Effect of sulphonylurea treatment on glycaemic control is related to TCF7L2 genotype in patients with type 2 diabetes

The effects of transcription factor 7-like 2 rs7903146 and paired box 4 rs2233580 variants associated with type 2 diabetes on the therapeutic efficacy of hypoglycemic agents

Aim

This study aims to investigate the effects of the TCF7L2 rs7903146 and PAX4 rs2233580 (R192H) variants associated with T2D on the therapeutic efficacies of various HAs in patients with T2D after follow-up for 3 years.

Methods

A total of 526 patients who were followed up at the Diabetic Clinic of Siriraj Hospital during 2016-2019 were enrolled. The variants TCF7L2 rs7903146 and PAX4 rs2233580 (R192H) were genotyped using the RNase H2 enzyme-based amplification (rhAmp) technique and the associations between genotypes and glycemic control after treatments with different combinations HA were evaluated using Generalized Estimating Equations (GEE) analysis.

Results

Patients who carried TCF7L2 rs7903146C/T + T/T genotypes when they were treated with biguanide alone had significantly lower fasting plasma glucose (FPG) than those of the patients who carried the C/C genotype (p = 0.01). Patients who carried the PAX4 rs2233580 G/G genotype when they were treated with sulfonylurea alone had significantly lower FPG than those of the patients who carried G/A + A/A genotypes (p = 0.04).

Conclusion

Genotypes of TCF7L2 rs7903146 and PAX4 rs2233580 (R192H) variants associated with T2D influence the therapeutic responses to biguanide and sulfonylurea. Different genotypes of these two variants might distinctively affect the therapeutic effects of HAs. This finding provides evidence of pharmacogenetics in the treatment of diabetes.

Sex Differences in the Effects of CDKAL1 Variants on Glycemic Control in Diabetic Patients: Findings from the Korean Genome and Epidemiology Study

BACKGROUND

Using long-term data from the Korean Genome and Epidemiology Study, we defined poor glycemic control and investigated possible risk factors, including variants related to type 2 diabetes mellitus (T2DM). In addition, we evaluated interaction effects among risk factors for poor glycemic control.

METHODS

Among 436 subjects with newly diagnosed diabetes, poor glycemic control was defined based on glycosylated hemoglobin trajectory patterns by group-based trajectory modeling. For the variants related to T2DM, genetic risk scores (GRSs) were calculated and divided into quartiles. Risk factors for poor glycemic control were assessed using a logistic regression model.

RESULTS

Of the subjects, 43% were in the poor-glycemic-control group. Body mass index (BMI) and triglyceride (TG) were associated with poor glycemic control. The risk for poor glycemic control increased by 11.0% per 1 kg/m2 increase in BMI and by 3.0% per 10 mg/dL increase in TG. The risk for GRS with poor glycemic control was sex-dependent (Pinteraction=0.07), and a relationship by GRS quartiles was found in females but not in males. Moreover, the interaction effect was found to be significant on both additive and multiplicative scales. The interaction effect was evident in the variants of cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like (CDKAL1).

CONCLUSION

Females with risk alleles of variants in CDKAL1 associated with T2DM had a higher risk for poor glycemic control than males.

The Prevalence of Pharmacogenomics Variants and Their Clinical Relevance Among the Pakistani Population

Background:

Pharmacogenomics (PGx), forming the basis of precision medicine, has revolutionized traditional medical practice. Currently, drug responses such as drug efficacy, drug dosage, and drug adverse reactions can be anticipated based on the genetic makeup of the patients. The pharmacogenomic data of Pakistani populations are limited. This study investigates the frequencies of pharmacogenetic variants and their clinical relevance among ethnic groups in Pakistan.

Methods:

The Pharmacogenomics Knowledge Base (PharmGKB) database was used to extract pharmacogenetic variants that are involved in medical conditions with high (1A + 1B) to moderate (2A + 2B) clinical evidence. Subsequently, the allele frequencies of these variants were searched among multiethnic groups of Pakistan (Balochi, Brahui, Burusho, Hazara, Kalash, Pashtun, Punjabi, and Sindhi) using the 1000 Genomes Project (1KGP) and ALlele FREquency Database (ALFRED). Furthermore, the published Pharmacogenomics literature on the Pakistani population was reviewed in PubMed and Google Scholar.

Results:

Our search retrieved (n = 29) pharmacogenetic genes and their (n = 44) variants with high to moderate evidence of clinical association. These pharmacogenetic variants correspond to drug-metabolizing enzymes (n = 22), drug-metabolizing transporters (n = 8), and PGx gene regulators, etc. (n = 14). We found 5 pharmacogenetic variants present at >50% among 8 ethnic groups of Pakistan. These pharmacogenetic variants include CYP2B6 (rs2279345, C; 70%-86%), CYP3A5 (rs776746, C; 64%-88%), FLT3 (rs1933437, T; 54%-74%), CETP (rs1532624, A; 50%-70%), and DPP6 (rs6977820, C; 61%-86%) genes that are involved in drug response for acquired immune deficiency syndrome, transplantation, cancer, heart disease, and mental health therapy, respectively.

