Abstract
Rates of cannabis use among adolescents are high, and are increasing concurrent with changes in the legal status of marijuana and societal attitudes regarding its use. Recreational cannabis use is understudied, especially in the adolescent period when neural maturation may make users particularly vulnerable to the effects of Δ-9-tetrahydrocannabinol (THC) on brain structure. In the current study, we used voxel-based morphometry to compare gray matter volume (GMV) in forty-six 14-year-old human adolescents (males and females) with just one or two instances of cannabis use and carefully matched THC-naive controls. We identified extensive regions in the bilateral medial temporal lobes as well as the bilateral posterior cingulate, lingual gyri, and cerebellum that showed greater GMV in the cannabis users. Analysis of longitudinal data confirmed that GMV differences were unlikely to precede cannabis use. GMV in the temporal regions was associated with contemporaneous performance on the Perceptual Reasoning Index and with future generalized anxiety symptoms in the cannabis users. The distribution of GMV effects mapped onto biomarkers of the endogenous cannabinoid system providing insight into possible mechanisms for these effects.
SIGNIFICANCE STATEMENT Almost 35% of American 10th graders have reported using cannabis and existing research suggests that initiation of cannabis use in adolescence is associated with long-term neurocognitive effects. We understand very little about the earliest effects of cannabis use, however, because most research is conducted in adults with a heavy pattern of lifetime use. This study presents evidence suggesting structural brain and cognitive effects of just one or two instances of cannabis use in adolescence. Converging evidence suggests a role for the endocannabinoid system in these effects. This research is particularly timely as the legal status of cannabis is changing in many jurisdictions and the perceived risk by youth associated with smoking cannabis has declined in recent years.
Discussion
We present evidence of GMV differences in adolescents associated with only one or two instances of cannabis use. Although novel, this work is consistent with reports of a dose–response effect of cannabis on behavioral and brain measures following heavier use (Lorenzetti et al., 2010; Silins et al., 2014). We identified significantly greater GMV in adolescents who reported only one or two instances of cannabis use relative to cannabis naive controls in large medial temporal clusters incorporating the amygdala, hippocampus, and striatum, extending into the left prefrontal cortex. Significantly greater GMV was also observed in the lingual gyri, posterior cingulate, and cerebellum. The regions identified in this whole-brain, VBM approach replicated previous findings of differences in volume (Yücel et al., 2008; Ashtari et al., 2011; Schacht et al., 2012) and shape (Gilman et al., 2014; Smith et al., 2014, 2015) associated with cannabis use in ROI studies and with the spatial distribution of the eCB system (Burns et al., 2007). Although cannabis use has been associated with reduced brain volumes, studies typically report on adults with heavy substance use histories (cf. Ashtari et al., 2011). Gilman et al. (2014), however, have reported gray-matter density increases in the amygdala and nucleus accumbens of young adult recreational users and Medina et al. (2007) observed hippocampal enlargement in cannabis using adolescents. Our results are also consistent with the Avon Longitudinal Study of Parents and Children (French et al., 2015), which showed a trend for greater cortical thickness in male adolescents with <5 instances of cannabis use relative to THC-naive controls.
Converging evidence suggests that these effects may be a consequence of cannabis exposure. GMV differences could not be explained by group differences in demographic, personality, psychopathology, or other substance use factors. Examination of THC-naive 14-year-olds who later used cannabis showed no GMV differences, even using a more liberal ROI test, suggesting that the differences do not precede cannabis use and are not because of unidentified factors in those predisposed to use. Finally, the spatial distribution of GMV effects was associated with the eCB system, suggesting cannabis exposure may cause these findings.
The preclinical literature presents a number of possible mechanisms by which low levels of cannabis exposure could result in greater GMV relative to THC-naive controls. Adolescent rats treated with cannabinoid agonist showed altered gliogenesis in regions including the striatum and greater preservation of oligodendroglia relative to control animals (Bortolato et al., 2014). Zebra finches treated with cannabinoid agonist showed greater dendritic spine densities (Gilbert and Soderstrom, 2011); critically, these effects were observed in late-prenatal but not adult animals. Of particular relevance to this study, a single dose of Δ9THC transiently abolished eCB-mediated long-term depression (LTD) in the nucleus accumbens and hippocampus of adolescent mice (Mato et al., 2004). Suspension of LTD may interrupt maturation-related neural pruning and preserve gray matter. Future studies should assess whether these processes operate in human adolescents and whether they produce persisting alterations in GMV.
These findings should be interpreted in light of the study’s limitations. The IMAGEN sample is racially and ethnically homogenous so it remains to be determined whether the findings generalize to youth from more diverse backgrounds. Substance use was assessed using self-report and we do not have standard dose units of cannabis nor information on mode of use or a measure of drug metabolites. Combining images from different sites and imaging platforms remains controversial and is not completely controlled by including site as a covariate. Future studies should replicate the present results using images acquired at the same site on the same scanner or with equal numbers of cases and controls per scanner. We also note that the CNR1 gene expression (Hawrylycz et al., 2012) and CB1 receptor density (D’Souza et al., 2016) maps were generated in independent samples of adults and may not accurately represent the eCB system in our sample of adolescents. Although we report significant spatial associations between GMV effects and both CNR1 gene expression and CB1 receptor density, the effect sizes were small and any suggestion that these associations represent mechanisms for the effects we observe is speculative and requires further investigation.
