Influence of SH2B3, MTHFD1L, GGCX, and ITGB3 Gene Polymorphisms on theVariability on Warfarin Dosage Requirements and Susceptibility to CVD in the Jordanian Population
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Data Collection and Follow-Up Time
2.3. Outcome Measure
2.4. SNP Selection and Genotyping
2.5. Statistical Analysis
3. Results
3.1. Patient Characteristics
3.2. Genotyping and Allelic Frequencies
3.3. Association of SH2B3 and MTHFD1L Polymorphisms with Warfarin Sensitivity during the Initiation and Stabilization Phases of Therapy
3.4. Association of SH2B3 and MTHFD1L Polymorphisms and Warfarin Responsiveness during Initiation and Stabilization Phases of Therapy
3.5. Association between Warfarin Dose and Clinical Data
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
- Vogel, F. Moderne Probleme der Humangenetik. Ergebnisse der Inneren Medizin und Kinderheilkunde; Springer: Berlin/Heidelberg, Germany, 1959; pp. 52–125. [Google Scholar]
- Mroziewicz, M.; Tyndale, R.F. Pharmacogenetics: A tool for identifying genetic factors in drug dependence and response to treatment. Addict. Sci. Clin. Pract. 2010, 5, 17. [Google Scholar] [PubMed]
- Kim, Y.; Smith, A.; Wu, A.H. C3435T polymorphism of MDR1 gene with warfarin resistance. Clin. Chim. Acta 2013, 425, 34–36. [Google Scholar] [CrossRef] [PubMed]
- Eriksson, N.; Wadelius, M. Prediction of warfarin dose: Why, when and how? Pharmacogenomics 2012, 13, 429–440. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dentali, F.; Donadini, M.P.; Clark, N.; Crowther, M.A.; Garcia, D.; Hylek, E. Brand name versus generic warfarin: A systematic review of the literature. Pharmacother. J. Hum. Pharmacol. Drug Ther. 2011, 31, 386–393. [Google Scholar] [CrossRef]
- Eichelbaum, M.; Ingelman-sundberg, M.; Evans, W.E. Pharmacogenomics and Individualized drug theraby. Annu. Rev. Med. 2006, 57, 119–137. [Google Scholar] [CrossRef]
- D’Andrea, G.; D’Ambrosio, R.L.; Di Perna, P.; Chetta, M.; Santacroce, R.; Brancaccio, V.; Margaglione, M.A. Polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood 2005, 105, 645–649. [Google Scholar] [CrossRef]
- Muszkat, M.; Blotnik, S.; Elami, A.; Krasilnikov, I.; Caraco, Y. Warfarin metabolism and anticoagulant effect: A prospective, observational study of the impact of CYP2C9 genetic polymorphism in the presence of drug-disease and drug-drug interactions. Clin. Ther. 2007, 29, 427–437. [Google Scholar] [CrossRef]
- Al-Eitan, L.N.; Almasri, A.Y.; Al-Habahbeh, S.O. Effects of coagulation factor VII polymorphisms on warfarin sensitivity and responsiveness in Jordanian cardiovascular patients during the initiation and maintenance phases of warfarin therapy. Pharmacogenom. Personal. Med. 2019, 12, 1–8. [Google Scholar] [CrossRef] [Green Version]
- Pautas, E.; Moreau, C.; Gouin-Thibault, I.; Golmard, J.L.; Mahe, I.; Legendre, C.; Beaune, P. Genetic factors (VKORC1, CYP2C9, EPHX1, and CYP4F2) are predictor variables for warfarin response in very elderly, frail inpatients. Clin. Pharmacol. Ther. 2010, 87, 57–64. [Google Scholar] [CrossRef]
