Investigation of polygenic risk for complex traits enriched in biological systems with known drug targets
Approved Research ID: 58432
Approval date: October 8th 2020
Many human traits and diseases are impacted by genetic factors. Genetic risk is usually more complex than a single gene, rather hundreds to thousands of genes are likely involved in predisposition to a disease. Previous research has demonstrated that the risk contributed by each gene can be combined into a single genetic risk score. These risk scores are often termed polygenic risk scores or polygenic scores, named as such because many genes (polygenic) are involved. However, as these scores utilise a variety of different genes with diverse function, it is often difficult to interpret the biology of these scores as so many genes are involved. We have developed a method termed the pharmagenic enrichment score which aims to make genetic risk scores more directly relevant for treatment. These scores are different than traditional genetic risk scores because they only focus on groups of linked genes which can be targeted by currently available drugs. The concept underlying this is that individuals with high genetic risk in sets of genes with known drug targets may benefit from that particular drug or class of drugs. This approach may allow us to use existing drugs more efficiently, which is important due to the difficulty in developing new drugs for patient use.
We plan to use the UK biobank dataset to develop and refine our method, with a variety of human disorders to be considered including heart disease, diabetes, schizophrenia, and cancer. We will generate these scores for UK biobank participants and use the data collected from participants to try and establish which scores will be most useful. This project has an expected duration between 12 and 24 months. Genetic data is of increasing importance to medical practice and a greater understanding of how genetic risk factors for human disease can be used is warranted. This study will investigate a novel approach for translating genetic risk into clinical action, potentially highlighting new uses for existing drugs.