Pharmacogenomic analysis of ATP-sensitive potassium channels coexpressing the common type 2 diabetes risk variants E23K and S1369A. Pharmacogenet Genomics. 2012;22:206-214. [PMID: 22209866 DOI: 10.1097/fpc.0b013e32835001e7]

Dose Dependent Effect of Sulfamethoxazole on Inhibiting KATP Channel of Mouse Pancreatic β Cell

Sulfamethoxazole (SMX) is widely used as an antibiotic in the clinical application with side effects of hypoglycemia. This is because SMX contains the sulfonamide structure, which closes ATP-sensitive potassium (KATP) channels and induces insulin secretion. However, there are no detail reports that measure the effective dose that can close KATP channels and induce insulin secretion. In this study, whole-cell patch clamp recording was utilized to measure the effect of SMX on KATP channel activity on pancreatic β cells. Also, the static incubation assay with mice islets was assessed to measure the insulin secretion capacity of SMX. SMX was shown to inhibit the KATP channel in pancreatic β cell membrane and induce insulin secretion in relatively high concentration. The half maximal inhibitory concentration (IC50) for KATP channel activity of SMX was .46 ± .08 mM. It was also shown that a near IC50 concentration of SMX (.5 mM) was able to nearly fully block the KATP channel when simultaneously applied with low concentration sulfonylurea, tolbutamide (.01 mM). Our present data provide important information for the clinical use of SMX to treat infection in diabetic patients using sulfonylureas.

Association of ABCC8 gene variants with response to sulfonylurea in type 2 diabetes mellitus

Background

Diabetes mellitus (DM) is associated with high blood glucose levels and sulfonylureas (SFUs) are one of the treatment options for DM. SFUs bind to sulfonylurea-1 receptor (SUR1), which is encoded by the ABCC8 gene and leads to blood glucose reduction. Genetic variants like rs757110 and rs1799854 of ABCC8 can influence the response to the drug's efficiency. Therefore, this study aimed to investigate the association between the ABCC8 rs757110 and rs1799854 genetic variants and response to SFUs treatment.

Methods

Totally, 61 DM patients with SFUs treatment were included. Baseline characteristics of the patients were recorded and 5 ml of blood was taken from each patient. After DNA extraction, a sequence containing rs757110 and rs1799854 was synthesized by the PCR method, and the PCR products were used for Sanger sequencing.

Results

Frequencies of GG, GA, and AA genotypes of rs1799854 variant was 12 (40%), 14 (46.7%), and 4 (13.3%), and the frequencies of CC, AC, and AA genotypes for rs757110 variant was 3 (9.7%), 5 (16.1%) and 23 (74.2%) in, respectively. Patients with different genotypes had the same age, BMI (body mass index), initial FBS (Fasting blood sugar), initial HbA1c, treatment duration, gender and history of smoking, alcohol consumption, and exercise. There was no significant difference in FBS and HbA1c changes after SFUs treatment between patients with rs757110 variant (p = 0.39 for FBS and p = 0.76 for HbA1c) and rs1799854 (p = 0.24 for FBS and p = 0.36 for HbA1c).

Conclusion

The rs1799854 and rs757110 variants of the ABCC8 gene had no significant influence on response to SFUs treatment.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus

BACKGROUND

Nateglinide is a meglitinide used for the treatment of type 2 diabetes mellitus. Individual studies demonstrated the association of CYP2C9, SLCO1B1, and MTNR1B variants with the safety and efficacy of nateglinide. The current study aimed to develop a pharmacogenomic algorithm to optimize nateglinide therapy.

METHODS

Multiple linear regression (MLR) and classification and regression tree (CART) were used to develop a pharmacogenomic algorithm for nateglinide dosing based on the published nateglinide pharmacokinetic data on the area under the curve data (AUC) and C_max (n = 143). CYP2C9 metabolizer phenotype, SLCO1B1, MTNR1B genotypes, and CYP2C9 inhibitor usage were used as the input variables. The results and associations were further confirmed by meta-analysis and in silico studies.

