ABSTRACT
Objectives: To determine the correlations of ADP-induced platelet-inhibition rate (ADP-PIR) and CYP2C19 genotypes with carotid plaque types in acute ischemic stroke (AIS). Unstable carotid plaques are implicated in AIS. Clopidogrel (commonly prescribed in AIS) produces adenosine diphosphate (ADP)-induced platelet inhibition, and is metabolized by CYP2C19.
Methods: We retrospectively evaluated the data of AIS patients treated at our hospital during 2019–2022, and administered maintenance clopidogrel (75 mg/d). Carotid plaques, ADP-PIR, and CYP2C19 genotypes were assessed using color Doppler ultrasonography, thromboelastography, and polymerase chain reaction assays, respectively. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were conducted.
Results: Of 692 study patients, 378 (54.6%) and 128 (18.5%) had unstable and stable carotid plaques, respectively. Multivariate logistic regression identified PIR and CYP2C19 genotype as independent risk factors for stable carotid plaque (PIR, OR: 0.984, 95% CI: 0.974–0.995, p=0.003; intermediate metabolizer, OR: 0.158, 95% CI: 0.066–0.379, p<0.001; poor metabolizer, OR: 0.584, 95% CI: 0.155–2.206, p=0.428) and unstable carotid plaque (PIR, OR: 0.957, 95% CI: 0.949–0.966, p<0.001; intermediate metabolizer, OR: 0.151, 95% CI: 0.063–0.362, p<0.001; poor metabolizer, OR: 0.145, 95% CI: 0.051–0.416, p<0.001). Areas under the ROC curve for predicting unstable and stable carotid plaques were 0.700 (PIR) and 0.716 (CYP2C19 genotype), and 0.631 (PIR) and 0.650 (CYP2C19 genotype), respectively.
Conclusion: The PIR and CYP2C19 genotype are correlated with and may predict carotid plaque types in AIS.
The occurrence and development of ischemic stroke are driven by the co-action of multiple factors, among which unstable carotid plaques play a crucial role and pose an even greater hazard than does carotid artery stenosis.1,2 Unstable carotid plaques directly cause cerebral thrombosis, which disrupts the local blood supply in the brain and ultimately induces hypoxia, ischemia, and even liquefactive necrosis of brain tissue.3 Since unstable carotid plaques are a key therapeutic target in acute ischemic stroke (AIS), it is meaningful to investigate the potential risk factors associated with carotid plaques in AIS patients.
Unstable plaque refers to a dangerous plaque that is prone to rupture, thrombosis, and/or rapid progression.1,2 Unstable carotid plaques are characterized by a thin fibrous cap, a large lipid core, and an abundance of inflammatory cells. The probability of rupture of the luminal surface of the unstable plaque and intraplaque hemorrhage is high.1,2 Although computed tomography (CT), magnetic resonance imaging (MRI), and other methods have been used to diagnose carotid artery stenosis with high accuracy, they are associated with disadvantages such as high cost, inconvenient operation, and poor repeatability. Ultrasound examination is now being increasingly used to evaluate the characteristics of unstable carotid artery plaques, including plaque size, position, range, morphology, echo characteristics, and the presence or absence of ulcers, thrombosis, etc., on the surface.1,2
Extensive research4-6 indicates that platelets typically remain in a quiescent state rather than adhering to the vascular endothelium. However, certain conditions such as endothelial cell damage, impaired anti-thrombotic function, activation of platelets or coagulation factors, and fibrin formation, can trigger the release of thrombin and other platelet inducers, which promotes platelet adhesion to vessel walls. The adhered platelets can continue to interact with fibrin, resulting in further platelet aggregation and producing platelet clumps. Ultimately, this process culminates in the development of unstable plaques, which may result in arterial thrombosis.4-6 Recent studies7,8 have found that increased platelet activation is significantly correlated with atheromatous plaque formation in the walls of large arteries. Additionally, patients receiving antiplatelet drugs tend to have more stable atheromatous plaques with reduced plaque area and thickness than those who do not receive these prevention measures; the latter group is more likely to develop unstable plaques with larger plaque areas.7,8
