Cannabis Use and Normal Aging: Inverse Effect on Functional Network Connectivity Outcomes
Poster No:
902
Submission Type:
Abstract Submission
Authors:
Zening Fu1, Kent Hutchison2, Vince Calhoun3
Institutions:
1Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georg, Atlanta, GA, 2University of Colorado Anschutz Medical Campus, Denver, CO, 3GSU/GATech/Emory, Atlanta, GA
First Author:
Zening Fu
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georg
Atlanta, GA
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georg
Atlanta, GA
Co-Author(s):
Introduction:
Possibly due to the trend toward legalization and permissive societal attitudes(Bobitt et al., 2019; Luc et al., 2020; Pratt et al., 2019), there has been a significant rise in cannabis use, particularly among older adults, who represent the fastest-growing group of cannabis users(Pocuca et al., 2021). Cannabis use is associated with changes in brain function, which might contribute to cognitive outcomes in chronic users(Cousijn et al., 2014; Van Hell et al., 2011). Meanwhile, normal aging accompanied by significant brain changes may explain the notable cognitive decline among the elderly(Elliott, 2020). There is considerable variability regarding the extent of age-related changes in brain function, highlighting the importance of investigating factors that may exacerbate these alterations(Black & Rush, 2002). One such factor might be cannabis use, given its known heterogeneous effects on brain function. In this study, we assessed how cannabis use and aging are linked to functional network connectivity (FNC) in older adults. We hypothesized that cannabis use is connected to normal aging in terms of brain network organization, suggesting a process of neural dedifferentiation and a compensatory mechanism.
Methods:
This study is associated with Application 34175 for the UK Biobank (UKB) dataset, focusing on a subset of 25,317 subjects aged 45 to over 100 years. We downloaded the preprocessed resting-state data and normalized it to standard space using SPM12. An automated NeuroMark ICA framework(Du et al., 2020) was applied to capture individualized networks. FNC was calculated using the Pearson correlation between the timeseries of the networks. To explore changes in FNC related to cannabis use, we used a linear mixed-effect model (LMM), controlling for covariates such as age and gender. We also used the LMM to examine age-related changes in FNC while controlling for gender and cannabis use. We further divided cannabis-related FNCs into different groups according to their states to closely examine how these FNCs are associated with normal aging.
Results:
Clear modular patterns are observed from the average FNC in Fig. 1A, indicating the validity of implementing NeuroMark to the UKB data. Fig. 1B shows the t values between cannabis users and non-users (upper triangular matrix) and the t values associated with aging (lower triangular matrix). Cannabis use shows heterogeneous effects on the whole brain FNC. Specifically, for positive FNC, 154 pairs (e.g., FNC within SC) increased while 127 pairs (e.g., FNC within DM) decreased in the cannabis users. For negative FNC, 186 pairs increased (e.g., FNC between SM and DM) and 205 pairs decreased (e.g., FNC between SC and SM) in the cannabis users. Interestingly, FNC changes associated with cannabis use and age were inversely correlated, with a significant effect at the connectivity level (r = -0.3039, p = 7.83 × 10-31). When mapping FNCs into domain-level representations, we observed a general negative relationship between cannabis- and age-related models. When summarizing FNCs within each category, we found that FNCs larger in cannabis users tend to decline with age, and FNCs smaller in cannabis users tend to increase with age (Fig. 2). Our results revealed cannabis use and age affect overlapping brain systems but with a general reverse effect.
·Figure 1.
·Figure 2.
Conclusions:
In this study, we sought to examine the extent to which cannabis use and brain age overlap in brain function by mapping their associations to brain connections. We revealed overlapping brain patterns for cannabis use and age, characterized by altered within-domain FNC and between-domain FNC. Although there are some differences in their representations, these two constructs are strongly negatively correlated, which provides evidence that cannabis use and aging are companied by similar brain network structure reorganization, indicating the potential of cannabis usage in slowing down the process of neural dedifferentiation via compensational theory during normal aging.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural)
fMRI Connectivity and Network Modeling 2
Neuroinformatics and Data Sharing:
Brain Atlases
Keywords:
Aging
FUNCTIONAL MRI
Univariate
Other - Cannabis Use, Functional Network Connectivity, NeuroMark, ICA
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
Bobitt, J., Qualls, S. H., Schuchman, M., Wickersham, R., Lum, H. D., Arora, K., Milavetz, G. & Kaskie, B. (2019). Qualitative Analysis of Cannabis Use Among Older Adults in Colorado. Drugs and Aging, 36(7), 655–666.
Cousijn, J., Wiers, R. W., Ridderinkhof, K. R., van den Brink, W., Veltman, D. J. & Goudriaan, A. E. (2014). Effect of baseline cannabis use and working-memory network function on changes in cannabis use in heavy cannabis users: A prospective fMRI study. Human Brain Mapping, 35(5), 2470–2482.
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Elliott, M. L. (2020). MRI-based biomarkers of accelerated aging and dementia risk in midlife: how close are we? Ageing Research Reviews, 61.
Luc, M. H., Tsang, S. W., Thrul, J., Kennedy, R. D. & Moran, M. B. (2020). Content analysis of online product descriptions from cannabis retailers in six US states. International Journal of Drug Policy, 75.
Pocuca, N., Walter, T. J., Minassian, A., Young, J. W., Geyer, M. A. & Perry, W. (2021). The Effects of Cannabis Use on Cognitive Function in Healthy Aging: A Systematic Scoping Review. Archives of Clinical Neuropsychology, 36(5), 673–685.
Pratt, M., Stevens, A., Thuku, M., Butler, C., Skidmore, B., Wieland, L. S., Clemons, M., Kanji, S. & Hutton, B. (2019). Benefits and harms of medical cannabis: A scoping review of systematic reviews. Systematic Reviews, 8(1).
Van Hell, H. H., Vink, M., Ossewaarde, L., Jager, G., Kahn, R. S. & Ramsey, N. F. (2011). Chronic effects of cannabis use on the human reward system: An fMRI study. Psiquiatria Biologica, 18(2), 45–54.