| Title: | Validation of polygenic risk scores, based upon pooled discovery studies, for predisposition to major prevalent diseases affecting both quality-of-life and lifespan and testing for causation. |
| Lead Institution: | Genetic Technologies Ltd. |
| Principal investigator: | Dr Richard Allman |
Application 47401
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
This project is investigating genetic risk scores for predisposition to either cardiovascular disease, Type 2 diabetes or one of several common cancers. It is known that a combination of genetics, age, various clinical factors and lifestyle factors such as exercise and diet play a large part in a person's likelihood of developing those diseases. All of these factors vary from person to person. Using UK Biobank data, research from other groups has provided insight into the predictors for an individual's risk of developing a range of diseases. As cardiovascular disease, Type 2 diabetes and cancer are the most deadly and prevalent of diseases that early intervention can address and prevent, we are aiming to develop a number of risk prediction tests that can be performed simultaneously for these diseases in a simple and cost-effective manner. It is hoped that the public health impact will be significant by increasing lifespan, quality of life and decreasing the high cost on a healthcare system to treat the chronic diseases once already sick. This project is expected to take a year until the first tests are available to the public. The project also aims to investigate which factors could cause these major diseases by developing and testing new statistical methods. The methods applied by and further developed by this project could be used to investigate evidence for causation for multiple lifestyle factors and health outcomes. Relevant interventions could be applied to those factors found to be causal, and thus improve health on a population level.6 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 8106 | A combined clinical and genetic model for predicting risk of ovarian cancer | Gillian S. Dite (+3) | 2022 | European Journal of Cancer Prevention |
| 10135 | Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses | Shuai Li (+12) | 2024 | Genetic Epidemiology |
| 9769 | Development and validation of a clinical and genetic model for predicting risk of severe COVID-19 | Gillian S. Dite (+2) | 2021 | Epidemiology and Infection |
| 8052 | Polygenic risk scores for cardiovascular diseases and type 2 diabetes | Chi Kuen Wong (+6) | 2022 | PLOS ONE |
| 10513 | Predicting 10-Year Risk of Pancreatic Cancer Using a Combined Genetic and Clinical Model | Gillian S. Dite (+4) | 2023 | Gastro Hep Advances |
| 7920 | Validation of an Abridged Breast Cancer Risk Prediction Model for the General Population | Erika L. Spaeth (+3) | 2023 | Cancer Prevention Research |
Enabling scientific discoveries that improve human health