The use of meta-analysis risk estimates for candidate genes in combination to predict coronary heart disease risk.
ANN HUM GENET
611 - 619.
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, similar to 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.
|Title:||The use of meta-analysis risk estimates for candidate genes in combination to predict coronary heart disease risk|
|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, CARDIOVASCULAR-DISEASE, COMPLEX DISEASES, GENOTYPE, CHOLESTEROL, POPULATION, SMOKING, PROCAM, MEN|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
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