Analysis of the relationship between the Pro12Ala variant in the PPAR-gamma2 gene and the response rate to therapy with pioglitazone in patients with type 2 diabetes

Exploring the potential role of C-peptide in type 2 diabetes management

Type 2 diabetes (T2D) is a complex condition characterised by the interaction between insulin resistance and beta cell dysfunction. C-peptide, a key biomarker of endogenous insulin secretion, has a role in diagnosing type 1 diabetes (T1D). However, its utility in T2D has not been extensively studied. This review provides an overview of the progression of C-peptide levels over time in T2D and discuss its interpretation in clinical settings. We reviewed current evidence on the relationship between C-peptide levels and response to antidiabetic drugs, as well as the utility of C-peptide testing in T2D treatment strategies. We also reviewed available evidence for C-peptide in predicting future outcomes in T2D. In this review, we hoped to clarify the value of C-peptide testing in understanding and managing T2D and to highlight areas where further research is needed.

Analysis of an adult diabetes mellitus caused by a rare mutation of the gene: A case report

BACKGROUND

This study presents the clinical and genetic mutation characteristics of an unusual case of adult-onset diabetes mellitus occurring in adolescence, featuring a unique mutation in the peroxisome proliferator-activated receptor gamma (PPARG) gene. Data Access Statement: Research data supporting this publication are available from the NN repository at www.NNN.org/download/.

CASE SUMMARY

The methodology employed entailed meticulous collection of comprehensive clinical data from the probands and their respective family members. Additionally, high-throughput sequencing was conducted to analyze the PPARG genes of the patient, her siblings, and their offspring. The results of this investigation revealed that the patient initially exhibited elevated blood glucose levels during pregnancy, accompanied by insulin resistance and hypertriglyceridemia. Furthermore, these strains displayed increased susceptibility to diabetic kidney disease without any discernible aggregation patterns. The results from the gene detection process demonstrated a heterozygous mutation of guanine (G) at position 284 in the coding region of exon 2 of PPARG, which replaced the base adenine (A) (exon2c.284A>Gp.Tyr95Cys). This missense mutation resulted in the substitution of tyrosine with cysteine at the 95th position of the translated protein. Notably, both of her siblings harbored a nucleotide heterozygous variation at the same site, and both were diagnosed with diabetes.

CONCLUSION

The PPARG gene mutation, particularly the p.Tyr95Cys mutation, may represent a newly identified subtype of maturity-onset diabetes of the young. This subtype is characterized by insulin resistance and lipid metabolism disorders.

PPARs in Clinical Experimental Medicine after 35 Years of Worldwide Scientific Investigations and Medical Experiments

This year marks the 35th anniversary of Professor Walter Wahli's discovery of the PPARs (Peroxisome Proliferator-Activated Receptors) family of nuclear hormone receptors. To mark the occasion, the editors of the scientific periodical Biomolecules decided to publish a special issue in his honor. This paper summarizes what is known about PPARs and shows how trends have changed and how research on PPARs has evolved. The article also highlights the importance of PPARs and what role they play in various diseases and ailments. The paper is in a mixed form; essentially it is a review article, but it has been enriched with the results of our experiments. The selection of works was subjective, as there are more than 200,000 publications in the PubMed database alone. First, all papers done on an animal model were discarded at the outset. What remained was still far too large to describe directly. Therefore, only papers that were outstanding, groundbreaking, or simply interesting were described and briefly commented on.

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.

