Association analyses based on false discovery rate implicate new loci for coronary artery disease

Journal name:
Nature Genetics
Year published:
DOI:
doi:10.1038/ng.3913
Received
Accepted
Published online

Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10−8) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; ncases = 10,801) as well as a stricter definition without angina (HARD; ncases = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS2, 3. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold2, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.

At a glance

Figures

  1. Description of HARD and SOFT CAD phenotypes in UK Biobank.
    Figure 1: Description of HARD and SOFT CAD phenotypes in UK Biobank.

    (a) Diagram depicting individuals with the CAD phenotype definitions in UK Biobank. HARD CAD encompasses individuals with fatal or nonfatal myocardial infarction (MI), percutaneous transluminal coronary angioplasty (PTCA) or coronary artery bypass grafting (CABG). SOFT CAD includes individuals meeting the HARD CAD definition as well as those with chronic ischemic heart disease (IHD) and angina. In UK Biobank self-reported data, cases were defined as having 'vascular/heart problems diagnosed by doctor' or 'non-cancer illnesses that self-reported as angina or heart attack'. Self-reported surgery included PTCA, CABG or triple heart bypass. In HESIN hospital episodes data and death registry data from diagnosis and operation (primary and secondary causes), MI was defined as hospital admission or cause of death due to ICD9 410–412, ICD10 I21–I24, I25.2; PTCA was defined as hospital admission for PTCA (OPCS-4 K49, K50.1, K75); CABG was defined as hospital admission for CABG (OPCS-4 K40–K46); and angina or chronic IHD was defined as hospital admission or death due to ICD9 413, 414.0, 414.8, 414.9, ICD10 I20, I25.1, I25.5–I25.9. (b) Radar plot highlighting the proportions (%) of signals shared between the HARD and SOFT CAD phenotype definitions based on the results obtained with the 5% FDR threshold (Supplementary Table 4). P < 5 × 10−8 marks variants reaching genome-wide significance; OR > 1.05 corresponds to 85% power to detect a signal (α < 0.05) in the SOFT analysis. The results for all six subgroups of variants assessed did not differ statistically between the two phenotype definitions (P > 0.1).

  2. Transposed Manhattan plot showing meta-analysis results for the SOFT CAD definition under an additive model.
    Figure 2: Transposed Manhattan plot showing meta-analysis results for the SOFT CAD definition under an additive model.

    P values are truncated at −log10 (P) = 20. Markers shown are from the meta-analysis of UKBB with the 1000 Genomes–imputed GWAS data2 unless flagged by an asterisk (Exome chip markers). The red dashed lines denote the GWAS (P = 5 × 10−8) and 5% FDR (P = 6.28 × 10−5) significance thresholds. Known CAD risk loci are shown in black (Supplementary Table 2); KSR2 and ZNF507LOC400684 reached genome-wide significance under a recessive model2. The 11p15_MRVI1CTR9 locus had discordant results in the CAD 1000 Genomes–imputed GWAS2 and Exome data set4. The lead variant in the Exome data set, rs11042937, was associated with P = 3.21 × 10−8; data shown are from the meta-analysis with the 1000 Genomes–imputed GWAS, as this marker had an imputation info score of 1 (Online Methods). The 13 new CAD-associated loci that reached genome-wide significance in our study (including replication data; Table 1) are labeled in brown. EAF, effect allele frequency; OR, odds ratio.

  3. Comparison of single-marker P values for the 5% FDR variants in the published CARDIoGRAMplusC4D 1000 Genomes-imputed CAD GWAS meta-analysis and the current FDR-based analysis.
    Figure 3: Comparison of single-marker P values for the 5% FDR variants in the published CARDIoGRAMplusC4D 1000 Genomes–imputed CAD GWAS meta-analysis and the current FDR-based analysis.

    Of the 162 variants that had P < 5 × 10−5 in the CAD 1000 Genomes (1000G)-imputed GWAS2, 116 had a match or good proxy (r2 > 0.8) in the new FDR-defined list (blue circles). SNPs in red (n = 7) were present in the earlier FDR-defined list and reached genome-wide significance in the current analysis.

  4. Heat map showing DEPICT gene set enrichment results with zoom-in on a subset of the results.
    Figure 4: Heat map showing DEPICT gene set enrichment results with zoom-in on a subset of the results.

    556 gene sets were included that had evidence of enrichment at 1% FDR. The x axis shows the names of genes predicted to be included in the reconstituted gene sets shown along in the y axis. Red indicates higher z score, where z score is a value corresponding to a gene's inclusion in a reconstituted gene set. Clustering was performed on the basis of the complete linkage method. Highlighted pathways in the cluster include angiogenesis, blood vessel development and morphogenesis.

