Gene Polymorphisms of the Renin-Angiotensin System and Bleeding Complications of Warfarin: Genetic-Based Machine Learning Models

Overview

Journal Pharmaceuticals (Basel)

Publisher MDPI

Specialty Chemistry

Date 2021 Aug 28

PMID 34451921

Citations 1

Authors

Joo-Hee Kim

Jeong Yee

Byung-Chul Chang

Hye-Sun Gwak

Affiliations

Soon will be listed here.

Abstract

Background: This study aimed to investigate the effects of genetic variants and haplotypes in the renin-angiotensin system (RAS) on the risk of warfarin-induced bleeding complications at therapeutic international normalized ratios (INRs).

Methods: Four single nucleotide polymorphisms (SNPs) of , two SNPs of , three SNPs of , four SNPs of , and one SNP of , in addition to and variants, were investigated. We utilized logistic regression and several machine learning methods for bleeding prediction.

Results: The study included 142 patients, among whom 21 experienced bleeding complications. We identified a haplotype, H2 (TCG), carrying three SNPs of (rs1800764, rs4341, and rs4353), which showed a significant relation with bleeding complications. After adjusting covariates, patients with H2/H2 experienced a 0.12-fold (95% CI 0.02-0.99) higher risk of bleeding complications than the others. In addition, G allele carriers of rs5050 and A allele carriers of rs2640543 had 5.0- (95% CI 1.8-14.1) and 3.2-fold (95% CI 1.1-8.9) increased risk of bleeding complications compared with the TT genotype and GG genotype carriers, respectively. The AUROC values (mean, 95% CI) across 10 random iterations using five-fold cross-validated multivariate logistic regression, elastic net, random forest, support vector machine (SVM)-linear kernel, and SVM-radial kernel models were 0.732 (0.694-0.771), 0.741 (0.612-0.870), 0.723 (0.589-0.857), 0.673 (0.517-0.828), and 0.680 (0.528-0.832), respectively. The highest quartile group (≥75th percentile) of weighted risk score had approximately 12.0 times (95% CI 3.1-46.7) increased risk of bleeding, compared to the 25-75th percentile group, respectively.

Conclusion: This study demonstrated that RAS-related polymorphisms, including the H2 haplotype of the gene, could affect bleeding complications during warfarin treatment for patients with mechanical heart valves. Our results could be used to develop individually tailored intervention strategies to prevent warfarin-induced bleeding.

Citing Articles

Genetic Factors of Renin-Angiotensin System Associated with Major Bleeding for Patients Treated with Direct Oral Anticoagulants.

Yee J, Song T, Yoon H, Park J, Gwak H Pharmaceutics. 2022; 14(2).

PMID: 35213964 PMC: 8877686. DOI: 10.3390/pharmaceutics14020231.

References

Hubert C, Houot A, Corvol P, Soubrier F . Structure of the angiotensin I-converting enzyme gene. Two alternate promoters correspond to evolutionary steps of a duplicated gene. J Biol Chem. 1991; 266(23):15377-83. View

Pourgholi L, Goodarzynejad H, Mandegary A, Ziaee S, Hajhosseini Talasaz A, Jalali A . Gene polymorphisms and the risk of warfarin-induced bleeding complications at therapeutic international normalized ratio (INR). Toxicol Appl Pharmacol. 2016; 309:37-43. DOI: 10.1016/j.taap.2016.08.026. View

Zhao Y, Zhou J, Narayanan C, Cui Y, Kumar A . Role of C/A polymorphism at -20 on the expression of human angiotensinogen gene. Hypertension. 1999; 33(1):108-15. DOI: 10.1161/01.hyp.33.1.108. View

Pola E, Gaetani E, Pola R, Papaleo P, Flex A, Aloi F . Angiotensin-converting enzyme gene polymorphism may influence blood loss in a geriatric population undergoing total hip arthroplasty. J Am Geriatr Soc. 2002; 50(12):2025-8. DOI: 10.1046/j.1532-5415.2002.50616.x. View

Das S, Roy S, Sharma V, Kaul S, Jyothy A, Munshi A . Association of ACE gene I/D polymorphism and ACE levels with hemorrhagic stroke: comparison with ischemic stroke. Neurol Sci. 2014; 36(1):137-42. DOI: 10.1007/s10072-014-1880-8. View