Effects of PPARG and PPARGC1A gene polymorphisms on obesity markers

Pediatric obesity presents a multifactorial etiology, which involves genetic traits as well, including single nucleotide polymorphisms. The aim of the study is to investigate the contribution of PPARG gene polymorphisms (namely Pro12Ala rs1801282, His447His rs3856806, and Pro115Gln rs1800571) and PPARGC1A rs8192678 SNP on the anthropometric and metabolic parameters in a population of Romanian children. We conducted a cross-sectional study of 295 Caucasian children, divided according to the body mass index (BMI) z-score into the study (obese and overweight) group of 130 children and the control (normoponderal) group of 165 children. Anthropometric parameters were greater in the obese and overweight population as opposed to controls, with significant differences (p < 0.01) found for the weight (2.77 ± 1.54 SD vs. -0.04 ± 1.15 SD), body mass index (BMI) (2.28 ± 0.97 SD vs. -0.18 ± 1.19 SD), mid-upper arm circumference (MUAC) (4.59 ± 2.28 SD vs. 0.28 ± 3.45 SD), tricipital skin-fold (TSF) (3.31 ± 3.09 SD vs. 0.62 ± 7.28 SD) and waist-to-height ratio (WHtR) (0.61 ± 1.51 SD vs. -0.35 ± 1.35 SD) z-scores. Moreover, triglyceride values were higher in the study group (118.70 ± 71.99 SD vs. 77.09 ± 37.39 SD). No significant difference in the allele and genotype distribution of investigates gene polymorphisms was observed between the studied groups (p > 0.05). PPARG (rs1801282, rs3856806, and rs1800571) were not associated with demographic, anthropometric, and laboratory parameters. However, PPARGC1A rs8192678 CC genotype was associated with TSF z-score (p = 0.03), whereas total and LDL cholesterol levels were significantly higher among TT homozygotes (p < 0.01). Our data suggest that PPARG (rs1801282, rs3856806, and rs1800571) and PPARGC1A (rs8192678) gene polymorphisms were not associated with childhood and adolescence overweight and obesity. The present study identified a significant increase in fasting glucose levels, triglyceride, albumin, and ALT levels in children with excess weight, as well as expected important upward variation of anthropometric parameters (BMI, MUAC, TSF z-scores).

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.

Genetics and Clinical Characteristics of PPARγ Variant-Induced Diabetes in a Chinese Han Population

OBJECTIVES

PPARγ variants cause lipodystrophy, insulin resistance, and diabetes. This study aimed to determine the relationship between PPARγ genotypes and phenotypes and to explore the pathogenesis of diabetes beyond this relationship.

METHODS

PPARγ2 exons in 1,002 Chinese patients with early-onset type 2 diabetes (diagnosed before 40 years of age) were sequenced. The functions of variants were evaluated by in vitro assays. Additionally, a review of the literature was performed to obtain all reported cases with rare PPARγ2 variants to evaluate the characteristics of variants in different functional domains.

RESULTS

Six (0.6%) patients had PPARγ2 variant-induced diabetes (PPARG-DM) in the early-onset type 2 diabetes group, including three with the p.Tyr95Cys variant in activation function 1 domain (AF1), of which five patients (83%) had diabetic kidney disease (DKD). Functional experiments showed that p.Tyr95Cys suppresses 3T3-L1 preadipocyte differentiation. A total of 64 cases with damaging rare variants were reported previously. Patients with rare PPARγ2 variants in AF1 of PPARγ2 had a lower risk of lipodystrophy and a higher rate of obesity than those with variants in other domains, as confirmed in patients identified in this study.

CONCLUSION

The prevalence of PPARG-DM is similar in Caucasian and Chinese populations, and DKD was often observed in these patients. Patients with variants in the AF1 of PPARγ2 had milder clinical phenotypes and lack typical lipodystrophy features than those with variants in other domains. Our findings emphasize the importance of screening such patients via genetic testing and suggest that thiazolidinediones might be a good choice for these patients.

Pharmacogenetic Aspects of Type 2 Diabetes Treatment

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

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.

Pathophysiology-based phenotyping in type 2 diabetes: A clinical classification tool

BACKGROUND

Type 2 diabetes may be a more heterogeneous disease than previously thought. Better understanding of pathophysiological subphenotypes could lead to more individualized diabetes treatment. We examined the characteristics of different phenotypes among 5813 Danish patients with new clinically diagnosed type 2 diabetes.

METHODS

We first identified all patients with rare subtypes of diabetes, latent autoimmune diabetes of adults (LADA), secondary diabetes, or glucocorticoid-associated diabetes. We then used the homeostatic assessment model to subphenotype all remaining patients into insulinopenic (high insulin sensitivity and low beta cell function), classical (low insulin sensitivity and low beta cell function), or hyperinsulinemic (low insulin sensitivity and high beta cell function) type 2 diabetes.

RESULTS

Among 5813 patients diagnosed with incident type 2 diabetes in the community clinical setting, 0.4% had rare subtypes of diabetes, 2.8% had LADA, 0.7% had secondary diabetes, 2.4% had glucocorticoid-associated diabetes, and 93.7% had WHO-defined type 2 diabetes. In the latter group, 9.7% had insulinopenic, 63.1% had classical, and 27.2% had hyperinsulinemic type 2 diabetes. Classical patients were obese (median waist 105 cm), and 20.5% had cardiovascular disease (CVD) at diagnosis, while insulinopenic patients were fairly lean (waist 92 cm) and 17.5% had CVD (P = 0.14 vs classical diabetes). Hyperinsulinemic patients were severely obese (waist 112 cm), and 25.5% had CVD (P < 0.0001 vs classical diabetes).

