TCF7L2 and therapeutic response to sulfonylureas in patients with type 2 diabetes. BMC Med Genet. 2011;12:30. [PMID: 21349175 PMCID: PMC3051886 DOI: 10.1186/1471-2350-12-30]

Pharmacometabolomics of sulfonylureas in patients with type 2 diabetes: a cross-sectional study

Background

Sulfonylureas have been a longstanding pharmacotherapy in the management of type 2 diabetes, with potential benefits beyond glycemic control. Although sulfonylureas are effective, interindividual variability exists in drug response. Pharmacometabolomics is a potent method for elucidating variations in individual drug response. Identifying unique metabolites associated with treatment response can improve our ability to predict outcomes and optimize treatment strategies for individual patients. Our objective is to identify metabolic signatures associated with good and poor response to sulfonylureas, which could enhance our capability to anticipate treatment outcome.

Methods

In this cross-sectional study, clinical and metabolomics data for 137 patients with type 2 diabetes who are taking sulfonylurea as a monotherapy or a combination therapy were obtained from Qatar Biobank. Patients were empirically categorized according to their glycosylated hemoglobin levels into poor and good responders to sulfonylureas. To examine variations in metabolic signatures between the two distinct groups, we have employed orthogonal partial least squares discriminant analysis and linear models while correcting for demographic confounders and metformin usage.

Results

Good responders showed increased levels of acylcholines, gamma glutamyl amino acids, sphingomyelins, methionine, and a novel metabolite 6-bromotryptophan. Conversely, poor responders showed increased levels of metabolites of glucose metabolism and branched chain amino acid metabolites.

Conclusion

The results of this study have the potential to empower our knowledge of variability in patient response to sulfonylureas, and carry significant implications for advancing precision medicine in type 2 diabetes management.

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.

Effects of the TCF7L2 and KCNQ1 common variant on sulfonylurea response in type 2 diabetes mellitus patients: a preliminary pharmacogenetic study

Background

Type 2 diabetes mellitus (T2DM) is a common chronic condition characterized by high blood glucose levels which is caused by genetic and environmental factors. Currently, pharmacogenomics (PGx) is anticipated to enable the development of personalized treatment in a wide range of health issues. Sulfonylureas (SFUs) are among the oral anti-diabetic drugs that are very popular due to their low cost. Genetic variants in transcription factor 7 like 2 (TCF7L2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have been reported for altered therapeutic response to sulfonylurea. The aim of the present study is to evaluate any association between common genetic variant of the TCF7L2 and KCNQ1 (rs7903146 and rs2237892, respectively) and the response to sulfonylurea in a group of Iranian patients for the first time.

Methods

Genotyping was carried out in 30 T2DM patients who received sulfonylurea treatment for more than two months in addition to previous medication using the Sanger sequencing method.

Results

In 30 T2DM patients who received SFUs treatment, 60%, 33.3% and 6.7% had CC, CT and TT genotypes, respectively. After treatment, adjusted fasting blood sugar (FBS) mean reduction level in CT and TT carriers was lower than CC carriers. Adjusted hemoglobin A1c (HbA1c) mean reduction level was also lower in CT and TT compared with CC carriers, but, none of these differences were statistically significant. Genotype frequencies of TT, CT and CC genotypes of rs2237892 variant of KCNQ1 gene were 0 (0%), 3 (10%) and 27 (90%) respectively. Patients with CT and CC genotypes of rs2237892 variant had also similar changes in FBS (P=0.200) and HbA1c (P=0.436) after treatment with SFUs.

Conclusions

Genotypes of TCF7L2 and KCNQ1 common variant did not show any impact on the treatment response among T2DM patients receiving SFUs.

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.

TCF7L2 rs7903146 C>T gene polymorphism is not associated with hypoglycemia in sulfonylurea-treated type 2 diabetic patients

Objectives

Hypoglycemia is the most common adverse effect of sulfonylureas (SUs) and a major concern when using these drugs. Transcription factor 7-like 2 (TCF7L2) rs7903146 C>T polymorphism is an established and well characterized genetic marker of type 2 diabetes (T2DM) risk. The aim of the present study was to analyze the potential association of TCF7L2 rs7903146 C>T polymorphism with SU-induced hypoglycemia in a well characterized cohort of SU-treated patients previously genotyped for cytochrome P450 2C9 (CYP2C9) and P450 oxidoreductase (POR).

