Impact of SLC22A1 rs12208357 on therapeutic response to metformin in type 2 diabetes patients

Tripathi BK, Srivastava AK. Diabetes mellitus: complications and therapeutics. Med Sci Monit. 2006;12(7):130–47.

Google Scholar 

Pawlyk AC, Giacomini KM, McKeon C, Shuldiner AR, Florez JC. Metformin pharmacogenomics: current status and future directions. Diabetes. 2014;63(8):2590–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Triggle C, Ding H. Metformin is not just an antihyperglycaemic drug but also has protective effects on the vascular endothelium. Acta Physiol. 2017;219(1):138–51.

Article  CAS  Google Scholar 

Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, et al. Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Spectr. 2012;25(3):154–71.

Article  Google Scholar 

Peng A, Gong C, Xu Y, Liang X, Chen X, Hong W et al. Association between organic cation transporter genetic polymorphisms and metformin response and intolerance in T2DM individuals: a systematic review and meta-analysis. Front Public Health. 2023;11.

Rena G, Hardie DG, Pearson ER. The mechanisms of action of metformin. Diabetologia. 2017;60(9):1577–85.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cook M, Girman C, Stein P, Alexander C. Initial monotherapy with either metformin or sulphonylureas often fails to achieve or maintain current glycaemic goals in patients with type 2 diabetes in UK primary care. Diabet Med. 2007;24(4):350–8.

Article  CAS  PubMed  Google Scholar 

Gong L, Goswami S, Giacomini KM, Altman RB, Klein TE. Metformin pathways: pharmacokinetics and pharmacodynamics. Pharmacogenet Genomics. 2012;22(11):820.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kimura N, Masuda S, Tanihara Y, Ueo H, Okuda M, Katsura T, et al. Metformin is a superior substrate for renal organic cation transporter OCT2 rather than hepatic OCT1. Drug Metab Pharmacokinet. 2005;20(5):379–86.

Article  CAS  PubMed  Google Scholar 

Florez JC. The pharmacogenetics of metformin. Diabetologia. 2017;60(9):1648–55.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhou K, Donnelly LA, Kimber CH, Donnan PT, Doney AS, Leese G, et al. Reduced-function SLC22A1 polymorphisms encoding organic cation transporter 1 and glycemic response to metformin: a GoDARTS study. Diabetes. 2009;58(6):1434–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Nasykhova YA, Barbitoff YA, Tonyan ZN, Danilova MM, Nevzorov IA, Komandresova TM, et al. Genetic and phenotypic factors affecting glycemic response to metformin therapy in patients with type 2 diabetes mellitus. Genes. 2022;13(8):1310.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Buchan DWA, Minneci F, Nugent TCO, Bryson K, Jones DT. Scalable web services for the PSIPRED Protein Analysis Workbench. Nucleic Acids Res. 2013;41(W1):W349–57.

Article  PubMed  PubMed Central  Google Scholar 

Yachdav G, Kloppmann E, Kajan L, Hecht M, Goldberg T, Hamp T, et al. PredictProtein—an open resource for online prediction of protein structural and functional features. Nucleic Acids Res. 2014;42(W1):W337–43.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sim N-L, Kumar P, Hu J, Henikoff S, Schneider G, Ng PC. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res. 2012;40(W1):W452–7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–9.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tang H, Thomas PD. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation. Bioinformatics. 2016;32(14):2230–2.

Article  CAS  PubMed  Google Scholar 

Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GL, Edwards KJ, et al. Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models. Hum Mutat. 2013;34(1):57–65.

Article  CAS  PubMed  Google Scholar 

Choi Y, Chan AP. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015;31(16):2745–7.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Capriotti E, Calabrese R, Fariselli P, Martelli PL, Altman RB, Casadio R. WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation. BMC Genomics. 2013;14(3):S6.

Article  PubMed  PubMed Central  Google Scholar 

Xu Z, Taylor JA. SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res. 2009;37(suppl2):W600–5.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li B, Krishnan VG, Mort ME, Xin F, Kamati KK, Cooper DN, et al. Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics. 2009;25(21):2744–50.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Capriotti E, Calabrese R, Casadio R. Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics. 2006;22(22):2729–34.

Article  CAS  PubMed  Google Scholar 

Capriotti E, Fariselli P, Casadio R. I-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005;33(suppl2):W306–10.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Cheng J, Randall A, Baldi P. Prediction of protein stability changes for single-site mutations using support vector machines. Proteins Struct Funct Bioinform. 2006;62(4):1125–32.

Article  CAS  Google Scholar 

Fariselli P, Martelli PL, Savojardo C, Casadio R. INPS: predicting the impact of non-synonymous variations on protein stability from sequence. Bioinformatics. 2015;31(17):2816–21.

Article  CAS  PubMed  Google Scholar 

Chen C-W, Lin J, Chu Y-W, editors. iStable: off-the-shelf predictor integration for predicting protein stability changes. BMC bioinformatics; 2013: BioMed Central.

Biasini M, Bienert S, Waterhouse A, Arnold K, Studer G, Schmidt T, et al. SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res. 2014;42(Web Server issue):W252–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res. 2015;44(D1):D1202–13.

Article  PubMed  PubMed Central  Google Scholar 

Law V, Knox C, Djoumbou Y, Jewison T, Guo AC, Liu Y, et al. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 2013;42(D1):D1091–7.

Article  PubMed  PubMed Central  Google Scholar 

Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem. 2009;30(16):2785–91.

Article  CAS  PubMed  PubMed Central 

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