Abstract
Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.
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Data availability
The full summary statistics of the Olink CVD-I protein GWAS have been deposited at the SCALLOP CVD-I online resource (www.scallop-consortium.com), allowing access to interactive SCALLOP CVD-I tools and unrestricted download access for secondary analyses. Additionally, a full copy has been deposited with https://doi.org/10.5281/zenodo.2615265 for long-term retention, as well as with the GWAS Catalog. A copy of the polygenic scores have been deposited at the Polygenic Score Catalog (PGS) Catalog.
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Acknowledgements
Secure computing was supported by NeIC Tryggve, which is the Nordic collaboration for sensitive data funded by NeIC and ELIXIR nodes of participating countries. Sources of funding for SMCC, part of the national research infrastructure SIMPLER: We acknowledge the national research infrastructure SIMPLER (the Swedish Infrastructure for Medical Population-based Life-course and Environmental Research) for provisioning of facilities and support. SIMPLER receives funding through the Swedish Research Council under grant 2017-00644. This study was also supported by additional grants from the Swedish Research Council (grants 2017-06100, 2015-05997 and 2015-03257), the Swedish Research Council for Health, Working Life and Welfare (FORTE grant 2017-00721) and Stiftelsen Olle Engkvist Byggmästare (grant 2017/49). S.L was supported by NIH grant 1R01HL139731 and American Heart Association grant 18SFRN34250007. The Orkney Complex Disease Study (ORCADES) was supported by the Chief Scientist Office of the Scottish Government (CZB/4/276 and CZB/4/710), a Royal Society URF to J.F.W., the MRC Human Genetics Unit quinquennial programme ‘QTL in Health and Disease', Arthritis Research UK and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). DNA extractions were performed at the Edinburgh Clinical Research Facility. G.D.S. works in the Medical Research Council Integrative Epidemiology Unit at the University of Bristol (MC_UU_00011/1). We would like to acknowledge the invaluable contributions of the research nurses in Orkney, the administrative team in Edinburgh and the people of Orkney. M.A-.K. is supported by a Senior Research Fellowship from the National Health and Medical Research Council (NHMRC) of Australia (APP1158958). He also has a research grant from the Sigrid Juselius Foundation, Finland. A.D.B. was supported by a Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. J.G.S. and the genotyping of MPP-RES was supported by grants from the Swedish Heart-Lung Foundation (2016-0134 and 2016-0315), the Swedish Research Council (2017-02554), the European Research Council (ERC-STG-2015-679242), the Crafoord Foundation, Skåne University Hospital, Scania County, governmental funding of clinical research within the Swedish National Health Service, a generous donation from the Knut and Alice Wallenberg foundation to the Wallenberg Center for Molecular Medicine in Lund, and funding from the Swedish Research Council (Linnaeus grant Dnr 349-2006-237, Strategic Research Area Exodiab Dnr 2009-1039) and the Swedish Foundation for Strategic Research (Dnr IRC15-0067) to the Lund University Diabetes Center. The study of the LifeLines-DEEP cohort is supported by the Netherlands Heart Foundation CVON grant 2018-27 to J.F. and A.Z., Netherlands Organization for Scientific Research (NWO-VIDI grant 864.13.013 to J.F., 016.178.056 to A.Z., 917.14.374 to L. Franke, VENI grant 194.006 to D.V.Z., Gravitation grant ExposomeNL 024.004.017 to A.Z. and gravitation 024.003.001 to J.F.), European Research Council (ERC starting grant 715772 to A.Z. and 637640 to L. Franke). L. Franke also receives financial support from Oncode Institute. The CROATIA_Vis study was funded by grants from the Medical Research Council (UK), European Commission Framework 6 project EUROSPAN (contract no. LSHG-CT-2006-018947) and the Republic of Croatia Ministry of Science, Education and Sports research grants (108-1080315-0302). We would like to acknowledge the staff of several institutions in Croatia that supported the field work, including but not limited to The University of Split and Zagreb Medical Schools, Institute for Anthropological Research in Zagreb and the Croatian Institute for Public Health. The SNP genotyping for the Vis cohort was performed in the core genotyping laboratory of the Clinical Research Facility at the Western General Hospital, Edinburgh, Scotland. C.H. is supported by MRC University Unit Programme Grant MC_UU_00007/10 (QTL in Health and Disease). P.W.F. was supported by a grant from the European Research Council (CoG-2015_681742_NASCENT). P.S. is supported by a Rutherford Fund Fellowship from the Medical Research Council, grant MR/S003746/1. J.D. holds a British Heart Foundation Professorship and a National Institute for Health Research Senior Investigator Award. Participants in the INTERVAL randomized controlled trial were recruited with active collaboration and funding from NHS Blood and Transplant England (www.nhsbt.nhs.uk), the National Institute for Health Research (NIHR), the NIHR BioResource (http://bioresource.nihr.ac.uk) and the NIHR Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust, NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014-10024), UK Medical Research Council (MR/L003120/1) and British Heart Foundation (SP/09/002, RG/13/13/30194 and RG/18/13/33946). We would like to thank J. Parks at Wake Forest School of Medicine, Winston-Salem, NC, USA, and D. Rader at Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA, for their kind donations of samples from transgenic mice and controls. Estonian Biobank analyses were funded by EU H2020 grant 692145, Estonian Research Council grant PUT1660, European Union through the European Regional Development Fund Project nos. 2014-2020.4.01.15-0012 and 2014-2020.4.01.16-0125, ERA-CVD grant Detectin-HF. Data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. M.V.H. works in a unit that receives funding from the UK Medical Research Council and is supported by a British Heart Foundation Intermediate Clinical Research Fellowship (FS/18/23/33512) and the National Institute for Health Research Oxford Biomedical Research Centre. This research has been conducted using the UK Biobank Resource under Application no. 13721. Finally, we would like to thank Moving Science for beautiful work on the front-page art proposal (https://movingscience.dk). This work was carried out on behalf of the SCALLOP consortium.