Conclusions:

This study highlights the frequency of important clinical pharmacogenetic variants (1A, 1B, 2A, and 2B) among multi-ethnic Pakistani populations. The high prevalence (>50%) of single nucleotide pharmacogenetic variants may contribute to the drug response/diseases outcome. These PGx data could be used as pharmacogenetic markers in the selection of appropriate therapeutic regimens for specific ethnic groups of Pakistan.

KCNQ1 rs2237895 polymorphism is associated with the therapeutic response to sulfonylureas in Iranian type 2 diabetes mellitus patients

Background and Aims

Sulfonylureas are the most secondary prescribed oral anti-diabetic drug. Understanding its genetic role in pharmacodynamics can elucidate a considerable knowledge about personalized treatment in type 2 diabetes patients. This study aimed to assess the impact of KCNQ1 variants on sulfonylureas response among type 2 diabetes Iranian patients.

Methods and Results

100 patients were recruited who were under sulfonylureas therapy for six months. 50 responder and 50 non-responder patients were selected. KCNQ1 variants were determined by the RFLP method, and their role in treatment response was assessed retrospectively. Patients with rs2237895 CC and AC genotypes demonstrated a significant decrement in FBS and HbA1c after treatment over patients with AA genotypes (All P < 0.001). Compared to the A allele, the odds ratio for treatment success between carriers with rs2237895 C allele was 4.22-fold (P < 0.001). Patients with rs2237892 CT heterozygous genotype exhibit a higher reduction rate in HbA1c and FBS than CC homozygotes (P=0.064 and P=0.079, respectively). The rs2237892 T allele carriers showed an odds ratio equals to 2.83-fold over C allele carriers in the responder group compared to the non-responder group (p=0.081).

Conclusion

Findings suggest that the KCNQ1 rs2237895 polymorphism is associated with the sulfonylureas response on Iranian type 2 diabetes patients.

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.

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.

The role of transcription factor 7-like 2 in metabolic disorders

Transcription factor 7-like 2 (TCF7L2), a member of the T cell factor/lymphoid enhancer factor family, generally forms a complex with β-catenin to regulate the downstream target genes as an effector of the canonical Wnt signalling pathway. TCF7L2 plays a vital role in various biological processes and functions in many organs and tissues, including the liver, islet and adipose tissues. Further, TCF7L2 down-regulates hepatic gluconeogenesis and promotes lipid accumulation. In islets, TCF7L2 not only affects the insulin secretion of the β-cells but also has an impact on other cells. In addition, TCF7L2 influences adipogenesis in adipose tissues. Thus, an out-of-control TCF7L2 expression can result in metabolic disorders. The TCF7L2 gene is composed of 17 exons, generating 13 different transcripts, and has many single-nucleotide polymorphisms (SNPs). The discovery that these SNPs have an impact on the risk of type 2 diabetes (T2D) has attracted thorough investigations in the study of TCF7L2. Apart from T2D, TCF7L2 SNPs are also associated with type 1, posttransplant and other types of diabetes. Furthermore, TCF7L2 variants affect the progression of other disorders, such as obesity, cancers, metabolic syndrome and heart diseases. Finally, the interaction between TCF7L2 variants and diet also needs to be investigated.

Diabetes and Genetics: A Relationship Between Genetic Risk Alleles, Clinical Phenotypes and Therapeutic Approaches

Unveiling human genome through successful completion of Human Genome Project and International HapMap Projects with the advent of state of art technologies has shed light on diseases associated genetic determinants. Identification of mutational landscapes such as copy number variation, single nucleotide polymorphisms or variants in different genes and loci have revealed not only genetic risk factors responsible for diseases but also region(s) playing protective roles. Diabetes is a global health concern with two major types - type 1 diabetes (T1D) and type 2 diabetes (T2D). Great progress in understanding the underlying genetic predisposition to T1D and T2D have been made by candidate gene studies, genetic linkage studies, genome wide association studies with substantial number of samples. Genetic information has importance in predicting clinical outcomes. In this review, we focus on recent advancement regarding candidate gene(s) associated with these two traits along with their clinical parameters as well as therapeutic approaches perceived. Understanding genetic architecture of these disease traits relating clinical phenotypes would certainly facilitate population stratification in diagnosing and treating T1D/T2D considering the doses and toxicity of specific drugs.

