ADP activates platelets through two G protein-coupled receptors:
Clopidogrel resistance (CR) has been used to reflect the failure of clopidogrel to achieve its effect of antiplatelet aggregation. The underlying mechanism remains unclear. The extrinsic or intrinsic factors may contribute to the variability of platelet activity, including the role of genetic polymorphisms of transporters and enzymes participating in clopidogrel absorption and metabolic transformation and nongenetic causes, such as drug-drug interactions, comorbidities, and age [
DNA methylation is a reliable epigenetic marker and specifically occurs in the context of cytosine-phosphate-guanine (CpG) dinucleotide [
The evidence of the association between DNA methylation and the risk of clopidogrel resistance was scarce. Since multiple single-nucleotide polymorphisms (SNPs) associated with poor activity to clopidogrel [
One hundred and six patients with CAD were collected from the Ningbo No. 1 Hospital. All of them were Han Chinese originated from Ningbo city in Eastern China. The inclusion criteria were as follows. (1) Patients for PCI: with drug-eluting stent, PCI was carried out according to current standard guidelines (ACC/AHA guidelines) through the radial route. (2) All the individuals were administrated with a loading dose of aspirin (300 mg) as well as clopidogrel (300 mg) before PCI. followed by 75 mg of clopidogrel and 100 mg of aspirin daily. (3) Patients of age ≥18 years and ≤80 years were included. The exclusion criteria were as follows: (1) the administration of concomitant glycoprotein IIb/IIIa inhibitor administration, (2) recent or chronic clopidogrel treatment, (3) sudden death, (4) history of bleeding diathesis, (5) haematocrit < 35% or >50%, and (6) total platelet count <150 000
Written informed consent was obtained from all the subjects. The study was approved by the Ethics Committee of Ningbo No. 1 Hospital and conformed with the principles outlined in the Declaration of Helsinki.
Blood samples were obtained overnight fast from the antecubital vein. The serologic markers, such as the concentrations of TG, LDL, ALT, AST, and uric acid in plasma, were measured by the IFCC reference measurement systems. All the tests applied the standard procedures recommended by the manufacturers and then the data were collected and entered into a central database.
As there may be no significant changes of platelet reactivity from days 3 to 5 in AMI patients undergoing PCI [
The VerifyNow
Human genomic DNA was extracted from leucocytes of peripheral blood samples with a commercially available kit (QIAamp DNA Blood Mini Kit, Qiagen, Hilden, Germany). DNA concentrations were quantified by the ultramicronucleic acid ultraviolet tester (NANODROP 1000, Wilmington, USA), and all of them were more than 500 ng/
Bisulfite pyrosequencing technology was applied to determine the methylation levels of 2 CpG dinucleotides on the fragment of
Primers for
Group | DNA sequence |
---|---|
Forward primer |
|
Reverse primer |
|
Sequencing primer |
|
All data for continuous variables were described as means ± standard deviation and skewed variables as the median with interquartile range (IQR). A series of statistical analyses were performed to investigate the association among
For analysis of the association between categorical variables, we used either Pearson’s chi-square or Fisher’s exact test when appropriate.
A two-tailed
From October 2012 to October 2013, a total of 106 CAD patients who met the inclusion criteria were recruited in the current association study. Among them, by the VerifyNow
Characteristics comparison between CR and non-CR.
