Skip to main content

Advertisement

Log in

Pharmacogenetics and personalized treatment of type 2 diabetes mellitus

  • Review Article
  • Published:
International Journal of Diabetes in Developing Countries Aims and scope Submit manuscript

Abstract

Type 2 diabetes mellitus (T2DM) is one of the most prevalent diseases in the world. An important difference in effectiveness and toxicity of hypoglycemic agents has been associated with the presence of genetic variants in people with T2DM. We conducted a literature review up November 2015 by combining keywords type 2 diabetes mellitus, hypoglycemic agents and pharmacogenetics (PKG). Metformin, sulfonylureas, and meglitinide drugs are widely used for the T2DM treatment, although new drugs in combination with metformin are administered. Genetic variants in proteins that function as carriers, channels, or metabolizing enzymes affect both the pharmacokinetics and pharmacodynamics of these agents. Significant progress in T2DM’s pharmacogenetics has been made; however, more studies involving a larger number of patients from different ethnic groups must be done. Furthermore, patients with T2DM generally are complex patients receiving hypolipidemic and hypotensive medications. Drug-drug interaction studies between these drugs must be done to really know the contribution of each polymorphism in drug effectiveness and/or toxicity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Panten U, Schwanstecher M, Schwanstecher C. Sulfonylurea receptors and mechanism of sulfonylurea action. Exp Clin Endocrinol Diabetes. 1996;104:1–9. doi:10.1055/s-0029-1211414.

    Article  CAS  PubMed  Google Scholar 

  2. 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;91:2334–9. doi:10.1210/jc.2005-2323.

    Article  CAS  PubMed  Google Scholar 

  3. Javorsky M, Klimcakova L, Schroner Z, Zidzik J, Babjakova E, Fabianova M, et al. KCNJ11 gene E23K variant and therapeutic response to sulfonylureas. Eur J Intern Med. 2012;23:245–9. doi:10.1016/j.ejim.2011.10.018.

    Article  CAS  PubMed  Google Scholar 

  4. Holstein A, Hahn M, Stumvoll M, Kovacs P. The E23K variant of KCNJ11 and the risk for severe sulfonylurea-induced hypoglycemia in patients with type 2 diabetes. Horm Metab Res. 2009;41:387–90. doi:10.1055/s-0029-1192019.

    Article  CAS  PubMed  Google Scholar 

  5. Zhang H, Liu X, Kuang H, Yi R, Xing H. Association of sulfonylurea receptor 1 genotype with therapeutic response to gliclazide in type 2 diabetes. Diabetes Res Clin Pract. 2007;77:58–61. doi:10.1016/j.diabres.2006.10.021.

    Article  CAS  PubMed  Google Scholar 

  6. Xu H, Murray M, McLachlan AJ. Influence of genetic polymorphisms on the pharmacokinetics and pharmaco-dynamics of sulfonylurea drugs. Curr Drug Metab. 2009;10:643–58.

    Article  CAS  PubMed  Google Scholar 

  7. Wang J, Hu F, Feng T, Zhao J, Yin L, Li L, et al. Meta-analysis of associations between TCF7L2 polymorphisms and risk of type 2 diabetes mellitus in the Chinese population. BMC Med Genet. 2013;14:8. doi:10.1186/1471-2350-14-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Javorský M, Schroner Z. Association between TCF7L2 genotype and glycemic control in diabetic patients treated with gliclazide. Int J Endocrinol. 2013;2013:1–5. doi:10.1155/2013/374858.

    Article  Google Scholar 

  9. Schroner Z, Dobrikova M, Klimcakova L, Javorsky M, Zidzik J, Kozarova M, et al. Variation in KCNQ1 is associated with therapeutic response to sulphonylureas. Med Sci Monit. 2011;17:CR392–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. 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;27:1394–8.

    Article  CAS  PubMed  Google Scholar 

  11. Kirchheiner J, Brockmöller J, Meineke I, Bauer S, Rohde W, Meisel C, et al. Impact of CYP2C9 amino acid polymorphisms on glyburide kinetics and on the insulin and glucose response in healthy volunteers. Clin Pharmacol Ther. 2002;71:286–96. doi:10.1067/mcp.2002.122476.