Methods

The study group consisted of 176 SU-treated T2DM patients of whom 92 had experienced at least one drug-associated hypoglycemic event. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used for TCF7L2 rs7903146 genotyping.

Results

TCF7L2 rs7903146 C>T genotype and allele frequency did not differ between cases and controls (p=0.745 and 0.671, respectively). In logistic regression analysis adjusted for other factors affecting hypoglycemia, including CYP2C9 and POR genotypes, TCF7L2 rs7903146 C>T polymorphism did not increase the risk of hypoglycemia (OR=1.238, 95% C.I.=0.750–2.044, p=0.405).

Conclusions

TCF7L2 rs7903146 C>T polymorphism is not associated with SU-induced hypoglycemia. Identifying additional gene polymorphisms associated with SU-induced hypoglycemia is crucial for improving T2DM patient therapy with SUs.

TCF7L2 rs7903146 C>T gene polymorphism is not associated with hypoglycemia in sulfonylurea-treated type 2 diabetic patients

OBJECTIVES

Hypoglycemia is the most common adverse effect of sulfonylureas (SUs) and a major concern when using these drugs. Transcription factor 7-like 2 (TCF7L2) rs7903146 C>T polymorphism is an established and well characterized genetic marker of type 2 diabetes (T2DM) risk. The aim of the present study was to analyze the potential association of TCF7L2 rs7903146 C>T polymorphism with SU-induced hypoglycemia in a well characterized cohort of SU-treated patients previously genotyped for cytochrome P450 2C9 (CYP2C9) and P450 oxidoreductase (POR).

METHODS

The study group consisted of 176 SU-treated T2DM patients of whom 92 had experienced at least one drug-associated hypoglycemic event. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used for TCF7L2 rs7903146 genotyping.

RESULTS

TCF7L2 rs7903146 C>T genotype and allele frequency did not differ between cases and controls (p=0.745 and 0.671, respectively). In logistic regression analysis adjusted for other factors affecting hypoglycemia, including CYP2C9 and POR genotypes, TCF7L2 rs7903146 C>T polymorphism did not increase the risk of hypoglycemia (OR=1.238, 95% C.I.=0.750-2.044, p=0.405).

CONCLUSIONS

TCF7L2 rs7903146 C>T polymorphism is not associated with SU-induced hypoglycemia. Identifying additional gene polymorphisms associated with SU-induced hypoglycemia is crucial for improving T2DM patient therapy with SUs.

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.

Pharmacogenetic Aspects of Type 2 Diabetes Treatment

In this article, we analyze the role of different variants of the KCNJ11, TCF7L2, SLC22A1, SLC22A3, CYP2C9, CYP2C8, PPARγ genes polymorphisms in efficacy of diabetes mellitus pharmacotherapy. T allele of the KCNJ11 rs2285676 gene polymorphism and G allele of KCNJ11 rs5218 gene polymorphism are associated with the response to IDPP-4 therapy; the presence of KCNJ11 gene rs5210 polymorphism A allele is a predictor of poor response. The effect of rs7903146 polymorphism of TCF7L2 gene was evaluated on the response to treatment of patients taking linagliptin. Linagliptin significantly reduced HbA1c levels for all three rs7903146 genotypes (CC: –0.82 %; CT: –0.77 %; TT: –0.57 %). A significantly smaller effect of therapy was observed with the genotype with ТТ. The rs622342 polymorphism of SLC22A1 gene was studied in effectiveness of metformin. The researches demonstrated that carriers of variant AA had an average decrease of HbA1c of 0.53 %, heterozygous – decrease of 0.32 %, and carriers of a minor variant of SS had an increase of 0.2 % in the level of HbA1c. A significant effect of CYP2C9 polymorphisms on the pharmacokinetic parameters of PSM was noted. When studying the kinetics of glibenclamide, it was found that carriage of the allele *2 significantly reduces glibenclamide metabolism: homozygous carriers had clearance 90 % lower than homozygous carriers of the wild variant. The studies confirmed the association of the allelic variants of Thr394Thr and Gly482Ser of PPARγ gene with higher efficacy of the rosiglitazone. The data obtained from the analysis of the association of the Pro12Ala polymorphism of PPARγ gene and the response to therapy is contradictory. Thus the personalized approach, based on the knowledge of polymorphism options, will allow choosing the most effective drug with transparent kinetics for each individual patient.