CONCLUSIONS

Patients clinically diagnosed with type 2 diabetes are a heterogeneous group. In the future, targeted treatment based on pathophysiological characteristics rather than the current "one size fits all" approach may improve patient prognosis.

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.

A Practical Review of C-Peptide Testing in Diabetes

C-peptide is a widely used measure of pancreatic beta cell function. It is produced in equimolar amounts to endogenous insulin but is excreted at a more constant rate over a longer time. Methods of estimation include urinary and unstimulated and stimulated serum sampling. Modern assays detect levels of c-peptide which can be used to guide diabetes diagnosis and management. We explore the evidence behind the various tests available. We recommend the glucagon stimulation c-peptide testing owing to its balance of sensitivity and practicality. C-peptide levels are associated with diabetes type and duration of disease. Specifically a c-peptide level of less than 0.2 nmol/l is associated with a diagnosis of type 1 diabetes mellitus (T1DM). C-peptide level may correlate with microvascular and macrovascular complications and future use of insulin therapy, as well as likely response to other individual therapies. We explore the potential uses of c-peptide measurement in clinical practice.

A genetic variant in GLP1R is associated with response to DPP-4 inhibitors in patients with type 2 diabetes

Incretin hormone-based therapy in type 2 diabetes has been widely used, and dipepdityl peptidase-4 (DPP-4) inhibitors, which prevent incretin degradation, have become popular oral hypoglycemic agents. The efficacy of DPP-4 inhibitors varies from individuals, and factors determining responses to DPP-4 inhibitors have not been fully established. We aimed to investigate whether genetic variations in glucagon-like peptide (GLP-1) receptor are associated with responses to DPP-4 inhibitors in patients with type 2 diabetes.Genetic variations of rs3765467 in GLP-1 receptor were explored in 246 patients with type 2 diabetes who received DPP-4 inhibitors treatment for 24 weeks in addition to previous medication. Patients with glycated hemoglobin (HbA1c) > 7% and who were naive to any DPP-4 inhibitors were enrolled. Responders were defined as those who showed a > 10% reduction in HbA1c after DPP-4 inhibitor treatment.DPP-4 inhibitors improved glycemic parameters and lipid profiles. Compared to the major genotype (GG), a larger proportion of patients with the minor allele genotype (GA/AA) were responders (P = 0.018), and also showing greater HbA1c reductions (1.3 ± 1.1 vs 0.9 ± 1.2%; P = 0.022). This genetic effect remained significant even after adjustment for other confounding factors (OR = 2.00, 95% CI = 1.03-3.89).Polymorphism in the GLP-1 receptor may influence DPP-4 inhibitor response. Further studies in larger population will help determine the association between genetic variation and interindividual differences in DPP-4 inhibitor therapy.

Precision medicine: The future in diabetes care?

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

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.

New insights from monogenic diabetes for "common" type 2 diabetes

Boundaries between monogenic and complex genetic diseases are becoming increasingly blurred, as a result of better understanding of phenotypes and their genetic determinants. This had a large impact on the way complex disease genetics is now being investigated. Starting with conventional approaches like familial linkage, positional cloning and candidate genes strategies, the scope of complex disease genetics has grown exponentially with scientific and technological advances in recent times. Despite identification of multiple loci harboring common and rare variants associated with complex diseases, interpreting and evaluating their functional role has proven to be difficult. Information from monogenic diseases, especially related to the intermediate traits associated with complex diseases comes handy. The significant overlap between traits and phenotypes of monogenic diseases with related complex diseases provides a platform to understand the disease biology better. In this review, we would discuss about one such complex disease, type 2 diabetes, which shares marked similarity of intermediate traits with different forms of monogenic diabetes.

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.

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.

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.

The pharmacogenetics of type 2 diabetes: a systematic review

OBJECTIVE

We performed a systematic review to identify which genetic variants predict response to diabetes medications.

RESEARCH DESIGN AND METHODS

We performed a search of electronic databases (PubMed, EMBASE, and Cochrane Database) and a manual search to identify original, longitudinal studies of the effect of diabetes medications on incident diabetes, HbA1c, fasting glucose, and postprandial glucose in prediabetes or type 2 diabetes by genetic variation. Two investigators reviewed titles, abstracts, and articles independently. Two investigators abstracted data sequentially and evaluated study quality independently. Quality evaluations were based on the Strengthening the Reporting of Genetic Association Studies guidelines and Human Genome Epidemiology Network guidance.