    Article  CAS  PubMed  Google Scholar 

  12. Becker M, Visser L, Trienekens P, Hofman A, van Schaik R, Bhc S. Cytochrome P450 2C9 *2 and *3 polymorphisms and the dose and effect of sulfonylurea in type II diabetes mellitus. Clin Pharmacol Ther. 2008;83:288–92. doi:10.1038/sj.clpt.6100273.

    Article  CAS  PubMed  Google Scholar 

  13. Shon J, Yoon Y, Kim M-J, Kim K, Lim Y, Liu K, et al. Chlorpropamide 2-hydroxylation is catalysed by CYP2C9 and CYP2C19 in vitro: chlorpropamide disposition is influenced by CYP2C9, but not by CYP2C19 genetic polymorphism. Br J Clin Pharmacol. 2005;59:552–63. doi:10.1111/j.1365-2125.2005.02364.x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Niemi M, Cascorbi I, Timm R, Kroemer HK, Neuvonen PJ, Kivistö KT. Glyburide and glimepiride pharmacokinetics in subjects with different CYP2C9 genotypes. Clin Pharmacol Ther. 2002;72:326–32. doi:10.1067/mcp.2002.127495.

    Article  CAS  PubMed  Google Scholar 

  15. Suzuki K, Yanagawa T, Shibasaki T, Kaniwa N, Hasegawa R, Tohkin M. Effect of CYP2C9 genetic polymorphisms on the efficacy and pharmacokinetics of glimepiride in subjects with type 2 diabetes. Diabetes Res Clin Pract. 2006;72:148–54. doi:10.1016/j.diabres.2005.09.019.

    Article  CAS  PubMed  Google Scholar 

  16. Tan B, Zhang Y, Chen X, Zhao X-H, Li G-X, Zhong D-F. The effects of CYP2C9 and CYP2C19 genetic polymorphisms on the pharmacokinetics and pharmacodynamics of glipizide in Chinese subjects. Eur J Clin Pharmacol. 2010;66:145–51. doi:10.1007/s00228-009-0736-2.

    Article  CAS  PubMed  Google Scholar 

  17. Lee CR, Pieper JA, Hinderliter AL, Blaisdell JA, Goldstein JA. Evaluation of cytochrome P4502C9 metabolic activity with tolbutamide in CYP2C91 heterozygotes. Clin Pharmacol Ther. 2002;72:562–71. doi:10.1067/mcp.2002.127913.

    Article  CAS  PubMed  Google Scholar 

  18. Malaisse WJ. Mechanism of action of a new class of insulin secretagogues. Exp Clin Endocrinol Diabetes. 1999;107(Suppl :S140–3). doi:10.1055/s-0029-1212170.

  19. Dornhorst A. Insulinotropic meglitinide analogues. Lancet. 2001;358:1709–16. doi:10.1016/S0140-6736(01)06715-0.

    Article  CAS  PubMed  Google Scholar 

  20. Kirchheiner J, Meineke I, Müller G, Bauer S, Rohde W, Meisel C, et al. Influence of CYP2C9 and CYP2D6 polymorphisms on the pharmacokinetics of nateglinide in genotyped healthy volunteers. Clin Pharmacokinet. 2004;43:267–78. doi:10.2165/00003088-200443040-00005.

    Article  CAS  PubMed  Google Scholar 

  21. Cheng Y, Wang G, Zhang W, Fan L, Chen Y, Zhou H-H. Effect of CYP2C9 and SLCO1B1 polymorphisms on the pharmacokinetics and pharmacodynamics of nateglinide in healthy Chinese male volunteers. Eur J Clin Pharmacol. 2013;69:407–13. doi:10.1007/s00228-012-1364-9.

    Article  CAS  PubMed  Google Scholar 

  22. Niemi M, Backman JT, Kajosaari LI, Leathart JB, Neuvonen M, Daly AK, et al. Polymorphic organic anion transporting polypeptide 1B1 is a major determinant of repaglinide pharmacokinetics. Clin Pharmacol Ther. 2005;77:468–78. doi:10.1016/j.clpt.2005.01.018.

    Article  CAS  PubMed  Google Scholar 

  23. Kalliokoski A, Neuvonen M, Neuvonen PJ, Niemi M. Different effects of SLCO1B1 polymorphism on the pharmacokinetics and pharmacodynamics of repaglinide and nateglinide. J Clin Pharmacol. 2008;48:311–21. doi:10.1177/0091270007311569.

