BioMed Research International

BioMed Research International / 2017 / Article

Research Article | Open Access

Volume 2017 |Article ID 4138376 | https://doi.org/10.1155/2017/4138376

Zi-Kai Song, Hong-Yan Cao, Hai-Di Wu, Li-Ting Zhou, Ling Qin, "LPA Gene Polymorphisms and Gene Expression Associated with Coronary Artery Disease", BioMed Research International, vol. 2017, Article ID 4138376, 6 pages, 2017. https://doi.org/10.1155/2017/4138376

LPA Gene Polymorphisms and Gene Expression Associated with Coronary Artery Disease

Academic Editor: Klaus Wimmers
Received23 Oct 2016
Revised27 Mar 2017
Accepted24 Oct 2017
Published31 Dec 2017

Abstract

The aim of our study was to investigate the influence of LPA gene polymorphisms for CAD risk and Lp(a) in a case-control study of Chinese Han population. In addition, we further analyzed the effect of LPA gene expression on plasma levels of Lp(a) and CAD risk. First, five SNPs (rs1367211, rs3127596, rs6415085, rs9347438, and rs9364559) in LPA gene were genotyped using the SEQUENOM Mass-ARRAY system in two groups. Second, we used quantitative real-time PCR to examine the mRNA expression levels of LPA gene in 92 cases and 32 controls. Results showed that the frequency of rs6415085-T allele was significantly higher in case group than that in control group (). Haplotypes were not associated with CAD risk (). And cases with the TT/TG genotype had significantly higher plasma Lp(a) levels compared with those that have the rs6415085 GG genotype (). Additionally, the mRNA expression levels in case group are significantly higher than that in control group (). Our study confirmed that rs6415085 was associated with CAD and increased plasma Lp(a) levels. And increased mRNA expression level of LPA gene may be a mechanism in development of CAD.

1. Introduction

The developing of CAD was associated with many risk factors in many studies [1, 2]. Among these factors, the lipid level is one of the main CAD risk factors. Therefore, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and several other conventional risk factors are often used to predict the risk for cardiovascular disease (CVD) [3, 4]. In the study by Emerging Risk Factors Collaboration, for individuals without known CVD, the combination of lipoprotein(a), apolipoprotein B and A-I, or lipoprotein-associated phospholipase A2 mass to risk scores containing total cholesterol and HDL-C led to slight improvement in CVD prediction [5]. However, the mechanism of action of lipoprotein(a) [Lp(a)] in cardiovascular risk and the significance of treatment for Lp(a) are not clear.

The structure of Lp(a) is complex. It is a plasma lipoprotein consisting of a cholesterol-rich low-density lipoprotein cholesterol (LDL) particle with one molecule of apolipoprotein B100 and an additional protein, apolipoprotein(a), attached via a disulphide bond [6]. Additionally, the plasma levels of Lp(a) are effected by genetic factors. A Genome Wide Association Study (GWAS) studied by R. Clarke showed that LPA gene variants were strongly associated with both an increased plasma levels of Lp(a) and an increased risk of coronary disease [7].

LPA, located on chromosome 6q25-q26, encodes the apolipoprotein(a) component of the Lp(a) lipoprotein particle. In studies for the association between LPA and CAD risk and plasma Lp(a) levels, rs10455872 and rs3798220 were strongly associated with increased plasma levels of Lp(a), a reduced copy number in LPA (which determines the number of kringle IV-type 2 repeats), and a small Lp(a) lipoprotein size [7, 8]. However, another three loci (rs3127596, rs6415084, and rs9364559) were also significantly associated with CAD risk, and rs3127596 and rs6415084 were also significantly associated with increased plasma levels of Lp(a). Therefore, the aim of our study was to investigate a possible association between LPA gene polymorphisms and CAD risk in a case-control study of Chinese Han population. In addition, we further analyzed the effect of LPA gene expression on plasma Lp(a) levels and CAD risk in Chinese Han population.