RESULTS

The MLR models of AUC and C_max explain 87.4% and 59% variability in nateglinide pharmacokinetics. The Bland and Altman analysis of the nateglinide dose predicted by these two MLR models showed a bias of ± 26.28 mg/meal. The CART algorithm was proposed based on these findings. This model is further justified by the meta-analysis showing increased AUCs in CYP2C9 intermediate metabolizers and SLCOB1 TC and CC genotypes compared to the wild genotypes. The increased AUC in SLCO1B1 mutants is due to decreased binding affinity of nateglinide to the mutant affecting the influx of nateglinide into hepatocytes. MTNR1B rs10830963 G-allele-mediated poor response to nateglinide is attributed to increased transcriptional factor binding causing decreased insulin secretion.

CONCLUSION

CYP2C9, SLCO1B1, and MTNR1B genotyping help in optimizing nateglinide therapy based on this algorithm and ensuring safety and efficacy.

The role of sulfonylureas in the treatment of type 2 diabetes

INTRODUCTION

Type 2 diabetes (T2D) is increasingly prevalent and associated with increased risk for cardiovascular and renal disease. After lifestyle modification, metformin is usually the first-line pharmacotherapy and sulfonylureas are traditionally added after metformin failure. However, with newer glucose lowering drugs that may have less risk of hypoglycemia or that may reduce cardiovascular and renal events, the position of sulfonylureas is being reevaluated.

AREAS COVERED

In this article, the authors review relevant publications related to the use of sulfonylureas.

EXPERT OPINION

Sulfonylureas are potent glucose lowering drugs. The risk of hypoglycemia varies with different drugs within the class and can be minimized by using the safer drugs, possibly in lower doses. Cardiovascular events do not appear to be increased with some of the newer generation drugs. The durability of glycemic control also appears comparable to other newer agents. Sulfonylureas are the preferred treatment for some types of monogenic diabetes and selection of T2D patients who may have greater benefit from sulfonylureas based on certain phenotypes and genotypes is likely to be refined further by precision medicine. Sulfonylureas are inexpensive and readily available everywhere and they are still the most frequently used second-line treatment for T2D in many parts of the world.

Therapeutic Dilemma in personalized medicine

The practice of medicine depends over a long time on identifying therapies that target an entire population. The increase in scientific knowledge over the years has led to the gradual change towards individualization and personalization of drug therapy. The hope of this change is to achieve a better clinical response to given medications and reduction of their adverse effects. Tailoring of medicine on the road of personalized medicine considers molecular and genetic mapping of the individual. However, many factors still impede the smooth application of personalized medicine and represent challenges or limitations in its achievement. In this article, we put some clinical examples that show dilemmas in the application of personalized medicine such as opioids in pain control, fluoropyrimidines in malignancy, clopidogrel as antiplatelet therapy and oral hypoglycemic drugs in Type2 diabetes in adults. Shaping the future of medicine through the application of personalized medicine for a particular patient needs to put into consideration many factors such as patient's genetic makeup and life style, pathology of the disease and dynamic changes in its course as well as interactions between administered drugs and their effects on metabolizing enzymes. We hope in the coming years, the personalized medicine will foster changes in health care system in the way not only to treat patients but also to prevent diseases.

Diabetes: Is There a Future for Pharmacogenomics Guided Treatment?

Diabetes is a disease defined on the basis of hyperglycemia. There are monogenic forms of diabetes where defining the genetic cause has a dramatic impact on treatment—with patients being able to transition from insulin to sulfonylureas. However, the majority of diabetes is type 2 diabetes. This review outlines the robust evidence accrued to date for pharmacogenetics of metformin, sulfonylureas, thiazolidinediones, and dipeptidyl peptidase‐4 inhibitors but highlights that these variants will only be of clinical utility when the genotype is already known at the point of prescribing. The future of pharmacogenetics in diabetes and other common complex disease relies on a paradigm shift—that of preemptive panel genotyping and use of clinical decision support tools to assimilate this genetic information with other clinical phenotypic data and to present this information simply to the prescriber. Given the recent dramatic fall in genotyping costs, this future is not far off.

