Common polymorphisms of the peroxisome proliferator-activated receptor-gamma (Pro12Ala) and peroxisome proliferator-activated receptor-gamma coactivator-1 (Gly482Ser) and the response to pioglitazone in Chinese patients with type 2 diabetes mellitus

Correlation between PPARG Pro12Ala Polymorphism and Therapeutic Responses to Thiazolidinediones in Patients with Type 2 Diabetes: A Meta-Analysis

Background: Thiazolidinediones (TZDs) are a type of oral drug that are utilized for the treatment of type 2 diabetes mellitus (T2DM). They function by acting as agonists for a nuclear transcription factor known as peroxisome proliferator-activated receptor-gamma (PPAR-γ). TZDs, such as pioglitazone and rosiglitazone, help enhance the regulation of metabolism in individuals with T2DM by improving their sensitivity to insulin. Previous studies have suggested a relationship between the therapeutic efficacy of TZDs and the PPARG Pro12Ala polymorphism (C > G, rs1801282). However, the small sample sizes of these studies may limit their applicability in clinical settings. To address this limitation, we conducted a meta-analysis assessing the influence of the PPARG Pro12Ala polymorphism on the responsiveness of TZDs. Method: We registered our study protocol with PROSPERO, number CRD42022354577. We conducted a comprehensive search of the PubMed, Web of Science, and Embase databases, including studies published up to August 2022. We examined studies investigating the association between the PPARG Pro12Ala polymorphism and metabolic parameters such as hemoglobin A1C (HbA1C), fasting plasma glucose (FPG), triglyceride (TG), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and total cholesterol (TC). The mean difference (MD) and 95% confidence intervals (CIs) between pre- and post-drug administration were evaluated. The quality of the studies included in the meta-analysis was assessed by using the Newcastle-Ottawa Scale (NOS) tool for cohort studies. Heterogeneity across studies was assessed by using the I2 value. An I2 value greater than 50% indicated substantial heterogeneity, and a random-effects model was used for meta-analysis. If the I2 value was below 50%, a fixed-effects model was employed instead. Both Begg's rank correlation test and Egger's regression test were performed to detect publication bias, using R Studio software. Results: Our meta-analysis incorporated 6 studies with 777 patients for blood glucose levels and 5 studies with 747 patients for lipid levels. The included studies were published between 2003 and 2016, with the majority involving Asian populations. Five of the six studies utilized pioglitazone, while the remaining study employed rosiglitazone. The quality scores, as assessed with the NOS, ranged from 8 to 9. Patients carrying the G allele exhibited a significantly greater reduction in HbA1C (MD = -0.3; 95% CI = -0.55 to -0.05; p = 0.02) and FPG (MD = -10.91; 95% CI = -19.82 to -2.01; p = 0.02) levels compared to those with the CC genotype. Furthermore, individuals with the G allele experienced a significantly larger decrease in TG levels than those with the CC genotype (MD = -26.88; 95% CI = -41.30 to -12.46; p = 0.0003). No statistically significant differences were observed in LDL (MD = 6.69; 95% CI = -0.90 to 14.29; p = 0.08), HDL (MD = 0.31; 95% CI = -1.62 to 2.23; p = 0.75), and TC (MD = 6.4; 95% CI = -0.05 to 12.84; p = 0.05) levels. No evidence of publication bias was detected based on Begg's test and Egger's test results. Conclusions: This meta-analysis reveals that patients with the Ala12 variant in the PPARG Pro12Ala polymorphism are more likely to exhibit positive responses to TZD treatment in terms of HbA1C, FPG, and TG levels compared to those with the Pro12/Pro12 genotype. These findings suggest that genotyping the PPARG Pro12Ala in diabetic patients may be advantageous for devising personalized treatment strategies, particularly for identifying individuals who are likely to respond favorably to TZDs.

Renal insulin resistance in type 2 diabetes mellitus and progression of chronic kidney disease: potential pathogenic mechanisms

INTRODUCTION

A bidirectional association exists between insulin resistance (IR) and chronic kidney disease (CKD) in Type 2 Diabetes Mellitus (T2DM). Baseline measures of IR are predictive of CKD progression, and uremia in progressive CKD is itself, in turn, associated with a worsening of IR. Pre-clinical research reveals that intrinsic IR in glomerular podocytes and the renal tubule may serve as a pathogenic driver of CKD in T2DM.

AREAS COVERED

The present manuscript takes as its point of departure, the recently identified prognostic utility of severe insulin resistance as a predictor of CKD in T2DM. Findings from a series of studies describing the association of IR with pathological alterations in both established, and less commonly assessed dynamic measures of renal impairment are discussed. Drawing upon the pre-clinical mechanistic evidence base, the cellular and molecular basis of intrinsic renal IR as a promoter of CKD is considered.