The role of platelet activation in atherosclerotic disease progression has been demonstrated by a reduction of major adverse cardiovascular and cerebrovascular events after platelet inhibition therapies.7,8 The platelet-inhibition rate (PIR) is commonly used to evaluate the efficacy of platelet-inhibition therapies and to select antiplatelet drugs. Among antiplatelet drugs, P2RY12 receptor inhibitors (e.g., ticagrelor, clopidogrel) treat atherosclerotic stroke more effectively than other antiplatelet drugs.9,10 Hence, P2RY12 receptors are a promising therapeutic target in atherosclerosis. Despite new guidelines do not recommending ticagrelor as the primary treatment for AIS and coronary heart disease, clopidogrel remains the most prescribed type of P2RY12 inhibitor in China.10 Clopidogrel is metabolized by cytochrome P450, especially CYP2C19, into active metabolites that irreversibly bind with adenosine diphosphate (ADP) receptors on platelets to prevent thrombosis.11 Furthermore, CYP2C19 genotypes have been linked to high platelet reactivity.12,13 However, it is unclear how the ADP-induced platelet response and different CYP2C19 genotypes relate to the properties of carotid plaques in AIS patients. Therefore, we designed this study to identify whether the ADP-induced platelet response and CYP2C19 genotypes are associated with carotid plaque properties (stable vs. unstable plaques) among AIS patients, and whether these indicators can be used to predict carotid plaque types, which would improve clinical diagnosis and treatment decisions in AIS.
Methods
Study subjects
We retrospectively enrolled patients with emerging or re-emerging AIS treated in the neurology department of the Second Affiliated Hospital, Guangzhou Medical University, during January 2019–December 2022. The diagnosis of AIS was based the American Heart Association/American Stroke Association criteria, and MRI or CT.14 The study conformed to the tenets of the Helsinki Declaration, and received ethical approval (approval number: 2023-LCYJ-XS-23) from the ethics committee of our hospital, which waived the requirement of patient consent for this retrospective study. We registered this study on the Chinese Clinical Trial Registry website (registration number: ChiCTR2300073944).
Inclusion criteria
Carotid ultrasonography and assessment of the ADP-induced platelet-inhibition rate (ADP-PIR) were performed at our hospital.
For calculation of the ADP-PIR, the maintenance dose of clopidogrel (75 mg/d) was required to be administered for more than 3 days because ADP-induced platelet reactivity reaches a steady state at 3–7 days. In this study, the ADP-PIR was calculated after 5±2 days of clopidogrel administration.
No treatment with another P2Y12 inhibitor or medication that might affect blood coagulation function within the past week (heparin, warfarin, ticagrelor, cilostazol, rivaroxaban, etc.).
Age ≥35 years and <90 years
The platelet count inclusion criterion of >100 × 10⁹/L and <600×10⁹/L was set to ensure participants have a platelet count that minimizes risks associated with abnormal levels. This range excludes individuals with thrombocytopenia (low counts increasing bleeding risk) and thrombocytosis (high counts increasing clotting risk), thereby protecting participant safety and ensuring reliable study outcomes.
Exclusion criteria
Severe cardiac, hepatic, or renal damage; concurrent bleeding; malignancies; respiratory disorders; or immune system diseases
Recent history of a major surgical procedure or significant trauma
No history of statin and antithrombotic drug treatment within the past week
History of anticoagulant therapy for cardiogenic cerebral embolism or apoplexy associated with brain tumors
Insufficient clinical information
Patient data
We gathered the following patient data through the medical records system of our hospital: (1) clinicodemographic information, including sex, age, blood pressure, and medical, personal, medication, and family history; (2) National Institutes of Health Stroke Scale (NIHSS) score, which indicated stroke severity; (3) CYP2C19 genotype; (4) imaging data, including brain MRI or CT scans, and carotid ultrasonography; and (5) laboratory test results, including PIR, complete blood count, lipid profile, glucose level, coagulation function, biochemical profile, and hemoglobin A1c (HbA1c) level.
