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Examining the association between prenatal cannabis exposure and child autism traits: A multi-cohort investigation in the environmental influences on child health outcome program

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This study examined the association between prenatal cannabis exposure and autism spectrum disorder (ASD) diagnoses and traits. A total sample of 11,570 children (ages 1–18; 53% male; 25% Hispanic; 60% White) from 34 cohorts of the National Institutes of Health-funded environmental influences on child health outcomes consortium were included in analyses. Results from generalized linear mixed models replicated previous studies showing that associations between prenatal cannabis exposure and ASD traits in children are not significant when controlling for relevant covariates, particularly tobacco exposure. Child biological sex did not moderate the association between prenatal cannabis exposure and ASD. In a large sample and measuring ASD traits continuously, there was no evidence that prenatal cannabis exposure increases the risk for ASD. This work helps to clarify previous mixed findings by addressing concerns about statistical power and ASD measurement.

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Assessing rates and predictors of cannabis-associated psychotic symptoms across observational, experimental and medical research

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Cannabis, one of the most widely used psychoactive substances worldwide, can give rise to acute cannabis-associated psychotic symptoms (CAPS). While distinct study designs have been used to examine CAPS, an overarching synthesis of the existing findings has not yet been carried forward. To that end, we quantitatively pooled the evidence on rates and predictors of CAPS (k = 162 studies, n = 210,283 cannabis-exposed individuals) as studied in (1) observational research, (2) experimental tetrahydrocannabinol (THC) studies, and (3) medicinal cannabis research. We found that rates of CAPS varied substantially across the study designs, given the high rates reported by observational and experimental research (19% and 21%, respectively) but not medicinal cannabis studies (2%). CAPS was predicted by THC administration (for example, single dose, Cohen’s d = 0.7), mental health liabilities (for example, bipolar disorder, d = 0.8), dopamine activity (d = 0.4), younger age (d = −0.2), and female gender (d = −0.09). Neither candidate genes (for example, COMT, AKT1) nor other demographic variables (for example, education) predicted CAPS in meta-analytical models. The results reinforce the need to more closely monitor adverse cannabis-related outcomes in vulnerable individuals as these individuals may benefit most from harm-reduction efforts.

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