Sequence variation in PPARG may underlie differential response to troglitazone

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.

Physiologic Interpretation of GWAS Signals for Type 2 Diabetes

This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.

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.

DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes

DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380 000 associations between >16 000 genes and 13 000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/

Divergent compensatory responses to high-fat diet between C57BL6/J and C57BLKS/J inbred mouse strains

Impaired glucose tolerance (IGT) and type 2 diabetes (T2DM) are polygenic disorders with complex pathophysiologies; recapitulating them with mouse models is challenging. Despite 70% genetic homology, C57BL/6J (BL6) and C57BLKS/J (BLKS) inbred mouse strains differ in response to diet- and genetic-induced obesity. We hypothesized these differences would yield insight into IGT and T2DM susceptibility and response to pharmacological therapies. To this end, male 8-wk-old BL6 and BLKS mice were fed normal chow (18% kcal from fat), high-fat diet (HFD; 42% kcal from fat), or HFD supplemented with the PPARγ agonist pioglitazone (PIO; 140 mg PIO/kg diet) for 16 wk. Assessments of body composition, glucose homeostasis, insulin production, and energy metabolism, as well as histological analyses of pancreata were undertaken. BL6 mice gained weight and adiposity in response to HFD, leading to peripheral insulin resistance that was met with increased β-cell proliferation and insulin production. By contrast, BLKS mice responded to HFD by restricting food intake and increasing activity. These behavioral responses limited weight gain and protected against HFD-induced glucose intolerance, which in this strain was primarily due to β-cell dysfunction. PIO treatment did not affect HFD-induced weight gain in BL6 mice, and decreased visceral fat mass, whereas in BLKS mice PIO increased total fat mass without improving visceral fat mass. Differences in these responses to HFD and effects of PIO reflect divergent human responses to a Western lifestyle and underscore the careful consideration needed when choosing mouse models of diet-induced obesity and diabetes treatment.

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.

Genetic determinants of cardiometabolic risk: a proposed model for phenotype association and interaction

This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes, and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus, it follows that the genetics of dyslipidemia, obesity, and nonalcoholic fatty liver disease are central in triggering progression of the syndrome to overt expression of disease traits and have become a key focus of interest for early detection and for designing prevention and treatments. To support the "birds' eye view" approach, we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacologic targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance.

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.

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?

Type 2 diabetes in pediatrics and adults: thoughts from a clinical pharmacology perspective

Type 2 diabetes results when insulin secretion is unable to keep the plasma glucose levels as per acceptable range. This leads to chronic hyperglycemia and its associated microvascular complications such as renal impairment (diabetic nephropathy), retinal abnormalities (diabetic retinopathy), and autonomic, sensory, and motor neuropathies (diabetic neuropathy) and macrovascular disease. Historically, type 2 diabetes is well known as an adult-onset disease; however, lately, the incidence of the disease is reported to be increasing in children. Despite the wealth of information concerning type 2 diabetes in adults, data unique to the pediatric age group regarding the pathophysiology and therapy for type 2 diabetes are limited. For treatment in pediatric type 2 diabetes, metformin and insulin are the only antidiabetic agents approved currently. There are data of use of other oral antidiabetic drugs including glimepiride, rosiglitazone, and glyburide (in combination with metformin) in pediatric patients; however, formal clinical trials to establish the safety and efficacy have not been conducted. This review will compare the clinical pharmacology aspects of the oral type 2 diabetic drugs in pediatric and adult populations in order to determine any differences between the two patient groups.

Type 2 Diabetes Genetics: Beyond GWAS

The global epidemic of type 2 diabetes mellitus (T2D) is one of the most challenging problems of the 21(st) century leading cause of and the fifth death worldwide. Substantial evidence suggests that T2D is a multifactorial disease with a strong genetic component. Recent genome-wide association studies (GWAS) have successfully identified and replicated nearly 75 susceptibility loci associated with T2D and related metabolic traits, mostly in Europeans, and some in African, and South Asian populations. The GWAS serve as a starting point for future genetic and functional studies since the mechanisms of action by which these associated loci influence disease is still unclear and it is difficult to predict potential implication of these findings in clinical settings. Despite extensive replication, no study has unequivocally demonstrated their clinical role in the disease management beyond progression to T2D from impaired glucose tolerance. However, these studies are revealing new molecular pathways underlying diabetes etiology, gene-environment interactions, epigenetic modifications, and gene function. This review highlights evolving progress made in the rapidly moving field of T2D genetics that is starting to unravel the pathophysiology of a complex phenotype and has potential to show clinical relevance in the near future.

