Trends and challenges in managing diabetes mellitus-personalized medicine
Keywords:
Diabetes Mellitus, Personalized Medicine, Pharmacogenomics, Genetic Research, Type 1 Diabetes, Type 2 Diabetes, MODY, NDM, GWASAbstract
Background: Diabetes Mellitus (DM) is a major global health issue, contributing to significant morbidity, mortality, and economic burden. The World Health Organization reported an increase in DM diagnoses, with 422 million adults affected globally by 2014. Despite a decline in newly diagnosed cases in the U.S., DM remains prevalent, significantly impacting cardiovascular health and incurring substantial healthcare costs. Aim: This article aims to explore the trends and challenges in managing DM through personalized medicine, focusing on genetic insights and pharmacogenomics to improve treatment strategies. Methods: The review encompasses recent advancements in genetic research and pharmacogenomics relevant to DM. It discusses the genetic underpinnings of both Type 1 and Type 2 DM, including monogenic forms like MODY and NDM. Various methodologies, such as genome-wide association studies (GWAS) and candidate gene studies, are evaluated for their contributions to understanding DM susceptibility and treatment responses. Results: The findings highlight significant progress in identifying genetic variants associated with DM risk and treatment response. Key genes, including TCF7L2, KCNJ11, and PPAR-γ, have been implicated in susceptibility and drug response. Monogenic forms like MODY and NDM present distinct genetic profiles that necessitate tailored treatment approaches.
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References
World Health Organization. Diabetes: Key Facts, November 2016. Available from www.who.int/mediacentre/factsheets/fs312/en/. Accessed February 13, 2017.
World Health Organization. Diabetes: Global report on diabetes. Available from www.who.int/diabetes/global-report/en/. Accessed February 13, 2017.
Centers for Disease Control and Prevention. Chronic Disease Prevention and Health Promotion: Diabetes, July 2016. Available from www.cdc.gov/chronicdisease/resources/publications/aag/diabetes.htm. Accessed February 13 2017.
American Diabetes Association. Economic costs of diabetes in the U.S. in 2012. Diabetes Care 2013; 36: 1033–46. DOI: https://doi.org/10.2337/dc12-2625
American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2016; 39: S1–106.
Barroso I. Genetics of type 2 diabetes. Diabet Med 2005; 22: 517–35. DOI: https://doi.org/10.1111/j.1464-5491.2005.01550.x
Hupfeld CJ, Courtney H, Olefsky JM. Type 2 diabetes mellitus: etiology, pathogenesis, and natural history. In: JL Jameson, LJ De Groot, eds. Endocrinology: adult and pediatric. Philadelphia, PA: Elsevier Health Sciences, 2010: 765–87. DOI: https://doi.org/10.1016/B978-1-4160-5583-9.00041-1
Carmody D, Naylor RN, Bell CD, et al. GCK-MODY in the US National Monogenic Diabetes Registry: frequently misdiagnosed and unnecessarily treated. Acta Diabetol 2016; 53: 703–8. DOI: https://doi.org/10.1007/s00592-016-0859-8
Tan JT, Chia KS, Ku CS. The molecular genetics of type 2 diabetes: past, present and future. In: Encyclopedia of life sciences. Chichester, UK: John Wiley & Sons, 2009. doi: 10.1002/9780470015902.a0021994. DOI: https://doi.org/10.1002/9780470015902.a0021994
Denny JC, Ritchie MD, Basford MA, et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations. Bioinformatics 2010; 26: 1205–10. DOI: https://doi.org/10.1093/bioinformatics/btq126
Brunetti A, Chiefari E, FTI D. Recent advances in the molecular genetics of type 2 diabetes mellitus. World J Diabetes 2014; 5: 128–40. DOI: https://doi.org/10.4239/wjd.v5.i2.128
Owen KR, McCarthy MI. Genetics of type 2 diabetes. Curr Opin Genet Dev 2007; 17: 239–44. DOI: https://doi.org/10.1016/j.gde.2007.04.003
Doria A, Patti M-E, Kahn CR. The emerging genetic architecture of type 2 diabetes. Cell Metab 2008; 8: 186–200. DOI: https://doi.org/10.1016/j.cmet.2008.08.006
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. DOI: https://doi.org/10.1038/ng.2383
The Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447: 661–78.
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. DOI: https://doi.org/10.1038/ng1732
Fuchsberger C, Flannick J, Teslovich TM, et al. The genetic architecture of type 2 diabetes. Nature 2016; 536: 41–7. DOI: https://doi.org/10.1038/nature18642
GWAS Catalog. The NHGRI-EBI catalog of published genome-wide association studies, February 2017. Available from www.ebi.ac.uk/gwas/. Accessed February 13, 2017.
