Ser1369Ala variant in sulfonylurea receptor gene ABCC8 is associated with antidiabetic efficacy of gliclazide in Chinese type 2 diabetic patients

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

Background

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

Methods

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

Results

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

Conclusion

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

Advances in multi-omics study of biomarkers of glycolipid metabolism disorder

Glycolipid metabolism disorder are major threats to human health and life. Genetic, environmental, psychological, cellular, and molecular factors contribute to their pathogenesis. Several studies demonstrated that neuroendocrine axis dysfunction, insulin resistance, oxidative stress, chronic inflammatory response, and gut microbiota dysbiosis are core pathological links associated with it. However, the underlying molecular mechanisms and therapeutic targets of glycolipid metabolism disorder remain to be elucidated. Progress in high-throughput technologies has helped clarify the pathophysiology of glycolipid metabolism disorder. In the present review, we explored the ways and means by which genomics, transcriptomics, proteomics, metabolomics, and gut microbiomics could help identify novel candidate biomarkers for the clinical management of glycolipid metabolism disorder. We also discuss the limitations and recommended future research directions of multi-omics studies on these diseases.

On the Verge of Precision Medicine in Diabetes

The epidemic of type 2 diabetes (T2D) is a significant global public health challenge and a major cause of morbidity and mortality. Despite the recent proliferation of pharmacological agents for the treatment of T2D, current therapies simply treat the symptom, i.e. hyperglycemia, and do not directly address the underlying disease process or modify the disease course. This article summarizes how genomic discovery has contributed to unraveling the heterogeneity in T2D, reviews relevant discoveries in the pharmacogenetics of five commonly prescribed glucose-lowering agents, presents evidence supporting how pharmacogenetics can be leveraged to advance precision medicine, and calls attention to important research gaps to its implementation to guide treatment choices.

Pharmacogenomics of sulfonylureas in type 2 diabetes mellitus; a systematic review

Purpose

Genetic factors have a role in response to a target medication (personalized medicine). This study aimed to review available evidence about the relationship between gene variants and therapeutic response to sulfonylureas in type 2 diabetes, systematically.

Methods

An extensive search was done in Scopus, PubMed, and Web of Science with specific search strategy in the field from the beginning until the 1st of Jan. 2021. After sending records to endnote software and removing duplicate records remained documents were screened by title and abstract. Full texts of remained documents were assessed after removing un-related records. Required data was extracted from remained documents and records were categorized according to gene/SNP studied.

Results

Finally, 26 studies with 9170 T2DM patients with a mean age of 59.47 ± 6.67 (49.7-75.2 years) remained. The most contribution was from China, Slovakia and Greece, respectively and the most genes studied were CYP2C9, KCNJ11, and both KCNQ1 and ABCC8 with 10, 7, and 4 articles, respectively. Also, rs1799853 and rs1057910 (each with seven studies), rs5219 with six studies and CYP2C9*1(with four articles), respectively were the most common variants investigated. Studies about each gene obtained different positive or negative results and were not consistent.

Conclusion

Considering heterogeneity between SFUs pharmacogenomic studies regarding the method, sample size, population, gene/variant studied, and outcome and findings, these studies are not conclusive and need further studies.

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.

Quantile-Dependent Heritability of Glucose, Insulin, Proinsulin, Insulin Resistance, and Glycated Hemoglobin

BACKGROUND

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., insulin resistance) is high or low relative to its distribution.

METHODS

Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for fasting glucose concentrations in 6,453 offspring-parent pairs from the Framingham Heart Study.

RESULTS

Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), increased 0.0045 ± 0.0007 (p = 8.8 × 10-14) for each 1% increment in the fasting glucose distribution, that is, h2 ± SE were 0.057 ± 0.021, 0.095 ± 0.024, 0.146 ± 0.019, 0.293 ± 0.038, and 0.456 ± 0.061 at the 10th, 25th, 50th, 75th, and 90th percentiles of the fasting glucose distribution, respectively. Significant increases in quantile-specific heritability were also suggested for fasting insulin (p = 1.2 × 10-6), homeostatic model assessment of insulin resistance (HOMA-IR, p = 5.3 × 10-5), insulin/glucose ratio (p = 3.9 × 10-5), proinsulin (p = 1.4 × 10-6), proinsulin/insulin ratio (p = 2.7 × 10-5), and glucose concentrations during a glucose tolerance test (p = 0.001), and their logarithmically transformed values.

