Obesity, the excessive accumulation of body fat, has been linked to several common diseases, including cardiovascular disease, type II diabetes and many types of cancer. There are several pathways through which obesity may influence health, but these have not yet been comprehensively mapped. Current evidence suggests obesity’s effects extend beyond simple caloric excess, involving complex interactions between adipose tissue function, inflammatory processes, and organ-specific pathophysiology. While individual associations between obesity and conditions like type 2 diabetes, cardiovascular disease, and certain cancers are established, the broader landscape of obesity-related disease clusters remains poorly understood.
By using genetic variants associated with obesity as instruments, we can minimize confounding influences and investigate causal relationships between obesity and multiple health outcomes. This approach can be used to allow us to identify distinct clusters of diseases that share genetic architecture, potentially revealing relevant biological pathways and therapeutic response patterns.
Understanding the clusters of diseases affected by obesity will help us put in place better prevention measures and improve our understanding of the impact of the recent obesity medications.
The main aim of this work is to investigate how obesity influences patterns and groupings of related health outcomes through genetic analysis.