Bonnefond A, Froguel P. Rare and common genetic events in type 2 diabetes: what should biologists know? Cell Metab 2015; 21: 357–68. DOI: https://doi.org/10.1016/j.cmet.2014.12.020
Vaxillaire M, Froguel P. Genetic basis of maturity-onset diabetes of the young. Endocrinol Metab Clin North Am 2006; 35: 371–84. DOI: https://doi.org/10.1016/j.ecl.2006.02.009
Chambers C, Fouts A, Dong F, et al. Characteristics of maturity onset diabetes of the young in a large diabetes center. Pediatr Diabetes 2016; 17: 360–7. DOI: https://doi.org/10.1111/pedi.12289
Pihoker C, Gilliam LK, Ellard S, et al. Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for Diabetes in Youth. J Clin Endocrinol Metab 2013; 98: 4055–62. DOI: https://doi.org/10.1210/jc.2013-1279
Rubio-Cabezas O, Hattersley AT, Njølstad PR, et al. ISPAD Clinical Practice Consensus Guidelines 2014. The diagnosis and management of monogenic diabetes in children and adolescents. Pediatr Diabetes 2014; 15(Suppl 20): 47–64. DOI: https://doi.org/10.1111/pedi.12192
Babenko AP, Polak M, Cave H, et al. Activating mutations in the ABCC8 gene in neonatal diabetes mellitus. N Engl J Med 2006; 355: 456–66. DOI: https://doi.org/10.1056/NEJMoa055068
Gloyn AL, Pearson ER, Antcliff JF, et al. Activating mutations in the gene encoding the ATP-sensitive potassium-channel subunit Kir6.2 and permanent neonatal diabetes. N Engl J Med 2004; 350: 1838–49. DOI: https://doi.org/10.1056/NEJMoa032922
Colombo C, Delvecchio M, Zecchins C, et al. Transient neonatal diabetes mellitus is associated with a recurrent (R201H) KCNJ11 (KIR6.2) mutation. Diabetologia 2005; 48: 2439–41. DOI: https://doi.org/10.1007/s00125-005-1958-1
Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Pharmacologic management of type 2 diabetes: 2016 interim update. Can J Diabetes 2016; 40: 193–5. DOI: https://doi.org/10.1016/j.jcjd.2016.02.006
Gong L, Goswami S, Giacomini KM, Altman RB, Klein TE. Metformin pathways: pharmacokinetics and pharmacodynamics. Pharmacogenet Genomics 2012; 22: 820–7. DOI: https://doi.org/10.1097/FPC.0b013e3283559b22
Zhou G, Myers R, Li Y, et al. Role of AMP-activated protein kinase in mechanism of metformin action. J Clin Invest 2001; 108: 1167–74. DOI: https://doi.org/10.1172/JCI13505
Pawlyk AC, Giacomini KM, McKeon C, Shuldiner AR, Florez JC. Metformin pharmacogenomics: current status and future directions. Diabetes 2014; 63: 2590–9. DOI: https://doi.org/10.2337/db13-1367
Kahn SE, Haffner SM, Heise MA, et al. Glycemic durability of rosiglitazone, metformin, or glyburide monotherapy. N Engl J Med 2006; 355: 2427–43. DOI: https://doi.org/10.1056/NEJMoa066224
Riedel AA, Heien H, Wogen J, Plauschinat CA. Loss of glycemic control in patients with type 2 diabetes mellitus who were receiving initial metformin, sulfonylurea, or thiazolidinedione monotherapy. Pharmacotherapy 2007; 27: 1102–10. DOI: https://doi.org/10.1592/phco.27.8.1102
Jablonski KA, McAteer JB, De Bakker PIW, 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. DOI: https://doi.org/10.2337/db10-0543
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. DOI: https://doi.org/10.1172/JCI30558
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. DOI: https://doi.org/10.2337/db08-0896
Becker ML, Pearson ER, Tkáč I. Pharmacogenetics of oral antidiabetic drugs. Int J Endocrinol 2013; 2013: Article ID 686315. doi: 10.1155/2013/686315. DOI: https://doi.org/10.1155/2013/686315
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. DOI: https://doi.org/10.1007/s00125-012-2537-x
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. DOI: https://doi.org/10.1097/FPC.0b013e32832cc7e9
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. DOI: https://doi.org/10.1038/ng.735
Florez JC, Barrett-Connor E, Jablonski KA, et al. The C allele of ATM rs11212617 does not associate with metformin response in the diabetes prevention program. Diabetes Care 2012; 35: 1864–7. DOI: https://doi.org/10.2337/dc11-2301
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. DOI: https://doi.org/10.1038/clpt.2009.176