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.

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.

Polymorphisms of the peroxisome proliferator-activated receptor γ (PPARγ) gene are associated with osteoporosis

Stimulation of PPARγ turns mesenchymal stem cells into adipocytes instead of osteoblasts. We investigated the effect of polymorphisms in the PPARγ gene on BMD and fracture risk in two Danish cohorts and found opposing effects of certain SNPs and haplotypes in the two cohorts probably owing to environmental factors.

INTRODUCTION

Stimulation of PPARγ causes development of mesenchymal stem cells to adipocytes instead of osteoblasts leading to decreased osteoblast number and BMD. The aim of this study was to examine the effect of PPARG polymorphisms on BMD and fracture risk in two Danish cohorts: AROS, a case-control population comprising 809 individuals and DOPS, a population comprising 1,716 perimenopausal women allocated to hormone therapy or not at baseline and followed for 10 years. On the basis of linkage disequilibrium between SNPs throughout the gene and previous studies we chose 10 polymorphisms for investigation.

METHODS

In AROS, individuals heterozygous for the polymorphisms rs12497191, rs4135263, and rs1151999 had an increased risk of vertebral fractures (OR = 1.48-1.76, p = 0.005-0.04) compared with individuals homozygous for the common allele. In DOPS, individuals heterozygous for rs1151999 had an increased BMD at the hip sites (p ≤ 0.02). An interaction between rs1151999 and diet was found on BMD in both cohorts.

RESULTS

For the polymorphism rs1152003 there was an interaction with body weight on BMD at all sites in both cohorts (p ≤ 0.07). Stratified analyses revealed that in the high weight group in AROS individuals homozygous for the variant allele had a decreased BMD (p ≤ 0.02), whereas the same pattern was found in the low weight group in DOPS (p ≤ 0.03). A number of haplotype associations were found as well, the direction of which was opposite in the two cohorts.

CONCLUSION

Our study suggests an association SNPs in PPARG and haplotypes thereof and BMD and fracture risk. The effect however appears to be modifiable by environmental factors.

PPAR Genomics and Pharmacogenomics: Implications for Cardiovascular Disease

The peroxisome proliferator-activated receptors (PPARs) consist of three related transcription factors that serve to regulate a number of cellular processes that are central to cardiovascular health and disease. Numerous pharmacologic studies have assessed the effects of specific PPAR agonists in clinical trials and have provided insight into the clinical effects of these genes while genetic studies have demonstrated clinical associations between PPAR polymorphisms and abnormal cardiovascular phenotypes. With the abundance of data available from these studies as a background, PPAR pharmacogenetics has become a promising and rapidly advancing field. This review focuses on summarizing the current state of understanding of PPAR genetics and pharmacogenetics and the important implications for the individualization of therapy for patients with cardiovascular diseases.

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.

Nuclear receptors as new perspective for the management of liver diseases

Nuclear receptors (NRs) are ligand-activated transcription factors that act as sensors for a broad range of natural and synthetic ligands and regulate several key hepatic functions including bile acid homeostasis, bile secretion, lipid and glucose metabolism, as well as drug deposition. Moreover, NRs control hepatic inflammation, regeneration, fibrosis, and tumor formation. Therefore, NRs are key for understanding the pathogenesis and pathophysiology of a wide range of hepatic disorders. Finally, targeting NRs and their alterations offers exciting new perspectives for the treatment of liver diseases.

Inherited destiny? Genetics and gestational diabetes mellitus

Despite years of investigation, very little is known about the genetic predisposition for gestational diabetes mellitus (GDM). However, the advent of genome-wide association and identification of loci contributing to susceptibility to type 2 diabetes mellitus has opened a small window into the genetics of GDM. More importantly, the study of the genetics of GDM has not only illuminated potential new biology underlying diabetes in pregnancy, but has also provided insights into fetal outcomes. Here, I review some of the insights into GDM and fetal outcomes gained through the study of both rare and common genetic variation. I also discuss whether recent testing of type 2 diabetes mellitus susceptibility loci in GDM case-control samples changes views of whether GDM is a distinct form of diabetes. Finally, I examine how the study of susceptibility loci can be used to influence clinical care, one of the great promises of the new era of human genome analysis.

