Katherine E. Beaney

Clinical Utility of a Coronary Heart Disease Risk Prediction Gene Score in UK Healthy Middle Aged Men and in the Pakistani Population.

Background Numerous 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. Methods We 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. Results In 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. Conclusion 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.

Influence of Genetic Risk Factors on Coronary Heart Disease Occurrence in Afro-Caribbeans

Background Despite excessive rates of cardiovascular risk factors such as hypertension, diabetes, and obesity, Afro-Caribbeans have lower mortality rates from coronary heart disease (CHD) than do whites. This study evaluated the association of genetic risk markers previously identified in whites and CHD in Afro-Caribbeans. Methods We studied 537 Afro-Caribbean individuals (178 CHD cases and 359 controls) who were genotyped for 19 CHD-related single-nucleotide polymorphisms (SNPs). A genetic risk score (GRS) incorporating the 19 SNPs was calculated. These participants were compared with 1360 white individuals from the Second Northwick Park Heart Study. Results In Afro-Caribbeans, patients with CHD had higher rates of hypertension (78.7% vs 30.1%), hypercholesterolemia (52.8% vs 15.0%), and diabetes (53.9% vs 14.8%) and were more often men (64.0% vs 43.7%) and smokers (27.5% vs 13.4%) compared with non-CHD controls (all P < 0.001). The GRS was higher in Afro-Caribbeans with CHD than in those without CHD (13.90 vs 13.17; P < 0.001) and was significantly associated with CHD after adjustment for cardiovascular risk factors, with an odds ratio of 1.40 (95% confidence interval, 1.09-1.80) per standard deviation change. There were significant differences in allelic distributions between the 2 ethnic groups for 14 of the 19 SNPs. The GRS was substantially lower in Afro-Caribbean controls compared with white controls (13.17 vs 16.59; P < 0.001). Conclusions This study demonstrates that a multilocus GRS composed of 19 SNPs associated with CHD in whites is a strong predictor of the disease in Afro-Caribbeans. The differences in CHD occurrence between Afro-Caribbeans and whites might be a result of significant discrepancies in common gene variant distribution.

Assessment of the clinical utility of adding common single nucleotide polymorphism genetic scores to classical risk factor algorithms in coronary heart disease risk prediction in UK men

Abstract Background: Risk prediction algorithms for coronary heart disease (CHD) are recommended for clinical use. However, their predictive ability remains modest and the inclusion of genetic risk may improve their performance. Methods: QRISK2 was used to assess CHD risk using conventional risk factors (CRFs). The performance of a 19 single nucleotide polymorphism (SNP) gene score (GS) for CHD including variants identified by genome-wide association study and candidate gene studies (weighted using the results from the CARDIoGRAMplusC4D meta-analysis) was assessed using the second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases). To improve the GS, five SNPs with weak evidence of an association with CHD were removed and replaced with seven robustly associated SNPs – giving a 21-SNP GS. Results: The weighted 19 SNP GS was associated with lipid traits (p<0.05) and CHD after adjustment for CRFs, (OR=1.31 per standard deviation, p=0.03). Addition of the 19 SNP GS to QRISK2 showed improved discrimination (area under the receiver operator characteristic curve 0.68 vs. 0.70 p=0.02), a positive net reclassification index (0.07, p=0.04) compared to QRISK2 alone and maintained good calibration (p=0.17). The 21-SNP GS was also associated with CHD after adjustment for CRFs (OR=1.39 per standard deviation, 1.42×10−3), but the combined QRISK2 plus GS score was poorly calibrated (p=0.03) and showed no improvement in discrimination (p=0.55) or reclassification (p=0.10) compared to QRISK2 alone. Conclusions: The 19-SNP GS is robustly associated with CHD and showed potential clinical utility in the UK population.

How close are we to implementing a genetic risk score for coronary heart disease

ABSTRACT Introduction: Genome-wide association meta-analysis have now identified more than 150 loci where common variants (SNPs) are significantly associated with coronary heart disease (CHD) and CHD end points. Areas covered: The authors review publications from their own laboratory and published recently where identified CHD risk SNPs are used in combination, and ‘scaled’ by their effect size, to create a ‘weighted’ Genetic risk Score (GRS), which, in combination with an individual’s classical CHD risk factors, can be used to identify those at overall low, intermediate and high future risk. Those at highest risk can be offered life-style and therapeutic options to reduce their risk and those at intermediate levels can be monitored. Expert commentary: The authors discuss the selection of the best variants to be included in the GRS, and the potential utility of such scores in different clinical settings. The limitations of the current data sets and the way forward in the next 5 years is discussed.

Functional Analysis of the Coronary Heart Disease Risk Locus on Chromosome 21q22.

Background. The coronary heart disease (CHD) risk locus on 21q22 (lead SNP rs9982601) lies within a “gene desert.” The aim of this study was to assess if this locus is associated with CHD risk factors and to identify the functional variant(s) and gene(s) involved. Methods. A phenome scan was performed with UCLEB Consortium data. Allele-specific protein binding was studied using electrophoretic mobility shift assays. Dual-reporter luciferase assays were used to assess the impact of genetic variation on expression. Expression quantitative trait analysis was performed with Advanced Study of Aortic Pathology (ASAP) and Genotype-Tissue Expression (GTEx) consortium data. Results. A suggestive association between QT interval and the locus was observed (rs9982601  p = 0.04). One variant at the locus, rs28451064, showed allele-specific protein binding and its minor allele showed 12% higher luciferase expression (p = 4.82 × 10−3) compared to the common allele. The minor allele of rs9982601 was associated with higher expression of the closest upstream genes (SLC5A3 1.30-fold increase p = 3.98 × 10−5; MRPS6 1.15-fold increase p = 9.60 × 10−4) in aortic intima media in ASAP. Both rs9982601 and rs28451064 showed a suggestive association with MRPS6 expression in relevant tissues in the GTEx data. Conclusions. A candidate functional variant, rs28451064, was identified. Future work should focus on identifying the pathway(s) involved.