Impact of MCP-1 and CCR-2 gene polymorphismson coronary artery disease susceptibility

Hsiu-Ling Lin • Kwo-Chang Ueng •

Yih-Shou Hsieh • Whei-Ling Chiang •

Shun-Fa Yang • Shu-Chen Chu

Received: 29 November 2011 / Accepted: 9 June 2012 / Published online: 3 July 2012

� Springer Science+Business Media B.V. 2012

Abstract Coronary artery disease (CAD) was the second

leading cause of death during the last 3 years in Taiwan.

Smooth muscle cells, monocytes/macrophages, and endo-

thelial cells produce monocyte chemoattractant protein-1

(MCP-1) within atherosclerotic plaques following binding

to the chemokine receptor-2 (CCR-2). Previous studies

have well-documented the association between MCP-1

expression and susceptibility to, or clinicopathological

features, of CAD. This study investigated the relationships

between MCP-1-2518A/G and CCR-2-V64I genetic poly-

morphisms and CAD in the Taiwanese population. A total

of 608 subjects, including 392 non-CAD controls and 216

patients with CAD, were recruited and subjected to poly-

merase chain reaction-restriction fragment length poly-

morphism (PCR–RFLP) to evaluate the effects of these two

polymorphic variants on CAD. Results indicated a signif-

icant association between MCP-1 -2548 gene polymor-

phism and susceptibility to CAD. GG genotypes (OR =

1.629; 95 % CI = 1.003–2.644), or individuals with at

least one G allele (OR = 1.511; 95 % CI = 1.006–2.270),

had a higher risk of CAD as compared with AA genotypes.

Results also revealed that subjects with at least one A allele

of the V64I CCR2 gene polymorphism had significantly

increased risk of CAD. G allele in MCP-1-2518 might

contribute to higher prevalence of atrial fibrillation in CAD

patients (OR = 4.254; p \ 0.05). In conclusion, MCP-1-

2518G and CCR-2 64I gene polymorphisms represent

important factors in determining susceptibility to CAD, and

the contribution of MCP-1-2518G could be through effects

on atrial fibrillation in CAD patients.

Keywords MCP-1 � CCR-2 � Single nucleotide

polymorphism � Coronary artery disease

Introduction

According to the World Health Organization (WHO)

classification, coronary artery disease (CAD), otherwise

known as coronary heart disease (CHD), is the partial or

total loss of the vascular supply to the myocardium [1]. In

WHO reports, ischemic heart disease, including CAD, is

the leading cause of death worldwide. In Taiwan, heart

Hsiu-Ling Lin and Kwo-Chang Ueng have contributed equally to this

article.

H.-L. Lin � Y.-S. Hsieh

Institute of Biochemistry and Biotechnology,

Chung Shan Medical University, Taichung, Taiwan

H.-L. Lin � K.-C. Ueng

Department of Internal Medicine, Chung Shan Medical

University Hospital, Taichung, Taiwan

K.-C. Ueng

School of Medicine, Chung Shan Medical University,

Taichung, Taiwan

Y.-S. Hsieh

Department of Clinical Laboratory, Chung Shan Medical

University Hospital, Taichung, Taiwan

W.-L. Chiang

School of Medical Laboratory and Biotechnology,

Chung Shan Medical University, Taichung, Taiwan

S.-F. Yang

Institute of Medicine, Chung Shan Medical University,

Taichung, Taiwan

S.-C. Chu (&)

Department of Food Science, Central Taiwan University

of Science and Technology, Taichung, Taiwan

e-mail: scchu@ctust.edu.tw

123

Mol Biol Rep (2012) 39:9023–9030

DOI 10.1007/s11033-012-1773-y

disease was the second leading cause of death within the

last 3 years.

Well-known risk factors of CAD are smoking, alcohol

consumption, hypertension, hyperlipidemia, diabetes mel-

litus (DM), and obesity [1]. Continuous elevation of serum

cholesterol and lipids leads to their accumulation within the

artery wall, subsequent inflammatory response, and for-

mation of atherosclerotic plaques [2]. Continued inflam-

matory response leads to the formation of vulnerable

plaques, which may contribute to acute thrombus formation

on a plaque surface. The thrombus may then restrict the

blood flow leading to acute coronary syndromes, such as

unstable angina and acute myocardial infarction [2–4].