DISCUSSION/CONCLUSION

These findings suggest alternative interpretations to precision medicine and gene-environment interactions, including alternative interpretation of reported synergisms between ACE, ADRB3, PPAR-γ2, and TNF-α polymorphisms and being born small for gestational age on adult insulin resistance (fetal origin theory), and gene-adiposity (APOE, ENPP1, GCKR, IGF2BP2, IL-6, IRS-1, KIAA0280, LEPR, MFHAS1, RETN, TCF7L2), gene-exercise (INS), gene-diet (ACSL1, ELOVL6, IRS-1, PLIN, S100A9), and gene-socioeconomic interactions.

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.

Current progress in pharmacogenomics of Type 2 diabetes: A systemic overview

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a prevalent disease with incidences increasing globally at a rapid rate. The goal of T2DM treatment is to control glucose levels and prevent the aggravation of glycemic symptoms.

TREATMENT OPTIONS

T2DM regimen include metformin as the first-line, with sulfonylurea, thiazolidinedione (TZD), GLP-1, DPP4I, and SGLT2 inhibitor as the second-line treatment options. However, even with a multitude of choices, patient-to-patient variability due to pharmacogenomic differences still prevail.

CONCLUSION

This review aims to discuss the responses of the major T2DM medications influenced by pharmacogenomics and investigate improved personalized therapy for T2DM patients.

Genetic Variants Associated With Intraparenchymal Hemorrhage Progression After Traumatic Brain Injury

IMPORTANCE

Intracerebral hemorrhage progression is associated with unfavorable outcome after traumatic brain injury (TBI). No effective treatments are currently available. This secondary injury process reflects an extreme form of vasogenic edema and blood-brain barrier breakdown. The sulfonylurea receptor 1-transient receptor potential melastatin 4 (SUR1-TRPM4) cation channel is a key underlying mechanism. A phase 2 trial of SUR1-TRPM4 inhibition in contusional TBI is ongoing, and a phase 3 trial is being designed. Targeted identification of patients at increased risk for hemorrhage progression may inform prognostication, trial design (including patient selection), and ultimately treatment response.

OBJECTIVE

To determine whether ABCC8 (SUR1) and TRPM4 genetic variability are associated with intraparenchymal hemorrhage (IPH) progression after severe TBI, based on the putative involvement of the SUR1-TRPM4 channel in this pathophysiology.

DESIGN, SETTING, AND PARTICIPANTS

In this genetic association study, DNA was extracted from 416 patients with severe TBI prospectively enrolled from a level I trauma academic medical center from May 9, 2002, to August 8, 2014. Forty ABCC8 and TRPM4 single-nucleotide variants (SNVs) were genotyped (multiplex, unbiased). Data were analyzed from January 7, 2020, to May 3, 2021.

MAIN OUTCOMES AND MEASURES

Primary analyses addressed IPH progression at 6, 24, and 120 hours in patients without acute craniectomy (n = 321). Multivariable regressions and receiver operating characteristic curves assessed SNV and haplotype associations with progression. Spatial modeling and functional predictions were determined using standard software.