Carotid plaque examination
Carotid plaque examination was jointly performed by 2 professionally trained and licensed technicians, by using high-resolution ultrasonography (Philips IE33 Color Doppler Echocardiography machine; Philips, Amsterdam, The Netherlands). The technicians searched for plaques in the common carotid artery (near and far walls), carotid bifurcation, and internal carotid artery.15 Plaque dimensions, including the diameter of the upper and lower ends of the plaque, total plaque length, and maximum plaque thickness, were measured on long-axis images of the vessel. In the case of asymmetrical plaques, examination in the transverse plane was used to ascertain the maximum plaque thickness. Carotid plaques were defined according to the combined thickness of the tunica intima and tunica media of the local arterial wall: (i) localized intima-media thickness (IMT) ≥1.5 mm, or (ii) localized IMT ≥ 0.5 mm and at least 50% thicker than the adjacent IMT.16
The echo intensity of the plaque was categorized as strong, high, equal, or low, by comparison with the following reference standards: blood was defined as “anechoic”; the sternocleidomastoid muscle was “isoechoic”; and the adventitia of the vessel walls were “hyperechoic.” An echo signal was considered “low” or “hypoechoic” if it was below that of the sternocleidomastoid muscle, “equal” or “isoechoic” if it was the same as that of the sternocleidomastoid muscle, and “high” or “hyperechoic” if it was the same as that of the vascular adventitia. Hyperechoic signals with a sound shadow were considered as “strong” echo signals. Plaques with more than 2 different echo intensities were considered to have “mixed” echo signals. The ultrasound reports primarily focused on the physical attributes of the plaques, including low, high, and mixed echo signals. Hypoechoic plaques, which contain lipid components, are fragile and susceptible to rupture and bleeding, leading to thrombosis.15,17 Therefore, hypoechoic plaques and those associated with symptoms of transient cerebral ischemia were defined as “unstable” plaques in this study. Conversely, isoechoic plaques, hyperechoic plaques, and plaques containing a hyperechoic acoustic shadow within calcified lesions were considered “stable.”
Measurement of platelet function by thromboelastography
ADP-PIR was determined using thromboelastography (TEG 5000, Shenzhen Yuepu Corp., China). After treatment with clopidogrel (75 mg/day) for 5±2 days, we collected 2 venous blood samples from each patient: a 3-mL sample in a heparin-containing tube and a 2-mL sample in a sodium citrate-containing tube. The samples were used for the ADP-PIR test within 2 hours after collection. Platelet reactivity induced by ADP activators was calculated according to the manufacturer’s instructions (Thromboelastography 5000Hemostasis system, Shenzhen Lepu Corporation), by using the following equation:
ADP-PIR (%)=1-[(MAADP−MAfibrin)/(MAthrombin − MAfibrin)] *100%, where MA indicates the maximum amplitude of clot strength, and MAADP, MAfibrin, and MAthrombin represent the ADP-induced, ADP activator-induced, and thrombin-induced clot strength, respectively.