Percutaneous transluminal coronary angioplasty (PTCA) is

currently considered the most accurate tool for diagnosis of

CAD.

The major cause of CAD is coronary artery atheroscle-

rosis, a chronic inflammatory disease, in which monocytes/

macrophages accumulate within the vessel walls of the

coronary arteries during the initial phase of atherosclerosis

[5–7]. The accumulation of oxidized low-density lipopro-

tein (Ox-LDL) within monocytes/macrophages also has a

significant role during the formation and progression of

atherosclerosis [8]. Prior research has demonstrated the

association between cytokines and their receptors, such as

monocyte chemoattractant protein-1 (MCP-1), IL-6, and

IL-1 beta, with activation of monocytes and macrophages,

and accumulation of Ox-LDL [9–12]. Further previous

studies suggested that increased serum MCP-1 levels

associated with risk of CAD or other atherosclerotic vas-

cular diseases, and served as a direct marker of inflam-

matory activity in patients [13, 14]. Binding of MCP-1 to

the monocyte chemokine (C–C motif) receptor 2 (CCR-2),

a seven-transmembrane G-protein coupled receptor,

recruits monocytes to the sites of injured endothelium,

subsequently causing their differentiation to macrophages,

and involvement in the initiation and progression of ath-

erosclerosis [14–18]. In 1998, Boring et al.’s [19] CCR-2

knockout study in ApoE-/- mice showed decreased for-

mation of atherosclerotic plaques, further indicating the

effects of MCP-1 and CCR-2 on recruitment of monocytes/

macrophages into the vessel wall during the initial phase of

atherosclerosis.

Several recent investigations have suggested that MCP-

1 polymorphisms might have involvement in the preva-

lence of CAD because of their influence on protein

expression. Therefore, identification of MCP-1 polymor-

phisms could elucidate the pathways of atherosclerosis

disease pathology and might provide a novel therapeutic

target [10]. Recently, Rovin et al. [18] identified a func-

tional polymorphism in the MCP-1 distal regulatory region

at position -2518 (-2518A/G), which increased MCP-1

expression in vitro. Other studies have also identified a

high presence of the MCP-1-2518G/G genotype in patients

suffering from ischemic heart disease, hypertension, or

myocardial infarction (MI) [20–22]. However, different

populations in other genetic association studies have pro-

vided contradictory results on the association between

MCP-1-2518A/G and CAD, MI, and hypertension [22–30].

Kostrikis et al. [31] first described the Val/Ile polymor-

phism in the gene for CCR-2, at position 64, in an HIV-

related study, suggesting that the 64I-allele has a protective

role. Results from the recent study by Petrkova et al. [32]

also indicated that the CCR-2-V64I polymorphism asso-

ciated with CAD in Czech patients. However, none of these

studies have investigated the roles of these two gene

polymorphisms on susceptibility to CAD in Taiwan. The

present study, therefore, investigates the relationship

between MCP-1-2518A/G and CCR-2-V64I polymor-

phisms and CAD in the Taiwanese population.

Materials and methods

Population

Between the years 2005 and 2009, a total of 608 Taiwanese

patients (Han population) were recruited and analyzed in

this study. The average patient age is 65.32 ± 11.43-years-

old. There were 419 male (130 non-CAD and 289 CAD)

and 189 female (86 non-CAD and 103 CAD) patients. All

the patients were given an informed consent, and were well

told of the study protocol. The study was approved by the

hospital ethnic committee. Blood samples were collected

via venipuncture, and were analyzed by the central

research laboratory. The patients also received echocar-

diographic examination during the study period.

Genomic DNA extraction

Venous blood from each subject was drawn into Vacutainer

tubes containing EDTA and stored at 4 �C. Genomic DNA

was extracted by QIAamp DNA blood mini kits (Qiagen,

Valencia, USA) according to the manufacture’s instruc-

tions. DNA was dissolved in TE buffer [10 mM Tris (PH

7.8), 1 mM EDTA] and then quantitated by a measurement

of OD 260. Final preparation was stored at -20 �C and

used as templates for polymerase chain reaction (PCR).