2. Materials and Methods

2.1. Study Subjects

92 cases and 32 controls were collected for genetic and mRNA expression level analysis. All subjects were Chinese of Han descent from the First Hospital of Jilin University during February 2013 and March 2014. Diagnosis of CAD was carried independently by at least two well-trained physicians based on the following criteria. All patients were identified with CAD by coronary computed tomographic angiography (SIEMNS Somatom Definition row spiral CT). CAD was defined by ≥50% stenosis in any major coronary artery. Patients with nonatherosclerotic vascular diseases, congenital heart disease, cardiomyopathy, valvular disease, renal or hepatic disease, and cancer were excluded. All control subjects had ECG, chest X-ray, and serum analysis. They were classified as healthy subjects based on their normal physical examination results coupled with the absence of personal or family history and reasons for being suspected CAD.

The presence of cardiovascular risk factors, including diabetes mellitus (fasting blood glucose ≥ 7.0 mmol/L, and/or using glucose-lowering medication, including insulin), hypertension, and cigarette smoking, was obtained from all participants. Hypertension was defined according to seated blood pressure readings of 140/90 mmHg and higher, and/or subjects’ receiving antihypertensive medication. In this study, a smoking habit was defined as a daily intake of >10 cigarettes [9].

This study complied with the Declaration of Helsinki. All the subjects have written informed consent for the study, which was approved by ethics committee of Jilin University, Changchun, China.

2.2. Laboratory Examination

Before starting the study, all participants underwent an initial screening assessment that included medical history, vital signs, a 12-lead electrocardiogram, and measurement of lipid variables and novel risk factors. Venous blood was collected in the morning after an overnight (8–12 hours) fast. Serum/plasma samples were frozen and stored at −80°C prior to analysis. All measurements were performed in a central laboratory.

2.3. SNP Selection, Identification, and Genotyping

The candidate single nucleotide polymorphisms (SNPs) (rs3127596 and rs9364559) were selected from a GWAS study. Another three tagging SNPs (rs1367211, rs6415085, and rs9347438) were chosen from genotyped SNPs in Chinese Han population (CHB) of the HapMap project (the Phase I database). All SNPs were restricted to minor allele frequency bigger than 15% in HAPMAP-CHB database (https://www.hapmap.org). Genomic DNA used for PCR amplification was extracted from the whole blood sample using a DNA extraction kit (Takara, China). Primers of amplification and extension were used by AssayDesigner3.1 software. Amplification and extension primers sequences of five loci in LPA gene were described by us previously [10]. Genotypes were assigned real-time using Typer 4.0 software (Sequenom). As quality controls, 5–10% of the samples were genotyped in duplicate. No inconsistencies were observed. Controls distributed in each 384-well plate were also consistent. Cluster plots were made of the signals from the low and the high mass allele.

2.4. RNA Isolation and Quantification

High-quality total RNA was isolated from human peripheral blood samples from case and control groups with different genotypes in Chinese Han population, and 500 ng of total RNA was reverse transcribed. LPA mRNAs were quantified by real-time quantitative polymerase chain reaction using the 5′ nuclease assay and the ABI Prism 7300 Sequence Detection System (Applied Biosystems, Foster City, CA). Oligonucleotide primers and TaqMan probes are given: 5′-GGGACAAATAAATGGGCAGGT-3′, 5′-AATGAAGAGGATGCACAGAGAGG3′. The relative gene expression levels were calculated by () [11].

2.5. Statistical Analysis

Data were expressed as percentages of total for categorical variables, or mean ± SD. The statistical analyses on the characteristics of the subjects were performed with Pearson test for the categorical variables such as sex, smokers, drinkers, hypertension, and diabetes and with Student’s -test for the continuous variable of age, total cholesterol (TC), triglyceride (TG), LDL-C, and HDL-C with normal distribution. Association between different groups and alleles or genotypes of LPA gene polymorphisms was analyzed using either or Fisher exact test. Plasma Lp(a) levels and mRNA expression levels of the LPA gene were nonnormal distribution data, which were expressed as M ± Q. For the association between SNPs and the mRNA expression level of the LPA gene, rank-sum test was used. SPSS 16.0 was used for above analyses.