Nishimura R, Otto C, Bonow R, Carabello B, Erwin 3rd J, Guyton R . 2014 AHA/ACC Guideline for the Management of Patients With Valvular Heart Disease: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014; 129(23):2440-92. DOI: 10.1161/CIR.0000000000000029. View

Cosgun E, Limdi N, Duarte C . High-dimensional pharmacogenetic prediction of a continuous trait using machine learning techniques with application to warfarin dose prediction in African Americans. Bioinformatics. 2011; 27(10):1384-9. PMC: 3087957. DOI: 10.1093/bioinformatics/btr159. View

Whirl-Carrillo M, McDonagh E, Hebert J, Gong L, Sangkuhl K, Thorn C . Pharmacogenomics knowledge for personalized medicine. Clin Pharmacol Ther. 2012; 92(4):414-7. PMC: 3660037. DOI: 10.1038/clpt.2012.96. View

Rigat B, Hubert C, Corvol P, Soubrier F . PCR detection of the insertion/deletion polymorphism of the human angiotensin converting enzyme gene (DCP1) (dipeptidyl carboxypeptidase 1). Nucleic Acids Res. 1992; 20(6):1433. PMC: 312213. DOI: 10.1093/nar/20.6.1433-a. View

10.

Philipp C, Dilley A, Saidi P, Evatt B, Austin H, Zawadsky J . Deletion polymorphism in the angiotensin-converting enzyme gene as a thrombophilic risk factor after hip arthroplasty. Thromb Haemost. 1998; 80(6):869-73. View

11.

Ma Z, Wang P, Gao Z, Wang R, Khalighi K . Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose. PLoS One. 2018; 13(10):e0205872. PMC: 6195267. DOI: 10.1371/journal.pone.0205872. View

12.

Marie I, Leprince P, Menard J, Tharasse C, Levesque H . Risk factors of vitamin K antagonist overcoagulation. QJM. 2011; 105(1):53-62. DOI: 10.1093/qjmed/hcr136. View

13.

Su X, Lee L, Li X, Lv J, Hu Y, Zhan S . Association between angiotensinogen, angiotensin II receptor genes, and blood pressure response to an angiotensin-converting enzyme inhibitor. Circulation. 2007; 115(6):725-32. DOI: 10.1161/CIRCULATIONAHA.106.642058. View

14.

Fuchs S, Philippe J, Germain S, Mathieu F, Jeunemaitre X, Corvol P . Functionality of two new polymorphisms in the human renin gene enhancer region. J Hypertens. 2002; 20(12):2391-8. DOI: 10.1097/00004872-200212000-00018. View

15.

Mathur P, Srivastava S, Xu X, Mehta J . Artificial Intelligence, Machine Learning, and Cardiovascular Disease. Clin Med Insights Cardiol. 2020; 14:1179546820927404. PMC: 7485162. DOI: 10.1177/1179546820927404. View

16.

Cuocolo R, Perillo T, De Rosa E, Ugga L, Petretta M . Current applications of big data and machine learning in cardiology. J Geriatr Cardiol. 2019; 16(8):601-607. PMC: 6748901. DOI: 10.11909/j.issn.1671-5411.2019.08.002. View

17.

Rigat B, Hubert C, Alhenc-Gelas F, Cambien F, Corvol P, Soubrier F . An insertion/deletion polymorphism in the angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J Clin Invest. 1990; 86(4):1343-6. PMC: 296868. DOI: 10.1172/JCI114844. View

18.

Ward L, Kellis M . HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res. 2015; 44(D1):D877-81. PMC: 4702929. DOI: 10.1093/nar/gkv1340. View

19.

Yee J, Kim W, Chang B, Chung J, Lee K, Gwak H . APOB gene polymorphisms may affect the risk of minor or minimal bleeding complications in patients on warfarin maintaining therapeutic INR. Eur J Hum Genet. 2019; 27(10):1542-1549. PMC: 6777606. DOI: 10.1038/s41431-019-0450-1. View

20.

Ruiz-Ortega M, Lorenzo O, Ruperez M, Esteban V, Suzuki Y, Mezzano S . Role of the renin-angiotensin system in vascular diseases: expanding the field. Hypertension. 2001; 38(6):1382-7. DOI: 10.1161/hy1201.100589. View