Polymerase chain reaction-restriction fragment length

polymorphism (PCR–RFLP)

Gene polymorphism for MCP-1-2518G/A and its receptor

CCR-2-V64I were determined by PCR-restriction fragment

length polymorphism assay [33]. Sequences of primers

9024 Mol Biol Rep (2012) 39:9023–9030

123

used for analysis of -2518G/A of MCP-1 genotype were

50-TCTCTCACGCCAGCACTGACC-30 (forward) and 50-GA

GTGTTCACATAGGCTTCTG-30 (reverse) to yield a product

of 234 bps. The CCR-2-V64I polymorphism was amplified

with the following primer: 50-ATTTCCCCAGTACATCCA

CAAC-30 (forward) and 50-CCCACAATGGGAGAGTAA

TAAG-30 (reverse) (317 bp). Polymerase chain reaction was

performed in a 10 lL volume containing 100 ng DNA tem-

plate, 1.0 lL of 109 PCR buffer (Invitrogen, Carlsbad, CA),

0.25 U of Taq DNA polymerase (Invitrogen), 0.2 mM dNTPs

(Promega, Madison, WI), and 200 nM of each primer (MDBio

Inc, Taipei, Taiwan). The PCR cycling conditions were 5 min

at 94 �C followed by 35 cycles of 1 min at 94 �C, 1 min at

57 �C, and 2 min at 72 �C, with a final step at 72 �C for

20 min to allow a complete extension of all PCR fragments. A

10 lL aliquot of PCR product was subjected to digestion at

37 �C for 4 h in a 15 lL reaction containing 5 U of PvuII

(New England Biolabs, Beverly, MA) and 1.5 lL 109 buffer

(New England Biolabs). Digested products were separated on

a 2.5 % agarose gel and then stained with ethidium bromide.

Furthermore, the genotypes determined by PCR–RFLP were

confirmed by DNA sequencing analysis. For each assay, a

negative control (without DNA template) was added to

monitor PCR contamination. To validate results from PCR–

RFLP, around 20 % of assays were repeated and several

cases of each genotype were confirmed by the DNA

sequence analysis.

Statistical analysis

Hardy–Weinberg equilibrium was assessed using a goodness-

of-fit v2 test for biallelic markers. The average age are pre-

sented as the mean ± SE. A Mann–Whitney U test and a

Fisher’s exact test were used to compare the differences of age

as well as demographic characteristics distributions between

non-CAD and patients with CAD, since the small sample size

was present in some categorical variables. The odds ratios

(ORs) with their 95 % confidence intervals (CIs) of the asso-

ciation between genotype frequencies and CAD susceptibility

as well as clinical characteristics were estimated by multiple

logistic regression models. A p value\0.05 was considered

significant. The data were analyzed on SAS statistical software

(Version 9.1, 2005; SAS Institute Inc., Cary, NC).

Results

Table 1 displays the demographic and clinical characteris-

tics of the study participants. There were significant differ-

ences in gender, weight, TIMI risk score for UA/USTEMI

(more than three) [34], smoking habits, aspirin use during the

previous 7 days, recent severe angina (\24 h), cardiac

marker levels, and the presence of atrial fibrillation (AF),

congestive heart failure (CHF), hypertension, and DM

between the CAD patients and non-CAD controls.

Table 1 Demographics and

clinical features of subjects in

Non-CAD and CAD groups.

(n = 608)

