Abtehale Al-Hussaini

The South Asian genome.

The genetic sequence variation of people from the Indian subcontinent who comprise one-quarter of the worlds population, is not well described. We carried out whole genome sequencing of 168 South Asians, along with whole-exome sequencing of 147 South Asians to provide deeper characterisation of coding regions. We identify 12,962,155 autosomal sequence variants, including 2,946,861 new SNPs and 312,738 novel indels. This catalogue of SNPs and indels amongst South Asians provides the first comprehensive map of genetic variation in this major human population, and reveals evidence for selective pressures on genes involved in skin biology, metabolism, infection and immunity. Our results will accelerate the search for the genetic variants underlying susceptibility to disorders such as type-2 diabetes and cardiovascular disease which are highly prevalent amongst South Asians.

114 Whole genome sequencing to identify genetic variants underlying cardiovascular disease among Indian Asians

Introduction Indian Asians have a twofold higher risk of cardiovascular disease compared to Europeans which is not explained by conventional cardiovascular risk factors or known genetic variants. The genetic architecture of Indian Asians has not previously been described. We hypothesised that whole genome sequencing of Indian Asians may identify both common and rare variants specific to this population that contribute to their increased cardiovascular disease risk. Methods We carried out whole genome sequencing (mean depth 28.4×) in eight men of Indian Asian origin participating in the London Life Sciences Population (LOLIPOP) study. Sequencing was carried out using paired end and mate pair libraries on an Illumina GA2 machine. Read alignment was done by BWA, and variants called using GATK and SAMtools. Sensitivity for single nucleotide polymorphism (SNP) detection was assessed by comparison to whole genome data. Results We identified 6 602 840 autosomal variants, 436 823 of which are novel SNPs. Of these, 50 585 appear to be common (present at least twice, corresponding to minor allele frequency >10%). We found 21 659 autosomal SNPs that were expected to affect protein coding, of which 2174 are novel. Among the coding SNPs identified, 145 are in genes linked to human diseases, such as obesity (FTO, UCP1), diabetes mellitus (CDKAL1, GCGR, HNF1B), lipid metabolism (APOB), hypertension (NOS2), and renal disease (NPHP4, PKD1). We also found 65 613 novel autosomal indels of which 35 097 are present at least twice, and 2301 novel deletions >100 bp. We show that >50% of the novel genetic variants are not in high LD (r2¡Ý0.8) with tag SNPs and hence not captured on available high-density microarrays. Conclusions We identify more than 500 000 genetic variants not previously reported in 1000 genomes or dbSNP, and likely to be Indian Asian specific. The novel variants identified here are strong candidates for genetic factors underlying the increased risk of diabetes and cardiovascular disease among Indian Asians.

DRUG-ELUTING STENTS VERSUS BARE METAL STENTS IN PATIENTS WITH ST-ELEVATION MYOCARDIAL INFARCTION UNDERGOING PRIMARY PERCUTANEOUS CORONARY INTERVENTION

In primary percutaneous coronary intervention (PPCI) for ST-segment elevation myocardial infarction (STEMI), the relative safety of drug-eluting stents (DES) versus bare metal stents (BMS) continues to be debated. Whilst DES use is associated with reduced target lesion revascularization rates, stent

151 Nuclear magnetic resonance profiling of serum identifies novel biomarker associated with coronary atherosclerosis

Introduction Coronary heart disease (CHD) is the leading cause of death worldwide. Current CHD risk prediction tools do not accurately identify risk of CHD in all populations. There is an urgent need for discovery of novel biomarkers to help understand mechanisms underlying CHD and improve risk functions to identify people at increased risk. We used serum metabonomic nuclear magnetic resonance (NMR) profiling to identify biomarkers associated with the presence of coronary artery calcification (CAC), a quantitative measure of coronary atherosclerosis. Methods We investigated 2358 men and women aged 35–75 years participating in the London Life Sciences Population (LOLIPOP) Study. Participants with prior history of CHD were excluded. All participants completed a structured health questionnaire, underwent physical assessment and had blood collected after an 8 h fast. CAC was quantified using electron beam CT. Quantitative NMR spectroscopy was used to characterise serum samples for lipoproteins, fatty acids and low molecular weight markers. Linear regression was used to determine the relationship between metabolites and Agatston score. Statistical significance was inferred at p<0.0013, corresponding to a Bonferroni correction for 39 primary NMR measures. Results CAC was associated with older age, male gender, cigarette smoking, raised systolic and diastolic blood pressure, obesity and hypercholesterolaemia. Among the 39 NMR measures, 11 were associated with CAC after adjustment for age, sex and ethnicity (p=0.0013 to p=5.0×10−12). In multivariate analysis, after further adjustment for conventional risk factors, we identified an association of the metabonomic biomarker (an abundant naturally occurring non-essential amino acid) with coronary artery calcium (p=7.9×10−4). The OR for the presence of significant coronary atherosclerosis (CAC>100) was 2.21 (95% CI 1.59 to 3.07, p=2.2×10−6) among people in the lowest quartile for the novel metabolite, compared to those in the highest quartile, implying that lower levels of the metabonomic biomarker confers increased CHD risk. Conclusions Using NMR spectroscopy, we have identified a novel metabonomic biomarker to be independently associated with CAC, a measure of coronary atherosclerosis. Further testing in large prospective cohorts is required to evaluate the predictive value of this novel metabonomic biomarker to CHD.