Pharmacogenomic Studies of Current Antidiabetic Agents and Potential New Drug Targets for Precision Medicine of Diabetes

Diabetes is a major threat to people's health and has become a burden worldwide. Current drugs for diabetes have limitations, such as different drug responses among individuals, failure to achieve glycemic control, and adverse effects. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Currently pharmacogenomics has provided potential for individualized drug therapy based on genetic and genomic information of patients, and has made precision medicine possible. Responses and adverse effects to antidiabetic drugs are significantly associated with gene polymorphisms in patients. Many new targets for diabetes also have been discovered and developed, and even entered clinical trial phases. This review summarizes pharmacogenomic evidence of some current antidiabetic agents applied in clinical settings, and highlights potential drugs with new targets for diabetes, which represent a more effective treatment in the future.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

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.

Utility of Precision Medicine in the Management of Diabetes: Expert Opinion from an International Panel

AIM

The primary objective of this review is to develop a practice-based expert group opinion on the role of precision medicine with a specific focus on sulfonylureas (SUs) in diabetes management.

BACKGROUND

The clinical etiology, presentation and complications of diabetes vary from one patient to another, making the management of the disease challenging. The pre-eminent feature of diabetes mellitus (DM) are chronically elevated blood glucose concentrations; however, in clinical practice, the exclusion of autoimmunity, pregnancy, pancreatic disease or injury and rare genetic forms of diabetes is crucial. Within this framework, precision medicine provides unique insights into the risk factors and natural history of DM. Precision medicine goes beyond genomics and encompasses patient-centered care, molecular technologies and data sharing. Precision medicine has evolved in the field of diabetology. It has helped improve the efficacy of SUs, a class of drugs, which have been effectively used in the management of diabetes mellitus for decades, and it has enabled the expansion of SUs use in diabetes patients with genetic mutations.

REVIEW RESULTS

After due discussions, the expert group analyzed studies that focused on the use of SUs in diabetes patients with genomic variations and rare mutations. The expert group opined that SUs are important glucose-lowering drugs and that precision medicine helps in improving the efficacy of SUs by matching them to those patients who will benefit most.

CONCLUSION

Precision medicine opens new vistas for the effective use of SUs in unexpected patient populations, such as those with genetic mutations.

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

The global role of biotechnology for non communicable disorders

The World Health Organization (WHO) has tagged non-communicable diseases (NCDs) as one of the twenty-first century's major development challenges. NCDs account for over 15 million deaths annually and over 80% of those deaths occur in developing countries and among the poorest populations. Biotechnology presents unique opportunities to improve the early diagnosis and the treatment of NCDs. This review describes the major applications of biotechnology for a better clinical management of NCDs, i.e. the implementation of innovative diagnostic approaches and the production of innovative treatments, including those based on monoclonal antibodies, recombinant proteins, regulatory nucleic acids and cell-based therapies for regenerative medicine. In this context, it also examines the major challenges faced by biotechnology in developing countries.

Pharmacogenetics and target identification in diabetes

In diabetes, pharmacogenetics can be used both to identify patient subgroups who will have most benefit and/or least harm from a particularly treatment, and to gain insights into the molecular mechanisms of drug action and disease aetiology. There is increasing evidence that genetic variation alters response to diabetes treatments-both in terms of glycaemic response and side effects. This can be seen with dramatic impact on clinical care, in patients with genetic forms of diabetes such as Maturity Onset Diabetes of the Young caused by HNF1A mutations, and Neonatal diabetes due to activating mutations in ABCC8 or KCNJ11. Beyond monogenic diabetes, pharmacogenetic variants have yet to impact on clinical practice, yet the effect sizes (e.g. for metformin intolerance and OCT1 variants; or for metformin action and SLC2A2 variants) are potentially of clinical utility, especially if the genotype is already known at the point of prescribing. Over the next few years, increasing cohort sizes and linkage at scale to electronic medical records will provide considerable potential for stratification and novel target identification in diabetes.

KCNJ11, ABCC8 and TCF7L2 polymorphisms and the response to sulfonylurea treatment in patients with type 2 diabetes: a bioinformatics assessment

BACKGROUND

Type 2 diabetes (T2D) is a worldwide epidemic with considerable health and economic consequences. Sulfonylureas are widely used drugs for the treatment of patients with T2D. KCNJ11 and ABCC8 encode the Kir6.2 (pore-forming subunit) and SUR1 (regulatory subunit that binds to sulfonylurea) of pancreatic β cell KATP channel respectively with a critical role in insulin secretion and glucose homeostasis. TCF7L2 encodes a transcription factor expressed in pancreatic β cells that regulates insulin production and processing. Because mutations of these genes could affect insulin secretion stimulated by sulfonylureas, the aim of this study is to assess associations between molecular variants of KCNJ11, ABCC8 and TCF7L2 genes and response to sulfonylurea treatment and to predict their potential functional effects.

