There is a strong positive association between tobacco and cannabis use on the one hand, and mental health disorders attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder on the other. This association may arise through shared risk factors (genetic and/or environmental). Alternatively, there may be causal effects such that mental health disorders lead to higher tobacco/cannabis use, or tobacco/cannabis use negatively impact mental health. Some epidemiological evidence for both causal mechanisms exists, but novel methods are needed to firmly establish direction of causality. Mendelian randomization (MR) is an exciting, innovative technique that was proposed in 1986 but only recently became viable following advances in the genetics field. MR utilizes genetic variant(s) strongly associated with a predictor variable, as proxy, or ‘instrument’, to test causal effects on an outcome variable. Confounding and reverse causation are thereby minimized. In this Rubicon project I will apply MR in large samples from international cohort studies. The host institute where the project will take place is renowned for its pioneering role in the field of causal inference and particularly MR. The results will have profound implications for our understanding of the aetiology of mental health disorders, and development of preventive interventions and clear, evidence-based public health messages.
There is a strong positive association between tobacco and cannabis use on the one hand, and mental health disorders attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder on the other. This association may arise through shared risk factors (genetic and/or environmental). Alternatively, there may be causal effects such that mental health disorders lead to higher tobacco/cannabis use, or tobacco/cannabis use negatively impact mental health. Some epidemiological evidence for both causal mechanisms exists, but novel methods are needed to firmly establish direction of causality. Mendelian randomization (MR) is an exciting, innovative technique that was proposed in 1986 but only recently became viable following advances in the genetics field. MR utilizes genetic variant(s) strongly associated with a predictor variable, as proxy, or ‘instrument’, to test causal effects on an outcome variable. Confounding and reverse causation are thereby minimized. In this Rubicon project I will apply MR in large samples from international cohort studies. The host institute where the project will take place is renowned for its pioneering role in the field of causal inference and particularly MR. The results will have profound implications for our understanding of the aetiology of mental health disorders, and development of preventive interventions and clear, evidence-based public health messages.

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