Diabetes Prevention Data Solutions Core

University Of Kentucky, Lexington KY

Investigators

Linked publications, trials & patents

Abstract

ABSTRACT – DIABETES PREVENTION DATA SOLUTIONS CORE The Data Solutions Core (DSC) within the University of Kentucky Diabetes Prevention COBRE (UK-DPC) is positioned at the forefront of using advanced data analytics to enhance our understanding of diabetes risk factors, optimize prevention strategies, and contribute to the broader research goals of UK-DPC investigators, University of Kentucky researchers and others in the COBRE community interested in diabetes prevention. The DSC team will consult on experimental design, including statistical power considerations and randomization, and apply sophisticated statistical techniques and machine learning algorithms to identify novel biomarkers and predictive indicators that inform the development of targeted interventions for diabetes prevention. Collaboration is central to the core's mission, fostering interdisciplinary partnerships among researchers, clinicians, and data scientists at University of Kentucky. As such, the core will serve as a hub for data sharing that will facilitate seamless communication and collaboration within UK-DPC. Privacy and ethical considerations are paramount, and the DSC will adhere to rigorous standards to ensure participant confidentiality and data security. The proposed infrastructure is designed to be scalable, accommodating the evolving needs of the diabetes prevention research community. The DSC will support the appropriate use of commercially available software, novel adaptations of that software, and the design of fundamentally new methods. This combination of strategies, coupled with the expertise of the DSC team in outcomes particular to diabetes studies, will fulfill project-specific needs and thus identify modifiable risk factors and effective preventive measures for diabetes. At the same time, the team will be generating innovative tools for the global community in diabetes prevention data analysis. Integration with emerging technologies such as high- throughput RNA sequencing, kinome antibody arrays, and continuous monitoring tools will enhance data interpretation, and provide a comprehensive understanding of the dynamic interplay between metabolism, lifestyle factors, and diabetes prevention. This analytical resource will be unique on campus due to the published expertise of the team in the outcomes and tool development unique to diabetes prevention studies. The DSC will be a catalyst for advancing rigorous and reproducible diabetes prevention research, implementing the Data Management and Sharing Plan, bridging gaps between disparate data sources, fostering collaboration, and driving innovation. By harnessing the power of data-driven insights, the lasting impact of the DSC will be the identification of targeted and scalable preventive strategies, ultimately mitigating the impact of diabetes on public health.