Principal Investigator: Dr Robert Culverhouse
Washington University in St. Louis, Missouri, USATags: 48123, cancer, cardiovascular disease, Genetic risk prediction, lung disease, neuropsychiatric disease, substance use and addiction
The goal of our project is to gain a better understanding of the causes and consequences neuropsychiatric diseases, with a particular focus on of substance use, substance dependence, and related traits and medical conditions. Data from the UK Biobank will play and important role in this long-term project: It will both help us identify novel associations and interactions and provide data for potential replication of associations identified in other datasets.
These analyses will be targeted on the prediction of substance use and dependence and prediction of the risks for a variety of consequences from substance use as well as frequently comorbid neuropsychiatric diseases such as schizophrenia and bipolar illness. Because smoking and alcohol and illicit substances impact so many medical conditions, this large dataset will provide statistical power to examine outcomes that are only modestly associated with substance use. It will also provide an opportunity to tease apart factors related to comorbid substance use.
The ultimate public health goal of this project is to decrease the misuse of alcohol, tobacco, and illicit substances; to help those who are addicted to quit; and to ameliorate the negative consequences of substance misuse, and to gain a better understanding of the relationship between substance use and serious neuropsychiatric illnesses. For example, improved predictive models may identify high-risk children so that extra prevention resources can be directed to them. Genetically guided treatments, such as some we are testing now, may improve successful smoking cessation. Genetically informed models for the risks of cancers or other diseases may provide physicians with guidance for increased monitoring of some patients and substance users with added incentives to quit.