EXPERT OPINION

Measurement of insulin sensitivity may add value to profiling of renal risk in T2DM. Rational selection of therapeutic strategies targeting the enhancement of insulin sensitivity merits special attention regarding the personalized management of CKD in insulin resistance predominant T2DM.

G Allele of the rs1801282 Polymorphism in PPARγ Gene Confers an Increased Risk of Obesity and Hypercholesterolemia, While T Allele of the rs3856806 Polymorphism Displays a Protective Role Against Dyslipidemia: A Systematic Review and Meta-Analysis

BACKGROUND

The relationships between the rs1801282 and rs3856806 polymorphisms in nuclear receptor peroxisome proliferator-activated receptor gamma (PPARγ) gene and obesity indexes as well as serum lipid levels have been extensively investigated in various studies, but the results were inconsistent and even contradictory.

METHODS

PubMed, Google Scholar, Embase, Cochrane Library, Web of Science, Wanfang, CNKI and VIP databases were searched for eligible studies. The random-effTPDEects model was used, and standardized mean difference (SMD) with 95% confidence interval (CI) was calculated to estimate the differences in obesity indexes and serum lipid levels between the subjects with different genotypes in a dominant model. Heterogeneity among studies was assessed by Cochran's x²-based Q-statistic test. Publication bias was identified by using Begg's test.

RESULTS

One hundred and twenty studies (70,317 subjects) and 33 studies (18,353 subjects) were identified in the analyses for the rs1801282 and rs3856806 polymorphisms, respectively. The G allele carriers of the rs1801282 polymorphism had higher levels of body mass index (SMD = 0.08 kg/m², 95% CI = 0.04 to 0.12 kg/m², p < 0.001), waist circumference (SMD = 0.12 cm, 95% CI = 0.06 to 0.18 cm, p < 0.001) and total cholesterol (SMD = 0.07 mmol/L, 95% CI = 0.02 to 0.11 mmol/L, p < 0.01) than the CC homozygotes. The T allele carriers of the rs3856806 polymorphism had lower levels of low-density lipoprotein cholesterol (SMD = -0.09 mmol/L, 95% CI = -0.15 to -0.03 mmol/L, p < 0.01) and higher levels of high-density lipoprotein cholesterol (SMD = 0.06 mmol/L, 95% CI = 0.02 to 0.10 mmol/L, p < 0.01) than the CC homozygotes.

CONCLUSIONS

The meta-analysis suggests that the G allele of the rs1801282 polymorphism confers an increased risk of obesity and hypercholesterolemia, while the T allele of the rs3856806 polymorphism displays a protective role against dyslipidemia, which can partly explain the associations between these polymorphisms and cardiovascular disease.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier [CRD42022319347].

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.

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.

Personalized approach for type 2 diabetes pharmacotherapy: where are we and where do we need to be?

INTRODUCTION

Cluster analysis has identified distinct groups of type 2 diabetes (T2D) subjects with distinct metabolic characteristics. Thus, personalizing pharmacologic therapy to individual phenotypic and pathophysiologic characteristics has potential to improve metabolic control and reduce risk of microvascular and macrovascular complications.

AREAS COVERED

The authors review the classification of T2D, genetic markers, pathophysiology and natural history of T2D, the ABCDE approach to therapy, the ADA/EASD stepwise approach to therapy, available antidiabetic agents, and provide a more rational therapeutic approach based upon pathophysiology and cardiovascular and renal outcome trials.

EXPERT OPINION

Although insulin resistance is the earliest detectable abnormality, overt T2D does not occur in the absence of progressive beta cell failure. Because of the complex etiology of T2D (Ominous Octet), initiation of therapy with combined agents that (i) target both insulin resistance and beta cell dysfunction and (ii) prevent macrovascular, as well as microvascular, complications will be required. The ratio of C-peptide at 120 minutes (OGTT) to baseline C-peptide predicts with high sensitivity who will respond to metformin, the response to glucose-lowering agents and provides a useful tool to guide optimal glucose lowering therapy.

PPARγ and Diabetes: Beyond the Genome and Towards Personalized Medicine

PURPOSE OF REVIEW

Full and partial synthetic agonists targeting the transcription factor PPARγ are contained in FDA-approved insulin-sensitizing drugs and used for the treatment of metabolic syndrome-related dysfunctions. Here, we discuss the association between PPARG genetic variants and drug efficacy, as well as the role of alternative splicing and post-translational modifications as contributors to the complexity of PPARγ signaling and to the effects of synthetic PPARγ ligands.

