- Open Access
Associations of lipid levels susceptibility loci with coronary artery disease in Chinese population
© Wang et al. 2015
- Received: 10 February 2015
- Accepted: 10 July 2015
- Published: 25 July 2015
Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) that were associated with blood lipid levels in Caucasians. This study investigated whether these loci influenced lipid levels and whether they were associated with the risk of coronary artery disease (CAD) and its angiographic severity in Chinese population.
Six SNPs were genotyped in 1100 CAD cases and 1069 controls using the high-resolution melting (HRM) method. Coronary atherosclerosis severity was assessed by the vessel scores and the Gensini scoring system.
Among the 6 SNPs and the genetic risks scores (GRS), the minor alleles of HNF1A rs1169288 (odd ratio (OR) = 1.18, 95 % confidence interval (CI) 1.05–1.33, P = 0.006) and MADD-FOLH1 rs7395662 (OR = 1.20, 95 % CI 1.07–1.36, P = 0.002) as well as the GRS (P = 1.06 × 10-5) were significantly associated with increased risk of CAD after false discovery rate (FDR) correction. The vessel (P = 0.013) and Gensini scores (β = 0.113, P = 0.002) differed among CAD patients with different SNP rs1169288 C > T genotypes. The multiple linear regression analyses using an additive model revealed that the minor allele C of SNP rs1169288 (β = 0.060, P = 0.001) and the GRS (β = 0.033, P = 3.59 × 10-4) were significantly associated with increased total cholesterol (TC) levels, the minor allele A of SNP rs7395662 (β = -0.024, P = 0.007) and the GRS (β = -0.013, P = 0.004) were significantly associated with decreased high-density lipoprotein cholesterol (HDL-c) levels.
The present study demonstrated that SNPs rs1169288, rs7395662 and the GRS were significantly associated with lipid levels and the risk of CAD in Chinese population. Furthermore, the allele C of SNP rs1169288 increased the odds of coronary atherosclerosis severity.
- Coronary artery disease
- HNF1A rs1169288
- MADD-FOLH1 rs7395662
- Gensini scores
Coronary artery disease (CAD), one of the most common cardiovascular disease , is associated with high morbidity and mortality and remains one of the most common causes of death globally . A main underlying pathology of CAD is atherosclerosis, a process of cumulative deposition of lipoproteins in the arteries supplying blood to the heart that eventually leads to impaired or absent blood supply and myocardial infarction (MI) . Atherosclerosis has numerous genetic and environmental risk factors , and abnormalities of plasma lipids and lipoproteins are heritable risk factors for CAD, with heritability estimates ranging from 40–60 % for total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c) and 30–60 % for CAD . Recently, independent genome-wide association studies (GWAS) have identified several loci that influence blood lipid levels and CAD risk in Caucasians [6–11]. However, the associations between these novel single nucleotide polymorphisms (SNPs), lipid levels and the risk of CAD were not well established in Chinese population. Otherwise, few studies have examined the utility of genetic risk scores (GRS) to identify Chinese subjects at increased CAD risk [12, 13].
The locus rs7395662 on chromosome 11p11.2, was first identified as a strongly lipid-associated locus according to a GWAS in Caucasians . This study also identified SNP rs12670798 as a novel lipid-associated locus located in intron of the dynein axonemal heavy chain 11 (DNAH11) gene . SNP rs9411489, which is located 4.3 kb downstream of the ABO blood group (ABO) gene, was also found to be associated with lipid levels in a GWAS of Europeans . Then a large-scale association analysis in individuals of European descent identified the following three variants associated with lipid levels and CAD risk: SNPs rs1169288, rs1495741 and rs10128711, which located in or near the hepatocyte nuclear factor 1-α (HNF1A) gene, N-acetyltransferase 2 (NAT2) gene and SPT2, Suppressor of Ty, domain containing 1 (SPTY2D1) gene, respectively .
In this study, we aimed to examine the associations of these 6 lipid-associated variants (individually and in combination) with lipid levels and CAD risk in Chinese population. Additionally, a cross-sectional study on the associations between these six SNPs and the severity of coronary atherosclerosis has been conducted.