    Article  CAS  PubMed  Google Scholar 

  24. Ruzilawati AB, Gan SH. CYP3A4 genetic polymorphism influences repaglinide’s pharmacokinetics. Pharmacology. 2010;85:357–64. doi:10.1159/000302731.

    Article  CAS  PubMed  Google Scholar 

  25. Huang Q, Yin J-Y, Dai X-P, Wu J, Chen X, Deng C-S, et al. Association analysis of SLC30A8 rs13266634 and rs16889462 polymorphisms with type 2 diabetes mellitus and repaglinide response in Chinese patients. Eur J Clin Pharmacol. 2010;66:1207–15. doi:10.1007/s00228-010-0882-6.

    Article  CAS  PubMed  Google Scholar 

  26. Xiang Q, Cui YM, Zhao X, Yan L, Zhou Y. The influence of MDR1 G2677T/a genetic polymorphisms on the pharmacokinetics of repaglinide in healthy Chinese volunteers. Pharmacology. 2012;89:105–10. doi:10.1159/000336345.

    Article  CAS  PubMed  Google Scholar 

  27. Yu M, Xu X-J, Yin J-Y, Wu J, Chen X, Gong Z-C, et al. KCNJ11 Lys23Glu and TCF7L2 rs290487(C/T) polymorphisms affect therapeutic efficacy of repaglinide in Chinese patients with type 2 diabetes. Clin Pharmacol Ther. 2010;87:330–5. doi:10.1038/clpt.2009.242.

    Article  CAS  PubMed  Google Scholar 

  28. Yu W, Hu C, Zhang R, Wang C, Qin W, Lu J, et al. Effects of KCNQ1 polymorphisms on the therapeutic efficacy of oral antidiabetic drugs in Chinese patients with type 2 diabetes. Clin Pharmacol Ther. 2011;89:437–42. doi:10.1038/clpt.2010.351.

    Article  CAS  PubMed  Google Scholar 

  29. Huang Q, Yin J, Dai X, Pei Q, Dong M, Zhou Z, et al. IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes in Chinese population. Acta Pharmacol Sin. 2010;31:709–17. doi:10.1038/aps.2010.47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kirpichnikov D, McFarlane SI, Sowers JR. Metformin: an update. Ann Intern Med. 2002;137:25–33.

    Article  CAS  PubMed  Google Scholar 

  31. Strack T. Metformin: a review. Drugs Today (Barc). 2008;44:303–14.

    Article  CAS  Google Scholar 

  32. Lipska KJ, Bailey CJ, Inzucchi SE. Use of metformin in the setting of mild-to-moderate renal insufficiency. Diabetes Care. 2011;34:1431–7. doi:10.2337/dc10-2361.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Gong L, Goswami S, Giacomini KM, Altman RB, Klein TE. Metformin pathways: pharmacokinetics and pharmacodynamics. Pharmacogenet Genomics. 2012;22:820–7. doi:10.1097/FPC.0b013e3283559b22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wang L, Weinshilboum R. Metformin pharmacogenomics: biomarkers to mechanisms. Diabetes. 2014;63:2609–10. doi:10.2337/db14-0609.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Tarasova L, Kalnina I, Geldnere K, Bumbure A, Ritenberga R, Nikitina-Zake L, et al. Association of genetic variation in the organic cation transporters OCT1, OCT2 and multidrug and toxin extrusion 1 transporter protein genes with the gastrointestinal side effects and lower BMI in metformin-treated type 2 diabetes patients. Pharmacogenet Genomics. 2012;22:659–66. doi:10.1097/FPC.0b013e3283561666.

    Article  CAS  PubMed  Google Scholar 

  36. Shu Y, Brown C, Castro RA, Shi RJ, Lin ET, Owen RP, et al. Effect of genetic variation in the organic cation transporter 1, OCT1, on metformin pharmacokinetics. Clin Pharmacol Ther. 2008;83:273–80. doi:10.1038/sj.clpt.6100275.

    Article  CAS  PubMed  Google Scholar 

  37. Christensen MMH, Brasch-Andersen C, Green H, Nielsen F, Damkier P, Beck-Nielsen H, et al. The pharmacogenetics of metformin and its impact on plasma metformin steady-state levels and glycosylated hemoglobin A1c. Pharmacogenet Genomics. 2011;21:837–50. doi:10.1097/FPC.0b013e32834c0010.