- Kumar, D.K.; Shewade, D.G.; Loriot, M.A.; Beaune, P.; Balachander, J.; Chandran, B.S.; Adithan, C. Effect of CYP2C9, VKORC1, CYP4F2 and GGCX genetic variants on warfarin maintenance dose and explicating a new pharmacogenetic algorithm in South Indian population. Eur. J. Clin. Pharmacol. 2014, 70, 47–56. [Google Scholar] [CrossRef]
- Caldwell, M.D.; Awad, T.; Johnson, J.A.; Gage, B.F.; Falkowski, M.; Gardina, P.; King, C.R. CYP4F2 genetic variant alters required warfarin dose. Blood 2008, 111, 4106–4112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lal, S.; Sandanaraj, E.; Jada, S.R.; Kong, M.C.; Lee, L.H.; Goh, B.C.; Chowbay, B. Influence of APOE genotypes and VKORC1 haplotypes on warfarin dose requirements in Asian patients. Br. J. Clin. Pharmacol. 2008, 65, 260–264. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Viitanen, L.; Pihlajamäki, J.; Miettinen, R.; Kärkkäinen, P.; Vauhkonen, I.; Halonen, P.; Laakso, M. Apolipoprotein E gene promoter (–219G/ T) polymorphism is associated with premature coronary heart disease. J. Mol. Med. 2001, 79, 732–737. [Google Scholar] [CrossRef] [PubMed]
- Al-Eitan, L.N.; Almasri, A.Y.; Al-habahbeh, S.O. Impact of a variable number tandem repeat in the CYP2C9 promoter on warfarin sensitivity and responsiveness in Jordanians with cardiovascular disease. Pharm. Pers. Med. 2019, 12, 15–22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Borgiani, P.; Ciccacci, C.; Forte, V.; Romano, S.; Federici, G.; Novelli, G. Allelic variants in the CYP2C9 and VKORC1 loci and interindividual variability in the anticoagulant dose effect of warfarin in Italians. Pharmacogenomics 2007, 8, 1545–1550. [Google Scholar] [CrossRef] [PubMed]
- Hamberg, A.K.; Dahl, M.L.; Barban, M.; Scordo, M.G.; Wadelius, M.; Pengo, V.; Jonsson, E.N. A PK-PD model for predicting the impact of age, CYP2C9, and VKORC1 genotype on individualization of warfarin therapy. Clin. Pharmacol. Ther. 2007, 81, 529–538. [Google Scholar] [CrossRef] [PubMed]
- AL-Eitan, L.N.; Tarkhan, A.H. Practical Challenges and Translational Issues in Pharmacogenomics and Personalized Medicine from 2010 Onwards. Curr. Pharm. Pers. Med. Former. Curr. Pharm. 2016, 14, 7–17. [Google Scholar] [CrossRef]
- Al-eitan, L.N.; Haddad, Y.A. Emergence of Pharmacogenomics in Academic Medicine and Public Health in Jordan: History, Present State and Prospects. Curr. Pharm. Pers. Med. Former. Curr. Pharm. 2014, 12, 167–175. [Google Scholar] [CrossRef]
- Xie, H.G.; Frueh, F.W. Pharmacogenomics steps toward personalized medicine. Per. Med. 2005, 2, 325–337. [Google Scholar] [CrossRef]
- Ji, Y.; Song, Y.; Wang, Q.; Xu, P.; Zhao, Z.; Li, X.; Chen, C. Sex-specific association of SH2B3 and SMARCA4 polymorphisms with coronary artery disease susceptibility. Oncotarget 2017, 8, 59397–59407. [Google Scholar] [CrossRef] [Green Version]
- Todd, J.A.; Walker, N.M.; Cooper, J.D.; Smyth, D.J.; Downes, K.; Plagnol, V.; Lowe, C.E. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes The Wellcome Trust Case Control Consortium. Nat. Genet. 2007, 39, 857–864. [Google Scholar] [CrossRef] [PubMed]