Study participants were recruited from Zhongnan hospital of Wuhan University and Asia Heart Hospital between January 2011 and October 2014. The present case–control study involved 1100 CAD cases and 1069 non-CAD controls. CAD cases were diagnosed based on ≥ 50 % luminal stenosis in at least one major coronary arteries or their major branches by standard coronary angiography. Non-CAD controls were the subjects without detectable stenosis by coronary angiography and healthy population controls without diagnosis of CAD, hypertension and diabetes mellitus (DM) by routine physical examinations. Otherwise, to assess the effects of these six SNPs on lipid levels in our control group, subjects who were undergoing lipid-lowering medication or dyslipidemia were also excluded from the controls.
Fasting concentrations of the plasma glucose, C-reactive protein (CRP), TC, TG, LDL-c and HDL-c were measured using standard methods . Other clinical data collected from study participants included age, sex, history of smoking, alcohol intake, body mass index (BMI), weight status (overweight and obesity status), hypertension, diabetes mellitus, dyslipidemia and pharmacological therapy (including lipid/glucose/blood pressure lowering drug treatment) status. BMI was defined as weight divided by height in square meters (kg/ m2). Overweight and obesity were defined as BMI ≥ 25 and ≥ 30, respectively . Hypertension was diagnosed based on usage of ongoing therapy for hypertension, systolic blood pressure (SBP) of ≥ 140 mmHg or diastolic blood pressure (DBP) of ≥ 90 mmHg . DM was defined as ongoing therapy for diabetes or fasting plasma glucose (FPG) levels of ≥ 7.0 mmol/L, or with plasma glucose levels of ≥ 11.1 mmol/L . This study was approved by ethnics committee of Zhongnan hospital of Wuhan University and met the declaration of Helsinki.
Scoring of coronary angiogram
Coronary angiograms were scored according to the vessel and Gensini scores. The vessel scores were defined as the number of vessels having ≥ 50 % stenosis. In the Gensini scoring system , the narrowing of the coronary artery lumen is scored 1 for 0–25 % stenosis, 2 for 26–50 %, 4 for 51–75 %, 8 for 76–90 %, 16 for 91–99 % and 32 for 100 %. Each stenosed segment was then weighted from 0.5 to 5, depending on the functional significance of the area supplied by that segment. These scores were multiplied by the coefficient defined for each coronary artery and segment, and the results were then summed.
The scores were independently assessed by two experienced interventional cardiologists who were blinded to the procedural data and clinical outcomes. The κ for inter-observer variability that was used to estimate the vessel and Gensini scores were 0.98, 0.88, respectively, whereas the κ for intra-observer variability that were 0.99, 0.93, respectively. Any disagreements regarding the scores were resolved by consensus.
SNP selection and genotyping
Characteristics of 6 SNPs in our study
HWE (P value)
Continuous variables with normal distribution were expressed as mean ± SD, and differences between groups were compared by the Student’s t-tests. Variables with skewed distributions were ln-transformed before analyses. Categorical variables were represented as percentages and were tested by the χ 2 tests, which were also used to test for deviation of genotype distributions from Hardy-Weinberg equilibrium (HWE) .
