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Introduction

Coronary artery disease (CAD) is characterized by the narrowed or blocked coronary arteries that can cause a lack of myocardial oxygen supply. CAD is the main cause of human fatalities worldwide (1). CAD is a complex disorder contributed by environmental and genetic factors (2). C-reactive protein (CRP) is a widely used inflammatory factor (3) in the detection of systemic inflammation diseases, such as atherosclerosis (4), which is an inflammation process closely linked to CAD (5,6). The circulating CRP level was found to be significantly associated with the risk of CAD (7–10). Aggregated C reactive protein was found to bind to low-density lipoproteins and very low-density lipoprotein (11) in the atherosclerotic plaques (12).

Recent genetic and genome-wide association studies have identified a number of genetic loci that are associated with CRP levels (9,13–16). Approximately 40% of CRP level variation was determined by genetic factors (10), including the CRP rs2794520 polymorphism, which was one of most significant markers in the meta-analysis of the genome-wide association studies among >80,000 European subjects (9).

In association with the previous studies, we hypothesized that the CRP rs2794520 polymorphism may influence the risk of CAD. Thus, a case control study was performed to assess the contribution of the CRP rs2794520 polymorphism to CAD in the Han Chinese population.

Materials and methods

Study population

A total of 891 unrelated individuals were carefully selected, which included 459 CAD patients (males, 69.9%; age, 59.7±9.48 years; diabetes mellitus, 22.1%; hypertension, 60.3%; body mass, 23.4±3.4 kg/m2; and smokers, 44.5%) and 432 non-CAD patients (males, 54.4%; age, 59.7±9.48 years; diabetes mellitus, 11.5%; hypertension, 49.3%; body mass, 23.3±3.4 kg/m2; and smokers, 31.7%). All were Han Chinese residents of Ningbo city in Eastern China. The standards required were that the involved CAD patients should have one or more major coronary arteries with a diameter stenosis ≥50%, or had a history of a coronary artery bypass surgery or prior angioplasty. The non-CAD patients were diagnosed with a diameter stenosis <50% of the major coronary arteries and without any atherosclerotic vascular disease. The diagnosis was made by at least two cardiologists (JZ and JL). All the samples were recruited between May 2008 and April 2014 from Ningbo Lihuili Hospital (Ningbo, China). Blood samples were collected in 3.2% citrate sodium-treated tubes and subsequently stored at −80°C. The protocol was approved by the Ethical Committee of Ningbo Lihuili Hospital and all the involved individuals provided signed informed consent.

Single-nucleotide polymorphism (SNP) genotyping

The genomic DNA was isolated from peripheral blood lymphocytes using a conventional phenol/chloroform method, and subsequently DNA was quantified using the PicoGreen® double strand (dsDNA) DNA Quantification kit (Molecular Probes, Inc., Eugene, OR, USA). Amplification of the genomic DNA was performed on the ABI Gene Amp® PCR System 9700 Dual 384-Well Sample Block Module (Applied Biosystems, Foster City, CA, USA) for the quantitative polymerase chain reaction (qPCR) analysis. The surrounding DNA sequence of the tested polymorphism was downloaded from the NCBI dbSNP. Online program (http://www6.appliedbiosystems.com/support/techtools/calc/) was used to design the primers. The sequences of the primers are as follows: Forward, 5′-GCGGGCAGGGCGGCCTGTGTGTATGAAGGGCAT AGGAC-3′; and 5′-GATTACCGCTGTGTGTATGAAGGG CATAGGAT-3′; and reverse, 5′-CAGGCCTCATTCAGTGTG GACC-3′. PCR amplification procedures consisted of an initial denaturation at 95°C for 30 sec to activate the enzyme activity, a 40-cycle denaturation (95°C for 30 sec, annealing stage at 59°C for 30 sec, and an extension at 72°C for another 30 sec), and a final extension for 5 min at 72°C. The amplified DNA was held at 4°C. DNA amplification for genotyping was performed on the SEQUENOM® Mass-ARRAY iPLEX® platform according to the manufacturer's instructions (17).

Data analysis

Arlequin program (version 3.5) was used to estimate the Hardy-Weinberg equilibrium (HWE) (18). Clump 16 software with 10,000 Monte Carlo simulations was used to compare the frequency of the genotype and allele between cases and controls (19). Odd ratio (OR) with 95% confidential interval (CI) was calculated using an online program (http://faculty.vassar.edu/lowry/odds2x2.html). The power of the study was assessed by Power and Sample Size Calculation software (v3.0.43) (20). χ2 analysis was used to compare the severity of CAD and the rs2794520 polymorphism (21). A two-sided P-value <0.05 was considered to indicate a statistically significant difference.

