Brain Imaging and Behavior

, Volume 12, Issue 1, pp 274–283 | Cite as

Global white matter microstructural abnormalities associated with addiction liability score in drug naïve youth

  • Leslie Hulvershorn
  • Tom Hummer
  • Yu-Chien Wu
  • Ralph Tarter
  • Parker Rea
  • Amit Anand
  • R. Andrew Chambers
  • Peter Finn
Original Research
  • 103 Downloads

Abstract

Abnormalities in brain white matter (WM) structure have been reported in youths having a family history of substance use disorders (SUDs). It was hypothesized that these abnormalities constitute features of the liability for SUDs transmitted across generations. The association between severity of intergenerational risk for SUD, measured by the Transmissible Liability Index (TLI), and white matter microstructure was examined. Diffusion tensor imaging (DTI) measured WM microstructure in forty-four drug-naïve 10–14 year-olds (N = 19 with parental SUD). Metrics of WM microstructure (i.e., fractional anisotropy, radial diffusivity, mean diffusivity and axial diffusivity) were quantified across the whole brain and in four tracts of interest: anterior corona radiata, superior and inferior longitudinal fasciculi and superior fronto-occipital fasciculi. The TLI was completed by the youths, their parents and, when available, their teachers. The relationship between WM structure and TLI score across the entire group was evaluated using linear multiple regression and between group comparisons were also examined. Fractional anisotropy and radial diffusivity in multiple tracts across the brain were significantly associated with TLI scores. Confirming and extending prior research, the findings indicate that global atypicality in WM tracts was linearly related to liability for eventual SUD development in drug naïve youths.

Keywords

Diffusion Substance use disorders Adolescence White matter 

Notes

Acknowledgements

We gratefully acknowledge Alisha Baker, BS, for the recruitment and scanning of the participants and Levent Kirisci, MD, who scored the TLI. Neuroradiologist Aaron Kamer, MD, consulted on interpreting our findings.

Compliance with ethical standards

Funding and disclosures

This study was funded by the National Institute of Drug Abuse AACAP Physician Scientist Program (K12DA000357) to LH.

Conflict of interest

None of the authors report any conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all parents/guardians of child participants included in the study. Assent was obtained from all child participants.