- Hong, L.; Jiang, Y.F.; Chen, M.; Zhang, N.N.; Yang, H.J.; Rui, Q.; Zhou, Y.F. Role of SH2B3 R262W gene polymorphism and risk of coronary heart disease A PRISMA-compliant meta-analysis. Medicine 2018, 97, e13436. [Google Scholar] [CrossRef] [PubMed]
- Palmer, B.R.; Slow, S.; Ellis, K.L.; Pilbrow, A.P.; Skelton, L.; Frampton, C.M.; Whalley, G.A. Genetic polymorphism rs6922269 in the MTHFD1L gene is associated with survival and baseline active vitamin B12 levels in post-acute coronary syndromes patients. PLoS ONE 2014, 9, e89029. [Google Scholar] [CrossRef] [PubMed]
- Angelakopoulou, A.; Shah, T.; Sofat, R.; Shah, S.; Berry, D.J.; Cooper, J.; Maniatis, N. Comparative analysis of genome-wide association studies signals for lipids, diabetes, and coronary heart disease: Cardiovascular Biomarker Genetics Collaboration. Eur. Heart J. 2012, 33, 393–407. [Google Scholar] [CrossRef] [Green Version]
- Samani, N.J.; Erdmann, J.; Hall, A.S.; Hengstenberg, C.; Mangino, M.; Mayer, B.; Barrett, J.H. UKPMC Funders Group Author Manuscript Genomewide Association Analysis of Coronary Artery Disease. N. Engl. J. Med. 2007, 357, 443–453. [Google Scholar] [CrossRef] [Green Version]
- Kamali, X.; Wulasihan, M.; Yang, Y.C.; Lu, W.H.; Liu, Z.Q.; He, P.Y. Association of GGCX gene polymorphism with warfarin dose in atrial fibrillation population in Xinjiang. Lipids Health Dis. 2013, 12, 149. [Google Scholar] [CrossRef] [Green Version]
- Weiss, L.A.; Veenstra-VanderWeele, J.; Newman, D.L.; Kim, S.J.; Dytch, H.; McPeek, M.S.; Abney, M. Genome-wide association study identifies ITGB3 as a QTL for whole blood serotonin. Eur. J. Hum. Genet. 2004, 12, 949–954. [Google Scholar] [CrossRef] [Green Version]
- Li, M.P.; Xiong, Y.; Xu, A.; Zhou, J.P.; Tang, J.; Zhang, Z.L.; Chen, X.P. Association of platelet ITGA2B and ITGB3 polymorphisms with ex vivo antiplatelet effect of ticagrelor in healthy Chinese male subjects. Int. J. Hematol. 2014, 99, 263–271. [Google Scholar] [CrossRef]
- Khatami, M.; Heidari, M.M.; Soheilyfar, S. Common rs5918 (PlA1/A2) polymorphism in the ITGB3 gene and risk of coronary artery disease. Arch. Med. Sci. Atheroscler. 2016, 1, 9–15. [Google Scholar] [CrossRef]
- Gage, B.F.; Lesko, L.J. Pharmacogenetics of warfarin: Regulatory, scientific, and clinical issues. J. Thromb. Thrombolysis 2008, 25, 45–51. [Google Scholar] [CrossRef]
- Md Arif, K.; Rahman, M.A. A Review of Warfarin Dosing and Monitoring. Faridpur. Med. Coll. J. 2018, 13, 40–43. [Google Scholar] [CrossRef]
- Klein, T.; Altman, R.; Eriksson, N. Europe PMC Funders Group Estimation of the Warfarin Dose with Clinical and Pharmacogenetic Data. N. Engl. J. Med. 2009, 360, 753–764. [Google Scholar] [PubMed]
- Higashi, M.K.; Veenstra, D.L.; Kondo, L.M.; Wittkowsky, A.K.; Srinouanprachanh, S.L.; Farin, F.M.; Rettie, A.E. Association Between CYP2C9 Genetic variants and anticoagulation-related outcomes during warfarin therapy. JAMA 2002, 287, 1690–1698. [Google Scholar] [CrossRef] [PubMed]
