The Genetics of Coronary Heart Disease across Ethnicities and in those with Type 2 Diabetes

Coronary heart disease (CHD) is the most common cause of the death worldwide, presenting a considerable burden to both individual and public health. The genetics of CHD was investigated in two contexts in this thesis - risk prediction and the identification of functional mechanisms through which associated loci affect CHD pathophysiology. The use of a 19 single nucleotide polymorphism (SNP) CHD gene score (GS) was assessed in three ethnic groups (European, South Asian and Afro-Caribbean), but there was no strong evidence of clinical utility. A systematic literature search identified all variants robustly associated with CHD. Most of these variants were from the meta-analysis performed by the CARDIoGRAMplusC4D consortium. The GS was updated using effect sizes from this meta-analysis, resulting in improved performance. Overall, there was evidence of potential clinical utility in the European and Afro-Caribbean groups and in those with type 2 diabetes (T2D) (all p<0.05). However, results from the Pakistani cohorts were inconsistent. T2D-specific GSs were also assessed and were associated with CHD in the T2D group only (p<0.05). Functional analysis of two risk loci was performed. Firstly, rs10911021, previously associated with CHD in T2D and this result was supported by the findings of this thesis. Counterintuitively, the CHD “protective” allele was associated with lower high density lipoprotein (HDL) cholesterol (p=5x10-4) and lower large HDL traits (false discovery rate adjusted p-values p<0.05) in T2D only, indicating a complex relationship between CHD, T2D and HDL. Secondly, the CHD risk locus on chromosome 21q22 (lead SNP rs9982601) was not associated with any CHD risk factors. Using bioinformatics tools and in vitro functional assays, a candidate functional SNP - rs28451064 - was identified (which showed allele-specific protein binding and the minor allele had 12 % higher expression p=4.82x10-3). Further investigation is required to define the underlying molecular pathways

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

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

Effect of SORT1, APOB and APOE polymorphisms on LDL-C and coronary heart disease in Pakistani subjects and their comparison with Northwick Park Heart Study II

BACKGROUND: Many SNPs have been identified in genes regulating LDL-C metabolism, but whether their influence is similar in subjects from different ethnicities is unclear. Effect of 4 such SNPs on LDL-C and coronary heart disease (CHD) was examined in Pakistani subjects and was compared with middle aged UK men from Northwick Park Heart Study II (NPHSII). METHODS: One thousand nine hundred sixty-five (1770 non CHD, 195 CHD) UK and 623 (219 non CHD, 404 CHD) Pakistani subjects were enrolled in the study. The SNPs SORT1 rs646776, APOB rs1042031 and APOE rs429358, rs7412 were genotyped by TaqMan/KASPar technique and their gene score was calculated. LDL-C was calculated by Friedewald equation, results were analyzed using SPSS. RESULTS: Allele frequencies were significantly different (p = <0.05) between UK and Pakistani subjects. However, the SNPs were associated with LDL-C in both groups. In UK non CHD, UK CHD, Pakistani non CHD and Pakistani CHD respectively, for rs646776, per risk allele increase in LDL-C(mmol/l) was 0.18(0.04), 0.06(0.11), 0.15(0.04) and 0.27(0.06) respectively. For rs1042031, per risk allele increase in LDL-C in four groups was 0.11(0.04), 0.04(0.14), 0.15(0.06) and 0.25(0.09) respectively. For APOE genotypes, compared to Ɛ3, each Ɛ2 decreased LDL-C by 0.11(0.06), 0.07(0.15), 0.20(0.08) and 0.38(0.09), while each Ɛ4 increased LDL-C by 0.43(0.06), 0.39(0.21), 0.19(0.11) and 0.39(0.14) respectively. Overall gene score explained a considerable proportion of sample variance in four groups (3.8 %, 1.26 % 13.7 % and 12.3 %). Gene score in both non-CHD groups was significantly lower than CHD subjects. CONCLUSIONS: The SNPs show a dose response association with LDL-C levels and risk of CHD in both populations

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

UK Medical Research Council; British Heart Foundation

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

Genetic risk analysis of coronary artery disease in Pakistani subjects using a genetic risk score of 21 variants

