PROJECT SUMMARY Trauma affects the vast majority of people (50-89%) during their lifetime, and it can have lasting impacts on not only psychiatric but also cardiovascular health. Both trauma exposure and posttraumatic stress disorder (PTSD)—the quintessential trauma-related psychiatric disorder—have been linked prospectively to increased risk of developing a range of cardiovascular outcomes. However, as described in a recent NHLBI Working Group report, critical knowledge gaps must be addressed before trauma or its psychiatric sequelae might be novel targets for reducing cardiovascular disease (CVD) risk. Indeed, our current understanding is limited by a disproportionate focus on PTSD when examining subsequent CVD risk in trauma-exposed individuals. Posttraumatic psychopathology manifests in heterogeneous ways (e.g., depression, anxiety, substance abuse) that have been linked to elevated CVD risk in non-trauma-exposed samples. Further, despite differences in the prevalence and manifestations of posttraumatic psychopathology and CVD in men and women, few studies have directly examined sex differences in these associations. The field's ability to investigate these questions has been hampered by a lack of rigorous measures of trauma exposure and posttraumatic psychopathology in most existing electronic medical record databases, which have extensive data on CVD outcomes. This study will address these knowledge gaps by harnessing a unique prospective, population-based trauma cohort in order to characterize “cardiotoxic” manifestations of posttraumatic psychopathology in men and women. This trauma cohort was created using Danish electronic health registry (EHR) data as part of R01MH110453 (PI: Gradus), and it identified over 1.4 million individuals exposed to a trauma between 1994 and 2016. This established data source includes rich, highly valid, and complete registry-based data with up to 25 years of follow-up on psychiatric and cardiovascular diagnoses following trauma. We will use this existing resource, restricted to persons age 18 years and older with no prior CVD events (n = 1,068,100), to comprehensively examine posttraumatic psychopathology as a predictor of incident CVD. In Aim 1, we will harness cutting edge, novel data science techniques (machine learning) to identify particularly “cardiotoxic” manifestations of psychopathology after trauma. Given sex differences in psychiatric disorders and CVD, sex-specific psychopathology profiles associated with incident CVD risk will be examined in stratified analyses. In Aim 2, we will use traditional analyses to quantify discovered psychiatric predictors and unanticipated/novel psychiatric comorbidity profiles associated with CVD risk in the machine learning analyses, as well as a priori literature-based combinations of psychiatric disorders that increase CVD risk. This EHR-based trauma cohort provides a unique opportunity to consider comprehensively the constellation of posttraumatic psychopathology ...