- AL-Eitan, L.N.; Almasri, A.Y.; Khasawneh, R.H. Effects of CYP2C9 and VKORC1 polymorphisms on warfarin sensitivity and responsiveness during the stabilization phase of therapy. Saudi Pharm. J. 2019, 27, 484–490. [Google Scholar] [CrossRef]
- AL-Eitan, L.; Almasri, A.; Khasawneh, R. Impact of CYP2C9 and VKORC1 Polymorphisms on Warfarin Sensitivity and Responsiveness in Jordanian Cardiovascular Patients during the Initiation Therapy. Genes 2018, 9, 578. [Google Scholar] [CrossRef] [Green Version]
- Soranzo, N.; Spector, T.D.; Mangino, M.; Kühnel, B.; Rendon, A.; Teumer, A.; Salo, P. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat. Genet. 2009, 41, 1182–1190. [Google Scholar] [CrossRef] [Green Version]
- Douroudis, K.; Kisand, K.; Nemvalts, V.; Rajasalu, T.; Uibo, R. Allelic variants in the PHTF1-PTPN22, C12orf30 and CD226 regions as candidate susceptibility factors for the type 1 diabetes in the Estonian population. BMC Med. Genet. 2010, 11, 11. [Google Scholar] [CrossRef] [Green Version]
- Zhernakova, A.; Elbers, C.C.; Ferwerda, B.; Romanos, J.; Trynka, G.; Dubois, P.C.; Bardella, M.T. Evolutionary and Functional Analysis of Celiac Risk Loci Reveals SH2B3 as a Protective Factor against Bacterial Infection. Am. J. Hum. Genet. 2010, 86, 970–977. [Google Scholar] [CrossRef] [Green Version]
- Dichgans, M.; Malik, R.; König, I.R.; Rosand, J.; Clarke, R.; Gretarsdottir, S.; Thorleifsson, G.; Mitchell, B.D.; Assimes, T.L.; Levi, C.; et al. Shared genetic susceptibility to ischemic stroke and coronary artery disease: A genome-wide analysis of common variants. Stroke 2014, 45, 24–36. [Google Scholar] [CrossRef] [Green Version]
- Ding, K.; Kullo, I.J. Geographic differences in allele frequencies of susceptibility SNPs for cardiovascular disease. BMC Med. Genet. 2011, 12, 55. [Google Scholar] [CrossRef] [Green Version]
- Muendlein, A.; Saely, C.H.; Rhomberg, S.; Sonderegger, G.; Loacker, S.; Rein, P.; Drexel, H. Evaluation of the association of genetic variants on the chromosomal loci 9p21.3, 6q25.1, and 2q36.3 with an giographically characterized coronary artery disease. Atherosclerosis 2009, 205, 174–180. [Google Scholar] [CrossRef] [PubMed]
Gene | SNP ID | Model | Patients % | Controls % | p-Value * |
---|---|---|---|---|---|
SH2B3 | AA/GA/GG | 39.6/42.9/17.4 | 42.2/41.3/16.4 | 0.86 | |
rs11065987 | AA/(GA + GG) | 39.6/60.4 | 42.2/57.8 | 0.58 | |
(AA + GA)/GG | 82.5/17.4 | 83.6/16.4 | 0.78 | ||
AA/AG/GG | 39.5/42.4/18.1 | 42.5/42.5/15.1 | 0.67 | ||
rs17696736 | AA/(AG + GG) | 39.5/60.5 | 42.5/57.5 | 0.54 | |
(AA + AG)/GG | 81.9/18.1 | 84.9/15.1 | 0.41 | ||
CC/TC/TT | 38.7/42/19.3 | 41.8/42.2/16 | 0.62 | ||
rs3184504 | CC/(TC + TT) | 38.7/61.3 | 41.8/58.2 | 0.51 | |
(CC + TC)/TT | 80.7/19.3 | 84/16 | 0.36 | ||
MTHFD1L | GG/CG/CC | 28.4/49.5/22.1 | 33.5/41.3/25.2 | 0.24 | |
rs491552 | GG/(CG + CC) | 28.4/71.6 | 33.5/66.5 | 0.27 | |
(GG + CG)/CC | 77.9/22.1 | 84.8/25.2 | 0.45 | ||
GG/AG/AA | 54.2/37.7/8 | 55.9/37.6/6.6 | 0.84 | ||
rs6922269 | GG/(AG + AA) | 54.2/45.8 | 55.9/44.1 | 0.74 | |
(GG + AG)/AA | 92/8 | 93.4/6.6 | 0.57 | ||
AA/GA/GG | 53.3/35.4/11.3 | 59.6/34.3/6.1 | 0.12 | ||
