Abstract
Synthetic cannabinoids (SC) have become increasingly popular in the last few years, especially among adolescents. Given ADHD is overrepresented in patients with substance use across adolescents compared to the general population, the current study aims were two-fold: i) examine structural brain network topology in SC users compared to healthy controls and, ii) examine the influence of ADHD on network topology in SC users. Diffusion-weighted magnetic resonance imaging scans were acquired from 27 SC users (14 without ADHD and 13 with ADHD combined type) and 13 controls. Structural networks were examined using network-based statistic and connectomic analysis. We found that SC users without ADHD had significantly weaker connectivity compared to controls in bilateral hemispheres, most notably in edges connecting the left parietal and occipital regions. In contrast, SC users with ADHD showed stronger structural connectivity compared to controls. In addition, adolescent SC users with ADHD, but not without ADHD, displayed reduced network organization, indicated by lower clustering coefficient and modularity, suggesting that poor structural network segregation and preserved structural network integration. These results suggest that comorbidity of ADHD and substance dependence may show different structural connectivity alterations than substance use alone. Therefore, future connectivity studies in the substance use population should account for the presence of ADHD in their samples, which may be associated with disparate connectivity profiles.
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References
American Association of Poison Control Centers, Synthetic Marijuana Data. (2015). https://aapcc.s3.amazonaws.com/files/library/Syn_Marijuana_Web_Data_through_7.6.15.pdf.
Atwood, B. K., Huffman, J., Straiker, A., & Mackie, K. (2010). JWH018, a common constituent of ‘Spice’herbal blends, is a potent and efficacious cannabinoid CB1 receptor agonist. British Journal of Pharmacology, 160(3), 585–593.
Barratt, M. J., Cakic, V., & Lenton, S. (2013). Patterns of synthetic cannabinoid use in Australia. Drug and Alcohol Review, 32(2), 141–146.
Beare, R., Adamson, C., Bellgrove, M. A., Vilgis, V., Vance, A., Seal, M. L., at al. (2017). Altered structural connectivity in ADHD: A network based analysis. Brain Imaging and Behavior, 11(3), 846–858.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B: Methodological, 289–300.
Bos, D. J., Oranje, B., Achterberg, M., Vlaskamp, C., Ambrosino, S., Reus, M. A., et al. (2017). Structural and functional connectivity in children and adolescents with and without attention deficit/hyperactivity disorder. Journal of Child Psychology and Psychiatry, 58(7), 810–818.
Bullmore, E., & Sporns, O. (2012). The economy of brain network organization. Nature Reviews Neuroscience, 13(5), 336–349.
Cadet, J. L., Bisagno, V., & Milroy, C. M. (2014). Neuropathology of substance use disorders. Acta Neuropathologica, 127(1), 91–107.
Cammoun, L., Gigandet, X., Meskaldji, D., Thiran, J. P., Sporns, O., Do, K. Q., Maeder, P., Meuli, R., & Hagmann, P. (2012). Mapping the human connectome at multiple scales with diffusion spectrum MRI. Journal of Neuroscience Methods, 203(2), 386–397.
Cao, Q., Shu, N., An, L., Wang, P., Sun, L., Xia, M. R., Wang, J. H., Gong, G. L., Zang, Y. F., Wang, Y. F., & He, Y. (2013). Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder. Journal of Neuroscience, 33(26), 10676–10687.
Cooper, R. E., Williams, E., Seegobin, S., Tye, C., Kuntsi, J., & Asherson, P. (2017). Cannabinoids in attention-deficit/hyperactivity disorder: A randomised-controlled trial. European Neuropsychopharmacology, 27(8), 795–808.
Dalton, V. S., & Zavitsanou, K. (2010). Cannabinoid effects on CB1 receptor density in the adolescent brain: An autoradiographic study using the synthetic cannabinoid HU210. Synapse, 64(11), 845–854.