CYP2C19 genotyping
The CYP2C19 genotypes were detected using DNA microarray chips. First, genomic DNA was extracted from human peripheral blood cells and purified as per the instructions provided in the nucleic acid-extraction kit. Second, the CYP2C19 gene was amplified using specific primer pairs under the following cycling conditions: initial denaturation at 50°C for 5 min; 94°C for 5 min; followed by 35 cycles of denaturation at 94°C for 25 s, annealing at 48°C for 40 s, and extension at 72°C for 30 s; and a final extension at 72°C for 5 min. The primer pairs used for CYP2C19*2 (rs4244285) were AAAGCAGGTATAAGTC (forward) and CATCCGTAGTAAACAC (reverse), while those used for CYP2C19*3 (rs4986893) were CACTTTCATCCTGGGCTGTG (forward) and TCTTTTCCAGATATTCACCCCAT (reverse). Third, the biotin-labeled amplification products were hybridized with the CYP2C19 genotype-detection probe fixed on an aldehyde substrate. The specific hybridization signal was visualized through enzymatic color reaction. Fourth, the hybridization patterns formed by the sample DNA-amplification products and the wild-type or mutation-type probes on the DNA microarrays were scanned and analyzed to determine the CYP2C19 genotype. Finally, patients were grouped using their CYP2C19 genotypes as follows: CYP2C19*1/*1, extensive metabolizers; CYP2C19*1/*2 or CYP2C19*1/*3, intermediate metabolizers; and CYP2C19*2/*2, CYP2C19*3/*3, or CYP2C19*2/*3, poor metabolizers. The necessary reagents (immunochromogenic reagents, nucleic acid-extraction and purification reagents, etc.) and instruments (PCR-amplification instrument, automatic hybridization instrument, genotype-analysis software, biochip reader, etc.) were purchased from Shanghai BioTEC Co. Ltd.
Statistical analysis
Data were statistically analyzed using SPSS Statistics (v27.0). According to the results of carotid ultrasonography, patients were categorized into 3 groups: no carotid plaque group (NCP group), unstable carotid plaque group (UCP group), and stable carotid plaque group (SCP group). Continuous variables were reported as mean ± standard deviation or median (interquartile range), while categorical variables were presented as numbers and percentages. Baseline characteristics were compared among the 3 carotid plaque groups by using the chi-squared test (categorical variables), or one-way analysis of variance or the Mann-Whitney U-test (continuous variables). Violin plots were used to illustrate the variations in PIR among the different carotid plaque groups, while column plots were used to demonstrate the discrepancies in PIR among individuals with different CYP2C19 genotypes. Potential risk factors for stable and unstable carotid plaques were identified using univariate logistic regression analysis. The parameters with significant between-group differences in the univariate analyses (p<0.05) were subjected to multivariate logistic regression analysis, with the NCP group as the reference group and adjustments for potential confounders. The ability of PIR and CYP2C19 genotype to predict stable and unstable carotid plaques was assessed using receiver operating characteristic (ROC) curves. Differences were considered statistically significant at p<0.05.
Results
Patient enrollment
According to our electronic records system, 36,621 patients were diagnosed with cerebral infarction (ICD-36.9) in our hospital between January 2019 and December 2022, of which 6541 patients had CT- or MRI-verified diagnoses. After applying the inclusion criteria, we found that 1023 participants were eligible for enrollment; of whom, 331 patients were excluded according to the exclusion criteria. Thus, ultimately, 692 participants were enrolled in this study. According to their carotid plaque characteristics, 186 (26.9%) subjects were assigned to the NCP group, 128 (18.5%) subjects to the SCP group, and 378 (54.6%) subjects to the UCP group. A total of 329 patients underwent genetic testing for CYP2C19, and the results were as follows: extensive metabolizers, 133 (40%) patients; intermediate metabolizers, 108 (33%) patients; and poor metabolizers, 88 (27%) patients (Figure 1).
- Flow chart depicting the study design. CT - computed tomography, MRI - magnetic resonance imaging, NCP - no carotid plaque, SCP - stable carotid plaque, TEG - thromboelastography, UCP - unstable carotid plaque
General clinical data
The differences in general clinical data among the NCP, SCP, and UCP groups are summarized in Table 1. The following parameters showed statistically significant differences among the NCP, SCP, and UCP groups: age (p<0.001), history of treatment with a calcium channel blocker (CCB; p= 0.017), hypertension (p=0.016), diabetes (p=0.025), high-density lipoprotein (HDL) level (p=0.012), HbA1C (p=0.002), PIR (p<0.001), and CYP2C19 genotype (p<0.001, n=329).
- Characteristics of patients stratified by carotid plaque type.
