Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.

We conducted a genome-wide association study to identify novel associations between genetic variants and circulating plasminogen activator inhibitor-1 (PAI-1) concentration, and examined functional implications of variants and genes that were discovered. A discovery metaanalysis was performed in 19 599 subjects, followed by replication analysis of genome-wide significant (P < 5 ؋ 10 ؊8 ) single nucleotide polymorphisms (SNPs) in 10 796 independent samples. We further examined associations with type 2 diabetes and coronary artery disease, assessed the functional significance of the SNPs for gene expression in human tissues, and conducted RNA-silencing experiments for one novel association. We confirmed the association of the 4G/5G proxy SNP rs2227631 in the promoter region of SERPINE1 (7q22.1) and discovered genome-wide significant associations at 3 additional loci: chromosome 7q22.1 close to SERPINE1 (rs6976053, discovery P ‫؍‬ 3.4 ؋ 10 ؊10 ); chromosome 11p15.2 within ARNTL (rs6486122, discovery P ‫؍‬ 3.0 ؋ 10 ؊8 ); and chromosome 3p25.2 within PPARG (rs11128603, discovery P ‫؍‬ 2.9 ؋ 10 ؊8 ). Replication was achieved for the 7q22.1 and 11p15.2 loci. There was nominal association with type 2 diabetes and coronary artery disease at ARNTL (P < .05). Functional studies identified MUC3 as a candidate gene for the second association signal on 7q22.1. In summary, SNPs in SERPINE1 and ARNTL and an SNP associated with the expression of MUC3 were robustly associated with circulating levels of PAI-1. (Blood. 2012;120(24):4873-4881)

Coronary artery disease (CAD) has a significant genetic contribution that is incompletely characterized. To complement genome-wide association (GWA) studies, we conducted a large and systematic candidate gene study of CAD susceptibility, including analysis of many uncommon and functional variants. We examined 49,094 genetic variants in ∼2,100 genes of cardiovascular relevance, using a customised gene array in 15,596 CAD cases and 34,992 controls (11,202 cases and 30,733 controls of European descent; 4,394 cases and 4,259 controls of South Asian origin). We attempted to replicate putative novel associations in an additional 17,121 CAD cases and 40,473 controls. Potential mechanisms through which the novel variants could affect CAD risk were explored through association tests with vascular risk factors and gene expression. We confirmed associations of several previously known CAD susceptibility loci (eg, 9p21.3:p<10−33; LPA:p<10−19; 1p13.3:p<10−17) as well as three recently discovered loci (COL4A1/COL4A2, ZC3HC1, CYP17A1:p<5×10−7). However, we found essentially null results for most previously suggested CAD candidate genes. In our replication study of 24 promising common variants, we identified novel associations of variants in or near LIPA, IL5, TRIB1, and ABCG5/ABCG8, with per-allele odds ratios for CAD risk with each of the novel variants ranging from 1.06–1.09. Associations with variants at LIPA, TRIB1, and ABCG5/ABCG8 were supported by gene expression data or effects on lipid levels. Apart from the previously reported variants in LPA, none of the other ∼4,500 low frequency and functional variants showed a strong effect. Associations in South Asians did not differ appreciably from those in Europeans, except for 9p21.3 (per-allele odds ratio: 1.14 versus 1.27 respectively; P for heterogeneity = 0.003). This large-scale gene-centric analysis has identified several novel genes for CAD that relate to diverse biochemical and cellular functions and clarified the literature with regard to many previously suggested genes.

Objective: Obesity and insulin resistance are major risk factors for metabolic diseases and are influenced by lifestyle and genetics. The lipogenic enzyme, stearoyl-coenzyme Adesaturase (SCD), is related to obesity. Further, SCD1-deficent mice are protected against obesity and insulin resistance. We hypothesized that genetic polymorphisms in the SCD1 gene would be associated with obesity, insulin sensitivity, and estimated SCD activity in humans. Research Methods and Procedures:The study population was 1143 elderly Swedish men taking part of a populationbased cohort study, the Uppsala Longitudinal Study of Adult Men. Associations between single nucleotide polymorphisms and obesity (waist circumference and BMI), insulin sensitivity (assessed by hyperinsulinemic euglycemic clamp), and estimated SCD activity (fatty acid ratios) were analyzed using linear regression analysis. Results: Subjects homozygous for the rare alleles of rs10883463, rs7849, rs2167444, and rs508384 had decreased BMI and waist circumference and improved insulin sensitivity. The rare allele of rs7849 demonstrated the strongest effect on both insulin sensitivity [regression coefficient (␤) ϭ 1.19, p ϭ 0.007] and waist circumference (␤ ϭ Ϫ4.4, p ϭ 0.028), corresponding to 23% higher insulin sensitivity and 4 cm less waist circumference. Conclusion:This study indicates that genetic variations in the SCD1 gene are associated with body fat distribution and insulin sensitivity, results that accord well with animal data. These results need confirmation in other populations with a larger sample size.