Pharmacogenomics of glibenclamide in patients with type 2 diabetes mellitus: A systematic review

authors:

avatar Shahrzad Mohseni , avatar Ozra Tabatabaei_Malazy , * , avatar Fatemeh Bandarian , avatar Bagher Larijani ORCID

Koomesh: Vol.24, issue 2; 183-190
published online: July 07, 2022
article type: Review Article
received: April 02, 2021
accepted: July 07, 2021

how to cite: Mohseni S, Tabatabaei_Malazy O, Bandarian F, Larijani B. Pharmacogenomics of glibenclamide in patients with type 2 diabetes mellitus: A systematic review. koomesh. 2022;24(2):e152659. 

Abstract

Introduction: One of the most widely used anti-diabetic drugs is sulfonylureas, which is often used as one of the first-line drugs in the treatment of type 2 diabetes. Due to the effect of the patient;#39s genetic structure on the drug response (personalized medicine), the identification of genetic variations not only reduces the rate of adverse drug reactions but can also predict the effectiveness of drugs. This study aimed to systematically review the pharmacogenomics of glibenclamide in type 2 diabetes. Materials and Methods: This systematic review was performed based on PRISMA flowchart. Using the search terms including "variant", “sulfonylurea”, "glibenclamide", "diabetes mellitus", "SNP" or their equivalents, a comprehensive search of the PubMed, Scopus and Web of Science databases was conducted until January 1, 2021. An initial search yielded 125 articles. Results: Finally, in nine articles included in this systematic review, glibenclamide monotherapy was performed in 3032 patients. Most studies were conducted in China and the most common methods of genotyping were RFLP-PCR and direct sequencing. The most common genes studied were CYP2C9, KCNJ11 and TCF7L2. The results of studies showed a significant effect of CYP2C9 polymorphism on appropriate therapeutic response and KCNJ11 gene polymorphism on failure of glibenclamide treatment. Conclusion: Among all genetic factors and specific genotypes of proteins involved in the metabolism of glibenclamide, CYP2C9 gene polymorphism has a role in proper response to treatment and KCNJ11 gene polymorphism has a role in treatment failure and hypoglycemic effects of glibenclamide.

References

  • 1.

    International Diabetes Federation. IDF Diabetes Atlas. Brussels, Belgium: International Diabetes Federation: 2019.

  • 2.

    Khodaeian M, Enayati S, Tabatabaei-Malazy O, Amoli MM. Association between genetic variants and diabetes mellitus in Iranian populations: a systematic review of observational studies. J Diabetes Res 2015; 2015: 585917.

  • 3.

    Sarbakhsh P, Namdari M, Mehrabi Y, Zayeri F, Daneshpour M. Association of polymorphisms and other risk factors with cholesterol level over time using logic random effect model: Tehran Lipid and Glucose Study. Koomesh 2015; 16: 193-201. (Persian).

  • 4.

    Campos C. Chronic hyperglycemia and glucose toxicity: pathology and clinical sequelae. Postgrad Med 2012; 124: 90-97.

  • 5.

    Tabatabaei-Malazy O, Nikfar S, Larijani B, Abdollahi M. Drugs for the treatment of pediatric type 2 diabetes mellitus and related co-morbidities. Exp Opin Pharmacother 2016; 17: 2449-2460.

  • 6.

    Hirst JA, Farmer AJ, Dyar A, Lung TW, Stevens RJ. Estimating the effect of sulfonylurea on HbA1c in diabetes: a systematic review and meta-analysis. Diabetologia 2013; 56: 973-984.

  • 7.

    Hamming KS, Soliman D, Matemisz LC, Niazi O, Lang Y, Gloyn AL, et al. Coexpression of the type 2 diabetes susceptibility gene variants KCNJ11 E23K and ABCC8 S1369A alter the ATP and sulfonylurea sensitivities of the ATP-sensitive K(+) channel. Diabetes Care 2009; 58: 2419-2424.

  • 8.

    Sokolova EA, Bondar IA, Shabelnikova OY, Pyankova OV, Filipenko ML. Replication of KCNJ11 (p.E23K) and ABCC8 (p.S1369A) association in Russian diabetes mellitus 2 type cohort and meta-analysis. PLoS One 2015; 10: e0124662.

  • 9.

    Castelan-Martinez OD, Hoyo-Vadillo C, Bazan-Soto TB, Cruz M, Tesoro-Cruz E, Valladares-Salgado A. CYP2C9*3 gene variant contributes independently to glycaemic control in patients with type 2 diabetes treated with glibenclamide. J Clin Pharm Ther 2018; 43: 768-774.

  • 10.

    American Diabetes Association. Approaches to glycemic treatment. Diabetes Care 2016; 39: S52-S59.

  • 11.

