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2000
Volume 22, Issue 1
  • ISSN: 1875-6921
  • E-ISSN: 1875-6913

Abstract

Type 2 diabetes mellitus is one of the leading causes of morbidity and mortality in the world. The two main components of the mechanism underlying T2DM are insulin resistance and impaired insulin secretion. The current algorithmic approach to the treatment of the disease does not take the individual genetic makeup of patients into consideration. However, multiple gene variants affect the efficacy and metabolism of anti-diabetes medications. For example, MATE1 works in conjunction with OCT1 and OCT2 to regulate metformin elimination, the rs1801282 (Pro12Ala) single nucleotide polymorphism is associated with a better therapeutic response to pioglitazone across different populations, and the K allele of KCNJ11 rs5219 (E23K) polymorphism is associated with a greater HbA1c reduction in Caucasian and Chinese patients treated with gliclazide, a sulfonylurea. Modern genetic techniques have ushered in the era of pharmacogenomics and precision medicine, identifying genetic variations that can be translated into personalized treatment approaches, improved diabetes risk prediction, ethnic-specific insights, identification of new drug targets, and reduction of adverse drug reactions. Challenges in the implementation of pharmacogenomics in the treatment of Type 2 diabetes include modest effect sizes of many genetic variants, heterogeneity of the disease due to complex interactions between genetics, environment, and lifestyles, and the cost of genetic testing and analysis. This review summarizes the genetic variations affecting each major class of non-insulin anti-diabetes medications.

This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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2025-03-10
2025-09-01
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References

  1. National diabetes statistics report, 2022. Estimates of diabetes and its burden in the United States. 2022. Available from: https://www.cdc.gov/diabetes/data/statistics-report/index.html
  2. Galicia-GarciaU. Benito-VicenteA. JebariS. Pathophysiology of type 2 diabetes mellitus.Int. J. Mol. Sci.20202117627510.3390/ijms21176275 32872570
    [Google Scholar]
  3. SaiyedN.S. YagoubU. Al QahtaniB. Risk factors of microvascular complications among type 2 diabetic patients using cox proportional hazards models: A cohort study in Tabuk Saudi Arabia.J. Multidiscip. Healthc.2022151619163210.2147/JMDH.S367241 35923155
    [Google Scholar]
  4. SanchesJ.M. ZhaoL.N. SalehiA. WollheimC.B. KaldisP. Pathophysiology of type 2 diabetes and the impact of altered metabolic interorgan crosstalk.FEBS J.2023290362064810.1111/febs.16306 34847289
    [Google Scholar]
  5. SonJ. AcciliD. Reversing pancreatic β-cell dedifferentiation in the treatment of type 2 diabetes.Exp. Mol. Med.20235581652165810.1038/s12276‑023‑01043‑8 37524865
    [Google Scholar]
  6. CaturanoA. D’AngeloM. MormoneA. Oxidative stress in type 2 diabetes: Impacts from pathogenesis to lifestyle modifications.Curr. Issues Mol. Biol.20234586651666610.3390/cimb45080420 37623239
    [Google Scholar]
  7. DludlaP.V. MabhidaS.E. ZiqubuK. Pancreatic β-cell dysfunction in type 2 diabetes: Implications of inflammation and oxidative stress.World J. Diabetes202314313014610.4239/wjd.v14.i3.130 37035220