In the case–control analyses, the allele frequencies in cases and controls were compared using the χ 2 tests. The genotypic associations of 6 SNPs with CAD risk were assessed by the logistic regression analyses under different models of inheritance (additive, recessive and dominant) after adjusting for age, sex, smoking, alcohol intake, weight status, hypertension, type 2 diabetes, dyslipidemia and pharmacological therapy covariates. The weighted GRS of CAD were the weighted sum across three significant (uncorrected) SNPs (rs1169288, rs7395662 and rs1495741) combining the odds ratios (ORs) and doses of risk alleles based on an additive model [22, 23]. The effects of SNPs on plasma lipid levels were assessed by the multiple linear regression analyses under an additive model. The weighted GRS of lipid levels were also assessed as the sum of doses of the risk alleles weighted by the β coefficients at the polymorphisms [24, 25]. For CAD cross-sectional study, the vessel scores were compared among the genotypes of six SNPs using the linear-by-linear association χ 2 test and the χ 2 test. Otherwise, the associations between the Gensini scores and six SNPs were assessed by treating the Gensini scores as quantitative traits (the multiple linear regression) and using median case–control methods (the logistic regression) [26, 27]. Using the false discovery rate (FDR) method , multiple testing correction for the associations with lipid levels, CAD risk and coronary atherosclerosis severity were conducted separately. The P FDR value was calculated by multiplying its P value by the number of tests performed and then divided by the rank order of each P value (where rank order 1 is assigned to the smallest P value). An FDR of 0.05 was used as a critical value to assess whether PFDR value was significant.
Statistical analyses were conducted by SPSS 17.0 (SPSS, Inc., Chicago, Illinois, USA). Power analysis was carried out using Power and Sample Size Program 3.0 (Vanderbilt University, Nashville, TN, USA).
Characteristics of the study population
Clinical characteristics of participants in the case–control study
CAD patients (n = 1100)
Controls (n = 1069)
59.9 ± 8.7
59.4 ± 9.3
Male, n (%)
Current smoking, n (%)
Alcohol intake, n (%)
24.0 ± 3.23
23.1 ± 3.35
Overweight, n (%)
Obesity, n (%)
Hypertension, n (%)
DM, n (%)
Hyperlipidemia, n (%)
Antihypertensive treatment, n (%)
Glucose-lowering treatment, n (%)
Lipid-lowering treatment, n (%)
4.32 ± 1.03
4.03 ± 0.42
1.53 ± 1.01
1.05 ± 0.36
2.78 ± 1.04
2.74 ± 0.26
1.22 ± 0.20
1.27 ± 0.22
4.54 ± 7.45
1.15 ± 1.78
22.3 (21.2, 23.5)
Associations with lipid levels
Associations of 6 SNPs with lipid levels in 1069 healthy control subjects
3.59 × 10 -4
2.76 × 10 -4
Associations with the risk of CAD
Allelic and genotypic associations of 6 SNPs with CAD risk in our case–control study
OR (95 % CI)
OR (95 % CI)
OR (95 % CI)
OR (95 % CI)
1.18 (1.05, 1.33)
1.25 (1.06, 1.45)
1.45 (1.13, 1.86)
1.22 (0.93, 1.61)
C vs A
1.20 (1.07, 1.36)
1.22 (1.05, 1.43)
1.50 (1.15, 1.97)
1.18 (0.91, 1.52)
A vs G
1.15 (1.02, 1.30)
1.16 (0.99, 1.36)
1.09 (0.82, 1.45)
1.31 (1.03, 1.66)
G vs A
1.08 (0.96, 1.22)
1.07 (0.92, 1.25)
1.19 (0.97, 1.47)
1.13 (0.87, 1.46)
T vs C
0.96 (0.83, 1.11)
0.98 (0.84, 1.15)
1.00 (0.83, 1.20)
0.97 (0.64, 1.49)
T vs C
1.04 (0.92, 1.17)
1.05 (0.92, 1.21)
1.09 (0.88, 1.36)
1.05 (0.85, 1.31)
C vs T
To explore the potential inheritance patterns, three models of inheritance including additive, dominant and recessive models were explored for each SNP (Table 4). Results from the logistic regression analyses indicated that SNPs rs1169288 and rs7395662 were significantly associated with the risk of CAD under both additive (OR = 1.25, 95 % CI = 1.06–1.45, P = 0.008, PFDR = 0.033 for SNP rs1169288; OR = 1.22, 95 % CI = 1.05–1.43, P = 0.012, PFDR = 0.043 for SNP rs7395662) and dominant models (OR = 1.45, 95 % CI = 1.13–1.86, P = 0.004, PFDR = 0.025 for SNP rs1169288; OR = 1.50, 95 % CI = 1.15–1.97, P = 0.003, PFDR = 0.025 for SNP rs7395662) after adjusting for age, sex, current smoking, alcohol intake, weight status, hypertension, type 2 diabetes, dyslipidemia and pharmacological therapy covariates. Significant genotypic association was identified between SNP rs1495741 and CAD risk under a recessive model (OR = 1.31, 95 % CI = 1.03–1.66, P = 0.029), but it was not sufficient robust to withstand the FDR correction (PFDR = 0.081). Associations between other three SNPs and CAD risk were not significant in neither allelic nor genotypic association analyses.