RECENT FINDINGS

PPARγ regulates the transcription of several target genes governing adipocyte differentiation and glucose and lipid metabolism, as well as insulin sensitivity and inflammatory pathways. These pleiotropic functions confer great relevance to PPARγ in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders. Accordingly, PPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue disorders and the related risk of insulin resistance and type 2 diabetes (T2D). Moreover, PPARγ alternative splicing isoforms-generating dominant-negative isoforms mainly expressed in human adipose tissue-have been related to impaired PPARγ activity and adipose tissue dysfunctions. Thus, multiple regulatory levels that contribute to PPARγ signaling complexity may account for the beneficial as well as adverse effects of PPARγ agonists. Further targeted analyses, taking into account all these aspects, are needed for better deciphering the role of PPARγ in human pathophysiology, especially in insulin resistance and T2D. The therapeutic potential of full and partial PPARγ synthetic agonists underlines the clinical significance of this nuclear receptor. PPARG mutations, polymorphisms, alternative splicing isoforms, and post-translational modifications may contribute to the pathogenesis of metabolic disorders, also influencing the responsiveness of pharmacological therapy. Therefore, in the context of the current evidence-based trend to personalized diabetes management, we highlight the need to decipher the intricate regulation of PPARγ signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.

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.

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

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

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

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

Association between Pro12Ala polymorphism and albuminuria in type 2 diabetic nephropathy

AIMS/INTRODUCTION

Diabetic nephropathy (DN) is a complication of diabetes mellitus that is characterized by the gradual loss of kidney function, which results in increased levels of albumin in the urine. The Pro12Ala polymorphism in the peroxisome proliferator-activated receptor-γ2 gene has been confirmed to improve insulin sensitivity, but its association with susceptibility to DN in patients with type 2 diabetes remains inconclusive.

MATERIALS AND METHODS

To examine whether the Pro12Ala polymorphism leads to the development of DN, a case-control study was carried out in 554 patients with type 2 diabetes. The genotypes of Pro12Ala polymorphism of the peroxisome proliferator-activated receptor gamma 2 gene were analyzed by real-time polymerase chain reaction with TaqMan® probe genotyping assay in all patients.

RESULTS

The mean age of the study population was 57.7 ± 8.8 years, with average diabetes duration of 12.8 ± 6.9 years. The prevalence of albuminuria was 43.5%. The frequency of genotype Pro12Pro, Pro12Ala and Ala12Ala genotype were 92.6%, 7.0%, 0.4% in our study population, and 90.4%, 8.9% and 0.7% in normal urinary albumin-to-creatinine ratio group, respectively. The Ala carriers (Pro12Ala + Ala12Ala) had significantly lower urinary albumin-to-creatinine ratio (15.0 vs 20.5 mg/g, P = 0.001) and better renal function (estimated glomerular filtration rate 81.8 [69.8-97.6] vs 78.7 mL/min/1.73 m2 [61.6-96.2]; P = 0.05) compared with those with the genotype Pro12Pro. After adjustment for age, sex and other confounders, the odds ratio of albuminuria for the Ala12 allele was 0.428 (95% confidence interval 0.195-0.940, P = 0.034]).

CONCLUSIONS

Our results suggest that the peroxisome proliferator-activated receptor gamma 2 Ala12 variant has significant protective effects against albuminuria and DN.

Role of Genetic Variations in the Hepatic Handling of Drugs

The liver plays a pivotal role in drug handling due to its contribution to the processes of detoxification (phases 0 to 3). In addition, the liver is also an essential organ for the mechanism of action of many families of drugs, such as cholesterol-lowering, antidiabetic, antiviral, anticoagulant, and anticancer agents. Accordingly, the presence of genetic variants affecting a high number of genes expressed in hepatocytes has a critical clinical impact. The present review is not an exhaustive list but a general overview of the most relevant variants of genes involved in detoxification phases. The available information highlights the importance of defining the genomic profile responsible for the hepatic handling of drugs in many ways, such as (i) impaired uptake, (ii) enhanced export, (iii) altered metabolism due to decreased activation of prodrugs or enhanced inactivation of active compounds, and (iv) altered molecular targets located in the liver due to genetic changes or activation/downregulation of alternative/compensatory pathways. In conclusion, the advance in this field of modern pharmacology, which allows one to predict the outcome of the treatments and to develop more effective and selective agents able to overcome the lack of effect associated with the existence of some genetic variants, is required to step forward toward a more personalized medicine.

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.