    [Google Scholar]
  8. ElSayedN.A. AleppoG. BannuruR.R. 9. Pharmacologic approaches to glycemic treatment: Standards of care in diabetes—2024.Diabetes Care202447Suppl. 1S158S17810.2337/dc24‑S009
    [Google Scholar]
  9. McCarthyM.I. Painting a new picture of personalised medicine for diabetes.Diabetologia201760579379910.1007/s00125‑017‑4210‑x 28175964
    [Google Scholar]
  10. SugandhF.N.U. ChandioM. RaveenaF.N.U. Advances in the management of diabetes mellitus: A focus on personalized medicine.Cureus2023158e4369710.7759/cureus.43697 37724233
    [Google Scholar]
  11. AliO. Genetics of type 2 diabetes.World J. Diabetes20134411412310.4239/wjd.v4.i4.114 23961321
    [Google Scholar]
  12. DawedA.Y. ZhouK. van LeeuwenN. Variation in the plasma membrane monoamine transporter (PMAT) (encoded by SLC29A4) and organic cation transporter 1 (OCT1) (encoded by SLC22A1) and gastrointestinal intolerance to metformin in type 2 diabetes: An IMI DIRECT study.Diabetes Care20194261027103310.2337/dc18‑2182 30885951
    [Google Scholar]
  13. RenaG. HardieD.G. PearsonE.R. The mechanisms of action of metformin.Diabetologia20176091577158510.1007/s00125‑017‑4342‑z 28776086
    [Google Scholar]
  14. WuT. HorowitzM. RaynerC.K. New insights into the anti-diabetic actions of metformin: From the liver to the gut.Expert Rev. Gastroenterol. Hepatol.201711215716610.1080/17474124.2017.1273769 27983877
    [Google Scholar]
  15. HundalH.S. RamlalT. ReyesR. LeiterL.A. KlipA. Cellular mechanism of metformin action involves glucose transporter translocation from an intracellular pool to the plasma membrane in L6 muscle cells.Endocrinology199213131165117310.1210/endo.131.3.1505458 1505458
    [Google Scholar]
  16. YeeS.W. ChenL. GiacominiK.M. The role of ATM in response to metformin treatment and activation of AMPK.Nat. Genet.201244435936010.1038/ng.2236 22456732
    [Google Scholar]
  17. ZhouK. BellenguezC. SutherlandC. The role of ATM in response to metformin treatment and activation of AMPK.Nat. Genet.201244436136210.1038/ng.2234 22456734
    [Google Scholar]
  18. KoepsellH. Update on drug-drug interaction at organic cation transporters: Mechanisms, clinical impact, and proposal for advanced in vitro testing.Expert Opin. Drug Metab. Toxicol.202117663565310.1080/17425255.2021.1915284 33896325
    [Google Scholar]
  19. Szymczak-PajorI. WenclewskaS. ŚliwińskaA. Metabolic action of metformin.Pharmaceuticals202215781010.3390/ph15070810 35890109
    [Google Scholar]
  20. MoonS.J. OhJ. LeeS.H. ChoiY. YuK.S. ChungJ.Y. Effect of plasma membrane monoamine transporter genetic variants on pharmacokinetics of metformin in humans.Transl. Clin. Pharmacol.2018262798510.12793/tcp.2018.26.2.79 32055553
    [Google Scholar]
  21. MoeezS. KhalidS. ShaeenS. Clinically significant findings of high-risk mutations in human SLC29A4 gene associated with diabetes mellitus type 2 in Pakistani population.J. Biomol. Struct. Dyn.20224023126601267310.1080/07391102.2021.1975561 34551672
    [Google Scholar]
  22. UmamaheswaranG. PraveenR.G. DamodaranS.E. DasA.K. AdithanC. Influence of SLC22A1 rs622342 genetic polymorphism on metformin response in South Indian type 2 diabetes mellitus patients.Clin. Exp. Med.201515451151710.1007/s10238‑014‑0322‑5 25492374
    [Google Scholar]