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Author information

  1. These authors contributed equally to this work.

    • Christopher P Nelson,
    • Anuj Goel,
    • Adam S Butterworth,
    • Stavroula Kanoni,
    • Heribert Schunkert,
    • Martin Farrall,
    • John Danesh,
    • Nilesh J Samani,
    • Hugh Watkins &
    • Panos Deloukas

Affiliations

  1. Department of Cardiovascular Sciences, University of Leicester, Leicester, UK.

    • Christopher P Nelson,
    • Tom R Webb,
    • Florence Y Lai,
    • Stephen E Hamby &
    • Nilesh J Samani
  2. National Institute for Health Research Leicester Biomedical Research Centre, Leicester, UK.

    • Christopher P Nelson,
    • Tom R Webb,
    • Florence Y Lai,
    • Stephen E Hamby &
    • Nilesh J Samani
  3. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.

    • Anuj Goel,
    • Christopher Grace,
    • Theodosios Kyriakou,
    • Martin Farrall &
    • Hugh Watkins
  4. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

    • Anuj Goel,
    • Christopher Grace,
    • Theodosios Kyriakou,
    • Martin Farrall &
    • Hugh Watkins
  5. MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

    • Adam S Butterworth,
    • Tao Jiang,
    • Emanuele Di Angelantonio,
    • Joanna M M Howson,
    • Michael J Sweeting &
    • John Danesh
  6. NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

    • Adam S Butterworth,
    • Emanuele Di Angelantonio &
    • John Danesh
  7. William Harvey Research Institute, Barts & the London Medical School, Queen Mary University of London, London, UK.

    • Stavroula Kanoni,
    • Eirini Marouli,
    • Ioanna Ntalla,
    • Olga Giannakopoulou &
    • Panos Deloukas
  8. Centre for Genomic Health, Queen Mary University of London, London, UK.

    • Stavroula Kanoni,
    • Eirini Marouli,
    • Ioanna Ntalla,
    • Olga Giannakopoulou &
    • Panos Deloukas
  9. German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany.

    • Lingyao Zeng,
    • Adnan Kastrati,
    • Thorsten Kessler &
    • Heribert Schunkert
  10. CTSU, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

    • Jemma C Hopewell &
    • Robert Clarke
  11. Department of Medicine, Stanford University School of Medicine, Stanford, California, USA.

    • Themistocles L Assimes
  12. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Erwin P Bottinger,
    • Yingchang Lu &
    • Ruth J F Loos
  13. Department of Epidemiology and Biostatistics, Imperial College London, London, UK.

    • John C Chambers,
    • Evangelos Evangelou &
    • Ioanna Tzoulaki
  14. Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK.

    • John C Chambers &
    • Jaspal S Kooner
  15. Imperial College Healthcare NHS Trust, London, UK.

    • John C Chambers &
    • Jaspal S Kooner
  16. Molecular and Clinical Medicine, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK.

    • Colin N A Palmer
  17. Pharmacogenomics Centre, Biomedical Research Institute, University of Dundee, Ninewells Hospital, Dundee, UK.

    • Colin N A Palmer
  18. Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.

    • Richard M Cubbon
  19. Cardiac Arrhythmia Service and Cardiovascular Research Center, Broad Institute of Harvard and Massachusetts Institute of Technology, Boston, Massachusetts, USA.

    • Patrick Ellinor
  20. Department of Cardiac Surgery, Tartu University Hospital, Tartu, Estonia.

    • Raili Ermel &
    • Arno Ruusalepp
  21. Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece.

    • Evangelos Evangelou &
    • Ioanna Tzoulaki
  22. Department of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Lund University Diabetes Center, Skåne University Hospital, Lund University, Malmö, Sweden.

    • Paul W Franks
  23. Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA.

    • Paul W Franks
  24. Department of Public Health and Clinical Medicine, Unit of Medicine, Umeå University, Umeå, Sweden.

    • Paul W Franks
  25. State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

    • Dongfeng Gu
  26. Institute of Cardiovascular Science, University College London,London, UK.

    • Aroon D Hingorani &
    • Amand F Schmidt
  27. Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.

    • Erik Ingelsson &
    • Xiangfeng Lu
  28. Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.

    • Terho Lehtimäki
  29. Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

    • Yingchang Lu
  30. Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria.

    • Winfried März
  31. Medical Clinic V (Nephrology, Rheumatology, Hypertensiology, Endocrinology, Diabetology), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.

    • Winfried März
  32. Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany.

    • Winfried März
  33. Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Ottawa, Ontario, Canada.

    • Ruth McPherson
  34. Estonian Genome Center, University of Tartu, Tartu, Estonia.

    • Andres Metspalu
  35. Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, UK.

    • Mar Pujades-Rodriguez
  36. Clinical Gene Networks AB, Stockholm, Sweden.

