An epidemiological study to investigate the multifactoral nature of diabetes risk among adults with COVID-19 with a genetic and social determinants of health lens

This proposal seeks to enhance our understanding of new-onset diabetes in individuals following infection. This study will investigate 1) the prevalence of new-onset diabetes post-infection 2) how individual and external factors influence the development of new-onset diabetes. Study findings will identify populations at risk, assess potential shifts in disease burden, and inform prevention and early intervention strategies. A systematic review and meta-analysis will be conducted to determine the true prevalence of new-onset diabetes in individuals post-infection. In addition, the study will utilize the All of Us database, a real-world data platform that encompasses one of the largest, multifaceted collections of biomedical data. The proposed study will use prospective survey data from the All of Us database to investigate individual and external factors related to new-onset diabetes. To inform risk of new-onset diabetes related to individual factors, genome wide association studies will be conducted by using data collected from the All of Us database. The training plan for this fellowship will provide opportunities to develop and apply knowledge on how individual and external factors influence health outcomes and disease prevalence, as well as advanced data analysis techniques. In addition, the fellow will partake in professional development activities aimed at nurturing a well-rounded nurse scientist. Such training opportunities include structured and experiential learning activities to develop substantive and methodological knowledge. Interdisciplinary team-based research experiences and mentorship will complement formal and experiential learning opportunities. A strong mentoring team has been assembled with experts in endocrinology and diabetes, health informatics and data science, and statistical methodology. The proposed study and study sponsors are supported by the institutional environment of Boston College Connell School of Nursing which has significant resources to support the proposed project. The mentoring team and institutional environment are well-suited for the successful completion of the proposed project and training plan for this fellowship. This study addresses the NIH priorities through leveraging real-world data to address chronic disease development (i.e., diabetes) with a replicable, methodologically rigorous approach, using clearly measurable health outcomes (i.e., new-onset diabetes). This strongly aligns with NIH priorities on real-world data platforms, reproducible science, training the future biomedical workforce, chronic disease research, and solution-oriented approaches to improving population health. Findings will identify populations at risk and guide the development of targeted interventions, enable earlier detection and prevention, while optimizing public health strategies to address the broader burden of the chronic disease crisis.