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Genome-Wide Association Identifies a Susceptibility Locus for Coronary Artery Disease in the Chinese Han Population
Supplementary Materials
Fan Wang1,13, Chengqi Xu1,13, Qing He2,13, Jianping Cai2,13, Xiuchun Li1,13, Dan Wang1,13, Xin
Xiong1,13, Yuhua Liao3,13, Qiutang Zeng3,13, Xiang Cheng3,13, Yanzong Yang4,13, Cong Li1, Rong
Yang1, Chuchu Wang1, Gang Wu5, Qiulun Lu1, Ying Bai1, Yufeng Huang1, Dan Yin1, Qing Yang1,
Xiaojing Wang1, Dapeng Dai2, Rongfeng Zhang4, Jing Wan6, Jianghua Ren6, Sisi Li1, Yuanyuan
Zhao1, Fenfen Fu1, Yuan Huang1, Qingxian Li7, Shengwei Shi7, Nan Lin7, Zhenwei Pan8, Yue Li9,
Bo Yu10, Yanxia Wu11, Yuhe Ke11, Jian Lei11, Nan Wang1, Chunyan Luo1, Liying Ji1, Lianjun Gao4,
Lei Li1, Hui Liu1, Erwen Huang1, Jin Cui1, Xiang Ren1, Hui Li1, Tie Ke1, Xianqin Zhang1, Jingyu
Liu1, Mugen Liu1, Hao Xia5, Bo Yang5, Lisong Shi1, Yunlong Xia4, Xin Tu1,* & Qing K. Wang1,12,*
1Key Laboratory of Molecular Biophysics of the Ministry of Education, Cardio-X Institute, College
of Life Science and Technology and Center for Human Genome Research, Huazhong University of
Science and Technology, Wuhan, P. R. China 2Beijing Hospital, Ministry of Health, Beijing, P. R. China 3Institute of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science
and Technology, Wuhan, P. R. China 4First Affiliated Hospital of Dalian Medical University, Dalian, P. R. China 5Renmin Hospital of Wuhan University, Wuhan, P. R. China
6Zhongnan Hospital of Wuhan University, Wuhan, P. R. China 7Affiliated Hospital of Jining Medical Collage, Shandong, P. R. China 8Department of Pharmacology, Harbin Medical University, Harbin, P. R. China 9The First Affiliated Hospital, Harbin Medical University, Harbin, P. R. China 10The Second Affiliated Hospital, Harbin Medical University, Harbin, P. R. China 11The First Hospital of Wuhan City, Wuhan, P. R. China 12Center for Cardiovascular Genetics, Cleveland Clinic, Cleveland, Ohio, USA 13These authors contributed equally to this work.
*Correspondence should be addressed to Q.K.W. ([email protected]) or X.T.
Nature Genetics: doi.10.1038/ng.783
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Supplemental Data Notes
Supplementary Figure 1 A genome-wide association study in the Chinese Han population
Supplementary Figure 2 Pairwise linkage disequilibrium (LD) analysis for chromosome 9p21
SNPs associated with risk of CAD
Supplementary Figure 3 Genomic structure and expression profile of C6orf105 and LD
analysis of SNPs in the region of C6orf105
Supplementary Figure4 Analysis of 113 SNPs in and close to the PHACTR1 gene on
chromosome 6p24 for association with CAD
Supplementary Table 1 Summary of GWAS results for SNPs with P < 0.01 in both discovery populations and assessment of their association with CAD in additional populations Supplementary Table 2 Analysis of genotypic association of between SNP rs6903956 and CAD under different genetic models in three stage 3 replication populations
Supplementary Table 3 Analysis of association between SNP rs6903956 and the known risk
factors for CAD
Supplementary Table 4 Primers used in real time PCR analysis for C6orf105 and β-actin
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Supplementary Figure 1 A genome-wide association study in the Chinese Han population. (a) Overall study design of GWAS. (b) Quantile-Quantile (QQ) plots for the two discovery populations.