A computational structural biology study to understand the impact of mutation on structure-function relationship of inward-rectifier potassium ion channel Kir6.2 in human

Type 2 diabetes (T2D) is clinically characterized via hyperglycemia. Polymorphism rs5219 in the KCNJ11 gene is a risk factor for developing T2D in humans. KCNJ11 encodes the 'inward-rectifier potassium ion channel (Kir6.2)'. However, because of the absence of the complete crystal/NMR structures of Kir6.2 proteins, insight into its structure and function and its interaction with diverse ligands remain elusive to date. Therefore, a computational approach was employed for predicting the best plausible 'three-dimensional' structure of Kir6.2 as well as for studying the influence of mutation (p. GLU23LYS) on both architectures as well as the function of Kir6.2 employing simulation studies. Results obtained revealed that though, with increased time, 'Gibbs free energy' becomes positive, residues in wild type Kir6.2 experiences less random movement as compared to mutant Kir6.2. The less random movement of residues in wild type Kir6.2 represents the standard coupling between open and closing of 'K_ATP channel' and thus the normal secretion of insulin. The more dispersed motion of mutant Kir6.2 residues represents 'overactivity' of the 'K_ATP channel' and thus insulin 'under-secretion'. Further, molecular docking and simulation studies identified two phytochemicals/drugs, namely, A-348441 and chushizisin I, which retains the wild type property of Kir6.2 after binding with mutant protein. Unlike A-348441, this is for the first time, the present study is reporting about the plausible anti-diabetic property of chushizisin I. As these two phytochemicals/drugs, namely, A-348441 and chushizisin I, have passed ADMET test, in the near future, they may be utilized as anti-diabetic drugs after further investigation.Communicated by Ramaswamy H. Sarma.

The influence of SLC22A1 rs622342 and ABCC8 rs757110 genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian patients with type 2 diabetes

Background: The incidence of Type 2 Diabetes Mellitus (T2DM) in Egypt is considered one of the highest in the world. Metformin and Sulfonylureas are usually prescribed together due to their efficacy and their relatively low cost. Organic cation transport 1, encoded by SLC22A1 gene, is the main transporter of metformin into hepatocytes, which is considered metformin site of action. Sulfonylureas enhance insulin release from pancreatic B-cells through binding to sulfonylurea receptor 1, encoded by ABCC8 gene. Single nucleotide polymorphisms in the SLC22A1 and ABCC8 genes might affect the response of each drug.

Aims: To investigate the influence of SLC22A1 rs622342 (A>C) and ABCC8 rs757110 (A>C) genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian T2DM patients.

Methods: Observational cross-sectional study in which patients receiving metformin and glimepiride combination therapy for at least 6 months were included for genotyping and classified into either responders or non-responders, based on their HbA1C level.

Results: A total of 127 patients were included and genotyped. They were divided into 93 responders (HbA1C<7%) and 34 non-responders (HbA1C≥7%). Minor allele frequencies for rs622342 and rs757110 were 0.189 and 0.271, respectively. Only SLC22A1 rs622342 variant was found to be associated with the response of combination therapy, in which AA alleles carriers were 2.7-times more responsive to metformin than C allele carriers (Recessive model, odds ratio = 2.718, p = 0.025, 95% CI = 1.112–6.385).

Conclusion: Genotyping of rs622342 can be useful in predicting the response to metformin in combination therapy in Egyptian T2DM patients.

Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.

Identification of genetic variants in pharmacogenetic genes associated with type 2 diabetes in a Mexican-Mestizo population

Type 2 diabetes mellitus (T2DM) is one of the most prevalent chronic pathologies in the world. In developing countries, such as Mexico, its prevalence represents an important public health and research issue. Determining factors triggering T2DM are environmental and genetic. While diet, exercise and proper weight control are the first measures recommended to improve the quality of life and life expectancy of patients, pharmacological treatment is usually the next step. Within every population there are variations in interindividual drug response, which may be due to genetic background. Some of the most frequent first line T2DM treatments in developing countries are sulfonylureas (SU), whose targets are ATP-sensitive potassium channels (K_ATP). Single nucleotide polymorphisms (SNPs) of the K_ATP coding genes, potassium voltage-gated channel subfamily J member 11 (KCNJ11) and ATP binding cassette subfamily C member 8 (ABCC8) have been associated with SU response variability. To date, there is little information regarding the mechanism by which these SNPs work within Mexican populations. The present study describes the distribution of three SNPs [KCNJ11 rs5219 (E23K), ABCC8 rs757110 (S1369A) and rs1799854 (-3C/T)] among Mestizo Mexican (MM) T2DM patients, and compares it with published data on various healthy subjects and T2DM populations. Through this comparison, no difference in the KCNJ11 rs5219 and ABCC8 rs757110 allelic and genotypic frequencies in MM were observed compared with the majority of the reported populations of healthy and diabetic individuals among other ethnic groups; except for African and Colombian individuals. By contrast, ABCC8 rs1799854 genomic and allelic frequencies among MM were observed to be significantly different from those reported by the 1000 Genomes Project, and from diabetic patients within other populations reported in the literature, such as the European, Asian and Latin-American individuals [T=0.704, G=0.296; CC=0.506, CT=0.397, TT=0.097; 95% confidence interval (CI); P≤0.05]; except for South Asian and Iberian populations, which may reflect the admixture origins of the present Mexican population. This genetic similarity has not been observed in the other Latin-American groups. To the best of our knowledge, this is the first study of ABCC8 rs757110 and rs1799854 SNP frequencies in any Mexican population and, specifically with diabetic Mexicans. Knowledge of the genetic structure of different populations is key to understanding the interindividual responses to drugs, such as SU and whether genotypic differences affect clinical outcome.