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.

Weight regain after a diet-induced loss is predicted by higher baseline leptin and lower ghrelin plasma levels

CONTEXT

Appetite-related hormones may play an important role in weight regain after obesity therapy.

OBJECTIVE

Our objective was to investigate the potential involvement of ghrelin, leptin, and insulin plasma levels in weight regain after a therapeutic hypocaloric diet.

DESIGN

A group of obese/overweight volunteers (49 women and 55 men; 35 ± 7 yr; 30.7 ± 2.4 kg/m(2)) followed an 8-wk hypocaloric diet (-30% energy expenditure) and were evaluated again 32 wk after treatment. Body weight as well as plasma fasting ghrelin, leptin, and insulin concentrations were measured at three points (wk 0, 8, and 32).

RESULTS

After the 8-wk hypocaloric diet, the average weight loss was -5.0 ± 2.2% (P < 0.001). Plasma leptin and insulin concentrations decreased significantly, whereas ghrelin levels did not markedly change. In the group regaining more than 10% of the weight loss, leptin levels were higher (P < 0.01), whereas ghrelin levels were lower (P < 0.05). No differences were observed in insulin levels. Weight regain at wk 32 was negatively correlated with ghrelin and positively associated with leptin levels at baseline (wk 0) and endpoint (wk 8). These outcomes showed a gender-specific influence, being statistically significant among men for ghrelin and between women for leptin. Moreover, a decrease in ghrelin after an 8-wk hypocaloric diet was related to an increased risk for weight regain (odds ratio = 3.109; P = 0.008) whereas a greater reduction in leptin (odds ratio = 0.141; P = 0.001) was related to weight-loss maintenance.

CONCLUSIONS

Subjects with higher plasma leptin and lower ghrelin levels at baseline could be more prone to regain lost weight, and hormones levels could be proposed as biomarkers for predicting obesity-treatment outcomes.

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.

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.

Personalized pharmacotherapy for Type 2 diabetes mellitus

Genome-wide linkage and association studies have been applied to Type 2 diabetes in order to discover common genetic variation that contributes to disease risk. While there has been progress in understanding how genetic variation predisposes to diabetes, there is less of an understanding of how genetics can alter drug response. The hope is that in the future, pharmacogenetics can help guide the treatment of diabetes, thereby improving control while minimizing side effects in a large group of patients.

Pharmacogenetics for type 2 diabetes: practical considerations for study design

There is a relative dearth of studies designed to elucidate genetic variation that can explain differences in the response to diabetes pharmacotherapy. When designing such studies, appropriate consideration of the various nongenetic variables that can affect the treatment response is necessary. In addition, disease stage and prior pharmacotherapy also influence drug efficacy. Selecting the appropriate genetic variant to test in such studies is also important, and common variants (known to be functional or otherwise) in a given candidate locus should be tested for the effect on the treatment response. Finally, an appropriate measure of treatment response is necessary to enable detection of pharmacogenetic effects. Perhaps prior to undertaking such studies, smaller studies utilizing well-characterized, homogenous populations with normal glucose tolerance or prediabetes (to avoid the problem of disease effects on treatment response) and surrogate measures of response such as insulin secretion should be completed.

Genetic susceptibility to type 2 diabetes and implications for therapy

Since 2000, we have witnessed an explosion of known genetic determinants of type 2 diabetes risk. These findings have seeded the expectation that our ability to make personalized, predictive, therapeutic clinical decisions is imminent. However, the loci discovered to date explain only a small fraction of overall inheritable risk for this disease. In many cases, the reported associations merely signal regions of the genome that are overrepresented in disease versus health but do not identify the causal variants. Well-powered cohort studies have shown that the set of markers detected thus far does not significantly improve individual risk prediction or stratification over common clinical variables, with the possible exception of younger subjects. On the other hand, risk genotypes may help target subgroups for more intensive surveillance or prevention efforts, although whether such a strategy improves patient outcomes and/or is cost-effective should be examined. Similarly, whether genetic information will help guide therapeutic decisions must be tested in adequately designed and rigorously conducted clinical trials.

