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The Role of Pharmacogenetics in Drug Disposition and Response of Oral Glucose-Lowering Drugs

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Abstract

The primary goal of type 2 diabetes mellitus (T2DM) disease management is improvement of quality of life and prevention of complications. One way to achieve these goals is improving glycemic control by using different types of oral glucose-lowering medications. Currently seven different pharmacological oral glucose-lowering drug classes are available, each with its own mechanism of action and characteristics regarding absorption, distribution, metabolism, and elimination. Unfortunately, the response to the different types of glucose-lowering medication is highly variable between individuals resulting in unnecessary treatment failure. Genetic factors are thought to contribute to the variability in response and may present an opportunity to improve treatment outcome. In recent years, many efforts were taken to identify genetic variants that influence the pharmacokinetics, pharmacodynamics, and ultimately the therapeutic response of the different oral glucose-lowering drugs. Indeed several genetic variants are associated with the response to oral glucose-lowering drugs. This review comprises current knowledge on genetic variants affecting both pharmacokinetics and pharmacodynamics of oral glucose-lowering drugs. Included variants are located in genes coding for drug transporters, i.e., the organic anion-transporting family and the organic cation transporter family; genes involved in metabolism, i.e., cytochrome P450 superfamily; genes coding for drug receptors; T2DM-associated genes; and genes identified by genome-wide association studies (GWASs). Furthermore, this review provides insight into current status and future directions for personalized medicine in T2DM.

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References

  1. Holman RR, Paul SK, Bethel MA, et al. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359:1577–89.

    Article  PubMed  CAS  Google Scholar 

  2. American Diabetes Association. Standards of medical care in diabetes—2013. Diabetes Care. 2013;36:s11–66.

    Article  CAS  Google Scholar 

  3. Nolan CJ, Damm P, Prentki M. Type 2 diabetes across generations: from pathophysiology to prevention and management. Lancet. 2011;378:169–81.

    Article  PubMed  Google Scholar 

  4. DeFronzo RA. Pharmacologic therapy for type 2 diabetes mellitus. Ann Intern Med. 1999;131:281–303.

    Article  PubMed  CAS  Google Scholar 

  5. Mannino GC, Sesti G. Individualized therapy for type 2 diabetes: clinical implications of pharmacogenetic data. Mol Diagn Ther. 2012;16:285–302.

    Article  PubMed  CAS  Google Scholar 

  6. Pearson ER. Pharmacogenetics and future strategies in treating hyperglycaemia in diabetes. Front Biosci. 2009;14:4348–62.

    Article  CAS  Google Scholar 

  7. Manolopoulos VG, Ragia G, Tavridou A. Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective. Pharmacogenomics. 2011;12:1161–91.

    Article  PubMed  CAS  Google Scholar 

  8. Distefano JK, Watanabe RM. Pharmacogenetics of anti-diabetes drugs. Pharmaceuticals (Basel). 2010;3:2610–46.

    Article  CAS  Google Scholar 

  9. Bozkurt O, De Boer A, Grobbee DE, et al. Pharmacogenetics of glucose-lowering drug treatment: a systematic review. Mol Diagn Ther. 2007;11:291–302.

    Article  PubMed  CAS  Google Scholar 

  10. European Medicines Agency. ICH topic E15 definitions for genomic biomarkers, pharmacogenomics, pharmacogenetics, genomic data and sample coding categories. London, EMA; 2013.

  11. Krentz AJ, Bailey CJ. Oral antidiabetic agents: current role in type 2 diabetes mellitus. Drugs. 2005;65:385–411.

    Article  PubMed  CAS  Google Scholar 

  12. Groop LC. Sulfonylureas in NIDDM. Diabetes Care. 1992;15:737–54.

    Article  PubMed  CAS  Google Scholar 

  13. Aquilante CL. Sulfonylurea pharmacogenomics in type 2 diabetes: the influence of drug target and diabetes risk polymorphisms. Expert Rev Cardiovasc Ther. 2010;8:359–72.

    Article  PubMed  CAS  Google Scholar 

  14. Relling MV, Aoyama T, Gonzalez FJ, et al. Tolbutamide and mephenytoin hydroxylation by human cytochrome P450s in the CYP2C subfamily. J Pharmacol Exp Ther. 1990;252:442–7.

    PubMed  CAS  Google Scholar 

  15. Kirchheiner J, Roots I, Goldammer M, et al. Effect of genetic polymorphisms in cytochrome p450 (CYP) 2C9 and CYP2C8 on the pharmacokinetics of oral antidiabetic drugs: clinical relevance. Clin Pharmacokinet. 2005;44:1209–25.

    Article  PubMed  CAS  Google Scholar 

  16. Scott J, Poffenbarger PL. Pharmacogenetics of tolbutamide metabolism in humans. Diabetes. 1979;28:41–51.

    Article  PubMed  CAS  Google Scholar 

  17. Vormfelde SV, Brockmoller J, Bauer S, et al. Relative impact of genotype and enzyme induction on the metabolic capacity of CYP2C9 in healthy volunteers. Clin Pharmacol Ther. 2009;86:54–61.

