Impact of IRS-1 rs956115 and CYP2C19 rs4244285 Genotypes on Clinical Outcome of Patients Undergoing PCI

Impact of IRS-1 rs956115 and CYP2C19 rs4244285 Genotypes on Clinical Outcome of Patients Undergoing PCI | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Original investigation Impact of IRS-1 rs956115 and CYP2C19 rs4244285 Genotypes on Clinical Outcome of Patients Undergoing PCI Jiaxin Zong, Yingdan Tang, Tong Wang, Inam Ullah, Ke Xu, Jing Wang, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1100332/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background insulin receptor substrate-1 (IRS-1) rs956115 is associated with vascular risk in patients with coronary artery disease (CAD) and concomitant diabetes. CYP2C19 rs4244285 modulates clopidogrel responsiveness and predicts outcome of CAD. We designed this study to explore the association between IRS-1 rs956115, CYP2C19 rs4244285, and platelet reactivity as well as 1-year outcome in patients with CAD undergoing percutaneous coronary intervention (PCI). Methods IRS-1 rs956115, CYP2C19 rs4244285 genotypes and platelet reactivity were assessed in 1611 post-PCI patients. Major adverse cardiovascular events (MACE) which were defined as a composite of cardiovascular death, myocardial infarction and ischemic stroke over 1-year were evaluated. One-way ANOVA was used to compare the platelet reactivity among different genotypes of rs956115 and rs4244285. Multivariable Cox proportional hazard model analysis was used to estimate the association between genotypes of rs956115 and rs4244285 and risk of MACE. Results At 1 month, patients with rs956115 CG genotype had significantly lower level of residual ADP-induced platelet aggregation (PL ADP ) than those with CC genotype. PL ADP significantly increased with the number of rs4244285 A alleles. Patients with rs956115 CG or GG genotype had a 2.09-fold higher risk of MACE than those with CC genotype (adjusted HR=2.09; 95%CI:1.04-4.19; P =0.0376), and those with rs4244285 GA genotype had a 2.19-fold higher risk than GG homozygotes (adjusted HR=2.19; 95%CI:1.13-4.24; P =0.0200). There was no significant difference in risk between AA and GG homozygotes. No interaction between rs956115 and rs4244285 was observed. Conclusions In post-PCI patients, rs956115 GG/CG and rs4244285 GA genotypes were associated with 2.09- and 2.19-fold cardiovascular risks respectively at 1-year follow-up. The effect of rs956115 appeared to be independent of known clinical predictors, while that of rs4244285 GA could be mediated by lower clopidogrel response. Trial registration: Pharmacogenetic and Pharmacokinetic Study of Clopidogrel (PPSC), NCT01968499. Registered October 17, 2013 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT01968499?term=NCT01968499&draw=1&rank=1 Cardiac & Cardiovascular Systems coronary artery disease CYP2C19 rs4244285 IRS-1 rs956115 percutaneous coronary intervention platelet reactivity. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Insulin receptor substrate-1 (IRS-1), a ligand of insulin receptor tyrosine kinase, plays a central role in insulin signal transduction system ( 1 , 2 ). Dysregulation of IRS-1 has been suggested as a common mechanism underlying insulin resistance which may lead to high platelet reactivity and low response to antiplatelet treatment in patients with type 2 diabetes mellitus (DM) ( 3 , 4 ). CYP2C19 is one of the isoenzymes of hepatic cytochrome P450 (CYP450) system which plays a key role in the bioactivation of clopidogrel( 5 , 6 ). Carriers of CYP2C19 loss of function *2 (rs4244285) generate less amounts of active metabolite of clopidogrel than wild-type homozygotes, which subsequently resulting in a lower clopidogrel responsiveness and an increased risk of major adverse cardiac events in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI)( 7 – 9 ). This study examined the association between IRS-1 rs956115, CYP2C19 rs4244285 and platelet reactivity as well as major adverse cardiovascular events (MACE) in patients with CAD who had undergone PCI and were treated with aspirin and clopidogrel. Methods The data that support the findings of this study are available from the corresponding author on reasonable request. Study Design This was a prospective single-center cohort study conducted in the First Affiliated Hospital of Nanjing Medical University, Nanjing, China. Complying with the Helsinki declarations and local regulations, the study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from each patient. The inclusion criteria were patients with CAD undergoing urgent or elective coronary stent implantation who were over 18 years old and planning to take dual antiplatelet treatment (DAPT) with clopidogrel 75 mg and aspirin 100 mg once daily for at least 1 year. Patients who met any of the following criteria were excluded: (1) allergic or intolerant to aspirin or clopidogrel; (2) at high risk of bleeding (e.g., platelet count <80×10 9 /L, known bleeding diathesis, active peptic ulcer, or with a history of cerebral hemorrhage within 1 year); and (3) planning to take drugs that could potentially interfere with the antiplatelet effects of aspirin (e.g., non-steroidal anti-inflammatory drugs) or clopidogrel (e.g., CYP3A inhibitors or CYP3A inducers). Baseline demographic and clinical characteristics, as well as medical and interventional treatments, were collected on a pre-specified case report form. Sample Collection and Preparation After receiving >5 days of aspirin and clopidogrel, blood was collected 2 hours post dosing (about 10am) from each patient into one 2-mL BD Vacutainer tube (Becton, Dickinson and Company, Franklin Lakes, NJ) containing 3.6 mg K2 EDTA and two 2-mL BD vacutainer tubes with 0.105 mol/L buffered sodium citrate (3.2%). Blood samples were transferred to the central laboratory within 1 hour after collection. Samples in EDTA tubes were frozen at −80°C for genotyping, whereas citrated samples were immediately processed for platelet aggregation studies. After centrifuging the citrated sample at 200g for 8 minutes at 22°C, platelet-rich plasma was carefully separated, and the remaining sample was centrifuged at 2465g for another 10 minutes to obtain platelet-poor plasma. The platelet count in platelet-rich plasma was standardized by addition of platelet-poor plasma to achieve a count of 250×10 9 /L. Platelet aggregation tests by light transmission aggregometry were performed within 3 hours of platelet-rich plasma preparation (10). At 1-month follow-up, patients received repeat blood collection for measurement of platelet reactivity as performed at baseline. Platelet Reactivity Assay Platelet aggregation testing was performed using a Chronolog Model 700 aggregometer (Chronolog Corporation, Havertown, PA). Immediately after preparation of platelet-rich plasma, 500 μL was transferred into each of the 2 test tubes, with 500 μL platelet-poor plasma as control. Platelet aggregation was induced using adenosine diphosphate (ADP) or arachidonic acid (AA) as agonists with final concentrations of 5 umol/L and 1 mmol/L, respectively. The ADP and AA-induced platelet aggregations (PL ADP and PL AA , respectively) were recorded using the maximum platelet aggregation within 8 minutes. Genotype Analysis IRS-1 (rs956115, C>G) and CYP2C19*2 (rs4244285, G>A) were genotyped using a custom-by-design improved multiplex ligation detection reaction technique (Genesky Biotechnologies Inc, Shanghai, China) based on the highly specific double ligation and the multiplex fluorescence polymerase chain reaction (11). For quality control, repeated testing was performed randomly in 5% of samples with high DNA quality. Clinical Follow-up Patients were followed-up for 12 months by 2 investigators who were blinded to the results of platelet reactivity testing and genotyping. The patients were followed in the clinic or by telephone if they were unable to attend the clinic. The primary endpoint was defined as the occurrence of MACE, a composite of cardiovascular death, myocardial infarction, and ischemic stroke within 12 months after PCI. The cardiovascular events in this study were defined according to the American College of Cardiology 2001 (12). Statistical Analysis Continuous variables were described as mean ± standard deviation (SD) or median with interquartile range (IQR) when data did not follow a normal distribution, and differences between groups were analyzed by t test or nonparametric test. Categorized variables were expressed as numbers and percentages and were analyzed by χ 2 test or Fisher exact method. One-way ANOVA was used to compare the platelet reactivity among different genotypes of rs956115 and rs4244285. Multivariable Cox proportional hazard model analysis was used to estimate the association between genotypes of rs956115 and rs4244285 and risk of MACE reported as hazard ratio (HR) and 95% confidence intervals (CI). The model was adjusted for clinical covariables including age, previous myocardial infraction (MI), hypertension, diabetes mellitus, smoking status, previous PCI, left ventricular ejection fraction (LVEF), serum creatinine, low density lipoprotein, and diagnosis. All analyses were performed using SAS, version 9.4 (SAS Institute, Cary, North Carolina) and figures were developed using R, version 3.2.