  23. XiaoD. GuoY. LiX. The impacts of SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms on metformin therapeutic efficacy in Chinese type 2 diabetes patients.Int. J. Endocrinol.201620161710.1155/2016/4350712 26977146
    [Google Scholar]
  24. ZaharenkoL. KalninaI. GeldnereK. Single nucleotide polymorphisms in the intergenic region between metformin transporter OCT2 and OCT3 coding genes are associated with short-term response to metformin monotherapy in type 2 diabetes mellitus patients.Eur. J. Endocrinol.2016175653154010.1530/EJE‑16‑0347 27609360
    [Google Scholar]
  25. HouW. ZhangD. LuW. Polymorphism of organic cation transporter 2 improves glucose-lowering effect of metformin via influencing its pharmacokinetics in Chinese type 2 diabetic patients.Mol. Diagn. Ther.2015191253310.1007/s40291‑014‑0126‑z 25573751
    [Google Scholar]
  26. TzvetkovM.V. VormfeldeS.V. BalenD. The effects of genetic polymorphisms in the organic cation transporters OCT1, OCT2, and OCT3 on the renal clearance of metformin.Clin. Pharmacol. Ther.200986329930610.1038/clpt.2009.92 19536068
    [Google Scholar]
  27. Reséndiz-AbarcaC.A. Flores-AlfaroE. Suárez-SánchezF. Altered glycemic control associated with polymorphisms in the SLC22A1 (OCT1) gene in a mexican population with type 2 diabetes mellitus treated with metformin: A cohort study.J. Clin. Pharmacol.201959101384139010.1002/jcph.1425 31012983
    [Google Scholar]
  28. PhaniN.M. VohraM. KakarA. Implication of critical pharmacokinetic gene variants on therapeutic response to metformin in type 2 diabetes.Pharmacogenomics2018191190591110.2217/pgs‑2018‑0041 29914345
    [Google Scholar]
  29. MoeezS. RiazS. MasoodN. Evaluation of the rs3088442 G>A SLC22A3 gene polymorphism and the role of microRNA 147 in groups of adult Pakistani populations with type 2 diabetes in response to metformin.Can. J. Diabetes2019432128135.e310.1016/j.jcjd.2018.07.001 30297296
    [Google Scholar]
  30. MousaviS. KohanL. YavarianM. HabibA. Pharmacogenetic variation of SLC47A1 gene and metformin response in type2 diabetes patients.Mol. Biol. Res. Commun.2017629194 28775995
    [Google Scholar]
  31. LiangH. XuW. ZhouL. YangW. WengJ. Differential increments of basal glucagon‐like‐1 peptide concentration among SLC 47A1 rs2289669 genotypes were associated with inter‐individual variability in glycaemic response to metformin in Chinese people with newly diagnosed Type 2 diabetes.Diabet. Med.201734798799210.1111/dme.13351 28321905
    [Google Scholar]
  32. StockerS.L. MorrisseyK.M. YeeS.W. The effect of novel promoter variants in MATE1 and MATE2 on the pharmacokinetics and pharmacodynamics of metformin.Clin. Pharmacol. Ther.201393218619410.1038/clpt.2012.210 23267855
    [Google Scholar]
  33. FlemmerM. ScottJ. Mechanism of action of thiazolidinediones.Curr. Opin. Investig. Drugs200121115641567 11763158
    [Google Scholar]
  34. SinghG. CanA.S. CorreaR. Pioglitazone.Treasure Island, FLStatPearls2024
    [Google Scholar]
  35. DivakaruniA.S. WileyS.E. RogersG.W. Thiazolidinediones are acute, specific inhibitors of the mitochondrial pyruvate carrier.Proc. Natl. Acad. Sci. USA2013110145422542710.1073/pnas.1303360110 23513224
    [Google Scholar]
  36. DawedA.Y. DonnellyL. TavendaleR. CYP2C8 and SLCO1B1 variants and therapeutic response to thiazolidinediones in patients with type 2 diabetes.Diabetes Care201639111902190810.2337/dc15‑2464 27271184