3. Results

3.1. Characteristics of Participants

The baseline characteristics of case and control groups are shown in Table 1. There was no significant difference of the mean age, sex, rate of drinking, prevalence of diabetes mellitus, body mass index (BMI), serum TG, and TC level between two groups. Compared with control group, case group had more smokers and more individuals with hypertension. Additionally, compared with control group, case group had higher level of serum LDL-C, HDL-C and Lp(a) ().


VariableCase group ()Control group ()

(year)0.296
Sex (%)58.775.00.100
(kg/m2)0.431
Smoking (%)37.518.10.021
Drinking (%)20.019.20.842
Hypertension (%)49.428.10.037
Diabetes mellitus (%)25.821.90.656
(mmol/L)0.143
(mmol/L)0.074
LDL- (mmol/L)0.021
HDL- (mmol/L)0.032
(mmol/L)0.000

are described based on mean ± SD. are described based on median ± QR.
3.2. Allele and Genotype Analysis

The distributions of alleles and genotypes of five loci among participants were presented in Table 2. Analysis with SPSS 16.0 showed that allele frequencies of rs6415085 were significantly higher in case group than that in control group (). But, there was no difference of genotype frequencies for rs6415085 between two groups (). Additionally, there were no differences in genotype and allele frequencies for the other four SNPs between two groups ().


SNPsGenotypeAllelic
Cases (92)Controls (32)Cases (92)Controls (32)

Rs13672112275831217311431846
Rs312759663223274014828584
Rs936455940401211182120644022
Rs64150855417152323125488
Rs934743813433111614691051844

.
3.3. Linkage Disequilibrium (LD) Analysis

LD analysis for five SNPs on LPA gene in cases and controls, respectively, results showed that rs1367211 and rs6415085 (), rs1367211 and rs9347438 (), and rs3127596 and rs9364559 () were in tight LD (Figure 1). Results of haplotype analysis showed that haplotypes were not associated with CAD risk ().

3.4. The Effect of LPA SNPs on Serum Lp(a) Levels in Chinese Han Population

Each SNP was tested for an association with Lp(a) levels. Results from this analysis are presented in Table 3. There were no significant differences in plasma Lp(a) levels between case and control groups with different genotypes (). But, we further analyzed the effect of LPA SNPs on serum Lp(a) levels in cases and controls, respectively. Results showed that patients with the TT/TG genotype had significantly higher plasma Lp(a) levels compared with those that have the rs6415085 GG genotype ().


SNPsCase groupControl groupχ2

rs1367211
 AA + AG1.9150.166
 GG
rs3127596
 GG + GA1.0770.299
 AA
rs9364559
 GG + GA0.8930.345
 AA
rs6415085
 TT + TG2.2340.135
 GG
rs9347438
 CC + CT1.5680.211
 TT

.
3.5. Real-Time RT-PCR Analyses Identified High Expression Level of LPA Gene Related to CAD Risk

Further comparing the mRNA expression levels of LPA gene in two groups (Figure 2), the mRNA expression levels in case group are significantly higher than that in control group ().

3.6. Assessment of Association between SNPs and the mRNA Expression Level of LPA Gene

We used quantitative real-time polymerase chain reaction (qRT-PCR) analysis to assess whether SNPs were associated with the expression level of LPA gene. The data showed that there was no significant association between SNPs and the expression level of LPA gene () (Table 4).


SNPsCase groupControl groupχ2

rs1367211
 AA + AG1.4010.237
rs3127596
 GG + GA1.2930.256
rs9364559
 GG + GA0.8720.350
rs6415085
 TT + TG0.1950.659
rs9347438
 CC + CT3.6220.057

3.7. Logistic Regression Analysis

As shown in Table 5, ageing, sex, diabetes mellitus, hypertension, smoking, drinking, TC, TG, LDL-C, HDL-C, Lp(a), mRNA expression level of LPA gene, and five SNPs were included in the multivariate logistic regression model. Result showed that LDL-C, smoking, Lp(a), and high mRNA expression level of LPA gene all increased the risk of CAD. But LDL-C was the most predictive risk factor for CAD.