RESULTS

Of 7,279 citations, we included 34 articles (N = 10,407) evaluating metformin (n = 14), sulfonylureas (n = 4), repaglinide (n = 8), pioglitazone (n = 3), rosiglitazone (n = 4), and acarbose (n = 4). Studies were not standalone randomized controlled trials, and most evaluated patients with diabetes. Significant medication-gene interactions for glycemic outcomes included 1) metformin and the SLC22A1, SLC22A2, SLC47A1, PRKAB2, PRKAA2, PRKAA1, and STK11 loci; 2) sulfonylureas and the CYP2C9 and TCF7L2 loci; 3) repaglinide and the KCNJ11, SLC30A8, NEUROD1/BETA2, UCP2, and PAX4 loci; 4) pioglitazone and the PPARG2 and PTPRD loci; 5) rosiglitazone and the KCNQ1 and RBP4 loci; and 5) acarbose and the PPARA, HNF4A, LIPC, and PPARGC1A loci. Data were insufficient for meta-analysis.

CONCLUSIONS

We found evidence of pharmacogenetic interactions for metformin, sulfonylureas, repaglinide, thiazolidinediones, and acarbose consistent with their pharmacokinetics and pharmacodynamics. While high-quality controlled studies with prespecified analyses are still lacking, our results bring the promise of personalized medicine in diabetes one step closer to fruition.

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.

The role of genetic variants in CYP2C8, LPIN1, PPARGC1A and PPARγ on the trough steady-state plasma concentrations of rosiglitazone and on glycosylated haemoglobin A1c in type 2 diabetes

OBJECTIVE

The aim of this study was to examine the effect of single nucleotide polymorphisms in CYP2C8, LPIN1, PPARGC1A and PPARγ on rosiglitazone's (i) trough steady-state plasma concentration (C(ss,min)), (ii) on glycosylated haemoglobin A1c (HbA1c) and (iii) the risk of developing adverse events, mainly oedema, in patients with type 2 diabetes mellitus (T2D).

METHODS

The data used in this study were obtained from the South Danish Diabetes Study including 371 T2D patients with a focus on the 187 patients who were treated with rosiglitazone. The study was a placebo-controlled, partly blinded and multicentre clinical trial. The C(ss,min) of rosiglitazone and HbA1c was determined and the genotype of the patients was identified.

RESULTS

The mean C(ss,min) of rosiglitazone was 21.3 ng/ml (95% confidence interval 18.8; 24.2 ng/ml), with observations ranging from 1 to 296 ng/ml. Carriers of CYP2C8*3 (n=32) (rs10509681 and rs11572080) had a statistically significantly lower mean C(ss,min) than wild types (n=106), and they also had a statistically significantly lower mean absolute difference in HbA1c during rosiglitazone treatment. Finally, the carriers of CYP2C8*3 had a lower odds ratio of developing oedema.

CONCLUSION

We showed that CYP2C8*3 was associated with lower plasma levels of rosiglitazone and hence a reduced therapeutic response but also a lower risk of developing oedema during treatment with rosiglitazone. Individualized treatment with rosiglitazone on the basis of the CYP2C8 genotype may therefore be possible.

The clinical utility of C-peptide measurement in the care of patients with diabetes

C-peptide is produced in equal amounts to insulin and is the best measure of endogenous insulin secretion in patients with diabetes. Measurement of insulin secretion using C-peptide can be helpful in clinical practice: differences in insulin secretion are fundamental to the different treatment requirements of Type 1 and Type 2 diabetes. This article reviews the use of C-peptide measurement in the clinical management of patients with diabetes, including the interpretation and choice of C-peptide test and its use to assist diabetes classification and choice of treatment. We provide recommendations for where C-peptide should be used, choice of test and interpretation of results. With the rising incidence of Type 2 diabetes in younger patients, the discovery of monogenic diabetes and development of new therapies aimed at preserving insulin secretion, the direct measurement of insulin secretion may be increasingly important. Advances in assays have made C-peptide measurement both more reliable and inexpensive. In addition, recent work has demonstrated that C-peptide is more stable in blood than previously suggested or can be reliably measured on a spot urine sample (urine C-peptide:creatinine ratio), facilitating measurement in routine clinical practice. The key current clinical role of C-peptide is to assist classification and management of insulin-treated patients. Utility is greatest after 3-5 years from diagnosis when persistence of substantial insulin secretion suggests Type 2 or monogenic diabetes. Absent C-peptide at any time confirms absolute insulin requirement and the appropriateness of Type 1 diabetes management strategies regardless of apparent aetiology.

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

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

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.

