Genome‐wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease

Chen Yao, George Chen, Ci Song, Joshua Keefe, Michael Mendelson, Tianxiao Huan, Benjamin B. Sun, Annika Laser, Joseph C. Maranville, Hongsheng Wu, Jennifer E. Ho, Paul Courchesne, Asya Lyass, Martin G. Larson, Christian Gieger, Johannes Graumann, Andrew D. Johnson, John Danesh, Heiko Runz, Shih-Jen Hwang, Chunyu Liu, Adam S. Butterworth, Karsten Suhre and Daniel Levy ()
Additional contact information
Chen Yao: Framingham Heart Study
George Chen: Framingham Heart Study
Ci Song: Framingham Heart Study
Joshua Keefe: Framingham Heart Study
Michael Mendelson: Framingham Heart Study
Tianxiao Huan: Framingham Heart Study
Benjamin B. Sun: University of Cambridge
Annika Laser: German Research Center for Environmental Health
Joseph C. Maranville: MRL, Merck & Co., Inc
Hongsheng Wu: Wentworth Institute of Technology
Jennifer E. Ho: Massachusetts General Hospital
Paul Courchesne: Framingham Heart Study
Asya Lyass: Framingham Heart Study
Martin G. Larson: Framingham Heart Study
Christian Gieger: German Research Center for Environmental Health
Johannes Graumann: Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff Institute
Andrew D. Johnson: Framingham Heart Study
John Danesh: University of Cambridge
Heiko Runz: MRL, Merck & Co., Inc
Shih-Jen Hwang: Framingham Heart Study
Chunyu Liu: Framingham Heart Study
Adam S. Butterworth: University of Cambridge
Karsten Suhre: Weill Cornell Medicine-Qatar, Education City
Daniel Levy: Framingham Heart Study

Nature Communications, 2018, vol. 9, issue 1, 1-11

Abstract: Abstract Identifying genetic variants associated with circulating protein concentrations (protein quantitative trait loci; pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome’s causal role in disease and bridge a knowledge gap regarding SNP-disease associations. We provide the results of GWAS of 71 high-value cardiovascular disease proteins in 6861 Framingham Heart Study participants and independent external replication. We report the mapping of over 16,000 pQTL variants and their functional relevance. We provide an integrated plasma protein-QTL database. Thirteen proteins harbor pQTL variants that match coronary disease-risk variants from GWAS or test causal for coronary disease by Mendelian randomization. Eight of these proteins predict new-onset cardiovascular disease events in Framingham participants. We demonstrate that identifying pQTLs, integrating them with GWAS results, employing Mendelian randomization, and prospectively testing protein-trait associations holds potential for elucidating causal genes, proteins, and pathways for cardiovascular disease and may identify targets for its prevention and treatment.

Date: 2018
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DOI: 10.1038/s41467-018-05512-x

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