Pharmacogenetics in type 2 diabetes: influence on response to oral hypoglycemic agents

Type 2 diabetes is one of the leading causes of morbidity and mortality, consuming a significant proportion of public health spending. Oral hypoglycemic agents (OHAs) are the frontline treatment approaches after lifestyle changes. However, huge interindividual variation in response to OHAs results in unnecessary treatment failure. In addition to nongenetic factors, genetic factors are thought to contribute to much of such variability, highlighting the importance of the potential of pharmacogenetics to improve therapeutic outcome. Despite the presence of conflicting results, significant progress has been made in an effort to identify the genetic markers associated with pharmacokinetics, pharmacodynamics, and ultimately therapeutic response and/or adverse outcomes to OHAs. As such, this article presents a comprehensive review of current knowledge on pharmacogenetics of OHAs and provides insights into knowledge gaps and future directions.

Personalized medicine in diabetes mellitus: current opportunities and future prospects

Diabetes mellitus affects approximately 382 million individuals worldwide and is a leading cause of morbidity and mortality. Over 40 and nearly 80 genetic loci influencing susceptibility to type 1 and type 2 diabetes, respectively, have been identified. In addition, there is emerging evidence that some genetic variants help to predict response to treatment. Other variants confer apparent protection from diabetes or its complications and may lead to development of novel treatment approaches. Currently, there is clear clinical utility to genetic testing to find the at least 1% of diabetic individuals who have monogenic diabetes (e.g., maturity-onset diabetes of the young and KATP channel neonatal diabetes). Diagnosing many of these currently underdiagnosed types of diabetes enables personalized treatment, resulting in improved and less invasive glucose control, better prediction of prognosis, and enhanced familial risk assessment. Efforts to enhance the rate of detection, diagnosis, and personalized treatment of individuals with monogenic diabetes should set the stage for effective clinical translation of current genetic, pharmacogenetic, and pharmacogenomic research of more complex forms of diabetes.

Stratified medicine for the use of antidiabetic medication in treatment of type II diabetes and cancer: where do we go from here?

At present, the global diabetes epidemic is affecting 347 million individuals, 90% of whom are diagnosed with type II diabetes mellitus (T2DM). T2DM is commonly treated with more than one type of therapy, including oral antidiabetic drugs (OADs) and agents used in the treatment of diabetic complications. Several pharmacological classes of OADs are currently available for the treatment of T2DM, of which insulin secretagogues (i.e. sulphonylureas and meglitinides), insulin sensitizers [thiazolidinediones (TZDs)] and biguanides are the most commonly prescribed. Although many of these OADs have been used for more than half a century in the treatment of T2DM, the pharmacogenomic characteristics of these compounds have only recently been investigated, primarily in retrospective studies. Recent advances in pharmacogenomics have led to the identification of polymorphisms that affect the expression and function of drug-metabolizing enzymes and drug transporters, as well as drug targets and receptors. These polymorphisms have been shown to affect the therapeutic response to and side effects associated with OADs. The aim of this review was to provide an up-to-date summary of some of the pharmacogenomic data obtained from studies of T2DM treatment, with a focus on polymorphisms in genes affecting pharmacokinetics, pharmacodynamics and treatment outcome of the most commonly prescribed OADs. In addition, the implications of pharmacogenomics in the use of the OAD metformin in cancer will be briefly discussed. Finally, we will focus on recent advances in novel 'omics' technologies and discuss how these might aid in the personalized management of T2DM.