We adopted a whole-brain, VBM approach to detect effects that were not limited by anatomical boundaries and to allow exploration of spatial relationships between GMV effects and the eCB system. There is evidence, however, that brain perfusion can influence VBM measures of local volume (Franklin et al., 2013, 2015; Ge et al., 2017; cf. Hawkins et al., 2018) so future studies should combine VBM with other measures of brain structure to provide confirmatory evidence. In particular, shape analysis has been shown to be sensitive to brain structural differences associated with cannabis use (Gilman et al., 2014; Smith et al., 2014, 2015; Weiland et al., 2015). Moreover, combining morphometry metrics allows for testing of associations between them, which can identify different relationships between shape deformations and local volume (Gilman et al., 2014) providing evidence of further differences between cannabis users and controls.
One source of variability in the human findings on brain structural correlates of cannabis use may be comorbid substance use (Weiland et al., 2015; Gillespie et al., 2018). Given recent evidence of different patterns of functional connectivity in groups using alcohol, nicotine, and cannabis alone and in combination (Vergara et al., 2018), it will be important to account for any possible interaction effects of cannabis with other psychoactive substances. This issue is particularly important considering the ways in which comorbid substance use has been addressed in two recent, widely cited studies. Gilman et al. (2014) covaried for alcohol and nicotine use and found gray-matter density increases and shape deformations associated with cannabis use. Weiland et al. (2015) matched groups on alcohol and nicotine use and reported no morphometric differences associated with cannabis use, concluding that previously reported differences associated with cannabis may instead be attributable to alcohol use. The participants in Weiland et al.’s (2015) study, however, were using alcohol and nicotine at higher levels than those in Gilman et al.’s (2014) study. It is possible that cannabis, alcohol, and nicotine have differential effects on brain morphometry; specifically, recreational cannabis use has been associated with volume increases, whereas alcohol has been associated with volume reductions. In the current study, we matched the groups on alcohol and nicotine use and, within the cannabis using group, neither alcohol nor nicotine use was associated with individual differences in GMV, suggesting that the GMV differences we report are associated with cannabis use.
We note individual differences in GMV effects: although regional GMV was greater at the group level for adolescents with low levels of cannabis exposure, the distributions showed a high degree of overlap such that many cannabis users had GMV equivalent to that of controls. None of the tested demographic, personality, or substance use factors stratified GMV in the cannabis users. We note evidence that an association between cannabis use and cortical thickness was stratified by genetic risk for schizophrenia (French et al., 2015) and that an association between cannabis use and hippocampal shape was stratified by dopamine-relevant genes (Batalla et al., 2018). Some adolescents may be vulnerable to GMV effects at extremely low levels of cannabis use and it will be critical to identify those at risk as these structural brain changes may be associated with individual risk for psychopathology and deleterious effects on mood and cognition.
Of the behavioral variables tested, only sensation seeking and agoraphobia differed between the cannabis users and controls and these factors were not related to GMV differences. In the cannabis using participants, GMV in the medial temporal clusters was associated with PRIQ and psychomotor speed such that greater GMV in these regions was associated with reduced performance. The finding that right medial temporal GMV predicted generalized anxiety symptoms at follow-up for those participants who had used cannabis should be interpreted with caution given the small sample size and that we were not able to identify factors that drove the individual differences in cannabis effects on GMV at baseline. These findings are notable, however, as panic and anxiety symptoms are frequently reported side effects by naive and occasional cannabis users (Hall and Solowij, 1998). We also note fMRI evidence of hypersensitivity of the amygdala to signals of threat in a partly overlapping sample of cannabis using adolescents (Spechler et al., 2015) and a relationship between adolescent cannabis use and future mood complaints (Wittchen et al., 2007), even with comparatively low levels of use (Cheung et al., 2010).
We have revealed greater GMV in adolescents with only one or two instances of cannabis use in regions rich in CB1 receptors and CNR1 gene expression. Critically, we were able to control for a range of demographic and substance use effects, to confirm that these structural brain effects were not associated with comorbid psychopathology, and to demonstrate that these effects were unlikely to precede cannabis use. The pattern of results is characterized by individual differences in GMV effects in the cannabis users; these individual differences were associated with PRIQ and with vulnerability to future symptoms of generalized anxiety. Given the increasing levels of cannabis use among adolescents today, we suggest that studying the effects of recreational use early in life is an area of particular importance that should be addressed in the future by large scale, prospective studies.
Source: Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence | Journal of Neuroscience (jneurosci.org) March 2019