Influence of SLCO1B1 and CYP2C8 gene polymorphisms on rosiglitazone pharmacokinetics in healthy volunteers

Polymorphisms in drug transporter genes and/or drug-metabolising enzyme genes may contribute to inter-individual variability in rosiglitazone pharmacokinetics in humans. We sought to determine the joint effects of polymorphisms in the SLCO1B1 drug transporter gene and the cytochrome P450 ( CYP ) 2C8-metabolising enzyme gene on rosiglitazone pharmacokinetics in healthy volunteers. Healthy Caucasian subjects were prospectively enrolled on the basis of SLCO1B1 521 T > C genotype. Additionally, subjects were genotyped for SLCO1B1 -11187 G > A, -10499 A > C and 388 A > G polymorphisms, and the CYP2C8*3 polymorphism. SLCO1B1 haplotypes and diplotypes were computationally assigned. Rosiglitazone plasma concentrations were determined by high-performance liquid chromatography and analysed using non-compartmental methods. The study population consisted of 26 subjects, with a mean age of 33 +/- 9 years, and a mean weight of 66.6 +/- 11.7 kg. There were no significant differences in rosiglitazone pharmacokinetic parameters between SLCO1B1 diplotype groups. Subjects with the CYP2C8*1/*3 genotype ( n = 7), however, had significantly lower rosiglitazone area under the plasma concentration-time curve (AUC) and significantly higher rosiglitazone oral clearance, compared with CYP2C8 wild-type homozygotes ( n = 19). Stepwise linear regression analysis revealed that CYP2C8 genotype ( p = 0.006) and weight ( p = 0.022) were significant predictors of rosiglitazone AUC (overall p = 0.002; R 2 = 41.6 per cent). We concluded that polymorphisms in the CYP2C8 drug-metabolising enzyme gene, but not the SLCO1B1 drug transporter gene, significantly influence rosiglitazone disposition in humans. Future studies examining the influence of CYP2C8 genotypes and haplotypes on thiazolidinedione disposition and response in patients with type 2 diabetes are warranted.

Pharmacogenetics in diabetes

Genetic variation can impact on efficacy and risk of adverse events to commonly used oral agents in -diabetes. Metformin is not metabolized and its mechanism of action remains debated; however, several cation transporters have been identified. Variation in these pharmacokinetic genes might influence metformin response. Conversely, although the cytochrome P450 system has been implicated in sulfonylurea response in some small studies, to date variants affecting pharmacodynamics, including those in ABCC8 (SUR1) and TCF7L2, are the most promising. For thiazolidinedione response, variants in PPARG or ADIPOQ (adiponectin) have been variably associated with response. With increasing well-phenotyped cohorts and new methods, including genome-wide association studies, the next few years offer great hope to use pharmacogenetics to unravel drug and disease mechanisms, as well as the possibility to individualize therapy by genotype.

Clinical translation of genetic predictors for type 2 diabetes

PURPOSE OF REVIEW

To highlight recent type 2 diabetes (T2D)-associated genetic discoveries and their potential for clinical application.

RECENT FINDINGS

The advent of genome-wide association screening has uncovered many loci newly associated with T2D. This review describes the techniques applied to discover novel T2D genes and compares their relative strengths, biases, and findings to date. The results of large-scale genome-wide association studies carried out since 2007 are summarized, and limitations of interpreting this preliminary data are offered. Recent studies exploring the clinical potential of these discoveries are reviewed, focusing on insights into T2D pathogenesis, risk prediction of future diabetes, and utility in guiding pharmacotherapy. The new T2D-associated loci have been implicated in beta-cell development and function, highlighting insulin secretion in the disease process. Preliminary risk prediction studies show that more loci are needed to improve T2D risk indices. Studies have also revealed that genes may play a role in the pharmacologic response to antidiabetic medications.

SUMMARY

Since 2007, genome-wide association studies have rapidly increased the number of T2D-associated loci. This review summarizes the history of genetic association studies, the results from the new genome-wide association studies, and the clinical application of these findings.

The Pro 12 Ala PPAR gamma gene polymorphism: possible modifier of the activity and severity of thyroid-associated orbitopathy (TAO)

OBJECTIVE

The PPAR gamma transcription factor, is involved in both adipogenesis and inflammation, which have been implicated in the pathogenesis of thyroid-associated orbitopathy (TAO). The aim of this study was to explore the possibility that the Pro(12)Ala polymorphism of the PPAR gamma gene, associated with a modified transcriptional activity, might be affecting the severity of TAO.