ATP-dependent potassium channels and type 2 diabetes mellitus

Diabetes mellitus is a public health problem, which affects a millions worldwide. Most diabetes cases are classified as type 2 diabetes mellitus, which is highly associated with obesity. Type 2 diabetes is considered a multifactorial disorder, with both environmental and genetic factors contributing to its development. An important issue linked with diabetes development is the failure of the insulin releasing mechanism involving abnormal activity of the ATP-dependent potassium channel, KATP. This channel is a transmembrane protein encoded by the KCNJ11 and ABCC8 genes. Furthermore, polymorphisms in these genes have been linked to type 2 diabetes because of the role of KATP in insulin release. While several genetic variations have been reported to be associated with this disease, the E23K polymorphism is most commonly associated with this pathology, as well as to obesity. Here, we review the molecular genetics of the potassium channel and discusses its most described polymorphisms and their associations with type 2 diabetes mellitus.

KCNJ11: Genetic Polymorphisms and Risk of Diabetes Mellitus

Diabetes mellitus (DM) is a major worldwide health problem and its prevalence has been rapidly increasing in the last century. It is caused by defects in insulin secretion or insulin action or both, leading to hyperglycemia. Of the various types of DM, type 2 occurs most frequently. Multiple genes and their interactions are involved in the insulin secretion pathway. Insulin secretion is mediated through the ATP-sensitive potassium (KATP) channel in pancreatic beta cells. This channel is a heteromeric protein, composed of four inward-rectifier potassium ion channel (Kir6.2) tetramers, which form the pore of the KATP channel, as well as sulfonylurea receptor 1 subunits surrounding the pore. Kir6.2 is encoded by the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene, a member of the potassium channel genes. Numerous studies have reported the involvement of single nucleotide polymorphisms of the KCNJ11 gene and their interactions in the susceptibility to DM. This review discusses the current evidence for the contribution of common KCNJ11 genetic variants to the development of DM. Future studies should concentrate on understanding the exact role played by these risk variants in the development of DM.

Pharmacogenomics of glinides

Glinides, including repaglinide, nateglinide and mitiglinide, are a type of fasting insulin secretagogue that could help to mimic early-phase insulin release, thus providing improved control of the postprandial glucose levels. Glinides stimulate insulin secretion by inhibiting ATP-sensitive potassium channels in the pancreatic β-cell membrane. Although glinides have been widely used clinically and display excellent safety and efficacy, the response to glinides varies among individuals, which is partially due to genetic factors involved in drug absorption, distribution, metabolism and targeting. Several pharmacogenomic studies have demonstrated that variants of genes involved in the pharmacokinetics or pharmacodynamics of glinides are associated with the drug response. Polymorphisms of genes involved in drug metabolism, such as CYP2C9, CYP2C8 and SLCO1B1, may influence the efficacy of glinides and the incidence of adverse effects. In addition, Type 2 diabetes mellitus susceptibility genes, such as KCNQ1, PAX4 and BETA2, also influence the efficacy of glinides. In this article, we review and discuss current pharmacogenomics researches on glinides, and hopefully provide useful data and proof for clinical application.

Patient profiling in diabetes and role of canagliflozin

Background

Physicians attempt to achieve glycemic goals in patients with type 2 diabetes mellitus (T2DM) through various means, including glucose-lowering medications. There is interindividual variability in response to medications, which can be partially explained by the presence of genetic polymorphisms that affect drug metabolism. Pharmacogenomics studies the hereditary basis of interpatient variations in drug response and aims to identify subgroups of patients whose drug management could be tailored accordingly. The aim of this review is to explore patient profiling in the management of T2DM with a focus on the sodium glucose transporter inhibitor canagliflozin.

Methods

The PubMed database was searched using the terms “pharmacogenomics” and “diabetes” through May 31, 2014. Published articles and abstracts presented at national/international meetings were considered.