RESULTS

Of the 321 patients included in the analysis (mean [SD] age, 37.0 [16.3] years; 247 [76.9%] male), IPH progression occurred in 102. Four ABCC8 SNVs were associated with markedly increased odds of progression (rs2237982 [odds ratio (OR), 2.60-3.80; 95% CI, 1.14-5.90 to 1.80-8.02; P = .02 to P < .001], rs2283261 [OR, 3.37-4.77; 95% CI, 1.07-10.77 to 1.89-12.07; P = .04 to P = .001], rs3819521 [OR, 2.96-3.92; 95% CI, 1.13-7.75 to 1.42-10.87; P = .03 to P = .009], and rs8192695 [OR, 3.06-4.95; 95% CI, 1.02-9.12 to 1.67-14.68]; P = .03-.004). These are brain-specific expression quantitative trait loci (eQTL) associated with increased ABCC8 messenger RNA levels. Regulatory annotations revealed promoter and enhancer marks and strong and/or active brain-tissue transcription, directionally consistent with increased progression. Three SNVs (rs2283261, rs2237982, and rs3819521) in this cohort have been associated with intracranial hypertension. Four TRPM4 SNVs were associated with decreased IPH progression (rs3760666 [OR, 0.40-0.49; 95% CI, 0.19-0.86 to 0.27-0.89; P = .02 to P = .009], rs1477363 [OR, 0.40-0.43; 95% CI, 0.18-0.88 to 0.23-0.81; P = .02 to P = .006], rs10410857 [OR, 0.36-0.41; 95% CI, 0.20-0.67 to 0.20-0.85; P = .02 to P = .001], and rs909010 [OR, 0.27-0.40; 95% CI, 0.12-0.62 to 0.16-0.58; P = .002 to P < .001]). Significant SNVs in both genes cluster downstream, flanking exons encoding the receptor site and SUR1-TRPM4 binding interface. Adding genetic variation to clinical models improved receiver operating characteristic curve performance from 0.6959 to 0.8030 (P = .003).

CONCLUSIONS AND RELEVANCE

In this genetic association study, 8 ABCC8 and TRPM4 SNVs were associated with IPH progression. Spatial clustering, brain-specific eQTL, and regulatory annotations suggest biological plausibility. These findings may have important implications for neurocritical care risk stratification, patient selection, and precision medicine, including an upcoming phase 3 trial design for SUR1-TRPM4 inhibition in severe TBI.

Association of common genetic variants of KCNJ11 gene with the risk of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a multifactorial polygenic disease. Potassium inwardly-rectifying channel, subfamily J, member 11 (KCNJ11) gene mutations can result in susceptibility of T2DM. The aim of this study is to investigate the relationship between risk of T2DM and its complications (retinopathy & renal) and polymorphisms rs5210 and rs5215 of the KCNJ11 gene in a group of Iranian population. In this case-control study, 111 Iranian patients with T2DM and 82 control subjects were genotyped for each polymorphism by polymerase chain reaction (PCR) and Sanger Sequencing methods. Frequencies of genotypes of rs5210 polymorphism among subjects with and without diabetes mellitus were 53.15% vs. 51.22% for GG and 37.84% vs. 42.68% for AG (p = 0.7), respectively. Corresponding frequencies for rs5215 polymorphism among diabetics and non-diabetics were 13.51% vs. 13.41% for CC and 50.45% vs. 37.80% for CT (p = 0.2). G allele carriers (rs5210 polymorphism) and C allele carriers (rs5215 polymorphism) had the same frequency among diabetics and non-diabetics (p = 0.9 for G allele and p = 0.2 for C allele). Our results suggested that none of the polymorphisms of KCNJ11, rs5210 (p = 0.7) and rs5215 (p = 0.2), were significantly associated with T2DM. Only, the relationship between CT genotype of rs5215 and retinopathy (p = 0.01) showed a borderline significant association.

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.

Could personalised risk prediction for type 2 diabetes using polygenic risk scores direct prevention, enhance diagnostics, or improve treatment?