SUBJECTS AND DESIGN

We studied two cohorts of patients with Graves' disease (GD): Group 1 comprised 172 patients of Dutch ethnic origin with TAO, who attended the outpatients' clinic, Department of Endocrinology and Orbital Centre of the Academic Medical Centre, Amsterdam. Group 2 comprised 93 consecutive patients with GD of Greek ethnic origin, who did not have TAO. In group 1, exophthalmometry measurements, lid oedema, diplopia (n = 172) and clinical activity score (CAS) (n = 110), always assessed by the same group of three investigators, were recorded. Autoantibody levels were measured.

RESULTS

Allele frequency was 11.5%. There was no difference in the distribution of the polymorphism between GD patients with and without TAO. Among group 1 patients proptosis was significantly lower in Pro(12)Ala carriers (20.1 +/- 3.3 vs. 22.1 +/- 3.1, P = 0.003, t-test). PPAR gamma polymorphism carriers had lower TSH-Rab levels (mean rank 61.8 vs. 83.2, P = 0.015) and lower CAS (available in 110 patients) (mean rank 38.9 vs. 55.4, P = 0.022, M-W-test). The frequency of the polymorphism decreased with increasing CAS (P = 0.023 linear by linear association). Multivariate analysis (step) showed that the association of either proptosis or CAS with the PPAR gamma gene variant remained significant when age, smoking and TSH-Rab levels were taken into account (P < 0.01).

CONCLUSIONS

The distribution of the Pro(12)Ala PPAR gamma gene polymorphism is equally present in patients with GD with or without TAO. Among patients with TAO this polymorphism is associated with less-severe and less-active disease.

PPAR transcriptional activator complex polymorphisms and the promise of individualized therapy for heart failure

The PPAR gene pathway consists of interrelated genes that encode transcription factors, enzymes, and downstream targets which coordinately act to regulate cellular processes central to glucose and lipid metabolism. The pathway includes the PPAR genes themselves, other class II nuclear hormone receptor transcription factors within the PPAR family, PPAR co-activators, PPAR co-repressors, and downstream metabolic gene targets. This review focuses on the transcription factors that comprise the PPAR transcriptional activator complex--the PPARs (PPARalpha, PPARbeta, or PPARgamma), PPAR heterodimeric partners, such as RXRalpha, and PPAR co-activators, such as PPARgamma coactivator 1alpha (PGC-1alpha) and the estrogen-related receptors (ERRalpha, ERRbeta, and ERRgamma). These transcription factors have been implicated in the development of myocardial hypertrophy and dilated cardiomyopathy as well as response to myocardial ischemia/infarction and, by association, ischemic cardiomyopathy. Human expression studies and animal data are presented as the background for a discussion of the emerging field of pharmacogenetics as it applies to these genes and the consequent implications for the individualization of therapy for patients with heart failure.

Genetics: how the UKPDS contributed to determining the genetic landscape of Type 2 diabetes

The identification and functional characterisation of genetic variants that either cause or predispose to diabetes is a major focus of biomedical research. The molecular basis is now known for the majority of monogenic forms of diabetes arising from pancreatic beta-cell dysfunction; however finding the genetic variants underlying susceptibility to Type 2 diabetes (T2DM) has been a greater technical, statistical and biological challenge. The advent of biology-agnostic approaches made possible by the improved arsenal of research platforms and genetic tools available has increased the number of known T2DM genes dramatically and provided important insights into the pathophysiology of T2DM. Over the past 18 months, the list of T2DM susceptibility genes has grown from three to close to 20, illustrating the substantial progress which has been made. These recent milestones have not only illustrated the limited knowledge we have of the pancreatic beta-cell, but have also reinforced our belief in the involvement of common genetic variants in the genes involved in monogenic forms of diabetes in the susceptibility to T2DM and have clearly shown a primary role for pancreatic beta-cell dysfunction in T2DM. Both of these concepts were explored in the early work of the UK Prospective Diabetes Study (UKPDS) genetics research groups.

Pharmacogenetics: potential role in the treatment of diabetes and obesity

BACKGROUND

Common genetic variation is associated with increased risk of common metabolic diseases such as type 1 and type 2 diabetes, and obesity. Increasing experience with genetic association studies has led to an understanding of the large sample sizes required to detect a weak to moderate genetic predisposition to disease, the need to reproduce such associations in independent cohorts, and the statistical criteria required to detect a true association. This approach has been used successfully to identify disease-associated gene variation usually in representative populations of large numbers.