rs803422 | AA/(GA + GG) | 53.3/46.7 | 59.6/40.4 | 0.19 | |
(AA + GA)/GG | 88.7/11.3 | 93.9/6.1 | 0.06 | ||
AA/GA/GG | 86.7/12.8/0.5 | 79.8/18.3/1.9 | 0.1 | ||
rs803455 | AA/(GA + GG) | 86.7/13.3 | 79.8/20.2 | 0.06 | |
(AA + GA)/GG | 99.5/0.5 | 98.1/1.9 | 0.17 |
Gene | SNP ID | Genotype | Sensitive a | Moderate b | Resistance c | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | rs11065987 | AA | (14/84) 16.7% | (57/84) 67.9% | (13/84) 15.5% | 0.99 |
p-value * | 0.87 | 0.97 | 0.99 | |||
GA | (13/91) 14.3% | (63/91) 69.2% | (15/91) 16.5% | |||
p-value * | 0.96 | 1 | 0.99 | |||
GG | (5/37) 13.5% | (26/37) 70.3% | (6/37) 16.2% | |||
p-value * | 0.96 | 0.98 | 1 | |||
rs17696736 | AA | (13/83) 15.7% | (57/83) 68.7% | (13/83) 15.7% | 0.99 | |
p-value* | 0.99 | 1 | 1 | |||
AG | (14/89) 15.7% | (61/89) 68.5% | (14/89) 15.7% | |||
p-value * | 0.99 | 0.99 | 1 | |||
GG | (5/38) 13.2% | (27/38) 71.1% | (6/38) 15.8% | |||
p-value * | 0.92 | 0.96 | 1 | |||
rs3184504 | CC | (14/82) 17.1% | (56/82) 68.3% | (12/82) 14.6% | 0.94 | |
p-value * | 0.81 | 0.99 | 0.90 | |||
TC | (12/89) 13.5% | (61/89) 68.5% | (16/89) 18% | |||
p-value * | 0.86 | 1 | 0.81 | |||
TT | (6/41) 14.6% | (29/41) 70.7% | (6/41) 14.6% | |||
p-value * | 1 | 0.96 | 0.97 | |||
MTHFD1L | rs491552 | CC | (6/45) 13.3% | (34/45) 75.6% | (5/45) 11.1% | 0.79 |
p-value * | 0.98 | 0.66 | 0.63 | |||
CG | (13/101) 12.9% | (71/101) 70.3% | (17/101) 16.8% | |||
p-value * | 0.86 | 1 | 0.90 | |||
GG | (10/58) 17.2% | (38/58) 65.5% | (10/58) 17.2% | |||
p-value* | 0.74 | 0.67 | 0.93 | |||
rs6922269 | AA | (2/17) 11.8% | (14/17) 82.4% | (1/17) 5.9% | 0.03 | |
p-value * | 0.92 | 0.46 | 0.49 | |||
AG | (11/80) 13.8% | (48/80) 60% | (21/80) 26.2% | |||
p-value * | 0.91 | 0.09 | 0.01 | |||
GG | (19/115) 16.5% | (84/115) 73% | (12/115) 10.4% | |||
p-value * | 0.82 | 0.36 | 0.05 | |||
rs803422 | AA | (2/24) 8.3% | (8/24) 75% | (4/24) 16.7% | 0.58 | |
p-value * | 0.62 | 0.79 | 1 | |||
GA | (15/75) 20% | (50/75) 66.7% | (10/75) 13.3% | |||
p-value * | 0.34 | 0.88 | 0.73 | |||
GG | (15/113) 13.3% | (78/113) 69% | (20/113) 17.7% | |||
p-value * | 0.73 | 1 | 0.78 | |||
rs803455 | AA | (0/1) 0% | (1/1) 100% | (0/1) 0% | 0.49 | |
p-value * | 0.91 | 0.80 | 0.91 | |||
GA | (7/27) 25.9% | (17/27) 63% | (3/27) 11.1% | |||
p-value * | 0.25 | 0.76 | 0.79 | |||
GG | (25/183) 13.7% | (128/183) 69.9% | (30/183) 16.4% | |||
p-value * | 0.30 | 0.84 | 0.74 |
Gene | SNP ID | Genotype | Sensitive a | Moderate b | Resistance c | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | rs11065987 | AA | (5/52) 9.6% | (36/52) 69.2% | (11/52) 21.2% | 0.41 |
p-value * | 0.46 | 0.38 | 0.86 | |||
GA | (9/63) 14.3% | (37/63) 58.7% | (17/63) 27% | |||
p-value * | 1 | 0.79 | 0.72 | |||
GG | (6/24) 25% | (13/24) 54.2% | (5/24) 20.8% | |||
p-value * | 0.27 | 0.69 | 0.93 | |||
rs17696736 | AA | (4/51) 7.8% | (36/51) 70.6% | (11/51) 21.6% | 0.31 | |
p-value * | 0.23 | 0.23 | 0.87 | |||
AG | (10/61) 16.4% | (35/61) 57.4% | (16/61) 26.2% | |||
p-value * | 0.87 | 0.70 | 0.87 | |||