METHODS

Based on a comprehensive literature search, we found 13 pharmacogenetic studies showing that single nucleotide polymorphisms (SNPs) located in KCNJ11: rs5219 (E23K), ABCC8: rs757110 (A1369S), rs1799854 (intron 15, exon 16 -3C/T), rs1799859 (R1273R), and TCF7L2: rs7903146 (intron 4) were significantly associated with responses to sulfonylureas. For in silico bioinformatics analysis, SIFT, PolyPhen-2, PANTHER, MutPred, and SNPs3D were applied for functional predictions of 36 coding (KCNJ11: 10, ABCC8: 24, and TCF7L2: 2; all are missense), and HaploReg v4.1, RegulomeDB, and Ensembl's VEP were used to predict functions of 7 non-coding (KCNJ11: 1, ABCC8: 1, and TCF7L2: 5) SNPs, respectively.

RESULTS

Based on various in silico tools, 8 KCNJ11 missense SNPs, 23 ABCC8 missense SNPs, and 2 TCF7L2 missense SNPs could affect protein functions. Of them, previous studies showed that mutant alleles of 4 KCNJ11 missense SNPs and 5 ABCC8 missense SNPs can be successfully rescued by sulfonylurea treatments. Further, 3 TCF7L2 non-coding SNPs (rs7903146, rs11196205 and rs12255372), can change motif(s) based on HaploReg v4.1 and are predicted as risk factors by Ensembl's VEP.

CONCLUSIONS

Our study indicates that a personalized medicine approach by tailoring sulfonylurea therapy of T2D patients according to their genotypes of KCNJ11, ABCC8, and TCF7L2 could attain an optimal treatment efficacy.

Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool?

In recent years, technological and analytical advances have led to an explosion in the discovery of genetic loci associated with type 2 diabetes. However, their ability to improve prediction of disease outcomes beyond standard clinical risk factors has been limited. On the other hand, genetic effects on drug response may be stronger than those commonly seen for disease incidence. Pharmacogenetic findings may aid in identifying new drug targets, elucidate pathophysiology, unravel disease heterogeneity, help prioritise specific genes in regions of genetic association, and contribute to personalised or precision treatment. In diabetes, precedent for the successful application of pharmacogenetic concepts exists in its monogenic subtypes, such as MODY or neonatal diabetes. Whether similar insights will emerge for the much more common entity of type 2 diabetes remains to be seen. As genetic approaches advance, the progressive deployment of candidate gene, large-scale genotyping and genome-wide association studies has begun to produce suggestive results that may transform clinical practice. However, many barriers to the translation of diabetes pharmacogenetic discoveries to the clinic still remain. This perspective offers a contemporary overview of the field with a focus on sulfonylureas and metformin, identifies the major uses of pharmacogenetics, and highlights potential limitations and future directions.

Polymorphisms of the KCNQ1 gene are associated with the therapeutic responses of sulfonylureas in Chinese patients with type 2 diabetes

KCNQ1 channel is a member of the voltage-gated potassium channel KQT-like subfamily. The KCNQ1 gene has recently been identified as a susceptibility locus for type 2 diabetes mellitus (T2DM). In the present study, we examined the effects of KCNQ1 variants on the therapeutic response to modified-release gliclazide (gliclazide MR) treatment in Chinese patients newly diagnosed with T2DM. A total of 100 newly diagnosed T2DM patients without a history of any anti-diabetic medications were treated with gliclazide MR for 16 weeks, but 91 patients completed the entire study. The anthropometric parameters were determined at baseline and at the final visit, while clinical laboratory tests were performed at baseline and on weeks 2, 4, 6, 12, 16. Two SNPs, rs2237892 and rs2237895, in the region of the KCNQ1 gene were genotyped in all the participants. All calculations and statistical analyses were conducted using SPSS. The rs2237892 TT homozygotes exhibited significantly higher 2-h glucose levels at baseline (P<0.05) and a lower cumulative attainment rate of the target 2-h glucose level (Plog-rank=0.020) than the C allele carriers. Patients with greater numbers of rs2237892 T alleles exhibited larger augmentations (Δ) in the 2-h glucose levels (P=0.027); and patients with the rs2237892 TT genotype exhibited a higher Δ homeostasis model assessment of β-cell function (HOMA-β) than CC and CT genotype carriers (P=0.021 and P=0.043, respectively). Moreover, the rs2237895 C allele was associated with a greater decrement in Δ glycated hemoglobin (HbA1c) (P=0.024); and patients with the CC genotype exhibited greater variance than those with the AA and AC genotypes (P=0.005 and 0.021, respectively). Compared with the C allele, the odds ratio for treatment success among carriers of the rs2237892 T allele was 2.533 (P=0.007); and the rs2237895 C allele was associated with a 2.360-fold decrease in HbA1c compared with the A allele (P=0.009). KCNQ1 polymorphisms are associated with gliclazide MR efficacy in Chinese patients with type 2 diabetes.

