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

Author

Listed:
  • Chen Yao

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • George Chen

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Ci Song

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health
    Uppsala University
    Uppsala University)

  • Joshua Keefe

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Michael Mendelson

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health
    Boston Children’s Hospital)

  • Tianxiao Huan

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Benjamin B. Sun

    (University of Cambridge)

  • Annika Laser

    (German Research Center for Environmental Health
    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
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Asya Lyass

    (Framingham Heart Study
    Boston University)

  • Martin G. Larson

    (Framingham Heart Study
    Boston University School of Public Health)

  • Christian Gieger

    (German Research Center for Environmental Health
    German Research Center for Environmental Health
    German Center for Diabetes Research (DZD))

  • Johannes Graumann

    (Max Planck Institute for Heart and Lung Research, W.G. Kerckhoff Institute)

  • Andrew D. Johnson

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • John Danesh

    (University of Cambridge
    Addenbrooke’s Hospital
    Wellcome Trust Genome Campus)

  • Heiko Runz

    (MRL, Merck & Co., Inc)

  • Shih-Jen Hwang

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Chunyu Liu

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

  • Adam S. Butterworth

    (University of Cambridge
    University of Cambridge)

  • Karsten Suhre

    (Weill Cornell Medicine-Qatar, Education City)

  • Daniel Levy

    (Framingham Heart Study
    National Heart, Lung, and Blood Institute, National Institutes of Health)

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.

Suggested Citation

  • 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 Lya, 2018. "Genome‐wide mapping of plasma protein QTLs identifies putatively causal genes and pathways for cardiovascular disease," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-05512-x
    DOI: 10.1038/s41467-018-05512-x
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    Cited by:

    1. Yihao Lu & Meritxell Oliva & Brandon L. Pierce & Jin Liu & Lin S. Chen, 2024. "Integrative cross-omics and cross-context analysis elucidates molecular links underlying genetic effects on complex traits," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Robert F. Hillary & Danni A. Gadd & Zhana Kuncheva & Tasos Mangelis & Tinchi Lin & Kyle Ferber & Helen McLaughlin & Heiko Runz & Riccardo E. Marioni & Christopher N. Foley & Benjamin B. Sun, 2024. "Systematic discovery of gene-environment interactions underlying the human plasma proteome in UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Grace Png & Andrei Barysenka & Linda Repetto & Pau Navarro & Xia Shen & Maik Pietzner & Eleanor Wheeler & Nicholas J. Wareham & Claudia Langenberg & Emmanouil Tsafantakis & Maria Karaleftheri & George, 2021. "Mapping the serum proteome to neurological diseases using whole genome sequencing," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    4. Jia You & Yu Guo & Yi Zhang & Ju-Jiao Kang & Lin-Bo Wang & Jian-Feng Feng & Wei Cheng & Jin-Tai Yu, 2023. "Plasma proteomic profiles predict individual future health risk," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    5. Richard Howey & So-Youn Shin & Caroline Relton & George Davey Smith & Heather J Cordell, 2020. "Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data," PLOS Genetics, Public Library of Science, vol. 16(3), pages 1-35, March.
    6. Andrew A. Brown & Juan J. Fernandez-Tajes & Mun-gwan Hong & Caroline A. Brorsson & Robert W. Koivula & David Davtian & Théo Dupuis & Ambra Sartori & Theodora-Dafni Michalettou & Ian M. Forgie & Jonath, 2023. "Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    7. Maik Pietzner & Eleanor Wheeler & Julia Carrasco-Zanini & Nicola D. Kerrison & Erin Oerton & Mine Koprulu & Jian’an Luan & Aroon D. Hingorani & Steve A. Williams & Nicholas J. Wareham & Claudia Langen, 2021. "Synergistic insights into human health from aptamer- and antibody-based proteomic profiling," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    8. Lingyan Chen & James E. Peters & Bram Prins & Elodie Persyn & Matthew Traylor & Praveen Surendran & Savita Karthikeyan & Ekaterina Yonova-Doing & Emanuele Angelantonio & David J. Roberts & Nicholas A., 2022. "Systematic Mendelian randomization using the human plasma proteome to discover potential therapeutic targets for stroke," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    9. Andrew D Bretherick & Oriol Canela-Xandri & Peter K Joshi & David W Clark & Konrad Rawlik & Thibaud S Boutin & Yanni Zeng & Carmen Amador & Pau Navarro & Igor Rudan & Alan F Wright & Harry Campbell & , 2020. "Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits," PLOS Genetics, Public Library of Science, vol. 16(7), pages 1-24, July.
    10. Erik Duijvelaar & Jack Gisby & James E. Peters & Harm Jan Bogaard & Jurjan Aman, 2024. "Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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