Abstract
Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.
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Data availability
The GWAS meta-analysis summary statistics are available on the EMBL-EBI GWAS catalog (accession numbers: GCST90278455 for the combined data and GCST90278456 for the European-only data) and the Downloads page of the Cardiovascular Disease Knowledge Portal (CVDKP) and will be integrated into CVDKP. Locus zoom plots are available at https://my.locuszoom.org/gwas/125033/ and FUMA output results are available through the FUMA website. STARNET eQTL data are available in the Database for Genotypes and Phenotypes (dbGaP) via accession: phs001203.v1.p1, as well as web browser: http://starnet.mssm.edu. Coronary artery snATAC data are available in the Gene Expression Omnibus database via accession: GSE175621. Athero-Express scRNAseq data are available at https://doi.org/10.34894/TYHGEF. snATAC and scRNAseq processed datasets are also available on the PlaqView web portal. Athero-Express GWAS, and phenotype data are available at https://doi.org/10.34894/4IKE3T. Genetic variants for imputation were obtained from 1000 Genomes Phase 3 (v5). Variant annotations were obtained from Ensembl (v92). PheWAS data were obtained from the GWAS Atlas. Gene annotations were obtained from GENCODE (v30). eQTL data were also obtained from Genotype Tissue Expression (GTEx v8). Epigenomics data were obtained from Roadmap Epigenomics (release 9) and ENCODE (v4). Pathway annotations were obtained from MsigDB (v6.2) and Kyoto Encyclopedia of Genes and Genomes (KEGG2). Druggability annotations were obtained from DGIDb (v4.0), IDGTargets, Pharos, ChEMBL, DrugBank and ClinicalTrials.gov. Source data are provided with this paper.
Code availability
General post-GWAS analysis scripts are available at https://github.com/CirculatoryHealth/CHARGE_1000G_CAC. Post-GWAS fine-mapping scripts are available at https://github.com/MillerLab-CPHG/Fine_mapping/. Coronary artery snATAC is available at https://github.com/MillerLab-CPHG/Coronary_scATAC.
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Acknowledgements
This work was supported by grants from the National Institutes of Health (R01HL148239 and R01HL164577 to C.L.M.; R01HL142809 and R01HL159514 to R.M.; F31HL156463 to D.W.; R01HL125863 to J.L.M.B.; R01HL146860 to P.S.d.V., K01HL164687 to C.L.L.C., N.R.H., P.A.P. and L.F.B.; R01HL163972 to N.F.; P30DK063491 to J.I.R.; R01DK114183 to T.L.A.; European Union funded H2020 TO_AITION (grant 848146 to S.W.v.d.L.); Netherlands CardioVascular Research Initiative of the Netherlands Heart Foundation (CVON 2011/B019 and CVON 2017-20 (to S.W.v.d.L. and M.d.W.)—generating the best evidence-based pharmaceutical targets for atherosclerosis (GENIUS I&II)), the ERA-CVD program ‘druggable-MI-targets’ (01KL1802 to S.W.v.d.L.) and the Leducq Foundation (‘PlaqOmics’ 18CVD02 to C.L.M., J.L.M.B., G.P. and S.W.v.d.L.). The CHARGE Consortium was supported by NHLBI (grant R01HL105756). M.d.W. was supported by the Netherlands Heart Foundation and Spark-Holding BV (2019B016); Leducq Foundation (LEAN 16CVD01); Amsterdam UMC; ZonMW (Open Competition 09120011910025). A full list of the funding support for each study is provided in Supplementary Note. A full list of acknowledged funding support for individual studies is provided in Supplementary Table 23.