    [Google Scholar]
  37. KalliokoskiA. NeuvonenM. NeuvonenP.J. NiemiM. No significant effect of SLCO1B1 polymorphism on the pharmacokinetics of rosiglitazone and pioglitazone.Br. J. Clin. Pharmacol.2008651788610.1111/j.1365‑2125.2007.02986.x 17635496
    [Google Scholar]
  38. HsiehM.C. LinK.D. TienK.J. Common polymorphisms of the peroxisome proliferator-activated receptor–γ (Pro12Ala) and peroxisome proliferator-activated receptor–γ coactivator–1 (Gly482Ser) and the response to pioglitazone in Chinese patients with type 2 diabetes mellitus.Metabolism20105981139114410.1016/j.metabol.2009.10.030 20045142
    [Google Scholar]
  39. PriyaS.S. SankaranR. RamalingamS. SairamT. SomasundaramL.S. Genotype phenotype correlation of genetic polymorphism of PPAR gamma gene and therapeutic response to pioglitazone in type 2 diabetes mellitus- a pilot study.J. Clin. Diagn. Res.2016102FC11FC1410.7860/JCDR/2016/16494.7331 27042481
    [Google Scholar]
  40. ProksP. ReimannF. GreenN. GribbleF. AshcroftF. Sulfonylurea stimulation of insulin secretion.Diabetes200251Suppl. 3S368S37610.2337/diabetes.51.2007.S368 12475777
    [Google Scholar]
  41. FengY. MaoG. RenX. Ser1369Ala variant in sulfonylurea receptor gene ABCC8 is associated with antidiabetic efficacy of gliclazide in Chinese type 2 diabetic patients.Diabetes Care200831101939194410.2337/dc07‑2248 18599530
    [Google Scholar]
  42. NikolacN. SimundicA.M. KatalinicD. TopicE. CipakA. Zjacic RotkvicV. Metabolic control in type 2 diabetes is associated with sulfonylurea receptor-1 (SUR-1) but not with KCNJ11 polymorphisms.Arch. Med. Res.200940538739210.1016/j.arcmed.2009.06.006 19766903
    [Google Scholar]
  43. JavorskyM. KlimcakovaL. SchronerZ. KCNJ11 gene E23K variant and therapeutic response to sulfonylureas.Eur. J. Intern. Med.201223324524910.1016/j.ejim.2011.10.018 22385882
    [Google Scholar]
  44. LiY. The KCNJ11 E23K gene polymorphism and type 2 diabetes mellitus in the Chinese Han population: A meta-analysis of 6,109 subjects.Mol. Biol. Rep.201340114114610.1007/s11033‑012‑2042‑9 23054005
    [Google Scholar]
  45. RagiaG. TavridouA. PetridisI. ManolopoulosV.G. Association of KCNJ11 E23K gene polymorphism with hypoglycemia in sulfonylurea-treated Type 2 diabetic patients.Diabetes Res. Clin. Pract.201298111912410.1016/j.diabres.2012.04.017 22591706
    [Google Scholar]
  46. HolsteinA. HahnM. StumvollM. KovacsP. The E23K variant of KCNJ11 and the risk for severe sulfonylurea-induced hypoglycemia in patients with type 2 diabetes.Horm. Metab. Res.200941538739010.1055/s‑0029‑1192019 19214942
    [Google Scholar]
  47. DawedA.Y. YeeS.W. ZhouK. Genome-wide meta-analysis identifies genetic variants associated with glycemic response to sulfonylureas.Diabetes Care202144122673268210.2337/dc21‑1152 34607834
    [Google Scholar]
  48. Díaz-GarcíaJ.D. Leyva-LeyvaM. Sánchez-AguillónF. Association study of CACNA1D, KCNJ11, KCNQ1, and CACNA1E single-nucleotide polymorphisms with type 2 diabetes mellitus.Int. J. Mol. Sci.20242517919610.3390/ijms25179196 39273144
    [Google Scholar]
  49. SchronerZ. DobrikovaM. KlimcakovaL. Variation in KCNQ1 is associated with therapeutic response to sulphonylureas.Med. Sci. Monit.2011177CR392CR39610.12659/MSM.881850 21709633
