Effect of Long-term Cannabis Use on Axonal Fibre Connectivity

Andrew Zalesky; Nadia Solowij; Murat Yücel; Dan I. Lubman; Michael Takagi; Ian H. Harding; Valentina Lorenzetti; Ruopeng Wang; Karissa Searle; Christos Pantelis; Marc Seal

Disclosures

Brain. 2012;135(7):2245-2255. 

In This Article

Discussion

This is the first study to comprehensively investigate axonal fibre connectivity among individuals with a history of longstanding, heavy cannabis use. Axonal connectivity was found to be impaired in the right fimbria of the hippocampus (fornix), splenium of the corpus callosum and commissural fibres extending to the precuneus. The fornix and corpus callosum are two of only a very small number of fibre-enriched structures that have abundant cannabinoid receptors in the developing rat brain (Romero et al., 1997; Molina-Holgado et al., 2002). All users in this study commenced regular use during adolescence or early adulthood, a time of continuing white matter development (Barnea-Gorlay et al., 2005). As such, our findings are particularly compelling given that our whole-brain investigation of white matter exclusively localized some of the very few fibre pathways that have abundant cannabinoid receptors during brain development.

This is also the first study to demonstrate that the age at which regular cannabis use begins is a key factor determining the severity of any microstructural white matter alteration. Radial and axial diffusivity were both positively associated with the age at which regular use commenced. Caution should be exercised when interpreting this result in terms of underlying tissue microstructure. An increase in radial diffusivity, which reflects the diffusion of water perpendicular to a fibre, is generally considered a marker of reduced myelination (Song et al., 2005). In contrast, a decrease in axial diffusivity, which reflects the diffusion of water parallel to a fibre, is often considered a marker of axonal injury (Budde et al., 2009). In some circumstances, however, a bona fide decrease in axial diffusivity can result in a commensurate decrease in radial diffusivity (Wheeler-Kingshott and Cercignani, 2009).

This was the situation encountered in this study and was most likely the result of crossing fibres, eigenvalue sorting bias (Pierpaoli and Basser, 1996) or microstructural geometry that was not fully characterizable with the diffusion tensor model. As such, it was difficult to unequivocally ascertain a microstructural basis for the association with the age at which regular use commenced. This should not be misconstrued as evidence against the validity or statistical significance of the association itself. The association presents compelling evidence for white matter reacting differently to cannabis exposure commencing during adolescence compared with adulthood, most likely due to the high concentration of cannabinoid receptors contained within structures, such as the corpus callosum and fornix during adolescence. The association remained significant when biological age and cumulative lifetime exposure were included as nuisance regressors, arguing against simple brain maturation or dose-dependent effects. Using a crossing fibre model (Tournier et al., 2008) may have enabled better characterization of the association's microstructural basis; however, the MRI parameters used in this study were not ideally suited to use of such models.

This result accords with an earlier study that reported an analogous association between fractional anisotropy and age of regular cannabis and inhalant use among adolescent users (Yücel et al., 2010). It is also in line with a recent study reporting that the age of onset of cannabis use positively correlated with measures of frontal fractional anisotropy and inversely with mean diffusivity (Gruber et al., 2011). Our finding also supports mounting evidence suggesting a link between adolescent cannabis use and schizophrenia in later life (Rais et al., 2008; Peters et al., 2009; Dekker et al., 2010; Ho et al., 2011; James et al., 2011) as well as with evidence for greater adverse cognitive effects in adolescent cannabis users (Solowij et al., 2011a, 2012). An earlier study (Arnone et al., 2008) using a sophisticated region of interest approach also found evidence of microstructural alteration in the corpus callosum of cannabis users. More generally, a review of diffusion tensor imaging studies in alcohol, cannabis and cocaine addiction noted focal disruption of commissural connectivity in the corpus callosum (Arnone et al., 2006). Previous studies investigating white matter among cannabis users have recruited substantially smaller samples. With a sample size of 59, this study is better positioned to resolve the lack of consistency in findings reflected across these prior studies. Furthermore, unlike most of the previous studies that confined their investigations to predefined regions of interest, the novel data-driven strategy used in this study was not biased by a subjective choice of regions of interest. All axonal fibre pathways were interrogated using a powerful exploratory approach controlling for the family-wise error rate.