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed P value of <0.05 was considered statistically significant. Results From Mar 2011 to September 2016, 2213 patients were consecutively screened, among whom 1614 patients who met the inclusion and the exclusion criteria were enrolled. Of the 1614 enrolled patients, 3 were not included in the final analysis due to unsatisfactory blood sample quality. All the remaining patients completed the genotype assessment and 1-year clinical follow-up. Platelet aggregation testing were performed in 1175 patients at baseline and in 624 patients at 1-month follow-up (Figure 1 ). Patients’ Characteristics The baseline characteristics of patients included in this study are summarized in Table 1 . Compared with patients who did not experience MACE, those who experienced MACE were older [69.00 (14.50) vs. 64.00 (15.00), P =0.0069], more commonly had reduced LVEF (25.0% vs . 7.66%, P <0.001) and history of ST-segment-elevation myocardial infarction (STEMI) or non-ST-segment elevation acute coronary syndromes (NSTE-ACS) (63.63% vs. 42.44%, P =0.0010). Table 1 Baseline Characteristics of Patients Grouped by the Occurrence of MACE Variables MACE (n=44) MACE free (n=1, 567) P value Age, median (IQR), years 69.00 (14.50) 64.00 (15.00) 0.0069 Sex, No. (%) 0.2966 Female 8(18.18) 393(25.08) Male 36(81.82) 1174(74.92) Previous MI, No. (%) 0.7166 No 42(95.45) 1499(95.66) Yes 2(4.55) 68(4.34) Hypertension, No. (%) 0.4109 No 12(27.27) 520(33.18) Yes 32(72.73) 1047(66.82) Diabetes Mellitus, No. (%) 0.3568 No 30(68.18) 1165(74.35) Yes 14(31.82) 402(25.65) Smoking, No. (%) 0.3503 No 24(54.55) 743(47.42) Yes 20(45.45) 824(52.58) Previous PCI, No. (%) 0.4246 No 42(95.45) 1424(90.87) Yes 2(4.55) 143(9.13) LVEF, No. (%) <0.001 ≥ 55% 33(75.00) 1447(92.34) 133µmol/L 2(4.55) 30(1.91) Low density lipoprotein, No. (%) 0.5350 ≥ 1.8mmol/L 36(81.82) 1335(85.19) < 1.8mmol/L 8(18.18) 232(14.81) Diagnosis, No. (%) 0.0010 SA 16(36.36) 902(57.56) NSTE-ACS 12(27.27) 412(26.29) STEMI 16(36.36) 253(16.15) Values are presented as median (IQR) or number of patients (percentage) as appropriate. P values were calculated with the use of t test or \({\chi }^{2}\) test as appropriate. Abbreviations: LVEF. left ventricular ejection fraction; MACE. major adverse cardiovascular events, including cardiovascular death, myocardial infarction and ischemic stroke; MI. myocardial infarction; NSTE-ACS. non-ST-segment elevation acute coronary syndromes; PCI. percutaneous coronary intervention; SA. stable angina pectoris; STEMI. ST-segment-elevation myocardial infarction. On-Treatment Platelet Reactivity and Genotypes. The baseline and 1-month PL ADP were (29.88±14.34)% and (26.27±15.10)%, respectively. There was no significant difference in PL ADP among different rs956115 genotypes at the baseline assessment ( F =0.20, P =0.8200, Figure 2 A). At 1-month follow-up, PL ADP was significantly different among the three genotypes ( F =3.28, P =0.0381, Figure 2 A). CG genotype was associated with a significantly lower PL ADP compared with CC genotype ( P =0.0158, Figure 2 A). Regarding PL AA , there were no significant difference among the three genotypes of rs956115 either at baseline ( F =2.73, P =0.0656, Figure S1A ) or at 1-month follow-up ( F =0.20, P =0.8180, Figure S1A ). For rs4244285, PL ADP were significantly different among the three genotypes at baseline ( F =53.27, P <0.001, Figure 2 B) and 1-month follow-up ( F =12.07, P <0.001, Figure 2 B). By pairwise comparisons, the platelet reactivities corresponding to different genotypes of rs4244285 were all significantly different except the comparison between GA and AA at 1-month follow-up ( P =0.4392, Figure 2 B). As shown in Figure 2 B, the platelet reactivity increased with the number of the A alleles of rs4244285. Regarding PL AA , there were no significant difference among the three genotypes of rs4244285 either at baseline ( F =0.38, P =0.6870, Figure S1B ) or at 1-month follow-up ( F =0.78, P =0.4590, Figure S1B ). Association between IRS/CYP2C19 Genotypes and Cardiovascular Outcomes. A total of 44 patients experienced MACE, including 15 cardiac deaths, 16 nonfatal myocardial infarctions, and 13 ischemic strokes. For rs956115, patients with CG or GG genotypes had a 1.99-fold higher MACE risk than those with CC homozygote (dominant model, adjusted HR=1.99, 95%CI: 1.00-3.98, P =0.0499; additive model, adjusted HR=1.95, 95%CI: 1.05-3.61, P =0.0341; Table 2 ). When further adjusted for rs4244285 genotypes, patients with CG or GG genotypes had a 2.09-fold higher MACE risk than those with CC homozygote (dominant model, adjusted HR=2.09, 95%CI: 1.04-4.19, P =0.0376; additive model, adjusted HR=2.04, 95%CI: 1.10-4.19, P =0.0244; Table 2 and Figure 3 A). There was no significant difference in risk of MACE risk between CG and CC genotypes (adjusted HR=1.91, 95%CI: 0.94-3.88, P =0.0751) or between GG and CC genotypes (adjusted HR=4.23, 95%CI: 0.55-32.29, P = 0.1643) (Table 2 ). Table 2 MACE risk by Multi-Cox regression SNP Gene Geno-type MACE N Censored N Comparison Unadjusted model Adjusted model a Adjusted model b HR (95%CI) P value HR (95%CI) P value HR (95%CI) P value rs956115 IRS1 CC 32 1245 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) CG 11 305 CG vs. CC 1.66(0.82,3.34) 0.1571 1.91(0.94,3.88) 0.0751 1.99(0.98,4.08) 0.0586 GG 1 17 GG vs. CC 2.65(0.36,19.53) 0.3377 4.23(0.55,32.29) 0.1643 4.70(0.62,35.84) 0.1351 Dominant 1.71(0.87,3.38) 0.1211 1.99(1.00,3.98) 0.0499 2.09(1.04,4.19) 0.0376 Recessive 2.35(0.32,17.11) 0.3992 3.58(0.48,26.96) 0.2157 3.91(0.52,29.33) 0.1851 Additive 1.65(0.91,3.00) 0.1013 1.95(1.05,3.61) 0.0341 2.04(1.10,3.81) 0.0244 rs4244285 CYP2C19 GG 14 712 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) GA 28 666 GA vs. GG 2.04(1.07,3.90) 0.0303 2.13(1.10,4.12) 0.0248 2.19(1.13,4.24) 0.0200 AA 2 189 AA vs. GG 0.60(0.14,2.65) 0.5010 0.58(0.13,2.61) 0.4814 0.58(0.13,2.60) 0.4787 Dominant 1.76(0.93,3.33) 0.0843 1.81(0.94,3.49) 0.0759 1.85(0.96,3.56) 0.0666 Recessive 0.40(0.10,1.65) 0.2049 0.37(0.09,1.56) 0.1767 0.37(0.09,1.53) 0.1702 Additive 1.17(0.75,1.82) 0.4853 1.16(0.74,1.81) 0.5114 1.17(0.75,1.81) 0.4936 a Model adjusted for clinical covariates, including age, previous MI, hypertension, diabetes mellitus, LVEF, serum creatinine, diagnosis, low density lipoprotein, smoking status, previous PCI. b Model adjusted for rs4244285/ rs956115 and clinical covariates, including age, previous MI, hypertension, diabetes mellitus, LVEF, serum creatinine, diagnosis, low density lipoprotein, smoking status, previous PCI. Dominant model: CG and GG vs. CC. Recessive model: GG vs. CC and CG. Addictive model: the number of risk alleles is proportional to the risk of MACE. Abbreviations: CI, confidence intervals; HR, hazard ratio; Other abbreviations as in Table 1 . For rs4244285, patients with GA genotype had a 2.13-fold higher MACE risk than those with GG genotype (adjusted HR=2.13, 95%CI: 1.10-4.12, P =0.0248; Table 2 ). Patients with AA genotype showed no increased MACE risk to GG genotype (adjusted HR=0.58; 95%CI:0.13-2.60; P=0.4787). When further adjusted for rs956115 genotypes, patients with GA genotype had a 2.19-fold higher risk than those with GG genotype (adjusted HR=2.19, 95%CI: 1.13-4.24, P =0.0200; Table 2 and Figure 3 B). No significant difference of MACE risk was found while using either dominant (P=0.0666; Table 2 ) or additive model (P=0.4936; Table 2 ). Interaction Analysis Among patients with GG genotype of rs4244285, those who had CG or GG genotype of rs956115 presented a 4.85-fold higher MACE risk than those who had CC genotype (adjusted HR=4.85, P =0.0081; Figure 4 ). By comparison, among patients with non-GG genotype of rs4244285, those who had CG or GG genotype of rs956115 presented a 1.40-fold higher risk than those who had CC genotype (adjusted HR=1.40, P =0.4764; Figure 4 ). The interaction between rs956115 and rs4244285 was none-statistically significant ( P =0.1453; Figure 4 ). Association Of Rs956115 With Mace In Subgroup Analysis We performed multivariable Cox-regression analysis for rs956115 in different patient subgroups (Figure 5 ). The association between rs956115 genotypes and MACE remained statistically significant in subgroup of normal serum creatinine (adjusted HR=2.09, 95%CI: 1.04-4.18) (Figure 5 ). Although the adjusted HR between CG or GG and CC genotypes of rs956115 did not reach statistically significant in the diabetes subgroup (Figure 5 ), the dominant model HR of MACE for patients with CG or GG genotype of rs956115 tended to be similar across subgroups. No significant interactions were observed in any of those subgroups except LVEF subgroup (Interaction P =0.0006) (Figure 5 ). Discussion This study examined the impacts of IRS-1 rs956115 and CYP2C19 rs4244285 polymorphisms on clinical outcome of patients undergoing PCI and receiving DAPT treatment and found that G allele carriers of IRS-1 rs956115 had a 2.09-fold higher risk of MACE compared with non-carriers at 1-year follow-up. The rs4244285 GA genotype had a 2.19-fold higher risk than GG homozygotes. The effect of rs956115 was independent to known clinical covariables, while that of rs4244285 GA could be mediated by lower clopidogrel response. Angiolillo et al. examined 7 single nucleotide polymorphisms (SNPs) of IRS-1 and found that rs956115 polymorphism was associated with a hyperreactive platelet phenotype and adverse cardiovascular outcomes in type-2 DM Caucasian patients concomitant with coronary artery disease (CAD) ( 13 ). However, uncertainty remains about the effects of IRS-1 rs956115 polymorphism on platelet function and cardiovascular outcome in non-selective CAD patients. In this study, we found that