Clinical and genetic predictors of secondary sulfonylurea failure in Type 2 diabetes patients: the SUCLINGEN study

Background: Due to several limitations in the study designs of sulfonylurea pharmacogenomics studies, we investigated the clinical and genetic predictors of secondary sulfonylurea failure in Type 2 diabetes patients. Materials & methods: Patients receiving the maximum sulfonylurea and metformin doses for >1 year were enrolled. Secondary sulfonylurea failure was defined as HbA1c >7.0% (>53 mmol/mol) after a 12-month follow-up. Results: By multivariate analysis, increased insulin resistance (HOMA2-IR), baseline HbA1c >7.0%, residing in eastern Peninsular Malaysia, and the CC genotype of rs757110 ABCC8 gene polymorphism were independent predictors of secondary sulfonylurea failure (p < 0.05) while sulfonylurea-induced hypoglycemia was protective against such failure (p < 0.05). Conclusion: Sulfonylurea does not benefit patients with an increased risk of secondary sulfonylurea failure.

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.

Effects of TCF7L2 rs7903146 variant on metformin response in patients with type 2 diabetes

The response to metformin, the most commonly used drug for the treatment of type 2 diabetes (T2D), is highly variable. The common variant rs7903146 C>T within the transcription factor 7-like 2 gene (TCF7L2) is the strongest genetic risk factor associated with T2D to date. In this study, we explored the effects of the TCF7L2 rs7903146 genotype on metformin response in T2D. The study included 86 newly diagnosed patients with T2D, incident users of metformin. Levels of fasting glucose, insulin, HbA1c, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, and anthropometric parameters were measured prior to metformin therapy, and 6 and 12 months after the treatment. Genotyping of the TCF7L2 rs7903146 was performed by the Sequenom MassARRAY® iPLEX® platform. At baseline, the diabetes risk allele (T) showed an association with lower triglyceride levels (p = 0.037). After 12 months of metformin treatment, the T allele was associated with 25.9% lower fasting insulin levels (95% CI 10.9-38.3%, p = 0.002) and 29.1% lower HOMA-IR index (95% CI 10.1-44.1%, p = 0.005), after adjustment for baseline values. Moreover, the T allele was associated with 6.7% lower fasting glucose levels (95% CI 1.1-12.0%, p = 0.021), adjusted for baseline glucose and baseline HOMA-%B levels, after 6 months of metformin treatment. This effect was more pronounced in the TT carriers who had 16.8% lower fasting glucose levels (95% CI 7.0-25.6%, p = 0.002) compared to the patients with CC genotype. Our results suggest that the TCF7L2 rs7903146 variant affects markers of insulin resistance and glycemic response to metformin in newly diagnosed patients with T2D within the first year of metformin treatment.

Single nucleotide polymorphisms in treatment of polycystic ovary syndrome: a systematic review

As 15-20% of reproductive aged females are suffering from polycystic ovary syndrome (PCOS), a large number of pharmacological preparations are frequently available in the market for the treatment of PCOS; however, they seem to be ineffective and cause undesirable side effects. This has emphasized the need to optimize dosage regimens for individualized treatment. The objective of this systematic review is to review single nucleotide polymorphisms (SNPs) associated with drugs used for the treatment of PCOS to understand pharmacogenetics variability of patients to drug response there by helping clinicians in designing tailored treatments and possibly reducing adverse drug reactions. A comprehensive electronic literature search was conducted to highlight some clinically relevant SNPs that act to influence PCOS and associated co-morbidities. A total of 16 studies were included in this review. These genetic variations can be used as a potential target for pharmacotherapy and pharmacogenetic clinical trials for better diagnosis, management, and treatment planning.

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.

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.

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10-8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis.