Genetic variations in TCF7L2 influence therapeutic response to sulfonylureas in Indian diabetics

Sulfonylureas are widely used to treat type 2 diabetes, with considerable inter-individual variation in the hypoglycaemic response to sulfonylureas. Genetic variants in the gene encoding for transcription factor-7-like 2 (TCF7L2) have been associated with type 2 diabetes. This study aimed to study the effect of variations in TCF7L2 on therapeutic response to sulfonylureas in Type 2 diabetes mellitus patients. The effect of TCF7L2 rs12255372, rs7903146 and rs4506565 genotypes on glycaemic response was observed in 250 diabetic patients treated with sulfonylureas and sulfonylureas along with metformin. The genotyping tests were done by allele-specific multiplex PCR. Glycated haemoglobin (HbA1c) levels were used as phenotypic marker. 60% of sulfonylurea users did not achieve a target HbA1c levels of ⩽6.5% (48mmol/mol) (which denotes good control in diabetics). Genotype influenced response to sulfonylureas, with more treatment failure in the TT homozygotes in case of rs12255372 and rs4506565. The GG genotype at rs12255372 favourably influences treatment success with sulfonylurea therapy in patients with type 2 diabetes (p⩽0.05). At rs12255372, 70.5% GT or TT genotype failed to achieve therapeutic target, an absolute difference of 19% compared to GG homozygotes. Our preliminary data show that genetic variation at rs12255372 has a direct correlation with therapeutic success with sulfonylureas in type 2 diabetes, hence paving the way for better treatment outcomes in diabetics.

A missense variant in GLP1R gene is associated with the glycaemic response to treatment with gliptins

Gliptins act by increasing endogenous incretin levels. Glucagon-like peptide-1 receptor (GLP1R) and glucose-dependent insulinotropic peptide receptor (GIPR) are their indirect drug targets. Variants of GLP1R and GIPR have previously been associated with the incretin effect. The aim of the present pilot study was to examine associations of the GLP1R and GIPR gene variants with the glycaemic response to gliptins. A total of 140 consecutive patients with type 2 diabetes were followed-up 6 months after initiation of gliptin treatment. GLP1R rs6923761 (Gly168Ser) and GIPR rs10423928 genotyping was performed using real-time PCR, with subsequent high-resolution melting analysis. The main study outcome was reduction in glycated haemoglobin (HbA1c) after treatment. GLP1R Gly168Ser variant was significantly associated with reduction in HbA1c in an additive model (β = -0.33, p = 0.011). The mean reduction in HbA1c in Ser/Ser homozygotes was significantly lower compared with Gly-allele carriers [0.12 ± 0.23% vs. 0.80 ± 0.09% (1.3 ± 2.5 mmol/mol vs. 8.7 ± 1.0 mmol/mol); p = 0.008]. In conclusion, GLP1R missense variant was associated with a reduced response to gliptin treatment. The genotype-related effect size of ∼0.7% (8 mmol/mol) is equal to an average effect of gliptin treatment and makes this variant a candidate for use in precision medicine.

Genetic and Clinical Predictive Factors of Sulfonylurea Failure in Patients with Type 2 Diabetes

BACKGROUND

Sulfonylureas are widely used to treat type 2 diabetes (T2DM). Although genetic variations are associated with sulfonylurea treatment responses in T2DM patients, whether these variations can be used to predict heterogeneous treatment responses is unclear. In this study, we assessed the potential utility of combining information from multiple variants and phenotypes to predict sulfonylurea response.

METHODS

Using data from the "Glibenclamide" arm (365 patients) of the Xiaoke Pill Trial that evaluated the safety and efficacy of sulfonylurea, we identified genetic variants associated with sulfonylurea treatment response, and we explored their ability to predict drug response when combined with phenotype information.

RESULTS

The association of 780 single-nucleotide polymorphisms (using Infinium HD iSelect chip) with drug efficacy was evaluated, and four genes identified with drug metabolism (FMO2, FMO3, UGT2B15, and CYP51A1, P < 0.05) were found to be associated with changes in HbA1c. In a clinical model, the baseline values of HbA1c and disposition index (DI) were significantly associated with HbA1c and fasting plasma glucose (FPG) target achievements. Compared with clinical models, the inclusion of genetic markers significantly increased the predictive ability for both HbA1c- and FPG-based outcomes.

CONCLUSIONS

Our findings suggest that altered protein function in multiple pathways may cooperatively contribute to the increased discrimination by area under receiver operating curve for T2DM patients, and it may explain, in part, the relationship between inter-individual variability and the sulfonylurea response.

Pharmacogenomics in diabetes mellitus: insights into drug action and drug discovery

Genomic studies have greatly advanced our understanding of the multifactorial aetiology of type 2 diabetes mellitus (T2DM) as well as the multiple subtypes of monogenic diabetes mellitus. In this Review, we discuss the existing pharmacogenetic evidence in both monogenic diabetes mellitus and T2DM. We highlight mechanistic insights from the study of adverse effects and the efficacy of antidiabetic drugs. The identification of extreme sulfonylurea sensitivity in patients with diabetes mellitus owing to heterozygous mutations in HNF1A represents a clear example of how pharmacogenetics can direct patient care. However, pharmacogenomic studies of response to antidiabetic drugs in T2DM has yet to be translated into clinical practice, although some moderate genetic effects have now been described that merit follow-up in trials in which patients are selected according to genotype. We also discuss how future pharmacogenomic findings could provide insights into treatment response in diabetes mellitus that, in addition to other areas of human genetics, facilitates drug discovery and drug development for T2DM.

