Massive genetic map reveals which proteins drive disease—and which ones drugs can target
Scientists analyzed genetic data from nearly 80,000 people to map how DNA controls blood protein levels and connected this to disease risk. The findings identify thousands of new drug targets and reveal which existing medications might work against diseases they weren't designed for, potentially accelerating drug development and cutting costs.
Originaltitel: Multi-cohort proteogenomic analyses reveal genetic effects across the proteome and diseasome.
Understanding the genetic regulation of circulating protein levels can provide new insights into disease mechanisms. Here, we present the largest proteogenomic study to date (n = 78,664 participants across 38 studies), identifying >24,000 protein quantitative trait loci (QTLs) associated with 1,116 proteins, acting near to (n = 5,040) or distant (n = 19,698) from the cognate gene. Using machine learning-guided effector gene assignment, we provide genetic evidence for pathways, cell types, and tissues that modulate circulating protein levels, highlighting N-linked glycosylation as an important regulatory pathway. We demonstrate that genetic instruments of protein production/function ("cis") versus modulation ("trans") reveal distinct phenotypic insights. We identify proteins as candidates for drug targets and engagement (e.g., plasma furin and cardiovascular diseases) by comparing cis-based genetic evidence with protein-disease associations. Systematic triangulation of trans-protein QTLs (pQTLs) with genetic and protein associations across many diseases highlights potential drug repurposing opportunities, e.g., tyrosine kinase 2 (TYK2) inhibitors for rheumatoid arthritis. Our multi-cohort meta-analyses generate proteogenomic insights into disease mechanisms and new treatment opportunities.