Associations of 6 SNPs with the vessel scores in the 1100 CAD patients
Diseased vessel scores (%)
χ 2 test
Linear-by- linear χ 2 test
χ 2 value
χ 2 value
Associations of 6 SNPs with the ln-transformed Gensini socre in the 1100 CAD patients under additive model
SNP (risk allele)
Quantitative trait association
Median case–control associationa
Risk allele frequency (%)
OR (95 % CI)
1.30 (1.09, 1.53)
0.98 (0.82, 1.16)
1.10 (0.93, 1.31)
1.06 (0.89, 1.26)
1.05 (0.86, 1.29)
0.89 (0.75, 1.05)
In this study, we have demonstrated that two SNPs (HNF1A rs1169288, MADD-FOLH1 rs7395662) and the GRS were associated with lipid levels in Chinese population. The present study also indicated that these two SNPs and the GRS were associated with CAD risk after correction for multiple testing, and this is the first investigation demonstrating that SNP rs1169288 was significantly associated with the angiographic severity of coronary atherosclerosis.
SNP rs7395662 on chromosome 11p11.2 showed reliable evidence for associations with HDL-c levels and the risk of CAD in our study, which was consistent with the results from previous GWAS in Caucasians . However, another association study including 727 Guangxi Han population demonstrated that this locus was significantly associated with TC, TG, HDL-c and LDL-c levels . To our knowledge, the frequencies of G allele in the Guangxi Han subjects were significant lower than those in our Hubei control subjects (43.7 % vs 51.9 %) and also much lower than those in the HapMap CHB database (43.7 % vs 56.5 %), suggesting that the Chinese population may not be genetically similar. Apart from genetic background, such as sample size and different statistical method, may also contribute to the discrepancies among our study and other studies in Chinese population. The role that this SNP might play in lipoprotein metabolism is still unclear now. SNP rs7395662 is assigned as MADD-FOLH1 locus of chromosome 11p, and the two genes flanking the locus, MAP-kinase activating death domain (MADD) gene and folate hydrolase 1 (FOLH1) gene have not been implicated in lipid metabolism. However, the liver X receptors alpha variant 1 (LXRA) gene, an orphan member of the nuclear receptor that regulate pathways central to lipid homeostasis [30, 31], is located just 0.5 kb telomeric of MADD gene. Moreover, polymorphisms of this gene have been associated with lipid levels and CAD risk in Caucasians . So whether SNP rs7395662 is a functional one, or just a tagging one, needs to be determined by further functional studies.
Another SNP, rs1169288, which is a non-synonymous SNP in the coding region of HNF1A gene, has been reported to be associated with TC, LDL-c levels and CAD risk in a GWAS of Caucasians . Reiner et al. also found significant associations of the minor allele C with higher LDL-c levels and increased risk of CAD in the two case–control samples from African -Americans and Caucasians . In our study, the minor allele C of SNP rs1169288 was associated with higher TC levels and increased risk of CAD, but not associated with LDL-c levels in Chinese population. One possible reason of these differences is that our sample size is not enough to detect the association because of the subtle effect size of the individual variant on LDL-c levels. Another explanation is that different linkage disequilibrium patterns existed in different populations. After all, a number of studies have suggested that there may be genetic differences between the determinants of lipid profiles in different ethnicities [34, 35]. HNF1A gene, encoded the transcription factor hepatocyte nuclear factor 1-α, which regulated the transcription of numerous genes involved in lipid transport and metabolism . SNP rs1169288 is located within the HNF1A dimerization domain that has been associated with decreased in vitro transcriptional activity of downstream target gene promoters . Therefore, this variant may influence multiple atherosclerosis-related genes or their plasma products through effects on HNF-1α structure or function .
