Proteomics has emerged as an indispensable tool in biomarker discovery for the detection, prognosis, and treatment of disease. The UK Biobank (UKB) Pharma Proteomics Project represents the prime example of large-scale proteomics, using Olink® Explore to quantify levels of nearly 3,000 proteins in plasma samples from over 50,000 individuals. When combined with e.g., genomic or healthcare data in UKB, the opportunities for biomarker research in biology and medicine are tremendous.
This study aimed to estimate the future risk of a large and diverse set of diseases for all protein biomarkers available in UKB, thus generating a library of protein-disease risk associations freely available to researchers worldwide. In total, 107 diseases were selected from the PheWAS ontology and mapped to diagnosis codes in UKB. For each protein, the association between plasma levels and time to first occurrence (up to 10 years) of each disease was assessed using Cox regression, generating over 300,000 protein-disease risk associations adjusted for sex, age, BMI, and smoking.
Our results reveal a large heterogeneity in strength and number of associations both across diseases and proteins. Some proteins, for example GDF15, have statistically significant associations to a high proportion of all included diseases. Several strong associations, e.g., TNFRSF13B with leukemia, have been previously reported in independent research.
The complete set of results has been made freely available via Olink Insight, an online portal to support proteomic research. This new resource can enhance future studies by guiding biomarker selection or acting as a cross-reference post study.