Testing associations between cannabis use and subcortical volumes in two large population‐based samples

Gillespie, Nathan A.; Neale, Michael C.; Bates, Timothy C.; Eyler, Lisa T.; Fennema-Notestine, Christine; Vassileva, Jasmin; Lyons, Michael J.; Prom‐Wormley, Elizabeth; McMahon, Katie L.; Thompson, Paul M.; Zubicaray, Greig I. de; Hickie, Ian B.; McGrath, John J.; Strike, Lachlan T.; Rentería, Miguel E.; Panizzon, Matthew S.; Martin, Nicholas G.; Franz, Carol E.; Kremen, William S.; Wright, Margaret J.

doi:10.1111/add.14252

Cited by 25 publications

(23 citation statements)

References 78 publications

(131 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The present results differ from those of Gillespie et al 31 and Chye et al 20 , in which results indicated an absence of association between non-clinical levels of cannabis use and hippocampal or amygdalar morphometry. One likely reason for this is the improved resolution of the measurement of cannabis use in the current study, which measured cannabis use using both selfreported and biological measures, assessed for use both past and recent used, and distinguished between problematic and non-problematic cannabis use.…”

Section: Cannabis Hippocampus Amygdala: 15contrasting

confidence: 99%

“…One exception includes a study by Chye et al that examined 22 non-dependent cannabis users, finding them not to differ from healthy controls in hippocampal volume 20 . Additionally, the largest investigation of cannabis use in a non-clinical sample to date was a two-part study, with study one including 622 young adults and study two including 474 middle-aged men drawn from the general population; this investigation also did not find associations between hippocampal or amygdalar volume and cannabis use in either study after correcting for multiple comparisons 31 .…”

Section: Cannabis Hippocampus Amygdala:mentioning

confidence: 97%

See 1 more Smart Citation

Cannabis Use is Associated with Lower Hippocampus and Amygdala Volume: High-Resolution Segmentation of Structural Subfields in a Large Non-clinical Sample

Mm¹,

MacKillop²,

Sweet³

2019

Preprint

View full text Add to dashboard Cite

There is mixed evidence that individuals who use cannabis have reduced hippocampal and amygdalar gray matter volume, potentially because of small sample sizes and imprecise morphological characterization. New automated segmentation procedures have improved the measurement of these structures and allow better examination of their subfields, which have been linked to distinct aspects of memory and emotion. The current study applies this new segmentation procedure to the Human Connectome Project Young Adult dataset (N = 1081) to investigate associations of cannabis use with gray matter volume in the hippocampus and amygdala. Results revealed significant bilateral inverse associations of hippocampal volume with recent cannabis use (positive THC urine drug screen) and total lifetime consumption (ps<.001), as well as association of the left amygdala total lifetime consumption (p<.001). Hippocampal subfield analyses indicated these associations were primarily driven by the head of the hippocampus, the first section of the cornu amonis (CA1), and the subicular complex, which have been linked to verbal working memory, episodic memory, and spatial memory respectively. In the amygdala, the association was driven by subfields in the basolateral complex, which links the amygdala to the cortex and is critical in emotion regulation. No associations were detected for age of cannabis initiation or lifetime presence of cannabis use disorder. In one of the largest studies to date, these results support the hypothesis that cannabis use is linked with hippocampal and amygdalar volume and clarify both the specific subfields and the specific aspects of cannabis use that are responsible for these links.

show abstract

Section: Cannabis Hippocampus Amygdala: 15contrasting

confidence: 99%

Section: Cannabis Hippocampus Amygdala:mentioning

confidence: 97%

Cannabis Use is Associated with Lower Hippocampus and Amygdala Volume: High-Resolution Segmentation of Structural Subfields in a Large Non-clinical Sample