The genetics of type 2 diabetes and its clinical relevance

The increasing worldwide prevalence of type 2 diabetes (T2D) motivates efforts to use genetics to define key pathways involved in disease predisposition, and thereby to improve management of the disease. Research over the past 5 years has taken the total number of genetic loci implicated in T2D susceptibility beyond 60, and the emphasis is now shifting to the translation of these genetic insights into clinical value. Clinical translation may flow from the identification of novel therapeutic targets, but opportunities also exist with respect to individual prediction, diagnostic biomarkers and therapeutic optimization. To date, the main clinical impact has been seen for relatively rare, monogenic forms of diabetes rather than common T2D. However, the advent of high throughput sequencing approaches may herald discovery of rare and low frequency variants that offer greater translational potential.

Association of the PPARG Pro12Ala polymorphism with type 2 diabetes and incident coronary heart disease in a Hong Kong Chinese population

AIMS

We examined the risk association between single nucleotide polymorphisms (SNPs) in eleven candidate genes with type 2 diabetes (T2D). T2D-associated polymorphisms were also examined for prediction of incident CHD.

METHODS

113 tagging SNPs were genotyped in stage 1 (467 T2D cases, 290 controls), and 15 SNPs were analyzed in the final cohort (1462 T2D cases, 600 controls). Three T2D-associated SNPs were further tested for prediction of CHD within a subset of 1417 T2D cases free of CHD at enrolment.

RESULTS

In the case-control analysis, PPARG rs1801282 (Pro12Ala) (OR=1.48 (1.02-2.16)), ADIPOQ rs1063539 (OR=1.17 (1.01-1.35)), and HNF4A rs1884614 (OR=1.16 (1.00-1.32) were associated with T2D (P(allelic)<0.05). Joint analysis of rs1801282-C, rs1063539-G, and rs1884614-T risk alleles showed an additive dosage effect (P for trend=0.001). Moreover, carriers with two PPARG rs1801282-C risk alleles were associated with an increased risk of incident CHD (HR=4.38 (1.03-18.57), P=0.045) in T2D patients in the prospective analysis.

CONCLUSIONS

Genetic variants of PPARG, ADIPOQ and HNF4A were individually and jointly associated with T2D in Hong Kong Chinese. The PPARG Pro12 risk allele contributed to increased risk for both T2D and CHD.

Exercise training, genetics and type 2 diabetes-related phenotypes

Type 2 diabetes mellitus (T2DM) is at virtually pandemic levels world-wide. Diabetes has been referred to as 'a geneticist's nightmare'. However, dramatic advances in our understanding of the genetics of T2DM have occurred in the past 5 years. While endurance exercise training and increased habitual physical activity levels have consistently been shown to improve or be associated with improved T2DM-related phenotypes, there is substantial interindividual variation in these responses. There is some evidence that T2DM-related phenotype responses to exercise training are heritable, indicating that they might have a genetic basis. Genome-wide linkage studies have not identified specific chromosomal loci that could account for these differences, and no genome-wide association studies have been performed relative to T2DM-related phenotype responses to exercise training. From candidate gene studies, there are relatively strong and replicated data supporting a role for the PPARγ Pro12Ala variant in the interindividual differences in T2DM-related phenotype responses to training. This is a potentially important candidate locus because it affects T2DM susceptibility, has high biological plausibility and is the target for the primary pharmaceutical method for treating T2DM. Is it time to conduct a hypothesis-driven large-scale exercise training intervention trial based on PPARγ Pro12Ala genotype with T2DM-related phenotypes as the primary outcome measures, while also assessing potential mechanistic changes in skeletal muscle and adipose tissue? Or would it be more appropriate to propose a smaller trial to address the specific skeletal muscle and adipose tissue mechanisms affected by the interaction between the PPARγ Pro12Ala genotype and exercise training?

Pharmacogenetics in type 2 diabetes: potential implications for clinical practice

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

Polymorphism of peroxisome proliferator-activated receptor γ (PPARγ) Pro12Ala in the Iranian population: relation with insulin resistance and response to treatment with pioglitazone in type 2 diabetes