Cases ( |
Controls ( |
|
|
---|---|---|---|
Male gender, |
35 (71.43) | 46 (80.70) | 0.262 |
Hypertension, |
36 (73.47) | 36 (63.16) | 0.257 |
Diabetes mellitus, |
10 (20.41) | 13 (22.81) | 0.765 |
Dyslipidemia, |
20 (40.82) | 26 (45.61) | 0.619 |
Current smoking, |
19 (38.78) | 21 (36.84) | 0.838 |
Alcohol abuse | 9 (18.37) | 10 (17.54) | 0.912 |
Age, y |
|
|
0.120 |
BMI, kg/m2, |
|
|
0.695 |
Number of stents per patient |
|
|
0.116 |
Left ventricular ejection fraction, % |
|
|
0.115 |
Total cholesterol, mg/dL |
|
|
0.382 |
Triglycerides, mg/dL |
|
|
0.907 |
HDL cholesterol, mg/dL |
|
|
0.608 |
LDL cholesterol, mg/dL |
|
|
0.459 |
GLU, mmol/L |
|
|
0.284 |
HbA1c, % |
|
|
0.972 |
ALT, umol/L |
|
|
0.908 |
AST, umol/L |
|
|
0.977 |
TBIL, umol/L |
|
|
0.464 |
Albumin (A), g/L |
|
|
|
BUN, mmol/L |
|
|
0.618 |
CREA, mmol/L |
|
|
0.807 |
UA, umol/L |
|
|
0.241 |
hsCRP, mg/L |
|
|
0.636 |
PLT, |
|
|
0.248 |
MPV, fL |
|
|
0.058 |
PCT, % |
|
|
0.375 |
PDW, % |
|
|
0.664 |
|
|
|
0.420 |
|
|
|
0.821 |
In this study, we selected a fragment (GRCh37.p13:151103600-151101600) containing 2 CpG dinucleotides. Through bisulfite pyrosequencing assay, we explored the association of
Comparison of
We performed a breakdown analysis by clinical characteristics to evaluate whether the methylation levels of
Comparison of
Alcohol abuse | No alcohol abuse | |||||
---|---|---|---|---|---|---|
Cases ( |
Controls ( |
|
Cases ( |
Controls ( |
|
|
|
|
|
|
|
|
0.897 |
|
|
|
|
|
|
0.469 |
Comparison of
Current smoking | No current smoking | |||||
---|---|---|---|---|---|---|
Cases ( |
Controls ( |
|
Cases ( |
Controls ( |
|
|
|
|
|
|
|
|
0.598 |
|
|
|
0.112 |
|
|
0.384 |
Comparison of
Albumin < 35 | Albumin ≥ 35 | |||||
---|---|---|---|---|---|---|
Cases ( |
Controls ( |
|
Cases ( |
Controls ( |
|
|
|
|
|
|
|
|
0.963 |
|
|
|
0.207 |
|
|
0.872 |
We applied the method of multiple linear regression to explore the effect on DNA methylation from clinical factors. And we observed that the level of DNA methylation might be affected by some clinical marks (Table
Multiple linear regression between
Model |
|
|
|
|
|
|
---|---|---|---|---|---|---|
|
(Constant) | 33.069 | 0.012 | 9.302 | 0.001 | 0.724 |
TBIL | −0.362 | 0.013 | ||||
LEVF | 0.690 | 0.001 | ||||
Albumin | −0.755 | 0.019 | ||||
AST | 0.017 | 0.050 | ||||
|
||||||
|
(Constant) | 21.666 | 0.020 | 10.033 | 0.001 | 0.667 |
LEVF | 0.619 | 0.000a | ||||
Albumin | −0.668 | 0.010 | ||||
AST | 0.017 | 0.014 | ||||
|
||||||
|
(Constant) | 28.035 | 0.004 | 6.193 | 0.005 | 0.251 |
LEVF | 0.318 | 0.026 | ||||
TBIL | −0.314 | 0.049 | ||||
|
||||||
|
(Constant) | −19.001 | 0.109 | 14.345 | 0.000a | 0.840 |
LEVF | 0.643 | 0.000a | ||||
CRP | 0.129 | 0.001 | ||||
BUN | 2.228 | 0.006 | ||||
Triglycerides | 3.205 | 0.044 |
Considering the influence of confounding variables, we carried out logistic regression analysis with nongenetic and genetic factors. The result showed that the quantity of stent and fasting blood-glucose were associated with CR, while the HbAC1 was inversely correlated with it (
Logistic regression analysis with nongenetic and genetic factors in total population.