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Construction of Quantile-Quantile (QQ) plots for the two discovery populations, Dis-Hubei (the left panel) and Dis-Beijing (the right panel). For the SNPs that passed standard project filters (MAF ≥0.01, PHWE≥0.001, missing genotyping rate ≤0.1), QQ plots were constructed using SAS (version 8.1) by ranking a set of values of a statistic (Chi-square values) from smallest to largest and plotting them against their expected values, given the assumption that the values have been sampled from a known theoretical distribution (Chi-square distribution, one degree of freedom). Deviations from the line of equality indicate either the incorrect theoretical form or the true association. (c) Strategy for selection of SNPs from the stage 1 discovery phase of GWAS. The –Log10(P) values from Dis-Beijing were plotted on the vertical axis and the –Log10(P) values from Dis-Hubei were on the horizontal axis. Only SNPs showing P values of <0.01 (–Log10(P) =2) in both Dis-Beijing and Dis-Hubei were selected for stage 2 validation and stage 3 replication studies. SNPs with a P value larger than 0.05 (-Log10(P)<1.3) were not shown.
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Supplementary Figure 2 Pairwise linkage disequilibrium (LD) analysis for chromosome 9p21 SNPs associated with risk of CAD. (a) LD analysis for SNPs rs1333048 and rs1333049 on chromosome 9p21 using the genotyping data from the two discovery populations from our GWAS, Dis-Hubei at the top panel and Dis-Beijing at the bottom panel. LD is indicated by the R2 value in each diamond. The red-to-white color gradient shows the degree of LD (D’ value) from high-to-low values. D’=1.00 and 0.98 for Dis-Hubei and Dis-Beijing, respectively; r2=0.98 and 0.95 for
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Dis-Hubei and Dis-Beijing, respectively. (b) LD characteristics for chromosome 9p21 SNPs that are associated with CAD, including rs1333048 and rs1333049 identified by GWAS in this study and rs10757274, rs2282206, rs2383207, and rs10757278 which were found by GWAS in populations of European ancestry. The graph was generated using SNAP (SNP Annotation and Proxy Search, http://www.broadinstitute.org/mpg/snap) using the GWAS genotyping data for CHB and JPT populations from the HapMap database (http://hapmap.ncbi.nlm.nih.gov/, 1000 Genomes Pilot 1). The R2 values are shown at the left vertical axis, and the recombination rates among the SNPs are shown using green lines (the right vertical axis). The pairwise R2 values among the GWAS SNPs, including rs1333048, rs1333049, rs10757274, rs2282206 and rs10757278 are from 0.93 to 1.00, indicating that they are in the same LD block.
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Supplementary Figure 3 Genomic structure and expression profile of C6orf105 and LD analysis of SNPs in the region of C6orf105. (a) Schematic diagram showing the structure of the C6orf105 gene and location of SNP rs6903956 associated with CAD. (b) Analysis of expression of C6orf105 in the stomach, heart, kidney, skin, leukocytes, HeLa cells, and HepG2 cells by RT-PCR analysis. (c) LD analysis among the SNPs in the region of SNP rs6903956 using the GWAS genotyping data from the two discovery cohorts for GWAS, Dis-Hubei at the top panel and Dis-Beijing at the bottom panel. SNP rs6903956 is indicated by a red square box. LD is indicated by the R2 value in each diamond. The red-to-white color gradient shows the degree of LD (D’ value) from high-to-low values. Note that SNP rs6903956 does not form LD with any other SNPs. The same results were obtained from the genotyping data from the HapMap database.
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Supplementary Figure 4 Analysis of 113 SNPs in and close to the PHACTR1 gene on chromosome 6p24 for association with CAD. The (-log10(P)) values in the two discovery cohorts for GWAS, Dis-Hubei at the top panel and Dis-Beijing at the bottom panel (indicated by squares), are shown at the left vertical axis. The recombination rates among the SNPs are shown using green lines (the right vertical axis). The graph was generated using SNAP (SNP Annotation and Proxy Search, http://www.broadinstitute.org/mpg/snap).