    Article  PubMed  CAS  Google Scholar 

  18. Shon JH, Yoon YR, Kim KA, et al. Effects of CYP2C19 and CYP2C9 genetic polymorphisms on the disposition of and blood glucose lowering response to tolbutamide in humans. Pharmacogenetics. 2002;12:111–9.

    Article  PubMed  CAS  Google Scholar 

  19. Kirchheiner J, Bauer S, Meineke I, et al. Impact of CYP2C9 and CYP2C19 polymorphisms on tolbutamide kinetics and the insulin and glucose response in healthy volunteers. Pharmacogenetics. 2002;12:101–9.

    Article  PubMed  CAS  Google Scholar 

  20. Wang R, Chen K, Wen SY, et al. Pharmacokinetics of glimepiride and cytochrome P450 2C9 genetic polymorphisms. Clin Pharmacol Ther. 2005;78:90–2.

    Article  PubMed  CAS  Google Scholar 

  21. Zhang Y, Si D, Chen X, et al. Influence of CYP2C9 and CYP2C19 genetic polymorphisms on pharmacokinetics of gliclazide MR in Chinese subjects. Br J Clin Pharmacol. 2007;64:67–74.

    Article  PubMed  CAS  Google Scholar 

  22. Yin OQ, Tomlinson B, Chow MS. CYP2C9, but not CYP2C19, polymorphisms affect the pharmacokinetics and pharmacodynamics of glyburide in Chinese subjects. Clin Pharmacol Ther. 2005;78:370–7.

    Article  PubMed  CAS  Google Scholar 

  23. Kirchheiner J, Brockmoller J, Meineke I, 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.

    Article  PubMed  CAS  Google Scholar 

  24. Zhou K, Donnelly L, Burch L, et al. Loss-of-function CYP2C9 variants improve therapeutic response to sulfonylureas in type 2 diabetes: a Go-DARTS study. Clin Pharmacol Ther. 2010;87:52–6.

    Article  PubMed  CAS  Google Scholar 

  25. Holstein A, Plaschke A, Ptak M, et al. Association between CYP2C9 slow metabolizer genotypes and severe hypoglycaemia on medication with sulphonylurea hypoglycaemic agents. Br J Clin Pharmacol. 2005;60:103–6.

    Article  PubMed  CAS  Google Scholar 

  26. Holstein A, Hahn M, Patzer O, et al. Impact of clinical factors and CYP2C9 variants for the risk of severe sulfonylurea-induced hypoglycemia. Eur J Clin Pharmacol. 2011;67:471–6.

    Article  PubMed  CAS  Google Scholar 

  27. Florez JC, Jablonski KA, Kahn SE, et al. Type 2 diabetes-associated missense polymorphisms KCNJ11 E23K and ABCC8 A1369S influence progression to diabetes and response to interventions in the Diabetes Prevention Program. Diabetes. 2007;56:531–6.

    Article  PubMed  CAS  Google Scholar 

  28. Nielsen EM, Hansen L, Carstensen B, et al. The E23K variant of Kir6.2 associates with impaired post-OGTT serum insulin response and increased risk of type 2 diabetes. Diabetes. 2003;52:573–7.

    Article  PubMed  CAS  Google Scholar 

  29. Sato R, Watanabe H, Genma R, et al. ABCC8 polymorphism (Ser1369Ala): influence on severe hypoglycemia due to sulfonylureas. Pharmacogenomics. 2010;11:1743–50.

    Article  PubMed  CAS  Google Scholar 

  30. Hamming KS, Soliman D, Matemisz LC, 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. 2009;58:2419–24.

    Article  PubMed  CAS  Google Scholar 

  31. Zhang H, Liu X, Kuang H, et al. Association of sulfonylurea receptor 1 genotype with therapeutic response to gliclazide in type 2 diabetes. Diabetes Res Clin Pract. 2007;77:58–61.

    Article  PubMed  CAS  Google Scholar 

  32. Feng Y, Mao G, Ren X, et al. Ser1369Ala variant in sulfonylurea receptor gene ABCC8 is associated with antidiabetic efficacy of gliclazide in Chinese type 2 diabetic patients. Diabetes Care. 2008;31:1939–44.

    Article  PubMed  CAS  Google Scholar 

  33. Sesti G, Laratta E, Cardellini M, 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.

    Article  PubMed  CAS  Google Scholar 

  34. Holstein A, Hahn M, Stumvoll M, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  35. Javorsky M, Klimcakova L, Schroner Z, et al. KCNJ11 gene E23K variant and therapeutic response to sulfonylureas. Eur J Intern Med. 2012;23:245–9.

    Article  PubMed  CAS  Google Scholar 

  36. Sanghera DK, Blackett PR. Type 2 diabetes genetics: beyond GWAS. J Diabetes Metab. 2012;3.

  37. Becker ML, Aarnoudse AJ, Newton-Cheh C, et al. Common variation in the NOS1AP gene is associated with reduced glucose-lowering effect and with increased mortality in users of sulfonylurea. Pharmacogenet Genomics. 2008;18:591–7.