Frequency of CYP2C9 (*2, *3 and IVS8-109A>T) allelic variants, and their clinical implications, among Mexican patients with diabetes mellitus type 2 undergoing treatment with glibenclamide and metformin

The majority of Mexican patients with diabetes mellitus type 2 (DMT2) (67.9-85.0%) are prescribed sulphonylureas (SUs), which are metabolized by cytochrome P450 2C9 (abbreviated as CYP2C9). SUs are a type of oral anti-diabetic compound which inhibit ATP-sensitive potassium channels, thus inducing glucose-independent insulin release by the β-pancreatic cells. The wide variability reported in SU responses has been attributed to the polymorphisms of CYP2C9. The present study aimed to describe CYP2C9 polymorphisms (*2, *3 and IVS8-109T) within a sample of Mexican patients with DMT2, while suggesting the potential clinical implications in terms of glibenclamide response variability. From a sample of 248 patients with DMT2 who initially consented to be studied, those ultimately included in the study were treated with glibenclamide (n=11), glibenclamide combined with metformin (n=112) or metformin (n=76), and were subsequently genotyped using a reverse transcription-quantitative polymerase chain reaction (PCR), end-point allelic discrimination and PCR amplifying enzymatic restriction fragment long polymorphism. Clinical data were gathered through medical record revision. The frequencies revealed were as follows: CYP2C9*1/*1, 87.5%; *1/*2, 6.5%; *1/*3, 5.2%; and CYP2C9, IVS8-109A>T, 16.1%. Glibenclamide significantly reduced the level of pre-prandial glucose (P<0.01) and the percentage of glycated hemoglobin (%HbA1c; P<0.01) for IVS8-109A>T compared with combined glibenclamide and metformin treatment. Concerning the various treatments with respect to the different genotypes, the percentages obtained were as follows: Glibenclamide A/A, HbA1c<6.5=33.3%; glibenclamide + metformin A/A, HbA1c<6.5=24.6%; glibenclamide A/T, HbA1c<6.5=33.3%; glibenclamide + metformin A/T, HbA1c<6.5=25%; glibenclamide T/T, HbA1c<6.5=100%; and glibenclamide + metformin T/T, HbA1c<6.5=12.5%. Altogether, these results revealed that, although genetically customized prescriptions remain a desirable goal to increase the chances of therapeutic success, within the studied population neither allelic variants nor dosages demonstrated a clear association with biomarker levels. A key limitation of the present study was the lack of ability to quantify either the plasma concentrations of SU or their metabolites; therefore, further, precise experimental and observational studies are required.

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.

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.

Pharmacogenetics of Antidiabetic Drugs

Pharmacogenetic studies of antidiabetic drugs have so far focused largely on response to metformin, which is the first-line therapy for treatment of type 2 diabetes (T2D). The first studies of metformin pharmacogenetics were focused on candidate genes that were implicated in metformin pharmacokinetics and transport. Since 2011, genome-wide association studies have been conducted in large cohorts of individuals with T2D identifying genes that are associated with glycemic response to metformin. There have been fewer pharmacogenetic studies of other antidiabetic drugs, and those have been largely limited to candidate gene studies with small sample sizes. Understanding the pharmacogenetics of antidiabetes medications is important for the integration of genetic screening into therapeutic decision making, and to achieve the goal of "precision medicine" for patients with T2D. In this chapter, we provide a review of the pharmacogenetics investigations of metformin and other antidiabetes medications. In addition, we highlight the importance of collaborative efforts with large sample size and representation from multiple ethnic groups in pharmacogenetics studies.

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.

Effects of functional CYP2C8,CYP2C9,CYP3A5,and ABCB1 genetic variants on the pharmacokinetics of insulin sensitizer pioglitazone in Chinese Han individuals

BACKGROUND AND OBJECTIVES

Pioglitazone is a thiazolidinedione antihyperglycemic drug with insulin-sensitizing properties. We investigated whether the variant genotypes of cytochrome P450 2C8 (CYP2C8), CYP2C9, CYP3A5 and transporter ABCB1 influence the pharmacokinetic phenotype of the substrate pioglitazone in Chinese individuals.

PARTICIPANTS AND METHODS

Single-nucleotide polymorphisms were determined by the PCR-restriction fragment length polymorphism method in 244 (CYP2C8 and CYP2C9) healthy Chinese Han individuals. After a single oral dose of 30 mg pioglitazone, the plasma concentrations of the parent drug and of two major active metabolites M-III and M-IV were measured using a validated LC-MS/MS in 21 (genotyping CYP3A5 and ABCB1) of these 244 volunteers.

