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RESEARCH ARTICLE

Analysis of PTGS1 and PEAR1 Polymorphisms for Aspirin Resistance Prediction in Patients with Cerebral Infarction

The Open Medicinal Chemistry Journal 11 Nov 2025 RESEARCH ARTICLE DOI: 10.2174/0118741045412609251014072341

Abstract

Introduction

This study aimed to evaluate the predictive potential of prostaglandin-endoperoxide synthase 1 (PTGS1) and platelet endothelial aggregation receptor-1 (PEAR1) gene polymorphisms, combined with biochemical and demographic factors, for aspirin resistance (AR) and recurrence of cerebral infarction (CI) in Chinese patients.

Methods

A retrospective study was conducted on 280 CI patients admitted to the Department of Neurology, Affiliated Hospital of Beihua University, between January and December 2021. Based on telephone follow-up, patients were divided into recurrent (n = 97) and non-recurrent (n = 183) groups. Clinical characteristics, medical history, and laboratory indicators were collected. Genotyping for PEAR1 and PTGS1 was performed. Logistic regression identified independent predictors, and receiver operating characteristic (ROC) curves evaluated predictive performance.

Results

Univariate analysis showed significant differences in PEAR1 and PTGS1 genotypes, hypertension, and homocysteine (HCY) levels between groups (P < 0.05). Multivariate analysis showed PEAR1, PTGS1, and HCY as independent predictors of recurrence (p < 0.05). ROC analysis revealed AUC values as follows: PEAR1 = 0.529, PTGS1 = 0.642, HCY = 0.696, and combined model = 0.721.

Discussion

PEAR1 may influence platelet activation, while PTGS1 can alter COX-1 function, reducing aspirin’s antiplatelet efficacy. Elevated HCY promotes endothelial dysfunction and thrombosis. The combined model offered superior predictive value, supporting its potential clinical utility in guiding antiplatelet therapy for individualized risk stratification. However, this single-center study with a limited sample size requires validation in larger multicenter cohorts.

Conclusion

PEAR1 and PTGS1 genes integrated with HCY can effectively predict the risk of recurrence in patients with cerebral infarction.

Keywords: PEAR1, PTGS1, Cerebral infarction, Recurrence, Prediction model, Neurological symptoms.
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