    [Google Scholar]
  50. SeeringerA. ParmarS. FischerA. Genetic variants of the insulin receptor substrate‐1 are influencing the therapeutic efficacy of oral antidiabetics.Diabetes Obes. Metab.201012121106111210.1111/j.1463‑1326.2010.01301.x 20977583
    [Google Scholar]
  51. YuM. XuX-J. YinJ-Y. KCNJ11 Lys23Glu and TCF7L2 rs290487(C/T) polymorphisms affect therapeutic efficacy of repaglinide in Chinese patients with type 2 diabetes.Clin. Pharmacol. Ther.201087333033510.1038/clpt.2009.242 20054294
    [Google Scholar]
  52. BlackC. DonnellyP. McIntyreL. RoyleP. ShepherdJ.J. ThomasS. Meglitinide analogues for type 2 diabetes mellitus.Cochrane Libr.200720101CD00465410.1002/14651858.CD004654.pub2 17443551
    [Google Scholar]
  53. ZhouX. ChenC. YinD. A variation in the ABCC8 gene is associated with type 2 diabetes mellitus and repaglinide efficacy in chinese type 2 diabetes mellitus patients.Intern. Med.201958162341234710.2169/internalmedicine.2133‑18 31118371
    [Google Scholar]
  54. HeY. ZhangR. ShaoX. Association of KCNJ11 and ABCC8 genetic polymorphisms with response to repaglinide in Chinese diabetic patients.Acta Pharmacol. Sin.200829898398910.1111/j.1745‑7254.2008.00840.x 18664331
    [Google Scholar]
  55. DaiX.P. HuangQ. YinJ.Y. KCNQ1 gene polymorphisms are associated with the therapeutic efficacy of repaglinide in C hinese T ype 2 diabetic patients.Clin. Exp. Pharmacol. Physiol.201239546246810.1111/j.1440‑1681.2012.05701.x 22414228
    [Google Scholar]
  56. ZhouX. ZhuJ. BaoZ. A variation in KCNQ1 gene is associated with repaglinide efficacy on insulin resistance in Chinese type 2 diabetes mellitus patients.Sci. Rep.2016613729310.1038/srep37293 27857189
    [Google Scholar]
  57. SinghS. UsmanK. BanerjeeM. Pharmacogenetic studies update in type 2 diabetes mellitus.World J. Diabetes201671530231510.4239/wjd.v7.i15.302 27555891
    [Google Scholar]
  58. CornellS. A review of GLP-1 receptor agonists in type 2 diabetes: A focus on the mechanism of action of once-weekly agents.J. Clin. Pharm. Ther.202045Suppl. 1172710.1111/jcpt.13230
    [Google Scholar]
  59. DawedA.Y. MariA. BrownA. Pharmacogenomics of GLP-1 receptor agonists: A genome-wide analysis of observational data and large randomised controlled trials.Lancet Diabetes Endocrinol.2023111334110.1016/S2213‑8587(22)00340‑0 36528349
    [Google Scholar]
  60. SathananthanA. ManC.D. MichelettoF. Common genetic variation in GLP1R and insulin secretion in response to exogenous GLP-1 in nondiabetic subjects: A pilot study.Diabetes Care20103392074207610.2337/dc10‑0200 20805279
    [Google Scholar]
  61. de LuisD.A. Diaz SotoG. IzaolaO. RomeroE. Evaluation of weight loss and metabolic changes in diabetic patients treated with liraglutide, effect of RS 6923761 gene variant of glucagon-like peptide 1 receptor.J. Diabetes Complications201529459559810.1016/j.jdiacomp.2015.02.010 25825013
    [Google Scholar]
  62. KlenJ. DolžanV. Glucagon-like peptide-1 receptor agonists in the management of type 2 diabetes mellitus and obesity: The impact of pharmacological properties and genetic factors.Int. J. Mol. Sci.2022237345110.3390/ijms23073451 35408810
    [Google Scholar]
  63. KIM Y AN. 1479-P: Targeted exome sequencing for longterm efficacy and weight loss of dulaglutide in type 2 diabetes. Diabetes 2023; 72(Supplement_1).