The Gensini scoring system is a well-used method for measuring the severity of coronary atherosclerosis, which is the primary pathophysiological process underlying CAD . Because our 1100 Gensini scores were in accordance with normal distribution after ln-transformation, we performed quantitative trait association and median case–control association analyses for the six SNPs. For both analyses, the associations between the Gensini scores and SNP rs1169288 were significant even after FDR correction. Moreover, we also observed a dose-dependent effect of genotypes of this polymorphism on the vessel scores. Although the exact biological mechanism of these associations remained to be explored, our study provided evidence that SNP rs1169288 may contribute to the etiology of the severity of coronary atherosclerosis and played an important role in the atherosclerotic process.
To combine the relatively small effects of individual genes and to better consider the actual effect of each SNP on the trait , we calculated the weighted GRS based on the three significant (uncorrected) SNPs. The results indicated that each additional risk allele was associated with increased TC levels and decreased HDL-c levels even after multiple testing. More importantly, for weighted GRS of CAD, quintile 5 had a 1.89 times increased odds of CAD as compared to quintile 1, suggesting a potential predictive effect on CAD risk.
Limitations of our study merit consideration. First, the retrospective design of this study has inherent drawbacks and precludes causal inferences . Second, the sample size of the present study may not enough either to detect a marginal effect from very low penetrance SNPs or to identify significant associations of the effect in different genetic model analyses. Third, the GRS were based on SNPs that were significantly associated with CAD risk in our study, and this process may resulted in the possible exaggeration of risk prediction . Because the effect sizes of SNPs were calculated and tested in the same cohort. Finally, due to lack of clinical data, we have not examined the effects of SNPs and the GRS on more biomarkers such as lipoprotein (a), apolipoprotein A1 and apolipoprotein B, and on imaging measures, such as the extent of coronary atherosclerosis (the Sullivan Extent scores) and carotid intima-media thickness (CIMT).
In summary, in a case–control study with 1100 CAD patients and 1069 controls, we have identified that two SNPs (HNF1A rs1169288, MADD-FOLH1 rs7395662) as well as the GRS were significantly associated with TC, HDL-c levels and CAD risk, and correlation may exist between the HNF1A rs1169288 and severity of coronary atherosclerosis. Functional studies are required to explore the mechanisms governing these effects.
This study was supported by grants from the National Natural Science Foundation of China (81270365 and 81370554).
- Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ, et al. Executive summary: heart disease and stroke statistics--2014 update: a report from the American Heart Association. Circulation. 2014;129:399–410.PubMedView ArticleGoogle Scholar
- Miller CL, Anderson DR, Kundu RK, Raiesdana A, Nurnberg ST, Diaz R, et al. Disease-related growth factor and embryonic signaling pathways modulate an enhancer of TCF21 expression at the 6q23.2 coronary heart disease locus. PLoS Genet. 2013;9:e1003652.PubMed CentralPubMedView ArticleGoogle Scholar
- Weber C, Noels H. Atherosclerosis: current pathogenesis and therapeutic options. Nat Med. 2011;17:1410–22.PubMedView ArticleGoogle Scholar
- Asselbergs FW, Guo Y, van Iperen EP, Sivapalaratnam S, Tragante V, Lanktree MB, et al. Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci. Am J Hum Genet. 2012;91:823–38.PubMed CentralPubMedView ArticleGoogle Scholar