References

  1. Acheson, A., Wijtenburg, S. A., Rowland, L. M., Winkler, A. M., Gaston, F., Mathias, C. W., Fox, P. T., Lovallo, W. R., Wright, S. N., Hong, L. E., Dougherty, D. M., Kochunov, P. (2014). Assessment of whole brain white matter integrity in youths and young adults with a family history of substance-use disorders. Human brain mapping.Google Scholar
  2. Alexander, A. L., Lee, J. E., Lazar, M., & Field, A. S. (2007). Diffusion tensor imaging of the brain. Neurotherapeutics: the journal of the American Society for Experimental NeuroTherapeutics, 4, 316–329.CrossRefGoogle Scholar
  3. Asato, M.R., Terwilliger, R., Woo, J., Luna, B., 2010. White matter development in adolescence: a DTI study. Cerebral cortex (New York, NY: 1991) 20, 2122–2131.Google Scholar
  4. Baker, S. T., Yucel, M., Fornito, A., Allen, N. B., & Lubman, D. I. (2013). A systematic review of diffusion weighted MRI studies of white matter microstructure in adolescent substance users. Neuroscience and Biobehavioral Reviews, 37, 1713–1723.CrossRefPubMedGoogle Scholar
  5. Bava, S., Jacobus, J., Mahmood, O., Yang, T. T., & Tapert, S. F. (2010). Neurocognitive correlates of white matter quality in adolescent substance users. Brain and Cognition, 72, 347–354.CrossRefPubMedGoogle Scholar
  6. Berg, S. A., Sentir, A. M., Cooley, B. S., Engleman, E. A., & Chambers, R. A. (2014). Nicotine is more addictive, not more cognitively therapeutic in a neurodevelopmental model of schizophrenia produced by neonatal ventral hippocampal lesions. Addiction Biology, 19, 1020–1031.CrossRefPubMedGoogle Scholar
  7. Berns, G. S., Moore, S., & Capra, C. M. (2009). Adolescent engagement in dangerous behaviors is associated with increased white matter maturity of frontal cortex. PloS One, 4, e6773.CrossRefPubMedPubMedCentralGoogle Scholar
  8. Chambers, R. A., Sentir, A. M., Conroy, S. K., Truitt, W. A., & Shekhar, A. (2010). Cortical-striatal integration of cocaine history and prefrontal dysfunction in animal modeling of dual diagnosis. Biological Psychiatry, 67, 788–792.CrossRefPubMedGoogle Scholar
  9. Elofson, J., Gongvatana, W., & Carey, K. B. (2013). Alcohol use and cerebral white matter compromise in adolescence. Addictive Behaviors, 38, 2295–2305.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Enoch, M. A. (2012). The influence of gene-environment interactions on the development of alcoholism and drug dependence. Current Psychiatry Reports, 14, 150–158.CrossRefPubMedPubMedCentralGoogle Scholar
  11. First, M. B., Spitzer, R. L., Gibbon, M., Williams, J. B. (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-patient Edition. (SCID-I/NP).Google Scholar
  12. Giorgio, A., Watkins, K. E., Douaud, G., James, A. C., James, S., De Stefano, N., Matthews, P. M., Smith, S. M., & Johansen-Berg, H. (2008). Changes in white matter microstructure during adolescence. NeuroImage, 39, 52–61.CrossRefPubMedGoogle Scholar
  13. Gruber, S. A., Silveri, M. M., Dahlgren, M. K., & Yurgelun-Todd, D. (2011). Why so impulsive? White matter alterations are associated with impulsivity in chronic marijuana smokers. Experimental and Clinical Psychopharmacology, 19, 231–242.CrossRefPubMedPubMedCentralGoogle Scholar
  14. Herting, M. M., Schwartz, D., Mitchell, S. H., & Nagel, B. J. (2010). Delay discounting behavior and white matter microstructure abnormalities in youth with a family history of alcoholism. Alcoholism, Clinical and Experimental Research, 34, 1590–1602.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Herting, M. M., Fair, D., & Nagel, B. J. (2011). Altered fronto-cerebellar connectivity in alcohol-naïve youth with a family history of alcoholism. NeuroImage, 54, 2582–2589.CrossRefPubMedGoogle Scholar
  16. Hill, S. Y., Terwilliger, R., & McDermott, M. (2013). White matter microstructure, alcohol exposure, and familial risk for alcohol dependence. Psychiatry Research, 212, 43–53.CrossRefPubMedPubMedCentralGoogle Scholar