    Article  CAS  PubMed  Google Scholar 

  38. Yang P, Nicolás JC, Galván CA, Vélez P, Da Ronco L, Díaz GT, et al. Effectiveness of metformin in patients with type II diabetes related to variants in the SLC22A1 gene | Eficácia de Metformina em doentes com diabetes tipo II, relacionado com variantes do gene SLC22A1. Acta Bioquim Clin Latinoam. 2014;48:229–35.

    Google Scholar 

  39. Song IS, Shin HJ, Shim EJ, Jung IS, Kim WY, Shon JH, et al. Genetic variants of the organic cation transporter 2 influence the disposition of metformin. Clin Pharmacol Ther. 2008;84:559–62. doi:10.1038/clpt.2008.61.

    Article  CAS  PubMed  Google Scholar 

  40. Becker ML, Visser LE, van Schaik RHN, Hofman A, Uitterlinden AG, Stricker BHC. Genetic variation in the multidrug and toxin extrusion 1 transporter protein influences the glucose-lowering effect of metformin in patients with diabetes: a preliminary study. Diabetes. 2009;58:745–9. doi:10.2337/db08-1028.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Stocker SL, Morrissey KM, Yee SW, Castro RA, Xu L, Dahlin A, et al. The effect of novel promoter variants in MATE1 and MATE2 on the pharmacokinetics and pharmacodynamics of metformin. Clin Pharmacol Ther. 2013;93:186–94. doi:10.1038/clpt.2012.210.

    Article  CAS  PubMed  Google Scholar 

  42. Choi JH, Yee SW, Ramirez AH, Morrissey KM, Jang GH, Joski PJ, et al. A common 5′-UTR variant in MATE2-K is associated with poor response to metformin. Clin Pharmacol Ther. 2011;90:674–84. doi:10.1038/clpt.2011.165.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Zhou K, Bellenguez C, Spencer CCA, Bennett AJ, Coleman RL, Tavendale R, et al. Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet. 2011;43:117–20. doi:10.1038/ng.735.

    Article  CAS  PubMed  Google Scholar 

  44. Hauner H. The mode of action of thiazolidinediones. Diabetes Metab Res Rev. 2012;18(Suppl 2):S10–5.

    Google Scholar 

  45. Kung J, Henry RR. Thiazolidinedione safety. Expert Opin Drug Saf. 2012;11:565–79. doi:10.1517/14740338.2012.691963.

    Article  CAS  PubMed  Google Scholar 

  46. Wang L, Teng Z, Cai S, Wang D, Zhao X, Yu K. The association between the PPARγ2 Pro12Ala polymorphism and nephropathy susceptibility in type 2 diabetes: a meta-analysis based on 9,176 subjects. Diagn Pathol. 2013;8:118. doi:10.1186/1746-1596-8-118.

    PubMed  PubMed Central  Google Scholar 

  47. Knouff C, Auwerx J. Peroxisome proliferator-activated receptor-gamma calls for activation in moderation: lessons from genetics and pharmacology. Endocr Rev. 2004;25:899–918. doi:10.1210/er.2003-0036.

    Article  CAS  PubMed  Google Scholar 

  48. Ramírez-Salazar M, Pérez-Luque E, Fajardo-Araujo M, Garza SM, Malacara JM. Effect of the Pro12Ala polymorphism of the PPAR gamma 2 gene on response to pioglitazone treatment in menopausal women. Menopause. 2008;15:1151–6. doi:10.1097/gme.0b013e31816d5b2d.

    Article  PubMed  Google Scholar 

  49. Kang ES, Park SY, Kim HJ, Kim CS, Ahn CW, Cha BS, et al. Effects of Pro12Ala polymorphism of peroxisome proliferator-activated receptor gamma2 gene on rosiglitazone response in type 2 diabetes. Clin Pharmacol Ther. 2005;78:202–8. doi:10.1016/j.clpt.2005.04.013.

    Article  CAS  PubMed  Google Scholar 

  50. Hsieh M-C, Lin K-D, Tien K-J, Tu S-T, Hsiao J-Y, Chang S-J, et al. Common polymorphisms of the peroxisome proliferator-activated receptor-gamma (Pro12Ala) and peroxisome proliferator-activated receptor-gamma coactivator-1 (Gly482Ser) and the response to pioglitazone in Chinese patients with type 2 diabetes mellitus. Metabolism. 2010;59:1139–44. doi:10.1016/j.metabol.2009.10.030.

