Urine metabolites as a predictor of warfarin response based on INR in atrial fibrillation

• Main Authors: Bawadikji, Abdulkader Ahmad, Teh, Chin-Hoe, Kader, Muhamad Ali Bin Sheikh Abdul, Sulaiman, Syed Azhar Syed, Ibrahim, Baharudin
• Format: Article
• Published: Bentham Science Publ Ltd 2022
• Subjects: RS Pharmacy and materia medica
• Online Access: http://eprints.um.edu.my/46289/; https://doi.org/10.2174/1389200223666220413112649

Background: Warfarin is an anticoagulant with wide inter-individual variations in drug responses monitored based on the International Normalized Ratio (INR). It is commonly prescribed for Atrial Fibrillation (AF) and stroke. Oral anticoagulants (e.g., warfarin) reduce the risk of getting a stroke but increase the risk of hemorrhage. The proton Nuclear Magnetic Resonance (H-1-NMR) pharmacometabonomics technique is useful for determining drug responses. Furthermore, pharmacometabonomics analysis can help identify novel biomarkers of warfarin outcome/INR stability in urine. Objectives: The focus of this research was to determine if urine metabolites could predict the warfarin response based on INR in patients who were already taking warfarin (identification; phase I) and to determine if urine metabolites could distinguish between unstable and stable INR in patients who had just started taking warfarin (validation; phase II). Methods: A cross-sectional study was conducted. Ninety urine samples were collected for phase 1, with 49 having unstable INR and 41 having stable INR. In phase II, 21 urine samples were obtained, with 13 having an unstable INR and eight having a stable INR. The metabolites associated with unstable INR and stable INR could be determined using univariate and multivariate logistic regression analysis. Results: Multivariate Logistic Regression (MVLR) analysis showed that unstable INR was linked with seven regions. Discussion: The urine pharmacometabonomics technique utilized could differentiate between the urine metabolite profiles of the patients on warfarin for INR stability. Conclusion: H-1-NMR-based pharmacometabonomics can help lead to a more individualized, controlled side effect for warfarin, thus minimizing undesirable effects in the future.