1 Data were presented as 1

number (percentage) with v2

test/Fisher exact test2 Mean ± SD with independent

two-sample t test* p \ 0.05

Non-CAD (n = 216) CAD (n = 392) p value

Male 130 (60.2 %) 289 (73.7 %) 0.001*

Age (years) 66.43 ± 12.18 65.73 ± 11.20 0.476

Height (cm) 160.50 ± 8.70 161.79 ± 8.47 0.075

Weight (kg) 64.84 ± 12.82 66.99 ± 12.59 0.045*

BMI (kg/m2) 25.05 ± 3.75 25.56 ± 4.40 0.149

AF positive (%) 57 (26.4 %) 39 (9.9 %) \0.001*

TIMI risk (%) 101 (46.8 %) 232 (59.2 %) 0.003*

Age [65 year (%) 126 (58.3 %) 211 (53.8 %) 0.285

Family history (%) 49 (22.7 %) 83 (21.2 %) 0.665

Hypertension (%) 134 (62.0 %) 289 (73.7 %) 0.003*

Diabetes mellitus (%) 73 (33.8 %) 166 (42.3 %) 0.039*

Active smoker (%) 76 (35.2 %) 171 (46.3 %) 0.043*

Hyperlipidemia (%) 83 (39.0 %) 159 (40.8 %) 0.442

ASA use in the past 7 days (%) 59 (27.4 %) 156 (41.7 %) 0.001*

Recent (\24 h) sever angina (%) 126 (58.3 %) 285 (73.1 %) \0.001*

Cardiac markers elevation (%) 81 (37.5 %) 223 (56.9 %) \0.001*

Stock 27 (13.4 %) 42 (11.2 %) 0.438

CHF 73 (33.8 %) 86 (21.9 %) 0.001*

SBP (mm Hg) 131.33 ± 20.58 132.39 ± 21.27 0.558

DBP (mm Hg) 78.04 ± 14.86 79.11 ± 15.28 0.410

Mol Biol Rep (2012) 39:9023–9030 9025

123

Table 2 presents ORs and 95 % CI of MCP-1-2518 and

CCR-2-V64I G/A genotype distributions associated with

susceptibility to CAD. In our recruited control group, the

frequencies of -2518 G/A of MCP-1 (p = 0.784, v2 value:

0.075) and V64I of CCR-2 (p = 0.158, v2 value: 1.994)

were in Hardy–Weinberg equilibrium, respectively. For

-2518G/A MCP-1 gene polymorphism, GG homozygote

subjects had a 1.629 fold (95 % CI = 1.003–2.644) sig-

nificantly increased risk of CAD compared to A/A homo-

zygote individuals. Individuals with at least one mutated G

allele, A/G or G/G, had a 1.511-fold (95 % CI = 1.006–

2.270) significantly increased risk of CAD compared to

A/A homozygote individuals. For CCR-2-V64I gene

polymorphism, subjects with at least one mutated A allele,

A/G or A/A, had a 1.486-fold (95 % CI = 1.026–2.154)

significantly increased risk of CAD compared to G/G

homozygote individuals. Since both of the MCP-1-2518

and CCR-2-V64I gene polymorphisms lead an individual

to have a high CAD risk were revealed, the combinative

effect of MCP-1-2518 and CCR-2-V64I gene polymor-

phisms was further evaluated. It was found that the subjects

with MCP-1 AG/CCR-2 GG (OR = 1.697; CI = 1.016–

2.834) and MCP-1 GG/CCR-2 GA (OR = 3.621; CI =

1.595–8.223) genotypes also have a higher CAD risk than

those with MCP-1 AA/CCR-2 GG genotype (Table 3).

Table 4 presents the relationships between -2518G/A

MCP-1 and V64I CCR2 gene polymorphisms and demo-

graphic characteristics. There were no significant associa-

tions between gene polymorphisms and CAD demographics.

Tables 5 and 6 display -2518G/A MCP-1 and V64I CCR2

gene polymorphisms, respectively, and clinical features of

CAD. Individuals with at least one mutated G allele, A/G or

G/G, had a 4.254-fold (95 % CI = 1.000–18.097) signifi-

cantly increased risk of AF compared to A/A homozygote

individuals.

