The goal of this project is to make a significant contribution to the discovery of genes influencing cannabis use disorders (CUD). Given the widespread use of cannabis, increasing recognition of the potential health effects of this drug, and a growing recognition of CUDs as distinct clinical entities, this application seeks funding to conduct clinical interviews on a large sample of Australian twins and their non-twin siblings, and run genome wide linkage and individual genome wide association scan (WGAS) to detect quantitative trait loci (QTL) for CUDs.
The specific aims are:
Aim 1 : To fund structured clinical interviews in order to obtain item level data and DSM-IV diagnoses of cannabis abuse and dependence on 1000 Australian twins and their non-twin siblings from the Brisbane Adolescent Twin Sample. Item level data and DSM-IV diagnoses for other drugs, as well as measures of lifetime patterns of drug use, drug use disorders, and contextual and developmental risk factors for CUD phenotypes will also be obtained. Using the same model fitting strategy proposed in the K99 (see Section 4.D.3.2.4), these data will allow us to determine whether the best fitting empirical CUD phenotypes based on MATR data, provide a good fit to the Australian data.;
Aim 2 : Identify QTLs for CUDs using genome wide linkage analyses based on 1000 individuals from 460 families, followed by individual WGAS analyses on 3000 individuals. The damage to individuals and the social cost to the community caused by CUDs are enormous. The identification of QTLs responsible for CUDs is required to fill gaps in our knowledge, to develop targeted treatments, and to provide an empirical basis for addressing policy issues and public concerns about the cause of cannabis use disorders. By capitalizing on the US and Australian data, Dr Gillespie is also proposing, as part of future analyses, a number of enormously cost-effective opportunities to test novel research questions and specific hypotheses which will improve our understanding of drug use disorders. These will enable us to determine the degree to which genetic liability to CUDs can be explained by the same QTLs responsible for liability to other drug use disorders and/or psychiatric disorders.
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