Study on the correlation between KCNJ11 gene polymorphism and metabolic syndrome in the elderly

The aim of the study was to examine the correlation between KCNJ11 gene polymorphism and metabolic syndrome in elderly patients. From January 2014 to January 2015, 54 elderly patients with metabolic syndrome were enrolled in this study as the observation group. During the same period, 46 healthy elderly individuals were enrolled in this study as the control group. KCNJ11 gene polymorphism (rs28502) was analyzed using polymerase chain reaction-restriction fragment length polymorphism. The expression levels of mRNA in different genotypes were detected using FQ-PCR. ELISA was used to evaluate the KCNJ11 protein expression in different genotypes. KCNJ11 gene polymorphism and metabolic syndrome was studied by measuring the blood pressure levels in patients with different genotypes. Three genotypes of KCNJ11 gene in rs28502 were CC, CT and TT. The CC, CT and TT genotype frequencies in healthy population were 8.5, 9.2 and 82.2%, respectively, while the genotype frequencies in patients with metabolic syndrome were 42.4, 49.8 and 7.8%, respectively. There were significant differences between groups (P≤0.05). However, the genotype frequencies of C/T in healthy individuals and metabolic syndrome patients were 35.3 and 38.3%, respectively. There were no significant differences between groups (P>0.05). FQ-PCR results showed that the KCNJ11 mRNA expression levels in the control and observation groups had no significant differences (P>0.05). However, the results obtained from ELISA analysis revealed that KCNJ11 protein expression level in the observation group was significantly higher than that in the control group (P<0.05). In conclusion, KCNJ11 gene polymorphism is associated with metabolic syndrome in the elderly. Elderly patients with the CC and TT genotypes are more likely to develop metabolic syndrome.

Using Personalized Medicine in the Management of Diabetes Mellitus

Diabetes mellitus is a worldwide problem with an immense pharmacoeconomic burden. The multifactorial and complex nature of the disease lends itself to personalized pharmacotherapeutic approaches to treatment. Variability in individual risk and subsequent development of diabetes has been reported in addition to differences in response to the many oral glucose lowering therapies currently available for diabetes pharmacotherapy. Pharmacogenomic studies have attempted to uncover the heritable components of individual variability in risk susceptibility and response to pharmacotherapy. We review the current pharmacogenomics evidence as it relates to common oral glucose lowering therapies and how they can be utilized in the management of polygenic and monogenic forms of diabetes. Evidence supports the use of genetic testing and personalized approaches to the treatment of monogenic diabetes of the young. The data are not as robust for the current application of pharmacogenetic approaches to the treatment of polygenic type 2 diabetes mellitus, but there are suggestions as to future applications in this regard. We reviewed pertinent primary literature sources as well as current evidence-based guidelines on diabetes management.

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.

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.

The Application of Genomics in Diabetes: Barriers to Discovery and Implementation

The emerging availability of genomic and electronic health data in large populations is a powerful tool for research that has drawn interest in bringing precision medicine to diabetes. In this article, we discuss the potential application of genomics to the prediction, prevention, and treatment of diabetes, and we use examples from other areas of medicine to illustrate some of the challenges involved in conducting genomics research in human populations and implementing findings in practice. At this time, a major barrier to the application of genomics in diabetes care is the lack of actionable genomic findings. Whether genomic information should be used in clinical practice requires a framework for evaluating the validity and clinical utility of this approach, an improved integration of genomic data into electronic health records, and the clinical decision support and educational resources for clinicians to use these data. Efforts to identify optimal approaches in all of these domains are in progress and may help to bring diabetes into the era of genomic 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.

Precision medicine: The future in diabetes care?

Personalized medicine aims at better targeting therapeutic intervention to the individual to maximize benefit and minimize harm. Type 2 diabetes (T2D) is a heterogeneous disease from a genetic, pathophysiological and clinical point of view. Thus, the response to any antidiabetic medication may considerably vary between individuals. Numerous glucose-lowering agents, with different mechanisms of action, have been developed, a diversified armamentarium that offers the possibility of a patient-centred therapeutic approach. In the current clinical practice, a personalized approach is only based upon phenotype, taking into account patient and disease individual characteristics. If this approach may help increase both efficacy and safety outcomes, there remains considerable room for improvement. In recent years, many efforts were taken to identify genetic and genotype SNP's (Single Nucleotide Polymorphism's) variants that influence the pharmacokinetics, pharmacodynamics, and ultimately the therapeutic response of oral glucose-lowering drugs. This approach mainly concerns metformin, sulphonylureas, meglitinides and thiazolidinediones, with only scarce data concerning gliptins and gliflozins yet. However, the contribution of pharmacogenetics and pharmacogenomics to personalized therapy still needs to mature greatly before routine clinical implementation is possible. This review discusses both opportunities and challenges of precision medicine and how this new paradigm may lead to a better individualized treatment of T2D.