    Article  PubMed  CAS  Google Scholar 

  38. Schulz R, Rassaf T, Massion PB, et al. Recent advances in the understanding of the role of nitric oxide in cardiovascular homeostasis. Pharmacol Ther. 2005;108:225–56.

    Article  PubMed  CAS  Google Scholar 

  39. Cho HJ, Lee SY, Kim YG, et al. Effect of genetic polymorphisms on the pharmacokinetics and efficacy of glimepiride in a Korean population. Clin Chim Acta. 2011;412:1831–4.

    Article  PubMed  CAS  Google Scholar 

  40. Almind K, Bjorbaek C, Vestergaard H, et al. Aminoacid polymorphisms of insulin receptor substrate-1 in non-insulin-dependent diabetes mellitus. Lancet. 1993;342:828–32.

    Article  PubMed  CAS  Google Scholar 

  41. Jellema A, Zeegers MP, Feskens EJ, et al. Gly972Arg variant in the insulin receptor substrate-1 gene and association with type 2 diabetes: a meta-analysis of 27 studies. Diabetologia. 2003;46:990–5.

    Article  PubMed  CAS  Google Scholar 

  42. Sesti G, Marini MA, Cardellini M, 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  PubMed  CAS  Google Scholar 

  43. Seeringer A, Parmar S, Fischer A, et al. Genetic variants of the insulin receptor substrate-1 are influencing the therapeutic efficacy of oral antidiabetics. Diabetes Obes Metab. 2010;12:1106–12.

    Article  PubMed  CAS  Google Scholar 

  44. Grant SF, Thorleifsson G, Reynisdottir I, et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat Genet. 2006;38:320–3.

    Article  PubMed  CAS  Google Scholar 

  45. Pearson ER. Translating TCF7L2: from gene to function. Diabetologia. 2009;52:1227–30.

    Article  PubMed  CAS  Google Scholar 

  46. Pearson ER, Donnelly LA, Kimber C, et al. Variation in TCF7L2 influences therapeutic response to sulfonylureas: a GoDARTs study. Diabetes. 2007;56:2178–82.

    Article  PubMed  CAS  Google Scholar 

  47. Schroner Z, Javorsky M, Tkacova R, et al. Effect of sulphonylurea treatment on glycaemic control is related to TCF7L2 genotype in patients with type 2 diabetes. Diabetes Obes Metab. 2011;13:89–91.

    Article  PubMed  CAS  Google Scholar 

  48. Holstein A, Hahn M, Korner A, et al. TCF7L2 and therapeutic response to sulfonylureas in patients with type 2 diabetes. BMC Med Genet. 2011;12:30.

    Article  PubMed  CAS  Google Scholar 

  49. Swen JJ, Guchelaar HJ, Baak-Pablo RF, et al. Genetic risk factors for type 2 diabetes mellitus and response to sulfonylurea treatment. Pharmacogenet Genomics. 2011;21:461–8.

    Article  PubMed  CAS  Google Scholar 

  50. Gat-Yablonski G, Shalitin S, Phillip M. Maturity onset diabetes of the young—review. Pediatr Endocrinol Rev. 2006;3(Suppl 3):514–20.

    PubMed  Google Scholar 

  51. Tattersall RB, Fajans SS. A difference between the inheritance of classical juvenile-onset and maturity-onset type diabetes of young people. Diabetes. 1975;24:44–53.

    Article  PubMed  CAS  Google Scholar 

  52. Pearson ER, Starkey BJ, Powell RJ, et al. Genetic cause of hyperglycaemia and response to treatment in diabetes. Lancet. 2003;362:1275–81.

    Article  PubMed  CAS  Google Scholar 

  53. Hattersley A, Bruining J, Shield J, et al. The diagnosis and management of monogenic diabetes in children and adolescents. Pediatr Diabetes. 2009;10(Suppl 12):33–42.

    Article  PubMed  Google Scholar 

  54. Pearson ER, Flechtner I, Njolstad PR, et al. Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations. N Engl J Med. 2006;355:467–77.

    Article  PubMed  CAS  Google Scholar 

  55. Proks P, Arnold AL, Bruining J, et al. A heterozygous activating mutation in the sulphonylurea receptor SUR1 (ABCC8) causes neonatal diabetes. Hum Mol Genet. 2006;15:1793–800.

    Article  PubMed  CAS  Google Scholar 

  56. Cheng Y, Wang G, Zhang W, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  57. Zhang W, He YJ, Han CT, et al. Effect of SLCO1B1 genetic polymorphism on the pharmacokinetics of nateglinide. Br J Clin Pharmacol. 2006;62:567–72.

    Article  PubMed  CAS  Google Scholar 

  58. Kalliokoski A, Neuvonen M, Neuvonen PJ, et al. Different effects of SLCO1B1 polymorphism on the pharmacokinetics and pharmacodynamics of repaglinide and nateglinide. J Clin Pharmacol. 2008;48:311–21.

