Abstract
BackgroundNumerous risk prediction algorithms based on conventional risk factors for Coronary Heart Disease (CHD) are available but provide only modest discrimination. The inclusion of genetic information may improve clinical utility.MethodsWe tested the use of two gene scores (GS) in the prospective second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases), and Pakistani case-control studies from Islamabad/Rawalpindi (321 cases/228 controls) and Lahore (414 cases/219 controls). The 19-SNP GS included SNPs in loci identified by GWAS and candidate gene studies, while the 13-SNP GS only included SNPs in loci identified by the CARDIoGRAMplusC4D consortium.ResultsIn NPHSII, the mean of both gene scores was higher in those who went on to develop CHD over 13.5 years of follow-up (19-SNP p=0.01, 13-SNP p=7x10-3). In combination with the Framingham algorithm the GSs appeared to show improvement in discrimination (increase in area under the ROC curve, 19-SNP p=0.48, 13-SNP p=0.82) and risk classification (net reclassification improvement (NRI), 19-SNP p=0.28, 13-SNP p=0.42) compared to the Framingham algorithm alone, but these were not statistically significant. When considering only individuals who moved up a risk category with inclusion of the GS, the improvement in risk classification was statistically significant (19-SNP p=0.01, 13-SNP p=0.04). In the Pakistani samples, risk allele frequencies were significantly lower compared to NPHSII for 13/19 SNPs. In the Islamabad study, the mean gene score was higher in cases than controls only for the 13-SNP GS (2.24 v 2.34, p=0.04). There was no association with CHD and either score in the Lahore study.ConclusionThe performance of both GSs showed potential clinical utility in European men but much less utility in subjects from Pakistan, suggesting that a different set of risk loci or SNPs may be required for risk prediction in the South Asian population.
Highlights
Despite being largely preventable, coronary heart disease (CHD) remains the most common cause of the death worldwide [1, 2]
The 19-SNP gene scores (GS) included SNPs in loci identified by genomewide association studies (GWAS) and candidate gene studies, while the 13-SNP GS only included SNPs in loci identified by the CARDIoGRAMplusC4D consortium
There was no association with Coronary Heart Disease (CHD) and either score in the Lahore study. The performance of both GSs showed potential clinical utility in European men but much less utility in subjects from Pakistan, suggesting that a different set of risk loci or SNPs may be required for risk prediction in the South Asian population
Summary
Coronary heart disease (CHD) remains the most common cause of the death worldwide [1, 2]. There is a growing CHD burden in the developing world [3], in South Asian countries such as Pakistan where the prevalence of CHD in urban Karachi has approximately doubled since 1970[4] This increase is most likely due to the adoption of a more “Western” lifestyle combined with a greater susceptibility to metabolic syndrome[5]. A number of conventional risk factor (CRF) scores to determine 10-year risk CHD risk have been developed. Lower cut-offs have been proposed in both the USA [13] and the UK, with the 2014 National Institute for Health and Care Excellence (NICE) guidelines setting the threshold at 10%[14] To date, such risk scores have provided only modest discrimination. Numerous risk prediction algorithms based on conventional risk factors for Coronary Heart Disease (CHD) are available but provide only modest discrimination.
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