Risk factorBS.E.Wald

Lp(a)0.0100.0047.0680.008
LDL-C1.4380.4838.8520.003
Smoking−1.2140.6073.9970.046
LPA expression level0.0930.0424.8330.028

4. Discussion

The pathogenesis of CAD is not clear. But many studies proved that the interaction of genetic and environmental factors is the main factor for the developing of CAD. In addition to environmental factors such as age, gender, bad behavior, poor diet, obesity, dyslipidemia, hypertension, and diabetes, GWAS study has identified several novel susceptibility loci for CAD [1216]. But many SNPs appear in noncoding regions of the genome. Therefore, the complex mechanisms are still largely unknown. Many studies have confirmed that SNPs which influence mRNA expression are known as expression Quantitative Trait Loci (eQTL) [1720].

In this study, we observed frequency of T allele of rs6415085 was increased in individuals with CAD. But there was no difference of genotype frequencies for rs6415085 between two groups. Further results of LD analysis showed that rs1367211 and rs6415085, rs1367211 and rs9347438, and rs3127596 and rs9364559 were in tight LD. But haplotypes were not associated with CAD risk. In addition, patients with the rs6415085 TT/TG genotype had significantly higher Lp(a) levels than that with the rs6415085 GG genotype. Therefore, above result suggests that LPA gene may be the potential mechanism leading to atherosclerosis and associated with an increased level of Lp(a). Above results are consistent with previous studies [2123]. Rs10455872 and rs3798220 in LPA gene were proved strongly associated with plasma Lp(a) levels and CAD and reduce the copy number at LPA (which determines the number of kringle IV-type 2 repeats) and a small Lp(a) lipoprotein size [7, 8].

Meanwhile, we found that LPA gene expression was significantly increased in individuals with CAD compared to those without CAD. And CAD patients have higher plasma Lp(a) levels than healthy individuals. Therefore, these results further confirmed the relationship between Lp(a) levels and CAD risk [2426].

The mechanism research by Niccoli et al. showed that higher plasma Lp(a) levels exhibited a higher prevalence of lipidic plaque at the site of the culprit stenosis, a wider lipid arc, and a higher prevalence of thin-cap fibroatheroma [27]. Therefore, the role of therapies targeting Lp(a) can decrease CAD risk through reduction of vulnerable plaque features of patients with CAD. Regression analysis results showed that the plasma Lp(a) and LDL-C levels are associated with CAD. Combined with above results, we speculate rs6415085 TT/TG genotype may, through increased plasma Lp(a) levels, increase CAD risk.

But our results showed that LPA mRNA expression level is not significantly increased in patients with rs6415085 TT/TG genotype. The above results are mainly due to rs6415085 being intron variant in noncoding regions of LPA gene. In the future through the study of introns and siRNA research it is expected to clear the mechanism of SNP.

A potential limitation of our study was the numbers of subject in our study, which may limit statistical power and generalization to the overall Chinese population. Nevertheless, our results are in accordance with former studies that suggested a putative influence of LPA gene polymorphisms in the mechanisms associated with CAD. In addition, we did not collect data of treatment for hyperlipidemia, which maybe affect the relationship between genotypes and lipid levels. In further study, we should collect more comprehensive data about angiography and history of treatment to analyze association between gene variants, lipid level, and CAD severity.

In conclusion, our study confirmed that T allele of rs6415085 was associated with CAD and rs6415085 TT/TG genotype which maybe increased plasma Lp(a) levels. And increased mRNA expression level of LPA gene may be a mechanism in development of CAD. However, further studies encompassing larger number of patients are needed to confirm the results obtained in this study.

Conflicts of Interest

The authors have declared that no conflicts of interest exist.

Authors’ Contributions

Zi-Kai Song contributed to this work.

Acknowledgments

The authors thank all participants for their support and participation. Special thanks are due to the support of Hepatology Department, Institute of Translational Medicine, the First Hospital, Jilin University, Changchun, China.