    • Arno Ruusalepp &
    • Johan L M Björkegren
  37. Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Eric E Schadt &
    • Johan L M Björkegren
  38. Lebanese American University, School of Medicine, Beirut, Lebanon.

    • Pierre A Zalloua
  39. Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

    • Pierre A Zalloua
  40. Department of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.

    • Kamal AlGhalayini
  41. Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

    • Bernard D Keavney
  42. Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.

    • Bernard D Keavney &
    • Maciej Tomaszewski
  43. Cardiovascular Science, National Heart and Lung Institute, Imperial College London, London, UK.

    • Jaspal S Kooner
  44. Mindich Child Health Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

    • Ruth J F Loos
  45. Farr Institute of Health Informatics, UCL, London, UK.

    • Riyaz S Patel
  46. Bart's Heart Centre, St Bartholomew's Hospital, London, UK.

    • Riyaz S Patel
  47. Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

    • Martin K Rutter
  48. Manchester Diabetes Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.

    • Martin K Rutter
  49. Division of Medicine, Central Manchester NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.

    • Maciej Tomaszewski
  50. Wellcome Trust Sanger Institute, Hinxton, UK.

    • Eleftheria Zeggini
  51. Institute for Cardiogenetics, University of Lübeck, Lübeck, Germany.

    • Jeanette Erdmann
  52. DZHK (German Research Centre for Cardiovascular Research), partner site Hamburg/Lübeck/Kiel, Lübeck, Germany.

    • Jeanette Erdmann
  53. University Heart Center Lübeck, Lübeck, Germany.

    • Jeanette Erdmann
  54. Department of Nutrition-Dietetics, Harokopio University, Athens, Greece.

    • George Dedoussis
  55. Integrated Cardio Metabolic Centre, Department of Medicine, Karolinska Institutet, Karolinska Universitetssjukhuset, Huddinge, Sweden.

    • Johan L M Björkegren
  56. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.

    • John Danesh
  57. Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia.

    • Panos Deloukas

Consortia

  1. EPIC-CVD Consortium

  2. A list of members and affiliations appears in the Supplementary Note.

  3. CARDIoGRAMplusC4D

  4. A list of members and affiliations appears in the Supplementary Note.

  5. The UK Biobank CardioMetabolic Consortium CHD working group

  6. A list of members and affiliations appears in the Supplementary Note.

Contributions

C.P.N., A.G., A.S.B., S.K., T.R.W., E.M., I.N., J.C.H., O.G., H.S., M.F., J.D., N.J.S., H.W. and P.D. wrote and edited the manuscript. All authors contributed and discussed the results and commented on the manuscript. A.S.B., O.G., T.J., L.Z., S.E.H., E.A., T.L.A., E.P.B., J.C.C., R.C., R.M.C., P.E., R.E., E.E., P.W.F., C.G., D.G., A.H., J.M.M.H., E.I., A.K., T. Kessler, T. Kyriakou, T.L., X.L., Y.L., W.M., R.M., A.M., C.N.A.P., M.P.-R., A.F.S., M.J.S., P.A.Z., K.A., R.J.F.L., E.Z., J.E., G.D., H.S., J.D., N.J.S., H.W. and P.D. generated data and cohorts. C.P.N., A.S.B., I.N., F.Y.L., J.C.H., O.G., B.D.K., J.S.K., R.J.F.L., R.S.P., M.R., M.T., I.T., E.Z., J.E., G.D., H.S., J.D., N.J.S., H.W. and P.D. analyzed phenotype data for UKBB and replication studies. C.P.N., A.G., A.S.B., S.K., T.J. and M.F. performed the statistical analyses. C.P.N., S.K., T.R.W., A.S.B., R.E., A.R., E.E.S. and J.L.M.B. performed functional annotation. E.M. and P.D. performed biological and clinical enrichment and pathway analyses.

Competing financial interests

P.W.F. has been a paid consultant for Eli Lilly and Sanofi Aventis and has received research support from several pharmaceutical companies as part of a European Union Innovative Medicines Initiative (IMI) project. E.I. is an advisor and consultant for Precision Wellness, Inc., and an advisor for Cellink for work unrelated to the present project. M.K.R. has acted as a consultant for GSK, Roche, Ascensia and MSD and participated in advisory board meetings on their behalf. M.K.R. has received lecture fees from MSD and grant support from Novo Nordisk, MSD and GSK. J.L.M.B. is the founder and chairman of Clinical Gene Networks. CGN has financially contributed to the STARNET study. J.L.M.B., E.E.S. and A.R. are on the board of directors for CGN. J.L.M.B. and A.R. own equity in CGN and receive financial compensation from CGN.

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Supplementary information

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    Supplementary Tables 2, 4, 6, 7 and 9–11.

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