RESULTS

The results confirmed that the unique frequencies of CYP2C8*2 (0.0%), CYP2C8*3 (0.0%), and CYP2C9*2 (0.0%) alleles were significantly different from those reported in Whites and Africans, and there were only 10 variant CYP2C9*1/*3 heterozygous (CYP2C9*3 carriers) among 244 Chinese individuals. These results were similar to those reported in Asian ethnic populations, including the Chinese. Unexpectedly, the pioglitazone AUC0-48 in CYP2C9*3 carriers was lower (50.8%), whereas the AUC0-48 ratios of metabolites M-III/pioglitazone and M-IV/pioglitazone increased to 134.3 and 155.8%, respectively, compared with the wild-type CYP2C9*1/*1 homozygous. Moreover, this phenomenon was not observed in individuals with genetic variants of CYP3A5*3 and ABCB1 (C1236T).

CONCLUSION

The present research suggests that the CYP2C8, CYP3A5, and ABCB1 genes play no significant role in the interindividual variation of pioglitazone pharmacokinetics, whereas CYP2C9*3 carriers are likely to accelerate the metabolism of this antidiabetic drug in the Chinese Han ethnic population.

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.

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

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

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

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

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

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

Genotype Phenotype Correlation of Genetic Polymorphism of PPAR Gamma Gene and Therapeutic Response to Pioglitazone in Type 2 Diabetes Mellitus- A Pilot Study

INTRODUCTION

Pro12Ala polymorphism is a missense mutation at codon 12 in peroxisome proliferator-activated receptor γ gene (PPARG). This polymorphism is known to be associated with increased insulin sensitivity. Pioglitazone, a thiazolidinedione, is an anti-diabetic drug which acts as an agonist at PPAR γ receptor.

AIM

To determine the association between Pro12Ala polymorphism of the PPARG and variation in therapeutic response to the PPARγ agonist, pioglitazone.

MATERIALS AND METHODS

The study was done as a hospital based pilot project in 30 patients with type 2 diabetes mellitus, on treatment with sulfonylurea or metformin but without adequate glycaemic control. They were started on pioglitazone as add on therapy for a period of 12 weeks. The participants were categorized as responders and non-responders based on the change in HbA1C level after 12 weeks. Pro12Ala polymorphism was analysed by polymerase chain reaction-restriction fragment length polymorphism.

STATISTICAL ANALYSIS

Logistic regression analysis was done to evaluate the associations between age, baseline body weight, BMI, waist circumference, waist-hip ratio and Pro12Ala variants with the response to pioglitazone. The p-value< 0.05 was considered significant.

RESULTS

The frequency distributions of PPAR gamma genotypes were 80% for Pro/Pro and 20% for Pro/Ala in the study population. Among the study participants, 30% were non-responders and 70% responders to pioglitazone. A significantly higher frequency of the polymorphism was detected in the responders (p=0.005) compared to non-responders group.

CONCLUSION

Our study suggests that there is a potential association between Pro12Ala polymorphism and glycaemic response to pioglitazone.

The Gly482Ser polymorphism of the peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is associated with type 2 diabetes in Tunisian population

BACKGROUND AND AIMS

Peroxisome proliferator-activated receptor-γ co-activator-1α (PGC-1α) is a transcriptional co-activator involved in adaptive thermogenesis, skeletal muscle metabolism, fatty acid oxidation, and gluconeogenesis. Several studies have suggested that the common PGC-1α polymorphism Gly482Ser (rs8192678) may be associated with risk of type 2 diabetes (T2D), with conflicting results. The aim of this study was to analyze whether the Gly482Ser variant is a risk factor for development of T2D in Tunisian population.

METHODS

In a case-control study 487 unrelated patients with type 2 diabetes and 402 apparently healthy controls were recruited from January 2008 to August 2010. The Gly482Ser polymorphism was determined by PCR-RFLP analysis.

RESULTS

A significant difference in genotypes distribution was observed between patients (Gly/Gly: 34.1%; Gly/Ser: 47.1%; Ser/Ser: 18.5%) and controls (Gly/Gly: 43.8%; Gly/Ser: 42.3%; Ser/Ser: 13.9%) (χ(2)=9.44, p=0.009). The T2D patient group showed a significant higher frequency of the Ser allele compared to the controls (43% vs. 34%; OR: 1.35, 95% [CI]: 1.11-1.65, p=0.002). The association between the Gly482Ser polymorphism and T2D remained significant after adjustment for other well-established cardiovascular risk factors.

CONCLUSIONS

In the current study, a significant and independent association between the Gly482Ser polymorphism (rs8192678) of the PGC-1α gene and T2D in the Tunisian population was found.

