This project will use UK Biobank’s Olink protein data to understand how patterns of protein activity in blood relate to future health outcomes such as heart disease, asthma, or other major conditions. Rather than looking at thousands of proteins one by one, we will group related proteins into biological pathways – such as inflammation, immune response, or metabolism – and calculate a single “pathway activity score” for each. These pathway scores summarise how strongly each biological process is activated in a person’s blood sample.
Our research aims to answer three questions:
Are these pathway activity scores linked to future health events, even after accounting for age, sex, lifestyle, and other factors?
Can these scores improve prediction of disease risk beyond traditional clinical measures?
Are the results similar across different ages, sexes, and genetic backgrounds?
To do this, we will clean and standardise the Olink data, calculate pathway activity scores using our TopMD topological algorithm, and use statistical models to test their association with disease outcomes and their ability to predict risk. This approach reduces noise, avoids over-fitting, and produces results that are easier to interpret – for example, showing that “a one-unit increase in immune pathway activity is linked to higher risk of disease X.”
All analyses will take place securely within the UK Biobank Research Analysis Platform, and only aggregated, non-identifiable results (such as summary statistics, model coefficients, and performance metrics) will be exported.