Bookmarks
Understanding how genes influence osteoarthritis and complications of type 2 diabetes
Safe People
Organisation name
Helmholtz Munich
Organisation sector
Government Agency (Health and Adult Social Care)
Applicant name(s)
Lorraine Southam
Funders/ Sponsors
Safe Projects
Project ID
OFHS250157
Lay summary
This research aims to better understand the genetic factors that cause people to develop osteoarthritis and health problems due to type 2 diabetes. Both diseases are common conditions that affect millions of people worldwide. They are complex diseases that are influenced by genetics and lifestyle factors, like exercise and weight, and can seriously impact a person’s quality of life. We will study genetic data from people taking part in Our Future Health by comparing the genes of people with and without the diseases. For osteoarthritis we will look at different joints, like the hip, knee, hand, and spine, to find out whether different genes are linked to different types. For type 2 diabetes, we will focus on understanding why some people go on to develop complications affecting the heart, brain, kidneys, nerves, or eyes. We will also combine our results with data from large genetic studies around the world. This will help us gain a clearer picture of the genetic factors that influence both diseases, with the ultimate aim of improving diagnosis, and treatment. We are conducting large-scale genetic studies to better understand two common health conditions: osteoarthritis and type 2 diabetes (T2D). In our recent osteoarthritis study involving nearly 2 million people, we identified hundreds of genetic regions contributing to the disease, some of which are already targeted by existing medicines. We now plan to include more diverse populations worldwide and use advanced techniques to explore how these genetic changes affect joint tissues, bringing us closer to understanding how osteoarthritis develops and how to treat it. For T2D, while we already know genes and lifestyle both play a role in its development, far less is known about the genes linked to complications, which are associated health problems affecting the heart, brain, kidneys, nerves, and eyes once someone has T2D. Our next step is to study the genes of people with T2D from many different backgrounds to uncover why some people experience complications and others do not. These insights could lead to new ways of predicting, preventing, or treating these complications by helping doctors tailor care to each person’s genetic risk. Together, these studies aim to uncover how genetic differences influence disease risk and progression, and ultimately lead to more effective, personalised treatments.
Public benefit statement
Osteoarthritis and type 2 diabetes (T2D) are two of the most common long-term health conditions worldwide, affecting millions of people and placing a major burden on individuals and healthcare systems. Our research aims to understand the genetic and biological causes of both diseases, so that we can improve prevention, diagnosis, and treatment. For osteoarthritis, we are identifying the genetic and tissue-level changes that drive the disease, using data from large and diverse populations. This could lead to earlier identification of people at risk, and to the development of treatments that are more effective, inclusive, personalised and potentially include new uses for existing medicines. For T2D, we are focusing on why some people develop serious complications while others do not. By identifying genetic risk factors across global populations, we aim to develop tests that help doctors predict who is most likely to be affected. This could enable earlier, more personalised care, helping people avoid or delay serious health problems. Together, these studies will help ensure that future treatments are based on a better understanding of how these diseases work, and are designed to benefit people from all backgrounds, leading to better health and quality of life.
Request category type
Public Health Research
Other approval committees
Project start date
19/05/2026
Latest approval date
02/02/2026
Safe Data
Dataset(s) name
Safe Setting
Access type
TRE