A person’s risk of developing heart disease, obesity, or an eye disorder depends on a mix of their genes and their environment, and this project is sifting through the DNA of tens of thousands of volunteer participants to pinpoint which genetic differences matter. The problem is that most common diseases are complex—they are not caused by a single faulty gene, but by many small genetic variations interacting with lifestyle and surroundings. Current medicine often treats these conditions only after they appear. This research aims to identify the genetic markers that predict disease risk years or decades in advance, filling a gap in our ability to forecast who will get sick and why. If successful, the work will enable doctors to stratify patients by genetic risk, offering early screening or preventive treatments tailored to an individual’s DNA. This is a step toward personalised medicine—where a prescription or lifestyle advice is matched to a person’s genetic profile rather than given to everyone with the same diagnosis. The project also relies on linking genetic data to NHS electronic health records, creating a long-term resource for studying how genes and environment interact across a lifetime.
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Our aim is to understand the genetic and environmental causes of variation in complex traits and diseases. These include common conditions such as heart disease, obesity and disorders of the eye. We develop and apply a range of statistical analysis methods to identify genetic differences that are connected with either good or bad health throughout a person’s lifetime. This will help to predict the risk of people developing particular conditions, as well as providing a foundation for the future development of personalised and precision medicine. To achieve this we are using “Biobanks” of large numbers of volunteer research participants, to enable research ranging from simple postal surveys to clinical studies with hospital visits, and detailed and wide-ranging analyses of the collected biological samples, such as blood and urine. The volunteers in our biobanks also gave consent for researchers to link to their NHS electronic health record data, allowing for long-term follow-up of their health via medical records, and relating this to their genetic make-up The results will help to understand the relationships between genetic variation, gene function and health, integrating computational and experimental approaches. This will allow new scientific discoveries to be made that are relevant to a wide range of conditions and will contribute to advances in medical research and customised healthcare for patients and populations.
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