This project aims to develop and apply novel statistical approaches to address key causal questions in the of substance use, abuse and dependence. The development will focus on extending Mendelian Randomization methodology to new data types that test its key assumptions. These developments include: estimating and controlling for biases due to non- random mating; analyses of data from unrelated but genotyped individuals; extension to longitudinal data; multivariate network models; and multiple-group analyses to test for sex, age and other group differences. These new methods will be applied to unique longitudinal phenotype, genotype and methylation data on smokers and non- smokers from the Netherlands Twin Register, and data from the UK biobank. Precise identification of causal pathways will enable evidence- based prevention and treatment methods to be devised and implemented.
Substance use abuse and dependence are especially complex disorders, with innumerable genetic and environmental risk factors, highly variable patterns of onset, offset and comorbidity with psychiatric disorders, cardiovascular disease and cancer. This project will develop Mendelian randomization based statistical methods and software and apply them to unique data from the Netherlands on genomic methylation. The project will improve understanding of the causes and effects of substance abuse and dependence, and how best to prevent and treat these disorders and their sequelae.