BACKGROUND AND AIMS: Conventional coronary artery disease (CAD) risk factors like age, gender, blood lipids, hypertension and smoking have been the basis of CAD risk prediction algorithms, but provide only modest discrimination. Genetic risk score (GRS) may provide improved discrimination over and above conventional risk factors. Here we analyzed the genetic risk of CAD in subjects from Pakistan, using a GRS of 21 variants in 18 genes and examined whether the GRS is associated with blood lipid levels. METHODS: 625 (405 cases and 220 controls) subjects were genotyped for variants, NOS3 rs1799983, SMAD3 rs17228212, APOB rs1042031, LPA rs3798220, LPA rs10455872, SORT1 rs646776, APOE rs429358, GLUL rs10911021, FTO rs9939609, MIA3 rs17465637, CDKN2Ars10757274, DAB2IP rs7025486, CXCL12 rs1746048, ACE rs4341, APOA5 rs662799, CETP rs708272, MRAS rs9818870, LPL rs328, LPL rs1801177, PCSK9 rs11591147 and APOE rs7412 by TaqMan and KASPar allele discrimination techniques. RESULTS: Individually, the single SNPs were not associated with CAD except APOB rs1042031 and FTO rs993969 (p = 0.01 and 0.009 respectively). However, the combined GRS of 21 SNPs was significantly higher in cases than controls (19.37 ± 2.56 vs. 18.47 ± 2.45, p = 2.9 × 10(-5)), and compared to the bottom quintile, CAD risk in the top quintile of the GRS was 2.96 (95% CI 1.71-5.13). Atherogenic blood lipids showed significant positive association with GRS. CONCLUSIONS: The GRS was quantitatively associated with CAD risk and showed association with blood lipid levels, suggesting that the mechanism of these variants is likely to be, in part at least, through creating an atherogenic lipid profile in subjects carrying high numbers of risk alleles

A 19-SNP coronary heart disease gene score profile in subjects with type 2 diabetes: the coronary heart disease risk in type 2 diabetes (CoRDia study) study baseline characteristics

Background: The coronary risk in diabetes (CoRDia) trial (n = 211) compares the effectiveness of usual diabetes care with a self-management intervention (SMI), with and without personalised risk information (including genetics), on clinical and behavioural outcomes. Here we present an assessment of randomisation, the cardiac risk genotyping assay, and the genetic characteristics of the recruits. / Methods: Ten-year coronary heart disease (CHD) risk was calculated using the UKPDS score. Genetic CHD risk was determined by genotyping 19 single nucleotide polymorphisms (SNPs) using Randox’s Cardiac Risk Prediction Array and calculating a gene score (GS). Accuracy of the array was assessed by genotyping a subset of pre-genotyped samples (n = 185). / Results: Overall, 10-year CHD risk ranged from 2–72 % but did not differ between the randomisation groups (p = 0.13). The array results were 99.8 % concordant with the pre-determined genotypes. The GS did not differ between the Caucasian participants in the CoRDia SMI plus risk group (n = 66) (p = 0.80) and a sample of UK healthy men (n = 1360). The GS was also associated with LDL-cholesterol (p = 0.05) and family history (p = 0.03) in a sample of UK healthy men (n = 1360). / Conclusions: CHD risk is high in this group of T2D subjects. The risk array is an accurate genotyping assay, and is suitable for estimating an individual’s genetic CHD risk. / Trial registration: This study has been registered at ClinicalTrials.gov; registration identifier NCT0189178

Clinical utility of a coronary heart disease risk prediction gene score in UK healthy middle aged men and in the Pakistani population

8 Sep 2015: Beaney KE, Cooper JA, Ullah Shahid S, Ahmed W, Qamar R, et al. (2015) Correction: Clinical Utility of a Coronary Heart Disease Risk Prediction Gene Score in UK Healthy Middle Aged Men and in the Pakistani Population. PLOS ONE 10(9): e0139651. https://doi.org/10.1371/journal.pone.0139651© 2015 Beaney et al. 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.KEB is supported by a Medical Research Council CASE award (1270920) with Randox Laboratories. SUS is supported by Higher Education Commisson Pakistan (IRSIP 24 BMS 41). SEH is a British Heart Foundation Professor and he and JAC are supported by the British Heart Foundation (RG008/08) and by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. NPHSII was supported by the British Medical Research Council, the US National Institutes of Health [grant number NHLBI 33014] and Du Pont Pharma, Wilmington Delaware