The peroxisome proliferator-activated receptor γ (PPARγ) has important effects on insulin sensitivity, obesity and diabetes. Pioglitazone improves insulin sensitivity by activating PPARγ. In view of inter-individual variability in therapeutic response to pioglitazone, this study was designed to search for an association between type 2 diabetes mellitus and Pro12Ala single-nucleotide polymorphism (SNP) in PPARγ (SNP rs1801282) and to investigate whether these genetic variants affect pioglitazone response in an Iranian population. A total of 101 patients with type 2 diabetes were treated for 12 weeks with pioglitazone (15 mg/day). Paraclinical parameters were measured before and after therapy. We genotyped 128 control participants without diabetes and all patients with type 2 diabetes. The Pro12Ala polymorphism in PPARγ was detected with real-time PCR. The Ala allele was found in 7% of the control participants vs. 3% of those with type 2 diabetes (P=0.04). The genotypic frequencies of Pro/Ala were 14.06% in the former group vs. 5.94% in the latter (P=0.036). There were significant changes in some laboratory values and biochemical markers of insulin sensitivity after pioglitazone therapy. The Pro12Ala polymorphism was associated with significant changes in insulin-to-glucose ratio after treatment (P=0.015 and P=0.005). Our findings suggest that in carriers of the 12Ala variant, pioglitazone significantly reduced the risk of type 2 diabetes, and in diabetic patients with the Pro12Ala genotype, the therapeutic response to treatment was better than in patients with the Pro12Pro genotype, although the difference between groups did not reach statistical significance.

Pioglitazone versus Rosiglitazone: Effects on Lipids, Lipoproteins, and Apolipoproteins in Head-to-Head Randomized Clinical Studies

Peroxisome proliferator-activated receptors (PPARs) play an important role in regulating both glucose and lipid metabolism. Agonists for both PPARγ and PPARγ have been used to treat dyslipidemia and hyperglycemia, respectively. In addition to affecting glucose metabolism, PPARγ agonists also regulate lipid metabolism. In this review, we will focus on the randomized clinical trials that directly compared the lipid effects of the thiazolidinedione class of PPARγ agonists, pioglitazone and rosiglitazone, head-to-head either as monotherapy or in combination with other lipid-altering or glucose-lowering agents

PPARγ2 P12A polymorphism and albuminuria in patients with type 2 diabetes: a meta-analysis of case-control studies

BACKGROUND

Insulin resistance has a role in diabetic nephropathy. The A12 variant of the PPARγ2 P121A polymorphism has been firmly associated with reduced risk of insulin resistance, while its role on the risk of albuminuria in patients with type 2 diabetes is uncertain. This study investigated whether the PPARγ2 P12A polymorphism modulates the risk of albuminuria in these patients.

METHODS

We tested the association between the A12 variant and albuminuria in three new case-control studies in diabetic patients from Italy (n = 841, n = 623 and n = 714 patients, respectively) and then performed a meta-analysis of all studies available to date. The nine studies we meta-analysed (six previously published and three presented here) comprised a total of 2376 cases and 4188 controls.

RESULTS

In none of the three new studies was a significant association observed with odds ratio (OR) [95% confidence intervals (95% CI)] being 1.115, 0.799 and 0.849 (P = 0.603, 0.358 and 0.518, respectively). At meta-analysis, the overall OR (95% CI) for association between A12 and albuminuria was 0.694 (0.528-0.912). A significant heterogeneity of the genetic effect was observed (P = 0.026), which was totally explained by the different method of urine collection and albuminuria definition utilized across the studies. In fact, most of the effect was observed in the four studies determining albumin excretion rate rather than in those using albumin concentration in a single spot (OR, 95% CI: 0.529, 0.397-0.706, P = 0.0000164 and 0.919, 0.733-1.153, P = 0.47, respectively).

CONCLUSION

The present study shows that the PPARγ2 Ala12 variant is significantly associated with a reduced risk of albuminuria among patients with type 2 diabetes.

Therapy with oral antidiabetic drugs: applied pharmacogenetics

Pharmacogenetics focuses on the relationship between individual gene variants and variable drug effects. The present brief review addresses the importance of pharmacogenetic factors for the efficacy and adverse effects of oral antidiabetic drugs in the therapy of type 2 diabetes mellitus. In particular, genetic polymorphisms of cytochrome P450 drug metabolizing enzymes, peroxisome proliferator-activated receptor- γ gene, TCF7L2 gene regulating insulin resistance and secretion and organic cation transporters or organic anion transporting polypeptides modify the individual response to drugs such as metformin, thiazolidinediones, sulphonylureas, meglitinides, and DPP4 inhibitors. However, apart from a complex variety of individual factors, genetic heterogeneity makes assessing the role of genetic factors in diabetes therapy for a single individual highly challenging. Continuing advances in pharmacogenetics will uncover further genetic variants that modify responses to diabetes medications and may offer targeted pharmacotherapy to the patient.

Statistical issues in gene association studies

This chapter reviews statistical issues related to gene association studies. The goal is to review various aspects of study design and analysis for individuals who do not have an extensive statistical background. We will review statistical issues as they relate to both genome-wide and candidate gene studies. Topics reviewed include study design, power and sample size, data checking, statistical methods, population stratification, and multiple testing. We draw examples from the type 2 diabetes genetics literature to illustrate some of the issues discussed.

