Harness All of Us for Equitable Disease Risk Prediction: A Tutorial with Case Study on Genetic Prediction Score for Rheumatoid Arthritis

Abstract The multimodal data assembled through All of Us Research Program with enriched recruitment of populations underrepresented in biomedical research have provided a rich resource for equitable health research. The complexity of the All of Us research platform, however, is a common hurdle at the initiation of studies. This tutorial aims to demonstrate to researchers a practical, transparent and reproducible workflow for streamlining data curation and analysis. This tutorial covers modules: (1) design of All of Us studies; (2) selecting study cohort; (3) curating multimodal data (electronic health records, surveys, genomics, and wearable devices); (4) harmonizing disease onset outcomes in risk models. We showcased the proposed workflow using a case study for genetic risk prediction of rheumatoid arthritis for minority race/ethnicity groups. Step-by-step guides are provided in the supplementary materials and the online repository with links to SQL/R/Python example code and All of Us user interface operations.