Cohort studies and meta-analyses have documented a robust association between cannabis use, heavy use, and misuse with future risk of schizophrenia.^1-3 Despite adjusting for covariates, including current psychotic symptoms, other psychopathology, and social integration,¹ the ability of these models to determine the degree to which cannabis causes schizophrenia is limited and dependent on their ability to capture all relevant confounders. When evaluating efforts to reduce cannabis use as a means of preventing schizophrenia, the proportion of this association that is causal is critical.

Given the high heritability of schizophrenia, we reviewed reports that relied on 4 genetic methods (Table) capable of addressing the nature of the cannabis-schizophrenia association. We evaluated 3 hypotheses: (1) it is entirely causal, (2) it is partly causal and partly confounded by genetic/familial effects and/or reverse causation, or (3) it is entirely noncausal. (We are unable to review the literature regarding short-term psychiatric effects of cannabis administration.⁹) Confounding here refers to genetic risks that increase the probability of both using/misusing cannabis and schizophrenia, thereby explaining at least part of the association. In this example, reverse causality refers to a theoretical underlying mechanism in which schizophrenia liability or symptoms increase the risk of using cannabis. The first 2 methods are natural experiments, discordant relative designs, and mendelian randomization, that directly evaluate each hypothesis. The 2 other methods, linkage disequilibrium score regression (LDSR) and polygenic risk scores (PRSs), measure genetic associations, which, although less definitive, provide evidence of correlated genetic risks that undermine the plausibility of hypothesis 1. Each hypothesis generates distinct expectations under each method (Table). Therefore, our approach determines which of the hypothetical expectations best fit the aggregate results. By examining multiple methods with different strengths and limitations, we attempt to triangulate the observed results hoping thereby to increase confidence in our conclusions.