OBJECTIVE

To review the current understanding of how common genetic variation influences predisposition to, and treatment of, metabolic disease.

METHODOLOGY

Review of scientific literature.

RESULTS

While there has been progress in understanding how genetic variation predisposes to diabetes and obesity, and how candidate genes may alter drug response, several caveats limit the interpretation and significance of pharmacogenetic studies published to date: those caveats typically include relatively small numbers of participants and choice of endpoints in determining gene-associated differences in response, which may not be clinically significant or relevant as a biomarker or predictor of a desired clinical effect. The genetic variants studied at a given locus are often limited in number and may not represent a comprehensive map of the region under study.

CONCLUSIONS

The pharmacogenetic associations in diabetes and obesity that have been reported to date have had limited impact on the choice of individual treatments. We perceive, however, that this field is in its infancy in these multifactorial metabolic diseases, and with further advances and future drug intervention trials designed in a way that allows a more clear interpretation of the impact of genetic variation on differences in drug response in obesity and diabetes, it is anticipated that pharmacogenetics will have a significant impact on individualizing medical care.

Pharmacogenomics of metabolic effects of rosiglitazone

INTRODUCTION

Thiazolidinediones are increasingly used drugs for the treatment of Type 2 diabetes. The individual response to thiazolidinedione therapy, ranging from the variable degree of metabolic improvement to harmful side-effects, is empirical, yet the underlying mechanisms remain elusive. In order to assess the pharmacogenomic component of thiazolidinediones' metabolic action, we compared the effect of rosiglitazone in two genetically defined models of metabolic syndrome, polydactylous (PD) and BN.SHR4 inbred rat strains, with their insulin-sensitive, normolipidemic counterpart, the Brown Norway (BN) rat.

MATERIALS & METHODS

5-month-old male rats were fed a high-fat diet for 4 weeks, and the experimental groups received rosiglitazone (0.4 mg/100 g body weight) during the last 2 weeks of high-fat diet feeding. We assessed metabolic and morphometric profiles, oxidative stress parameters and gene expression in white adipose tissue.

RESULTS

In many followed parameters, we observed genetic background-specific effects of rosiglitazone administration. The mass and the sensitivity of visceral adipose tissue to insulin-stimulated lipogenesis increased with rosiglitazone treatment only in PD, correlating with a PD-specific significant increase in expression of prostaglandin D2 synthase. The glucose tolerance was enhanced in all strains, although fasting plasma glucose was increased by rosiglitazone in BN and BN.SHR4. Among the markers of lipid peroxidation, we observed the rosiglitazone-driven increase of plasma-conjugated dienes only in BN.SHR4. The genes with genotype-specific expression change included ADAM metallopeptidase domain 7, aquaporin 9, carnitine palmitoyltransferase 1B, caveolin 1, catechol-O-methyl transferase, leptin and prostaglandin D2 synthase 2.

CONCLUSION

Rosiglitazone's effects on lipid deposition and insulin sensitivity of peripheral tissues are largely dependent on the genetic background it acts upon.

SNPs in PPARG associate with type 2 diabetes and interact with physical activity

PURPOSE

To study the associations of seven single-nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptor gamma (PPARG) gene with the conversion from impaired glucose tolerance (IGT) to type 2 diabetes (T2D), and the interactions of the SNPs with physical activity (PA).

METHODS

Overweight individuals with IGT who participated in the Finnish Diabetes Prevention Study (DPS) (N = 479) were followed, on average, 4.2 yr. PA was assessed yearly with a 12-month validated questionnaire.

RESULTS

In Cox regression analyses, the rare alleles of rs17036314 and rs1801282 (Pro12Ala) predicted conversion to T2D (P = 0.038 and 0.037, respectively), but only rs17036314 predicted T2D after adjustment for baseline fasting glucose (P = 0.030). The change in the total amount of PA, stratified by median, modified the association of rs17036314 and rs1801282 with the risk of T2D during the intervention (P = 0.002 and 0.031, respectively, for interaction between PA change and genotype); an increase in PA seemed to remove the effect of the risk alleles. The distinct rs1152003 polymorphism interacted with the study group on the conversion to T2D (P = 0.027) and tended to increase the risk of T2D in the intervention group (P = 0.050). No interaction between rs1152003 and the change in PA was found.