Discussion

Gene polymorphisms that regulate expression and bio-

availability of chemokines and their cellular receptors

might affect leukocyte adhesion in inflammatory diseases,

Table 2 Odds ratio (OR) and

95 % confidence interval (CI) of

CAD patients associated with

genotypic frequencies

of MCP-1-2518 and

CCR-2-V64I

The odds ratio (OR) with their

95 % confidence intervals were

estimated by logistic regression* p \ 0.05

Variable Non-CAD (n = 216) (%) CAD (n = 392) (%) OR (95 % CI) p value

MCP-1

A/A 52 (24.1) 68 (17.3) 1.00

A/G 110 (50.9) 209 (53.3) 1.483 (0.947–2.230) 0.087

G/G 54 (25.0) 115 (29.3) 1.629 (1.003–2.644) 0.048*

A/A 52 (24.1) 68 (17.3) 1.00

A/G or G/G 164 (75.9) 324 (82.6) 1.511 (1.006–2.270) 0.046*

CCR-2

G/G 161 (74.5) 260 (66.3) 1.00

A/G 48 (22.2) 113 (28.8) 1.458 (0.986–2.155) 0.058

A/A 7 (3.3) 19 (4.9) 1.681 (0.691–4.087) 0.247

G/G 161 (74.5) 260 (66.3) 1.00

A/G or A/A 55 (25.5) 132 (33.7) 1.486 (1.026–2.154) 0.036*

Table 3 Genotyping the

frequency of MCP-1/CCR-2

genes polymorphisms in 216

non-CAD control and 392

patients with CAD patients

Variable Non-CAD (n = 216) (%) CAD (n = 392) (%) OR (95 % CI) p value

MCP-1/CCR-2

AA/GG 39 (18.1) 42 (10.7) Reference

AA/GA 12 (5.6) 22 (5.6) 1.702 (0.744–3.894) 0.205

AA/AA 1 (0.5) 4 (1.0) 3.714 (0.398–34.689) 0.221

AG/GG 81 (37.5) 148 (37.8) 1.697 (1.016–2.834) 0.042*

AG/GA 26 (12.0) 52 (13.3) 1.857 (0.978–3.527) 0.057

AG/AA 3 (1.4) 9 (2.3) 2.786 (0.703–11.044) 0.133

GG/GG 41 (18.9) 70 (17.9) 1.585 (0.886–2.837) 0.120

GG/GA 10 (4.6) 39 (9.9) 3.621 (1.595–8.223) 0.002*

GG/AA 3 (1.4) 6 (1.5) 1.857 (0.434–7.940) 0.398

9026 Mol Biol Rep (2012) 39:9023–9030

123

including atherosclerosis [35]. Investigators have exten-

sively studied the MCP-1/CCR-2 CC chemokine and its

involvement in atherosclerotic plaque formation [14–17].

However, the effects of the -2518 A/G MCP-1 and V64I

CCR-2 gene polymorphisms on CAD among different

populations remain controversial.

The present study data identified significantly higher

polymorphic frequencies of the MCP-1 heterozygous A/G

and homozygous G/G genotypes in the CAD group com-

pared to the non-CAD group; 82.6 and 75.9 %, respec-

tively (p \ 0.05, OR = 1.511). This finding supports

Szalai et al.’s [21] reports of significantly higher MCP-1-

2518 G/G genotype frequency in CAD patients than in

controls. The present study data (Table 1) also showed a

larger proportion of clinical features, such as TIMI risk and

hypertension, in CAD compared to non-CAD cases, indi-

cating that higher risk scores for TIMI and hypertension are

potential risk factors for CAD. In an Egyptian population,

the MCP-1-2518 A/G and G/G genotype frequencies were

significantly higher in the acute MI group compared to the

control group [29]. Similarly, the hypertension patient

group in a Tunisian population showed a significantly

higher frequency of the G allele compared to the controls

(OR = 0.24 vs. 0.18, 95 % CI 1.46 (1.11–1.91), p \ 0.01)

[22]. Evidence from these previous studies, therefore,

indicates that MCP-1-2518 G/G genotype frequency has

involvement in determining the prevalence of CAD, MI,

and hypertension among different races. However, in a

Japanese population, there were no significant differences

in the MCP-1-2518A/G genotype frequencies between the

Table 4 Comparison of the

demographics features between

two allele of MCP-1-2518 and

CCR-2-V64I for CAD patients

group

MCP-1 A/A (n = 68) MCP-1 A/G ? G/G (n = 324) p value

Age (years) 64.47 ± 12.11 66.00 ± 11.00 0.308

Height (cm) 162.02 ± 10.39 161.74 ± 8.03 0.803

Weight (kg) 68.34 ± 14.03 66.71 ± 12.27 0.329

BMI (kg/m2) 26.17 ± 6.10 25.43 ± 3.95 0.214

SBP (mm Hg) 131.56 ± 20.14 132.59 ± 21.53 0.729

DBP (mm Hg) 77.80 ± 14.45 79.38 ± 15.46 0.447

CCR-2 G/G (n = 260) CCR-2 A/G ? A/A (n = 132)

