Proteomics as a bridge between genomics and human health: a systematic approach to identify therapeutic targets in large population health cohorts like the UK biobank

Understanding the dynamics of the human proteome is crucial for identifying biomarkers to be used as measurable indicators for disease severity and progression, patient stratification, and drug development. It can also help us translate the impact our genetics has on more real-time health. The Proximity Extension Assay (PEA) translates protein information into actionable insights across large sample sizes in both healthy and disease samples. We have combined the PEA technology with automated sample preparation and a high-throughput sequencing readout for parallel measurement of >5,400 proteins for up to 172 samples at a time. Coverage includes low abundant proteins (e.g., cytokines), tissue leakage proteins (e.g., troponins), and overlap with high abundant proteins well served by mass spectrometry (e.g., globins). Characterizing the proteome alongside genetic and clinical data enables a protein quantitative trait loci (pQTL) framework to not only validate known clinical targets and identify new clinical targets but to also suggest repurposing opportunities of clinical candidates for new indications. We will discuss goals and results of large population health studies integrating proteomics, genomics and clinical data, including the UK Biobank-Pharma Proteomics Project (UKB-PPP).