    Article  PubMed  CAS  Google Scholar 

  59. Kalliokoski A, Backman JT, Neuvonen PJ, et al. Effects of the SLCO1B1*1B haplotype on the pharmacokinetics and pharmacodynamics of repaglinide and nateglinide. Pharmacogenet Genomics. 2008;18:937–42.

    Article  PubMed  CAS  Google Scholar 

  60. Weaver ML, Orwig BA, Rodriguez LC, et al. Pharmacokinetics and metabolism of nateglinide in humans. Drug Metab Dispos. 2001;29:415–21.

    PubMed  CAS  Google Scholar 

  61. McLeod JF. Clinical pharmacokinetics of nateglinide: a rapidly-absorbed, short-acting insulinotropic agent. Clin Pharmacokinet. 2004;43:97–120.

    Article  PubMed  CAS  Google Scholar 

  62. Kirchheiner J, Meineke I, Muller G, et al. Influence of CYP2C9 and CYP2D6 polymorphisms on the pharmacokinetics of nateglinide in genotyped healthy volunteers. Clin Pharmacokinet. 2004;43:267–78.

    Article  PubMed  CAS  Google Scholar 

  63. Niemi M, Leathart JB, Neuvonen M, et al. Polymorphism in CYP2C8 is associated with reduced plasma concentrations of repaglinide. Clin Pharmacol Ther. 2003;74:380–7.

    Article  PubMed  CAS  Google Scholar 

  64. Bidstrup TB, Damkier P, Olsen AK, et al. The impact of CYP2C8 polymorphism and grapefruit juice on the pharmacokinetics of repaglinide. Br J Clin Pharmacol. 2006;61:49–57.

    Article  PubMed  CAS  Google Scholar 

  65. Ruzilawati AB, Gan SH. CYP3A4 genetic polymorphism influences repaglinide’s pharmacokinetics. Pharmacology. 2010;85:357–64.

    Article  PubMed  CAS  Google Scholar 

  66. Tomalik-Scharte D, Fuhr U, Hellmich M, et al. Effect of the CYP2C8 genotype on the pharmacokinetics and pharmacodynamics of repaglinide. Drug Metab Dispos. 2011;39:927–32.

    Article  PubMed  CAS  Google Scholar 

  67. He YY, Zhang R, Shao XY, et al. Association of KCNJ11 and ABCC8 genetic polymorphisms with response to repaglinide in Chinese diabetic patients. Acta Pharmacol Sin. 2008;29:983–9.

    Article  PubMed  CAS  Google Scholar 

  68. Yu M, Xu XJ, Yin JY, 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.

    Article  PubMed  CAS  Google Scholar 

  69. Yu W, Hu C, Zhang R, 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.

    Article  PubMed  CAS  Google Scholar 

  70. 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 Genomics. 2012;22:206–14.

    Article  PubMed  CAS  Google Scholar 

  71. Huang Q, Yin JY, Dai XP, et al. IGF2BP2 variations influence repaglinide response and risk of type 2 diabetes in Chinese population. Acta Pharmacol Sin. 2010;31:709–17.

    Article  PubMed  CAS  Google Scholar 

  72. Qin W, Zhang R, Hu C, et al. A variation in NOS1AP gene is associated with repaglinide efficacy on insulin resistance in type 2 diabetes of Chinese. Acta Pharmacol Sin. 2010;31:450–4.

    Article  PubMed  CAS  Google Scholar 

  73. Sheng FF, Dai XP, Qu J, et al. NAMPT −3186C/T polymorphism affects repaglinide response in Chinese patients with type 2 diabetes mellitus. Clin Exp Pharmacol Physiol. 2011;38:550–4.

    Article  PubMed  CAS  Google Scholar 

  74. Jiang F, Li Q, Hu C, et al. Association of a SLC30A8 genetic variant with monotherapy of repaglinide and rosiglitazone effect in newly diagnosed type 2 diabetes patients in China. Biomed Environ Sci. 2012;25:23–9.

    PubMed  CAS  Google Scholar 

  75. Gong ZC, Huang Q, Dai XP, et al. NeuroD1 A45T and PAX4 R121W polymorphisms are associated with plasma glucose level of repaglinide monotherapy in Chinese patients with type 2 diabetes. Br J Clin Pharmacol. 2012;74:501–9.

    Article  PubMed  CAS  Google Scholar 

  76. Nathan DM, Buse JB, Davidson MB, et al. Medical management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2009;32:193–203.

    Article  PubMed  CAS  Google Scholar 

  77. Kimura N, Masuda S, Tanihara Y, et al. Metformin is a superior substrate for renal organic cation transporter OCT2 rather than hepatic OCT1. Drug Metab Pharmacokinet. 2005;20:379–86.

    Article  PubMed  CAS  Google Scholar 

  78. Otsuka M, Matsumoto T, Morimoto R, et al. A human transporter protein that mediates the final excretion step for toxic organic cations. Proc Natl Acad Sci U S A. 2005;102:17923–8.

    Article  PubMed  CAS  Google Scholar 

  79. Owen MR, Doran E, Halestrap AP. Evidence that metformin exerts its anti-diabetic effects through inhibition of complex 1 of the mitochondrial respiratory chain. Biochem J. 2000;348(Pt 3):607–14.