  64. AndersenE.S. DeaconC.F. HolstJ.J. Do we know the true mechanism of action of the DPP ‐4 inhibitors?Diabetes Obes. Metab.2018201344110.1111/dom.13018 28544214
    [Google Scholar]
  65. VellaA. Mechanism of action of DPP-4 inhibitors--new insights.J. Clin. Endocrinol. Metab.20129782626262810.1210/jc.2012‑2396 22869847
    [Google Scholar]
  66. ŰrgeováA. JavorskýM. KlimčákováL. Genetic variants associated with glycemic response to treatment with dipeptidylpeptidase 4 inhibitors.Pharmacogenomics202021531732310.2217/pgs‑2019‑0147 32308134
    [Google Scholar]
  67. JavorskýM. GotthardováI. KlimčákováL. A missense variant inGLP1R gene is associated with the glycaemic response to treatment with gliptins.Diabetes Obes. Metab.201618994194410.1111/dom.12682 27160388
    [Google Scholar]
  68. HanE. ParkH.S. KwonO. A genetic variant in GLP1R is associated with response to DPP-4 inhibitors in patients with type 2 diabetes.Medicine20169544e515510.1097/MD.0000000000005155 27858848
    [Google Scholar]
  69. JamaluddinJ.L. HuriH.Z. VethakkanS.R. Clinical and genetic predictors of dipeptidyl peptidase-4 inhibitor treatment response in Type 2 diabetes mellitus.Pharmacogenomics201617886788110.2217/pgs‑2016‑0010 27249660
    [Google Scholar]
  70. GotthardováI. JavorskýM. KlimčákováL. KCNQ1 gene polymorphism is associated with glycaemic response to treatment with DPP-4 inhibitors.Diabetes Res. Clin. Pract.201713014214710.1016/j.diabres.2017.05.018 28624668
    [Google Scholar]
  71. ZimdahlH. IttrichC. Graefe-ModyU. Influence of TCF7L2 gene variants on the therapeutic response to the dipeptidylpeptidase-4 inhibitor linagliptin.Diabetologia20145791869187510.1007/s00125‑014‑3276‑y 24906949
    [Google Scholar]
  72. LiaoW.L. LeeW.J. ChenC.C. Pharmacogenetics of dipeptidyl peptidase 4 inhibitors in a Taiwanese population with type 2 diabetes.Oncotarget2017811180501805810.18632/oncotarget.14951 28160554
    [Google Scholar]
  73. FaruquiA.A. Can DPP-4 enhibitors and SGLT-2 inhibitors pleotropic effects be extended to treat diabetic nephropathy?J. Med. (Dhaka)2023241434910.3329/jom.v24i1.64903
    [Google Scholar]
  74. KułakK.B. Chamera-CyrekK. JanikI. SGLT-2 inhibitors in heart failure: A literature review on mechanisms, efficacy and safety.Quality in Sport2024155208310.12775/QS.2024.15.52083
    [Google Scholar]
  75. ZimdahlH. HauptA. BrendelM. Influence of common polymorphisms in the SLC5A2 gene on metabolic traits in subjects at increased risk of diabetes and on response to empagliflozin treatment in patients with diabetes.Pharmacogenet. Genomics201727413514210.1097/FPC.0000000000000268 28134748
    [Google Scholar]
  76. FranckeS. MamidiR.N.V.S. SolankiB. In vitro metabolism of canagliflozin in human liver, kidney, intestine microsomes, and recombinant uridine diphosphate glucuronosyltransferases (UGT) and the effect of genetic variability of UGT enzymes on the pharmacokinetics of canagliflozin in humans.J. Clin. Pharmacol.20155591061107210.1002/jcph.506 25827774
    [Google Scholar]
  77. VenkatachalapathyP. PadhilahouseS. SellappanM. Pharmacogenomics and personalized medicine in type 2 diabetes mellitus: Potential implications for clinical practice.Pharm. Genomics Pers. Med.2021141441145510.2147/PGPM.S329787 34803393
    [Google Scholar]
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