Common variants near ATM are associated with glycemic response to metformin in type 2 diabetes

Antidiabetic drugs and risk of cancer

Antidiabetic drugs are an important group of medications used worldwide. They differ from each other in the mechanisms of lowering blood glucose as well as in adverse effects that may affect the course of the treatment and its efficacy. In recent years, new drugs have been discovered in order to improve the maintenance of proper blood glucose level and to reduce unwanted effects of these drugs. Their growing administration is related to the increasing incidence of diabetes observed in all countries in the world. Epidemiological data indicate that diabetes increases the risk of cancer, as well as the risk of death linked with neoplasms. It is still unknown whether this is an effect of antidiabetic drugs or just the effect of diabetes itself. In recent years there have been numerous investigations and meta-analyzes, based on both comparative and cohort studies trying to establish the relationship between antidiabetic pharmacotherapy and the incidence and mortality due to cancer. According to their findings, most of antidiabetic drugs increase the risk of cancer while only few of them show antitumor properties. Different mechanisms of action of glucose-lowering drugs may be responsible for these effects. However, most of the published studies concerning the influence of these drugs on cancer incidence were designed with some limitations and differed from each other in the approach. In this review, we discuss the association between antidiabetic drugs used in monotherapy or polytherapy and cancer risk, and consider potential mechanisms responsible for the observed effects.

An update on the pharmacogenomics of metformin: progress, problems and potential

The increasing prevalence of Type 2 diabetes has emphasized the need to optimize treatment regimens. Metformin, the most widely used oral agent, is recommended as first-line drug therapy by multiple professional organizations. Response to metformin varies significantly at the individual level; this heterogeneity may be explained in part by genetic factors. Understanding these underlying factors may aid with tailoring treatment for individual patients as well as with designing improved Type 2 diabetes therapies. The past 10 years have seen substantial progress in the understanding of the pharmacogenetics of metformin response. The majority of this work has focused on genes involved in the pharmacokinetics of metformin. Owing to the uncertainty surrounding its mechanism of action, studies of pharmacodynamic genetics have been relatively few; genome-wide approaches have the potential to illuminate the molecular details of metformin response. In this review we summarize current knowledge about metformin pharmacogenetics and suggest directions for future investigation.

Association of Organic Cation Transporter 1 With Intolerance to Metformin in Type 2 Diabetes: A GoDARTS Study

Metformin is the most widely prescribed medication for the treatment of type 2 diabetes (T2D). However, gastrointestinal (GI) side effects develop in ~25% of patients treated with metformin, leading to the discontinuation of therapy in ~5% of cases. We hypothesized that reduced transport of metformin via organic cation transporter 1 (OCT1) could increase metformin concentration in the intestine, leading to increased risk of severe GI side effects and drug discontinuation. We compared the phenotype, carriage of reduced-function OCT1 variants, and concomitant prescribing of drugs known to inhibit OCT1 transport in 251 intolerant and 1,915 fully metformin-tolerant T2D patients. We showed that women and older people were more likely to be intolerant to metformin. Concomitant use of medications, known to inhibit OCT1 activity, was associated with intolerance (odds ratio [OR] 1.63 [95% CI 1.22-2.17], P = 0.001) as was carriage of two reduced-function OCT1 alleles compared with carriage of one or no deficient allele (OR 2.41 [95% CI 1.48-3.93], P < 0.001). Intolerance was over four times more likely to develop (OR 4.13 [95% CI 2.09-8.16], P < 0.001) in individuals with two reduced-function OCT1 alleles who were treated with OCT1 inhibitors. Our results suggest that reduced OCT1 transport is an important determinant of metformin intolerance.

Personalized medicine in diabetes mellitus: current opportunities and future prospects

Diabetes mellitus affects approximately 382 million individuals worldwide and is a leading cause of morbidity and mortality. Over 40 and nearly 80 genetic loci influencing susceptibility to type 1 and type 2 diabetes, respectively, have been identified. In addition, there is emerging evidence that some genetic variants help to predict response to treatment. Other variants confer apparent protection from diabetes or its complications and may lead to development of novel treatment approaches. Currently, there is clear clinical utility to genetic testing to find the at least 1% of diabetic individuals who have monogenic diabetes (e.g., maturity-onset diabetes of the young and KATP channel neonatal diabetes). Diagnosing many of these currently underdiagnosed types of diabetes enables personalized treatment, resulting in improved and less invasive glucose control, better prediction of prognosis, and enhanced familial risk assessment. Efforts to enhance the rate of detection, diagnosis, and personalized treatment of individuals with monogenic diabetes should set the stage for effective clinical translation of current genetic, pharmacogenetic, and pharmacogenomic research of more complex forms of diabetes.

