Research Question
Endocrine disorders, particularly diabetes and metabolic syndromes, affect millions globally and are major contributors to morbidity and mortality. These conditions increase the risk of cardiovascular issues, cognitive decline, and chronic diseases, posing a significant public health challenge. However, the complex interactions among metabolic factors, gut microbiota, environmental exposures, and disease management remain underexplored. A comprehensive multi-omics approach is needed to improve risk stratification and prevention strategies.
Objective
This study aims to use an integrated approach, leveraging data from the UK Biobank (UKB), to investigate endocrine disorders. The UKB provides extensive multi-omics and epidemiological datasets, including genetic information, health records, and lifestyle factors. Through multidimensional analyses, we seek to identify genetic and environmental risk factors for disease onset and progression. By integrating clinical indicators with multi-omics data, we aim to develop predictive models for early diagnosis and personalized interventions.
Scientific Rationale
Exploring the interplay between metabolic biomarkers, gut microbiota, environmental exposures, and endocrine disorders offers insights into their pathogenesis. Previous studies often focus on isolated variables. Interactions among genetics, metabolism, environment, and clinical strategies remain poorly understood, limiting risk stratification and interventions. We will integrate multi-omics (metabolomics, microbiomics, genomics) with epidemiological data to investigate risk factors and pathways. This approach aims to uncover biomarkers, refine disease classification, and improve early diagnosis, risk prediction, and personalized strategies for endocrine diseases like type 2 diabetes, gestational diabetes, and metabolic syndrome.