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Supplementary Table 1 Summary of GWAS results for SNPs with P < 0.01 in both discovery populations and assessment of their association with CAD in additional populations a. Analysis of association of 9 SNPs with CAD in discovery populations
Chr SNP Risk
allele
Discover
set
Risk allele
frequency
Case/Control
Pobs PGC OR (95%CI) Gene
in the region
Dic-Hubei 0.80/0.69 8.00×10-3 9.00×10
-31.85 (1.18-2.9)
1p31.3 rs1712246
0 G
Dis-Beijing 0.76/0.65 9.00×10-3 0.01 1.67 (1.14-2.44)
NF1-A
Dic-Hubei 0.43/0.31 9.00×10-3 0.01 1.73 (1.14-2.61)
2p25.3 rs7563810 T Dis-Beijing 0.51/0.34 1.00×10
-4 2.00×10
-41.99 (1.40-2.84)
TSSC1
Dic-Hubei 0.10/0.04 8.00×10-3 0.01 3.07 (1.27-7.45)
6p24.1 rs6903956 A Dis-Beijing 0.15/0.06 2.00×10
-3 2.00×10
-32.59 (.41-4.78)
C6orf105
Dic-Hubei 0.42/0.28 7.00×10-3 7.00×10
-31.80 (1.18-2.76)
6q21 rs2179118 A Dis-Beijing 0.46/0.35 9.00×10
-3 0.01 1.60 (1.12-2.28)
U6 spliceosomal RNA
Dic-Hubei 0.57/0.41 1.00×10-3 2.00×10
-31.93 (1.29-2.89)
9p21.3 rs1333048 G Dis-Beijing 0.54/0.41 5.00×10
-3 6.00×10
-31.65 (1.16-2.33)
Dic-Hubei 0.58/0.40 6.00×10-4 7.00×10
-42.00 (1.34-2.99)
9p21.3 rs1333049 C Dis-Beijing 0.54/0.43 8.00×10
-3 9.00×10
-31.60 (1.13-2.26)
ANRIL
Dic-Hubei 0.41/0.27 5.00×10-3 5.00×10
-31.83 (1.19-2.82)
9q31.3 rs2229594 G Dis-Beijing 0.38/0.27 9.00×10
-3 0.01 1.64 (1.13-2.39)
BAT
Dic-Hubei 0.68/0.56 5.00×10-3 6.00×10
-31.79 (1.19-2.70)
16q12.1 rs9925751 C Dis-Beijing 0.65/0.53 7.00×10
-3 9.00×10
-31.61 (1.14-2.33)
7SK RNA
Dic-Hubei 0.95/0.86 4.00×10-3 4.00×10
-32.94 (1.37-6.25)
22q12.1 rs1072967 C Dis-Beijing 0.96/0.87 1.00×10
-3 1.00×10
-33.33 (1.61-7.14)
TTC28
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b. Assessment of the association between SNPs rs17122460, rs7563810, rs6903956, rs2179118, rs1333048, rs2229594, and rs9925751 selected from the discovery phase and CAD in stage 2 validation population
Chromosome SNP Risk allele Risk allele frequency Case/Control PHWE Pobs OR(95%CI)
1p31.3 rs17122460 G 0.72/0.71 0.91 0.79 1.03(0.84-1.24) 2p25.3 rs7563810 C 0.65/0.61 0.92 0.04 1.20(1.01-1.47) 6p24.1 rs6903956 A 0.08/0.05 0.64 5.00×10-3 1.71(1.18-2.48) 6q21 rs2179118 G 0.58/0.58 0.27 0.93 0.99(0.83-1.19) 9p21.3 rs1333048 G 0.59/0.53 0.18 4.00×10-3 1.29(1.09-1.56) 9q31.3 rs2229594 G 0.38/0.36 0.06 0.43 1.08(0.89-1.30) 16q12.1 rs9925751 T 0.42/0.42 0.69 0.79 1.02(0.85-1.23) c. Significant association between SNP rs1333048 on chromosome 9p21 and CAD
Without adjustment After adjustment Population
(n, case/control)
G allele
Frequency
Case /Control
PHWE Pobs OR (95%CI) Padj OR (95%CI)
Rep-Shandong(811 /818) 0.57/0.51 0.85 2.00×10-3 1.28 (1.09-1.49) 1.00×10-3 1.34 (1.13-1.59)
Stage 2 validation population
+ Rep-Shandong(1,383/1,254) 0.59/0.52 0.70 4.57×10-6 1.32 (1.17-1.48) 4.11×10-5 1.30 (1.14-1.47)
PHWE: P value from Hardy-Weinberg equilibrium tests; Pobs, P values without any adjustment; PGC, P values after adjustment using genomic control corrected; Padj: P value after adjustment for covariates; OR, odds ratio; CI, confidence interval.