Di Biase, M. A., Cropley, V. L., Baune, B. T., Olver, J., Amminger, G. P., Phassouliotis, C., et al. (2017). White matter connectivity disruptions in early and chronic schizophrenia. Psychological Medicine, 47(16), 2797–2810.
D'souza, D. C., Ranganathan, M., Braley, G., Gueorguieva, R., Zimolo, Z., Cooper, T., et al. (2008). Blunted psychotomimetic and amnestic effects of Δ-9-tetrahydrocannabinol in frequent users of cannabis. Neuropsychopharmacology, 33(10), 2505–2516.
Ersche, K. D., Jones, P. S., Williams, G. B., Turton, A. J., Robbins, T. W., & Bullmore, E. T. (2012). Abnormal brain structure implicated in stimulant drug addiction. Science, 335(6068), 601–604.
European Monitoring Centre for Drugs and Drugs Addiction. (2012). Drugnet Europe 78, Lisbon. http://www.emcdda.europa.eu/publications/drugnet/78.
Gurdal, F., Asirdizer, M., Aker, R. G., Korkut, S., Gocer, Y., Kucukibrahimoglu, E. E., & Ince, C. H. (2013). Review of detection frequency and type of synthetic cannabinoids in herbal compounds analyzed by Istanbul narcotic Department of the Council of forensic medicine, Turkey. Journal of Forensic and Legal Medicine, 20(6), 667–672.
Hong, S. B., Zalesky, A., Fornito, A., Park, S., Yang, Y. H., Park, M. H., Song, I. C., Sohn, C. H., Shin, M. S., Kim, B. N., Cho, S. C., Han, D. H., Cheong, J. H., & Kim, J. W. (2014). Connectomic disturbances in attention-deficit/hyperactivity disorder: A whole-brain tractography analysis. Biological Psychiatry, 76(8), 656–663.
Jacobson, L. A., Peterson, D. J., Rosch, K. S., Crocetti, D., Mori, S., & Mostofsky, S. H. (2015). Sex-based dissociation of white matter microstructure in children with attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 54(11), 938–946.
Kaufman, J., Birmaher, B., Brent, D., Rao, U., Flynn, C., Moreci, P., et al. (1997). Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980–988.
Kim, D. J., Skosnik, P. D., Cheng, H., Pruce, B. J., Brumbaugh, M. S., Vollmer, J. M., Hetrick, W. P., O'Donnell, B. F., Sporns, O., Puce, A., & Newman, S. D. (2011). Structural network topology revealed by white matter tractography in cannabis users: A graph theoretical analysis. Brain Connectivity, 1(6), 473–483.
Leemans, A., & Jones, D. K. (2009). The B-matrix must be rotated when correcting for subject motion in DTI data. Magnetic Resonance in Medicine, 61(6), 1336–1349.
Lord, L. D., Stevner, A. B., Deco, G., & Kringelbach, M. L. (2017). Understanding principles of integration and segregation using whole-brain computational connectomics: Implications for neuropsychiatric disorders. Philosophical Transactions of the Royal Society A, 375(2096), 20160283.
Lubman, D. I., Cheetham, A., & Yücel, M. (2015). Cannabis and adolescent brain development. Pharmacology & Therapeutics, 148, 1–16.
