1,2,3,4, Mabelle Sardinas1,2,3, Tzu-Wen Wang5,2,3, Donita Robinson6,7, Ryan Vetreno6,7, Fulton Crews6,7,8, Yen-Yu Shih1,2,3,4
Institutions:
1Center for Animal MRI, University of North Carolina, Chapel Hill, NC, 2Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, 3Department of Neurology, University of North Carolina, Chapel Hill, NC, 4Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, 5University of North Carolina at Chapel Hill, Chapel Hill, NC, 6Bowles Center for Alcohol Studies, University of North Carolina, Chapel Hill, NC, 7Department of Psychiatry, University of North Carolina, Chapel Hill, NC, 8Department of Pharmacology, University of North Carolina, Chapel Hill, NC
First Author:
Sung-Ho Lee
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Co-Author(s):
Tatiana Shnitko
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
LiMing Hsu
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Margaret Broadwater
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Mabelle Sardinas
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Tzu-Wen Wang
University of North Carolina at Chapel Hill|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
University of North Carolina at Chapel Hill|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Donita Robinson
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC
Ryan Vetreno
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC
Fulton Crews
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina|Department of Pharmacology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Bowles Center for Alcohol Studies, University of North Carolina|Department of Psychiatry, University of North Carolina|Department of Pharmacology, University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Yen-Yu Shih
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Center for Animal MRI, University of North Carolina|Biomedical Research Imaging Center, University of North Carolina|Department of Neurology, University of North Carolina|Bowles Center for Alcohol Studies University of North Carolina
Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC|Chapel Hill, NC
Introduction:
Alcohol abuse, a significant cause of premature mortality, is notably prevalent among adolescents, increasing risks for alcohol use disorder (AUD) (Crews et al., 2000; Squeglia et al., 2015; Sohi et al., 2021; Miech et al., 2023). Early alcohol exposure disrupts critical neurodevelopmental, hormonal, and cognitive processes, particularly affecting the frontal cortex during pivotal adolescent brain changes (Walker et al., 2022). This period coincides with maturing executive functions and inhibitory control (Saito et al., 2022; Broadwater et al., 2018). This study investigates the impact of acute alcohol intoxication on functional connectivity (FC), taking into account variables including sex and age. Despite evolutionary distinctions, rodent models provide valuable insights into neural mechanisms of addiction. We employed a rat fMRI protocol to investigate the "triple-network" model, analogous to human brain networks, in the context of addiction (Menon et al., 2019; Lee et al., 2021). We examined the age, sex, and alcohol dose-dependent effects on intra- and inter-network connectivity in rats, including the lateral cortical network (LCN), default mode network (DMN), and salience network (SN) (Lee et al., 2021; Mandino et al., 2022).
Methods:
This study employed 38 in-house bred Wistar rats, categorized by sex and age (P45, P80). Each rat underwent a single resting-state fMRI (rs-fMRI) session that included both baseline and post-injection scans using saline and varying alcohol doses (0, 1, 2, 4 g/kg). Anesthesia and imaging protocols were conducted as described in Lee et al., 2021.
For data preprocessing, we implemented several steps: slice timing correction, motion correction, skull-stripping, spatial normalization, removal of nuisance signals, and band-pass filtering. A Pearson's correlation coefficient matrix was generated for each subject using our in-house rat brain atlas. To assess the effects of sex, age, alcohol exposure, and dose, we conducted a non-parametric factorial ANOVA. Additionally, a moderation analysis was performed to evaluate the influences of sex and age on alcohol-induced changes in FC.
For data preprocessing, we implemented several steps: slice timing correction, motion correction, skull-stripping, spatial normalization, removal of nuisance signals, and band-pass filtering. A Pearson's correlation coefficient matrix was generated for each subject using our in-house rat brain atlas. To assess the effects of sex, age, alcohol exposure, and dose, we conducted a non-parametric factorial ANOVA. Additionally, a moderation analysis was performed to evaluate the influences of sex and age on alcohol-induced changes in FC.
Results:
The rs-fMRI matrix from baseline data in this study aligned with prior rat rs-fMRI datasets (Lee et al., 2021), attesting to our FC assessments' reproducibility, shown in Figure 1. The experimental design, in Figure 2A, sets a framework for fMRI sessions, capturing dynamic FC changes post-alcohol administration. Figure 2B reveals sex, age, and alcohol dose effects on FC. Sex differences were evident in FC patterns among intra-network FC within LCN, DMN, SN, and inter-network FC between DMN and other networks. Age altered FC within and between the DMN and SN. Alcohol exposure led to a dose-responsive FC increase across networks. Acute alcohol administration caused significant changes, especially in intra-network FC within LCN and inter-network FC between LCN, DMN, SN. The moderation analysis in Figure 2D highlights age as a more significant factor than sex in alcohol-induced FC alterations, with older subjects showing greater increases in LCN-related FC due to alcohol.
Conclusions:
This study used rs-fMRI to examine the effects of acute alcohol on functional connectivity in rat brains, specifically focusing on the DMN, SN, and LCN. Reproducibility was confirmed by comparing with previous datasets. The research revealed sex- and age-dependent differences in connectivity. Notably, acute alcohol exposure increased connectivity within the LCN and between LCN, DMN, and SN. Age was a significant moderator in alcohol-induced FC changes, aligning with prior findings on age-related behavioral responses to alcohol. This work supports the utility of rs-fMRI in studying alcohol's acute effects on brain networks and suggests a mechanism for adolescent insensitivity to alcohol intoxication.
Lifespan Development:
Early life, Adolescence, Aging 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Novel Imaging Acquisition Methods:
BOLD fMRI
Physiology, Metabolism and Neurotransmission :
Pharmacology and Neurotransmission
Keywords:
Addictions
ANIMAL STUDIES
FUNCTIONAL MRI
HIGH FIELD MR
Other - Alcohol
1|2Indicates the priority used for review
Provide references using author date format
Crews F.T. et al., (2000), 'Binge ethanol consumption causes differential brain damage in young adolescent rats compared with adult rats', Alcoholism: Clinical and Experimental Research, 24(11), 1712-1723.
Lee S. et al., (2021), 'An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI', NeuroImage, 243:118541.
Mandino F. et al., (2022), 'A triple-network organization for the mouse brain', Molecular Psychiatry, 27(2), 865-872.
Menon B., (2019), 'Towards a new model of understanding - The triple network, psychopathology and the structure of the mind', Medical Hypotheses, 133:109385.
Miech R.A. et al., (2023). 'Monitoring the Future National Survey Results on Drug Use, 1975–2022: Secondary School Students', Ann Arbor: Institute for Social Research, The University of Michigan.
Saito D.N. et al., (2022), 'Development of attentional networks during childhood and adolescence: A functional MRI study', Neuropsychopharmacology Reports, 42(2), 191-198.
Sohi I. et al., (2021), 'The global impact of alcohol consumption on premature mortality and health in 2016', Nutrients, 13(9).
Squeglia L.M. et al., (2015), 'Brain development in heavy-drinking adolescents', American Journal of Psychiatry, 172(6), 531-542.
Walker C.D. et al., (2022), 'Diverging Effects of Adolescent Ethanol Exposure on Tripartite Synaptic Development across Prefrontal Cortex Subregions', Cells, 11(19), 11193111.