rs956115 G allele was an independent prognostic factor of adverse cardiovascular outcomes in non-selective CAD patients, irrespective of CYP2C19*2 (rs4244285) polymorphism, diabetes mellitus and other known risk factors. Although rs956115 G allele didn’t show a significant correlation with MACE in the subgroup of diabetes mellitus, our results showed the consistent tendency of almost all subgroups as shown in Figure 5 . Regarding the underlying mechanism, Angiolillo et al suggested that rs956115 polymorphism was associated with a hyperactive platelet phenotype in Caucasian type-2 DM patients ( 13 ). However, in a later study by Zhang et al , no association was observed between rs956115 polymorphism and platelet function profile ( 14 ). Our results were in consistent with that of Zhang et al in a larger Chinese population, showing no significant difference in AA or ADP-induced platelet aggregation at baseline among different IRS-1 rs956115 genotypes. Moreover, ADP-induced platelet aggregation was even lower in rs956115 CG genotype compared with CC genotype at 1-month follow-up. Along with the results of Zhang’s study, we suggest that the association between IRS-1 rs956115 polymorphisms and risk of MACE cannot be explained by impaired platelet reactivity to either clopidogrel or aspirin. Theoretically, IRS-1 is one of the central nodes in insulin signaling network ( 15 ). It has been reported that IRS-1 is necessary for insulin-stimulated activation of phosphatidylinositol 3 kinase (PI3K)/AKT pathway and subsequent enhanced production of nitric oxide (NO) in endothelial cells ( 16 ), which plays a critical role in maintaining cardiovascular homeostasis ( 17 ). Previous studies have demonstrated that functional variants of IRS-1 directly impaired insulin regulated NO synthesis in cultured human endothelial cells ( 18 , 19 ). Considering the pivotal role of IRS-1 in PI3K/AKT signaling pathway of insulin, it may be reasonable to assume IRS-1 rs956115 polymorphism affects the same process or an unknown pathway and consequently impacts the clinical outcome of CAD patients. Our results were consistent with previously reports and further confirmed that CYP2C19*2 (rs4244285) loss of function polymorphism is a strong predictor of impaired clopidogrel response and adverse clinical outcomes ( 7 – 9 ). This consistency, in turn, enhances the credibility of our results on rs956115. Meanwhile, from the interaction analysis, we did not find a statistically significant interaction between IRS-1 rs956115 and CYP2C19 rs4244285 polymorphism, which proved IRS-1 rs956115 G allele to be an independent risk factor of MACE in CAD patients after PCI. Conclusions IRS-1 rs956115 G allele significantly increased the cardiovascular risk of post-PCI patients by 2.09-fold at 1-year follow-up, which was independent to CYP2C19 rs4244285 genotypes, pharmacological platelet response and known clinical covariables. Declarations Ethics approval and consent to participate Complying with the Helsinki declarations and local regulations, the study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from each patient. Consent for publication As stated above, informed consent on participation and publication was obtained from all participants. Availability of data and materials The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work was supported by a grant from the National Natural Science Funding of China (81170181, 82170351), the Jiangsu Province’s Key Provincial Talents Program (ZDRCA2016013), the Second Level of 333 High Level Talent Training Project in Jiangsu Province (BRA2019099), Special Fund for Key R & D Plans (Social Development) of Jiangsu Province (BE2019754), and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutes (PAPD). Authors’ contributions CL contributed to the conceptualization and supervision of the study, review and editing the manuscript. YZ contributed to the supervision of the study, interpretation of the data, review and editing the manuscript. JZ contributed to the investigation of the patients, writing the original draft. YT contributed to interpretation of the data, writing the original draft. IU, TW, KX, PC, ZC, JW, TZ, JC, JL, FW, LY, YF, LS, XG contributed to the investigation of the patients. All authors read and approved the final manuscript. Acknowledgements Not applicable. References DeFronzo RA, Tripathy D. Skeletal muscle insulin resistance is the primary defect in type 2 diabetes. Diabetes Care. 2009;32 Suppl 2:S157-63. Copps KD, White MF. Regulation of insulin sensitivity by serine/threonine phosphorylation of insulin receptor substrate proteins IRS1 and IRS2. Diabetologia. 2012;55(10):2565-82. Randriamboavonjy V, Fleming I. Insulin, insulin resistance, and platelet signaling in diabetes. Diabetes Care. 2009;32(4):528-30. Ferreira IA, Mocking AI, Feijge MA, Gorter G, van Haeften TW, Heemskerk JW, et al. Platelet inhibition by insulin is absent in type 2 diabetes mellitus. Arterioscler Thromb Vasc Biol. 2006;26(2):417-22. Kazui M, Nishiya Y, Ishizuka T, Hagihara K, Farid NA, Okazaki O, et al. Identification of the human cytochrome P450 enzymes involved in the two oxidative steps in the bioactivation of clopidogrel to its pharmacologically active metabolite. Drug Metab Dispos. 2010;38(1):92-9. Cattaneo M. Response variability to clopidogrel: is tailored treatment, based on laboratory testing, the right solution? J Thromb Haemost. 2012;10(3):327-36. Hulot JS, Bura A, Villard E, Azizi M, Remones V, Goyenvalle C, et al. Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. Blood. 2006;108(7):2244-7. Hochholzer W, Trenk D, Fromm MF, Valina CM, Stratz C, Bestehorn H-P, et al. Impact of Cytochrome P450 2C19 Loss-of-Function Polymorphism and of Major Demographic Characteristics on Residual Platelet Function After Loading and Maintenance Treatment With Clopidogrel in Patients Undergoing Elective Coronary Stent Placement. Journal of the American College of Cardiology. 2010;55(22):2427-34. Mega JL, Close SL, Wiviott SD, Shen L, Hockett RD, Brandt JT, et al. Cytochrome p-450 polymorphisms and response to clopidogrel. N Engl J Med. 2009;360(4):354-62. Li C, Hirsh J, Xie C, Johnston MA, Eikelboom JW. Reversal of the anti-platelet effects of aspirin and clopidogrel. J Thromb Haemost. 2012;10(4):521-8. Li HM, Zhang TP, Leng RX, Li XP, Wang DG, Li XM, et al. Association of leptin and leptin receptor gene polymorphisms with systemic lupus erythematosus in a Chinese population. J Cell Mol Med. 2017;21(9):1732-41. Cannon CP, Battler A, Brindis RG, Cox JL, Ellis SG, Every NR, et al. American College of Cardiology key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes. A report of the American College of Cardiology Task Force on Clinical Data Standards (Acute Coronary Syndromes Writing Committee). J Am Coll Cardiol. 2001;38(7):2114-30. Angiolillo DJ, Bernardo E, Zanoni M, Vivas D, Capranzano P, Malerba G, et al. Impact of Insulin Receptor Substrate-1 Genotypes on Platelet Reactivity and Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus and Coronary Artery Disease. Journal of the American College of Cardiology. 2011;58(1):30-9. Zhang D, Zhang X, Liu D, Liu T, Cai W, Yan C, et al. Association between insulin receptor substrate-1 polymorphisms and high platelet reactivity with clopidogrel therapy in coronary artery disease patients with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:50. Taniguchi CM, Emanuelli B, Kahn CR. Critical nodes in signalling pathways: insights into insulin action. Nat Rev Mol Cell Biol. 2006;7(2):85-96. Montagnani M, Ravichandran LV, Chen H, Esposito DL, Quon MJ. Insulin receptor substrate-1 and phosphoinositide-dependent kinase-1 are required for insulin-stimulated production of nitric oxide in endothelial cells. Mol Endocrinol. 2002;16(8):1931-42. Tousoulis D, Kampoli AM, Tentolouris C, Papageorgiou N, Stefanadis C. The role of nitric oxide on endothelial function. Curr Vasc Pharmacol. 2012;10(1):4-18. Federici M, Pandolfi A, De Filippis EA, Pellegrini G, Menghini R, Lauro D, et al. G972R IRS-1 variant impairs insulin regulation of endothelial nitric oxide synthase in cultured human endothelial cells. Circulation. 2004;109(3):399-405. Huang C, Li G, Dong H, Sun S, Chen H, Luo D, et al. Arg⁹⁷² insulin receptor substrate-1 inhibits endothelial nitric oxide synthase expression in human endothelial cells by upregulating microRNA-155. Int J Mol Med. 2015;36(1):239-48. Supplementary Files FigureS1.tif Figure S1. Platelet reactivities (PLAA) in patients with different genotypes of rs956115 and rs4244285 (A) Boxplot of rs956115 and PLAA at baseline and 1 month; (B) Boxplot of rs4244285 and PLAA at baseline and 1 month. Abbreviations: PLAA, arachidonic acid induced platelet aggregation. