| Literature DB >> 29875488 |
Benjamin B Sun1, Joseph C Maranville2,3, James E Peters1,4, David Stacey1, James R Staley1, James Blackshaw1, Stephen Burgess1,5, Tao Jiang1, Ellie Paige1,6, Praveen Surendran1, Clare Oliver-Williams1,7, Mihir A Kamat1, Bram P Prins1, Sheri K Wilcox8, Erik S Zimmerman8, An Chi2, Narinder Bansal1,9, Sarah L Spain10, Angela M Wood1, Nicholas W Morrell4,11, John R Bradley12, Nebojsa Janjic8, David J Roberts13,14, Willem H Ouwehand4,15,16,17,18, John A Todd19, Nicole Soranzo4,15,17,18, Karsten Suhre20, Dirk S Paul1, Caroline S Fox2, Robert M Plenge2,3, John Danesh21,22,23,24, Heiko Runz2,25, Adam S Butterworth26,27.
Abstract
Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development.Entities:
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Year: 2018 PMID: 29875488 PMCID: PMC6697541 DOI: 10.1038/s41586-018-0175-2
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962