Results and conclusion

Genome-wide association studies have opened the door for patient profiling and research into genetic variants in multifactorial T2DM. Clinically, it may be possible to tailor the type of medication used based on the presence or absence of the various genetic variants. However, the polymorphisms studied may only explain some of the variability in response to T2DM drugs and needs further validation to ensure its authenticity. There are still unidentified factors which appear to play a role in the interindividual variability seen in clinical practice. The potential exists for pharmacogenomics to promote efficacious, safe, and cost-effective individualized diabetes management. Pharmacogenomics is still in its early stages, and the idea of defining patients genetically to predict individual responses to drugs and obtain safe and effective T2DM management is promising, in spite of existing barriers. Currently, clinical profiling of patients with T2DM and using an individualized approach with most drugs, including canagliflozin, based on comorbid conditions still remains the most accepted approach for the management of T2DM.

Pharmacogenetics of type 2 diabetes mellitus: An example of success in clinical and translational medicine

The pharmacological interventions currently available to control type 2 diabetes mellitus (T2DM) show a wide interindividual variability in drug response, emphasizing the importance of a personalized, more effective medical treatment for each individual patient. In this context, a growing interest has emerged in recent years and has focused on pharmacogenetics, a discipline aimed at understanding the variability in patients’ drug response, making it possible to predict which drug is best for each patient and at what doses. Recent pharmacological and clinical evidences indicate that genetic polymorphisms (or genetic variations) of certain genes can adversely affect drug response and therapeutic efficacy of oral hypoglycemic agents in patients with T2DM, through pharmacokinetic- and/or pharmacodynamic-based mechanisms that may reduce the therapeutic effects or increase toxicity. For example, genetic variants in genes encoding enzymes of the cytochrome P-450 superfamily, or proteins of the ATP-sensitive potassium channel on the beta-cell of the pancreas, are responsible for the interindividual variability of drug response to sulfonylureas in patients with T2DM. Instead, genetic variants in the genes that encode for the organic cation transporters of metformin have been related to changes in both pharmacodynamic and pharmacokinetic responses to metformin in metformin-treated patients. Thus, based on the individual’s genotype, the possibility, in these subjects, of a personalized therapy constitutes the main goal of pharmacogenetics, directly leading to the development of the right medicine for the right patient. Undoubtedly, this represents an integral part of the translational medicine network.

Pharmacogenetics and personalized treatment of type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a worldwide epidemic with considerable health and economic consequences. T2DM patients are often treated with more than one drug, including oral antidiabetic drugs (OAD) and drugs used to treat diabetic complications, such as dyslipidemia and hypertension. If genetic testing could be employed to predict treatment outcome, appropriate measures could be taken to treat T2DM more efficiently. Here we provide a review of pharmacogenetic studies focused on OAD and a role of common drug-metabolizing enzymes (DME) and drug-transporters (DT) variants in therapy outcomes. For example, genetic variations of several membrane transporters, including SLC2A1/2 and SLC47A1/2 genes, are implicated in the highly variable glycemic response to metformin, a first-line drug used to treat newly diagnosed T2DM. Furthermore, cytochrome P450 (CYP) enzymes are implicated in variation of sulphonylurea and meglitinide metabolism. Additional variants related to drug target and diabetes risk genes have been also linked to interindividual differences in the efficacy and toxicity of OAD. Thus, in addition to promoting safe and cost-effective individualized diabetes treatment, pharmacogenomics has a great potential to complement current efforts to optimize treatment of diabetes and lead towards its effective and personalized care.

Individualized therapy for type 2 diabetes: clinical implications of pharmacogenetic data

