CDKN2BAS polymorphisms are associated with coronary heart disease risk a Han Chinese population

The goal of our study was to determine whether CDKN2BAS polymorphisms are associated with coronary heart disease (CHD) risk in a Han Chinese population. Eight SNPs were genotyped in 676 men and 465 women. We used χ2 tests and genetic model analyses to evaluate associations between the SNPs and CHD risk. We found that rs10757274 was associated with an increased risk of CHD in both men (allele G: Odds ratio [OR] = 1.30, 95% confidence interval [CI]: 1.05-1.61, P = 0.018; codominant model: P = 0.042; recessive model: OR = 1.70, 95% CI: 1.10-2.62, P = 0.016; log-additive model: OR = 1.34, 95% CI: 1.05-1.71, P = 0.019) and women (dominant model: OR = 2.26, 95% CI: 1.28-3.99, P = 0.004). In addition, rs7865618 was associated with an 8.10-fold increased risk of CHD in women under a recessive model (OR = 8.10, 95% CI: 1.74-37.68, P = 0.006). Interestingly, the haplotype AA (rs10757274 and rs1333042) of CDKN2BAS was associated with decreased the risk of CHD in men (OR = 0.72, 95% CI: 0.55 - 0.95, P = 0.022).


INTRODUCTION
Coronary heart disease (CHD), is a major cause of morbidity and mortality worldwide [1] and one of the most common chronic inflammatory diseases, characterized by remodeling and narrowing of the blood vessels (coronary arteries) that supply oxygen and blood to the heart [2]. CHD is a complex disease influenced by both environmental and genetic factors [3,4]. Epidemiological studies have identified many risk factors for CHD, including age, gender, smoking, obesity, diabetes, hyperlipidemia, hypertension, lack of exercise, and dietary factors. Twin and family studies have demonstrated that a significant proportion (40-50%) of susceptibility to CHD is inherited [5]. Although atherosclerosis is one of the main pathophysiological mechanisms of CHD [2], the responsible molecular and genetic determinants remain largely unidentified. Recently, both genome-wide association studies (GWAS) and candidate gene studies have reported that CDKN2BAS (cyclin-dependent kinase inhibitor 2B antisense RNA) is a risk gene for CHD susceptibility [6][7][8].
CDKN2BAS encodes an antisense non-coding RNA, and is located near the CDKN2A-CDKN2B gene. The precise function of CDKN2BAS is unclear, but it regulates the expression of neighboring protein-coding genes, like CDKN2A, CDKN2B, and MTAP, that enhance the progression of atherosclerosis by influencing vascular remodeling, thrombogenesis, and plaque stability [9,10]. Therefore, CDKN2BAS expression plays a pivotal role in the development of CHD by altering the dynamics of vascular cell proliferation. In addition, single nucleotide polymorphisms (SNPs) in CDKN2BAS are associated with the risk of multiple diseases, including comprising CHD [7,9,11], myocardial infarction [7], type 2 diabetes [12], ischemic stroke [13], and periodontitis [14].

Research Paper: Pathology
Oncotarget 82047 www.impactjournals.com/oncotarget While many studies have demonstrated that polymorphisms in CDKN2BASare associated with the risk of CHD, few studies have focused on the effects of these alterations on susceptibility to CHD in the Han Chinese population. Therefore, we performed a case-control study to investigate the associations between these SNPs and the risk of CHD in the Han Chinese men and women.