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1100332","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Original investigation","associatedPublications":[],"authors":[{"id":65940959,"identity":"c99629a9-942f-4a71-aee2-b8018cd73267","order_by":0,"name":"Jiaxin Zong","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiaxin","middleName":"","lastName":"Zong","suffix":""},{"id":65940960,"identity":"46fbc066-b27c-4975-92e6-b009378b1031","order_by":1,"name":"Yingdan Tang","email":"","orcid":"","institution":"Nanjing Medical University School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yingdan","middleName":"","lastName":"Tang","suffix":""},{"id":65940961,"identity":"dfc35413-8e15-4722-8693-1d5b2ca3777a","order_by":2,"name":"Tong Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tong","middleName":"","lastName":"Wang","suffix":""},{"id":65940962,"identity":"2837a562-0f30-45f8-8610-e5e8d9d86c54","order_by":3,"name":"Inam Ullah","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Inam","middleName":"","lastName":"Ullah","suffix":""},{"id":65940963,"identity":"f9f34109-b099-43dd-bcfb-56ec971889fd","order_by":4,"name":"Ke Xu","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ke","middleName":"","lastName":"Xu","suffix":""},{"id":65940964,"identity":"109df459-da7d-4b3b-baa5-13accf3167fb","order_by":5,"name":"Jing Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Wang","suffix":""},{"id":65940965,"identity":"26bf3dfa-b58e-4a19-9466-e9f44f9e7ef8","order_by":6,"name":"Pengsheng Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pengsheng","middleName":"","lastName":"Chen","suffix":""},{"id":65940966,"identity":"36b60c1b-9bb4-4693-aa7f-68b08109fd77","order_by":7,"name":"Zengguang Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zengguang","middleName":"","lastName":"Chen","suffix":""},{"id":65940967,"identity":"8718447e-ca34-4b84-be2c-87eda24015a4","order_by":8,"name":"Tiantian Zhu","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tiantian","middleName":"","lastName":"Zhu","suffix":""},{"id":65940968,"identity":"cfdcc6c0-56f9-4628-9cf9-bf985aed493f","order_by":9,"name":"Jun Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Chen","suffix":""},{"id":65940969,"identity":"18c0748a-2c69-4cb8-a740-7edaa4ec0ba2","order_by":10,"name":"Jimin Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jimin","middleName":"","lastName":"Li","suffix":""},{"id":65940970,"identity":"7fa1d90f-fa02-4e87-a768-c84c163d6813","order_by":11,"name":"Fei Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Wang","suffix":""},{"id":65940971,"identity":"3664f46e-ef8a-407f-93af-e03fb452aa25","order_by":12,"name":"Lu Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Yang","suffix":""},{"id":65940972,"identity":"bdfdb634-8d84-43fe-ab94-054a14db789e","order_by":13,"name":"Yuansheng Fan","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuansheng","middleName":"","lastName":"Fan","suffix":""},{"id":65940973,"identity":"af701bb9-855b-439b-b3df-8ced2a58291c","order_by":14,"name":"Lu Shi","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Shi","suffix":""},{"id":65940974,"identity":"5d42fd25-d874-44eb-99dc-3904d2b9c2c7","order_by":15,"name":"Xiaoxuan Gong","email":"","orcid":"","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoxuan","middleName":"","lastName":"Gong","suffix":""},{"id":65940975,"identity":"21a6a813-7289-483e-a900-0b4354126b3c","order_by":16,"name":"John W. Eikelboom","email":"","orcid":"","institution":"McMaster University Department of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"W.","lastName":"Eikelboom","suffix":""},{"id":65940976,"identity":"4ea7bfe9-8da9-4f2e-89d9-dce3595f852e","order_by":17,"name":"Yang Zhao","email":"","orcid":"","institution":"Nanjing Medical University School of Public Health","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Zhao","suffix":""},{"id":65940977,"identity":"2b42cc5e-f9ee-4209-8b9a-ed37b01cacbe","order_by":18,"name":"Chunjian Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYBACPmaGBAaGCgZmMI+HGC1sYC1nSNICIhjboDzitLAzPPzMO+8Ou+6MBMYHb9sY5M2JcFiyNO+2Z8xmNxKYDee2MRjubCCsJQGo5TBIC5s0bxtDgsEBImz5zTsHrIX9N7Fa0qR5GyC2MBOtxXLOMaCWMw+bJeeckzDcQEgLP/+Z5Btvag4nmx1PPvjhTZmNPEFbgHGRwASMjmRg7DQAeRIE1QMB+wHGHwwMdsQoHQWjYBSMghEKAISVOKzU73fWAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-2359-7570","institution":"The First Affiliated Hospital of Nanjing Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Chunjian","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2021-11-21 10:38:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1100332/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1100332/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16033649,"identity":"334fd0e3-0b9b-4768-98cd-dc9f465c8a35","added_by":"auto","created_at":"2021-11-30 17:49:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100736,"visible":true,"origin":"","legend":"Study flow chart. \nAbbreviations: PLADP, adenosine diphosphate induced platelet aggregation. \n","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/b70fc2f9eb3428894369a498.png"},{"id":16033650,"identity":"32ac8842-dc0b-47d1-bb49-76d07c3b305d","added_by":"auto","created_at":"2021-11-30 17:49:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1505545,"visible":true,"origin":"","legend":"Platelet reactivities (PLADP) in patients with different genotypes of rs956115 and rs4244285 \n (A) Boxplot of rs956115 and PLADP at baseline and 1 month; (B) Boxplot of rs4244285 and PLADP at baseline and 1 month. Abbreviations: PLADP, adenosine diphosphate induced platelet aggregation. \n","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/d321c4771aa9420ffe57e2b3.png"},{"id":16034040,"identity":"454f9b89-6bc9-4e17-b6d6-5e959caedbd5","added_by":"auto","created_at":"2021-11-30 17:52:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":114792,"visible":true,"origin":"","legend":"Survival curve of MACE free rate and rs956115/rs4244285. \n(A) Survival curve of MACE free rate and rs956115. Cox regression model adjusted for rs4244285 and clinical covariates, including age, previous MI, hypertension, diabetes mellitus, smoking status, previous PCI, LVEF, serum creatinine, low density lipoprotein and diagnosis; (B) Survival curve of MACE free rate and rs4244285. Cox regression model adjusted for rs956115 and clinical covariates, including age, previous MI, hypertension, diabetes mellitus, smoking status, previous PCI, LVEF, serum creatinine, low density lipoprotein and diagnosis. Abbreviations: CI, confidence intervals; HR, hazard ratio; LVEF, left ventricular ejection fraction; MACE, major adverse cardiovascular events; MI, myocardial infarction; PCI, percutaneous coronary intervention.\n\n","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/9bac389b7fb48d938464bc5f.png"},{"id":16033654,"identity":"40e8d6ba-ef21-464a-b12b-0452e3e12dbb","added_by":"auto","created_at":"2021-11-30 17:49:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90081,"visible":true,"origin":"","legend":"The hazard ratio of rs956115 mutation by different genotypes of rs4244285. \nModel adjusted for clinical covariates, including age, previous MI, hypertension, diabetes mellitus, smoking status, previous PCI, LVEF, serum creatinine, low density lipoprotein, diagnosis. a P value indicated the association between rs956115 and MACE in all patients. \n","description":"","filename":"OnlineFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/466f4e49ad2b09706a40b249.png"},{"id":16034041,"identity":"734ace4d-3faf-4501-a02b-f65ecdfad4e0","added_by":"auto","created_at":"2021-11-30 17:52:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1214757,"visible":true,"origin":"","legend":"Forest plot of MACE risk in different rs956115 genotypes \na P value indicated the association between rs956115 and MACE. \n","description":"","filename":"OnlineFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/64dffc7ffb8b2a5ef7ed1ec5.png"},{"id":16034043,"identity":"7cce4076-b31f-4209-8b57-10870d186ca5","added_by":"auto","created_at":"2021-11-30 17:52:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1224463,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/cd833007-d4af-4117-acb5-79c86a03d014.pdf"},{"id":16033652,"identity":"38268d91-df39-45c7-a082-013c684f4eb8","added_by":"auto","created_at":"2021-11-30 17:49:11","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1944640,"visible":true,"origin":"","legend":"Figure S1. Platelet reactivities (PLAA) in patients with different genotypes of rs956115 and rs4244285 \n(A) Boxplot of rs956115 and PLAA at baseline and 1 month; (B) Boxplot of rs4244285 and PLAA at baseline and 1 month. Abbreviations: PLAA, arachidonic acid induced platelet aggregation. \n","description":"","filename":"FigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-1100332/v1/07df25206f3e94bdfe9f12de.tif"}],"financialInterests":"","formattedTitle":"Impact of IRS-1 rs956115 and CYP2C19 rs4244285 Genotypes on Clinical Outcome of Patients Undergoing PCI","fulltext":[{"header":"Background","content":"\u003cp\u003eInsulin receptor substrate-1 (IRS-1), a ligand of insulin receptor tyrosine kinase, plays a central role in insulin signal transduction system (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Dysregulation of IRS-1 has been suggested as a common mechanism underlying insulin resistance which may lead to high platelet reactivity and low response to antiplatelet treatment in patients with type 2 diabetes mellitus (DM) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCYP2C19 is one of the isoenzymes of hepatic cytochrome P450 (CYP450) system which plays a key role in the bioactivation of clopidogrel(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Carriers of CYP2C19 loss of function *2 (rs4244285) generate less amounts of active metabolite of clopidogrel than wild-type homozygotes, which subsequently resulting in a lower clopidogrel responsiveness and an increased risk of major adverse cardiac events in coronary artery disease (CAD) patients after percutaneous coronary intervention (PCI)(\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study examined the association between IRS-1 rs956115, CYP2C19 rs4244285 and platelet reactivity as well as major adverse cardiovascular events (MACE) in patients with CAD who had undergone PCI and were treated with aspirin and clopidogrel.