    Article  CAS  PubMed  Google Scholar 

  51. Pei Q, Huang Q, Yang G, Zhao Y, Yin J, Song M, et al. PPAR-γ2 and PTPRD gene polymorphisms influence type 2 diabetes patients’ response to pioglitazone in China. Acta Pharmacol Sin. 2013;34:255–61. doi:10.1038/aps.2012.144.

    Article  CAS  PubMed  Google Scholar 

  52. Makino H, Shimizu I, Murao S, Kondo S, Tabara Y, Fujiyama M, et al. A pilot study suggests that the G/G genotype of resistin single nucleotide polymorphism at −420 may be an independent predictor of a reduction in fasting plasma glucose and insulin resistance by pioglitazone in type 2 diabetes. Endocr J. 2009;56:1049–58.

    Article  CAS  PubMed  Google Scholar 

  53. Wang J, Bao Y, Hu C, Zhang R, Wang C, Lu J, et al. Effects of ABCA1 variants on rosiglitazone monotherapy in newly diagnosed type 2 diabetes patients. Acta Pharmacol Sin. 2008;29:252–8. doi:10.1111/j.1745-7254.2008.00744.x.

    Article  CAS  PubMed  Google Scholar 

  54. Daily EB, Aquilante CL. Cytochrome P450 2C8 pharmacogenetics: a review of clinical studies. Pharmacogenomics. 2009;10:1489–510. doi:10.2217/pgs.09.82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Stage TB, Christensen MMH, Feddersen S, Beck-Nielsen H, Brøsen K. The role of genetic variants in CYP2C8, LPIN1, PPARGC1A and PPARγ on the trough steady-state plasma concentrations of rosiglitazone and on glycosylated haemoglobin A1c in type 2 diabetes. Pharmacogenet Genomics. 2013;23:219–27. doi:10.1097/FPC.0b013e32835f91fc.

    Article  CAS  PubMed  Google Scholar 

  56. Zhou F, Huang Q, Dai X, Yin J, Wu J, Zhou H, et al. Impact of retinol binding protein 4 polymorphism on rosiglitazone response in Chinese type 2 diabetic patients. Zhong Nan Da Xue Xue Bao Yi Xue Ban2011;36:949–57. doi:10.3969/j.issn.1672-7347.2011.10.004.

  57. Kang ES, Park SY, Kim HJ, Ahn CW, Nam M, Cha BS, et al. The influence of adiponectin gene polymorphism on the rosiglitazone response in patients with type 2 diabetes. Diabetes Care. 2005;28:1139–44. doi:10.2337/diacare.28.5.1139.

    Article  CAS  PubMed  Google Scholar 

  58. van de Laar FA. Alpha-glucosidase inhibitors in the early treatment of type 2 diabetes. Vasc Health Risk Manag. 2008;4:1189–95.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Andrulionyte L, Kuulasmaa T, Chiasson J-L, Laakso M. Single nucleotide polymorphisms of the peroxisome proliferator-activated receptor-alpha gene (PPARA) influence the conversion from impaired glucose tolerance to type 2 diabetes: the STOP-NIDDM trial. Diabetes. 2007;56:1181–6. doi:10.2337/db06-1110.

    Article  CAS  PubMed  Google Scholar 

  60. Andrulionytè L, Zacharova J, Chiasson J-L, Laakso M. Common polymorphisms of the PPAR-gamma2 (Pro12Ala) and PGC-1alpha (Gly482Ser) genes are associated with the conversion from impaired glucose tolerance to type 2 diabetes in the STOP-NIDDM trial. Diabetologia. 2004;47:2176–84. doi:10.1007/s00125-004-1577-2.

    Article  PubMed  Google Scholar 

  61. Scheen AJ. A review of gliptins for 2014. Expert Opin Pharmacother. 2015;16:43–62. doi:10.1517/14656566.2015.978289.

    Article  CAS  PubMed  Google Scholar 

  62. Filippatos TD, Athyros VG, Elisaf MS. The pharmacokinetic considerations and adverse effects of DPP-4 inhibitors [corrected]. Expert Opin Drug Metab Toxicol. 2014;10:787–812. doi:10.1517/17425255.2014.907274.

