Associations between adolescent cannabis use frequency and adult brain structure : A prospective study of boys followed to adulthood, M.H. Meier et al., 2019

Associations between adolescent cannabis use frequency and adult brain structure : A prospective study of boys followed to adulthood.

Madeline H. Meier, Roberta A. Schriber, Jordan Beardslee, Jamie Hanson, Dustin Pardini
Drug and Alcohol Dependence, 2019, 202, 191-199
Copyright © 2019. Published by Elsevier B.V.
PMID : 31357120
DOI : 10.1016/j.drugalcdep.2019.05.012

Abstract

BACKGROUND : Few studies have tested the hypothesis that adolescent cannabis users show structural brain alterations in adulthood. The present study tested associations between prospectively-assessed trajectories of adolescent cannabis use and adult brain structure in a sample of boys followed to adulthood.

METHODS : Data came from the Pittsburgh Youth Study – a longitudinal study of ˜1000 boys. Boys completed self-reports of cannabis use annually from age 13-19, and latent class growth analysis was used to identify different trajectories of adolescent cannabis use. Once adolescent cannabis trajectories were identified, boys were classified into their most likely cannabis trajectory. A subset of boys (n = 181) subsequently underwent structural neuroimaging in adulthood, when they were between 30-36 years old on average. For this subset, we grouped participants according to their classified adolescent cannabis trajectory and tested whether these groups showed differences in adult brain structure in 14 a priori regions of interest, including six subcortical (volume only: amygdala, hippocampus, nucleus accumbens, caudate, putamen, and pallidum) and eight cortical regions (volume and thickness: superior frontal gyrus; caudal and rostral middle frontal gyrus; inferior frontal gyrus, separated into pars opercularis, pars triangularis, and pars orbitalis; lateral and medial orbitofrontal gyrus).

RESULTS : We identified four adolescent cannabis trajectories: non-users/infrequent users, desisters, escalators, and chronic-relatively frequent users. Boys in different trajectory subgroups did not differ on adult brain structure in any subcortical or cortical region of interest.

CONCLUSIONS : Adolescent cannabis use is not associated with structural brain differences in adulthood.

KEYWORDS : Adolescent; Brain structure; Cannabis; Magnetic resonance imaging

1. Introduction
Cannabis is, by far, the most commonly used illicit drug by adolescents. Data from the nationally representative Monitoring the Future study showed that 10.5%, 27.5%, and 35.9% of 8th, 10th, and 12th graders used cannabis in 2018, respectively (Johnston, 2019). These high rates of adolescent cannabis use are concerning, because adolescents might be particularly vulnerable to the effects of cannabis on brain structure and function. Specifically, it has been proposed that cannabis use disrupts critical brain changes that occur in adolescence, including myelination, synaptic pruning, and maturation of the endogenous cannabinoid system (Brumback et al., 2016; Lisdahl et al., 2013; Lisdahl et al., 2014; Lubman et al., 2015; Solowij and Battisti, 2008), making adolescent cannabis users susceptible to perhaps lasting structural and functional brain alterations. However, relatively few studies have examined associations between adolescent cannabis use and adult brain structure. The few studies that have examined this association have mainly relied on adult cannabis users’ retrospective reports of age-of-onset of cannabis use (Ashtari et al., 2011; Battistella et al., 2014; Cousijn et al., 2012; Filbey et al., 2015; Gilman et al., 2014; Lorenzetti et al., 2014; Matochik et al., 2005; Pagliaccio et al., 2015; Wilson et al., 2000), which are subject to recall bias. Moreover, reports of age-of-onset of cannabis use do not capture important individual differences in frequency and duration of cannabis use in adolescence, which may be important for understanding adolescents’ vulnerability to lasting cannabis effects. The present study redressed these limitations by obtaining prospective reports of cannabis use annually from age 13-19 and by assessing brain structure later in adulthood. To jointly account for age-of-onset, frequency, and duration of adolescent cannabis use, we mapped different trajectories of cannabis use over the adolescent years (e.g., infrequent use/non-use, desisting use, escalating use, chronic-relatively frequent use) and tested associations between trajectories of adolescent cannabis use and adult brain structure.
Case-control studies of adult cannabis users and comparison individuals have shown evidence of neuroanatomical differences, particularly in brain regions enriched with cannabinoid receptors, such as the hippocampus (Ashtari et al., 2011; Lorenzetti et al., 2015; Schacht et al., 2012; Yücel et al., 2008), amygdala (Lorenzetti et al., 2015; Schacht et al., 2012; Yücel et al., 2008), striatum (Pagliaccio et al., 2015), and prefrontal cortex (Battistella et al., 2014; Filbey et al., 2014). The most consistent finding is that cannabis users have lower hippocampal volume (Batalla et al., 2013; Brumback et al., 2016; Lorenzetti et al., 2014; Lorenzetti et al., 2016; Rocchetti et al., 2013). Some of these studies examined associations between retrospectively-reported age-of-onset of cannabis use and adult brain structure (e.g., (Ashtari et al., 2011; Battistella et al., 2014; Cousijn et al., 2012; Filbey et al., 2015; Gilman et al., 2014; Matochik et al., 2005; Pagliaccio et al., 2015; Wilson et al., 2000). Reviews of these studies (Lorenzetti et al., 2014; Lorenzetti et al., 2016) have revealed that, although a few studies have found evidence of an association between an earlier age-of-onset of cannabis use and adult brain structure (e.g., (Battistella et al., 2014; Wilson et al., 2000), most studies have not (Ashtari et al., 2011; Cousijn et al., 2012; Filbey et al., 2015; Gilman et al., 2014; Lorenzetti et al., 2014; Matochik et al., 2005).
There are a number of possible explanations for inconsistent or null findings regarding the relation between an earlier age-of-onset of cannabis use and adult brain structure. One explanation is that recall bias contributes to inaccurate retrospective reports of age-of-onset of cannabis use. In fact, a number of studies have shown evidence of recall bias in retrospective reports of age-of-onset of cannabis use and other substance use (Johnson and Schultz, 2005; Shillington et al., 2012). Another explanation is that different studies define age-of-onset differently, with some studies reporting on age of first use and other studies reporting on age of first regular use, with definitions of regular use also varying across studies (Lorenzetti et al., 2016). A third explanation is that reports of an earlier age-of-onset do not capture important individual differences in frequency and duration of cannabis use in adolescence that might be associated with risk for lasting brain alterations. For example, frequent cannabis use throughout adolescence is more likely to be associated with lasting brain alterations than short-term, infrequent cannabis use in adolescence. Consistent with this notion, some evidence suggests that cannabis users with the highest levels of cannabis exposure show the most pronounced brain differences (Ashtari et al., 2011; Batalla et al., 2013; Cousijn et al., 2012; Lorenzetti et al., 2016; Yücel et al., 2008). Importantly, the aforementioned explanations are not mutually exclusive. It is also possible that adolescent cannabis use might not have lasting effects on brain structure.
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