Association between ILMN_1726554 (<i>IREB2</i>) expression and the main haplotypes derived from rs1394371, rs13180, and rs950776.

<p>See the first paragraph of legend in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003240#pgen-1003240-g002" target="_blank">Figure 2</a> for explanations. In CTS, the rs950776 was substituted by its proxy rs1948 (r² = 0.96). The original haplotypic association (dark grey bars) was compatible with the effects of three common haplotypes associated with increased <i>IREB2</i> expression, CCT (β = +0.121, p = 1.75 10⁻¹² and β = +0.096, p = 2.40 10⁻²⁵ in CTS and GHS, respectively), CCC (β = +0.205, p = 2.69 10⁻²⁹ and β = +0.118, p = 1.10 10⁻³⁰, resp.) and CTC (β = +0.115, p = 7.87 10⁻¹⁰ and β = +0.059, p = 5.31 10⁻¹⁰, resp.). After adjusting for the best imputed <i>cis</i> eSNP rs12592111 in GHS (light grey), the effect of the CCT and CCC haplotypes were no longer significant (β = −0.026, p = 0.575 and β = +0.011, p = 0.302, respectively) while the effect of the CTC haplotype was barely modified (β = +0.051, p = 2.01 10⁻⁷). The CCT and CCC haplotypes are the only two haplotypes carrying the rs13180-C allele, suggesting that these haplotypes were reflecting an effect of rs13180. This is in accordance with the nearly complete association between rs13180 and the best <i>cis</i> eSNP rs12592111 (r² = 0.96).</p

Association between ILMN_1757379 (<i>OPN1SW</i>) expression and the haplotypes derived from rs1109552, rs4731507, rs4731513, and rs339088.

<p>The top panel shows the results in the discovery cohort CTS and the bottom panel in the replication cohort GHS. Each bar corresponds to the expected mean of gene expression associated with one dose of the corresponding haplotype under the assumption of additive haplotype effects. According to this model, the expression level of an individual is the sum of the levels of his (her) two haplotypes. Haplotype frequencies are indicated under each haplotype label. In CTS, the rs4731507 and rs339088 were substituted by their perfect proxies (r² = 1) rs4283986 and rs339085, respectively. The original haplotypic association (dark grey bars) was due to a unique rare haplotype derived from 4 common htSNPs. This rare haplotype, GGGG, was associated with a strong increase in <i>OPN1SW</i> expression (β = +0.240, p = 8.12 10⁻²⁶ and β = +0.341, p<10⁻³⁰⁷ in CTS and GHS, respectively). After adjusting in GHS for the best imputed <i>cis</i> eSNP rs142976957 (light grey bars), the effect of this rare haplotype was still highly significant (β = +0.208, p = 4.78 10⁻¹³⁵).</p

Association between ILMN_2367638 (<i>CAMKK2</i>) expression and the main haplotypes derived from rs1140886, rs1063843, and rs11065504.

<p>The left panel shows the results in the discovery cohort CTS and the right panel in the replication cohort GHS. Each bar corresponds to the expected mean of gene expression associated with one dose of the corresponding haplotype under the assumption of additive haplotype effects. According to this model, the expression level of an individual is the sum of the levels of his (her) two haplotypes. Haplotype frequencies are indicated under each haplotype label. For ease of presentation, mean expression for the most frequent haplotype in CTS was set to be the same as that observed in GHS. In CTS, the rs11065504 was substituted by its proxy rs3794207 (r² = 0.96). After imputation, the best <i>cis</i> eSNP in GHS was rs11065504 whose allele C was carried by an unique haplotype, TCC, which was associated with increased <i>CAMKK2</i> expression (β = +0.338, p = 9.05 10⁻¹⁵⁶ and β = +0.217, p = 5.69 10⁻¹⁵¹ in CTS and GHS, respectively) compared to the TCT haplotype. In addition, the less common CCG haplotype was associated with an even stronger increase in <i>CAMKK2</i> expression (β = +0.386, p = 5.09 10⁻⁵⁶ and β = +0.269, p = 4.00 10⁻⁵³, resp.).</p

Association between ILMN_1731596 (<i>AP3S2</i>) expression and the main haplotypes derived from rs7173483, rs3803536, and rs1269077.