    Article  CAS  PubMed  Google Scholar 

  63. Zimdahl H, Ittrich C, Graefe-Mody U, Boehm BO, Mark M, Woerle H-J, et al. Influence of TCF7L2 gene variants on the therapeutic response to the dipeptidylpeptidase-4 inhibitor linagliptin. Diabetologia. 2014;57:1869–75. doi:10.1007/s00125-014-3276-y.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Asakura M, Fujii H, Atsuda K, Itoh T, Fujiwara R. Dipeptidyl peptidase-4 greatly contributes to the hydrolysis of vildagliptin in human liver. Drug Metab Dispos. 2015;43:477–84. doi:10.1124/dmd.114.062331.

    Article  CAS  PubMed  Google Scholar 

  65. Beinborn M, Worrall CI, McBride EW, Kopin AS. A human glucagon-like peptide-1 receptor polymorphism results in reduced agonist responsiveness. Regul Pept. 2005;130:1–6. doi:10.1016/j.regpep.2005.05.001.

    Article  CAS  PubMed  Google Scholar 

  66. Christensen M, Knop FK. Once-weekly GLP-1 agonists: how do they differ from exenatide and liraglutide? Curr Diab Rep. 2010;10:124–32. doi:10.1007/s11892-010-0102-x.

    Article  CAS  PubMed  Google Scholar 

  67. de Luis DA, Ovalle HF, Soto GD, Izaola O, de la Fuente B, Romero E. Role of genetic variation in the cannabinoid receptor gene (CNR1) (G1359A polymorphism) on weight loss and cardiovascular risk factors after liraglutide treatment in obese patients with diabetes mellitus type 2. J Investig Med. 2014;62:324–7. doi:10.231/JIM.0000000000000032.

    Article  PubMed  Google Scholar 

  68. Jabbour SA, Goldstein BJ. Sodium glucose co-transporter 2 inhibitors: blocking renal tubular reabsorption of glucose to improve glycaemic control in patients with diabetes. Int J Clin Pract. 2008;62:1279–84. doi:10.1111/j.1742-1241.2008.01829.x.

    Article  CAS  PubMed  Google Scholar 

  69. Geerlings S, Fonseca V, Castro-Diaz D, List J, Parikh S. Genital and urinary tract infections in diabetes: impact of pharmacologically-induced glucosuria. Diabetes Res Clin Pract. 2014;103:373–81. doi:10.1016/j.diabres.2013.12.052.

    Article  CAS  PubMed  Google Scholar 

  70. Yu L, Lv J-C, Zhou X, Zhu L, Hou P, Zhang H. Abnormal expression and dysfunction of novel SGLT2 mutations identified in familial renal glucosuria patients. Hum Genet. 2011;129:335–44. doi:10.1007/s00439-010-0927-z.

    Article  CAS  PubMed  Google Scholar 

  71. Enigk U, Breitfeld J, Schleinitz D, Dietrich K, Halbritter J, Fischer-Rosinsky A, et al. Role of genetic variation in the human sodium-glucose cotransporter 2 gene (SGLT2) in glucose homeostasis. Pharmacogenomics. 2011;12:1119–26. doi:10.2217/pgs.11.69.

    Article  CAS  PubMed  Google Scholar 

  72. Kasichayanula S, Liu X, Griffen SC, Lacreta FP, Boulton DW. Effects of rifampin and mefenamic acid on the pharmacokinetics and pharmacodynamics of dapagliflozin. Diabetes Obes Metab. 2013;15:280–3. doi:10.1111/dom.12024.

    Article  CAS  PubMed  Google Scholar 

  73. Garber AJ, Abrahamson MJ, Barzilay JI, Blonde L, Bloomgarden ZT, Bush MA, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm—2016 executive summary. Endocr Pract. 2016;22:84–113. doi:10.4158/EP151126.CS.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

PY was supported by the Training Program from UCC-CONICET. This work was supported by UCC grant.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Néstor W. Soria.

Ethics declarations

Ethical responsibilities of authors

The manuscript has not been submitted to any other journals, has not been published previously, and has not been fabricated or manipulated.

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

The informed consent of each patient was collected in each of the cited articles.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, P., Heredia, V.O., Beltramo, D.M. et al. Pharmacogenetics and personalized treatment of type 2 diabetes mellitus. Int J Diabetes Dev Ctries 36, 508–518 (2016). https://doi.org/10.1007/s13410-016-0517-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13410-016-0517-2

Keywords

Navigation