Risha Nahar1, Renu Saxena2, Roumi Deb3, Rajiv Parakh4, Sujay Shad5, Prahlad K Sethi6, Parul Takkar7, Ishwar C Verma8. 1. Krishna Institute of Medical Sciences (KIMS), KIMS Foundation and Research Center (KFRC), Hyderabad, India; Center of Medical Genetics, Sir Ganga Ram Hospital,, New Delhi; Amity Institute of Biotechnology, Amity University, Noida, India. Electronic address: rishanahar@gmail.com. 2. Center of Medical Genetics, Sir Ganga Ram Hospital,, New Delhi; Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 3. Amity Institute of Biotechnology, Amity University, Noida, India; Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 4. Division of Peripheral Vascular & Endovascular Sciences, Medicity Medanta Hospital, New Delhi, India; Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 5. Department of Cardiac Surgery, Sir Ganga Ram Hospital, New Delhi, India; Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 6. Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 7. Department of Research, Sir Ganga Ram Hospital, New Delhi, India; Department of Neurology, Sir Ganga Ram Hospital, New Delhi, India. 8. Center of Medical Genetics, Sir Ganga Ram Hospital,, New Delhi.
Abstract
AIMS: The study aims to evaluate the impact of genetic, demographic and clinical data on various measures of outcome of anticoagulation quality in patients. PATIENTS AND METHODS: The study consisted of 310 patients receiving long-term oral anticoagulation therapy in our hospital. Apart from demographic and clinical variables, 21 SNPs (in 7 genes) were analyzed and compared with the outcomes of anticoagulation therapy. Various outcomes that were measured are; supra therapeutic INRs (INR >3, >6), anticoagulation stabilization, time taken to stabilize and proportion of INRs within (2-3), above (>3) and below (<2) therapeutic range. RESULTS: Supra therapeutic INRs were influenced by CYP2C9*2, *3, CYP4F2 rs2108622, VKORC1-1639G>A, 1173C>T, rs55894764 along with concomitant drugs, smoking, body weight and height. Persistently fluctuating INRs/absolute instability correlated with VKORC1-1639G>A, gender, height and body mass index. The time taken to stabilize was associated with CYP4F2 rs2108622, CYP2C9*14, smoking, clinical indication and concomitant drugs. The overall distribution of INR was influenced by variants in CYP4F2 rs2108622, CYP2C9*3, rs9332230, VKORC1 1173C>T, -1639G>A, rs55894764, ABCB1 rs2032582, rs1128503, rs1045642 and F5 rs6025, age, smoking and concomitant drugs. CONCLUSIONS: Knowledge of factors influencing the quality of long term anticoagulation can help clinicians to customize therapy either by dose variation, therapy with alternate choice of drug, concurrent heparin therapy and/or frequent INR monitoring.
AIMS: The study aims to evaluate the impact of genetic, demographic and clinical data on various measures of outcome of anticoagulation quality in patients. PATIENTS AND METHODS: The study consisted of 310 patients receiving long-term oral anticoagulation therapy in our hospital. Apart from demographic and clinical variables, 21 SNPs (in 7 genes) were analyzed and compared with the outcomes of anticoagulation therapy. Various outcomes that were measured are; supra therapeutic INRs (INR >3, >6), anticoagulation stabilization, time taken to stabilize and proportion of INRs within (2-3), above (>3) and below (<2) therapeutic range. RESULTS: Supra therapeutic INRs were influenced by CYP2C9*2, *3, CYP4F2rs2108622, VKORC1-1639G>A, 1173C>T, rs55894764 along with concomitant drugs, smoking, body weight and height. Persistently fluctuating INRs/absolute instability correlated with VKORC1-1639G>A, gender, height and body mass index. The time taken to stabilize was associated with CYP4F2rs2108622, CYP2C9*14, smoking, clinical indication and concomitant drugs. The overall distribution of INR was influenced by variants in CYP4F2rs2108622, CYP2C9*3, rs9332230, VKORC1 1173C>T, -1639G>A, rs55894764, ABCB1rs2032582, rs1128503, rs1045642 and F5 rs6025, age, smoking and concomitant drugs. CONCLUSIONS: Knowledge of factors influencing the quality of long term anticoagulation can help clinicians to customize therapy either by dose variation, therapy with alternate choice of drug, concurrent heparin therapy and/or frequent INR monitoring.
Authors: Alison E Fohner; Renee Robinson; Joseph Yracheta; Denise A Dillard; Brian Schilling; Burhan Khan; Scarlett Hopkins; Bert Boyer; Jynene Black; Howard Wiener; Hemant K Tiwari; Adam Gordon; Deborah Nickerson; Jesse M Tsai; Federico M Farin; Timothy A Thornton; Allan E Rettie; Kenneth E Thummel Journal: Pharmacogenet Genomics Date: 2015-07 Impact factor: 2.089
Authors: Aditi Shendre; Todd M Brown; Nianjun Liu; Charles E Hill; T Mark Beasley; Deborah A Nickerson; Nita A Limdi Journal: Pharmacotherapy Date: 2016-03-14 Impact factor: 4.705
Authors: Samantha Wasniewski; Luciano Consuegra-Sánchez; Pablo Conesa-Zamora; Luis García de Guadiana-Romualdo; Pablo Ramos-Ruiz; Marta Merelo-Nicolás; F Guillermo Clavel-Ruipérez; Begoña Alburquerque-González; Federico Soria-Arcos; Juan A Castillo-Moreno Journal: Biomed Res Int Date: 2018-10-17 Impact factor: 3.411