References

  1. S. M. Grundy, R. Pasternak, P. Greenland, S. J. r. Smith, and V. Fuster, “Assessment of cardiovascular risk by use of multiple-risk-factor assessment equations: a statement for healthcare professionals from the American Heart Association and the American College of Cardiology,” Circulation, vol. 100, no. 13, pp. 1481–1492, 1999. View at: Publisher Site | Google Scholar
  2. P. Greenland, M. D. Knoll, J. Stamler et al., “Major risk factors as antecedents of fatal and nonfatal coronary heart disease events,” The Journal of the American Medical Association, vol. 290, no. 7, pp. 891–897, 2003. View at: Publisher Site | Google Scholar
  3. J. Perk, G. De Backer, H. Gohlke et al., “European guidelines on cardiovascular disease prevention in clinical practice (version 2012). The fifth joint task force of the European Society of Cardiology and Other Societies on cardiovascular disease prevention in clinical practice (constituted by representatives of nine societies and by invited experts),” European Heart Journal, vol. 33, no. 13, pp. 1635–701, 2012. View at: Publisher Site | Google Scholar
  4. S. Parish, A. Offer, R. Clarke et al., “Heart Protection Study Collaborative G: Lipids and lipoproteins and risk of different vascular events in the MRC/BHF Heart Protection Study,” Circulation, vol. 125, no. 20, pp. 2469–2478, 2012. View at: Publisher Site | Google Scholar
  5. E. Di Angelantonio, P. Gao, and J. Danesh, “Cardiovascular Disease Risk Prediction Factors—Reply,” Journal of the American Medical Association, vol. 308, no. 19, p. 1969, 2012. View at: Publisher Site | Google Scholar
  6. J. B. Dubé, M. B. Boffa, R. A. Hegele, and M. L. Koschinsky, “Lipoprotein(a): More interesting than ever after 50 years,” Current Opinion in Lipidology, vol. 23, no. 2, pp. 133–140, 2012. View at: Publisher Site | Google Scholar
  7. R. Clarke, J. F. Peden, J. C. Hopewell et al., “Genetic variants associated with Lp(a) lipoprotein level and coronary disease,” The New England Journal of Medicine, vol. 361, no. 26, pp. 2518–2528, 2009. View at: Publisher Site | Google Scholar
  8. Y. Wang, L. Wang, X. Liu et al., “Genetic variants associated with myocardial infarction and the risk factors in Chinese population,” PLoS ONE, vol. 9, no. 1, Article ID e86332, 2014. View at: Publisher Site | Google Scholar
  9. Y.-H. Chen, J.-M. Liu, R.-J. Hsu et al., “Angiotensin converting enzyme DD genotype is associated with acute coronary syndrome severity and sudden cardiac death in Taiwan: a case-control emergency room study,” BMC Cardiovascular Disorders, vol. 12, article no. 6, 2012. View at: Publisher Site | Google Scholar
  10. Z.-K. Song, H.-D. Wu, H.-Y. Cao, and L. Qin, “The association between the LPA gene polymorphism and coronary artery disease in chinese han population,” BioMed Research International, vol. 2014, Article ID 370670, 2014. View at: Publisher Site | Google Scholar
  11. K. J. Livak and T. D. Schmittgen, “Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C (T)),” Methods, vol. 25, no. 4, pp. 402–408, 2001. View at: Publisher Site | Google Scholar
  12. P. R. Burton, D. G. Clayton, L. R. Cardon et al., “Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls,” Nature, vol. 447, no. 7145, pp. 661–678, 2007. View at: Publisher Site | Google Scholar
  13. R. McPherson, A. Pertsemlidis, N. Kavaslar et al., “A common allele on chromosome 9 associated with coronary heart disease,” Science, vol. 316, no. 5830, pp. 1488–1491, 2007. View at: Publisher Site | Google Scholar
  14. A. Helgadottir, G. Thorleifsson, A. Manolescu et al., “A common variant on chromosome 9p21 affects the risk of myocardial infarction,” Science, vol. 316, no. 5830, pp. 1491–1493, 2007. View at: Publisher Site | Google Scholar