RESULTS
Basic information on the eight SNPs in CDKN2BAS, including chromosomal position, role, allele, minor allele frequency (MAF), and Hardy-Weinberg Equilibrium (HWE) test results are shown in Table 1. All SNPs were in HWE in the control groups (P > 0.05). We then compared the differences in frequency distributions of alleles between cases and controls using Chi-squared tests and found that the frequency of allele "G" of rs10757274 in CDKN2BAS was higher in cases, and it was associated with a 1.30-fold increased risk of CHD in men at a 5% level (OR = 1.30, 95% CI: 1.05-1.61, P = 0.018).
We further assessed the association between each SNP and CHD risk using unconditional logistic regression analysis after adjusting for age. The results of genetic model analyses (codominant, dominant, recessive, logadditive) are presented in Table 2. We identified that  Linkage Disequilibrium (LD) analysis demonstrated that two SNPs (rs10757274 and rs1333042) in CDKN2BAS showed strong linkage ( Figure 1). Furthermore, the haplotype AA (rs10757274 and rs1333042) was significantly associated with a decreased risk of CHD in men (OR = 0.72, 95% CI: 0.55 -0.95, P = 0.022; Table 3).

DISCUSSION
The goal of our case-control study was to explore the associations of eight polymorphisms in CDKN2BAS with the risk of CHD in a Han Chinese population. We found that rs10757274 was associated with an increased risk of CHD both in men and women. However, rs7865618 was correlated with an increased risk of CHD only in women. In addition, we also found that the haplotype "AA" (rs10757274 and rs1333042) of CDKN2BAS was associated with a decreased CHD risk in men.
Previous studies have demonstrated that CDKN2BAS transcript levels show a strong correlation with the severity of atherosclerosis. In addition, the modulation of CDKN2BAS expression influences CHD susceptibility. The function of CDKN2BAS is unknown, but it regulates the expression of CDKN2A and CDKN2B, which encode cyclin-dependent kinase inhibitors 2A and 2B, indicating a regulatory role for CDKN2BAS in cellular proliferation. Polymorphisms at the 9p21 region may induce higher expression of the CDKN2BAS transcript, thereby inhibiting the expression of CDKN2A and CDKN2B.
Several studies have demonstrated a strong association of rs10757274 with CHD in Pakistani [9], Caucasian [15], and South-West Iranian [16] population. Our results are consistent with these previous findings d. However, one previous study found no association of rs10757274 with CHD in a Han Chinese population (Shenzhen) [17].The differences between our study and this study are likely due to differences in the two study populations. How rs10757274 affects the risk of CHD is unclear, but this SNP may regulate the expression of EU741058 and p16INK4a, which modulate the risk of developing CHD [18]. Some studies have also suggested that rs10757274impairs the mechanical properties of the arterial wall and thus influences vascular diseases [19].
It was previously shown that rs1333042 is associated with the risk of CHD in the Han Chinese [20,21] and Saudi populations [7], which is inconsistent with our findings. The differences in these studies may be explained by ethnic differences, environment, or lifestyle that also affected the development of CHD. We also observed that rs7865618 was associated with CHD risk in women. However, this SNP has previously only been found to interact with other SNPs to affect the development of CHD [6]. In future studies, we will verify our results using a larger sample size.
We didn't observe any association between rs1333040 and the risk of CHD, which is consistent with the studies by Cao et al. [21] and Golabgir Khademi et al. [22]. This SNP was significantly associated with the risk of CHD in a Northern Indian population [23] and in African American women [24]. Genetic variation and differences in life styles among populations probably explain the population disparities in the association of this SNP and susceptibility to CHD. Furthermore, recent studies have reported that the levels of TG, TC, HDL-C, LDL-C, CRE, NEU and PDW effectively predict the risk of CHD [25][26][27][28]. Interestingly, we also demonstrated that SNPs in CDKN2BAS were correlated with the levels of these biochemical indicators and differed between cases and controls.
Several limitations should be acknowledged in the present study. First, the sample size was relatively small and the participants were limited to Chinese ethnicity. Second, there were differences in some clinical characteristics between the patients and controls. Although several confounders have been adjusted for the statistical analyses, we could not completely eliminate the potential influences of these factors on the results. Finally, the biological mechanism of genetic variants in CDKN2BAS was not investigated in this study. It will be important to follow up and validate our findings with larger sample sizes.
In conclusion, our results suggest that, in a Chinese Han population, rs10757274 in CDKN2BAS is associated with the risk of CHD both in men and women, rs7865618 is correlated with an increased risk of CHD only in women, and the haplotype AA (rs10757274 and rs1333042) of CDKN2BAS is associated with a decreased CHD risk in men. Thus, these SNPs could have clinical importance as pre-diagnostic markers. Further study is required to determine the functional effects of these SNPs and validate these findings in larger populations.

