Prediction of autoimmune disease outcomes and progression using de-identified data from UK Biobank

University of Florida

Lay summary

Introduction:

Autoimmune diseases (AD) pose complex challenges, impacting millions worldwide. Our research project employs Artificial Intelligence (AI) and advanced data analysis to understand the intricate interactions between genetics and the environment in AD outcomes. By focusing on the UK Biobank data, we aim to advance personalized medicine and enhance early detection and care for AD.

Scientific Rationale:

The causes of AD remain elusive, but emerging evidence suggests a combination of genetic predisposition and behavioral/environmental triggers. Our research utilizes the rich UK Biobank dataset, encompassing genetic, clinical, behavioral and environmental factors. Through AI algorithms and cutting-edge analysis techniques, we aim to identify novel risk profiles, genetic markers, and modifiable behavioral/environmental factors influencing AD outcomes.

Project Aims:

1- Develop Clinically Useful Risk Profiles: We seek to create risk profiles enabling healthcare providers to identify individuals at high risk for AD, including T1D. Early detection facilitates timely intervention and preventive measures.

2- Uncover Interactions Between Factors: Employing explainable AI, we will quantify the contributions of genomics, clinical data, and environmental exposures. By revealing complex interactions, we aim to enhance our understanding of disease mechanisms and identify intervention targets.

3- Identify Novel Markers and Risk Profiles: Leveraging the UK Biobank dataset, we will explore relationships between genetic markers,clinical metadata, and modifiable environmental/behavioral factors. Our analysis aims to identify novel markers and risk profiles, enhancing risk prediction accuracy and guiding personalized treatments.

Project Duration:

This research project spans three years. During this period, we will collect and analyze UK Biobank data, apply AI algorithms, and collaborate with experts to ensure robust research outcomes.

Public Health Impact:

Our research extends beyond academia, aiming to transform patient care and public health. By unraveling connections between genetics, environment, and AD outcomes, we can improve health outcomes for individuals with AD. Clinically useful risk profiles will enable early detection and intervention, benefiting patients. Furthermore, our findings will shed light on disease mechanisms, paving the way for personalized treatments and precision medicine. Ultimately, our research aims to positively impact millions affected by autoimmune diseases, providing them with better diagnostic tools, effective interventions, and a brighter future.