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.

Association of KCNQ1 polymorphisms with gliclazide efficacy in Chinese type 2 diabetic patients

OBJECTIVES

To investigate the effects of KCNQ1 polymorphisms on the efficacy of gliclazide in type 2 diabetic patients.

MATERIALS AND METHODS

A total of 443 newly diagnosed type 2 diabetic patients were included in this study. After enrollment, patients went on an 8-week gliclazide monotherapy. Fasting plasma glucose (FPG) was measured before and after the treatment. Life-style information was collected by weekly follow-up. Genotyping of the two single-nucleotide polymorphisms was performed using the single base primer extension method. T-test, one-way analysis of variance, and Pearson χ-test were used to evaluate the effects of rs2237892 and rs2237897 on the FPG reduction and treatment success rate.

RESULTS

After 8 weeks of gliclazide therapy, the FPG decreased significantly from 10.9±2.8 to 7.4±2.2 mmol/l (P<0.001). Compared with the CC genotype, patients with CT or TT genotypes of rs2237897 achieved greater reduction in FPG (3.9±2.6 vs. 3.2±2.4 mmol/l, P=0.003; 33.9±19.0 vs. 27.7±17.4%, P<0.001) and a higher rate of treatment success (74.1 vs. 65.2%, P=0.042 for criterion 1; 61.1 vs. 44.5%, P<0.001 for criterion 2, respectively), whereas no significant difference was found in the FPG reduction and treatment success rate among different genotypes of rs2237892.

CONCLUSION

Our results indicated that a common variant of KCNQ1, rs2237897, was associated with the efficacy of gliclazide after 8-week monotherapy in Chinese newly diagnosed type 2 diabetic patients. The FPG reduction and treatment success rate were significantly higher in carriers of CT and TT genotypes.

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.

Genetics of drug response in type 2 diabetes

The introduction of several new drug groups into the treatment of type 2 diabetes in the past few decades leads to an increased requirement for an individualized treatment approach. A personalized treatment is important from the point of view of both efficacy and safety. Recent guidelines are based mainly on entirely phenotypic characteristics such as diabetes duration, presence of macrovascular complications, or risk of hypoglycemia with the use of individual drugs. So far, genetic knowledge is used to guide treatment in the monogenic forms of diabetes. With the accumulating pharmacogenetic evidence in type 2 diabetes, there are reasonable expectations that genetics might help in the adjustment of drug doses to reduce severe side effects, as well as to make better therapeutic choices among the drugs available for the treatment 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.

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.

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.

Untangling the interplay of genetic and metabolic influences on beta-cell function: Examples of potential therapeutic implications involving TCF7L2 and FFAR1

Deteriorating beta-cell function is a common feature of type 2 diabetes. In this review, we briefly address the regulation of beta-cell function, and discuss some of the main determinants of beta-cell failure. We will focus on the role of interactions between the genetic background and metabolic environment (insulin resistance, fuel supply and flux as well as metabolic signaling). We present data on the function of the strongest common diabetes risk variant, the single nucleotide polymorphism (SNP) rs7903146 in TCF7L2. As also mirrored by its interaction with glycemia on insulin secretion, this SNP in large part confers resistance against the incretin effect. Genetic influence on insulin secretion also interacts with free fatty acids, as evidenced by data on rs1573611 in FFAR1. Several medications marketed by now or currently under development for diabetes treatment engage these pathways, and therapeutic implications from these findings are soon to be expected.