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C.L.M., D.M.B., J.E.H., J.I.R., L.C.B., L.J.L., M.J.B., M.K., M.M.B., P.A.P., R.M., S.W.v.d.L. and V.G were responsible for study concept and design. A.G.U., A.T.H., B.G.K., C.L.M., D.B., D.M.B., J.I.R., J.v.d.G., J.v.M., K.D.T., L.-P.L., L.C.B., L.F.B., L.S., M.J.B., M.M., M.W.V., P.A.P., Q.W., R.S., R.Z., S.L.R.K., S.W.v.d.L., T.L.A., V.G. and X.G. were responsible for phenotype data acquisition and/or QC. A.W.T., B.G.K., C.J.H., C.L.L.C., C.L.M., D.B., D.M.B., H.J.B., H.S., J.A.S., J.I.R., K.D.T., L.C.B., L.F.B., M.B., M.J.B., M.M., M.W.V., N.R.Z., P.A.P., S.L.R.K., S.W.v.d.L. and V.G. were responsible for data acquisition. A.T.H., A.V.S., C.J.H., C.L.M., D.W., E.H., H.J.B., H.L., J.D., K.A.Y., L.-P.L., L.F.B., L.P.L.L., L.R.Y., L.S., M.K., M.M., M.M.B., P.A.P., Q.W., S.C., S.M.L., S.W.v.d.L., T.L.A. and X.G. were responsible for statistical analysis and data interpretation. C.L.L.C., C.J.H., C.L.M., D.W., H.J.B., H.L., L.P.L.L., M.K., M.M.B., P.A.P. and S.W.v.d.L. were responsible for drafting the paper. A.G.U., A.T.H., A.V.S., A.W.T., B.G.K., B.M.P., C.J.H., C.J.O., C.L.L.C., C.L.M., D.B., D.M.B., D.W., E.D.B., E.H., H.J.B., H.L., H.M.d.R., H.S., J.A.S., J.C.B., J.C.K., J.D., J.E.H., J.I.R., J.L.M.B., J.v.d.G., J.v.M., J.v.S., K.A.Y., K.D.T., L.-P.L., L.A.L., L.C.B., L.F.B., L.J.L., L.P.L.L., L.R.Y., M.A.I., M.B., M.J.B., M.K., M. Kho, M.M.B., M.W.V., N.F., N.R.H., N.R.Z., P.A.P., P.E.S., P.S.d.V., Q.W., R.M., R.S., R.Z., S.C., S.L.R.K, S.M., S.M.L., S.W.v.d.L., T.L.A., V.G., W.S.P. and X.G. were responsible for critical revision of the paper. B.G.K., C.L.M., D.M.B., D.P.v.d.K., G.P., H.M.d.R., H.S., J.I.R., L.A.L., L.C.B., L.J.L., M.d.W., M.J.B., M.K., N.F., N.R.H., P.A.P., P.E.S., P.S.d.V., R.M., R.S., S.L.R.K., S.M., S.W.v.d.L. and V.G. were responsible for funding support. A.D.H., A.W.T., B.I.F., C.D.L., C.F., C.J.O., D.R.J., D.W.B., F.A.A.M.H., I.I., J.C.K., J.G.T., J.J.C., J.L.M.B., J.v.S., J.X., L.A.C., M.A.S., M.F., M.K., M.F.F., O.T.R., R.V., S.-J.H., S.C. and T.L. were responsible for additional resources and/or materials.
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S.W.v.d.L. has received Roche funding for unrelated work. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. R.M. receives research funding from Angea Biotherapeutics and Amgen and serves as a consultant for Myokardia/BMS, Renovacor, Epizon Pharma and Third Pole, all unrelated to the current project. C.L.M. has received funding from AstraZeneca on an unrelated project. J.C.K. is the recipient of an Agilent Thought Leader Award (January 2022), which includes funding for research that is unrelated to the current paper. The other authors declare no competing interests.
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Nature Genetics thanks Guillaume Lettre, Alexandre Stewart and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
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Uncropped blots for RUsNX2 and GAPDH.
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Kavousi, M., Bos, M.M., Barnes, H.J. et al. Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification. Nat Genet 55, 1651–1664 (2023). https://doi.org/10.1038/s41588-023-01518-4
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DOI: https://doi.org/10.1038/s41588-023-01518-4
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