doi: 10.1111/j.1469-1809.2007.00359.x The use of Meta-Analysis Risk Estimates for Candidate Genes in Combination to Predict Coronary Heart Disease Risk F. Drenos 1, * , J. C. Whittaker 2 and S. E. Humphries 1 1 Centre for Cardiovascular Genetics, Dept. of Medicine, British Heart Foundation Laboratories, Rayne Building, Royal Free and University College Medical School, 5 University Street, London WC1E 6JF, UK 2 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK Summary Although the risk for coronary heart disease (CHD) associated with single SNPs is modest it has been suggested that, in combination, several common risk-associated alleles could lead to a substantially better heart disease risk prediction. We have modelled this using 10 SNPs in ten candidate genes (APOB, NOS3, APOE, ACE, SERPINE1, MTHFR, ITGA2B, PON 1, LPL, and CETP) and their predicted summary risk estimates from meta-analysis. Based on published allele frequencies, ∼ 29% of the general population would be expected to carry less than three risk alleles, approximately 55% would carry 3 or 4 risk alleles, 4% would have 6 and 1% 7 or more risk alleles. Compared to the mean of those with 3 or 4 risk associated genotypes, those with 6 and 7-or-more alleles have a significantly higher risk odds ratio (OR) of CHD (mean OR (95% Confidence Intervals), 1.70 (1.14 to 2.55); and 4.51 (2.89 to 7.04) respectively), while compared to those in the lowest decile of risk, those in the highest decile have a CHD odds ratio in the range of 3.05 (2.24 to 4.14). Taking into account age and the risk alleles carried, the mean 10 year probability for developing CHD for a 55 year old man was calculated to be 15% (8.6% to 24.8%), with nearly 1 in 5 having more than 20% risk. Whether this particular group of 10 SNPs will improve the accuracy of CHD predictions over the combination of classical risk factors in clinical use requires further experimental evidence. Keywords: Meta-analysis, candidate genes, coronary heart disease, risk, odds ratio, 10 year risk, APOB, NOS3, APOE, ACE, SERPINE1, MTHFR, ITGA2B, PON 1, LPL, CETP Introduction One of the major aims for genetic epidemiology is to use genetic information to identify individuals who have an inherited predisposition to multifactorial diseases, such as early coronary heart disease (CHD). Although some workers in the field have expressed doubts as to whether a candidate gene approach can ever add significantly to heart disease risk prediction (Humphries et al. 2004), because of the modest impact on risk, and the appar- ent inconsistency of effect, there is good supportive data ∗ Correspondence author: F. Drenos Tel: 0207 679 6964. Fax: 0207 679 6212; E-mail: f.drenos@ucl.ac.uk to refute this view (Janssens et al. 2006). Meta-analysis, based on the combined information from 2000–10000 subjects, gives strong support to the idea that some “can- didate” genes do contain common variants associated with a statistically significant effect on heart disease risk traits and risk itself (reviewed in Casas et al. 2006). Fur- ther analysis suggests that the effects of at least some of these genes are unlikely to be explained by publica- tion bias or confounded by ethnic heterogeneity, and examples include APOE, MTHFR, CETP, and NOS3 (Song & Liu, 2003; Casas et al. 2004; Boekholdt et al. 2005; Dominguez-Rodriguez et al. 2005). Although individually the impact of any one genotype on risk is modest, when such risk-genotypes are common their C  2007 The Authors Journal compilation C  2007 University College London Annals of Human Genetics (2007) 71,611–619 611