Results

Association between the SNP and CAD

In the present study, no significant association was found between rs2794520 and CAD (P=0.12; OR, 1.16; 95% CI, 0.96–1.41; Table I). As gender and age are two important factors in the risk of CAD, a subgroup analyses was further performed by age or gender; however, no positive results were revealed in all the tests (P>0.05; Tables I and II). Additional subgroup analysis by age and gender showed a negative result in rs2794520 with CAD (P>0.05; Table III). Under the dominant model, a significant result occurred between male CAD patients and controls (P=0.04; OR, 1.64; 95% CI, 1.02–2.63; Table IV), although the significance was not retained following the correction by the number of statistical tests. No significant association was found for the other genotype analyses (Table IV). The power of each analysis in the study was also calculated (Tables I–IV). These results showed that a moderate power existed in the current association test, indicating that the negative association in the study may be due to a lack of power (power=0.474; Table I). Future study or meta-analysis are required to establish the link of this polymorphism to CAD.

Table I Comparison of the genotype and allele frequencies between the cases and controls by gender.

Table I

Comparison of the genotype and allele frequencies between the cases and controls by gender.

						Allele, counts
	rs2794520	Genotype, counts		P-value					P-value
Subjects	group (n)	TT/TC/CC	χ2	(df=2)	HWE	T	C	χ2	(df=1)	OR (95%CI)	Power
All	CAD case (459)	146/230/83			0.70	522	396
	Non-CAD controls (432)	153/217/62	2.77	0.25	0.31	523	341	2.47	0.12	1.16 (0.96–1.41)	0.474
Male	CAD case (321)	100/159/62			1.00	359	283
	Non-CAD controls (235)	81/124/30	4.25	0.12	0.13	286	184	2.71	0.10	1.23 (0.96–1.56)	0.314
Female	CAD case (138)	46/71/21			0.60	163	113
	Non-CAD controls (197)	72/93/32	0.59	0.74	0.88	237	157	0.08	0.78	1.05 (0.76–1.43)	0.209

[i] df, degrees of freedom; HWE, Hardy-Weinberg equilibrium; OR, odds ratio; CI, confidence interval; CAD, coronary artery disease.

Table II Comparison of the genotype and allele frequencies between the cases and controls by age.

Table II

Comparison of the genotype and allele frequencies between the cases and controls by age.

		Genotype, counts				Allele, counts
	rs2794520			P-value				P-value
Age, years	group, n	TT/TC/CC	χ2	(df=2)	HWE	T/C	χ2	(df=1)	OR (95%CI)	Power
55≤	CAD case (115)	40/61/14			0.24	141/89
	Non-CAD controls (159)	57/81/21	0.13	0.94	0.41	195/123	0.000015	1.00	1.00 (0.71–1.42)	0.179
55–65	CAD case (162)	49/83/30			0.75	181/143
	Non-CAD controls (166)	59/86/21	2.52	0.28	0.25	204/128	2.11	0.15	1.26 (0.92–1.72)	0.209
≥65	CAD case (182)	57/86/39			0.55	200/164
	Non-CAD controls (107)	37/50/20	0.47	0.79	0.69	124/90	0.49	0.48	1.13 (0.80–1.59)	0.182

[i] df, degrees of freedom; HWE, Hardy-Weinberg equilibrium; OR, odds ratio; CI, confidence interval; CAD, coronary artery disease.

Table III Comparison of the genotype and allele frequencies between the cases and controls by age and gender.

Table III

Comparison of the genotype and allele frequencies between the cases and controls by age and gender.

		rs2794520	Genotype, counts		P-value		Allele, counts		P-value
Age, years	Gender	group (n)	TT/TC/CC	χ2	(df=2)	HWE	T/C	χ2	(df=1)	OR (95%CI)	Power
≤55	Male	CAD case (85)	30/44/11			0.50	104/66
		Non-CAD controls (99)	35/55/9	0.75	0.69	0.08	125/73	0.15	0.70	1.09 (0.71–1.66)	0.136
	Female	CAD case (30)	10/17/3			0.44	37/23
		Non-CAD controls (60)	22/26/12	2.01	0.37	0.43	70/50	0.18	0.67	0.87 (0.46–1.64)	0.089
55–65	Male	CAD case (118)	35/62/21			0.58	132/104
		Non-CAD controls (78)	27/43/8	2.23	0.33	0.16	97/59	1.51	0.22	1.30 (0.86–1.96)	0.137
	Female	CAD case (44)	14/21/9			1.00	49/39
		Non-CAD controls (88)	32/43/13	0.75	0.69	1.00	107/69	0.63	0.43	1.23 (0.74–2.07)	0.107
≥65	Male	CAD case (118)	35/53/30			0.27	123/113
		Non-CAD controls (58)	19/26/13	0.27	0.88	0.59	64/52	0.29	0.59	1.13 (0.72–1.77)	0.125
	Female	CAD case (64)	22/33/9			0.61	77/51
		Non-CAD controls (49)	18/24/7	0.08	0.96	1.00	60/38	0.03	0.87	1.05 (0.61–1.79)	0.101

[i] df, degrees of freedom; HWE, Hardy-Weinberg equilibrium; OR, odds ratio; CI, confidence interval; CAD, coronary artery disease.