Over the past three decades, the number of people globally with diabetes mellitus has more than doubled. It is estimated that by 2030, 439 million people will be suffering from the disease, 90-95% of whom will have type 2 diabetes (T2D). In 2017, 5 million deaths globally were attributable to T2D, placing it in the top 10 global causes of death. Because T2D is a result of both genetic and environmental factors, identification of individuals with high genetic risk can help direct early interventions to prevent progression to more serious complications. Genome-wide association studies have identified ~400 variants associated with T2D that can be used to calculate polygenic risk scores (PRS). Although PRSs are not currently more accurate than clinical predictors and do not yet predict risk with equal accuracy across all ethnic populations, they have several potential clinical uses. Here, we discuss potential usages of PRS for predicting T2D and for informing and optimising interventions. We also touch on possible health inequality risks of PRS and the feasibility of large-scale implementation of PRS in clinical practice. Before PRSs can be used as a therapeutic tool, it is important that further polygenic risk models are derived using non-European genome-wide association studies to ensure that risk prediction is accurate for all ethnic groups. Furthermore, it is essential that the ethical, social and legal implications of PRS are considered before their implementation in any context.

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.

Association between ABCC8 Ala1369Ser Polymorphism (rs757110 T/G) and Type 2 Diabetes Risk in an Iranian Population: A Case-Control Study

OBJECTIVE

Glucose metabolism increases ATP/ADP ratio within the β-cells and causes ATP-sensitive K+ (KATP) channel closure and consequently insulin secretion. The enhanced activity of the channel may be a mechanism contributing to the reduced first-phase of insulin secretion observed in T2DM. There is no study to date in the Kurdish ethnic group regarding the relationship between SNP Ala1369Ser (rs757110 T/G) of SUR1 gene and T2DM, and additionally, the results of this association in other populations are inconsistent. Therefore, our aim in this study was to explore the possible association between SNP Ala1369Ser and type 2 diabetes in an Iranian Kurdish ethnic group.

METHODS

In this study, we checked out the frequency of alleles and genotypes of SNP Ala1369Ser in T2DM individuals (207 patients; men/women: 106/101) and non-T2DM subjects (201 controls; men/women: 97/104), and their effects on anthropometric, clinical, and biochemical parameters. Genomic DNA was extracted from the leukocytes of blood specimens using a standard method. We amplified the ABCC8 rs757110 polymorphic site (T/G) using a polymerase chain reaction (PCR) method and a designed primer pair. To perform the PCR-RFLP method, the amplicons were subjected to restriction enzymes and the resulting fragments separated by gel electrophoresis.

RESULTS

The frequency of the G-allele of Ala1369Ser polymorphism was significantly (0.01) higher in the case group than the control group (19% vs. 9%, respectively). In the dominant model (TT vs. TG+GG), there was a significant relationship between this SNP and an increased risk of T2DM (P = 0.00). T2DM patients with TG+GG genotypes had significantly higher fasting plasma insulin and HOMA-IR than those who had the TT genotype (P = 0.02 and 0.01, respectively).

CONCLUSION

Our study is the first study to investigate the association between Ala1369Ser ABCC8 genetic variation and T2DM in the Kurdish population of western Iran. The obtained results clearly show that Ala1369Ser polymorphism of ABCC8 is associated with an increased risk of T2DM in this population.

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.

Pharmacogenetics of hypoglycemia associated with sulfonylurea therapy in usual clinical care

Hypoglycemia is a common complication among type 2 diabetes mellitus (T2DM) patients receiving sulfonylurea therapy. The aim of this study was to determine if genetic contributions to sulfonylurea pharmacokinetics or pharmacodynamics substantially affect the risk of hypoglycemia in these patients. In a retrospective case-control study in European American patients with T2DM, we examined the potential association between CYP2C9 reduced function variants and sulfonylurea-related hypoglycemia. We also explored the relationship between sulfonylurea-related hypoglycemia and several candidate genetic variants previously reported to alter the response to sulfonylureas. We detected no evidence of association between CYP2C9 reduced function alleles or any of the candidate genetic variants and sulfonylurea-related hypoglycemia. In conclusion, we identified no clinically significant predictors of hypoglycemia among genes associated with sulfonylurea pharmacokinetics or pharmacodynamics.

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.

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.