Metformin Treatment for the Prevention and/or Treatment of Breast/Mammary Tumorigenesis

There is increasing interest in metformin's effects on the development, treatment and/or progression of breast cancer. This emerges from observational studies that diabetic women treated with metformin in comparison to other antidiabetic compounds had lower breast cancer incidence and/or mortality rates. The mechanism of action is considered to be activation of hepatic AMPK resulting in reduced gluconeogenesis. Calorie restriction, which consistently reduces mammary tumorigenesis in rodents, is also thought to act through this pathway leading to the hypothesis that metformin's anticancer effects are mediated in a similar fashion. Here we review the literature evaluating metformin's anticancer effects in relation to breast/mammary tumorigenesis. We include clinical observations, as well as studies utilizing rodent models and mammary cell lines. In addition to the anticancer effect of metformin mediated through the AMPK pathway, additional mechanisms of action that directly target tissues have been identified including effects on stem cells, apoptosis, STAT3 and HER2.

Potential and real 'antineoplastic' and metabolic effect of metformin in diabetic and nondiabetic postmenopausal females

AIM

The goal of this study was to determine if the single nucleotide polymorphisms marking potential sensitivity to metformin (MF) correlate with hormone-metabolic status as well as with actual response to MF in postmenopausal cancer patients with or without Type 2 diabetes mellitus and in diabetics without cancer.

PATIENTS & METHODS

The carriage of ten different SNPs was evaluated in all patients by PCR, and hormone-metabolic status was estimated by anthropometry, ELISA and enzyme colorimetric assays. The response to daily 1-1.7 g of MF was studied based on hormone-metabolic parameters and indirect end points (endometrium thickness, mammographic breast density).

RESULTS & CONCLUSION

The changes in evaluated 'antineoplastic' and metabolic response marker values were seen in 33.3 and 61.8% of the cases, respectively. Several genetic markers were found that showed an inclination to less frequent 'antineoplastic' or more frequent metabolic response to MF which may be helpful in further studies of this drug in cancer patients.

Both high and low HbA1c predict incident heart failure in type 2 diabetes mellitus

BACKGROUND

Type 2 diabetes mellitus is an independent risk factor for heart failure development, but the relationship between incident heart failure and antecedent glycemia has not been evaluated.

METHODS AND RESULTS

The Genetics of Diabetes Audit and Research in Tayside Study study holds data for 8683 individuals with type 2 diabetes mellitus. Dispensed prescribing, hospital admission data, and echocardiography reports were linked to extract incident heart failure cases from December 1998 to August 2011. All available HbA1c measures until heart failure development or end of study were used to model HbA1c time-dependently. Individuals were observed from study enrolment until heart failure development or end of study. Proportional hazard regression calculated heart failure development risk associated with specific HbA1c ranges accounting for comorbidities associated with heart failure, including blood pressure, body mass index, and coronary artery disease. Seven hundred and one individuals with type 2 diabetes mellitus (8%) developed heart failure during follow up (mean 5.5 years, ±2.8 years). Time-updated analysis with longitudinal HbA1c showed that both HbA1c <6% (hazard ratio =1.60; 95% confidence interval, 1.38-1.86; P value <0.0001) and HbA1c >10% (hazard ratio =1.80; 95% confidence interval, 1.60-2.16; P value <0.0001) were independently associated with the risk of heart failure.

CONCLUSIONS

Both high and low HbA1c predicted heart failure development in our cohort, forming a U-shaped relationship.

Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics

In recent years, the utilization of genome-wide association study (GWAS) has proved to be a beneficial method to identify novel common genetic variations not only for disease susceptibility but also for drug efficacy and drug-induced toxicity, creating a field of pharmacogenomics studies. In addition, the findings from GWAS also generate new biologic hypotheses that could improve the understanding of pathophysiology for disease or the mechanism of drug-induced toxicity. This review highlights the implications of GWAS that have been published to date and discusses the successes as well as challenges of using GWAS in cancer pharmacogenomics. The aim of pharmacogenomics is to realize the vision of personalized medicine; it is hoped that through GWAS, novel common genetic variations could be identified to predict clinical outcome and/or toxicity in cancer therapies that subsequently could be implemented to improve the quality of lives of patients with cancer. Nevertheless, given the complexity of cancer therapies, underpowered studies, and large heterogeneity of study designs, collaborative efforts are needed to validate these findings and overcome the limitations of GWA studies before clinical implementation. See all articles in this ccr focus section, "Progress in pharmacodynamic endpoints."

Effect of zinc supplementation on insulin secretion: interaction between zinc and SLC30A8 genotype in Old Order Amish

AIMS/HYPOTHESIS

SLC30A8 encodes a zinc transporter in the beta cell; individuals with a common missense variant (rs13266634; R325W) in SLC30A8 demonstrate a lower early insulin response to glucose and an increased risk of type 2 diabetes. We hypothesised that zinc supplementation may improve insulin secretion in a genotype-dependent manner.

METHODS

We evaluated the early insulin response to glucose (using frequently sampled intravenous glucose tolerance testing) by R325W genotype before and after 14 days of supplementation with oral zinc acetate (50 mg elemental zinc) twice daily in healthy non-diabetic Amish individuals (N = 55).

RESULTS

Individuals with RW/WW genotypes (n = 32) had the lowest insulin response to glucose at 5 and 10 min at baseline (vs RR homozygotes [n = 23]). After zinc supplementation, the RW/WW group experienced 15% and 14% increases in the insulin response to glucose at 5 and 10 min, respectively (p ≤ 0.04), and, compared with RR homozygotes, experienced a 26% (p = 0.04) increase in insulin at 5 min. We observed reciprocal decreases in proinsulin:insulin in the RW/WW (p = 0.002) vs RR group (p = 0.048), suggesting a genotype-specific improvement in insulin processing.

CONCLUSIONS/INTERPRETATION

Zinc supplementation appears to affect the early insulin response to glucose differentially by rs13266634 genotype and could be beneficial for diabetes prevention and/or treatment for some individuals based on SLC30A8 variation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT00981448.

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.

Pharmacogenetics of type 2 diabetes mellitus: An example of success in clinical and translational medicine

The pharmacological interventions currently available to control type 2 diabetes mellitus (T2DM) show a wide interindividual variability in drug response, emphasizing the importance of a personalized, more effective medical treatment for each individual patient. In this context, a growing interest has emerged in recent years and has focused on pharmacogenetics, a discipline aimed at understanding the variability in patients’ drug response, making it possible to predict which drug is best for each patient and at what doses. Recent pharmacological and clinical evidences indicate that genetic polymorphisms (or genetic variations) of certain genes can adversely affect drug response and therapeutic efficacy of oral hypoglycemic agents in patients with T2DM, through pharmacokinetic- and/or pharmacodynamic-based mechanisms that may reduce the therapeutic effects or increase toxicity. For example, genetic variants in genes encoding enzymes of the cytochrome P-450 superfamily, or proteins of the ATP-sensitive potassium channel on the beta-cell of the pancreas, are responsible for the interindividual variability of drug response to sulfonylureas in patients with T2DM. Instead, genetic variants in the genes that encode for the organic cation transporters of metformin have been related to changes in both pharmacodynamic and pharmacokinetic responses to metformin in metformin-treated patients. Thus, based on the individual’s genotype, the possibility, in these subjects, of a personalized therapy constitutes the main goal of pharmacogenetics, directly leading to the development of the right medicine for the right patient. Undoubtedly, this represents an integral part of the translational medicine network.

Influence of SLC22A1 rs622342 genetic polymorphism on metformin response in South Indian type 2 diabetes mellitus patients