Variables |
|
|
Exp ( |
95% C.I. |
---|---|---|---|---|
|
−0.141 | 0.096 | 0.869 | 0.74–1.03 |
|
0.169 | 0.142 | 1.184 | 0.95–1.49 |
Age | 0.047 | 0.163 | 1.048 | 0.98–1.12 |
Gender (male) | −0.591 | 0.399 | 0.554 | 0.14–2.19 |
Hypertension | 0.569 | 0.324 | 1.767 | 0.57–5.47 |
DM | −0.979 | 0.282 | 0.376 | 0.06–2.24 |
Dyslipidemia | −0.538 | 0.395 | 0.584 | 0.17–2.02 |
Current smoking | −0.378 | 0.573 | 0.685 | 0.18–2.55 |
Alcohol abuse | 1.010 | 0.214 | 2.746 | 0.56–13.51 |
BMI | −0.073 | 0.514 | 0.930 | 0.75–1.16 |
Stent | 0.865 |
|
2.374 | 1.24–4.53 |
LEVF | −0.035 | 0.368 | 0.965 | 0.89–1.04 |
TC | 0.093 | 0.847 | 1.097 | 0.43–2.82 |
Triglycerides | 0.081 | 0.770 | 1.084 | 0.63–1.86 |
HDL | −1.283 | 0.308 | 0.277 | 0.02–3.27 |
LDL | −0.408 | 0.481 | 0.665 | 0.21–2.07 |
GLU | 0.681 |
|
1.976 | 1.15–3.39 |
HbAC1 | −0.907 |
|
0.404 | 0.19–0.88 |
ALT | −0.009 | 0.541 | 0.992 | 0.97–1.02 |
AST | 0.002 | 0.366 | 1.002 | 1.00–1.01 |
TBIL | −0.036 | 0.357 | 0.965 | 0.89–1.04 |
A | −0.091 | 0.264 | 0.913 | 0.78–1.07 |
BUN | −0.161 | 0.292 | 0.851 | 0.63–1.15 |
CR | −0.004 | 0.825 | 0.996 | 0.97–1.03 |
UA | 0.002 | 0.455 | 1.002 | 1.00–1.01 |
CRP | −0.007 | 0.677 | 0.993 | 0.96–1.03 |
PLT | 0.008 | 0.712 | 1.008 | 0.97–1.05 |
MPV | 0.380 | 0.507 | 1.462 | 0.48–4.50 |
PCT | −13.635 | 0.639 | 0.000 | 0.00–6.71 |
PDW | −0.183 | 0.736 | 0.832 | 0.29–2.42 |
Constant | 8.480 | 0.469 | 4815.697 |
Logistic regression analysis with nongenetic and genetic factors in subgroup of alcohol abuse.
Variables |
|
|
Exp ( |
95% C.I. |
---|---|---|---|---|
|
−0.362 | 0.242 | 0.697 | 0.38–1.28 |
|
0.087 | 0.841 | 1.091 | 0.47–2.55 |
Current smoking | −0.512 | 0.845 | 0.599 | 0.00–101.18 |
Albumin | −0.046 | 0.799 | 0.955 | 0.67–1.36 |
Stent | −0.549 | 0.567 | 0.578 | 0.09–3.77 |
GLU | −0.212 | 0.884 | 0.809 | 0.05–13.84 |
HbAC1 | −0.134 | 0.943 | 0.875 | 0.02–34.27 |
Constant | 17.144 | 0.134 |
|
Logistic regression analysis with nongenetic and genetic factors in subgroup of current smoking.
