Henning Jansen1, Christina Loley2, Wolfgang Lieb3, Michael J Pencina4, Christopher P Nelson5, Sekar Kathiresan6, Gina M Peloso7, Benjamin F Voight8, Muredach P Reilly8, Themistocles L Assimes9, Eric Boerwinkle10, Christian Hengstenberg1, Reijo Laaksonen11, Ruth McPherson12, Robert Roberts12, Unnur Thorsteinsdottir13, Annette Peters14, Christian Gieger14, Rajesh Rawal14, John R Thompson15, Inke R König2, Ramachandran S Vasan16, Jeanette Erdmann17, Nilesh J Samani5, Heribert Schunkert1. 1. Deutsches Herzzentrum and DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Technische Universität München, Munich, Germany. 2. Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Lübeck, Germany. 3. Institut für Epidemiologie, Universität zu Kiel, Kiel, Germany. 4. Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Durham, NC, USA. 5. Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, LE3 9QP, UK; Leicester National Institute for Health Research Biomedical Research Unit in Cardiovascular Disease, Glenfield Hospital, Leicester, LE3 9QP, UK. 6. Cardiovascular Research Center and Cardiology Division, Massachusetts General Hospital, Boston, MA, USA; Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, USA. 7. Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA. 8. The Cardiovascular Institute, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. 9. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. 10. University of Texas Health Science Center, Human Genetics Center and Institute of Molecular Medicine, Houston, TX, USA. 11. Science Center, Tampere University Hospital, Tampere, Finland. 12. The John & Jennifer Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Canada. 13. deCODE Genetics and University of Iceland, Faculty of Medicine, 101, Reykjavik, Iceland. 14. Institut für Epidemiologie II, Helmholtz Zentrum München, Neuherberg, Germany; Munich Heart Alliance, Munich, Germany. 15. Department of Health Sciences, University of Leicester, Leicester, UK. 16. School of Medicine, Section of Preventive Medicine and Epidemiology, Boston University, Boston, MA, USA. 17. Institut für Integrative und Experimentelle Genomik Universität zu Lübeck, DZHK (German Centre for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany.
Abstract
BACKGROUND: The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. METHODS AND RESULTS: We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD. CONCLUSIONS: Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting.
BACKGROUND: The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. METHODS AND RESULTS: We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p < 5*10(-8)) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p < 0.05), more than expected by chance (p = 5.0*10(-5)). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973-1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p = 7.2*10(-10) vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD. CONCLUSIONS: Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting.
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Authors: John Molvin; Amra Jujic; Peter M Nilsson; Margret Leosdottir; Ulf Lindblad; Bledar Daka; Louise Bennet; Lennart Råstam; Valeriya Lyssenko; Martin Magnusson Journal: ESC Heart Fail Date: 2019-12-20