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe data that support the findings of this study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis was a prospective single-center cohort study conducted in the First Affiliated Hospital of Nanjing Medical University, Nanjing, China. Complying with the Helsinki declarations and local regulations, the study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from each patient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria were patients with CAD undergoing urgent or elective coronary stent implantation who were over 18 years old and planning to take dual antiplatelet treatment (DAPT) with clopidogrel 75 mg and aspirin 100 mg once daily for at least 1 year. Patients who met any of the following criteria were excluded: (1) allergic or intolerant to aspirin or clopidogrel; (2) at high risk of bleeding (e.g., platelet count \u0026lt;80\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L, known bleeding diathesis, active peptic ulcer, or with a history of cerebral hemorrhage within 1\u003cem\u003e\u0026nbsp;\u003c/em\u003eyear); and (3) planning to take drugs that could potentially interfere with the antiplatelet effects of aspirin (e.g., non-steroidal anti-inflammatory drugs) or clopidogrel (e.g., CYP3A inhibitors or CYP3A inducers). Baseline demographic and clinical characteristics, as well as medical and interventional treatments, were collected on a pre-specified case report form.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eSample Collection and Preparation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eAfter receiving \u0026gt;5 days of aspirin and clopidogrel, blood was collected 2 hours post dosing (about 10am) from each patient into one 2-mL BD Vacutainer tube (Becton, Dickinson and Company, Franklin Lakes, NJ) containing 3.6 mg K2 EDTA and two 2-mL BD vacutainer tubes with 0.105 mol/L buffered sodium citrate (3.2%). Blood samples were transferred to the central laboratory within 1 hour after collection. Samples in EDTA tubes were frozen at \u0026minus;80\u0026deg;C for genotyping, whereas citrated samples were immediately processed for platelet aggregation studies. After centrifuging the citrated sample at 200g for 8 minutes at 22\u0026deg;C, platelet-rich plasma was carefully separated, and the remaining sample was centrifuged at 2465g for another 10 minutes to obtain platelet-poor plasma. The platelet count in platelet-rich plasma was standardized by addition of platelet-poor plasma to achieve a count of 250\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L. Platelet aggregation tests by light transmission aggregometry were performed within 3 hours of platelet-rich plasma preparation\u0026nbsp;(10). At 1-month follow-up, patients received repeat blood collection for measurement of platelet reactivity as performed at baseline.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003ePlatelet Reactivity Assay\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePlatelet aggregation testing\u0026nbsp;was performed using a Chronolog Model 700 aggregometer (Chronolog Corporation, Havertown, PA). Immediately after preparation of platelet-rich plasma, 500 \u0026mu;L was transferred into each of the 2 test tubes, with 500 \u0026mu;L platelet-poor plasma as control. Platelet aggregation was induced using adenosine diphosphate (ADP) or arachidonic acid (AA) as agonists with final concentrations of 5 umol/L and 1 mmol/L, respectively. The ADP and AA-induced platelet aggregations (PL\u003csub\u003eADP\u003c/sub\u003e and PL\u003csub\u003eAA\u003c/sub\u003e, respectively) were recorded using the maximum platelet aggregation within 8 minutes.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eGenotype Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eIRS-1 (rs956115, C\u0026gt;G) and CYP2C19*2 (rs4244285, G\u0026gt;A) were genotyped using a custom-by-design improved multiplex ligation detection reaction technique (Genesky Biotechnologies Inc, Shanghai, China) based on the highly specific double ligation and the multiplex fluorescence polymerase chain reaction\u0026nbsp;(11). For quality control, repeated testing was performed randomly in 5% of samples with high DNA quality.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eClinical Follow-up\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003ePatients were followed-up for 12 months by 2 investigators who were blinded to the results of platelet reactivity testing and genotyping. The patients were followed in the clinic or by telephone if they were unable to attend the clinic. The primary endpoint was defined as the occurrence of MACE, a composite of cardiovascular death, myocardial infarction, and ischemic stroke within 12 months after PCI. The cardiovascular events in this study were defined according to the American College of Cardiology 2001\u0026nbsp;(12).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eContinuous variables were described as mean \u0026plusmn; standard deviation (SD) or median with interquartile range (IQR) when data did not follow a normal distribution, and differences between groups were analyzed by \u003cem\u003et\u003c/em\u003e test or nonparametric test. Categorized variables were expressed as numbers and percentages and were analyzed by \u0026chi;\u003csup\u003e2\u003c/sup\u003e test or Fisher exact method. One-way ANOVA was used to compare the platelet reactivity among different genotypes of rs956115 and rs4244285. Multivariable Cox proportional hazard model analysis was used to estimate the association between genotypes of rs956115 and rs4244285 and risk of MACE reported as hazard ratio (HR) and 95% confidence intervals (CI). The model was adjusted for clinical covariables including age, previous myocardial infraction (MI), hypertension, diabetes mellitus, smoking status, previous PCI,\u0026nbsp;left ventricular ejection fraction (LVEF),\u0026nbsp;serum creatinine, low density lipoprotein, and diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll analyses were performed using SAS, version 9.4 (SAS Institute, Cary, North Carolina) and figures were developed using R, version 3.2.0 (R Foundation for Statistical Computing, Vienna, Austria). A two-tailed P value of \u0026lt;0.05 was considered statistically significant.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom Mar 2011 to September 2016, 2213 patients were consecutively screened, among whom 1614 patients who met the inclusion and the exclusion criteria were enrolled. Of the 1614 enrolled patients, 3 were not included in the final analysis due to unsatisfactory blood sample quality. All the remaining patients completed the genotype assessment and 1-year clinical follow-up. Platelet aggregation testing were performed in 1175 patients at baseline and in 624 patients at 1-month follow-up (Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch2\u003ePatients’ Characteristics\u003c/h2\u003e\n\u003cp\u003eThe baseline characteristics of patients included in this study are summarized in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared with patients who did not experience MACE, those who experienced MACE were older [69.00 (14.50) \u003cem\u003evs.\u003c/em\u003e 64.00 (15.00), \u003cem\u003eP\u003c/em\u003e=0.0069], more commonly had reduced LVEF (25.0% \u003cem\u003evs\u003c/em\u003e. 7.66%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and history of ST-segment-elevation myocardial infarction (STEMI) or non-ST-segment elevation acute coronary syndromes (NSTE-ACS) (63.63% \u003cem\u003evs.\u003c/em\u003e 42.44%, \u003cem\u003eP\u003c/em\u003e=0.0010).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of Patients Grouped by the Occurrence of MACE\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMACE\u003c/p\u003e \u003cp\u003e(n=44)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMACE free\u003c/p\u003e \u003cp\u003e(n=1, 567)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (IQR), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.00 (14.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.00 (15.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2966\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8(18.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e393(25.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36(81.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1174(74.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious MI, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7166\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42(95.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1499(95.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68(4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12(27.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e520(33.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32(72.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1047(66.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30(68.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1165(74.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14(31.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e402(25.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.3503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24(54.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e743(47.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20(45.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e824(52.