The goals of this fellowship are to further develop the applicant's knowledge and skills in advanced computational methods (i.e., twin modeling and network modeling), the comorbidity of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD), and basic neuroscience and genetics. In line with these goals, a cornerstone of the applicant's training will be the statistical and theoretical training he receives through workshops, coursework, annual visits to Virginia Commonwealth University (VCU) to meet with Drs. Gillespie and Neale, regular sponsor and co-sponsor meetings, and professional development activities. The project will serve as the applicant's dissertation and help him pursue his goal of becoming an independent investigator who uses advanced computational analyses of large datasets and multi-method laboratory studies to study the etiology, maintenance, and recurrence of phenotypes of depression and anxiety. In addition to the skills to be gained by the applicant, the project's goals will greatly advance the understanding of MDD and GAD symptom etiology by testing the central tenet of a novel theory of psychopathology (network theory). Understanding the causes of symptoms and their covariance is critical, as different causal models have markedly different implications for intervention. Additionally, the study is consistent with the NIMH's strategic objective to define mechanisms of complex behaviors and NIH's increased emphasis on replicability. Several twin studies have estimated the genetic and environmental etiology of individual MDD symptoms. However, no studies have considered the possibility of causal relationships between symptoms as hypothesized by the network theory. The present study will therefore use a novel method - direction of causation (DoC) modeling - of twin data to (1) test putative causal relationships between individual MDD and GAD symptoms and estimate the contributions of genetics and environment to each symptom, (2) evaluate the replicability of the best fitting model in aim 1 in an independent twin sample, and (3) explore sex differences in the phenotypic causal pathways and genetic and environmental liabilities of each symptom. This project greatly extends prior studies of individual MDD symptoms by testing putatively causal pathways hypothesized by the network theory and including both MDD and GAD symptoms in the same model, which is important given their high comorbidity and potential causal relationships between symptoms of the two disorders. Mentorship for this project will be provided by experts in the areas of twin and DoC modeling, network theory and modeling, the comorbidity of depressive and anxiety disorders, and neuroscience (sponsors: Shankman, Gillespie, and Fried; OSCs: Neale, Roitman). This fellowship will not only be an important step in the applicant's research career, but the proposed study's primary objective of testing different causal models of symptom co-occurrence and quantifying the genetic and environmental contributions to each symptom will have important implications for the prevention and treatment of MDD and GAD symptoms and for theories of symptom etiology.
The genetic and environmental etiology of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) ? two prevalent and commonly co-occurring disorders ? has traditionally been studied using twin modeling, but extant twin studies of MDD and/or GAD have not considered the possibility of causal relationships between symptoms as suggested by the network theory. The objectives of this study are to (1) use multivariate direction of causation (DoC) modeling to test and identify putative causal relationships between symptoms of MDD and GAD as well as quantify the genetic and environmental contributions to each individual symptom, (2) evaluate the replicability of the model in aim 1 in an independent twin sample, and (3) explore sex differences in the effects of other symptoms, genetics, and environment on individual symptoms. Findings from this study will directly inform interventions because different models of symptom etiology have markedly different implications for intervention and prevention ? for example, a model in which worry causes depressed mood suggests that an intervention that decreases worry will also decrease depressed mood, whereas a model in which worry and depressed co-occur because of shared risk factors suggests that reducing worry will have no impact on depressed mood unless the intervention reduces shared risk factors.