PIR
PIR was significantly lower in the UCP group than in the NCP (p<0.001) and SCP groups (p= 0.0075), and significantly higher in the intermediate and extensive metabolizer groups than in the poor metabolizer group (p<0.001 for both). Furthermore, the PIR at the baseline significantly better in the NCP group and in extensive metabolizers than in the SCP group and intermediate metabolizers, respectively (p<0.001 for both).
Univariate logistic regression analysis
Univariate logistic regression analyses indicated that age, hypertension, diabetes, previous CCB treatment, HDL level, and PIR were likely associated with stable carotid plaques (n=692, p<0.05), while age, diabetes, HDL level, serum uric acid (UA) level, and PIR were potentially related to unstable carotid plaques (n= 692, p<0.05; Table 2). The presence of numerous missing values for the CYP2C19 genotype necessitated its exclusion from the data analysis. Nevertheless, our findings still support an association of the CYP2C19 genotype with both stable and unstable carotid plaques (n=329, p<0.05; Table 3).
- Univariate logistic regression analyses for the SCP and UCP groups (n=692).
- Univariate logistic regression analyses for the patients with CYP2C19 genotyping data in the SCP and UCP groups (n=329).
Multivariate logistic regression analysis
With the NCP group as the control group, multivariate regression analyses identified the following as independent risk factors for unstable carotid plaques (Table 4): PIR (odds ratio [OR]: 0.957, 95% confidence interval [CI]: 0.949–0.966, p<0.001), intermediate metabolizer (n = 392; OR: 0.151, 95% CI: 0.063–0.362, p<0.001), poor metabolizer (n=392; OR: 0.145, 95% CI: 0.051–0.416, p<0.001), age (OR: 1.055, 95% CI: 1.034–1.077, p<0.001), HDL level (OR: 0.405, 95% CI: 0.178–0.919, p=0.031), UA level (OR: 1.003, 95% CI: 1.001–1.005, p=0.008), and diabetes (OR: 0.625, 95% CI: 0.395–0.991, p=0.046).
- Multivariate logistic regression analyses for the SCP and UCP groups.
The following parameters were shown to independently predict stable carotid plaques in the multivariate analyses: PIR (OR: 0.984, 95% CI: 0.974–0.995, p=0.003), intermediate metabolizer (n =392; OR: 0.158, 95% CI: 0.066–0.379, p<0.001), poor metabolizer (n=392; OR:0.584, 95% CI: 0.155–2.206, p=0.428), age (OR: 1.074, 95% CI: 1.049–1.100, p< 0.001), and HDL (OR: 0.337, 95% CI: 0.124–0.912, p=0.032).
ROC curve analysis
The overall ability of the PIR and CYP2C19 genotypes to discriminate between different types of carotid plaques was analyzed using ROC curves (Figure 2). In terms of predicting stable carotid plaques, the areas under the curve (AUCs) of PIR, CYP2C19 genotypes, and the combination of PIR + CYP2C19 genotypes were 0.631 (95% CI: 0.568–0.693), 0.650 (95% CI: 0.562–0.739), and 0.724 (95% CI: 0.645–0.803), respectively (Figure 2A). In terms of predicting unstable carotid plaques, the AUCs of the above 3 factors were 0.700 (95% CI: 0.653–0.747), 0.716 (95% CI: 0.648–0.784), and 0.837 (95% CI: 0.784–0.890), respectively (Figure 2B).
- ROC curves showing the performance of PIR and CYP2C19 genotype in predicting the stability of carotid plaques. (A) ROC curves for predicting SCPs. (B) ROC curves for predicting UCPs.
Discussion
The present study showed that ADP-PIR was significantly lower in patients with unstable carotid plaques than in patients with stable or no carotid plaques, and significantly lower in patients with stable carotid plaques than in those with no carotid plaques. Furthermore, ADP-PIR was significantly worse in poor metabolizers than in intermediate and extensive metabolizers, and significantly worse in intermediate metabolizers than in extensive metabolizers. Finally, ROC curve analyses suggested that both ADP-PIR and CYP2C19 genotype may predict carotid plaque types in AIS patients.