    Article  PubMed  CAS  Google Scholar 

  80. Zhou K, Bellenguez C, Spencer CC, et al. Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes. Nat Genet. 2011;43:117–20.

    Article  PubMed  CAS  Google Scholar 

  81. van Leeuwen N, Nijpels G, Becker ML, et al. A gene variant near ATM is significantly associated with metformin treatment response in type 2 diabetes: a replication and meta-analysis of five cohorts. Diabetologia. 2012;55:1971–7.

    Article  PubMed  CAS  Google Scholar 

  82. Florez JC, Jablonski K, Taylor A, et al. The C allele of ATM rs11212617 does not associate with metformin response in the diabetes prevention program (abstract). Diabetes. 2011;60:A386.

    Google Scholar 

  83. Woods A, Leiper JM, Carling D. The role of ATM in response to metformin treatment and activation of AMPK. Nat Genet. 2012;44:360–1.

    Article  PubMed  CAS  Google Scholar 

  84. Zhou K, Bellenguez C, Sutherland C, et al. The role of ATM in response to metformin treatment and activation of AMPK. Nat Genet. 2012;44:361–2.

    Article  PubMed  CAS  Google Scholar 

  85. Gitlin N, Julie NL, Spurr CL, et al. Two cases of severe clinical and histologic hepatotoxicity associated with troglitazone. Ann Intern Med. 1998;129:36–8.

    Article  PubMed  CAS  Google Scholar 

  86. Delea TE, Edelsberg JS, Hagiwara M, et al. Use of thiazolidinediones and risk of heart failure in people with type 2 diabetes: a retrospective cohort study. Diabetes Care. 2003;26:2983–9.

    Article  PubMed  CAS  Google Scholar 

  87. Colmers IN, Bowker SL, Majumdar SR, et al. Use of thiazolidinediones and the risk of bladder cancer among people with type 2 diabetes: a meta-analysis. CMAJ. 2012;184:E675–83.

    Article  PubMed  Google Scholar 

  88. Baldwin SJ, Clarke SE, Chenery RJ. Characterization of the cytochrome P450 enzymes involved in the in vitro metabolism of rosiglitazone. Br J Clin Pharmacol. 1999;48:424–32.

    Article  PubMed  CAS  Google Scholar 

  89. Jaakkola T, Laitila J, Neuvonen PJ, et al. Pioglitazone is metabolised by CYP2C8 and CYP3A4 in vitro: potential for interactions with CYP2C8 inhibitors. Basic Clin Pharmacol Toxicol. 2006;99:44–51.

    Article  PubMed  CAS  Google Scholar 

  90. Kirchheiner J, Thomas S, Bauer S, et al. Pharmacokinetics and pharmacodynamics of rosiglitazone in relation to CYP2C8 genotype. Clin Pharmacol Ther. 2006;80:657–67.

    Article  PubMed  CAS  Google Scholar 

  91. Ramirez-Salazar M, Perez-Luque E, Fajardo-Araujo M, et al. Effect of the Pro12Ala polymorphism of the PPAR gamma 2 gene on response to pioglitazone treatment in menopausal women. Menopause. 2008;15:1151–6.

    Article  PubMed  Google Scholar 

  92. Hsieh MC, Lin KD, Tien KJ, 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.

    Article  PubMed  CAS  Google Scholar 

  93. Mathur SK, Rathore R, Chandra S, et al. Primary pioglitazone failure in Asian Indian diabetics is not related to common Pro12Ala polymorph of PPAR-gamma gene. Indian J Physiol Pharmacol. 2009;53:175–80.

    PubMed  CAS  Google Scholar 

  94. Andrulionyte L, Kuulasmaa T, Chiasson JL, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  95. Drucker DJ, Nauck MA. The incretin system: glucagon-like peptide-1 receptor agonists and dipeptidyl peptidase-4 inhibitors in type 2 diabetes. Lancet. 2006;368:1696–705.

    Article  PubMed  CAS  Google Scholar 

  96. Morris AP, Voight BF, Teslovich TM, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90.

    Article  PubMed  CAS  Google Scholar 

  97. Ho PM, Rumsfeld JS, Masoudi FA, et al. Effect of medication nonadherence on hospitalization and mortality among patients with diabetes mellitus. Arch Intern Med. 2006;166:1836–41.

    Article  PubMed  Google Scholar 

  98. Cramer JA. A systematic review of adherence with medications for diabetes. Diabetes Care. 2004;27:1218–24.

    Article  PubMed  Google Scholar 

  99. Harper AR, Topol EJ. Pharmacogenomics in clinical practice and drug development. Nat Biotechnol. 2012;30:1117–24.

    Article  PubMed  CAS  Google Scholar 

  100. Tatonetti NP, Ye PP, Daneshjou R, et al. Data-driven prediction of drug effects and interactions. Sci Transl Med. 2012;4:125ra31.