The size of the connectivity differences in per cent terms was substantial, with an 84% reduction in streamline count in the fimbria and an 88% reduction in the commissural pathways extending to the precuneus. This should not be interpreted as evidence for a substantial reduction in the absolute number of axonal fibres comprising these structures, since a streamline is not tantamount to an individual axon. The precise microstructural underpinnings of an altered streamline count are not well understood, hence the reason for using the more interpretable measures of radial and axial diffusivity in the correlational analysis. Nevertheless, the substantial differences suggest these results are robust and reproducible.

Several potential limitations must be noted. Tractography was used to create high-resolution white matter connectivity maps indicating the extent of axonal connectivity between thousands of distinct voxel pairs. The accuracy of these connectivity maps was contingent on the reliability of the fibre tracking method. Fibre trajectories were tracked by following the principle direction of water diffusion indicated by the diffusion tensor (Conturo et al., 1999). While this is a reliable tracking method known to yield reproducible results (Catani et al., 2002), some fibres may have been overlooked due to inaccuracy of the diffusion tensor model in regions of complex fibre geometry (e.g. crossing fibres), partial volume effects or distal/flare bias (Zalesky et al., 2009). Between-group differences could not be tested at fibres that were not tracked, thus representing a minimal risk for type II error. Another potential risk for type II error was the narrow range of streamline counts evident for some voxel pairs. Streamline counts that rarely exceeded the values of 0 and 1 across individuals provide less sensitivity than a wider and dynamic range of counts. This range was widened by increasing the overall total number of streamlines generated, although beyond a certain increase, the stochastic diversity of the data was exhausted and computational tractability became a concern. The risk of committing a type II error due to this factor was minimal because very low streamline counts were most likely indicative of spurious tracking results.

While cannabis use was ascertained primarily by self-report (corroborated by urinalysis), self-report measures are generally reliable (Harrison, 1997; Buchan et al., 2002) and have been shown to be associated with brain structural alterations in a range of studies (Matochik et al., 2005; Yücel et al., 2008; Cousijn et al., 2012). Cannabis users had significantly greater trait anxiety and depressive symptoms, and smoked significantly greater amounts of tobacco than non-users. However, no participant had ever been diagnosed with an anxiety or depressive disorder or had sought treatment for such symptoms. While it is possible that reported between-group differences were mediated by differences in trait anxiety, depressive symptoms or tobacco use, a post hoc analysis revealed both connectivity differences remained significant after controlling for these variables.

The cannabis users of this study were asked to abstain from cannabis for at least 12 h (median self-reported abstinence: 15 h). Cannabinoid residues may affect cognition and measures of functional brain activation (Martin-Santos et al., 2010; Solowij and Pesa, 2012). Diffusion tensor metrics, on the other hand, are thought to index structural/morphological integrity or abnormalities, not functional abnormalities. Further, these metrics tend to be stable over time (Vollmar et al., 2010), and would be less affected by transient states, such as residual intoxication or withdrawal than are neurocognitive or functional brain activation measures. Structural or morphological abnormalities may, however, have functional consequences. It is possible that the white matter abnormalities associated with cannabis use could be reversible given a sufficient period of abstinence or functional adaptation. An important avenue for future research is to clarify whether abstinence can lead to recovery of axonal injury and the associated time-course.

Our results suggest that long-term cannabis use is hazardous to white matter in the developing brain. Given the association between cannabis-related harms and age of onset of regular use, delaying use may minimize such harmful effects. Disturbed brain connectivity in cannabis users may underlie cognitive impairment and vulnerability to psychosis, depression and anxiety disorders (Lim et al., 2002), all of which are significant public health concerns. White matter alterations have been associated with various functional and clinical outcomes in schizophrenia, including illness, symptomatic and cognitive measures (Walterfang et al., 2011), with white matter pathology underlying faulty integration of cortical–cerebellar–thalamic–cortical circuits thought to play a primary role in the observed cognitive deficits (Wexler et al., 2009). Similar connectivity disturbances, particularly in the fimbria of the hippocampus and commissural fibres extending to the precuneus reported in this study, may underlie the memory impairment and other cognitive deficits that are observed in long-term heavy cannabis users (Solowij et al., 2011b; Solowij and Pesa, 2012). The effect of long-term cannabis use on functional brain connectivity (van den Heuvel and Hulshoff Pol, 2010) and network topology (He and Evans, 2010; Rubinov and Sporns, 2010) remains an important avenue to pursue.

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