Liangsuo Ma1, John M Hettema2, Janna Cousijn3, James M Bjork4, Joel L Steinberg4, Lori Keyser-Marcus4, Kyle Woisard5, QiQi Lu6, Roxann Roberson-Nay7, Antonio Abbate8, F Gerard Moeller9. 1. Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, Virginia; Department of Radiology, Virginia Commonwealth University, Richmond, Virginia. Electronic address: Liangsuo.ma@vcuhealth.org. 2. Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia; Department of Psychiatry, Texas A&M University Health Science Center, Bryan, Texas. 3. Neuroscience of Addiction lab, Department of Psychology, University of Amsterdam, Amsterdam, Netherlands. 4. Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, Virginia; Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia. 5. Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, Virginia. 6. Department of Statistical Sciences and Operations Research, Virginia Commonwealth University, Richmond, Virginia. 7. Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia. 8. Department of Internal Medicine, Virginia Commonwealth University, Richmond, Virginia. 9. Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, Virginia; Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia; Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, Virginia; Department of Neurology, Virginia Commonwealth University, Richmond, Virginia.
Abstract
BACKGROUND: Anxiety and depression symptoms are common among cannabis users and could be a risk factor for cannabis use (CU) disorder. Thus, it is critical to understand the neuronal circuits underlying the associations between CU and these symptoms. Alterations in resting-state functional connectivity within and/or between the default mode network and salience network have been reported in CU, anxiety, and depressive disorders and thus could be a mechanism underlying the associations between CU disorder and anxiety/depression symptoms. METHODS: Using resting-state functional magnetic resonance imaging, effective connectivities (ECs) among 9 major nodes from the default mode network and salience network were measured using dynamic causal modeling in 2 datasets: the Human Connectome Project (28 CU participants and 28 matched non-drug-using control participants) and a local CU study (21 CU participants and 21 matched non-drug-using control participants) in separate and parallel analyses. RESULTS: Relative to the control participants, right amygdala to left amygdala, anterior cingulate cortex to left amygdala, and medial prefrontal cortex to right insula ECs were greater, and left insula to left amygdala EC was smaller in the CU group. Each of these ECs showed a reliable linear relationship with at least one of the anxiety/depression measures. Most findings on the right amygdala to left amygdala EC were common to both datasets. CONCLUSIONS: Right amygdala to left amygdala and anterior cingulate cortex to left amygdala ECs may be related to the close associations between CU and anxiety/depression symptoms. The findings on the medial prefrontal cortex to right insula and left insula to left amygdala ECs may reflect a compensatory mechanism.
BACKGROUND: Anxiety and depression symptoms are common among cannabis users and could be a risk factor for cannabis use (CU) disorder. Thus, it is critical to understand the neuronal circuits underlying the associations between CU and these symptoms. Alterations in resting-state functional connectivity within and/or between the default mode network and salience network have been reported in CU, anxiety, and depressive disorders and thus could be a mechanism underlying the associations between CU disorder and anxiety/depression symptoms. METHODS: Using resting-state functional magnetic resonance imaging, effective connectivities (ECs) among 9 major nodes from the default mode network and salience network were measured using dynamic causal modeling in 2 datasets: the Human Connectome Project (28 CU participants and 28 matched non-drug-using control participants) and a local CU study (21 CU participants and 21 matched non-drug-using control participants) in separate and parallel analyses. RESULTS: Relative to the control participants, right amygdala to left amygdala, anterior cingulate cortex to left amygdala, and medial prefrontal cortex to right insula ECs were greater, and left insula to left amygdala EC was smaller in the CU group. Each of these ECs showed a reliable linear relationship with at least one of the anxiety/depression measures. Most findings on the right amygdala to left amygdala EC were common to both datasets. CONCLUSIONS: Right amygdala to left amygdala and anterior cingulate cortex to left amygdala ECs may be related to the close associations between CU and anxiety/depression symptoms. The findings on the medial prefrontal cortex to right insula and left insula to left amygdala ECs may reflect a compensatory mechanism.
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