    Article  PubMed  Google Scholar 

  101. Lander ES. Initial impact of the sequencing of the human genome. Nature. 2011;470:187–97.

    Article  PubMed  CAS  Google Scholar 

  102. Suzuki K, Yanagawa T, Shibasaki T, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  103. Ragia G, Petridis I, Tavridou A, et al. Presence of CYP2C9*3 allele increases risk for hypoglycemia in type 2 diabetic patients treated with sulfonylureas. Pharmacogenomics. 2009;10:1781–7.

    Article  PubMed  CAS  Google Scholar 

  104. Becker ML, Visser LE, Trienekens PH, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  105. Swen JJ, Wessels JA, Krabben A, et al. Effect of CYP2C9 polymorphisms on prescribed dose and time-to-stable dose of sulfonylureas in primary care patients with type 2 diabetes mellitus. Pharmacogenomics. 2010;11:1517–23.

    Article  PubMed  CAS  Google Scholar 

  106. Gokalp O, Gunes A, Cam H, et al. Mild hypoglycaemic attacks induced by sulphonylureas related to CYP2C9, CYP2C19 and CYP2C8 polymorphisms in routine clinical setting. Eur J Clin Pharmacol. 2011;67:1223–9.

    Article  PubMed  CAS  Google Scholar 

  107. Surendiran A, Pradhan SC, Agrawal A, 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.

    Article  PubMed  CAS  Google Scholar 

  108. Hansen T, Echwald SM, Hansen L, et al. Decreased tolbutamide-stimulated insulin secretion in healthy subjects with sequence variants in the high-affinity sulfonylurea receptor gene. Diabetes. 1998;47:598–605.

    Article  PubMed  CAS  Google Scholar 

  109. Meirhaeghe A, Helbecque N, Cottel D, et al. Impact of sulfonylurea receptor 1 genetic variability on non-insulin-dependent diabetes mellitus prevalence and treatment: a population study. Am J Med Genet. 2001;101:4–8.

    Article  PubMed  CAS  Google Scholar 

  110. Holstein JD, Kovacs P, Patzer O, et al. The Ser1369Ala variant of ABCC8 and the risk for severe sulfonylurea-induced hypoglycemia in German patients with type 2 diabetes. Pharmacogenomics. 2012;13:5–7.

    Article  PubMed  CAS  Google Scholar 

  111. Zychma MJ, Gumprecht J, Strojek K, et al. Sulfonylurea receptor gene 16-3 polymorphism—association with sulfonylurea or insulin treatment in type 2 diabetic subjects. Med Sci Monit. 2002;8:CR512–5.

    PubMed  CAS  Google Scholar 

  112. Gloyn AL, Hashim Y, Ashcroft SJ, et al. Association studies of variants in promoter and coding regions of beta-cell ATP-sensitive K-channel genes SUR1 and Kir6.2 with type 2 diabetes mellitus (UKPDS 53). Diabet Med. 2001;18:206–12.

    Article  PubMed  CAS  Google Scholar 

  113. Niemi M, Backman JT, Kajosaari LI, et al. Polymorphic organic anion transporting polypeptide 1B1 is a major determinant of repaglinide pharmacokinetics. Clin Pharmacol Ther. 2005;77:468–78.

    Article  PubMed  CAS  Google Scholar 

  114. He J, Qiu Z, Li N, et al. Effects of SLCO1B1 polymorphisms on the pharmacokinetics and pharmacodynamics of repaglinide in healthy Chinese volunteers. Eur J Clin Pharmacol. 2011;67:701–7.

    Article  PubMed  CAS  Google Scholar 

  115. Xiang Q, Cui YM, Zhao X, et al. The influence of MDR1 G2677T/a genetic polymorphisms on the pharmacokinetics of repaglinide in healthy Chinese volunteers. Pharmacology. 2012;89:105–10.

    Article  PubMed  CAS  Google Scholar 

  116. Shu Y, Sheardown SA, Brown C, et al. Effect of genetic variation in the organic cation transporter 1 (OCT1) on metformin action. J Clin Invest. 2007;117:1422–31.

    Article  PubMed  CAS  Google Scholar 

  117. Tzvetkov MV, Vormfelde SV, Balen D, et al. The effects of genetic polymorphisms in the organic cation transporters OCT1, OCT2, and OCT3 on the renal clearance of metformin. Clin Pharmacol Ther. 2009;86:299–306.

    Article  PubMed  CAS  Google Scholar 

  118. Shikata E, Yamamoto R, Takane H, et al. Human organic cation transporter (OCT1 and OCT2) gene polymorphisms and therapeutic effects of metformin. J Hum Genet. 2007;52:117–22.

    Article  PubMed  CAS  Google Scholar 

  119. Becker ML, Visser LE, van Schaik RH, et al. Genetic variation in the organic cation transporter 1 is associated with metformin response in patients with diabetes mellitus. Pharmacogenomics J. 2009;9:242–7.

    Article  PubMed  CAS  Google Scholar 

  120. Zhou K, Donnelly LA, Kimber CH, et al. Reduced-function SLC22A1 polymorphisms encoding organic cation transporter 1 and glycemic response to metformin: a GoDARTS study. Diabetes. 2009;58:1434–9.