Pharmacogenetic aspects of the treatment of Type 2 diabetes with the incretin effect enhancers

Incretin effect enhancers are drugs used in the treatment of Type 2 diabetes and include GLP-1 receptor agonists and dipeptidyl peptidase-4 inhibitors (gliptins). Variants in several genes were shown to be involved in the physiology of incretin secretion. Only two gene variants have evidence also from pharmacogenetic studies. TCF7L2 rs7903146 C>T and CTRB1/2 rs7202877 T>G minor allele carriers were both associated with a smaller reduction in HbA1c after gliptin treatment when compared with major allele carriers. After replication in further studies, these observations could be of clinical significance in helping to identify patients with potentially lower or higher response to gliptin treatment.

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.

Prevalence of the rs7903146C>T polymorphism in TCF7L2 gene for prediction of type 2 diabetes risk among Iranians of different ethnicities

Background

Pharmacogenetics is the study of genetic polymorphisms affecting responses to drug therapy. The common rs7903146 (C>T) polymorphism of the TCF7L2 gene has recently been associated with type 2 diabetes (T2D). In this study, prevalence of the rs7903146 (C>T) polymorphism in the TCF7L2 gene for prediction of T2D risk was examined in an Iranian population of different ethnicities.

Methods

The prevalence of rs7903146 (C>T) and the predicted phenotypes, including extensive metabolizers, intermediate metabolizers, and poor metabolizers were investigated in blood samples of 300 unrelated healthy individuals in an Iranian population, including Fars, Turk, Lure, and Kurd, using polymerase chain reaction restriction fragment length polymorphism and direct genomic DNA sequencing.

Results

The homozygous wild-type (C/C), heterozygous (C/T), and homozygous (T/T) allelic frequencies of rs7903146 (C>T) in the TCF7L2 gene were 29% (extensive metabolizers), 66.34% (intermediate metabolizers), and 4.66% (poor metabolizers), respectively. The C/C, C/T, and T/T genotypic frequencies of the rs7903146 (C>T) allele were significantly different (P<0.01) among Iranians of different ethnicities. The frequency of the homozygous T/T variant of the rs7903146 (C>T) allele was significantly low in the Lure (P<0.01) and high in the Fars (P<0.001) ethnicities. Additionally, the frequency of the T/T variant of the rs7903146 (C>T) allele in the South of Iran was the highest (P<0.04), while the East of Iran had the lowest frequency (P<0.01).

Conclusion

The prediction of rs7903146 (C>T) is required in drug research and routine treatment, where the information would be helpful for clinicians to optimize therapy and adverse drug reactions and predict drug response in individuals at risk of T2D.

The Protective Effect of Transcription Factor 7-Like 2 Risk Allele rs7903146 against Elevated Fasting Plasma Triglyceride in Type 2 Diabetes: A Meta-Analysis

BACKGROUND

The results from published studies regarding association of transcription factor 7-like 2 (TCF7L2) variant rs7903146 with dyslipidemia have been conflicting and inconclusive.

METHODS

We carried out a meta-analysis that aimed to investigate the association of the rs7903146 variant with plasma lipid levels using electronic database and published studies. Data was extracted by a standard algorithm. Dominant, recessive, homozygote, and heterozygote comparison models were utilized.

RESULTS

24 studies incorporating 52,785 subjects were included in this meta-analysis. Overall, the minor allele (T) was associated with lower risk for hypertriglyceridemia in subjects with type 2 diabetes (dominant model: SMD = -0.04, 95% CI (-0.08, 0.00), P = 0.048, P heterogeneity = 0.47; recessive model: SMD = -0.10, 95% CI (-0.18, -0.02), P = 0.01, P heterogeneity = 0.56). No association was found between minor (T) allele and plasma TC, LDL-c, or HDL-c levels in subjects with type 2 diabetes or metabolic syndrome (MetS) and no association was found between minor (T) allele and plasma TG levels in nondiabetic subjects.

CONCLUSIONS

Our meta-analysis indicated the association between TCF7L2 rs7903146 polymorphism and low plasma triglyceride (TG) level in subjects with type 2 diabetes. No association was found between rs7903146 variant and plasma lipids in nondiabetic subjects.

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.

Personalized medicine in Type 2 Diabetes

Type 2 diabetes (T2D) is a global public health concern, its prevalence in Asia, especially Taiwan, rising every year. The risk of developing T2D and diabetes complications is not only controlled by environmental but also by genetic factors. Genetic association studies have shown polymorphisms at specific loci may help identify individuals at greatest risk and response to oral antidiabetic drugs. This review probes effect of genetic profiling on T2D and its complications, using our study population as examples. Also, pharmacogenetics and pharmacogenomics of oral anitdiabetic drug will be explored.