  15. H. Ding, Y. Xu, X. Wang et al., “9p21 is a Shared Susceptibility Locus Strongly for Coronary Artery Disease and Weakly for Ischemic Stroke in Chinese Han Population,” Circulation: Cardiovascular Genetics, vol. 2, no. 4, pp. 338–346, 2009. View at: Publisher Site | Google Scholar
  16. N. J. Samani, J. Erdmann, A. S. Hall et al., “Genomewide association analysis of coronary artery disease,” The New England Journal of Medicine, vol. 357, no. 5, pp. 443–453, 2007. View at: Publisher Site | Google Scholar
  17. D. L. Nicolae, E. Gamazon, W. Zhang, S. Duan, M. Eileen Dolan, and N. J. Cox, “Trait-associated SNPs are more likely to be eQTLs: Annotation to enhance discovery from GWAS,” PLoS Genetics, vol. 6, no. 4, Article ID e1000888, 2010. View at: Publisher Site | Google Scholar
  18. X. Zhang, A. D. Johnson, A. E. Hendricks et al., “Genetic associations with expression for genes implicated in GWAS studies for atherosclerotic cardiovascular disease and blood phenotypes,” Human Molecular Genetics, vol. 23, no. 3, Article ID ddt461, pp. 795–782, 2014. View at: Publisher Site | Google Scholar
  19. T. M. Teslovich, K. Musunuru, and A. V. Smith, “Biological, clinical and population relevance of 95 loci for blood lipids,” Nature, vol. 466, no. 7307, pp. 707–713, 2010. View at: Publisher Site | Google Scholar
  20. C. J. Willer, E. M. Schmidt, S. Sengupta et al., “Discovery and refinement of loci associated with lipid levels,” Nature genetics, vol. 45, no. (11), pp. 1274–1283, 2013. View at: Publisher Site | Google Scholar
  21. J.-P. Chretien, J. Coresh, Y. Berthier-Schaad et al., “Three single-nucleotide polymorphisms in LPA account for most of the increase in lipoprotein(a) level elevation in African Americans compared with European Americans,” Journal of Medical Genetics, vol. 43, no. 12, pp. 917–923, 2006. View at: Publisher Site | Google Scholar
  22. M. B. Lanktree, S. S. Anand, S. Yusuf, and R. A. Hegele, “Comprehensive analysis of genomic variation in the LPA locus and its relationship to plasma lipoprotein(a) in south asians, chinese, and european caucasians,” Circulation: Cardiovascular Genetics, vol. 3, no. 1, pp. 39–46, 2010. View at: Publisher Site | Google Scholar
  23. R. C. Deo, J. G. Wilson, C. Xing et al., “Single-nucleotide polymorphisms in LPA explain most of the Ancestry-specific variation in Lp(a) levels in African Americans,” PLoS ONE, vol. 6, no. 1, Article ID e14581, 2011. View at: Publisher Site | Google Scholar
  24. B. Mihaylova, J. Emberson, and L. Blackwell, “The effects of lowering LDL cholesterol with statin therapy in people at low risk of vascular disease: meta-analysis of individual data from 27 randomised trials,” The Lancet, vol. 380, no. 9841, pp. 581–590, 2012. View at: Publisher Site | Google Scholar
  25. M. V. Holmes, F. W. Asselbergs, T. M. Palmer et al., “Mendelian randomization of blood lipids for coronary heart disease,” European Heart Journal, vol. 36, no. 9, pp. 539–550, 2015. View at: Publisher Site | Google Scholar
  26. B. G. Nordestgaard, M. J. Chapman, K. Ray et al., “Lipoprotein(a) as a cardiovascular risk factor: current status,” European Heart Journal, vol. 31, no. 23, pp. 2844–2853, 2010. View at: Publisher Site | Google Scholar
  27. G. Niccoli, D. Chin, G. Scalone et al., “Data on the lipoprotein (a), coronary atherosclerotic burden and vulnerable plaque phenotype in angiographic obstructive coronary artery disease,” Data in Brief, vol. 7, pp. 1409–1412, 2016. View at: Publisher Site | Google Scholar

Copyright © 2017 Zi-Kai Song et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views1191
Downloads384
Citations

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.