  17. Hulvershorn, L. A., Finn, P., Hummer, T. A., Leibenluft, E., Ball, B., Gichina, V., & Anand, A. (2013). Cortical activation deficits during facial emotion processing in youth at high risk for the development of substance use disorders. Drug and Alcohol Dependence, 131, 230–237.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Hulvershorn, L. A., Hummer, T. A., Fukunaga, R., Leibenluft, E., Finn, P., Cyders, M. A., Anand, A., Overhage, L., Dir, A., & Brown, J. (2015). Neural activation during risky decision-making in youth at high risk for substance use disorders. Psychiatry Research, 233, 102–111.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Jacobus, J., McQueeny, T., Bava, S., Schweinsburg, B. C., Frank, L. R., Yang, T. T., & Tapert, S. F. (2009). White matter integrity in adolescents with histories of marijuana use and binge drinking. Neurotoxicology and Teratology, 31, 349–355.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Jacobus, J., Squeglia, L. M., Bava, S., & Tapert, S. F. (2013a). White matter characterization of adolescent binge drinking with and without co-occurring marijuana use: a 3-year investigation. Psychiatry Research, 214, 374–381.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Jacobus, J., Thayer, R. E., Trim, R. S., Bava, S., Frank, L. R., & Tapert, S. F. (2013b). White matter integrity, substance use, and risk taking in adolescence. Psychology of addictive behaviors: journal of the Society of Psychologists in Addictive Behaviors, 27, 431–442.CrossRefGoogle Scholar
  22. Jellison, B. J., Field, A. S., Medow, J., Lazar, M., Salamat, M. S., & Alexander, A. L. (2004). Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR. American Journal of Neuroradiology, 25, 356–369.PubMedGoogle Scholar
  23. Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17, 825–841.CrossRefPubMedGoogle Scholar
  24. Kaufman, J., Birmaher, B., Brent, D., Rao, U. M. A., Flynn, C., Moreci, P., Williamson, D., & Ryan, N. (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 and Adolescent Psychiatry, 36, 980–988.CrossRefPubMedGoogle Scholar
  25. Kirisci, L., Mezzich, A., & Tarter, R. (1995). Norms and sensitivity of the adolescent version of the drug use screening inventory. Addictive Behaviors, 20, 149–157.CrossRefPubMedGoogle Scholar
  26. Kirisci, L., Tarter, R., Mezzich, A., Ridenour, T., Reynolds, M., & Vanyukov, M. (2009). Prediction of cannabis use disorder between boyhood and young adulthood: clarifying the phenotype and environtype. The American Journal on Addictions, 18, 36–47.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Kirisci, L., Tarter, R., Ridenour, T., Zhai, Z. W., Fishbein, D., Reynolds, M., & Vanyukov, M. (2013). Age of alcohol and cannabis use onset mediates the association of transmissible risk in childhood and development of alcohol and cannabis disorders: evidence for common liability. Experimental and Clinical Psychopharmacology, 21, 38–45.CrossRefPubMedGoogle Scholar
  28. Kirisci, L., Tarter, R., Ridenour, T., Reynolds, M., Horner, M., & Vanyukov, M. (2015). Externalizing behavior and emotion dysregulation are indicators of transmissible risk for substance use disorder. Addictive Behaviors, 42, 57–62.CrossRefPubMedGoogle Scholar
  29. Li, W., Li, Q., Zhu, J., Qin, Y., Zheng, Y., Chang, H., Zhang, D., Wang, H., Wang, L., Wang, Y., & Wang, W. (2013). White matter impairment in chronic heroin dependence: a quantitative DTI study. Brain Research, 1531, 58–64.CrossRefPubMedGoogle Scholar
  30. Lin, F., Wu, G., Zhu, L., & Lei, H. (2013). Heavy smokers show abnormal microstructural integrity in the anterior corpus callosum: a diffusion tensor imaging study with tract-based spatial statistics. Drug and Alcohol Dependence, 129, 82–87.CrossRefPubMedGoogle Scholar
  31. McQueeny, T., Schweinsburg, B. C., Schweinsburg, A. D., Jacobus, J., Bava, S., Frank, L. R., & Tapert, S. F. (2009). Altered white matter integrity in adolescent binge drinkers. Alcoholism, Clinical and Experimental Research, 33, 1278–1285.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Passamonti, L., Fairchild, G., Fornito, A., Goodyer, I. M., Nimmo-Smith, I., Hagan, C. C., & Calder, A. J. (2012). Abnormal anatomical connectivity between the amygdala and orbitofrontal cortex in conduct disorder. PloS One, 7, e48789.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Peters, B. D., Szeszko, P. R., Radua, J., Ikuta, T., Gruner, P., DeRosse, P., Zhang, J. P., Giorgio, A., Qiu, D., Tapert, S. F., Brauer, J., Asato, M. R., Khong, P. L., James, A. C., Gallego, J. A., & Malhotra, A. K. (2012). White matter development in adolescence: diffusion tensor imaging and meta-analytic results. Schizophrenia Bulletin, 38, 1308–1317.CrossRefPubMedPubMedCentralGoogle Scholar
