“The National Institute for Health and Care Research Bristol Biomedical Research Centre (NIHR Bristol BRC) has been awarded nearly £12 million of new funding for the next five years. The funding has been awarded to University Hospitals Bristol and Weston NHS Foundation Trust by the NIHR, with the University of Bristol a major partner.” - Press release
See the NIHR Bristol Biomedical Research Centre website for more details on the overall BRC research portfolio.
Links to the Data Mining Epidemiological Relationships programme
The NIHR BRC Translational Data Science theme is co-led by Profs Tom Gaunt and John Macleod. The theme aims to translate research in the MRC IEU, in particular in the following two workstreams:
Prioritizing interventions
The first workstream will use genetic evidence to prioritise interventions building on some of our work in the use of molecular QTL Mendelian randomization and genetic colocalization and our collaborations with pharmaceutical partners. This theme will be co-led by Lavinia Paternoster and Gibran Hemani, with Tom Gaunt, Kate Tilling and George Davey Smith.
Mendelian randomization (MR) is a ground-breaking gene-based approach pioneered in Bristol by our Medical Director George Davey Smith. This approach doesn’t involve giving people a particular treatment. Instead, it uses natural variation in our genes to test the effects of a modifiable factor to estimate the effect of that factor on disease outcomes. It also allows us to explore how different populations are affected using existing datasets from around the world.
MR is now routinely used to decide which targets to focus on for medical and public health intervention. However, it has mainly been used for disease prevention rather than treatment. To address this, we will apply our new MR methods to genetic datasets to identify potential treatment targets.
The use of MR has also mainly focused on white European populations. We will work with our large population-based study collaborators, including Global Biobank Meta-analysis Initiative and Born in Bradford, to address this. This will allow us to predict ancestry-specific effects for existing and new drugs, and to prioritise interventions for a range of ethnic groups.
We are working with our other themes, including mental health and diet and physical activity, to apply our MR approaches in their research.
Omics for prediction and prognosis
The second workstream will use omics for prediction and prognosis building on some of Caroline Relton’s work in the MRC IEU on molecular epidemiology, and in particular use of epigenetics for prediction. The workstream will be co-led by Paul Yousefi, Mattew Suderman and Caroline Relton.
In this workstream we use large, complex molecular (‘omics’) datasets to identify biomarkers to predict who will get a disease and how it will progress.
We use machine learning to identify, optimise and validate these molecular biomarkers. We then combine them with data from health records, cohort studies and trials to develop disease prediction tools for use in a range of settings.
Our biomarker identification work will support other NIHR Bristol BRC themes, including respiratory and mental health.