Ethics statement
Written informed consent was obtained from all study participants before the interview. This study protocol

Study participants
The study included 676 men (291 CHD cases with a mean age of 60 years and 385 healthy controls with a mean age of 48 years) and 465 women (165 CHD cases with a mean age of 64 years and 300 healthy controls with a mean age of 50 years). All CHD cases were recruited from the Cardiovascular Internal Medicine Department of Yanan University Affiliated Hospital between February 2014 and April 2015. The 685 healthy controls were randomly selected from physical examination center of the same hospital during the same period. The inclusion and exclusion criteria for participants were as follows: First, all subjects were of the ethnic Han origin and not related to each other. Second, all participants diagnosis we based on standardized electrocardiogram, echocardiography, blood tests and coronary angiography and judged by two or three independent cardiologists. Third, all individuals were excluded from the study if they had other cardiac diseases (congenital heart disease, cardiomyopathy, or rheumatic heart disease), diabetes, hypertension, or severe liver or kidney disease.s, Patients who had previously received angioplasty, intravenous thrombolysis, coronary artery stents, or coronary artery bypass surgery were also excluded. Basic characteristics of all enrolled controls were collected with a standard epidemiological questionnaires conducted by well-trained interviewers. The cases information was collected through consultation with treating physicians or from medical chart review. Peripheral venous blood (5 ml) was collected from each participant using vacutainer tubes containing ethylene diamine tetra-acetic acid (EDTA) and then stored at -80°C. A clinical examination at which a blood sample was drawn for routine analysis of blood levels, biochemical tests, coagulation function, and genetic analyses.

SNP selection and genotyping
The eight SNPs in CDKN2BAS (rs7865618, rs1179023, rs1412832, rs6475606, rs1333040, rs1537370, rs10757274 and rs1333042) were selected from previous reports for their association with CHD [9,21,23,29,30]. The minor allele frequency of each SNP was > 5% in the HapMap of the Chinese Han Beijing (CHB) population. Genomic DNA was extracted from whole blood using the GoldMag-Mini Whole Blood Genomic DNA Purification Kit according to the manufacturer's protocol (GoldMag. Co. Ltd., Xi'an, China). DNA concentration and purity were evaluated using a spectrophotometer (NanoDrop 2000; Thermo Fisher Scientific, Waltham, MA, USA).
Polymerase chain reaction (PCR) and extension primers for the SNPs were designed using the Sequenom MassARRAY Assay Design 3.0 software (Sequenom, San Diego, CaliforniaCA, USA). Genotyping was performed using the Sequenom MassARRAY platform (Sequenom, San Diego, CA, USA) according to the standard instructions. Sequenom Typer 4.0 software was used for data management and analyses. SPSS 19.0 (SPSS Inc., Chicago, IL, USA) and Microsoft Excel (Microsoft Corp., Redmond, WA, USA) were used for statistical analyses. Genotypic frequencies in controls (men and women) were tested for departure from HWE using a Fisher's exact test. The allelic frequencies were compared between cases and controls by Chi-squared test/Fisher's exact test, and the relative risk was estimated by odd ratios (ORs) and 95% confidence intervals (CIs). The genetic model analyses (codominant, dominant, recessive, log-additive) were applied using PLINK software to assess the significance of SNPs. ORs and 95% CIs were calculated using unconditional logistic regression analysis with adjustment for age. The p values were calculated with the Wald test. Haploview software (version 4.2) was used for analyses of the pairwise linkage disequilibrium (LD), haplotype structure and genetic association at polymorphism loci. All p values were twosided, and p < 0.05 is considered statistically significant.