Major depressive disorder (MD) is a common psychiatric disorder and a leading cause of disability worldwide. Twin studies estimate the heritability of MD as ~37%, supporting a complex etiology with both genetic and environmental factors. Efforts to identify specific genetic variants influencing MD risk remain a challenge. Genome-wide association studies have identified numerous risk variants for many complex traits but until recently no replicable genome-wide significant associations had been reported for DSM-defined MD. This may reflect the extensive clinical and etiological heterogeneity of MD. To date, there has been little systematic work on addressing heterogeneity in a genetically informed framework. Here, the candidate proposes a research program aimed at leveraging sources of heterogeneity to increase the power of molecular genetic analyses of MD, towards identification of genetic variants conferring risk to MD in general, to specific subtypes and symptoms, as well as comorbid traits. Importantly, this research will move beyond simple phenotype-genotype association towards providing a deeper understanding of causal processes underlying MD. The overarching goal for this career development award is to integrate dimensional phenotype assessments with molecular genetic data into comprehensive models of disease risk. Through the support of a K01, the candidate will acquire and apply advanced training in psychiatric nosology, psychometrics, bioinformatics, and statistical genetic approaches to research causal mechanisms underlying liability to MD. By leveraging sources of heterogeneity in a multidisciplinary framework, the candidate's research program aims to (1) refine the MD phenotype for genetic analyses by developing quantitative indices of MD liability and symptom dimensions, (2) clarify the genetic architecture by applying aggregate genetic risk methodologies and moderating effects of the environment, and (3) develop novel methods to model causality and comorbidity by synthesizing divergent methodologies. Moving forward, the candidate's long-term career goal is to develop the training and experience needed to execute an independent, transformative, and federally-funded research programme that will elucidate causal processes underlying mood disorders and correlated traits, with a particular emphasis on statistical methods development.
Major depressive disorder (MD) is a leading cause of disability worldwide, arises from the action and interaction between diverse genetic and environmental factors, and is comorbid with numerous psychiatric and medical conditions. Although recent progress has yielded modest insight into the genetic architecture of MD, moving beyond simple phenotype-genotype association towards a deeper understanding of causal processes will require novel approaches incorporating environmental, clinical, and genomic data. During the course of this award, the applicant will receive advanced training in psychiatric nosology, psychometrics, bioinformatics, and statistical molecular genetic methods from renowned leaders in the field, and subsequently synthesize these approaches into an analytical framework for modeling causality in MD and its comorbidity with other complex traits.