  34. Ridenour, T. A., Kirisci, L., Tarter, R. E., & Vanyukov, M. M. (2011). Could a continuous measure of individual transmissible risk be useful in clinical assessment of substance use disorder? Findings from the National Epidemiological Survey on alcohol and related conditions. Drug and Alcohol Dependence, 119, 10–17.CrossRefPubMedPubMedCentralGoogle Scholar
  35. Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., Niazy, R. K., Saunders, J., Vickers, J., Zhang, Y., De Stefano, N., Brady, J. M., & Matthews, P. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(Suppl 1), S208–S219.CrossRefPubMedGoogle Scholar
  36. Squeglia, L. M., Jacobus, J., Brumback, T., Meloy, M. J., & Tapert, S. F. (2014). White matter integrity in alcohol-naive youth with a family history of alcohol use disorders. Psychological Medicine, 44, 2775–2786.CrossRefPubMedPubMedCentralGoogle Scholar
  37. Tarter, R. E., Kirisci, L., Mezzich, A., Cornelius, J. R., Pajer, K., Vanyukov, M., Gardner, W., Blackson, T., & Clark, D. (2003). Neurobehavioral disinhibition in childhood predicts early age at onset of substance use disorder. The American Journal of Psychiatry, 160, 1078–1085.CrossRefPubMedGoogle Scholar
  38. Thatcher, D. L., Pajtek, S., Chung, T., Terwilliger, R. A., & Clark, D. B. (2010). Gender differences in the relationship between white matter organization and adolescent substance use disorders. Drug and Alcohol Dependence, 110, 55–61.CrossRefPubMedPubMedCentralGoogle Scholar
  39. Thayer, R. E., Callahan, T. J., Weiland, B. J., Hutchison, K. E., & Bryan, A. D. (2013). Associations between fractional anisotropy and problematic alcohol use in juvenile justice-involved adolescents. The American Journal of Drug and Alcohol Abuse, 39, 365–371.CrossRefPubMedPubMedCentralGoogle Scholar
  40. Vanyukov, M. M., Kirisci, L., Tarter, R. E., Simkevitz, H. F., Kirillova, G. P., Maher, B. S., & Clark, D. B. (2003a). Liability to substance use disorders: 2. A measurement approach. Neuroscience and Biobehavioral Reviews, 27, 517–526.CrossRefPubMedGoogle Scholar
  41. Vanyukov, M. M., Tarter, R. E., Kirisci, L., Kirillova, G. P., Maher, B. S., & Clark, D. B. (2003b). Liability to substance use disorders: 1. Common mechanisms and manifestations. Neuroscience and Biobehavioral Reviews, 27, 507–515.CrossRefPubMedGoogle Scholar
  42. Vanyukov, M. M., Kirisci, L., Moss, L., Tarter, R. E., Reynolds, M. D., Maher, B. S., Kirillova, G. P., Ridenour, T., & Clark, D. B. (2009). Measurement of the risk for substance use disorders: phenotypic and genetic analysis of an index of common liability. Behavior Genetics, 39, 233–244.CrossRefPubMedPubMedCentralGoogle Scholar
  43. Vanyukov, M., Kim, K., Irons, D., Kirisci, L., Neale, M., Ridenour, T., Tarter, R. (2014). Genetic relationship between the addiction diagnosis in adults and their childhood measure of addiction liability. Behavioral Genetics (in press).Google Scholar
  44. Vanyukov, M., Kim, K., Irons, D., Kirisci, L., Neale, M., Ridenour, T., Hicks, B., Tarter, R., Reynolds, M., Kirillova, G., McGue, M., & Iacono, W. (2015). Genetic relationship between the addiction diagnosis in adults and their childhood measure of addiction liability. Behavior Genetics, 45, 1–11.CrossRefPubMedGoogle Scholar
  45. Wetherill, R. R., Bava, S., Thompson, W. K., Boucquey, V., Pulido, C., Yang, T. T., & Tapert, S. F. (2012). Frontoparietal connectivity in substance-naive youth with and without a family history of alcoholism. Brain Research, 1432, 66–73.CrossRefPubMedGoogle Scholar
  46. Yeh, P.-H., Simpson, K., Durazzo, T. C., Gazdzinski, S., & Meyerhoff, D. J. (2009). Tract-based spatial statistics (TBSS) of diffusion tensor imaging data in alcohol dependence: abnormalities of the motivational neurocircuitry. Psychiatry Research: Neuroimaging, 173, 22–30.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Leslie Hulvershorn
    • 1
  • Tom Hummer
    • 1
  • Yu-Chien Wu
    • 2
  • Ralph Tarter
    • 3
  • Parker Rea
    • 1
  • Amit Anand
    • 4
  • R. Andrew Chambers
    • 1
  • Peter Finn
    • 5
  1. 1.Department of PsychiatryIndiana University School of MedicineIndianapolisUSA
  2. 2.Department of RadiologyIndiana University School of MedicineIndianapolisUSA
  3. 3.Center for Education and Drug Abuse Research (CEDAR)University of Pittsburgh School of PharmacyPittsburghUSA
  4. 4.Center for Behavioral HealthCleveland ClinicClevelandUSA
  5. 5.Department of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA

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