Diminished Structural Brain Integrity in Long- term Cannabis Users Reflects a History of Polysubstance Use

BACKGROUND: Cannabis legalization and use are outpacing our understanding of its long-term effects on brain and behavior, which is fundamental for effective policy and health practices. Existing studies are limited by small samples, cross-sectional measures, failure to separate long-term from recreational use, and inadequate control for other substance use. Here, we address these limitations by determining the structural brain integrity of long-term cannabis users in the Dunedin Study, a longitudinal investigation of a population-representative birth cohort followed to midlife.METHODS: We leveraged prospective measures of cannabis, alcohol, tobacco, and other illicit drug use in addition to structural neuroimaging in 875 study members at age 45 to test for differences in both global and regional gray and white matter integrity between long-term cannabis users and lifelong nonusers. We additionally tested for dose -response associations between continuous measures of cannabis use and brain structure, including careful adjustments for use of other substances.RESULTS: Long-term cannabis users had a thinner cortex, smaller subcortical gray matter volumes, and higher machine learning-predicted brain age than nonusers. However, these differences in structural brain integrity were explained by the propensity of long-term cannabis users to engage in polysubstance use, especially with alcohol and tobacco.CONCLUSIONS: These findings suggest that diminished midlife structural brain integrity in long-term cannabis users reflects a broader pattern of polysubstance use, underlining the importance of understanding comorbid substance use in efforts to curb the negative effects of cannabis on brain and behavior as well as establish more effective policy and health practices.

Automated summary

Cannabis legalization and use are surpassing our understanding of its long-term effects on the brain and behavior. Long-term cannabis users show thinner cortex, smaller subcortical gray matter volumes, and higher machine learning-predicted brain age at midlife, with these differences explained by polysubstance use, especially alcohol and tobacco.