Search for genetic determinants of sulfonylurea efficacy in type 2 diabetic patients from China

AIMS/HYPOTHESIS

The aim of this study was to investigate whether genetic variance can influence the efficacy of glibenclamide in patients with type 2 diabetes.

METHODS

A total of 747 patients with type 2 diabetes was enrolled from the Xiaoke Pills Clinical Trial, which is a double-blind, randomised controlled trial. All the patients had been treated with glibenclamide for 48 weeks, with strict drug dose adjustment and data collection. Treatment failure was confirmed when patients reached the criteria for terminating their participation in the study (fasting blood glucose level ≥ 7.0 mmol/l on two consecutive tests 4 weeks after reaching the pre-set maximal dose or maximal tolerated dose). Using this cohort, we tested 44 single-nucleotide polymorphisms (SNPs) in 27 gene regions. The genes in our study were involved in the metabolism of sulfonylureas, islet beta cell function, insulin resistance and beta cell growth and differentiation. A logistic regression model was used to evaluate the relationship between genetic variants and treatment failure over a period of 48 weeks.

RESULTS

We found that no SNP reached the significance level of p < 0.00125 if Bonferroni correction was performed for multiple testing in the logistic regression model used in this pharmacogenetic study. Participants with the minor allele C of rs10811661 in CDKN2A/CDKN2B showed a significantly greater reduction in fasting blood glucose (TT vs TC vs CC: 9.3% (0-20.0%) vs 9.2% (0.9-20.5%) vs 12.7% (5.2-24.4%), p = 0.008) after the initial 4 weeks of treatment independent of age, sex and BMI. There was a significant difference in beta cell function among carriers of different genotypes of rs10811661.

CONCLUSIONS/INTERPRETATION

Our study demonstrated that the CDKN2A/CDKN2B gene may be nominally associated with the efficacy of glibenclamide, and that CDKN2A/CDKN2B is associated with beta cell function.

Preserved GLP-1 and exaggerated GIP secretion in type 2 diabetes and relationships with triglycerides and ALT

OBJECTIVE

To i) compare incretin responses to oral glucose and mixed meal of diabetic patients with the normoglycaemic population and ii) to investigate whether incretin responses are associated with hypertriglyceridaemia and alanine aminotransferase (ALT) as liver fat marker.

DESIGN

A population-based study.

METHODS

A total of 163 persons with normal glucose metabolism (NGM), 20 with intermediate hyperglycaemia and 20 with type 2 diabetes aged 40-65 years participated. Participants received a mixed meal and oral glucose load on separate occasions. Glucagon-like peptide 1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and glucagon profiles were analysed as total area under the curve (tAUC) and incremental area under the curve.

RESULTS

In diabetic patients compared with persons with NGM, we found increased GLP-1 secretion (tAUC per hour) following oral glucose (23.2 pmol/l (95% CI 17.7-28.7) vs 18.0 (95% CI 16.9-19.1), P<0.05) but not after the mixed meal. GIP secretion among diabetic patients was increased on both occasions (82.9 pmol/l (55.9-109.8) vs 47.1 (43.8-50.4) for oral glucose and 130.6 (92.5-168.7) vs 83.2 (77.5-88.9) for mixed meal, both P<0.05). After oral glucose, GLP-1 (tAUC per hour) was inversely related to fasting triglycerides. GIP (tAUC per hour) was positively related to fasting and postprandial triglycerides. Higher fasting GIP levels were related to higher fasting and postprandial triglyceride levels and ALT.

CONCLUSION

This study confirms that in type 2 diabetes, GLP-1 secretion is generally preserved and that GIP secretion is exaggerated. The mechanism underlying the divergent associations of GLP-1 and GIP metabolism with fat metabolism and liver fat accumulation warrants further study.

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.

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.

KCNJ11 gene E23K variant and therapeutic response to sulfonylureas

AIMS

Potassium inwardly rectifier 6.2 subunit (Kir6.2) of the ATP-sensitive potassium (K(ATP)) channel encoded by KCNJ11 gene is a therapeutical target for sulfonylureas. KCNJ11 E23K polymorphism was associated with type 2 diabetes in genetic association studies. The aim of the present pharmacogenetic study was to examine the effect of sulfonylurea treatment on glycemic control in relationship to KCNJ11 E23K variant.

PATIENTS AND METHODS

One hundred and one patients with type 2 diabetes who failed to achieve HbA1c<7% on previous metformin monotherapy were included to the study. Sulfonylurea drug was given in addition to metformin. The main outcome of the study was reduction in HbA1c level (ΔHbA1c) after 6-month sulfonylurea therapy. KCNJ11 genotypes were determined by real-time PCR with melting curve analysis.