<p>See the first paragraph of legend in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003240#pgen-1003240-g002" target="_blank">Figure 2</a> for explanations. In CTS, the rs7173483, rs3803536 and rs1269077 were substituted by their corresponding proxies, rs4932145 (r² = 1), rs10520684 (r² = 0.92) and rs1256854 (r² = 0.95), respectively. After imputation, the best <i>cis</i> eSNP in GHS was rs12148357 which was not among the associated htSNPs. Its minor allele was associated with decreased <i>AP3S2</i> expression (β = −0.146; p = 1.59 10⁻⁵⁴). However, in the conditional model adjusting for haplotype effects, its effect was no longer significant (β = −0.022, p = 0.420) suggesting that it was due to LD with haplotypes. The haplotypic association was compatible with the additive effects of three SNPs. The rs7173483-A allele was associated with decreased <i>AP3S2</i> expression (β = −0.147, p = 2.80 10⁻¹⁸ and β = −0.1500; p = 9.50 10⁻¹¹ in CTS and GHS, respectively), as were the rs3803536-G allele (β = −0.052, p = 5.03 10⁻⁴ and β = −0.065, p = 1.75 10⁻⁶, resp.) and the rs1269077-C allele (β = −0.067, p = 2.93 10⁻⁷ and β = −0.066, p = 9.49 10⁻¹⁷, resp.).</p

Association between ILMN_1689088 (<i>COLEC12</i>) expression and the main haplotypes derived from rs9966524, rs9960856, and rs2846666.

<p>See the first paragraph of legend in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003240#pgen-1003240-g002" target="_blank">Figure 2</a> for explanations. In CTS, the rs9966524 and rs2846666 were substituted by their corresponding proxies, rs3932728 (r² = 0.82) and rs2846667 (r² = 0.87). The original haplotypic association (dark grey bars) was due to two haplotypes associated with increased <i>COLEC12</i> expression, the TCA (β = +0.331 p = 3.07 10⁻¹⁰ and β = +0.111, p = 5.83 10⁻⁴, in CTS and GHS, respectively) and the CCA (β = +0.278 p = 5.96 10⁻¹⁸ and β = +0.204, p = 4.19 10⁻⁶⁰, in CTS and GHS, resp.). In GHS, the best imputed <i>cis</i> eSNP was rs11081136 whose minor allele was associated with increased <i>COLEC12</i> expression (β = +0.091, p = 1.02 10⁻²⁶). After adjustment for rs11081136 (light grey bars), the TCA (β = +0.092, p = 2.52 10⁻³) and CCA (β = +0.171, p = 1.39 10⁻⁴⁰) haplotypes were still associated with <i>COLEC12</i> expression. The rs11081136 effect also remained significant (β = +0.061, p = 1.12 10⁻¹³).</p

Overlap of significantly associated rSNPs identified by ASE and GTE.

<p>The percentage of overlapping rSNPs detected by allele-specific expression (ASE) and genotype expression (GTE) analysis is plotted for varying numbers of samples. The top 9536 SNPs from the GTE analysis are compared with the top 38203 SNPs from the ASE analysis, which corresponds to a Bonferroni threshold of p = 0.05 for a GTE sample size of 395 and an ASE sample size of 188. The p-value cut-offs were adapted so that the same SNP top-list sizes were obtained at all sample sizes for both GTE (p-value of 1.17E-7, 1.06E-4, 1.93E-3, 6.12E-3 for n = 395, n = 188, n = 95, and n = 50 respectively) and ASE (p-value of 8.06E-8, 9.35E-5, 4.90E-3 for n = 188, n = 95, and n = 50 respectively). The vertical axes show the percentage of SNPs in the top-lists detected by both GTE and ASE analysis and the horizontal axes show the number of samples analyzed using GTE and ASE, respectively. The percentage overlap is calculated by dividing the number of overlaps with the number of top SNPs in the GTE analysis. In (A), each line shows the effect on the number of overlapping SNPs detected by ASE analysis of a specific sample size when the sample size in GTE analysis was increased. In (B), each line shows the effect on the number of overlapping rSNPs detected by GTE analysis of a specific sample size when the samples size in ASE analysis is increased.</p

The ability of ASE and GTE analysis to detect significantly associated rSNPs at different MAF.

<p>Fractions of rSNPs are shown for different minor allele frequencies (MAF) with significant association signals according to a Bonferroni-corrected p-value of 0.05. Each data point underlying the curves represents the fraction of significant associations within a 1% MAF bin. Sliding 5% MAF window averages are plotted for different sample sizes analyzed by ASE and GTE. Both methods detect a lower fraction of low frequency rSNPs, compared to the fraction of all the SNPs at the same frequency (black line). The ASE method detects a higher fraction of the SNPs (solid lines) with a MAF <15% than GTE (dashed lines) regardless of sample size except for the largest GTE sample set.</p

Large-Scale Gene-Centric Analysis Identifies Novel Variants for Coronary Artery Disease

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