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious PCI, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42(95.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1424(90.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143(9.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33(75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1447(92.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120(7.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum creatinine, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 133\u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42(95.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1537(98.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 133\u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30(1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow density lipoprotein, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 1.8mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36(81.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1335(85.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 1.8mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8(18.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e232(14.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis, No. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16(36.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e902(57.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSTE-ACS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12(27.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e412(26.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTEMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16(36.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e253(16.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eValues are presented as median (IQR) or number of patients (percentage) as appropriate. \u003cem\u003eP\u003c/em\u003e values were calculated with the use of \u003cem\u003et\u003c/em\u003e test or \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\chi }^{2}\\)\u003c/span\u003e\u003c/span\u003e test as appropriate. Abbreviations: LVEF. left ventricular ejection fraction; MACE. major adverse cardiovascular events, including cardiovascular death, myocardial infarction and ischemic stroke; MI. myocardial infarction; NSTE-ACS. non-ST-segment elevation acute coronary syndromes; PCI. percutaneous coronary intervention; SA. stable angina pectoris; STEMI. ST-segment-elevation myocardial infarction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOn-Treatment Platelet Reactivity and Genotypes.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe baseline and 1-month PL\u003csub\u003eADP\u003c/sub\u003e were (29.88\u0026plusmn;14.34)% and (26.27\u0026plusmn;15.10)%, respectively. There was no significant difference in PL\u003csub\u003eADP\u003c/sub\u003e among different rs956115 genotypes at the baseline assessment (\u003cem\u003eF\u003c/em\u003e=0.20, \u003cem\u003eP\u003c/em\u003e=0.8200, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). At 1-month follow-up, PL\u003csub\u003eADP\u003c/sub\u003e was significantly different among the three genotypes (\u003cem\u003eF\u003c/em\u003e=3.28, \u003cem\u003eP\u003c/em\u003e=0.0381, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). CG genotype was associated with a significantly lower PL\u003csub\u003eADP\u003c/sub\u003e compared with CC genotype (\u003cem\u003eP\u003c/em\u003e=0.0158, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Regarding PL\u003csub\u003eAA\u003c/sub\u003e, there were no significant difference among the three genotypes of rs956115 either at baseline (\u003cem\u003eF\u003c/em\u003e=2.73, \u003cem\u003eP\u003c/em\u003e=0.0656, \u003cb\u003eFigure S1A\u003c/b\u003e) or at 1-month follow-up (\u003cem\u003eF\u003c/em\u003e=0.20, \u003cem\u003eP\u003c/em\u003e=0.8180, \u003cb\u003eFigure S1A\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor rs4244285, PL\u003csub\u003eADP\u003c/sub\u003e were significantly different among the three genotypes at baseline (\u003cem\u003eF\u003c/em\u003e=53.27, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) and 1-month follow-up (\u003cem\u003eF\u003c/em\u003e=12.07, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). By pairwise comparisons, the platelet reactivities corresponding to different genotypes of rs4244285 were all significantly different except the comparison between GA and AA at 1-month follow-up (\u003cem\u003eP\u003c/em\u003e=0.4392, Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). As shown in Figure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, the platelet reactivity increased with the number of the A alleles of rs4244285. Regarding PL\u003csub\u003eAA\u003c/sub\u003e, there were no significant difference among the three genotypes of rs4244285 either at baseline (\u003cem\u003eF\u003c/em\u003e=0.38, \u003cem\u003eP\u003c/em\u003e=0.6870, \u003cb\u003eFigure S1B\u003c/b\u003e) or at 1-month follow-up (\u003cem\u003eF\u003c/em\u003e=0.78, \u003cem\u003eP\u003c/em\u003e=0.4590, \u003cb\u003eFigure S1B\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAssociation between IRS/CYP2C19 Genotypes and Cardiovascular Outcomes.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 44 patients experienced MACE, including 15 cardiac deaths, 16 nonfatal myocardial infarctions, and 13 ischemic strokes.\u003c/p\u003e \u003cp\u003eFor rs956115, patients with CG or GG genotypes had a 1.99-fold higher MACE risk than those with CC homozygote (dominant model, adjusted HR=1.99, 95%CI: 1.00-3.98, \u003cem\u003eP\u003c/em\u003e=0.0499; additive model, adjusted HR=1.95, 95%CI: 1.05-3.61, \u003cem\u003eP\u003c/em\u003e=0.0341; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When further adjusted for rs4244285 genotypes, patients with CG or GG genotypes had a 2.09-fold higher MACE risk than those with CC homozygote (dominant model, adjusted HR=2.09, 95%CI: 1.04-4.19, \u003cem\u003eP\u003c/em\u003e=0.0376; additive model, adjusted HR=2.04, 95%CI: 1.10-4.19, \u003cem\u003eP\u003c/em\u003e=0.0244; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). There was no significant difference in risk of MACE risk between CG and CC genotypes (adjusted HR=1.91, 95%CI: 0.94-3.88, \u003cem\u003eP\u003c/em\u003e=0.0751) or between GG and CC genotypes (adjusted HR=4.23, 95%CI: 0.55-32.29, \u003cem\u003eP\u003c/em\u003e= 0.1643) (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMACE risk by Multi-Cox regression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGeno-type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMACE\u003c/p\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCensored\u003c/p\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eAdjusted model \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003eAdjusted model \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eHR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eHR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eHR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cb\u003evalue\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers956115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIRS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCG \u003cem\u003evs.\u003c/em\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.66(0.82,3.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.91(0.94,3.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.99(0.98,4.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0586\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGG \u003cem\u003evs.\u003c/em\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.65(0.36,19.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.23(0.55,32.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.1643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.70(0.62,35.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.1351\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.71(0.87,3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.99(1.00,3.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.09(1.04,4.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRecessive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.35(0.32,17.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.58(0.48,26.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.2157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.91(0.52,29.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.1851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdditive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.65(0.91,3.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.1013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.95(1.05,3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.04(1.10,3.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers4244285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCYP2C19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGA \u003cem\u003evs.\u003c/em\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.04(1.07,3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.13(1.10,4.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.19(1.13,4.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAA \u003cem\u003evs.\u003c/em\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60(0.14,2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.5010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.58(0.13,2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.4814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.58(0.13,2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.4787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.76(0.93,3.