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.

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Background: Obesity has become global epidemic in the last three decades, whereas Coronary Heart Disease (CHD) still remains the most important cause of mortality in the world. The study was aimed at determining the pattern of lipid profile for the obese and CHD population in Pakistan. As obesity is a strong predisposing risk factor for CHD, we aimed to analyze the lipid parameters in both conditions and compare them with the healthy controls of the same ethnicity. Methods: Blood samples were collected from one thousand individuals (500 with CHD, 250 with obesity, 250 healthy controls). The lipid profile (total Cholesterol, triglycerides, HDL-C, LDL-C and VLDL) was measured using commercially available kits. The pattern of dyslipidemia was then studied by comparing the results in both groups with controls as well as population cutoffs. The quantitative variables were checked for normality and log transformation was done for variables where appropriate. Analysis of variance and logistic regression were done to check the association of lipid parameters with obesity and CHD. Results: The obese and CHD groups showed a dyslipidemic profile than the healthy controls. CHD group had a higher proportion of CHD in any of the first degree blood relatives (36.0% vs. 1.8%), a similar trend was observed in the obese group, where 63.9% cases had positive family history. Among cases, 50.7% had combined lipid abnormalities, i.e., the values of TC, LDL-C, TG and HDL-C, all were deranged. Whereas 49.52% had TC more than normal cut off (> 200 mg/dl), 51.6% had LDL-C > 100 mg/dl. Similarly, 80.4% of patients had TG levels more than upper normal range (> 150 mg/dl) and 64% had HDL values in moderate CHD risk group (< 50 mg/dl). The results show that Pakistani cases are hyperlipidemic for lipid traits except for HDL which is lowered. Patients with comorbidities also had lipid profiles deviated from the normal range. Conclusion: The study provides information regarding the aberration of lipid profile in the metabolic disorders that can increase the predisposition to complications.

Back ground and Aims: Conventional risk factors like age, gender, blood lipids, hypertension and smoking have been the basis of coronary artery disease (CAD) risk prediction algorithms, but provide only modest discrimination. A genetic risk score (GRS) may provide improved discrimination over and above conventional risk factors alone. The current study analysed the genetic risk of CAD in Pakistani subjects using a GRS of 21 loci in 18 genes and examined whether its association with blood lipids in this cohort.Methods: 625 subjects were genotyped for the variants, NOS3 rs1799983, SMAD3 rs17228212, APOBrs1042031, LPArs3798220, LPA rs10455872, SORT1rs646776, APOE rs429358, GLUL rs10911021 and FTO rs9939609 (by TaqMan) and MIA3 rs17465637,CDKN2A rs10757274, DAB2IP rs7025486, CXCL12 rs1746048, ACE rs4341, APOA5 rs662799, CETP rs708272, MRAS rs9818870, LPL rs328,LPL rs1801177, PCSK9 rs11591147and APOE rs7412 (by KASPar technique).Results: Individually, risk allele frequencies were not significantly higher in cases than controls (p>0.05) except for APOB rs1042031 and FTO rs9939609 (p=0.007 and 0.003 respectively), and did not associate with CAD except rs1042031 and rs993969 (p=0.01 and 0.009 respectively). However, the GRS of 21 SNPs was significantly higher in cases than controls (17.53±2.52 vs16.64±2.44, p<0.001) and was associated with CAD risk. CAD risk in the top quintile of GRS was 2.96 (95% CI 1.71-5.13). Atherogenic blood lipid levels showed significant positive association with GRS. Conclusion:The GRS was quantitatively associated with d 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.