    Article  PubMed  CAS  Google Scholar 

  121. Shu Y, Brown C, Castro RA, et al. Effect of genetic variation in the organic cation transporter 1, OCT1, on metformin pharmacokinetics. Clin Pharmacol Ther. 2008;83:273–80.

    Article  PubMed  CAS  Google Scholar 

  122. Jablonski KA, McAteer JB, de Bakker PI, et al. Common variants in 40 genes assessed for diabetes incidence and response to metformin and lifestyle intervention in the diabetes prevention program. Diabetes. 2010;59:2672–81.

    Article  PubMed  CAS  Google Scholar 

  123. Tkac I, Klimcakova L, Javorsky M, et al. Pharmacogenomic association between a variant in SLC47A1 gene and therapeutic response to metformin in type 2 diabetes. Diabetes Obes Metab. 2013;15:189–91.

    Article  PubMed  CAS  Google Scholar 

  124. Christensen MM, Brasch-Andersen C, Green 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.

    Article  PubMed  CAS  Google Scholar 

  125. Leabman MK, Huang CC, Kawamoto M, et al. Polymorphisms in a human kidney xenobiotic transporter, OCT2, exhibit altered function. Pharmacogenetics. 2002;12:395–405.

    Article  PubMed  CAS  Google Scholar 

  126. Wang DS, Jonker JW, Kato Y, et al. Involvement of organic cation transporter 1 in hepatic and intestinal distribution of metformin. J Pharmacol Exp Ther. 2002;302:510–5.

    Article  PubMed  CAS  Google Scholar 

  127. Song IS, Shin HJ, Shim EJ, et al. Genetic variants of the organic cation transporter 2 influence the disposition of metformin. Clin Pharmacol Ther. 2008;84:559–62.

    Article  PubMed  CAS  Google Scholar 

  128. Chen Y, Li S, Brown C, et al. Effect of genetic variation in the organic cation transporter 2 on the renal elimination of metformin. Pharmacogenet Genomics. 2009;19:497–504.

    Article  PubMed  CAS  Google Scholar 

  129. Zolk O, Solbach TF, Konig J, et al. Functional characterization of the human organic cation transporter 2 variantp. 270Ala>Ser. Drug Metab Dispos. 2009;37:1312–8.

    Article  PubMed  CAS  Google Scholar 

  130. Li Q, Liu F, Zheng TS, et al. SLC22A2 gene 808 G/T variant is related to plasma lactate concentration in Chinese type 2 diabetics treated with metformin. Acta Pharmacol Sin. 2010;31:184–90.

    Article  PubMed  CAS  Google Scholar 

  131. Becker ML, Visser LE, van Schaik RH, et al. 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.

    Article  PubMed  CAS  Google Scholar 

  132. Toyama K, Yonezawa A, Tsuda M, et al. Heterozygous variants of multidrug and toxin extrusions (MATE1 and MATE2-K) have little influence on the disposition of metformin in diabetic patients. Pharmacogenet Genomics. 2010;20:135–8.

    Article  PubMed  CAS  Google Scholar 

  133. Stocker SL, Morrissey KM, Yee SW, 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.

    Article  PubMed  CAS  Google Scholar 

  134. Meyer zu Schwabedissen HE, Verstuyft C, Kroemer HK, et al. Human multidrug and toxin extrusion 1 (MATE1/SLC47A1) transporter: functional characterization, interaction with OCT2 (SLC22A2), and single nucleotide polymorphisms. Am J Physiol Renal Physiol. 2010;298:F997–1005.

    Article  PubMed  CAS  Google Scholar 

  135. Choi JH, Yee SW, Ramirez AH, et al. A common 5′-UTR variant in MATE2-K is associated with poor response to metformin. Clin Pharmacol Ther. 2011;90:674–84.

    Article  PubMed  CAS  Google Scholar 

  136. Joven J, Menendez J, Fernandez-Sender L, et al. Metformin: a cheap and well-tolerated drug that provides benefits for viral infections. HIV Med. 2013;14:133–240.

    Article  CAS  Google Scholar 

  137. Kang ES, Park SY, Kim HJ, 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.

    Article  PubMed  CAS  Google Scholar 

  138. Zhang KH, Huang Q, Dai XP, et al. Effects of the peroxisome proliferator activated receptor-gamma coactivator-1alpha (PGC-1alpha) Thr394Thr and Gly482Ser polymorphisms on rosiglitazone response in Chinese patients with type 2 diabetes mellitus. J Clin Pharmacol. 2010;50:1022–30.

    Article  PubMed  CAS  Google Scholar 

  139. Hruska MW, Amico JA, Langaee TY, et al. The effect of trimethoprim on CYP2C8 mediated rosiglitazone metabolism in human liver microsomes and healthy subjects. Br J Clin Pharmacol. 2005;59:70–9.

    Article  PubMed  CAS  Google Scholar 

  140. Pedersen RS, Damkier P, Brosen K. The effects of human CYP2C8 genotype and fluvoxamine on the pharmacokinetics of rosiglitazone in healthy subjects. Br J Clin Pharmacol. 2006;62:682–9.