Table IV Comparison of the genotype distribution between the cases and controls in the recessive and dominant models.

Table IV

Comparison of the genotype distribution between the cases and controls in the recessive and dominant models.

		Recessive						Dominant
	rs2794520				P-value
Subjects	group (n)	TT+CT	CC	χ2	(df=1)	OR (95%CI)	Power	TT	CC+CT	χ2	(df=1)	OR (95%CI)	Power
All	CAD case (459)	376	83					146	313
	Non-CAD controls (432)	370	62	2.27	0.13	1.32 (0.92–1.89)	0.284	153	279	1.30	0.25	1.18 (0.89–1.55)	0.442
Male	CAD case (321)	259	62					100	221
	Non-CAD controls (235)	205	30	4.21	0.04	1.64 (1.02–2.63)	0.175	81	154	0.68	0.41	1.16 (0.81–1.66)	0.292
Female	CAD case (138)	117	21					46	92
	Non-CAD controls (197)	165	32	0.06	0.80	0.93 (0.51–1.69)	0.146	72	125	0.37	0.54	1.15 (0.73–1.82)	0.195

a ? df, degrees of freedom; HWE, Hardy-Weinberg equilibrium; OR, odds ratio; CI, confidence interval; CAD, coronary artery disease.

In addition, the association between the severity of CAD and the rs2794520 polymorphism was also examined. All the cases were divided into three groups based on the number of major coronary artery with stenosis ≥50%. The correlation test revealed no significant association between the severity of CAD and rs2794520 (P=0.61; Table IV).

Discussion

CAD has become the leading cause of fatalities in developed and developing countries. The plasma cardiac troponin I (cTnI) level was regarded as a gold standard for the diagnosis of acute myocardial infarction (AMI) worldwide (22). However, the rise of the plasma cTnI level comes after 4–6 h when the clinical events occurred, and this may delay the diagnosis (23). CRP levels had higher sensitivity to cardiovascular events compared to cTnI (24). Increased concentrations of plasma CRP have been found in patients with unstable angina (25). The elevation of CRP was found at the time of hospital admission in patients with myocardial infarction (MI) and history of unstable angina (24). The level of CRP was able to predict cardiovascular events in the healthy population and CAD patients (26,27). A study with 911 typical exertional angina patients indicated that increased CRP levels had a positive correlation with the CAD risk (28). Additionally, a number of studies identified CRP polymorphisms as reliable biomarkers of CAD (9). A case-control study indicated that there is a significant association between the CRP 1059 G/C polymorphism (rs1800947) and AMI in Italian population (29). In the present study, a case-control study was performed that involved 459 CAD patients and 432 non-CAD patients to assess the association between CRP rs2794520 and CAD risks.

There was no association between rs2794520 and CAD (P=0.12). As gender and age are two well-known factors that contribute to the CAD risk (30), subgroup analyses were performed by stratifying the samples into gender and age groups. However, there was no association between the age and gender groups (P>0.05). Additionally, the subgroup analyses were performed by different genetic models that comprised of dominant and recessive models. A close significant result was found in the dominant model between male CAD patients and controls (P=0.04); however, possible multiple testing may exist in the analysis, and therefore, this result may not be considered significant. Other significant associations based on the genetic models in all the stratifications did not occur (P>0.05).

There were certain limitations in the present study. Firstly, the samples of the study were relatively small, and the power was 0.474 in the association between rs2794520 and CAD, which may influence the results of the study. Therefore, studies with larger-scale samples and stronger power are required in future research to confirm the current findings. Secondly, CAD is a complex disease that environmental and genetic status may alter the results of the study, although the cases and controls in the present study were carefully selected with the help of multiple professional doctors, any hidden factors that may influence the results of the current study could not be excluded. More carefully and precisely designed studies are required to strengthen the results of the study. Thirdly, there are 2,587 polymorphisms in the CRP based on the information in the dbSNP in PubMed. The present study only focused on one polymorphism that could not represent the whole contribution of CRP to CAD. Other CRP polymorphisms, such as CRP 1059 G/C (rs1800947), were previously found to be associated with the risk of CAD (29). Examining more CRP polymorphisms is required to assess their contribution to CAD.

In conclusion, the present study showed that the CRP rs2794520 polymorphism had no association with the risk of CAD in the Han Chinese population. Studies with different populations and stronger power are required to further confirm the findings of the study.

Acknowledgements

The present study was supported by the grants from the National Natural Science Foundation of China (nos. 31100919, 30772155 and 81371469), Natural Science Foundation of Zhejiang Province (no. LR13H020003), K. C. Wong Magna Fund in Ningbo University, Zhejiang provincial Program for the Cultivation of High 1 level Innovative Health Talents, Natural Science Foundation of Zhejiang Province (no. Y206608), the Scientific Innovation Team Project of Ningbo (no. 2011B82014), and the Youth and Doctor Foundation of Ningbo (no. 2005A610016).

References