The etiology of carotid plaques is multifactorial, and its common risk factors include age, hyperglycemia, hyperlipidemia, hypertension, hyperuricemia, and particularly, increased low-density lipoprotein levels.18,19 Carotid plaques are a main cause of stroke and cardiovascular disease, and unstable carotid plaques play a crucial role in the pathogenesis and progression of ischemic stroke.20,21 The early and accurate prediction of the development and type of carotid plaques enables prompt intervention, which is beneficial for reducing the occurrence and recurrence rates of AIS.
The current standard clinical therapy for carotid plaques consists of lipid-lowering drugs (e.g., statins). However, more than 50% of patients who receive statin therapy for the management of carotid plaques do not derive a clinical benefit in terms of preventing AIS occurrence/recurrence.22 Therefore, numerous studies have explored new therapeutic targets for atherosclerosis, and recent reports have suggested that P2RY12 receptor inhibitors (e.g., clopidogrel, ticagrelor) yield better treatment results than other medications in terms of preventing the occurrence/recurrence of atherosclerotic stroke.9,10,23,24 Animal experiments have revealed that P2RY12 receptors are essential for maintaining cholesterol homeostasis in advanced atherosclerosis; this suggests that P2RY12 receptor inhibitors might be useful for treating atherosclerotic diseases, especially unstable atherosclerotic plaques.25 Thus, the P2RY12 receptors on vessel walls, in addition to those on platelets, are a new therapeutic target for the management of atherosclerotic plaques. Additionally, multiple authors have confirmed a correlation between the efficacy of P2RY12 receptor inhibitors and CYP2C19 genotypes.12,13 However, limited research has examined the relationship between platelet aggregation rate, CYP2C19 genotype, and carotid plaques. Considering that antiplatelet agents are widely used for the secondary prevention of atherosclerotic ischemic stroke, we designed this study to explore the relationship between ADP-induced platelet response, CYP2C19 genotypes, and carotid plaque types in patients with AIS.
In our study, the prevalence rates of stable and unstable carotid plaques were 18.5% and 54.6%, respectively, which are aligned with prior studies.18,19 Compared with SCP group patients, UCP group patients had a lower PIR and higher frequencies of the CYP2C19*2 and CYP2C19*3 alleles. ROC curve analyses showed that the AUCs of PIR, CYP2C19 genotypes, and the combination of PIR + CYP2C19 genotypes in the UCP group were similar (0.700, 0.716, and 0.839, respectively). In the NCP and SCP groups, the AUCs of the above 3 predictors were smaller; nevertheless, they still had a certain predictive value (PIR: 0.631 vs. CYP2C19*2 or *3: 0.650 vs. PIR + CYP2C19 genotypes: 0.724), and the between-group difference in PIR was significant. Hence, it is possible to use ADP-PIR and CYP2C19 genotypes, and especially, the combination of PIR + CYP2C19 genotypes, to predict the nature of carotid plaques in AIS patients. Related studies have confirmed that not all antiplatelet drugs can effectively inhibit platelet function.10,13 Although relevant treatment guidelines have not explicitly recommended ticagrelor as the first choice of antiplatelet drugs, the low platelet inhibition rate in atherosclerotic stroke patients suggests that clopidogrel should be replaced with other P2Y12 receptor inhibitors, such as ticagrelor, which may improve the platelet inhibition rate and treat carotid artery atherosclerotic disease.9,10 PIR and CYP2C19 genotypes play an important role in the formulation of individualized antiplatelet treatment programs for patients with atherosclerotic stroke.