Ragia G, Petridis I, Tavridou A, Christakidis D, Manolopoulos VG. Presence of CYP2C9*3 allele increases risk for hypoglycemia in type 2 diabetic patients treated with sulfonylureas. Pharmacogenomics 2009; 10: 1781–7. DOI: https://doi.org/10.2217/pgs.09.96
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. DOI: https://doi.org/10.1111/j.1365-2125.2005.02379.x
Holstein A, Hahn M, Patzer O, Seeringer A, Kovacs P, Stingl J. Impact of clinical factors and CYP2C9 variants for the risk of severe sulfonylurea-induced hypoglycemia. Eur J Clin Pharmacol 2011; 67: 471–6. DOI: https://doi.org/10.1007/s00228-010-0976-1
Feng Y, Mao G, Ren X, et al. Ser 1369Ala 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. DOI: https://doi.org/10.2337/dc07-2248
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. DOI: https://doi.org/10.2337/db06-0966
Holstein JD, Kovacs P, Patzer O, Stumvoll M, Holstein A. The Ser1369Ala variant of ABCC8 and the risk for severe sulfonylurea-induced hypoglycemia in German patients with type 2 diabetes. Pharmacogenomics 2012; 13: 5–10. DOI: https://doi.org/10.2217/pgs.11.150
Pearson ER, Donnelly LA, Kimber C, et al. Variation in TCF7L2 influences therapeutic response to sulfonylureas: a GoDARTs study. Diabetes 2007; 56: 2178–82. DOI: https://doi.org/10.2337/db07-0440
Holstein A, Hahn M, Korner A, Stumvoll M, Kovacs P. TCF7L2 and therapeutic response to sulfonylureas in patients with type 2 diabetes. BMC Med Genet 2011; 12: 30. DOI: https://doi.org/10.1186/1471-2350-12-30
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. DOI: https://doi.org/10.1016/j.clpt.2005.04.013
Dawed AY, Donnelly L, Tavendale R, et al. CYP2C8 and SLCO1B1 variants and therapeutic response to thiazolidinediones in patients with type 2 diabetes. Diabetes Care 2016; 39: 1902–8. DOI: https://doi.org/10.2337/dc15-2464
Kang ES, Park SY, Kim HJ, 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: https://doi.org/10.2337/diacare.28.5.1139
Morris AD, Boyle DI, MacAlpine R, et al. The diabetes audit and research in Tayside Scotland (DARTS) study: electronic record linkage to create a diabetes register. DARTS/MEMO Collaboration. BMJ 1997; 315: 524–8. DOI: https://doi.org/10.1136/bmj.315.7107.524
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. DOI: https://doi.org/10.1038/sj.clpt.6100275
American Diabetes Association. 7. Approaches to glycemic treatment. Diabetes Care 2016; 39(Suppl 1): S52–9. DOI: https://doi.org/10.2337/dc16-S010
DeFronzo RA. Pharmacologic therapy for type 2 diabetes mellitus. Ann Intern Med 1999; 131: 281–303. DOI: https://doi.org/10.7326/0003-4819-131-4-199908170-00008
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. DOI: https://doi.org/10.1586/erc.09.154
Kirchheiner J, Roots I, Goldammer M, Rosenkranz B, Brockmoller J. 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. DOI: https://doi.org/10.2165/00003088-200544120-00002
Group UKPDS. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes. Lancet 1998; 352: 837–53. DOI: https://doi.org/10.1016/S0140-6736(98)07019-6
Schopman J, Simon A, Hoefnagel S, Hoekstra J, Scholten R, Holleman F. The incidence of mild and severe hypoglycaemia in patients with type 2 diabetes mellitus treated with sulfonylureas: a systematic review and meta-analysis. Diabetes Metab Res Rev 2014; 30: 11–22. DOI: https://doi.org/10.1002/dmrr.2470
Li Q, Chen M, Zhang R, et al. KCNJ11 E23K variant is associated with the therapeutic effect of sulphonylureas in Chinese type 2 diabetic patients. Clin Exp Pharmacol Physiol 2014; 41: 748–54. DOI: https://doi.org/10.1111/1440-1681.12280
Hamming KSC, 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. DOI: https://doi.org/10.2337/db09-0143
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. DOI: https://doi.org/10.1016/j.ejim.2011.10.018
Sesti G, Laratta E, Cardellini M, et al. The E23K Variant of KCNJ11 encoding the pancreatic β-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: https://doi.org/10.1210/jc.2005-2323