CONCLUSIONS

The rs17036314, rs1801282 (Pro12Ala), and rs1152003 were associated with the risk of T2D in the DPS. Increased PA seemed to decrease the effect of the risk alleles of rs17036314 and rs1801282 on the conversion to T2D. The effect of rs1152003 was modified by other lifestyle changes or the lifestyle intervention as a whole.

Effects of ABCA1 variants on rosiglitazone monotherapy in newly diagnosed type 2 diabetes patients

AIM

The aim of the present study was to investigate the relationship between R219K, M883I, and R1587K variants of the ATP-binding cassette transporter subfamily A number 1 (ABCA1) gene and response to rosiglitazone treatment in newly diagnosed patients with type 2 diabetes.

METHODS

A total of 105 diabetic patients with no history of antihyperglycemia medication were treated with rosiglitazone (4 or 8 mg daily) for 48 weeks. Three non-synonymous variants R219K, M883I, and R1587K, were genotyped in all patients.

RESULTS

Ninety-three patients completed the entire study. The R219K variant of ABCA1 had an effect on rosiglitazone response with the per-allele odds ratio of 2.04 for treatment failure (P<0.05). The RR homozygotes had a better improvement in indicators of insulin sensitivity, as determined by a significantly greater decrease in the homeostasis model assessment index of insulin resistance (-2.39+/-0.46 vs -0.69+/-0.51, P<0.05). No genotype-phenotype association was detected for M883I and R1587K.

CONCLUSION

The R219K variant of ABCA1 was associated with the therapeutic effect of rosiglitazone. The RR homozygotes had a better response to rosiglitazone treatment in terms of insulin sensitivity improvement than minor K allele carriers. Neither the M883I nor R1587K variant of the ABCA1 gene was associated with rosiglitazone response.

Pharmacogenetics of the PPAR genes and cardiovascular disease

The goal of pharmacogenetics is to define the genetic determinants of individual drug responsiveness, and thereby provide personalized treatment to each individual. The peroxisome proliferator-activated receptors (PPARs) are polypeptide products of a set of related genes functioning to regulate several cellular processes that are central to cardiovascular health and disease. Given their pleiotropic roles in lipid and glucose homeostasis, cardiac energy balance and regulation of adipocyte release of circulating inflammatory factors, it is not surprising that PPARs represent an attractive target for clinical investigation and intervention in disease states, such as diabetes, obesity, atherosclerosis, cardiomyopathy, cardiac hypertrophy and heart failure. Research into the manipulation of PPAR function by pharmacologic agents has already resulted in important advances in the treatment of diabetes mellitus and cardiovascular disease. It follows that PPAR pharmacogenetics promises important advances in the personalized treatment of cardiovascular disease.

Pharmacogenetics of thiazolidinedione therapy

The thiazolidinediones (TZDs) are peroxisome proliferator-activated receptor-γ agonists and have glucose-lowering, insulin-sensitizing and anti-inflammatory effects. TZDs are approved for the treatment of Type 2 diabetes, and have been studied as a diabetes-prevention strategy. Despite widespread use of TZDs, a large number of patients fail to achieve a substantial reduction in glucose, or an improvement in insulin sensitivity, following treatment. Available data suggest that polymorphisms in genes encoding TZD drug targets, effector proteins and metabolizing enzymes contribute to the observed interindividual variability in TZD response and disposition. The purpose of this review is to highlight recent developments in the field of TZD pharmacogenetics, specifically focusing on clinical studies that have investigated genetic determinants of TZD response (i.e., reduction in glycemia and improvement in insulin sensitivity), disposition (i.e., pharmacokinetics), and side effects in patients with Type 2 diabetes and patients at risk for Type 2 diabetes.

Monogenic disorders of the pancreatic β-cell: personalizing treatment for rare forms of diabetes and hypoglycemia

Over the past 10–20 years, our understanding of the genetic etiology of monogenic disorders of the pancreatic β-cell has greatly improved. This has enabled clinicians to provide patients with more accurate information regarding prognosis and inheritance and has influenced treatment. Maturity-onset diabetes of the young and neonatal diabetes are two such examples. Patients with maturity-onset diabetes of the young due to glucokinase mutations can usually be managed by diet alone, while those affected by HNF-1α and HNF-4α mutations respond well to low doses of sulfonylureas. The identification of mutations in the ATP-dependent potassium channel genes KCNJ11 and ABCC8 as the most common cause of permanent neonatal diabetes has improved treatment regimes for affected children. In addition to enabling patients to stop insulin injections, their glycemic control has also improved. These advances show the importance of unravelling the genetics of a disease to achieve the best individualized treatment for the patients affected.

