Senior Director, Global Population Health Olink Proteomics San Francisco, California, United States
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 samples sizes in both healthy and disease samples. Here we have combined the PEA technology with automated sample preparation and a high-throughput sequencing readout for parallel measurement of over 5,400 proteins for up to 344 samples in a next generation sequencing run. 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 like the UK Biobank Pharma Proteomics Project and SCALLOP Consortium. We will also share details on publicly available data resulting from such efforts as well as examples where such insights are enabling disease and application specific clinical tools.