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.81(0.94,3.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.85(0.96,3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.0666\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRecessive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40(0.10,1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.37(0.09,1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.1767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.37(0.09,1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.1702\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdditive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17(0.75,1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.4853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.16(0.74,1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.5114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.17(0.75,1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.4936\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003csup\u003ea\u003c/sup\u003e Model adjusted for clinical covariates, including age, previous MI, hypertension, diabetes mellitus, LVEF, serum creatinine, diagnosis, low density lipoprotein, smoking status, previous PCI. \u003csup\u003eb\u003c/sup\u003e Model adjusted for rs4244285/ rs956115 and clinical covariates, including age, previous MI, hypertension, diabetes mellitus, LVEF, serum creatinine, diagnosis, low density lipoprotein, smoking status, previous PCI. Dominant model: CG and GG \u003cem\u003evs.\u003c/em\u003eCC. Recessive model: GG \u003cem\u003evs.\u003c/em\u003eCC and CG. Addictive model: the number of risk alleles is proportional to the risk of MACE. Abbreviations: CI, confidence intervals; HR, hazard ratio; Other abbreviations as in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor rs4244285, patients with GA genotype had a 2.13-fold higher MACE risk than those with GG genotype (adjusted HR=2.13, 95%CI: 1.10-4.12, \u003cem\u003eP\u003c/em\u003e=0.0248; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Patients with AA genotype showed no increased MACE risk to GG genotype (adjusted HR=0.58; 95%CI:0.13-2.60; P=0.4787). When further adjusted for rs956115 genotypes, patients with GA genotype had a 2.19-fold higher risk than those with GG genotype (adjusted HR=2.19, 95%CI: 1.13-4.24, \u003cem\u003eP\u003c/em\u003e=0.0200; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). No significant difference of MACE risk was found while using either dominant (P=0.0666; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) or additive model (P=0.4936; Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch2\u003eInteraction Analysis\u003c/h2\u003e\n\u003cp\u003eAmong patients with GG genotype of rs4244285, those who had CG or GG genotype of rs956115 presented a 4.85-fold higher MACE risk than those who had CC genotype (adjusted HR=4.85, \u003cem\u003eP\u003c/em\u003e=0.0081; Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). By comparison, among patients with non-GG genotype of rs4244285, those who had CG or GG genotype of rs956115 presented a 1.40-fold higher risk than those who had CC genotype (adjusted HR=1.40, \u003cem\u003eP\u003c/em\u003e=0.4764; Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The interaction between rs956115 and rs4244285 was none-statistically significant (\u003cem\u003eP\u003c/em\u003e=0.1453; Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch2\u003eAssociation Of Rs956115 With Mace In Subgroup Analysis\u003c/h2\u003e\n\u003cp\u003eWe performed multivariable Cox-regression analysis for rs956115 in different patient subgroups (Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The association between rs956115 genotypes and MACE remained statistically significant in subgroup of normal serum creatinine (adjusted HR=2.09, 95%CI: 1.04-4.18) (Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Although the adjusted HR between CG or GG and CC genotypes of rs956115 did not reach statistically significant in the diabetes subgroup (Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the dominant model HR of MACE for patients with CG or GG genotype of rs956115 tended to be similar across subgroups. No significant interactions were observed in any of those subgroups except LVEF subgroup (Interaction \u003cem\u003eP\u003c/em\u003e=0.0006) (Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the impacts of IRS-1 rs956115 and CYP2C19 rs4244285 polymorphisms on clinical outcome of patients undergoing PCI and receiving DAPT treatment and found that G allele carriers of IRS-1 rs956115 had a 2.09-fold higher risk of MACE compared with non-carriers at 1-year follow-up. The rs4244285 GA genotype had a 2.19-fold higher risk than GG homozygotes. The effect of rs956115 was independent to known clinical covariables, while that of rs4244285 GA could be mediated by lower clopidogrel response.\u003c/p\u003e \u003cp\u003e \u003cem\u003eAngiolillo et al.\u003c/em\u003e examined 7 single nucleotide polymorphisms (SNPs) of IRS-1 and found that rs956115 polymorphism was associated with a hyperreactive platelet phenotype and adverse cardiovascular outcomes in type-2 DM Caucasian patients concomitant with coronary artery disease (CAD) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, uncertainty remains about the effects of IRS-1 rs956115 polymorphism on platelet function and cardiovascular outcome in non-selective CAD patients.\u003c/p\u003e \u003cp\u003eIn this study, we found that rs956115 G allele was an independent prognostic factor of adverse cardiovascular outcomes in non-selective CAD patients, irrespective of CYP2C19*2 (rs4244285) polymorphism, diabetes mellitus and other known risk factors. Although rs956115 G allele didn\u0026rsquo;t show a significant correlation with MACE in the subgroup of diabetes mellitus, our results showed the consistent tendency of almost all subgroups as shown in Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRegarding the underlying mechanism, \u003cem\u003eAngiolillo et al\u003c/em\u003e suggested that rs956115 polymorphism was associated with a hyperactive platelet phenotype in Caucasian type-2 DM patients (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, in a later study by \u003cem\u003eZhang et al\u003c/em\u003e, no association was observed between rs956115 polymorphism and platelet function profile (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Our results were in consistent with that of \u003cem\u003eZhang et al\u003c/em\u003e in a larger Chinese population, showing no significant difference in AA or ADP-induced platelet aggregation at baseline among different IRS-1 rs956115 genotypes. Moreover, ADP-induced platelet aggregation was even lower in rs956115 CG genotype compared with CC genotype at 1-month follow-up. Along with the results of \u003cem\u003eZhang\u0026rsquo;s\u003c/em\u003e study, we suggest that the association between IRS-1 rs956115 polymorphisms and risk of MACE cannot be explained by impaired platelet reactivity to either clopidogrel or aspirin.\u003c/p\u003e \u003cp\u003eTheoretically, IRS-1 is one of the central nodes in insulin signaling network (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). It has been reported that IRS-1 is necessary for insulin-stimulated activation of phosphatidylinositol 3 kinase (PI3K)/AKT pathway and subsequent enhanced production of nitric oxide (NO) in endothelial cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), which plays a critical role in maintaining cardiovascular homeostasis (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Previous studies have demonstrated that functional variants of IRS-1 directly impaired insulin regulated NO synthesis in cultured human endothelial cells (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Considering the pivotal role of IRS-1 in PI3K/AKT signaling pathway of insulin, it may be reasonable to assume IRS-1 rs956115 polymorphism affects the same process or an unknown pathway and consequently impacts the clinical outcome of CAD patients.\u003c/p\u003e \u003cp\u003eOur results were consistent with previously reports and further confirmed that CYP2C19*2 (rs4244285) loss of function polymorphism is a strong predictor of impaired clopidogrel response and adverse clinical outcomes (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This consistency, in turn, enhances the credibility of our results on rs956115. Meanwhile, from the interaction analysis, we did not find a statistically significant interaction between IRS-1 rs956115 and CYP2C19 rs4244285 polymorphism, which proved IRS-1 rs956115 G allele to be an independent risk factor of MACE in CAD patients after PCI.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIRS-1 rs956115 G allele significantly increased the cardiovascular risk of post-PCI patients by 2.09-fold at 1-year follow-up, which was independent to CYP2C19 rs4244285 genotypes, pharmacological platelet response and known clinical covariables.