GG | (6/25) 24% | (13/25) 52% | (6/25) 24% | |||
p-value * | 0.34 | 0.57 | 1 | |||
rs3184504 | CC | (5/51) 9.8% | (36/51) 70.6% | (10/51) 19.6% | 0.35 | |
p-value * | 0.50 | 0.27 | 0.68 | |||
TC | (9/61) 14.8% | (34/61) 55.7% | (18/61) 29.5% | |||
p-value * | 1 | 0.42 | 0.37 | |||
TT | (6/27) 22.2% | (16/27) 59.3% | (5/27) 18.5% | |||
p-value * | 0.30 | 0.95 | 0.78 | |||
MTHFD1L | rs491552 | CC | (2/25) 8% | (15/25) 60% | (8/25) 32% | 0.71 |
p-value * | 0.89 | 0.73 | 0.62 | |||
CG | (10/70) 14.3% | (46/70) 65.7% | (14/70) 20% | |||
p-value * | 0.98 | 0.82 | 0.45 | |||
GG | (5/36) 13.9% | (21/36) 58.3% | (10/36) 27.8% | |||
p-value * | 0.96 | 0.62 | 0.86 | |||
rs6922269 | AA | (2/11) 18.2% | (7/11) 63.6% | (2/11) 18.2% | 0.05 | |
p-value * | 0.93 | 0.99 | 0.90 | |||
AG | (7/57) 12.3% | (29/57) 50.9% | (21/57) 36.8% | |||
p-value * | 0.84 | 0.08 | 0.01 | |||
GG | (11/71) 15.5% | (50/71) 70.4% | (10/71) 14.1% | |||
p-value * | 0.93 | 0.11 | 0.02 | |||
rs803422 | AA | (2/14) 14.3% | (7/14) 50% | (5/14) 35.7% | 0.64 | |
p-value * | 1 | 0.63 | 0.54 | |||
GA | (9/52) 17.3% | (30/52) 57.7% | (13/52) 25% | |||
p-value * | 0.75 | 0.74 | 0.97 | |||
GG | (9/73) 12.3% | (49/73) 67.1% | (15/73) 20.5% | |||
p-value * | 0.77 | 0.41 | 0.65 | |||
rs803455 | GA | (4/20) 20% | (12/20) 60% | (4/20) 20% | 0.74 | |
p-value * | 0.75 | 0.98 | 0.94 | |||
GG | (16/118) 13.6% | (74/118) 62.7% | (28/118) 23.7% | |||
p-value * | 0.75 | 0.98 | 0.94 |
Gene | SNP ID | Genotype | Initiation Dose | Overall p-Value * | Maintenance Dose | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | AA | 35.66 (12.87) | 37.31 (14.39) | |||
rs11065987 | GA | 37.32 (14.74) | 0.1 | 40.00 (19.24) | 0.69 | |
GG | 45.32 (46.11) | 37.48 (21.18) | ||||
AA | 36.03 (12.70) | 37.90 (14.11) | ||||
rs17696736 | AG | 36.74 (14.78) | 0.09 | 38.42 (17.37) | 0.98 | |
GG | 45.36 (45.48) | 38.00 (20.90) | ||||
CC | 35.70 (12.74) | 36.61 (13.60) | ||||
rs3184504 | TC | 37.92 (14.86) | 0.17 | 41.07 (19.83) | 0.35 | |
TT | 43.74 (44.11) | 36.57 (20.12) | ||||
MTHFD1L | CC | 41.17 (40.85) | 39.06 (14.54) | |||
rs491552 | CG | 38.13 (15.48) | 0.62 | 39.76 (19.65) | 0.88 | |
GG | 36.65 (14.47) | 37.84 (17.42) | ||||
AA | 34.64 (09.87) | 35.25 (13.99) | ||||
rs6922269 | AG | 43.91 (33.84) | 0.02 | 44.52 (22.01) | 0.004 | |
GG | 34.49 (11.81) | 34.28 (12.84) | ||||
AA | 38.53 (13.39) | 40.86 (18.38) | ||||
rs803422 | GA | 36.58 (15.18) | 0.79 | 38.63 (19.85) | 0.87 | |
GG | 38.94 (28.49) | 38.07 (16.45) | ||||
AA | 34.80 (……) | |||||
rs803455 | GA | 33.11 (14.99) | 0.49 | 35.22 (15.28) | 0.39 | |
GG | 38.60 (24.01) | 38.85 (18.11) |
Gene | SNP ID | Genotype | Poor a | Good b | Ultra c | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | rs11065987 | AA | (17/84) 20.2% | (62/84) 73.8% | (5/84) 6% | 0.95 |
p-value * | 0.86 | 0.77 | 0.92 | |||
GA | (15/91) 16.5% | (72/91) 79.1% | (4/91) 4.4% | |||
p-value * | 0.82 | 0.72 | 0.90 | |||
GG | (7/37) 18.9% | (28/37) 75.7% | (2/37) 5.4% | |||
p-value * | 1 | 1 | 1 | |||
rs17696736 | AA | (17/83) 20.5% | (62/83) 74.7% | (4/83) 4.8% | 0.98 | |