Pharmacogenomics and pharmacogenetics of thiazolidinediones: role in diabetes and cardiovascular risk factors

The most important goal in the treatment of patients with diabetes is to prevent the risk of cardiovascular disease (CVD), the first cause of mortality in these subjects. Thiazolidinediones (TZDs), a class of antidiabetic drugs, act as insulin sensitizers increasing insulin-dependent glucose disposal and reducing hepatic glucose output. TZDs including pioglitazone, rosiglitazone and troglitazone, by activating PPAR-γ have shown pleiotropic effects in reducing vascular risk factors and atherosclerosis. However, troglitazone was removed from the market due to its hepatoxicity, and rosiglitazone and pioglitazone both have particular warnings due to being associated with heart diseases. Specific genetic variations in genes involved in the pathways regulated by TDZs have demonstrated to modify the variability in treatment with these drugs, especially in their side effects. Therefore, pharmacogenomics and pharmacogenetics are an important tool in further understand intersubject variability per se but also to assess the therapeutic potential of such variability in drug individualization and therapeutic optimization.

Adverse effects and safety of SGLT-2 inhibitors

In type 2 diabetes (T2DM), glycaemic control delays the development and slows the progression of complications. Although there are numerous glucose-lowering agents in clinical use, only approximately half of T2DM patients achieve glycaemic control, while undesirable side-effects, such as hypoglycaemia and body weight gain, often impede treatment in those taking these medications. Thus, there is a need for novel agents and treatment options. Sodium-glucose cotransporter-2 inhibitors (SGLT-2-i) have recently been developed for the treatment of T2DM. The available data suggest a good tolerability profile for the three available drugs - canagliflozin, dapagliflozin and empagliflozin - approved by the US Food and Drug Administration (FDA) for the American market as well as in other countries. The most frequently reported adverse events with SGLT-2-i are female genital mycotic infections, urinary tract infections and increased urination. The pharmacodynamic response to SGLT-2-i declines with increasing severity of renal impairment, requiring dosage adjustments or restrictions with moderate-to-severe renal dysfunction. Most patients treated with SGLT-2-i also have a modest reduction in blood pressure and modest effects on serum lipid profiles, some of which are beneficial (increased high-density lipoprotein cholesterol and decreased triglycerides) and others which are not (increased low-density lipoprotein cholesterol, LDL-C). A number of large-scale and longer-term cardiovascular trials are now ongoing. In patients treated with dapagliflozin, a non-significant excess number of breast and bladder cancers has been reported; considered as due to a bias, this is nevertheless being followed in the ongoing trials. No other significant safety issues have been reported so far. Although there is some benefit for several cardiovascular risk factors such as HbA1c, high blood pressure, obesity and increases in LDL-C, adequately powered trials are still required to determine the effects of SGLT-2-i on macrovascular outcomes.

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.

The 482Ser of PPARGC1A and 12Pro of PPARG2 Alleles Are Associated with Reduction of Metabolic Risk Factors Even Obesity in a Mexican-Mestizo Population

The aim of this study was to investigate the relationship between functional polymorphisms Gly482Ser in PPARGC1A and Pro12Ala in PPARG2 with the presence of obesity and metabolic risk factors. We included 375 individuals characterized as Mexican-Mestizos and classified by the body mass index (BMI). Body dimensions and distribution of body fat were measured. The HOMA-IR and adiposity indexes were calculated. Adipokines and metabolic profile quantification were performed by ELISA and routine methods. Genetic polymorphisms were determined by polymerase chain reaction restriction fragment length polymorphism analysis. A difference between obese and nonobese subjects in polymorphism PPARGC1A distribution was observed. Among obese individuals, carriers of genotype 482Gly/Gly were observed to have decreased body fat, BMI, and body fat ratio versus 482Ser/Ser carriers and increased resistin and leptin levels in carriers Gly+ phenotype versus Gly- phenotype. Subjects with PPARG2 Ala- phenotype (genotype 12Pro/Pro) showed a decreased HOMA-IR index versus individuals with Ala+ phenotype (genotypes 12Pro/Ala plus 12Ala/Ala). We propose that, in obese Mexican-Mestizos, the combination of alleles 482Ser in PPARGC1A and 12Pro in PPARG2 represents a reduced metabolic risk profile, even when the adiposity indexes are increased.

Pharmacogenomics of Drug Response in Type 2 Diabetes: Toward the Definition of Tailored Therapies?