    Mohan V, Khunti K, Chan SP, Filho FF, Tran NQ, Ramaiya K, et al. Management of type 2 diabetes in developing countries: balancing optimal glycaemic control and outcomes with affordability and accessibility to treatment. Diabetes Ther 2020; 11: 15-35.

  • 12.

    Groop LC. Sulfonylureas in NIDDM. Diabetes Care 1992; 15: 737-754.

  • 13.

    Wright AD, Cull CA, Macleod KM, Holman RR. Hypoglycemia in type 2 diabetic patients randomized to and maintained on monotherapy with diet, sulfonylurea, metformin, or insulin for 6 years from diagnosis: UKPDS73. J Diabetes Complications 2006; 20: 395-401.

  • 14.

    Rogowski W, Payne K, Schnell-Inderst P, Manca A, Rochau U, Jahn B, et al. Concepts of 'Personalization' in personalized medicine: implications for economic evaluation. Pharmaco Economics 2014; 33: 49-59.

  • 15.

    Holstein A, Beil W, Kovacs P. CYP2C metabolism of oral antidiabetic drugs-impact on pharmacokinetics, drug interactions and pharmacogenetic aspects. Exp Opin Drug Metab Toxicol 2012; 8: 1549-1563.

  • 16.

    Klen J, Dolzan V, Janez A. CYP2C9, KCNJ11 and ABCC8 polymorphisms and the response to sulphonylurea treatment in type 2 diabetes patients. Eur J Clin Pharmacol 2014; 70: 421-428.

  • 17.

    Nikolac N, Simundic AM, Katalinic D, Topic E, Cipak A, Zjacic RV. Metabolic control in type 2 diabetes is associated with sulfonylurea receptor-1 (SUR-1) but not with KCNJ11 polymorphisms. Arch Med Res 2009; 40: 387-392.

  • 18.

    Pearson ER, Donnelly LA, Kimber C, Whitley A, Doney A, McCarthy MI, et al. Variation in TCF7L2 influences therapeutic response to sulfonylureas: a GoDARTs study. Diabetes 2007; 56: 2178-2182.

  • 19.

    Ren Q, Han X, Ren J, Liu X, Ji L. Influence of the SLCO1B3 gene on sulfonylurea failure in patients with type 2 diabetes in China. Exp Clin Endocrinol Diabetes 2017; 125: 449-453.

  • 20.

    Ren Q, Xiao D, Han XY, Edwards SL, Wang HQ, Tang Y, et al. Genetic and clinical predictive factors of sulfonylurea failure in patients with type 2 diabetes. Diabetes Technol Ther 2016; 18: 586-593.

  • 21.

    Ren Q, Han X, Zhang S, Cai X, Ji L. Combined influence of genetic variants and gene-gene interaction on sulfonylurea efficacy in type 2 diabetic patients. Exp Clin Endocrinol Diabetes 2016; 124: 157-162.

  • 22.

    Ren Q, Han X, Tang Y, Zhang X, Zou X, Cai X, et al. Search for genetic determinants of sulfonylurea efficacy in type 2 diabetic patients from China. Diabetologia 2014; 57: 746-753.

  • 23.

    Salam RFA, Zeyada R, Osman NA. Effect of CYP2C9 gene polymorphisms on response to treatment with sulfonylureas in a cohort of Egyptian type 2 diabetes mellitus patients. Comp Clin Pathol 2014; 23: 341-346.

  • 24.

    Surendiran A, Pradhan SC, Agrawal A, Subrahmanyam DK, Rajan S, Anichavezhi D, et al. Influence of CYP2C9 gene polymorphisms on response to glibenclamide in type 2 diabetes mellitus patients. Eur J Clin Pharmacol 2011; 67: 797-801.

  • 25.

    Sesti G, Laratta E, Cardellini M, Andreozzi F, Del Guerra S, Irace C, et al. The E23K variant of KCNJ11 encoding the pancreatic beta-cell adenosine 5'-triphosphate-sensitive potassium channel subunit Kir6.2 is associated with an increased risk of secondary failure to sulfonylurea in patients with type 2 diabetes. J Clin Endocrinol Metab 2006; 91: 2334-2339.

  • 26.

    Sesti G, Marini MA, Cardellini M, Sciacqua A, Frontoni S, Andreozzi F, et al. The Arg972 variant in insulin receptor substrate-1 is associated with an increased risk of secondary failure to sulfonylurea in patients with type 2 diabetes. Diabetes Care 2004; 27: 1394-1398.##.

  • 27.

    Lang VY, Fatehi M, Light PE. Pharmacogenomic analysis of ATP-sensitive potassium channels coexpressing the common type 2 diabetes risk variants E23K and S1369A. Pharmacogenet Genom 2012; 22: 206-214.