Genetic susceptibility to type 2 diabetes and obesity: follow-up of findings from genome-wide association studies

Elucidating the underlying genetic variations influencing various complex diseases is one of the major challenges currently facing clinical genetic research. Although these variations are often difficult to uncover, approaches such as genome-wide association studies (GWASs) have been successful at finding statistically significant associations between specific genomic loci and disease susceptibility. GWAS has been especially successful in elucidating genetic variants that influence type 2 diabetes (T2D) and obesity/body mass index (BMI). Specifically, several GWASs have confirmed that a variant in transcription factor 7-like 2 (TCF7L2) confers risk for T2D, while a variant in fat mass and obesity-associated protein (FTO) confers risk for obesity/BMI; indeed both of these signals are considered the most statistically associated loci discovered for these respective traits to date. The discovery of these two key loci in this context has been invaluable for providing novel insight into mechanisms of heritability and disease pathogenesis. As follow-up studies of TCF7L2 and FTO have typically lead the way in how to follow up a GWAS discovery, we outline what has been learned from such investigations and how they have implications for the myriad of other loci that have been subsequently reported in this disease context.

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.

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.

SGLT2: a potential target for the pharmacogenetics of Type 2 diabetes?

The kidney has attracted the attention of diabetologists as an organ involved in the regulation of glucose homeostasis not only by gluconeogenesis, but also by renal glucose excretion. Sodium–glucose cotransporters (SGLTs), particularly SGLT2, are responsible for reabsorption of up to 99% of the filtered glucose. SGLT2 is coded by the SLC5A2 gene, which maps on chromosome 16. Pharmacological reduction of tubular glucose reabsorption results in improved glycemic control in Type 2 diabetic patients. Since the SGLTs reabsorb most of the filtered glucose (90%), it is not surprising that mutations in SLC5A2 cause familial renal glucosuria. A recent study pointed out a possible role of common genetic variation in SLC5A2 in the control of glucose homeostasis. SLC5A2 polymorphisms might therefore represent potential candidates for pharmacogenomic studies targeting the impact of these variants on the efficacy of antidiabetic treatment that is based on inhibition of SGLT2 activity.

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.

Lack of interaction of beta-cell-function-associated variants with hypertension on change in fasting glucose and diabetes risk: the Framingham Offspring Study

OBJECTIVE

To test whether pancreatic beta-cell genetic frailty and hypertension (HTN) interact in their associations with change over time in fasting glucose (ΔFG) or type 2 diabetes mellitus (T2D) risk.

METHODS AND RESULTS

We pooled data from 3471 Framingham Offspring Study participants into six ∼4-year periods (15 852 person-examinations; mean age 52; 54% women). We defined two genetic exposures reflecting beta-cell genetic risk burden: single nucleotide polymorphism (SNP) score counts of fasting glucose-associated and T2D-associated risk alleles at 16 and 33 putative beta-cell loci, respectively; and three HTN exposures: HTN versus no-HTN; treated versus untreated HTN; and five mutually exclusive antihypertensive categories (beta-blockers, thiazides, renin-angiotensin system agents, combinations, others) versus untreated HTN. We tested ∼4-year mean ΔFG or odds of T2D by per-risk allele score change and HTN category, seeking genetic score-by-HTN interaction. Genetic scores increased ∼4-year ΔFG (0.6  mg/dl per-risk allele; P = 8.9 × 10(-16)) and T2D-risk (∼17% per-risk allele; P = 2.1 × 10(-7)). As compared to no-HTN, HTN conferred higher ΔFG (2.6 versus 1.7 mg/dl; P < 0.0001) and T2D-risk [odds ratio (OR) = 2.9, 95% confidence interval (CI) 2.8-3.0; P < 0.0001]. As compared to untreated HTN, treated HTN conferred higher ΔFG (3.4 versus 3.0 mg/dl; P < 0.0001) and T2D-risk (OR = 1.4, 95% CI 1.3-1.5; P = 0.02). Beta-blockers (OR = 1.6, 95% CI 1.1-2.4), combinations (OR = 1.6, 95% CI 1.1-2.5), and others (OR = 2.0, 95% CI 1.4-2.9) increased T2D-risk (all P < 0.02). In joint models including interaction terms, all genetic score-by-HTN interaction terms were P value greater than 0.05. In joint models without interaction, fasting glucose-SNP or T2D-SNP genetic scores (both P < 0.001) and HTN (P < 0.0001) independently increased ΔFG or T2D-risk.

CONCLUSION

HTN, HTN treatment, and common fasting glucose-SNP genetic score/T2D-SNP genetic score independently predicted ΔFG and T2D incidence, but did not modify each other's association with ΔFG or T2D risk.

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.