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance, abnormally elevated hepatic glucose production, and reduced glucose-stimulated insulin secretion. Treatment with antihyperglycemic agents is initially successful in type 2 diabetes, but it is often associated with a high secondary failure rate, and the addition of insulin is eventually necessary for many patients, in order to restore acceptable glycemic control and to reduce the risk of development and progression of disease complications. Notably, even patients who appear to have similar requirements of antidiabetic regimens show great variability in drug disposition, glycemic response, tolerability, and incidence of adverse effects during treatment. Pharmacogenomics is a promising area of investigation and involves the search for genetic polymorphisms that may explain the interindividual variability in antidiabetic therapy response. The initial positive results portend that genomic efforts will be able to shed important light on variability in pharmacologic traits. In this review, we summarize the current understanding of genetic polymorphisms that may affect the responses of subjects with T2DM to antidiabetic treatment. These genes belong to three major classes: genes involved in drug metabolism and transporters that influence pharmacokinetics (including the cytochrome P450 [CYP] superfamily, the organic anion transporting polypeptide [OATP] family, and the polyspecific organic cation transporter [OCT] family); genes encoding drug targets and receptors (including peroxisome proliferator-activated receptor gamma [PPARG], the adenosine triphosphate [ATP]-sensitive potassium channel [K(ATP)], and incretin receptors); and genes involved in the causal pathway of T2DM that are able to modify the effects of drugs (including adipokines, transcription factor 7-like 2 (T cell specific, HMG-box) [TCF7L2], insulin receptor substrate 1 [IRS1], nitric oxide synthase 1 (neuronal) adaptor protein [NOS1AP], and solute carrier family 30 (zinc transporter), member 8 [SLC30A8]). In addition to these three major classes, we also review the available evidence on novel genes (CDK5 regulatory subunit associated protein 1-like 1 [CDKAL1], insulin-like growth factor 2 mRNA binding protein 2 [IGF2BP2], potassium voltage-gated channel, KQT-like subfamily, member 1 [KCNQ1], paired box 4 [PAX4] and neuronal differentiation 1 [NEUROD1] transcription factors, ataxia telangiectasia mutated [ATM], and serine racemase [SRR]) that have recently been proposed as possible modulators of therapeutic response in subjects with T2DM.

Association between TCF7L2 Genotype and Glycemic Control in Diabetic Patients Treated with Gliclazide

Previous studies showed associations between variants in TCF7L2 gene and the therapeutic response to sulfonylureas. All sulfonylureas stimulate insulin secretion by the closure of ATP-sensitive potassium (KATP) channel. The aim of the present study was to compare TCF7L2 genotype specific effect of gliclazide binding to KATP channel A-site (Group 1) with sulfonylureas binding to AB-site (Group 2). A total of 101 patients were treated with sulfonylureas for 6 months as an add-on therapy to the previous metformin treatment. TCF7L2 rs7903146 C/T genotype was identified by real-time PCR with subsequent melting curve analysis. Analyses using the dominant genetic model showed significantly higher effect of gliclazide in the CC genotype group in comparison with combined CT + TT genotype group (1.32 ± 0.15% versus 0.73 ± 0.11%, P (adj) = 0.005). No significant difference in ΔHbA1c between the patients with CC genotype and the T-allele carriers was observed in Group 2. In the multivariate analysis, only the TCF7L2 genotype (P = 0.006) and the baseline HbA1c (P < 0.001) were significant predictors of ΔHbA1c. After introducing an interaction term between the TCF7L2 genotype and the sulfonylurea type into multivariate model, the interaction became a significant predictor (P = 0.023) of ΔHbA1c. The results indicate significantly higher difference in ΔHbA1c among the TCF7L2 genotypes in patients treated with gliclazide than in patients treated with glimepiride, glibenclamide, or glipizide.

Pharmacogenetics of oral antidiabetic drugs

Oral antidiabetic drugs (OADs) are used for more than a half-century in the treatment of type 2 diabetes. Only in the last five years, intensive research has been conducted in the pharmacogenetics of these drugs based mainly on the retrospective register studies, but only a handful of associations detected in these studies were replicated. The gene variants in CYP2C9, ABCC8/KCNJ11, and TCF7L2 were associated with the effect of sulfonylureas. CYP2C9 encodes sulfonylurea metabolizing cytochrome P450 isoenzyme 2C9, ABCC8 and KCNJ11 genes encode proteins constituting ATP-sensitive K(+) channel which is a therapeutic target for sulfonylureas, and TCF7L2 is a gene with the strongest association with type 2 diabetes. SLC22A1, SLC47A1, and ATM gene variants were repeatedly associated with the response to metformin. SLC22A1 and SLC47A1 encode metformin transporters OCT1 and MATE1, respectively. The function of a gene variant near ATM gene identified by a genome-wide association study is not elucidated so far. The first variant associated with the response to gliptins is a polymorphism in the proximity of CTRB1/2 gene which encodes chymotrypsinogen. Establishment of diabetes pharmacogenetics consortia and reduction in costs of genomics might lead to some significant clinical breakthroughs in this field in a near future.