Age (years) 66.29 ± 11.03 64.64 ± 11.50 0.168

Height (cm) 161.68 ± 8.40 162.00 ± 8.63 0.722

Weight (kg) 66.82 ± 12.71 67.34 ± 12.39 0.698

BMI (kg/m2) 25.48 ± 4.06 25.72 ± 5.02 0.615

SBP (mm Hg) 132.37 ± 21.63 132.43 ± 20.62 0.980

DBP (mm Hg) 79.03 ± 15.95 79.27 ± 13.89 0.886

Table 5 Comparison of the

demographics and pathological

features between two allele of

MCP-1-2518 for CAD patients

group

1 Data were presented as

mean ± SD with independent

two-sample t test

* p \ 0.05

MCP-1 A/A

(n = 68) (%)

MCP-1 A/G ? G/G

(n = 324) (%)

OR (95 % CI) p value

Male 54 (79.4) 235 (72.5) 0.685 (0.362–1.294) 0.241

AF positive (%) 2 (2.9) 37 (11.4) 4.254 (1.000–18.097) 0.034*

TIMI risk (%) 34 (50.0) 198 (61.1) 1.571 (0.929–2.657) 0.090

Age [ 65 year (%) 33 (48.5) 178 (54.9) 1.293 (0.766–2.183) 0.335

Family history (%) 15 (22.1) 68 (21.0) 0.939 (0.499–1.767) 0.844

Hypertension (%) 49 (72.1) 240 (74.1) 1.108 (0.617–1.989) 0.731

Diabetes mellitus (%) 26 (38.2) 140 (43.2) 1.229 (0.719–2.101) 0.450

Active smoker (%) 31 (45.6) 140 (43.2) 0.908 (0.537–1.536) 0.719

Hyperlipidemia (%) 22 (32.4) 137 (42.3) 1.548 (0.890–2.695) 0.120

ASA use in the past

7 days (%)

32 (47.1) 124 (38.3) 0.716 (0.420–1.221) 0.219

Recent (\24 h) sever

angina (%)

51 (75.0) 234 (72.2) 0.825 (0.447–1.522) 0.537

Cardiac markers

elevation (%)

37 (54.4) 186 (57.4) 1.129 (0.668–1.910) 0.650

Stock 3 (4.4) 39 (12.0) 2.810 (0.840–9.399) 0.081

CHF 16 (23.5) 70 (21.6) 0.839 (0.449–1.570) 0.583

Mol Biol Rep (2012) 39:9023–9030 9027

123

MI and control groups (p [ 0.05) [28]. Similarly, in a Han

Chinese group of subjects, Zhang et al. [23] identified no

significant differences in the genotype or allele frequencies

of MCP-1-2518 between the CAD and control groups

(p = 0.581 and 0.310, respectively). Therefore, it seems

that the different results from these two reports and the

present study are not related to the racial/ethnic difference.

Although the reason for those discrepancies is not well-

known, the reporting bias, different inclusion or exclusion

criteria are a potential reason.

In the Framingham Heart Study, results indicated that

the MCP-1-2518 homozygous G/G genotype contributed to

higher basal unstimulated MCP-1 levels (358 ± 10 vs.

328 ± 3 pg/mL; p \ 0.01) and to higher prevalence of MI

(adjusted OR = 2.0; 95 % CI 1.2–3.3; p \ 0.01) [36].

A Japanese study also identified significant increases in

plasma MCP-1 levels in the MCP-1-2518 homozygous

G/G genotype (AA, 166 ± 36 ng/mL; GG ? AG, 184 ±

56 ng/mL; p \ 0.05) [37]. Results from these previous

studies, therefore, indicate the involvement of the MCP-1-

2518 homozygous G/G genotype in CAD prevalence

through elevation of serum MCP-1.