"H" for Heterogeneity in the Algorithm for Type 2 Diabetes Management

PURPOSE OF REVIEW

Genetic, socioeconomic and clinical features vary considerably among individuals with type 2 diabetes (T2D) influencing disease development, progression and response to therapy. Although a patient-centred approach to pharmacologic therapy of T2D is widely recommended, patients are often treated similarly, irrespective of the differences that may affect therapeutic response. Addressing the heterogeneity of T2D is a major task of diabetes research to lower the high rate of treatment failure as well as to reduce the risk of long-term complications.

RECENT FINDINGS

A pathophysiology-based clustering system seems the most promising to help in the stratification of diabetes in terms of complication risk and response to treatment. This urges for clinical studies looking at novel biomarkers related to the different metabolic pathways of T2D and able to inform about the therapeutic cluster of each patient. Here, we review the main settings of diabetes heterogeneity, to what extent it has been already addressed and the current gaps in knowledge towards a personalized therapeutic approach that considers the distinctive features of each patient.

The Importance of Precision Medicine in Type 2 Diabetes Mellitus (T2DM): From Pharmacogenetic and Pharmacoepigenetic Aspects

BACKGROUND

Type 2 Diabetes Mellitus (T2DM) is a worldwide disorder as the most important challenges of health-care systems. Controlling the normal glycaemia greatly profit long-term prognosis and gives explanation for early, effective, constant, and safe intervention.

MATERIAL AND METHODS

Finding the main genetic and epigenetic profile of T2DM and the exact molecular targets of T2DM medications can shed light on its personalized management. The comprehensive information of T2DM was earned through the genome-wide association study (GWAS) studies. In the current review, we represent the most important candidate genes of T2DM like CAPN10, TCF7L2, PPAR-γ, IRSs, KCNJ11, WFS1, and HNF homeoboxes. Different genetic variations of a candidate gene can predict the efficacy of T2DM personalized strategy medication.

RESULTS

SLCs and AMPK variations are considered for metformin, CYP2C9, KATP channel, CDKAL1, CDKN2A/2B and KCNQ1 for sulphonylureas, OATP1B, and KCNQ1 for repaglinide and the last but not the least ADIPOQ, PPAR-γ, SLC, CYP2C8, and SLCO1B1 for thiazolidinediones response prediction.

CONCLUSION

Taken everything into consideration, there is an extreme need to determine the genetic status of T2DM patients in some known genetic region before planning the medication strategies.

Genetic Risk Scores for Diabetes Diagnosis and Precision Medicine

During the last decade, there have been substantial advances in the identification and characterization of DNA sequence variants associated with individual predisposition to type 1 and type 2 diabetes. As well as providing insights into the molecular, cellular, and physiological mechanisms involved in disease pathogenesis, these risk variants, when combined into a polygenic score, capture information on individual patterns of disease predisposition that have the potential to influence clinical management. In this review, we describe the various opportunities that polygenic scores provide: to predict diabetes risk, to support differential diagnosis, and to understand phenotypic and clinical heterogeneity. We also describe the challenges that will need to be overcome if this potential is to be fully realized.

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

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

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

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

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

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

Reflections on the sulphonylurea story: A drug class at risk of extinction or a drug class worth reviving?

The role of sulphonylureas (SUs) in modern clinical practice poses ongoing clinical debate. With the advent of newer agents in diabetes management, there is an increasing shift away from the prescribing of SUs, but not necessarily to more effective agents. This review provides a different perspective on the debate, reflecting in depth upon the physiology of SUs, drawing on insights gained from monogenic diabetes to highlight the potential benefit of lower doses of SUs, and the probable benefit of gliclazide over most other, if not all SUs, in terms of sulphonylurea failure and cardiovascular outcomes.

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.

The Continuing Evolution of Precision Health in Type 2 Diabetes: Achievements and Challenges

PURPOSE OF REVIEW

The purpose of this review was to summarize recent advances in the genomics of type 2 diabetes (T2D) and to highlight current initiatives to advance precision health.