Type 2 diabetes is one of the major causes of mortality with rapidly increasing prevalence. Pharmacological treatment is the first recommended approach after failure in lifestyle changes. However, a significant number of patients shows-or develops along time and disease progression-drug resistance. In addition, not all type 2 diabetic patients have the same responsiveness to drug treatment. Despite the presence of nongenetic factors (hepatic, renal, and intestinal), most of such variability is due to genetic causes. Pharmacogenomics studies have described association between single nucleotide variations and drug resistance, even though there are still conflicting results. To date, the most reliable approach to investigate allelic variants is Next-Generation Sequencing that allows the simultaneous analysis, on a genome-wide scale, of nucleotide variants and gene expression. Here, we review the relationship between drug responsiveness and polymorphisms in genes involved in drug metabolism (CYP2C9) and insulin signaling (ABCC8, KCNJ11, and PPARG). We also highlight the advancements in sequencing technologies that to date enable researchers to perform comprehensive pharmacogenomics studies. The identification of allelic variants associated with drug resistance will constitute a solid basis to establish tailored therapeutic approaches in the treatment of type 2 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.

Genomic-based tools for the risk assessment, management, and prevention of type 2 diabetes

Type 2 diabetes (T2D) is a common and serious disorder and is a significant risk factor for the development of cardiovascular disease, neuropathy, nephropathy, retinopathy, periodontal disease, and foot ulcers and amputations. The burden of disease associated with T2D has led to an emphasis on early identification of the millions of individuals at high risk so that management and intervention strategies can be effectively implemented before disease progression begins. With increasing knowledge about the genetic basis of T2D, several genomic-based strategies have been tested for their ability to improve risk assessment, management and prevention. Genetic risk scores have been developed with the intent to more accurately identify those at risk for T2D and to potentially improve motivation and adherence to lifestyle modification programs. In addition, evidence is building that oral antihyperglycemic medications are subject to pharmacogenomic variation in a substantial number of patients, suggesting genomics may soon play a role in determining the most effective therapies. T2D is a complex disease that affects individuals differently, and risk prediction and treatment may be challenging for health care providers. Genomic approaches hold promise for their potential to improve risk prediction and tailor management for individual patients and to contribute to better health outcomes for those with T2D.

Patient profiling in diabetes and role of canagliflozin

Background

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

Methods

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

Results and conclusion

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

Association of the variants in the PPARG gene and serum lipid levels: a meta-analysis of 74 studies

Considerable studies have been carried out to investigate the relationship between the polymorphisms of PPARG (Pro12Ala, C161T and C1431T) and serum lipid levels, but the results were inconclusive. Hence, we conducted a meta-analysis to clarify the association. MEDLINE, EMBASE and the Cochrane Library databases were searched systematically. The subgroup analysis was performed based on ethnicity. Seventy-four studies with 54,953 subjects were included in this meta-analysis. In Pro12Ala, the group with the ‘PP’ (C/C genotype) genotype group had lower levels of total cholesterol (TC) (mean difference, MD: −0.02, P < 0.00001; I² = 28%), low-density lipoprotein cholesterol (LDL-C) (MD: −0.02, P < 0.00001; I² = 30%) and higher levels of triglyceride (TG) (MD: 0.06, P < 0.00001; I² = 30%) than the combined ‘PA+AA’ (PA = C/G genotype, AA = G/G genotype) genotype group in Asian population, and the group with the ‘PP’ genotype had higher levels of TG (MD: 0.07, P < 0.02; I² = 67%) than the combined ‘PA+AA’ genotype group in non-Asian population. No statistically significant differences in the levels of TC, TG, high-density lipoprotein cholesterol, LDL-C were detected between different genotypes in C161T(Asian or non-Asian) and C1431T(Asian) polymorphisms. This meta-analysis was a renewed and confirmed study to assess the association between PPARG polymorphisms and serum lipid levels in Asian and non-Asian populations. There is a prominent association between Pro12Ala polymorphism and the levels of TC, LDL-C and TG in Asian population. No statistically significant differences in serum lipid levels were detected between different genotypes in C161T and C1431T polymorphisms.