Mm¹,

MacKillop²,

Sweet³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Preclinical evidence has consistently demonstrated a causal relationship between cannabis exposure and changes to brain morphology (for review, see Panlilio and Justinova, 2018). The human evidence, however, has been variable reporting both increases and decreases in brain volumes (Ashtari et al, 2011;Cousijn et al, 2012;Gilman et al, 2014), no volume differences (Jager et al, 2007;Weiland et al, 2015;Gillespie et al, 2018), and modest effect sizes (Weiland et al, 2015). Factors including the age of cannabis use initiation, comorbid substance use, and levels of use are believed to contribute to variability in the human findings (Curran et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Dose-dependent associations with brain volumes have been reliably identified in preclinical studies (for review, see Lorenzetti et al, 2010) with some evidence of the same in humans (Battistella et al, 2014;French et al, 2015), suggesting consequences of lower levels of use. One study has reported differences in gray-matter density and shape of the amygdala and nucleus accumbens in recreational cannabis users (Gilman et al, 2014), but subsequent research has suggested that these findings may be associated with alcohol (Weiland et al, 2015) and nicotine (Gillespie et al, 2018) exposure in the cannabis users.…”

Section: Introductionmentioning

confidence: 99%

Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence

et al. 2019

View full text Add to dashboard Cite

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 ⌬-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 wellasthebilateralposteriorcingulate,lingualgyri,andcerebellumthatshowedgreaterGMVinthecannabisusers.Analysisoflongitudinaldata 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.

show abstract

“…In the UKB, smoking status was associated with thickness and surface of the thalamus (left and right), although we also found associations with the caudate and pallidum. Previous studies have reported association between tobacco usage and volume of left thalamus (Gallinat et al, 2006; Gillespie et al, 2018; Hanlon et al, 2016), which might be due to faster age related volume loss in smokers (Durazzo et al, 2017). We did not replicate other cortical or subcortical associations previously reported (Gallinat et al, 2006; Hanlon et al, 2016; Prom-Wormley et al, 2015).…”

Section: Discussionmentioning

confidence: 94%

Widespread associations between grey matter structure and the human phenome

Couvy‐Duchesne

Strike

Zhang

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

The recent availability of large-scale neuroimaging cohorts (here the UK Biobank [UKB] and the Human Connectome Project [HCP]) facilitates deeper characterisation of the relationship between phenotypic and brain architecture variation in humans. We tested the association between 654,386 vertex-wise measures of cortical and subcortical morphology (from T1w and T2w MRI images) and behavioural, cognitive, psychiatric and lifestyle data. We found a significant association of grey-matter structure with 58 out of 167 UKB phenotypes spanning substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains (UKB discovery sample: N=9,888). Twenty-three of the 58 associations replicated (UKB replication sample: N=4,561; HCP, N=1,110). In addition, differences in body size (height, weight, BMI, waist and hip circumference, body fat percentage) could account for a substantial proportion of the association, providing possible insight into previous MRI case-control studies for psychiatric disorders where case status is associated with body mass index. Using the same linear mixed model, we showed that most of the associated characteristics (e.g. age, sex, body size, diabetes, being a twin, maternal smoking, body size) could be significantly predicted using all the brain measurements in out-of-sample prediction. Finally, we demonstrated other applications of our approach including a Region Of Interest (ROI) analysis that retain the vertex-wise complexity and ranking of the information contained across MRI processing options. Highlights Our linear mixed model approach unifies association and prediction analyses for highly dimensional vertex-wise MRI data Grey-matter structure is associated with measures of substance use, blood assay results, education or income level, diet, depression, being a twin as well as cognition domains Body size (height, weight, BMI, waist and hip circumference) is an important source of covariation between the phenome and grey-matter structure Grey-matter scores quantify grey-matter based risk for the associated traits and allow to study phenotypes not collected The most general cortical processing (“fsaverage” mesh with no smoothing) maximises the brain-morphometricity for all UKB phenotypes

show abstract

Testing associations between cannabis use and subcortical volumes in two large population‐based samples

Abstract: In exploratory analyses based on young adult and middle-aged samples, normal variation in cannabis use is unrelated statistically to individual differences in brain morphology as measured by subcortical volume.

Cited by 25 publications

References 78 publications

Cannabis Use is Associated with Lower Hippocampus and Amygdala Volume: High-Resolution Segmentation of Structural Subfields in a Large Non-clinical Sample

Cannabis Use is Associated with Lower Hippocampus and Amygdala Volume: High-Resolution Segmentation of Structural Subfields in a Large Non-clinical Sample

Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence

Widespread associations between grey matter structure and the human phenome

Contact Info

Product

Resources

About