RECENT FINDINGS

Generation of multi-omic data to measure each of the "biologic layers," developments in describing genomic function and annotation in T2D relevant tissue, along with the increasing recognition that T2D is a heterogeneous disease, and large-scale collaborations have all contributed to advancing our understanding of the molecular basis of T2D. Substantial advances have been made in understanding the molecular basis of T2D pathogenesis, such that precision health diabetes is increasingly becoming a reality. For precision diabetes to become a routine in clinical and public health, additional large-scale multi-omic initiatives are needed along with better assessment of our environment to delineate an individual's diabetes subtype for improved detection and management.

Regionally clustered ABCC8 polymorphisms in a prospective cohort predict cerebral oedema and outcome in severe traumatic brain injury

OBJECTIVE

ABCC8 encodes sulfonylurea receptor 1, a key regulatory protein of cerebral oedema in many neurological disorders including traumatic brain injury (TBI). Sulfonylurea-receptor-1 inhibition has been promising in ameliorating cerebral oedema in clinical trials. We evaluated whether ABCC8 tag single-nucleotide polymorphisms predicted oedema and outcome in TBI.

METHODS

DNA was extracted from 485 prospectively enrolled patients with severe TBI. 410 were analysed after quality control. ABCC8 tag single-nucleotide polymorphisms (SNPs) were identified (Hapmap, r²>0.8, minor-allele frequency >0.20) and sequenced (iPlex-Gold, MassArray). Outcomes included radiographic oedema, intracranial pressure (ICP) and 3-month Glasgow Outcome Scale (GOS) score. Proxy SNPs, spatial modelling, amino acid topology and functional predictions were determined using established software programs.

RESULTS

Wild-type rs7105832 and rs2237982 alleles and genotypes were associated with lower average ICP (β=-2.91, p=0.001; β=-2.28, p=0.003) and decreased radiographic oedema (OR 0.42, p=0.012; OR 0.52, p=0.017). Wild-type rs2237982 also increased favourable 3-month GOS (OR 2.45, p=0.006); this was partially mediated by oedema (p=0.03). Different polymorphisms predicted 3-month outcome: variant rs11024286 increased (OR 1.84, p=0.006) and wild-type rs4148622 decreased (OR 0.40, p=0.01) the odds of favourable outcome. Significant tag and concordant proxy SNPs regionally span introns/exons 2-15 of the 39-exon gene.

CONCLUSIONS

This study identifies four ABCC8 tag SNPs associated with cerebral oedema and/or outcome in TBI, tagging a region including 33 polymorphisms. In polymorphisms predictive of oedema, variant alleles/genotypes confer increased risk. Different variant polymorphisms were associated with favourable outcome, potentially suggesting distinct mechanisms. Significant polymorphisms spatially clustered flanking exons encoding the sulfonylurea receptor site and transmembrane domain 0/loop 0 (juxtaposing the channel pore/binding site). This, if validated, may help build a foundation for developing future strategies that may guide individualised care, treatment response, prognosis and patient selection for clinical trials.

Precision medicine in the management of type 2 diabetes

The study of type 2 diabetes has been driven by advances in human genetics, epigenetics, biomarkers, mechanistic studies, and large clinical trials, enabling new insights into disease susceptibility, pathophysiology, progression, and development of complications. Simultaneously, several new drug classes with different mechanisms of action have been introduced over the past two decades, accompanied by data about cardiovascular safety and non-glycaemic outcomes. In this Review, we critically examine the progress and integration of this new science into clinical practice, and review opportunities for enabling the use of precision medicine in the diagnosis and treatment of type 2 diabetes. We contrast the success in delivering personalised medicine for monogenic diabetes with the greater challenge of providing a precision medicine approach for type 2 diabetes, highlighting gaps, limitations, and areas requiring further study.

Precision medicine in diabetes prevention, classification and management

Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best-known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi-omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.