Genetic polymorphisms in diabetes: influence on therapy with oral antidiabetics

Due to new genetic insights, etiologic classification of diabetes is under constant scrutiny. Hundreds, or even thousands, of genes are linked with type 2 diabetes. Three common variants (Lys23 of KCNJ11, Pro12 of PPARG, and the T allele at rs7903146 of TCF7L2) have been shown to be predisposed to type 2 diabetes mellitus across many large studies. Individually, each of these polymorphisms is only moderately predisposed to type 2 diabetes. On the other hand, monogenic forms of diabetes such as MODY and neonatal diabetes are characterized by unique clinical features and the possibility of applying a tailored treatment.Genetic polymorphisms in drug-metabolizing enzymes, transporters, receptors, and other drug targets have been linked to interindividual differences in the efficacy and toxicity of a number of medications. Mutations in genes important in drug absorption, distribution, metabolism and excretion (ADME) play a critical role in pharmacogenetics of diabetes.There are currently five major classes of oral pharmacological agents available to treat type 2 diabetes: sulfonylureas, meglitinides, metformin (a biguanide), thiazolidinediones, and α-glucosidase inhibitors. Other classes are also mentioned in literature.In this work, different types of genetic mutations (mutations of the gene for glucokinase, HNF 1α, HNF1β and Kir6.2 and SUR1 subunit of KATP channel, PPAR-γ, OCT1 and OCT2, cytochromes, direct drug-receptor (KCNJ11), as well as the factors that influence the development of the disease (TCF7L2) and variants of genes that lead to hepatosteatosis caused by thiazolidinediones) and their influence on the response to therapy with oral antidiabetics will be reviewed.

The genetics of type 2 diabetes: what have we learned from GWAS?

Type 2 diabetes mellitus has been at the forefront of human diseases and phenotypes studied by new genetic analyses. Thanks to genome-wide association studies, we have made substantial progress in elucidating the genetic basis of type 2 diabetes. This review summarizes the concept, history, and recent discoveries produced by genome-wide association studies for type 2 diabetes and glycemic traits, with a focus on the key notions we have gleaned from these efforts. Genome-wide association findings have illustrated novel pathways, pointed toward fundamental biology, confirmed prior epidemiological observations, drawn attention to the role of β-cell dysfunction in type 2 diabetes, explained ~10% of disease heritability, tempered our expectations with regard to their use in clinical prediction, and provided possible targets for pharmacotherapy and pharmacogenetic clinical trials. We can apply these lessons to future investigation so as to improve our understanding of the genetic basis of type 2 diabetes.

Genetic variants affecting incretin sensitivity and incretin secretion

Recent genome-wide association studies identified several novel risk genes for type 2 diabetes. The majority of these type 2 diabetes risk variants confer impaired pancreatic beta cell function. Though the molecular mechanisms by which common genetic variation within these loci affects beta cell function are not completely understood, risk variants may alter glucose-stimulated insulin secretion, proinsulin conversion, and incretin signals. In humans, the incretin effect is mediated by the secretion and insulinotropic action of two peptide hormones, glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1. This review article aims to give an overview of the type 2 diabetes risk loci that were found to associate with incretin secretion or incretin action, paying special attention to the potential underlying mechanisms.

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

We investigated the effects of the common polymorphisms in the peroxisome proliferator-activated receptor-gamma (PPAR-gamma; Pro12Ala) and in PPAR-gamma coactivator-1(PGC-1; Gly482Ser) genes on the response to pioglitazone in Chinese with type 2 diabetes mellitus. A total of 250 patients with type 2 diabetes mellitus were treated with pioglitazone (30 mg/d) for 24 weeks without a change in previous medications. All patients were genotyped for the PPAR-gamma Pro12Ala and PGC-1 Gly482Ser polymorphisms. The Ala12Ala and Pro12Ala genotypes (26.0% vs 13.5%, P = .025) and Ala allele (15.6% vs 7.3%, P = .008) were significantly more frequent in pioglitazone responders than in nonresponders. The distribution of PGC-1 genotypes and alleles was not significantly different between responders and nonresponders. The decrease in fasting glucose (50.4 +/- 52.2 vs 43.3 +/- 51.7 mg/dL, P < .001) and hemoglobin A(1c) (0.57% +/- 1.44% vs 0.35% +/- 1.10%, P = .004) levels was significantly greater in subjects with the Ala12 carriers (Pro12Ala and Ala12Ala) than in those without the allele (Pro12Pro). Baseline fasting glucose and triglyceride levels were related to the response of pioglitazone. Only the PPAR-gamma Pro12Ala polymorphism was found to be associated with the response of pioglitazone by multiple logistic regression analysis. The PPAR-gamma Pro12Ala gene polymorphism is associated with the response to pioglitazone in Chinese patients with type 2 diabetes mellitus. These findings may be helpful for targeted treatment of diabetes by identifying patients who are likely to respond to pioglitazone.

