Skip to navigation Skip to main content Skip to footer

Approved Research

Multivariate analysis of phenome, genome relationships using large EHR/Biobank data: a `big data` discovery approach towards personalized medicine

Principal Investigator: Professor Yaomin Xu
Approved Research ID: 43397
Approval date: April 8th 2021

Lay summary

Most diseases are complex.  Diabetes, high blood pressure and heart disease are examples.  These diseases can also lead to other problems.  For instance, high blood pressure that is not kept under control can cause kidney disease, stroke, or a heart attack. 

Many small things add up to cause these diseases.  Gene changes you are born with often play a role.  Your environment, like the air you breathe, your diet, or how much exercise you get can also factor in.  Complex diseases are the biggest cause of our health burden in the U.S. 

We want to learn more about complex diseases. We will use UK Biobank and other resources to study the links between gene changes, diseases, and other factors such as diet, environmental factors, etc.  We will try to improve how we find these diseases associated links.  The goal is to better predict who might be at risk for certain conditions.  Then, we could do a better job of catching them early.  We may even be able to delay or prevent the disease.  These results could also help us find better ways to treat these diseases.