Gene finding studies struggle to predict complex traits. The hypotheses being tested are that (1) common genetic markers are useful proxies for either real or actual genetic effects of complex traits, and (2) sets of genetic variants that comprise the total genetic variance of a complex trait in a reference population and the reference population itself can be used to better approximate a person?s behavioral severity. The goal of this research is to understand how sets of variants that reflect vulnerability across a number of biological mechanisms influences vulnerability to alcohol and other drug use disorders and related psychopathology. To date, polygenic scores have had limited utility due to lack of sensitivity to potential sources of genetic variation. This project aligns with the UKbiobank?s purpose because it seeks to develop a novel and integrative analytical approach to facilitate the prediction of health conditions using genetic, behavioral, and other data. We will test the central hypotheses using a novel and integrative analytical approaches (see Research Strategy Figure 1) that leverage increases in statistical power gained from using (A) large genetically-informed samples, (B) integrative functional genomics platforms, in particular, GeneWeaver (i.e., to incorporate and prioritize biological systems on the basis of experimental studies in model organisms and cell culture), and (3) novel data-mining tools that leverage components A and B. We are interested in examining the full cohort with data on our primary outcome variables alcohol and tobacco consumption and associated mental health problems associated with stress, mood, and support.
|Return ID||App ID||Description||Archive Date|
|2582||31187||Associations of cigarette smoking with gray and white matter in the UK Biobank||27 Oct 2020|
|2583||Associations of cigarette smoking with gray and white matter in the UK Biobank||Gray et al||2020||Neuropsychopharmacology (2020)|