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Supplementary Table 2 Analysis of genotypic association of between SNP rs6903956 and CAD under different genetic models in three stage 3 replication populations
HT, hypertension; Tch, total plasma cholesterol level; TG, plasma triglyceride level; HDL, plasma HDL-cholesterol level; LDL, plasma LDL- cholesterol level.
Population (n, case/control) Model Pobs Padj O R (95% CI)
Additive 1.20×10-2 1.30×10-2 1.41 (1.07-1.85)
Dominant 6.00×10-3 2.60×10-2 1.39 (1.04-1.86) Rep-Shandong population (811 cases / 818 controls)
Recessive 7.90×10-2 7.60×10-2 3.65 (0.87-15.29)
Additive 1.08×10-7 3.66×10-8 1.74 (1.43-2.11)
Dominant 9.99×10-7 8.97×10-7 1.74 (1.39-2.17) Rep-Hubei population (1012 cases / 1732 controls)
Recessive 4.57×10-5 7.13×10-5 4.45 (2.13-9.31)
Additive 7.00×10-3 1.00×10-3 1.94 (1.29-2.91)
Dominant 2.00×10-3 1.00×10-3 2.02 (1.32-3.09) Rep-North population (845 cases / 1,367 controls)
Recessive 0.95 0.54 1.96 (0.23-17.03)
Additive 6.96×10-11 6.54×10-13 1.63 (1.43-1.87)
Dominant 1.54×10-10 2.08×10-11 1.64 (1.42-1.90) Combined stage 2 and stage 3 population (3,240 cases /4,353 controls)
Recessive 1.45×10-4 3.53×10-5 3.53 (1.97-6.33)
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Supplementary Table 3 Analysis of association between SNP rs6903956 and the known risk factors for CAD
For HT, P values were calculated using multivariate logistic regression adjusted for sex, age, Tch, TG, HDL, and LDL. For Tch, TG, HDL, or LDL, P values were calculated using multivariate linear regression adjusted for sex, age, diabetes, smoking, and other lipid levels.
Supplementary Table 4 Primers used in real time PCR analysis for C6orf105 and β-actin Primer Sequence
C6orf105-Forword 5'- CCT GGA TGA TGT GCT GAA AAG AAC -3'
C6orf105-Reverse 5'- AGG ATC CAG AAT GCC AAA AAT ACA -3'
β-actin- Forword 5'- GGA CTT CGA GCA GGA GAT GG -3'
β-actin -Reverse 5'- GCA CCG TGT TGG CGT AGA GG -3'
Allele A of SNP rs6903956 Pobs Effect (95% CI) Padj Effect (95% CI)
HT 0.08 0.920 (0.810-1.030) 0.11 0.906 (0.803-1.203) Tch 0.04 0.076 (0.004-0.148) 0.74 0.008 (-0.037-0.052) TG 0.18 0.047 (-0.022-0.116) 0.56 0.020 (-0.046-0.085) HDL 0.38 0.011 (-0.014-0.036) 0.10 0.018 (-0.003-0.040) LDL 0.05 0.064 (-0.001-0.130) 0.33 0.022 (-0.022-0.066)
Nature Genetics: doi.10.1038/ng.783