Maier-Hein, K. H., Neher, P. F., Houde, J. C., Côté, M. A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F. C., Lin, Y. C., Ji, Q., Reddick, W. E., Glass, J. O., Chen, D. Q., Feng, Y., Gao, C., Wu, Y., Ma, J., Renjie, H., Li, Q., Westin, C. F., Deslauriers-Gauthier, S., González, J. O. O., Paquette, M., St-Jean, S., Girard, G., Rheault, F., Sidhu, J., Tax, C. M. W., Guo, F., Mesri, H. Y., Dávid, S., Froeling, M., Heemskerk, A. M., Leemans, A., Boré, A., Pinsard, B., Bedetti, C., Desrosiers, M., Brambati, S., Doyon, J., Sarica, A., Vasta, R., Cerasa, A., Quattrone, A., Yeatman, J., Khan, A. R., Hodges, W., Alexander, S., Romascano, D., Barakovic, M., Auría, A., Esteban, O., Lemkaddem, A., Thiran, J. P., Cetingul, H. E., Odry, B. L., Mailhe, B., Nadar, M. S., Pizzagalli, F., Prasad, G., Villalon-Reina, J. E., Galvis, J., Thompson, P. M., Requejo, F. D. S., Laguna, P. L., Lacerda, L. M., Barrett, R., Dell’Acqua, F., Catani, M., Petit, L., Caruyer, E., Daducci, A., Dyrby, T. B., Holland-Letz, T., Hilgetag, C. C., Stieltjes, B., & Descoteaux, M. (2017). The challenge of mapping the human connectome based on diffusion tractography. Nature Communications, 8(1), 1349.
Mole, J. P., Subramanian, L., Bracht, T., Morris, H., Metzler-Baddeley, C., & Linden, D. E. (2016). Increased fractional anisotropy in the motor tracts of Parkinson's disease suggests compensatory neuroplasticity or selective neurodegeneration. European Radiology, 26(10), 3327–3335.
Molina, B. S., Hinshaw, S. P., Arnold, L. E., Swanson, J. M., Pelham, W. E., Hechtman, L., et al. (2013). Adolescent substance use in the multimodal treatment study of attention-deficit/hyperactivity disorder (ADHD)(MTA) as a function of childhood ADHD, random assignment to childhood treatments, and subsequent medication. Journal of the American Academy of Child & Adolescent Psychiatry, 52(3), 250–263.
Molina-Holgado, E., Vela, J. M., Arévalo-Martín, A., Almazán, G., Molina-Holgado, F., Borrell, J., et al. (2002). Cannabinoids promote oligodendrocyte progenitor survival: Involvement of cannabinoid receptors and phosphatidylinositol-3 kinase/Akt signaling. Journal of Neuroscience, 22(22), 9742–9753.
Notzon, D. P., Pavlicova, M., Glass, A., Mariani, J. J., Mahony, A. L., Brooks, D. J., Levin F. R. (2016). ADHD is highly prevalent in patients seeking treatment for cannabis use disorders. Journal of Attention Disorders, 1087054716640109.
Nurmedov, S., Metin, B., Ekmen, S., Noyan, O., Yilmaz, O., Darcin, A., & Dilbaz, N. (2015). Thalamic and cerebellar gray matter volume reduction in synthetic cannabinoids users. European Addiction Research, 21(6), 315–320.
Oberlin, B. G., Dzemidzic, M., Tran, S. M., Soeurt, C. M., Albrecht, D. S., Yoder, K. K., & Kareken, D. A. (2013). Beer flavor provokes striatal dopamine release in male drinkers: Mediation by family history of alcoholism. Neuropsychopharmacology, 38(9), 1617–1624.
Onnink, A. M., Zwiers, M. P., Hoogman, M., Mostert, J. C., Kan, C. C., Buitelaar, J., et al. (2014). Brain alterations in adult ADHD: Effects of gender, treatment and comorbid depression. European Neuropsychopharmacology, 24(3), 397–409.
Renard, J., Vitalis, T., Rame, M., Krebs, M. O., Lenkei, Z., Le Pen, G., et al. (2016). Chronic cannabinoid exposure during adolescence leads to long-term structural and functional changes in the prefrontal cortex. European Neuropsychopharmacology, 26(1), 55–64.
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52(3), 1059–1069.
Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155.
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23, S208–S219.
Sotiropoulos, S. N., & Zalesky, A. (2017). Building connectomes using diffusion MRI: Why, how and but. NMR in Biomedicine, e3752.
Spaderna, M., Addy, P. H., & D’Souza, D. C. (2013). Spicing things up: Synthetic cannabinoids. Psychopharmacology, 228(4), 525–540.