RESULTS

After 6-month treatment, KCNJ11 K-allele carriers had higher decrease in HbA1c compared with EE homozygotes in the dominant genetic model (1.04±0.10 vs. 0.79±0.12%, p=0.036). In the log-additive model, greater mean reduction in HbA1c by 0.16% (95% CI 0.01-0.32, p=0.038) per each K-allele was observed. The relationship of treatment response with KCNJ11 genotype was also significant in the biggest subgroup of patients treated with gliclazide (n=55).

CONCLUSIONS

Carriers of the KCNJ11 K-allele have better therapeutic response to gliclazide. This observation might help to identify patients who will have the highest benefit from sulfonylurea treatment.

Variation in CDKAL1 gene is associated with therapeutic response to sulphonylureas

The aim of the present pilot pharmacogenetic study was to analyse quantitative effects of sulphonylurea treatment in addition to metformin on parameters of glycemic control with respect to CDKAL1 genotypes in patients with type 2 diabetes. Effect of 6-month sulphonylurea therapy on glycemic control according to CDKAL1 genotypes was evaluated in 101 patients with type 2 diabetes who failed to achieve glycemic control on metformin monotherapy. CDKAL1 rs7756992 polymorphism was determined by melting curve analysis of small amplicon following real-time PCR. After sulphonylurea treatment fasting plasma glucose (FPG) levels were significantly different (p=0.045) among three CDKAL1 genotype groups (AA: n=49; AG: n=36; GG: n=16). In a dominant genetic model, carriers of the G-allele (AG+GG, n=52) achieved significantly lower FPG levels in comparison with patients with the AA genotype (6.90±1.08 vs. 7.48±1.12 mmol/l, p=0.013). Consequently, adjusted ΔFPG was significantly higher in the AG+GG compared to the AA group (1.48±1.51 vs. 1.02±1.33 mmol/l, p=0.022). Similar trend was observed for HbA(1c) levels, but the difference between the genotype groups did not reach the level of statistical significance. Relatively small number of included patients is a limitation of the present study. In conclusion, our results suggest that the magnitude of FPG reduction after 6-month sulphonylurea treatment in patients with type 2 diabetes is related to the variation in CDKAL1.

Pharmacogenetics in type 2 diabetes: potential implications for clinical practice

Pharmacogenetic research aims to study how genetic variation may influence drug efficacy and/or toxicity; pharmacogenomics expands this quest to the entire genome. Pharmacogenetic findings may help to uncover new drug targets, illuminate pathophysiology, clarify disease heterogeneity, aid in the fine-mapping of genetic associations, and contribute to personalized treatment. In diabetes, there is precedent for the successful application of pharmacogenetic concepts to monogenic forms of the disease, such as maturity onset diabetes of the young or neonatal diabetes. Whether similar insights will be produced for the common form of type 2 diabetes remains to be seen. With recent advances in genetic approaches, the successive application of candidate gene studies, large-scale genotyping studies and genome-wide association studies has begun to generate suggestive results that may lead to changes in clinical practice. However, many potential barriers to the translation of pharmacogenetic discoveries to the clinical management of diabetes still remain. Here, we offer a contemporary overview of the field in its current state, identify potential obstacles, and highlight future directions.

Variation in KCNQ1 is associated with therapeutic response to sulphonylureas

Background

We aimed to analyse quantitative effects of treatment with sulphonylurea in addition to metformin on parameters of glycemic control in relation to KCNQ1 genotypes, and to identify factors predictive for the response to sulphonylurea treatment.

Material/Methods

Effect of 6-month sulphonylurea therapy in addition to metformin on glycemic control according to KCNQ1 genotypes was evaluated in 87 patients with type 2 diabetes who failed to achieve glycemic control on metformin monotherapy. KCNQ1 rs163184 (T>G) polymorphism was determined by real-time PCR with melting analysis of unlabeled probe.

Results

The reduction in fasting plasma glucose (ΔFPG) after 6-month sulphonylurea therapy significantly differed among 3 KCNQ1 genotype groups (ANOVA, p=0.017). In a recessive genetic model, carriers of the T-allele (TT+TG) achieved significantly lower FPG levels in comparison with patients with the GG genotype (6.95±0.13 vs. 7.50±0.21 mmol/L, p=0.033). Consequently, ΔFPG was significantly higher in the TT+TG group compared to the GG group (1.58±0.13 vs. 1.04±0.18 mmol/L, p=0.016). In multiple linear regression analysis KCNQ1 genotype (p=0.016) and baseline FPG (p<0.001) were the only significant independent predictors of ΔFPG (R²=0.48).

Conclusions

Our results suggest that the magnitude of FPG reduction after 6-month sulphonylurea treatment in addition to metformin in patients with type 2 diabetes is related to the variation in KCNQ1. The FPG response to sulphonylureas was significantly lower in carriers of the risk GG genotype.