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L. Folkersen, S.G., Q.W., D.H.H., Å.K.H., D.V.Z., E.F., E.M.D., E.I. and A.M. contributed to meta-analysis. L. Folkersen, Å.K.H., D.V.Z., Y.W., J.R.G., Y.C., A.C., F.M., E.F., L. Franke, T.Q., R.W., H.-J.W., J.Y. and A.M. contributed to functional analysis. L. Folkersen, S.G., Q.W., G.D.S., T.P., T.Q., J.Y., L.W., A.S.B., M.V.H., E.I. and A.M. contributed to MR analysis. S.G., J.P., N.E., S.E.B., T.S.B., A.D.B., St.E., A.K., M.A-.K., S.H.C., J.D., Sö.E, C.F., L. Franke, P.W.F., V.G., C. Haley, A.H., Å.J., P.K.J., L.L., C.M.L., S.L., E.M.D., M.M., A.P.M., R.M., M.W.N., O.P., B.P., E.P., J.S., P.S., U.V., H.-J.W., A.Z., J.Ä., J.F., J.G.S., T.E., C. Hayward, U.G., M.L., A. Siegbahn, J.F.W., L.W., A.S.B., E.I. and A.M. contributed to cohort-level analysis. B.E.S., L.M. and A.M. contributed to mouse experiments. K.P., J.D.G., J.L., W.Z., A.Q. and A.M. contributed to clinical trials. L. Folkersen, Å.K.H., A. Schork, J.R.G., F.M., E.F., A.I., T.W. and A.M. contributed to other downstream analysis. L. Folkersen, S.G., Å.K.H., G.E., C.F., O.M., K.M., P.M.N., J.N., M.O.M., M.S. and A.M. contributed to replication analysis. L. Folkersen, S.G., Q.W., M.V.H., E.I. and A.M. contributed to writing. L. Folkersen, S.G., Q.W., A.S.B., M.V.H., E.I. and A.M. contributed to project planning. All authors gave final approval to publish.
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J.P. received travel support from Olink AB. R.W., F.M. and D.H.H. are employees of Intomics A/S. A.M., A.Q., E.F., J.D.G., J.L., K.P., M.W.N. and W.Z. are employees of Pfizer Inc. E.I., after this work was completed, became an employee of GSK Inc.
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Extended data
Extended Data Fig. 1 MR-selected loci.
Chromosomal location of all primary associations that were selected as instrument variables for Mendelian Randomization, that is those passing Bonferroni corrected GWAS significance P < 5.6 × 10−10 with replication at nominal p < 0.05, or for non-heterogeneous variants (p < 9 × 10−5), surpassing a P-value threshold of P < 5 × 10−8 in the joint discovery and replication meta-analysis.
Extended Data Fig. 2 Online tools.
Illustration of the online interactive tools for visualization of genomic loci, regions and plausible networks (www.scallop-consortium.com). a. Illustration of hotspot loci on chromosome 10 (left) and illustration of hotspot loci with independent effects established using COJO analysis (right) b. Circular Manhattan plot for TNF-R2. C. The pathway implicated by trans-pQTLs for plasma TNF-R2. The network shows the likely path from pQTL to TNF-R2.
Extended Data Fig. 3 PrediXcan heatmap.
Heat map showing PrediXcan associations across tissues for any protein with significant associations between protein and predicted mRNA levels (FDR < 0.05) in at least one tissue. In each cell, numeric labels correspond to the uncorrected P-value from the association of protein with predicted expression levels. The colour palette shows the relative expression level of the gene across tissues in the GTeX resource.
Extended Data Fig. 4 CCR5-2 trial additional results.
Effect of exposure to PF-04634817 on EN-RAGE, FGF-23, KIM-1, myoglobin and TNFR-2. Box plots elements are according to standards for box-and-whisker diagrams.
Extended Data Fig. 5 Work flows 1.
Work flows describing meta analysis.
Extended Data Fig. 6 Work flows 2.
Work flows describing decisions on significance.
Extended Data Fig. 7 Work flows 3.
Work flows describing reasoning behind Mendelian Randomization evidence strength.
Extended Data Fig. 8 Polygenic risk score effects on complex outcomes.
Meta-regression of quantiles of ST2 polygenic risk score and relative risk of asthma (left) and inflammatory bowel disease (right). Values plotted on the x-axis relate to the quantile-specific mean difference in ST2 as compared to the 6th quantile. Values plotted on the y-axis relate to the quantile-specific log odds of disease as compared to the 6th quantile. The red line is the slope derived from the meta-regression across the ST2 quantiles of the PRS on log odds of disease, weighted by the standard error of the log odds.
Extended Data Fig. 9 Cis and trans comparison.
Comparison of absolute effect sizes of all primary cis- and trans loci listed in Supplementary Table 2. Box plots elements are according to standards for box-and-whisker diagrams.
Supplementary information
Supplementary Information
Supplementary Fig. 1: Overview of protein levels showing effects on complex phenotypes using MR. Similar to Fig. 4b, but also showing effects with intermediate evidence strength. Supplementary Fig. 2: Overview of complex phenotypes showing effects on protein levels using MR. Supplementary Note: Detailed overview of systems biology processes.
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Folkersen, L., Gustafsson, S., Wang, Q. et al. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals. Nat Metab 2, 1135–1148 (2020). https://doi.org/10.1038/s42255-020-00287-2
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DOI: https://doi.org/10.1038/s42255-020-00287-2
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