p-value * | 0.85 | 0.92 | 0.98 | |||
AG | (15/89) 16.9% | (69/89) 77.5% | (5/89) 5.6% | |||
p-value * | 0.85 | 0.93 | 0.98 | |||
GG | (7/38) 18.4% | (29/38) 76.3% | (2/38) 5.3% | |||
p-value * | 1 | 1 | 1 | |||
rs3184504 | CC | (17/82) 20.7% | (60/82) 73.2% | (5/82) 6.1% | 0.89 | |
p -value * | 0.78 | 0.69 | 0.98 | |||
TC | (14/89) 15.7% | (71/89) 79.8% | (4/89) 4.5% | |||
p-value * | 0.68 | 0.62 | 0.99 | |||
TT | (8/41) 19.5% | (31/41) 75.6% | (2/41) 4.9% | |||
p-value * | 0.90 | 0.93 | 1 | |||
MTHFD1L | rs491552 | CC | (11/45) 24.4% | (34/45) 75.6% | (0/45) 0% | 0.07 |
p-value * | 0.59 | 1 | 0.19 | |||
CG | (18/101) 17.8% | (79/101) 78.2% | (4/101) 4% | |||
p-value * | 0.90 | 0.67 | 0.67 | |||
GG | (10/58) 17.2% | (41/58) 70.7% | (7/58) 12.1% | |||
p-value * | 0.91 | 0.6 | 0.03 | |||
rs6922269 | AA | (4/17) 23.5% | (11/17) 64.7% | (2/17) 11.8% | 0.56 | |
p-value * | 0.85 | 0.49 | 0.44 | |||
AG | (15/80) 18.8% | (60/80) 75% | (5/80) 6.3% | |||
p-value * | 1 | 0.93 | 0.87 | |||
GG | (20/115) 17.4% | (91/115) 79.1% | (4/115) 3.5% | |||
p-value * | 0.92 | 0.6 | 0.47 | |||
rs803422 | AA | (4/24) 16.7% | (20/24) 83.3% | (0/24) 0% | 0.55 | |
p-value * | 0.98 | 0.70 | 0.48 | |||
GA | (11/75) 14.7% | (60/75) 80% | (4/75) 5.3% | |||
p-value * | 0.58 | 0.66 | 1 | |||
GG | (24/113) 21.2% | (82/113) 72.6% | (7/113) 6.2% | |||
p-value * | 0.73 | 1 | 0.78 | |||
rs803455 | AA | (0/1) 0% | (1/1) 100% | (0/1) 0% | 0.64 | |
p-value * | 0.89 | 0.86 | 0.97 | |||
GA | (4/27) 14.8% | (23/27) 85.2% | (0/27) 0% | |||
p-value * | 0.87 | 0.51 | 0.43 | |||
GG | (35/183) 19.1% | (137/183) 74.9% | (11/183) 6% | |||
p-value * | 0.83 | 0.45 | 0.41 |
Gene | SNP ID | Genotype | Poor a | Good b | Ultra c | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | rs11065987 | AA | (4/52) 7.7% | (44/52) 84.6% | (4/52) 7.7% | 0.56 |
p-value * | 0.90 | 0.40 | 0.32 | |||
GA | (4/63) 6.3% | (58/63) 92.1% | (1/63) 1.6% | |||
p-value * | 1 | 0.61 | 0.35 | |||
GG | (1/24) 4.2% | (22/24) 91.7% | (1/24) 4.2% | |||
p-value ** | 0.88 | 0.91 | 1 | |||
rs17696736 | AA | (4/51) 7.8% | (44/51) 86.3% | (3/51) 5.9% | 0.93 | |
p-value * | 0.90 | 0.73 | 0.80 | |||
AG | (4/61) 6.6% | (55/61) 90.2% | (2/61) 3.3% | |||
p-value * | 1 | 0.93 | 0.85 | |||
GG | (1/25) 4% | (23/25) 92% | (1/25) 4% | |||
p-value * | 0.85 | 0.87 | 1 | |||
rs3184504 | CC | (4/51) 7.8% | (43/51) 84.3% | (4/51) 7.8% | 0.53 | |
p-value * | 0.88 | 0.37 | 0.30 | |||
TC | (4/61) 6.6% | (56/61) 91.8% | (1/61) 1.6% | |||
p-value * | 1 | 0.68 | 0.39 | |||
TT | (1/27) 3.7% | (25/27) 92.6% | (1/27) 3.7% | |||
p-value * | 0.81 | 0.82 | 0.99 | |||
MTHFD1L | rs491552 | CC | (2/25) 8% | (23/25) 92% | (0/25) 0% | 0.26 |
p-value * | 0.97 | 0.84 | 0.48 | |||
CG | (5/70) 7.1% | (63/70) 90% | (2/70) 2.9% | |||
p-value * | 0.99 | 0.86 | 0.60 | |||
GG | (2/36) 5.6% | (30/36) 83.3% | (4/36) 11.1% | |||
p-value * | 0.94 | 0.51 | 0.09 | |||
rs6922269 | AA | (3/11) 27.3% | (6/11) 54.5% | (2/11) 18.2% | 0.30 | |
p-value * | 0.01 | <0.0001 | 0.06 | |||
AG | (4/57) 7% | (51/57) 89.5% | (2/57) 3.5% | |||
p-value * | 0.98 | 1 | 0.93 | |||