A 19-SNP coronary heart disease gene score profile in subjects with type 2 diabetes: the coronary heart disease risk in type 2 diabetes (CoRDia study) study baseline characteristics

Background The coronary risk in diabetes (CoRDia) trial (n = 211) compares the effectiveness of usual diabetes care with a self-management intervention (SMI), with and without personalised risk information (including genetics), on clinical and behavioural outcomes. Here we present an assessment of randomisation, the cardiac risk genotyping assay, and the genetic characteristics of the recruits. Methods Ten-year coronary heart disease (CHD) risk was calculated using the UKPDS score. Genetic CHD risk was determined by genotyping 19 single nucleotide polymorphisms (SNPs) using Randox’s Cardiac Risk Prediction Array and calculating a gene score (GS). Accuracy of the array was assessed by genotyping a subset of pre-genotyped samples (n = 185). Results Overall, 10-year CHD risk ranged from 2–72 % but did not differ between the randomisation groups (p = 0.13). The array results were 99.8 % concordant with the pre-determined genotypes. The GS did not differ between the Caucasian participants in the CoRDia SMI plus risk group (n = 66) (p = 0.80) and a sample of UK healthy men (n = 1360). The GS was also associated with LDL-cholesterol (p = 0.05) and family history (p = 0.03) in a sample of UK healthy men (n = 1360). Conclusions CHD risk is high in this group of T2D subjects. The risk array is an accurate genotyping assay, and is suitable for estimating an individual’s genetic CHD risk. Trial registration This study has been registered at ClinicalTrials.gov; registration identifier NCT0189178

Effectiveness of a self-management intervention with personalised genetic and lifestyle-related risk information on coronary heart disease and diabetes-related risk in type 2 diabetes (CoRDia): study protocol for a randomised controlled trial

Background Many patients with type 2 diabetes fail to achieve good glycaemic control. Poor control is associated with complications including coronary heart disease (CHD). Effective self-management and engagement in health behaviours can reduce risks of complications. However, patients often struggle to adopt and maintain these behaviours. Self-management interventions have been found to be effective in improving glycaemic control. Recent developments in the field of genetics mean that patients can be given personalised information about genetic- and lifestyle-associated risk of developing CHD. Such information may increase patients’ motivation to engage in self-management. The Coronary Risk in Diabetes (CoRDia) trial will compare the effectiveness of a self-management intervention, with and without provision of personalised genetic- and lifestyle-associated risk information, with usual care, on clinical and behavioural outcomes, the cognitive predictors of behaviour, and psychological wellbeing. Methods/Design Participants will be adults aged 25–74 years registered with general practices in the East of England, diagnosed with type 2 diabetes, with no history of heart disease, and with a glycated haemoglobin level of ≥6.45 % (47 mmol/mol). Consenting participants will be randomised to one of three arms: usual care control, group self-management only, group self-management plus personalised genetic- and lifestyle-associated risk information. The self-management groups will receive four weekly 2-hour group sessions, focusing on knowledge and information sharing, problem solving, goal setting and action planning to promote medication adherence, healthy eating, and physical activity. Primary outcomes are glycaemic control and CHD risk. Clinical data will be collected from GP records, including HbA1c, weight, body mass index, blood pressure, and HDL and total cholesterol. Self-reported health behaviours, including medication adherence, healthy eating and physical activity, and cognitive outcomes will be assessed by questionnaire. Measures will be taken at baseline, 3 months (questionnaire only), 6 months and 12 months post-baseline. Discussion This study will determine whether the addition of personalised genetic- and lifestyle-associated CHD risk information to a group self-management intervention improves diabetes control and CHD risk compared with group self-management and usual care. Effectiveness of the combined intervention on health behaviours cognitions theorised to predict them, and psychological outcomes will also be investigated. Trial registration This study has been registered at ClinicalTrials.gov; registration identifier NCT01891786, registered 28 June 2013