The results of this study indicated that the CCR-2-V64I

A allele associates with the prevalence of CAD. In a Czech

population, MI patients demonstrated increased CCR-2-

V64I A allele frequency compared to the control group

(p \ 0.05) with further analysis revealing association of

the A/A genotype with early onset MI (before or at the age

of 50 years) (p \ 0.01) [32]. A later study by Szalai et al.

[21] suggested that the CCR-2-V64I homozygous G/G

genotype confers some protection against severe CAD. In

contrast to the present study’s results on CCR-2-V64I,

Gonzalez et al.’s [38] findings in a Spanish population,

suggested that the A/A polymorphism has no effects on the

risk of development of MI or on the outcome of coronary

heart disease (p [ 0.05). A genetic investigation in an

Icelandic population also found no significant differences

in the frequencies of CCR-2-V64I between MI patients and

controls (OR = 0.93, 95 % CI 0.71–1.23) [25]. Similarly,

a previous study on CCR-2-V64I and severe human

internal carotid artery stenosis identified no significant

differences in the frequencies of CCR-2-V64I between

patients suffering from severe human internal carotid artery

stenosis and the control group (OR = 1.25, 95 % CI

0.75–2.14, p = 0.35) [39].

In the present study, individuals with at least one

mutated G allele had a 4.254 fold (95 % CI = 1.000–

18.097) significantly increased risk of AF compared to A/A

homozygote individuals. Recently, evidences from a range

of studies indicated the involvement of inflammation in the

pathogenesis of AF [40–44]. Jemaa et al. suggested that

MCP-1/CCR-2 may exert its influence on CAD in associ-

ation with established risk factors, such as age, smoking,

family CAD history, hypertension, and hypercholesterol-

emia [22]. The present study’s data, however, found no

association between other CAD risk factors and MCP-1

and CCR-2 genotype distribution therefore, further inves-

tigation of the hypothesis proposed by Ye et al. and of the

effects of MCP-1-2518A/G and CCR-2-V64I polymor-

phisms on the prevalence of CAD, are warranted.

In conclusion, results from the present study indicated

that MCP-1-2518A/G and CCR-2-V64I polymorphisms

associate with CAD in the Taiwanese population. With

further investigation, MCP-1/CCR-2 might potentially

Table 6 Comparison of

demographics and pathological

features between two allele of

CCR-2-V64I for CAD patients

group

1 Data were presented as

mean ± SD with independent

two-sample t test

* p \ 0.05

CCR-2 G/G

(n = 260) (%)

CCR-2 c A/G ? A/A

(n = 132) (%)

OR (95 % CI) p value

Male 188 (72.3) 101 (76.5) 1.248 (0.768–2.028) 0.371

AF positive (%) 25 (9.6) 14 (10.6) 1.115 (0.559–2.225) 0.757

TIMI risk (%) 157 (60.4) 75 (56.8) 0.862 (0.565–1.320) 0.497

Age [65 year (%) 146 (56.2) 65 (49.2) 0.758 (0.498–1.153) 0.195

Family history (%) 58 (22.3) 25 (18.9) 0.814 (0.482–1.375) 0.440

Hypertension (%) 189 (72.7) 100 (75.8) 1.174 (0.725–1.902) 0.515

Diabetes mellitus (%) 113 (43.5) 53 (40.2) 0.873 (0.570–1.336) 0.531

Active smoker (%) 109 (41.9) 62 (47.0) 1.227 (0.805–1.870) 0.341

Hyperlipidemia (%) 107 (41.2) 52 (39.4) 0.917 (0.598–1.407) 0.693

ASA use in the past

7 days (%)

101 (38.8) 55 (41.7) 1.127 (0.731–1.740) 0.588

Recent (\24 h) sever

angina (%)

186 (71.5) 99 (75.0) 1.161 (0.719–1.874) 0.540

Cardiac markers

elevation (%)

150 (57.7) 73 (55.3) 0.907 (0.595–1.384) 0.652

Stock 27 (10.4) 15 (11.4) 1.137 (0.581–2.224) 0.708

CHF 60 (23.1) 26 (19.7) 0.832 (0.495–1.399) 0.488

9028 Mol Biol Rep (2012) 39:9023–9030

123

represent a future target for therapeutic intervention or

diagnosis of CAD.

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