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplying with the Helsinki declarations and local regulations, the study was approved by the ethics committee of the First Affiliated Hospital of Nanjing Medical University. Written informed consent was obtained from each patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs stated above, informed consent on participation and publication was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work was supported by a grant from the National Natural Science Funding of China (81170181, 82170351),\u0026nbsp;the Jiangsu Province\u0026rsquo;s Key Provincial Talents Program (ZDRCA2016013), the Second Level of 333 High Level Talent Training Project in Jiangsu Province (BRA2019099), Special Fund for Key R \u0026amp; D Plans (Social Development) of Jiangsu Province (BE2019754), and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutes (PAPD).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCL contributed to the conceptualization and supervision of the study, review and editing the manuscript. YZ contributed to the supervision of the study, interpretation of the data,\u0026nbsp;review and editing the manuscript. JZ contributed to the investigation of the patients, writing the original draft. YT contributed to interpretation of the data, writing the original draft. IU, TW, KX, PC, ZC,\u0026nbsp;JW, TZ, JC, JL, FW, LY, YF, LS, XG contributed to the\u0026nbsp;investigation of the patients. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDeFronzo RA, Tripathy D. Skeletal muscle insulin resistance is the primary defect in type 2 diabetes. Diabetes Care. 2009;32 Suppl 2:S157-63.\u003c/li\u003e\n\u003cli\u003eCopps KD, White MF. Regulation of insulin sensitivity by serine/threonine phosphorylation of insulin receptor substrate proteins IRS1 and IRS2. Diabetologia. 2012;55(10):2565-82.\u003c/li\u003e\n\u003cli\u003eRandriamboavonjy V, Fleming I. Insulin, insulin resistance, and platelet signaling in diabetes. Diabetes Care. 2009;32(4):528-30.\u003c/li\u003e\n\u003cli\u003eFerreira IA, Mocking AI, Feijge MA, Gorter G, van Haeften TW, Heemskerk JW, et al. Platelet inhibition by insulin is absent in type 2 diabetes mellitus. Arterioscler Thromb Vasc Biol. 2006;26(2):417-22.\u003c/li\u003e\n\u003cli\u003eKazui M, Nishiya Y, Ishizuka T, Hagihara K, Farid NA, Okazaki O, et al. Identification of the human cytochrome P450 enzymes involved in the two oxidative steps in the bioactivation of clopidogrel to its pharmacologically active metabolite. Drug Metab Dispos. 2010;38(1):92-9.\u003c/li\u003e\n\u003cli\u003eCattaneo M. Response variability to clopidogrel: is tailored treatment, based on laboratory testing, the right solution? J Thromb Haemost. 2012;10(3):327-36.\u003c/li\u003e\n\u003cli\u003eHulot JS, Bura A, Villard E, Azizi M, Remones V, Goyenvalle C, et al. Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. Blood. 2006;108(7):2244-7.\u003c/li\u003e\n\u003cli\u003eHochholzer W, Trenk D, Fromm MF, Valina CM, Stratz C, Bestehorn H-P, et al. Impact of Cytochrome P450 2C19 Loss-of-Function Polymorphism and of Major Demographic Characteristics on Residual Platelet Function After Loading and Maintenance Treatment With Clopidogrel in Patients Undergoing Elective Coronary Stent Placement. Journal of the American College of Cardiology. 2010;55(22):2427-34.\u003c/li\u003e\n\u003cli\u003eMega JL, Close SL, Wiviott SD, Shen L, Hockett RD, Brandt JT, et al. Cytochrome p-450 polymorphisms and response to clopidogrel. N Engl J Med. 2009;360(4):354-62.\u003c/li\u003e\n\u003cli\u003eLi C, Hirsh J, Xie C, Johnston MA, Eikelboom JW. Reversal of the anti-platelet effects of aspirin and clopidogrel. J Thromb Haemost. 2012;10(4):521-8.\u003c/li\u003e\n\u003cli\u003eLi HM, Zhang TP, Leng RX, Li XP, Wang DG, Li XM, et al. Association of leptin and leptin receptor gene polymorphisms with systemic lupus erythematosus in a Chinese population. J Cell Mol Med. 2017;21(9):1732-41.\u003c/li\u003e\n\u003cli\u003eCannon CP, Battler A, Brindis RG, Cox JL, Ellis SG, Every NR, et al. American College of Cardiology key data elements and definitions for measuring the clinical management and outcomes of patients with acute coronary syndromes. A report of the American College of Cardiology Task Force on Clinical Data Standards (Acute Coronary Syndromes Writing Committee). J Am Coll Cardiol. 2001;38(7):2114-30.\u003c/li\u003e\n\u003cli\u003eAngiolillo DJ, Bernardo E, Zanoni M, Vivas D, Capranzano P, Malerba G, et al. Impact of Insulin Receptor Substrate-1 Genotypes on Platelet Reactivity and Cardiovascular Outcomes in Patients With Type 2 Diabetes Mellitus and Coronary Artery Disease. Journal of the American College of Cardiology. 2011;58(1):30-9.\u003c/li\u003e\n\u003cli\u003eZhang D, Zhang X, Liu D, Liu T, Cai W, Yan C, et al. Association between insulin receptor substrate-1 polymorphisms and high platelet reactivity with clopidogrel therapy in coronary artery disease patients with type 2 diabetes mellitus. Cardiovasc Diabetol. 2016;15:50.\u003c/li\u003e\n\u003cli\u003eTaniguchi CM, Emanuelli B, Kahn CR. Critical nodes in signalling pathways: insights into insulin action. Nat Rev Mol Cell Biol. 2006;7(2):85-96.\u003c/li\u003e\n\u003cli\u003eMontagnani M, Ravichandran LV, Chen H, Esposito DL, Quon MJ. Insulin receptor substrate-1 and phosphoinositide-dependent kinase-1 are required for insulin-stimulated production of nitric oxide in endothelial cells. Mol Endocrinol. 2002;16(8):1931-42.\u003c/li\u003e\n\u003cli\u003eTousoulis D, Kampoli AM, Tentolouris C, Papageorgiou N, Stefanadis C. The role of nitric oxide on endothelial function. Curr Vasc Pharmacol. 2012;10(1):4-18.\u003c/li\u003e\n\u003cli\u003eFederici M, Pandolfi A, De Filippis EA, Pellegrini G, Menghini R, Lauro D, et al. G972R IRS-1 variant impairs insulin regulation of endothelial nitric oxide synthase in cultured human endothelial cells. Circulation. 2004;109(3):399-405.\u003c/li\u003e\n\u003cli\u003eHuang C, Li G, Dong H, Sun S, Chen H, Luo D, et al. Arg⁹⁷\u0026sup2; insulin receptor substrate-1 inhibits endothelial nitric oxide synthase expression in human endothelial cells by upregulating microRNA-155. Int J Mol Med. 2015;36(1):239-48.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"coronary artery disease, CYP2C19 rs4244285, IRS-1 rs956115, percutaneous coronary intervention, platelet reactivity. ","lastPublishedDoi":"10.21203/rs.3.rs-1100332/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1100332/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003einsulin receptor substrate-1 (IRS-1) rs956115 is associated with vascular risk in patients with coronary artery disease (CAD) and concomitant diabetes. CYP2C19 rs4244285 modulates clopidogrel responsiveness and predicts outcome of CAD. We designed this study to explore the association between IRS-1 rs956115, CYP2C19 rs4244285, and platelet reactivity as well as 1-year outcome in patients with CAD undergoing percutaneous coronary intervention (PCI).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eIRS-1 rs956115, CYP2C19 rs4244285 genotypes and platelet reactivity were assessed in 1611 post-PCI patients. Major adverse cardiovascular events (MACE) which were defined as a composite of cardiovascular death, myocardial infarction and ischemic stroke over 1-year were evaluated. One-way ANOVA was used to compare the platelet reactivity among different genotypes of rs956115 and rs4244285. Multivariable Cox proportional hazard model analysis was used to estimate the association between genotypes of rs956115 and rs4244285 and risk of MACE.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e At 1 month, patients with rs956115 CG genotype had significantly lower level of residual ADP-induced platelet aggregation (PL\u003csub\u003eADP\u003c/sub\u003e) than those with CC genotype. PL\u003csub\u003eADP\u003c/sub\u003e significantly increased with the number of rs4244285 A alleles. Patients with rs956115 CG or GG genotype had a 2.09-fold higher risk of MACE than those with CC genotype (adjusted HR=2.09; 95%CI:1.04-4.19; \u003cem\u003eP\u003c/em\u003e=0.0376), and those with rs4244285 GA genotype had a 2.19-fold higher risk than GG homozygotes (adjusted HR=2.19; 95%CI:1.13-4.24; \u003cem\u003eP\u003c/em\u003e=0.0200). There was no significant difference in risk between AA and GG homozygotes. No interaction between rs956115 and rs4244285 was observed. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eIn post-PCI patients, rs956115 GG/CG and rs4244285 GA genotypes were associated with 2.09- and 2.19-fold cardiovascular risks respectively at 1-year follow-up. The effect of rs956115 appeared to be independent of known clinical predictors, while that of rs4244285 GA could be mediated by lower clopidogrel response. \u003c/p\u003e\u003cp\u003eTrial registration: Pharmacogenetic and Pharmacokinetic Study of Clopidogrel (PPSC), NCT01968499. Registered October 17, 2013 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT01968499?term=NCT01968499\u0026amp;draw=1\u0026amp;rank=1\u003c/p\u003e","manuscriptTitle":"Impact of IRS-1 rs956115 and CYP2C19 rs4244285 Genotypes on Clinical Outcome of Patients Undergoing PCI","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-11-30 17:49:09","doi":"10.21203/rs.3.rs-1100332/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0af9995-ea00-405e-81f9-44e94f243673","owner":[],"postedDate":"November 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":8801586,"name":"Cardiac \u0026 Cardiovascular Systems"}],"tags":[],"updatedAt":"2021-11-30T17:49:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-11-30 17:49:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1100332","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1100332","identity":"rs-1100332","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}