Kimber CH, Doney AS, Pearson ER, et al. TCF7L2 in the Go-DARTS study: evidence for a gene dose effect on both diabetes susceptibility and control of glucose levels. Diabetologia 2007; 50: 1186–91. DOI: https://doi.org/10.1007/s00125-007-0661-9
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. DOI: https://doi.org/10.2337/diacare.27.6.1394
Prudente S, Morini E, Lucchesi D, et al. IRS1 G972R missense polymorphism is associated with failure to oral antidiabetes drugs in white patients with type 2 diabetes from Italy. Diabetes 2014; 63: 3135–40. DOI: https://doi.org/10.2337/db13-1966
van Leeuwen N, Swen JJ, Guchelaar HJ, 't Hart LM. The role of pharmacogenetics in drug disposition and response of oral glucose-lowering drugs. Clin Pharmacokinet 2013; 52: 833–54. DOI: https://doi.org/10.1007/s40262-013-0076-3
Della-Morte D, Palmirotta R, Rehni AK, et al. Pharmacogenomics and pharmacogenetics of thiazolidinediones: role in diabetes and cardiovascular risk factors. Pharmacogenomics 2014; 15: 2063–82. DOI: https://doi.org/10.2217/pgs.14.162
Aquilante CL, Zhang W, McCollum M. Race, ethnicity, and use of thiazolidinediones among US adults with diabetes. Curr Med Res Opin 2007; 23: 489–94. DOI: https://doi.org/10.1185/030079906X167354
Aquilante CL, Bushman LR, Knutsen SD, Burt LE, Rome LC, Kosmiski LA. Influence of SLCO1B1 and CYP2C8 gene polymorphisms on rosiglitazone pharmacokinetics in healthy volunteers. Hum Genomics 2008; 3: 7–16. DOI: https://doi.org/10.1186/1479-7364-3-1-7
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. DOI: https://doi.org/10.1016/j.clpt.2006.09.008
Gouda HN, Sagoo GS, Harding A-H, Yates J, Sandhu MS, Higgins JPT. The association between the peroxisome proliferator-activated receptor-gamma2 (PPARG2) Pro12Ala gene variant and type 2 diabetes mellitus: a HuGE review and meta-analysis. Am J Epidemiol 2010; 171: 645–55. DOI: https://doi.org/10.1093/aje/kwp450
Aquilante CL. Pharmacogenetics of thiazolidinedione therapy. Pharmacogenomics 2007; 8: 917–31. DOI: https://doi.org/10.2217/14622416.8.8.917
Bluher M, Lubben G, Paschke R. Analysis of the relationship between the Pro12Ala variant in the PPAR-gamma2 gene and the response rate to therapy with pioglitazone in patients with type 2 diabetes. Diabetes Care 2003; 26: 825–31. DOI: https://doi.org/10.2337/diacare.26.3.825
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. DOI: https://doi.org/10.1016/j.metabol.2009.10.030
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. DOI: https://doi.org/10.2337/dc05-2466
Bailey SD, Xie C, Do R, et al. Variation at the NFATC2 locus increases the risk of thiazolidinedione-induced edema in the Diabetes REduction Assessment with ramipril and rosiglitazone Medication (DREAM) study. Diabetes Care 2010; 33: 2250–3. DOI: https://doi.org/10.2337/dc10-0452
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. DOI: https://doi.org/10.1016/S0140-6736(06)69705-5
Kleinberger JW, Pollin TI. Personalized medicine in diabetes mellitus: current opportunities and future prospects. Ann N Y Acad Sci 2015; 1346: 45–56. DOI: https://doi.org/10.1111/nyas.12757
't Hart LM, Fritsche A, Nijpels G, et al. The CTRB1/2 locus affects diabetes susceptibility and treatment via the incretin pathway. Diabetes 2013; 62: 3275–81. DOI: https://doi.org/10.2337/db13-0227
Nathan DM, Buse JB, Kahn SE, et al. Rationale and design of the glycemia reduction approaches in diabetes: a comparative effectiveness study (GRADE). Diabetes Care 2013; 36: 2254–61. DOI: https://doi.org/10.2337/dc13-0356
Hivert M-F, Jablonski KA, Perreault L, et al. Updated genetic score based on 34 confirmed type 2 diabetes loci is associated with diabetes incidence and regression to normoglycemia in the diabetes prevention program. Diabetes 2011; 60: 1340–8. DOI: https://doi.org/10.2337/db10-1119
Meigs JB, Shrader P, Sullivan LM, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med 2008; 359: 2208–19. DOI: https://doi.org/10.1056/NEJMoa0804742
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