Peroxisome proliferator-activated receptors as molecular targets in relation to obesity and Type 2 diabetes

The three isotypes of peroxisome proliferator-activated receptors (PPARs) are currently perceived as major regulatory nodes (or hubs) of metabolic pathway networks, linking most prevalent diseases including Type 2 diabetes, obesity, dyslipidemia and atherosclerosis. The integrative functions of PPARs are also reflected in their ecogenetic profile, when the variants underlying pharmacogenetic interactions were also shown to modulate the effect of lifestyle factors. Despite their extensive clinical use, there are many outstanding issues, especially concerning their safety. Critical pharmacogenomic assessment is warranted for the new potent ligands of multiple PPAR isoforms as many have displayed serious side-effects in a limited number of treated subjects. Nevertheless, the advent of genomic, transcriptomic and system biology-level approaches, integrating knowledge from model systems and human biology, should greatly facilitate the transition to individualized PPAR-based therapies.

Genetic influences of adiponectin on insulin resistance, type 2 diabetes, and cardiovascular disease

Recent evidence points to molecules secreted by the adipose tissue, or adipokines, as possible links between increased adipose mass and metabolic abnormalities. Among these molecules, adiponectin has drawn much attention because of its insulin-sensitizing and antiatherogenic actions, suggesting that genetic deficits in its production or action may contribute to insulin resistance and coronary artery disease (CAD). A meta-analysis of the data published to date supports this hypothesis. Two independent effects, corresponding to the two linkage disequilibrium blocks that can be identified at the adiponectin locus, appear to be present. In the 5' block, the g.-11391G-->A variant has a modest but significant effect on adiponectinemia, with a mean difference between genotypes of 1.64 ng/ml (95% CI 0.88-2.41). In the 3' block, the g.+276G-->T variant is a strong determinant of insulin resistance and CAD, with minor allele homozygotes having a lower homeostasis model assessment of insulin resistance (HOMA(IR)) index (-0.36 units, 95% CI 0.24-0.47) and a lower cardiovascular risk (odds ratio 0.55, 95% CI 0.38-0.80) than carriers of other genotypes. No consistent effect on BMI or risk of type 2 diabetes is evident. Polymorphisms in the genes coding for the adiponectin receptors may also influence the risk of insulin resistance and CAD, but data on these genes are still too sparse to draw firm conclusions. In summary, the studies published to date indicate that polymorphisms at the adiponectin locus are indeed predictors of circulating adiponectin levels, insulin sensitivity, and atherosclerosis, highlighting the pivotal role of this adipokine in the modulation of metabolism and atherogenesis.

Effects of the type 2 diabetes-associated PPARG P12A polymorphism on progression to diabetes and response to troglitazone

CONTEXT

The common P12A polymorphism in PPARG (a target for thiazolidinedione medications) has been consistently associated with type 2 diabetes.

OBJECTIVE

We examined whether PPARG P12A affects progression from impaired glucose tolerance to diabetes, or responses to preventive interventions (lifestyle, metformin, or troglitazone vs. placebo).

PATIENTS

This study included 3548 Diabetes Prevention Program participants.

DESIGN

We performed Cox regression analysis using genotype at PPARG P12A, intervention, and their interactions as predictors of diabetes incidence. We also genotyped five other PPARG variants implicated in the response to troglitazone and assessed their effect on insulin sensitivity at 1 yr.

RESULTS

Consistent with prior cross-sectional studies, P/P homozygotes at PPARG P12A appeared more likely to develop diabetes than alanine carriers (hazard ratio, 1.24; 95% confidence interval, 0.99-1.57; P=0.07) with no interaction of genotype with intervention. There was a significant interaction of genotype with body mass index and waist circumference (P=0.03 and 0.002, respectively) with the alanine allele conferring less protection in more obese individuals. Neither PPARG P12A nor five other variants significantly affected the impact of troglitazone on insulin sensitivity in 340 participants at 1 yr.

CONCLUSIONS

The proline allele at PPARG P12A increases risk for diabetes in persons with impaired glucose tolerance, an effect modified by body mass index. In addition, PPARG P12A has little or no effect on the beneficial response to troglitazone.