We are releasing the summary data from three meta-analyses of coronary artery disease and myocardial infarction, to empower other researchers to examine variants or loci in which they are interested for association with these disease traits.
- CARDIoGRAM GWAS is a meta-analysis of 22 GWAS studies of European descent imputed to HapMap 2 involving 22,233 cases and 64,762 controls - data as published in: Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011 43: 333-338
- C4D GWAS is a meta-analysis of GWAS studies of European and South Asian descent (PROCARDIS, HPS, PROMIS and LOLIPOP) involving 15,420 CHD cases and 15,062 controls - data as published in: Coronary Artery Disease (C4D) Genetics Consortium (Writing Committee: Peden JF, Hopewell JC, Saleheen D, Chambers JC, Hager J, Soranzo N, Collins R, Danesh J, Elliott P, Farrall M, Stirrups K, Zhang W, Hamsten A, Parish S, Lathrop M, Watkins H (Chair), Clarke R, Deloukas P, Kooner J). A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease. Nat Genet. 2011 43: 339-344
- CARDIoGRAMplusC4D Metabochip is a two stage meta-analysis of Metabochip and GWAS studies of European and South Asian descent involving 63,746 cases and 130,681 controls. The CARDIoGRAM GWAS data was used as Stage 1 - data as published in: CARDIoGRAMplusC4D Consortium, Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet 2013 45:25-33
- CARDIoGRAMplusC4D 1000 Genomes-based GWAS is a meta-analysis of GWAS studies of mainly European, South Asian, and East Asian, descent imputed using the 1000 Genomes phase 1 v3 training set with 38 million variants. The study interrogated 9.4 million variants and involved 60,801 CAD cases and 123,504 controls. Data as published in: CARDIoGRAMplusC4D Consortium, M Nikpey, A Goel, H Won, LM Hall C. Willenborg, S Kanoni, D Saleheen et al. A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease. Nat Genet 2015 47:1121-1130.
- Myocardial Infarction Genetics and CARDIoGRAM Exome is a meta-analysis of Exome-chip studies of European descent involving 42,335 patients and 78,240 controls. Results for low-frequency (1-5% minor allele frequency MAF)) and rare (MAF < 1%) coding variants were published in Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators, Stitziel NO, Stirrups KE, Masca NG, Erdmann J, et al. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease/. N Engl J Med. 2016 Mar 24;374(12):1134-44. doi: 10.1056/NEJMoa15076522. Results for common variants were published in Webb TR, Erdmann J, Stirrups KE, Stitziel NO, Masca NG, et al. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease. J Am Coll Cardiol. 2017 Feb 21;69(7):823-836. doi: 10.1016/j.jacc.2016.11.056.
We note that there is no sample overlap between CARDIoGRAM GWAS and C4D GWAS but CARDIoGRAMplusC4D Metabochip includes both sample sets in full.
The overlap between CARDIoGRAMplusC4D Metabochip and CARDIoGRAMplusC4D 1000 Genomes-based GWAS is ~55 % (34,997 (57.5%) cases and 49,512 (40.1%) controls).
Files are in text delimited format and include:
SNP ID, chromosomal position (b36), reference allele, other allele, REFERENCE_ALLELE_FREQ, Pvalue, Heterogeneity p value, log_odds, log_odds_se, beta, Standard error, No_cases, No_controls, model.
SNP ID, chromosomal position (b36), reference allele, other allele, log_odds stage 21, log_odds_se_stage 2, P value for stage 2, No_cases_stage 2, No_controls_stage 2, Heterogeneity p value_stage 2, model_stage2, Fisher_Pvalue2, No_samples (all), REFERENCE_ALLELE_FREQ, log_odds, log_odds_se, Heterogeneity p value3, model, InverseVariance_Pvalue.
( c ) 1000 Genomes-based GWAS
Markername, chr, bp_hg19, effect_allele, noneffect_allele, effect_allele_freq, median_info, model, beta, se_dgc, p_dgc, het_pvalue, n_studies. The 3 results files correspond to (i) all cases analysed with an additive model, (ii) all cases analysed with a recessive model, and (iii) all MI cases with an additive model.
- 1 beta = ln(OR)
- 2 used to combine stage 1 and stage 2 data for SNPs with same direction of effect
- 3 the random model was used for SNPs with p values below 0.01
( d ) Exome chip
SNP ID, chromosomal position (hg19), effect_allele, other allele, effect_allele_freq, log_OR, P value, se, No_samples, Heterogeneity p value. Analysis was performed using an additive model.
CARDIoGRAM GWAS & CARDIoGRAMplusC4D Metabochip data sets were adjusted for age, sex and study-specific covariates. In the C4D GWA meta-analysis and the 1000 Genomes-based GWAS meta-analyses adjustment was for study-specific covariates only.
Please note that CARDIoGRAMplusC4D is currently undertaking the analyses listed under Ongoing Projects, please contact the relevant PI if you wish to discuss collaborating.
These data are intended for research purposes only. The sample size and precision of the data presented should preclude de-identification of any individual subject. However, in downloading these data, you undertake not to attempt to de-identify individual subjects.
Acknowledging the data
When using data from the downloadable meta-analyses results please acknowledge the source of the data as follows: 'Data on coronary artery disease / myocardial infarction have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG'. For the Exome chip study please acknowledge the source of the data as follows: 'Data on coronary artery disease / myocardial infarction have been contributed by the Myocardial Infarction Genetics and CARDIoGRAM Exome investigators and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG'. In addition, please cite the relevant paper(s) for the data used.
Downloading the data
The data can be downloaded from the following links:
- CARDIoGRAM GWA meta-analysis: CARDIoGRAM GWA meta-analysis [DOC 77,154KB][77,154KB]
- C4D GWA meta-analysis: C4D GWA meta-analysis [DOC 14,213KB][14,213KB]
- CARDIoGRAMplusC4D Metabochip meta-analysis: CARDIoGRAMplusC4D Metabochip meta-analysis [DOC 4,296KB][4,296KB] (updated 18 August 2014)
- CARDIoGRAMplusC4D 1000 Genomes-based GWAS:
- CARDIoGRAMplusC4D 1000 Genomes-based GWAS - Additive [DOC 259,623KB][259,623KB]
- CARDIoGRAMplusC4D 1000 Genomes-based GWAS - Recessive [DOC 190,086KB][190,086KB]
- CARDIoGRAMplusC4D - mi.additive.Oct2015[388,902KB][388,902KB]
Myocardial Infarction Genetics and CARDIoGRAM Exome chip meta-analysis: Myocardial Infarction Genetics and CARDIoGRAM Exome chip Public release[2,307KB][2,307KB]
For any enquiries about the datasets, please contact the following individuals:
- CARDIoGRAM: Nilesh J Samani or Jeanette Erdmann
- C4D: Hugh Watkins or Jemma Hopewell
- CARDIoGRAMplusC4D: Panos Deloukas or Stavroula Kanoni
- CARDIoGRAMplusC4D 1000 Genomes-based GWAS: Anuj Goel or Martin Farrall
- Myocardial Infarction Genetics and CARDIoGRAM Exome chip: Nathan Stitziel or Sekar Kathiresan