Genotypic and Phenotypic Factors Influencing Drug Response in Mexican Patients With Type 2 Diabetes Mellitus

The treatment of Type 2 Diabetes Mellitus (T2DM) consists primarily of oral antidiabetic drugs (OADs) that stimulate insulin secretion, such as sulfonylureas (SUs) and reduce hepatic glucose production (e.g., biguanides), among others. The marked inter-individual differences among T2DM patients’ response to these drugs have become an issue on prescribing and dosing efficiently. In this study, fourteen polymorphisms selected from Genome-wide association studies (GWAS) were screened in 495 T2DM Mexican patients previously treated with OADs to find the relationship between the presence of these polymorphisms and response to the OADs. Then, a novel association screening method, based on global probabilities, was used to globally characterize important relationships between the drug response to OADs and genetic and clinical parameters, including polymorphisms, patient information, and type of treatment. Two polymorphisms, ABCC8-Ala1369Ser and KCNJ11-Glu23Lys, showed a significant impact on response to SUs. Heterozygous ABCC8-Ala1369Ser variant (A/C) carriers exhibited a higher response to SUs compared to homozygous ABCC8-Ala1369Ser variant (A/A) carriers (p-value = 0.029) and to homozygous wild-type genotypes (C/C) (p-value = 0.012). The homozygous KCNJ11-Glu23Lys variant (C/C) and wild-type (T/T) genotypes had a lower response to SUs compared to heterozygous (C/T) carriers (p-value = 0.039). The screening of OADs response related genetic and clinical factors could help improve the prescribing and dosing of OADs for T2DM patients and thus contribute to the design of personalized treatments.

Pharmacogenetics of oral antidiabetic therapy

Type 2 diabetes prevalence is still on the rise worldwide. Antidiabetic drugs are widely prescribed to patients with Type 2 diabetes. Most patients start with metformin which is mostly well tolerated. However, a high percentage of patients fail to achieve glycemic control. The effectiveness of metformin as well as most other antidiabetic drugs depends among other factors on interindividual genetic differences that are up to now ignored in the treatment of Type 2 diabetes. Interestingly, many genes influencing the effectiveness of antidiabetic drugs are Type 2 diabetes risk genes making matters worse. Here, we shed light on these interindividual genetic differences.

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.

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.

Factors of primary and secondary sulfonylurea failure in type 2 diabetic subjects

BACKGROUND

The aim of the present study was to investigate the value of clinical characteristics in predicting sulfonylurea (SU) treatment responses.

METHODS

All 747 subjects in the present study were from the Xiaoke Pill Clinical Trial evaluating the safety and efficacy of SU. Subjects had the same initial dose of glibenclamide and drug doses were adjusted every 4 weeks during the 48-week follow-up period. Primary SU failure was defined as a <10% reduction in fasting plasma glucose (FPG) at the end of Week 4 from randomization, whereas secondary SU failure was defined as a consecutive confirmed level of FPG >7 mmol/L.

RESULTS

Kaplan-Meier survival analysis revealed that lower baseline basal disposition index (DI _b ) and higher FPG predict secondary SU failure. Inversely, higher baseline DI _b and lower FPG predict primary SU failure. Primary SU failure can predict secondary SU failure. The combination of lower baseline DI _b with primary SU failure is a better predictor of secondary SU failure than lower baseline DI _b or primary SU failure alone.

CONCLUSIONS

Patients with good glycemic control and higher β-cell reserve at entry are more likely to experience primary SU failure but are less likely to experience secondary SU failure. By combining baseline DI _b with initial response at the first month of treatment, we can get quick information about the long-term efficacy of SU treatment.

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.

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.

Evolving to Personalized Medicine for Type 2 Diabetes

Type 2 diabetes is an expensive public health problem threatening society at many levels. Despite many advances in classification of diabetes, we're still in early stages of developing an etio-pathologic ontology of diabetes. Recognizing the various biologic and social determinants of disease outcomes, precision medicine applies to medical interventions as well as psychosocial measures, nutrition, and exercise that may also affect individuals differently. Using this highly personalized approach, one hopes to achieve cost-effective care. The striking evolution in generating "Big Data," Biomarker Fingerprints, and the Internet of Things will force all clinicians to be familiar with the terminology and understand the clinical relevance.

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.