Integrating developmental and genomic approaches to identify early trajectories of eating and internalizing disorder symptoms

PROJECT SUMMARY Eating disorders (ED) and non-eating disorders internalizing-spectrum disorders (nonED-INT; e.g., major depressive disorder, generalized anxiety disorder, social phobia, obsessive-compulsive disorder, posttraumatic stress disorder) have major public health importance due to their prevalence and significant personal and societal costs. These disorders often onset during adolescence and co-occur. Despite years of psychiatric research, detection and prevention strategies for ED and nonED-INT are not optimal. Little is understood about the developmental course of ED and nonED-INT symptoms, particularly their co-development, and the degree to which shared vs. unique genetic and phenotypic factors underlie ED and nonED-INT risk. In this study, we will elucidate the taxonomy of ED and nonED-INT symptoms: clarifying their joint (i.e., as an overarching internalizing dimension) and specific developmental course and identifying genetic and environmental predictors. We will leverage the rich genomic and phenotypic data from two large and well-characterized cohorts - the Adolescent Brain and Cognitive Development (ABCD) and the Avon Longitudinal Study of Parents and Children (ALSPAC) cohorts. We will deliver developmental models of ED and nonED-INT symptom course, explicate their joint and specific risk (genetic and environmental), and assess differences in models across samples and race/ethnicities. We propose three specific aims: First, using ABCD and ALSPAC data, we will empirically identify trajectories of ED and nonED-INT symptoms across development for each cohort and assess stability of the models across sex, race, and ethnicity. Second, using multi-trait genomic methods, we identify unique and common genetic risk across ED and nonED-INT phenotypes. Finally, we will determine genetic and phenotypic longitudinal predictors of ED and nonED-INT trajectories in each cohort and elucidate the stability and robustness of a predictive model based on both genetic and early-life risk indicators. In the short-term, our results will lend clarity to the taxonomy of ED and nonED-INT. In the long-term, improved understanding of developmental pathways will aid early intervention and identification of high-risk youth.