Pharmacogenetics of Anti-Diabetes Drugs

A variety of treatment modalities exist for individuals with type 2 diabetes mellitus (T2D). In addition to dietary and physical activity interventions, T2D is also treated pharmacologically with nine major classes of approved drugs. These medications include insulin and its analogues, sulfonylureas, biguanides, thiazolidinediones (TZDs), meglitinides, α-glucosidase inhibitors, amylin analogues, incretin hormone mimetics, and dipeptidyl peptidase 4 (DPP4) inhibitors. Pharmacological treatment strategies for T2D are typically based on efficacy, yet favorable responses to such therapeutics are oftentimes variable and difficult to predict. Characterization of drug response is expected to substantially enhance our ability to provide patients with the most effective treatment strategy given their individual backgrounds, yet pharmacogenetic study of diabetes medications is still in its infancy. To date, major pharmacogenetic studies have focused on response to sulfonylureas, biguanides, and TZDs. Here, we provide a comprehensive review of pharmacogenetics investigations of these specific anti-diabetes medications. We focus not only on the results of these studies, but also on how experimental design, study sample issues, and definition of 'response' can significantly impact our interpretation of findings. Understanding the pharmacogenetics of anti-diabetes medications will provide critical baseline information for the development and implementation of genetic screening into therapeutic decision making, and lay the foundation for "individualized medicine" for patients with T2D.

A review of the response to oral antidiabetes agents in patients with type 2 diabetes

In patients with type 2 diabetes, a progressive decline in glycemic control exacerbates the microvascular (retinopathy, neuropathy, and nephropathy) and macrovascular (cardiovascular disease, stroke, and peripheral arterial disease) complications associated with this disease. In a consensus statement, the American Diabetes Association and the European Association for the Study of Diabetes stated that the main goal of antidiabetes therapy is to achieve glycemic control, defined as a glycated hemoglobin of < 7%, although goals should be individualized to each patient, especially in patients at highest risk of cardiovascular disease events. However, because type 2 diabetes is a progressive disease, the response to oral antidiabetes (OAD) agents declines over time and the majority of patients are unable to maintain glycemic control, thus necessitating additional therapy. This requirement for additional antidiabetes therapies as the disease progresses suggests that more aggressive and earlier use of synergistic therapies may help achieve and prolong glycemic control. This review examines the efficacy of OAD therapies to address the unmet need for prompt and maintained glycemic control to the recommended goal in patients with type 2 diabetes, the factors that can affect the glycemic response to the various classes of OAD agents, and ways in which the management of hyperglycemia can be improved in patients with type 2 diabetes.

Effects of the peroxisome proliferator activated receptor-γ coactivator-1α (PGC-1α) Thr394Thr and Gly482Ser polymorphisms on rosiglitazone response in Chinese patients with type 2 diabetes mellitus

The objective was to investigate whether peroxisome proliferator activated receptor-γ coactivator-1α (PGC-1α) Thr394Thr and Gly482Ser polymorphisms influence rosiglitazone response in Chinese patients with type 2 diabetes mellitus. Among the 241 patients enrolled in genotyping for PGC-1α Thr394Thr and Gly482Ser polymorphisms by polymerase chain reaction-restriction fragment length polymorphism assay, 41 patients with different Thr394Thr or Gly482Ser genotypes received oral rosiglitazone (4 mg/d) for 12 consecutive weeks. Carriers of A allele of Thr394Thr had high density lipoprotein-cholesterol that was enhanced to a lesser degree and smaller attenuated postprandial serum insulin compared with G alleles (P < .05), and patients with PGC-1α Gly482Gly had fasting plasma glucose that was attenuated to a greater degree (P < .01) and postprandial serum insulin (P < .05) compared with Gly482Ser+Ser482Ser. After rosiglitazone treatment, carriers of A allele of Thr394Thr and Ser allele of Gly482Ser showed a trend in worsening for GG (P < .05) and a significant therapeutic response to rosiglitazone for Gly/Gly (P < .05). These data suggest that the PGC-1α Thr394Thr and Gly482Ser polymorphisms are associated with therapeutic efficacy of multiple-dose rosiglitazone in Chinese patients with type 2 diabetes mellitus.