Variables |
|
|
Exp ( |
95% C.I. |
---|---|---|---|---|
|
−0.107 | 0.056 | 0.898 | 0.81–1.00 |
Alcohol abuse | 0.291 | 0.707 | 1.338 | 0.29–6.12 |
Albumin | −0.088 | 0.241 | 0.916 | 0.79–1.06 |
Stent | 0.430 | 0.328 | 1.537 | 0.65–3.64 |
GLU | 0.577 | 0.150 | 1.781 | 0.81–3.91 |
HbAC1 | −0.847 | 0.128 | 0.429 | 0.14–1.28 |
Constant | 8.942 | 0.039 | 7648.274 |
Logistic regression analysis with nongenetic and genetic factors in subgroup of Albumin < 35.
Variables |
|
|
Exp ( |
95% C.I. |
---|---|---|---|---|
|
−0.414 | 0.199 | 0.661 | 0.35–1.24 |
Current smoking | −9.623 | 0.922 | 0.000 | 0.00–2.95 |
Alcohol abuse | 4.505 | 0.965 | 90.429 | 0.00–9.00 |
Stent | 0.803 | 0.711 | 2.233 | 0.03–157.51 |
GLU | −2.065 | 0.340 | 0.127 | 0.00–8.79 |
HbAC1 | 1.789 | 0.573 | 5.986 | 0.01–3041.06 |
Albumin | −1.016 | 0.307 | 0.362 | 0.05–2.55 |
Constant | 49.113 | 0.265 |
|
Since various trails had been keen on the single-nucleotide polymorphisms, some had averted their sight to epigenetics, such as miRNA, DNA methylation. Recently, we have found that aberrant methylation is interpreted to take part in the occurrence and development of diseases including colorectal cancer [
In this study, the relationship between
Although no public evidence had shown the value of Albumin and alcohol abuse would influence the clopidogrel responding, a new meta-analysis reported that the clinical benefit of clopidogrel treatment in reducing cardiovascular events (including death, myocardial infarction, and stroke) was discovered primarily in smokers, with little benefit in nonsmokers [
Additionally, we have to observe the influence of confounding variables on methylation. In our study, some clinical factors (e.g., TBIL, LEVF, Albumin, AST CRP, BUN, and Triglycerides) may influence the level of methylation in a particular population, though the
Furthermore, we should focus on the gene-environment interaction. Increasing evidence manifested that environmental and lifestyle factors could influence epigenetic mechanisms, though few were involved in cardiology. For instance, one recent study, which evaluated global DNA methylation from buccal cells of children exposed to smoking, demonstrated hypomethylation of LINE-1 repetitive elements [
Meanwhile, a large quantity of research indicates that some other extrinsic factors, comorbidities, for instance, might also contribute to clopidogrel resistance. We used the logistic regression analysis with confounding factors. In the total population, the quantity of stent, fasting blood-glucose, and lower HbAC1 were the predictors of CR. However, if we applied the logistic regression analysis in subgroups (Albumin < 35, current smoking, and alcohol abuse), all of them, including genetic and nongenetic causes, association were not found. Comorbidities, such as diabetes mellitus (including the type of diabetes [
Although considerable efforts have been made, there are some limitations inherent in our study. Firstly, the sample size is relatively small. Future investigation with larger samples can be arranged for further assessment. Secondly, for the whole promoter of
In summary, our study indicates that lower
The authors declare that there is no conflict of interests regarding the publication of this paper.
Jia Su, Hanbin Cui, Jin Xu, and Xiaomin Chen contributed to the conception of the study; Jia Su, Xiaojing Li, Weiping Du, Xiaohong Fei, Junsong Liu, Shaoyi Lin, Jian Wang, Wenyuan Zheng, Jinyan Zhong, and Lulu Zhang helped with sample and data collection; Jia Su, Xiaojing Li, Yahui Liu, Yaqing Wang, and Maoqing Tong performed the platelet function measurement and bisulfite pyrosequencing; Jia Su, Qinglin Yu, and Haojun Song carried out the analysis of the data and interpretation of the data. All the authors contributed to the writing, discussion, and approval of the paper.