Clinical application of genomics for complex disease is an important goal for personalized medicine. Its implementation will intersect with existing social, structural, and interpersonal dynamics in heretofore unexplored ways. Using immersive simulation technologies, it is possible to investigate potential influences of future applications like polygenic scores (PS; models that consider the entire genome to derive risk for common diseases). In immersive simulations, we can identify areas where PS might exacerbate or attenuate biased behavior and attitudes towards historically marginalized patients. A series of studies investigates how the emergence of PS for common conditions could influence healthcare provider beliefs, behavior, and biases, and whether these influences vary depending upon the characteristics of the patient to whom the PS are applied. The first study found that PS reports unintentionally affected many aspects of care recommendations, and differentially influenced bias-related beliefs and behavior depending upon the virtual patient’s apparent race. Patterns underscore the complexity of intersectional identities in clinical settings wherein obesity tends to be more highly stigmatized for White women than for Black women. To further understand PS influences, a larger, ongoing experiment immersing medical residents in telemedicine simulations with a virtual human patient evaluates the effects of PS of varying severity, integrated into the medical record on care decisions and interpersonal treatment of the virtual patient who varies in apparent race and also in body size.