- Arsenault BJ, Boekholdt SM, Kastelein JJ. Lipid parameters for measuring risk of cardiovascular disease. Nat Rev Cardiol. 2011;8:197–206.PubMedView ArticleGoogle Scholar
- Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, et al. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 2009;41:47–55.PubMed CentralPubMedView ArticleGoogle Scholar
- Chasman DI, Pare G, Mora S, Hopewell JC, Peloso G, Clarke R, et al. Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis. PLoS Genet. 2009;5:e1000730.PubMed CentralPubMedView ArticleGoogle Scholar
- Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 2013;45:25–33.PubMedView ArticleGoogle Scholar
- Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 2011;43:333–8.PubMed CentralPubMedView ArticleGoogle Scholar
- Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–13.PubMed CentralPubMedView ArticleGoogle Scholar
- Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–83.PubMedView ArticleGoogle Scholar
- Lv X, Zhang Y, Rao S, Qiu J, Wang M, Luo X, et al. Joint effects of genetic variants in multiple loci on the risk of coronary artery disease in Chinese Han subjects. Circ J. 2012;76:1987–92.PubMedView ArticleGoogle Scholar
- Wang Y, Wang L, Liu X, Zhang Y, Yu L, Zhang F, et al. Genetic variants associated with myocardial infarction and the risk factors in Chinese population. PLoS One. 2014;9:e86332.PubMed CentralPubMedView ArticleGoogle Scholar
- Alobeidy BF, Li C, Alzobair AA, Liu T, Zhao J, Fang Y, et al. The Association Study between Twenty One Polymorphisms in Seven Candidate Genes and Coronary Heart Diseases in Chinese Han Population. PLoS One. 2013;8:e66976.PubMed CentralPubMedView ArticleGoogle Scholar
- Who: Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004, 363:157-163.Google Scholar
- Zakopoulos N, Manios E, Moulopoulos S. Guidelines for the management of hypertension and target organ damage. J Hypertens. 2013;31:2463–4.PubMedView ArticleGoogle Scholar
- Amer Diabet Assoc: Standards of medical care in diabetes--2008. Diabetes Care. 2008, 31 Suppl 1:S12–54.Google Scholar
- Gensini GG. A more meaningful scoring system for determining the severity of coronary heart disease. Am J Cardiol. 1983;51:606.PubMedView ArticleGoogle Scholar
- Zhou L, Ding H, Zhang X, He M, Huang S, Xu Y, et al. Genetic variants at newly identified lipid loci are associated with coronary heart disease in a Chinese Han population. PLoS One. 2011;6:e27481.PubMed CentralPubMedView ArticleGoogle Scholar
- Chen X, Li S, Yang Y, Yang X, Liu Y, Liu Y, et al. Genome-wide association study validation identifies novel loci for atherosclerotic cardiovascular disease. J Thromb Haemost. 2012;10:1508–14.PubMedView ArticleGoogle Scholar
- Liew M, Pryor R, Palais R, Meadows C, Erali M, Lyon E, et al. Genotyping of single-nucleotide polymorphisms by high-resolution melting of small amplicons. Clin Chem. 2004;50:1156–64.PubMedView ArticleGoogle Scholar
- Brautbar A, Pompeii LA, Dehghan A, Ngwa JS, Nambi V, Virani SS, et al. A genetic risk score based on direct associations with coronary heart disease improves coronary heart disease risk prediction in the Atherosclerosis Risk in Communities (ARIC), but not in the Rotterdam and Framingham Offspring, Studies. Atherosclerosis. 2012;223:421–6.PubMed CentralPubMedView ArticleGoogle Scholar
- Ripatti S, Tikkanen E, Orho-Melander M, Havulinna AS, Silander K, Sharma A, et al. A multilocus genetic risk score for coronary heart disease: case–control and prospective cohort analyses. Lancet. 2010;376:1393–400.PubMed CentralPubMedView ArticleGoogle Scholar