Platelets are crucially involved in regulating the occurrence and progression of atherosclerotic plaques.8,26,27 Platelet consumption can reduce plaque size and the prevalence of unstable plaques. In our study, multivariate logistics regression analyses revealed that even after adjustments for confounders, PIR and CYP2C19 genotypes were correlated with both unstable and stable carotid plaques. In contrast, blood lipids (e.g., total cholesterol and triglycerides), blood glucose, and hypertension were not associated with carotid plaques, which is not consistent with previous studies.18,19 The reason for this difference may be the long-term administration of antilipemic, antiglycemic, and antihypertensive medications prior to the onset of the disease. Most AIS events are caused by the aggregation of platelets and the formation of a plaque, followed by plaque rupture or bleeding, which leads to the formation of unstable plaques that break off and enter the local microcirculation in the brain. In this study, ADP-PIR and CYP2C19 genotypes were identified as independent risk factors for unstable and stable carotid plaques, and both factors could predict carotid plaque types in patients with AIS. However, since CYP2C19 genotypes are not widely assessed, other cerebrovascular biomarkers are required to screen for disease, recognize plaques, assess treatment efficacy, and ultimately, prevent stroke recurrence in patients with carotid plaques, whether stable or unstable. Based on the above analysis, the PIR and CYP2C19 genotype should be added to the risk model for outcomes in patients with carotid plaques, which could offer a novel method to improve risk stratification for AIS patients in clinical practice. Age and HDL level have been verified as risk factors for atherosclerotic plaque formation in large arteries.18,19 Multivariate logistic regression analyses in our study confirmed the above finding, and showed that age and HDL level were related to both stable and unstable carotid plaques. Moreover, the analysis indicated that diabetes and serum UA were associated with unstable carotid plaques.
This study has some limitations. First, the retrospective design of the study could introduce bias in some indicators. For example, the history of smoking and transient ischemic attacks were collected by reviewing the electronic medical records, and it was likely that the doctors recording this information did not inquire about these factors in detail, resulting in negative records. Second, this research was a single-center study; multicenter prospective studies are required to verify the correlation of carotid plaque types with ADP-PIR and CYP2C19 genotypes. Third, medications have an obvious confounding effect on biomarker concentrations; indeed, this is a common limitation of case-control biomarker studies. Specifically, many subjects in the present study had taken anti-atherosclerotic, anti-hyperglycemic, and anti-hypertensive drugs before the occurrence of stroke. Even though common medications were used, and even though they were classified as confounders in the multivariate logistics regression analyses to exclude potential confounding effects, the adverse effects of drugs on biomarker levels (such as lipid and glucose levels) could not be eliminated. As a result, our study may exaggerate the predictive power of ADP-PIR and CYP2C19 genotypes, and underestimate the predictive value of other biomarkers. On the other hand, to be clinically useful, biomarkers must predict increased disease risk in the population with mass drug administration. Fourth, PIR is a dynamic biomarker;12 hence, our future study will aim to dynamically assess PIR, instead of limiting this assessment to about a week of administration. Finally, we did not perform independent validation cohort studies to lend more credibility to our findings, so we intend to pursue this in our future research. Notwithstanding the above limitations, in this study, all patients were strictly selected using the defined inclusion and exclusion criteria. Appropriate statistical methods were employed to derive the results, and the reasonable results provided candidate biomarkers that clinicians can use for the early identification of carotid plaque types, which could help prevent the recurrence of stroke.
Conclusion
In summary, our study suggested that both ADP-PIR and CYP2C19 genotype were correlated with stable and unstable carotid plaques. Furthermore, PIR and CYP2C19 genotype may possess the capability to predict the type of carotid plaques (stable vs. unstable) in patients with AIS. As an easily accessible parameter, PIR has the potential to become a crucial indicator for the clinical prevention and control of AIS recurrence.
Acknowledgments
We would like to acknowledge Editage (www.editage.com) for their professional English editing services provided for our paper.
Footnotes
Disclosure. Authors have no conflict of interests, and the work was not supported or funded by any drug company.
- Received September 15, 2024.
- Accepted May 17, 2025.
- Copyright: © Neurosciences
Neurosciences is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work.
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