Integrative proteo-genomic analysis to investigative immune-mediated disease aetiology

Most common diseases—like arthritis, diabetes, or asthma—are not caused by a single faulty gene but by the combined effect of hundreds of genetic variants, each nudging risk up or down by a tiny amount. This project aims to sharpen the tool that measures that cumulative genetic risk, called a polygenic risk score (PRS), by integrating it with detailed protein data from the same individuals. Current PRS calculations are blunt: they sum up risk alleles from genome-wide studies, but they ignore the functional consequences of those variants—what proteins they actually alter, and in which immune cells. By layering proteomic data onto genomic data, the researchers hope to identify which genetic changes matter most for immune-mediated diseases, and why. If successful, this could transform how doctors assess a person’s likelihood of developing conditions like rheumatoid arthritis or inflammatory bowel disease, moving from a population-level probability to a more precise, biologically grounded prediction. This is fundamental science—it does not promise an immediate diagnostic test—but it builds the mechanistic understanding needed to eventually target prevention or treatment to those who will benefit most.