Current clinical evidence on pioglitazone pharmacogenomics

Pioglitazone is the most widely used thiazolidinedione and acts as an insulin-sensitizer through activation of the Peroxisome Proliferator-Activated Receptor-γ (PPARγ). Pioglitazone is approved for use in the management of type 2 diabetes mellitus (T2DM), but its use in other therapeutic areas is increasing due to pleiotropic effects. In this hypothesis article, the current clinical evidence on pioglitazone pharmacogenomics is summarized and related to variability in pioglitazone response. How genetic variation in the human genome affects the pharmacokinetics and pharmacodynamics of pioglitazone was examined. For pharmacodynamic effects, hypoglycemic and anti-atherosclerotic effects, risks of fracture or edema, and the increase in body mass index in response to pioglitazone based on genotype were examined. The genes CYP2C8 and PPARG are the most extensively studied to date and selected polymorphisms contribute to respective variability in pioglitazone pharmacokinetics and pharmacodynamics. We hypothesized that genetic variation in pioglitazone pathway genes contributes meaningfully to the clinically observed variability in drug response. To test the hypothesis that genetic variation in PPARG associates with variability in pioglitazone response, we conducted a meta-analysis to synthesize the currently available data on the PPARG p.Pro12Ala polymorphism. The results showed that PPARG 12Ala carriers had a more favorable change in fasting blood glucose from baseline as compared to patients with the wild-type Pro12Pro genotype (p = 0.018). Unfortunately, findings for many other genes lack replication in independent cohorts to confirm association; further studies are needed. Also, the biological functionality of these polymorphisms is unknown. Based on current evidence, we propose that pharmacogenomics may provide an important tool to individualize pioglitazone therapy and better optimize therapy in patients with T2DM or other conditions for which pioglitazone is being used.

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.

PPAR-γ2 and PTPRD gene polymorphisms influence type 2 diabetes patients' response to pioglitazone in China

AIM

To investigate the influence of peroxisome proliferator-activated receptor γ2 (PPAR-γ2) gene polymorphism rs1801282 and protein tyrosine phosphatase receptor type D (PTPRD) gene polymorphism rs17584499 on the occurrence of type 2 diabetes and pioglitazone efficacy in a Chinese Han population.

METHODS

One hundred ninety seven type 2 diabetes patients and 212 healthy controls were enrolled. Among them, 67 type 2 diabetes patients were administered pioglitazone (30 mg/d, po) for 3 months. All the subjects were genotyped for genetic variants in PPAR-γ2 and PTPRD using MALDI-TOF mass spectrometry. Fasting plasma glucose, postprandial plasma glucose, glycated hemoglobin, serum triglyceride, total cholesterol, low-density and high-density lipoprotein-cholesterol were determined.

RESULTS

The PPAR-γ2 gene rs1801282 polymorphism was significantly associated with type 2 diabetes susceptibility (OR=0.515, 95% CI 0.268-0.990) and the PTPRD gene rs17584499 polymorphism was also significantly associated with type 2 diabetes (OR=1.984, 95% CI 1.135-3.469) in a dominant model adjusted for age, gender and BMI. After pioglitazone treatment for 3 months, the type 2 diabetes patients with PPAR-γ2 rs1801282 CG genotypes significantly showed higher differential values of postprandial plasma glucose and serum triglyceride compared with those with rs1801282 CC genotype. The patients with PTPRD rs17584499 CT+TT genotypes showed significantly lower differential value of postprandial plasma glucose compared to those with rs17584499 CC genotype.

CONCLUSION

Diabetes risk alleles in PPAR-γ2 (rs1801282) and PTPRD (rs17584499) are associated with pioglitazone therapeutic efficacy.

Pharmacogenomics of oral antidiabetic medications: current data and pharmacoepigenomic perspective

Type 2 diabetes mellitus (T2DM) is an increasingly prevalent disease. Several classes of drugs are currently available to treat T2DM patients; however, clinical response to these drugs often exhibits significant variation among individuals. For the oral antidiabetic drug classes of sulfonylureas, nonsulfonylurea insulin secretagogs, biguanides and thiazolidinediones, pharmacogenomic evidence has accumulated demonstrating an association between specific gene polymorphisms and interindividual variability in their therapeutic and adverse reaction effects. These polymorphisms are in genes of molecules involved in metabolism, transport and therapeutic mechanisms of the aforementioned drugs. Overall, it appears that pharmacogenomics has the potential to improve the management of T2DM and help clinicians in the effective prescribing of oral antidiabetic medications. Although pharmacogenomics can explain some of the heterogeneity in dose requirements, response and incidence of adverse effects of drugs between individuals, it is now clearly understood that much of the diversity in drug effects cannot be solely explained by studying the genomic diversity. Epigenomics, the field that focuses on nongenomic modifications that influence gene expression, may expand the scope of pharmacogenomics towards optimization of drug therapy. Therefore, pharmacoepigenomics, the combined analysis of genetic variations and epigenetic modifications, holds promise for the realization of personalized medicine. Although pharmacoepigenomics has so far been evaluated mainly in cancer pharmacotherapy, studies on epigenomic modifications during T2DM development provide useful data on the potential of pharmacoepigenomics to elucidate the mechanisms underlying interindividual response to oral antidiabetic treatment. In summary, the present article focuses on available data from pharmacogenomic studies of oral antidiabetic drugs and also provides an overview of T2DM epigenomic research, which has the potential to boost the development of pharmacoepigenomics in antidiabetic treatment.