Sun, Y., Wang, G. B., Lin, Q. X., Lu, L., Shu, N., Meng, S. Q., Wang, J., Han, H. B., He, Y., & Shi, J. (2017). Disrupted white matter structural connectivity in heroin abusers. Addiction Biology, 22(1), 184–195.
Turgay, A. (1994). Disruptive behavior disorders child and adolescent screening and rating scale for children, adolescents, parents, and teachers. West Blomfield: Integrative Therapy Institute Publication.
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15(1), 273–289.
Van Den Heuvel, M. P., & Sporns, O. (2011). Rich-club organization of the human connectome. Journal of Neuroscience, 31(44), 15775–15786.
van den Heuvel, M. P., & Sporns, O. (2013). Network hubs in the human brain. Trends in Cognitive Sciences, 17(12), 683–696.
Vardakou, I., Pistos, C., & Spiliopoulou, C. (2010). Spice drugs as a new trend: Mode of action, identification and legislation. Toxicology Letters, 197(3), 157–162.
Villemonteix, T., De Brito, S. A., Slama, H., Kavec, M., Balériaux, D., Metens, T., et al. (2015). Grey matter volume differences associated with gender in children with attention-deficit/hyperactivity disorder: A voxel-based morphometry study. Developmental Cognitive Neuroscience, 14, 32–37.
Volkow, N., & Morales, M. (2015). The brain on drugs: From reward to addiction. Cell, 162(4), 712–725.
Weinstein, A. M., Rosca, P., Fattore, L., & London, E. D. (2017). Synthetic cathinone and cannabinoid designer drugs pose a major risk for public health. Frontiers in Psychiatry, 8, 156.
Xia, M., Wang, J., & He, Y. (2013). BrainNet viewer: A network visualization tool for human brain connectomics. PLoS One, 8(7), e68910.
Zalesky, A., Fornito, A., & Bullmore, E. T. (2010). Network-based statistic: Identifying differences in brain networks. Neuroimage, 53(4), 1197–1207.
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., van den Heuvel, M. P., & Breakspear, M. (2016). Connectome sensitivity or specificity: Which is more important? Neuroimage, 142, 407–420.
Zhang, R., Jiang, G., Tian, J., Qiu, Y., Wen, X., Zalesky, A., Li, M., Ma, X., Wang, J., Li, S., Wang, T., Li, C., & Huang, R. (2016). Abnormal white matter structural networks characterize heroin-dependent individuals: A network analysis. Addiction Biology, 21(3), 667–678.
Zhang, Y., Li, M., Wang, R., Bi, Y., Li, Y., Yi, Z., et al. (2017). Abnormal brain white matter network in young smokers: A graph theory analysis study. Brain Imaging and Behavior, 11, 1–12.
Zorlu, N., Di Biase, M. A., Kalaycı, Ç. Ç., Zalesky, A., Bağcı, B., Oğuz, N., et al. (2016). Abnormal white matter integrity in synthetic cannabinoid users. European Neuropsychopharmacology, 26(11), 1818–1825.
Zorlu, N., Çapraz, N., Oztekin, E., Bagci, B., Di Biase, M. A., Zalesky, A., ... & Sarıçiçek, A. (2017). Rich club and reward network connectivity as endophenotypes for alcohol dependence: A diffusion tensor imaging study. Addiction biology. https://doi.org/10.1111/adb.12599.
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This research was funded by Ege University Science and Technology Application and Research Center (grant number 2015 EGEBAM 001) which had no role in the design of the study, collection and analysis of data and decision to publish.
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Çelik, Z.Ç., Çolak, Ç., Di Biase, M.A. et al. Structural connectivity in adolescent synthetic cannabinoid users with and without ADHD. Brain Imaging and Behavior 14, 505–514 (2020). https://doi.org/10.1007/s11682-018-0023-x
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DOI: https://doi.org/10.1007/s11682-018-0023-x