- Chang MH, Ned RM, Hong Y, Yesupriya A, Yang Q, Liu T, et al. Racial/ethnic variation in the association of lipid-related genetic variants with blood lipids in the US adult population. Circ Cardiovasc Genet. 2011;4:523–33.PubMedView ArticleGoogle Scholar
- Shah S, Casas JP, Gaunt TR, Cooper J, Drenos F, Zabaneh D, et al. Influence of common genetic variation on blood lipid levels, cardiovascular risk, and coronary events in two British prospective cohort studies. Eur Heart J. 2013;34:972–81.PubMed CentralPubMedView ArticleGoogle Scholar
- Gong P, Luo SH, Li XL, Guo YL, Zhu CG, Xu RX, et al. Relation of ABO blood groups to the severity of coronary atherosclerosis: an Gensini score assessment. Atherosclerosis. 2014;237:748–53.PubMedView ArticleGoogle Scholar
- Gu Y, Liu Z, Li L, Guo CY, Li CJ, Wang LS, et al. OLR1, PON1 and MTHFR gene polymorphisms, conventional risk factors and the severity of coronary atherosclerosis in a Chinese Han population. Cell Physiol Biochem. 2013;31:143–52.PubMedView ArticleGoogle Scholar
- Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B (Methodological). 1995;57:289–300.Google Scholar
- Huang KK, Yin RX, Zeng XN, Huang P, Lin QZ, Wu J, et al. Association of the rs7395662 SNP in the MADD-FOLH1 and several environmental factors with serum lipid levels in the Mulao and Han populations. Int J Med Sci. 2013;10:1537–46.PubMed CentralPubMedView ArticleGoogle Scholar
- Calkin AC, Tontonoz P. Transcriptional integration of metabolism by the nuclear sterol-activated receptors LXR and FXR. Nat Rev Mol Cell Biol. 2012;13:213–24.PubMed CentralPubMedGoogle Scholar
- Cruz-Garcia L, Schlegel A. Lxr-driven enterocyte lipid droplet formation delays transport of ingested lipids. J Lipid Res. 2014;55:1944–58.PubMedView ArticleGoogle Scholar
- Price ET, Pacanowski MA, Martin MA, Cooper-DeHoff RM, Pepine CJ, Zineh I, et al. Liver X receptor alpha gene polymorphisms and variable cardiovascular outcomes in patients treated with antihypertensive therapy: results from the INVEST-GENES study. Pharmacogenet Genomics. 2011;21:333–40.PubMed CentralPubMedView ArticleGoogle Scholar
- Reiner AP, Gross MD, Carlson CS, Bielinski SJ, Lange LA, Fornage M, et al. Common coding variants of the HNF1A gene are associated with multiple cardiovascular risk phenotypes in community-based samples of younger and older European-American adults: the Coronary Artery Risk Development in Young Adults Study and The Cardiovascular Health Study. Circ Cardiovasc Genet. 2009;2:244–54.PubMed CentralPubMedView ArticleGoogle Scholar
- Albert MA. Inflammatory biomarkers, race/ethnicity and cardiovascular disease. Nutr Rev. 2007;65:S234–238.PubMedView ArticleGoogle Scholar
- Frazier-Wood AC, Manichaikul A, Aslibekyan S, Borecki IB, Goff DC, Hopkins PN, et al. Genetic variants associated with VLDL, LDL and HDL particle size differ with race/ethnicity. Hum Genet. 2013;132:405–13.PubMed CentralPubMedView ArticleGoogle Scholar
- Shih DQ, Bussen M, Sehayek E, Ananthanarayanan M, Shneider BL, Suchy FJ, et al. Hepatocyte nuclear factor-1alpha is an essential regulator of bile acid and plasma cholesterol metabolism. Nat Genet. 2001;27:375–82.PubMedView ArticleGoogle Scholar
- Wu KJ, Wilson DR, Shih C, Darlington GJ. The transcription factor HNF1 acts with C/EBP alpha to synergistically activate the human albumin promoter through a novel domain. J Biol Chem. 1994;269:1177–82.PubMedGoogle Scholar
- Libby P, Theroux P. Pathophysiology of coronary artery disease. Circulation. 2005;111:3481–8.PubMedView ArticleGoogle Scholar
- Liang J, Lin C, Hu F, Wang F, Zhu L, Yao X, et al. APC polymorphisms and the risk of colorectal neoplasia: a HuGE review and meta-analysis. Am J Epidemiol. 2013;177:1169–79.PubMedView ArticleGoogle Scholar
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