GG | (2/71) 2.8% | (67/71) 94.4% | (2/71) 2.8% | |||
p-value * | 0.2 | 0.13 | 0.67 | |||
rs803422 | AA | (0/14) 0% | (14/14) 100% | (0/14) 0% | 0.18 | |
p-value * | 0.58 | 0.39 | 0.70 | |||
GA | (1/52) 1.9% | (49/52) 94.2% | (2/52) 3.8% | |||
p-value * | 0.24 | 0.34 | 0.98 | |||
GG | (8/73) 11% | (61/73) 83.6% | (4/73) 5.4% | |||
p-value * | 0.08 | 0.08 | 0.78 | |||
rs803455 | GA | (0/20) 0% | (20/20) 100% | (0/20) 0% | 0.24 | |
p-value * | 0.44 | 0.24 | 0.59 | |||
GG | (9/118) 7.6% | (103/118) 87.3% | (6/118) 5.1% | |||
P-value* | 0.44 | 0.24 | 0.59 |
Gene | SNP ID | Genotype | Initiation INR | Overall p-Value * | Maintenance INR | Overall p-Value * |
---|---|---|---|---|---|---|
SH2B3 | AA | 2.41 (0.75) | 2.68 (0.43) | |||
rs11065987 | GA | 2.51 (0.79) | 0.70 | 2.68 (0.37) | 0.80 | |
GG | 2.45 (0.79) | 2.74 (0.35) | ||||
AA | 2.39 (0.75) | 2.69 (0.42) | ||||
rs17696736 | AG | 2.53 (0.80) | 0.53 | 2.68 (0.38) | 0.86 | |
GG | 2.44 (0.78) | 2.73 (0.34) | ||||
CC | 2.41 (0.76) | 2.68 (0.43) | ||||
rs3184504 | TC | 2.50 (0.77) | 0.72 | 2.68 (0.38) | 0.75 | |
TT | 2.46 (0.81) | 2.74 (0.33) | ||||
MTHFD1L | CC | 2.33 (0.75) | 2.67 (0.39) | |||
rs491552 | CG | 2.40 (0.69) | 0.15 | 2.61 (0.37) | 0.02 | |
GG | 2.61 (0.93) | 2.83 (0.40) | ||||
AA | 2.30 (0.67) | 2.66 (0.49) | ||||
rs6922269 | AG | 2.55 (0.82) | 0.73 | 2.66 (0.42) | 0.65 | |
GG | 2.42 (0.76) | 2.72 (0.35) | ||||
AA | 2.46 (0.97) | 2.64 (0.37) | ||||
rs803422 | GA | 2.47 (0.50) | 0.62 | 2.73 (0.41) | 0.68 | |
GG | 1.70 (……) | 2.68 (0.38) | ||||
AA | 1.90 (……) | |||||
rs803455 | GA | 2.48 (0.66) | 0.76 | 2.85 (0.31) | 0.05 | |
GG | 2.46 (0.79) | 2.67 (0.40) |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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AL-Eitan, L.N.; Almasri, A.Y.; Khasawneh, R.H.; Alghamdi, M.A. Influence of SH2B3, MTHFD1L, GGCX, and ITGB3 Gene Polymorphisms on theVariability on Warfarin Dosage Requirements and Susceptibility to CVD in the Jordanian Population. J. Pers. Med. 2020, 10, 117. https://doi.org/10.3390/jpm10030117
AL-Eitan LN, Almasri AY, Khasawneh RH, Alghamdi MA. Influence of SH2B3, MTHFD1L, GGCX, and ITGB3 Gene Polymorphisms on theVariability on Warfarin Dosage Requirements and Susceptibility to CVD in the Jordanian Population. Journal of Personalized Medicine. 2020; 10(3):117. https://doi.org/10.3390/jpm10030117
Chicago/Turabian StyleAL-Eitan, Laith N., Ayah Y. Almasri, Rame H. Khasawneh, and Mansour A. Alghamdi. 2020. "Influence of SH2B3, MTHFD1L, GGCX, and ITGB3 Gene Polymorphisms on theVariability on Warfarin Dosage Requirements and Susceptibility to CVD in the Jordanian Population" Journal of Personalized Medicine 10, no. 3: 117. https://doi.org/10.3390/jpm10030117
APA StyleAL-Eitan, L. N., Almasri, A. Y., Khasawneh, R. H., & Alghamdi, M. A. (2020). Influence of SH2B3, MTHFD1L, GGCX, and ITGB3 Gene Polymorphisms on theVariability on Warfarin Dosage Requirements and Susceptibility to CVD in the Jordanian Population. Journal of Personalized Medicine, 10(3), 117. https://doi.org/10.3390/jpm10030117