    Article  PubMed  CAS  Google Scholar 

  141. Aquilante CL, Bushman LR, Knutsen SD, et al. Influence of SLCO1B1 and CYP2C8 gene polymorphisms on rosiglitazone pharmacokinetics in healthy volunteers. Hum Genomics. 2008;3:7–16.

    PubMed  CAS  Google Scholar 

  142. Yeo CW, Lee SJ, Lee SS, et al. Discovery of a novel allelic variant of CYP2C8, CYP2C8*11, in Asian populations and its clinical effect on the rosiglitazone disposition in vivo. Drug Metab Dispos. 2011;39:711–6.

    Article  PubMed  CAS  Google Scholar 

  143. Kalliokoski A, Neuvonen M, Neuvonen PJ, et al. No significant effect of SLCO1B1 polymorphism on the pharmacokinetics of rosiglitazone and pioglitazone. Br J Clin Pharmacol. 2008;65:78–86.

    Article  PubMed  CAS  Google Scholar 

  144. Kang ES, Park SE, Han SJ, et al. LPIN1 genetic variation is associated with rosiglitazone response in type 2 diabetic patients. Mol Genet Metab. 2008;95:96–100.

    Article  PubMed  CAS  Google Scholar 

  145. Kang ES, Cha BS, Kim HJ, et al. The 11482G >A polymorphism in the perilipin gene is associated with weight gain with rosiglitazone treatment in type 2 diabetes. Diabetes Care. 2006;29:1320–4.

    Article  PubMed  CAS  Google Scholar 

  146. Tornio A, Niemi M, Neuvonen PJ, et al. Trimethoprim and the CYP2C8*3 allele have opposite effects on the pharmacokinetics of pioglitazone. Drug Metab Dispos. 2008;36:73–80.

    Article  PubMed  CAS  Google Scholar 

  147. Li Z, Peng X, Wu Y, et al. The influence of adiponectin gene polymorphism on the pioglitazone response in the Chinese with type 2 diabetes. Diabetes Obes Metab. 2008;10:794–802.

    Article  PubMed  CAS  Google Scholar 

  148. Wang G, Wang X, Zhang Q, et al. Response to pioglitazone treatment is associated with the lipoprotein lipase S447X variant in subjects with type 2 diabetes mellitus. Int J Clin Pract. 2007;61:552–7.

    Article  PubMed  CAS  Google Scholar 

  149. Makino H, Shimizu I, Murao S, 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  PubMed  CAS  Google Scholar 

  150. Schafer SA, Tschritter O, Machicao F, et al. Impaired glucagon-like peptide-1-induced insulin secretion in carriers of transcription factor 7-like 2 (TCF7L2) gene polymorphisms. Diabetologia. 2007;50:2443–50.

    Article  PubMed  CAS  Google Scholar 

  151. Schafer SA, Mussig K, Staiger H, et al. A common genetic variant in WFS1 determines impaired glucagon-like peptide-1-induced insulin secretion. Diabetologia. 2009;52:1075–82.

    Article  PubMed  CAS  Google Scholar 

  152. Simonis-Bik AM, Nijpels G, van Haeften TW, et al. Gene variants in the novel type 2 diabetes loci CDC123/CAMK1D, THADA, ADAMTS9, BCL11A, and MTNR1B affect different aspects of pancreatic beta-cell function. Diabetes. 2010;59:293–301.

    Article  PubMed  CAS  Google Scholar 

  153. Sathananthan A, Man CD, Micheletto F, et al. Common genetic variation in GLP1R and insulin secretion in response to exogenous GLP-1 in nondiabetic subjects: a pilot study. Diabetes Care. 2010;33:2074–6.

    Article  PubMed  CAS  Google Scholar 

  154. 't Hart LM, Fritsche A, Nijpels G, et al. The CTRB1/2 locus affects diabetes susceptibility and treatment via the incretin pathway. Diabetes. 2013. [Epub ahead of print]

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Acknowledgments

Authors NvL and JJS contributed equally to this manuscript. No additional funding was received.

Conflict of interest

N. van Leeuwen, J.J. Swen, H.-J. Guchelaar, L.M. ’t Hart declare that no conflicting interests exist.

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Authors and Affiliations

  1. Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands

    N. van Leeuwen & L. M. ’t Hart

  2. Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, P.O. Box 9600, 2300 RC, Leiden, The Netherlands

    J. J. Swen & H.-J. Guchelaar

  3. Department of Molecular Epidemiology, Leiden University Medical Center, Leiden, The Netherlands

    L. M. ’t Hart

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  1. N. van Leeuwen
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  3. H.-J. Guchelaar
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Correspondence to H.-J. Guchelaar.

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van Leeuwen, N., Swen, J.J., Guchelaar, HJ. et al. The Role of Pharmacogenetics in Drug Disposition and Response of Oral Glucose-Lowering Drugs. Clin Pharmacokinet 52, 833–854 (2013). https://doi.org/10.1007/s40262-013-0076-3

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