Metformin is an oral antidiabetic drug, commonly used for treating type 2 diabetes mellitus (T2DM) patients. It is transported into the hepatocytes by polyspecific organic cation transporter 1, which is encoded by the gene SLC22A1. It has been hypothesized that genetic variations of SLC22A1 gene will influence inter-individual variation in glucose lowering efficacy of metformin. Previous studies have demonstrated this in other populations with conflicting results, but it remains to be elucidated in Indian population. Henceforth, the objective of the study was to evaluate the impact of SLC22A1 rs622342 gene polymorphism on the clinical efficacy of metformin in South Indian T2DM patients. A total of 122 newly detected, treatment naive T2DM patients of either sex were included in this study. The patients were started on metformin monotherapy and followed up for 12 weeks. Genotype was determined using qRT-PCR. Before and after treatment with metformin, body mass index (BMI), serum lipid profile, glycated hemoglobin (HbA1c), fasting and postprandial glucose level, and blood pressure (BP) were measured. The study cohort mean age was 49.57 ± 9.88 years. Of the 122 T2DM patients, 93 were classified as responders and 29 as non-responders based on fall in HbA1c levels. Interestingly, carriers of one variant allele 'C' (AC) of rs622342 polymorphism were less among the responders than those who did not (44.8 vs. 22.6 %). The response was even lesser (13.8 vs. 4.3 %) in carriers of two copies of "C" allele (CC). On the contrary, patients with two copies of allele 'A' (AA) had 5.6 times greater chance of responding to metformin treatment. A similar trend was observed when the proportion was analyzed under different genetic models (OR 3.85, 95 % CI 1.61-9.19 for dominant; OR 3.56, 95 % CI 0.83-15.26 for recessive; OR 0.35, 95 % CI 0.14-0.86 for over-dominant; and OR 4.10, 95 % CI 1.78-9.43 for additive). Further, metformin showed significant beneficial effects on BMI, HbA1c, FPG, PPG, lipid parameters and BP. These data suggest that the allele and genotypes of SLC22A1 rs622342 gene polymorphism were associated with the therapeutic efficacy of metformin in South Indian patients with T2DM.

Metformin: from mechanisms of action to therapies

Metformin is currently the first-line drug treatment for type 2 diabetes. Besides its glucose-lowering effect, there is interest in actions of the drug of potential relevance to cardiovascular diseases and cancer. However, the underlying mechanisms of action remain elusive. Convincing data place energy metabolism at the center of metformin's mechanism of action in diabetes and may also be of importance in cardiovascular diseases and cancer. Metformin-induced activation of the energy-sensor AMPK is well documented, but may not account for all actions of the drug. Here, we summarize current knowledge about the different AMPK-dependent and AMPK-independent mechanisms underlying metformin action.

RS11212617 is associated with metformin treatment response in type 2 diabetes in Shanghai local Chinese population

OBJECTIVE

This study was designed to examine the relevance of single-nucleotide polymorphism (SNP) rs11212617 with treatment success in type 2 diabetes patients from Shanghai local Chinese Han population.

METHODS

We genotyped rs11212617 in incident metformin users of type 2 diabetes patients from Shanghai local Chinese Han population. Association between rs11212617 and changes in HbA1c, fasting plasma glucose and postprandial glucose level were analysed.

RESULTS

Two hundred and seventy-four incident metformin users were included in the study sample. The SNP rs11212617 was significantly associated with metformin response in Shanghai local Chinese Han population.

CONCLUSION

The rs11212617 is associated with a reduction in HbA1c, fasting plasma glucose and postprandial glucose level. These results suggest that metformin treatment may be more efficacious in Shanghai and valuable for Chinese daily clinical practice.

Allele and genotype frequency of a genetic variant in ataxia telangiectasia mutated gene affecting glycemic response to metformin in South Indian population

Allele and genotype frequency of a genetic variant in ATM gene affecting glycemic response to metformin in South Indian population.

CONTEXT

The novel polymorphism in ATM gene (rs11212617), which is implicated to have association with metformin response, exhibits inter-ethnic variability in the allele and genotype frequency distribution.

AIMS AND DESIGN

The objective of the present study is to establish the allele and genotype frequency of rs11212617 single nucleotide polymorphism in ATM gene, in South Indian population and to find if this variant has any role in the etiology of type 2 diabetes mellitus.

MATERIALS AND METHODS

The study was performed in 2 cohorts of populations, 112 healthy volunteers and 118 type 2 diabetes mellitus patients. Genomic deoxyribonucleic acid (DNA) was extracted from peripheral blood leucocytes by phenol-chloroform method and genotyping was performed by real-time polymerase chain reaction using TaqMan assay.

RESULTS

In South Indian population, the frequency of major A allele was 0.65 and the minor C allele was 0.35. AA and CC are the homozygous genotypes with frequency of 0.39 and 0.09 respectively. The frequency of heterozygous genotype AC (0.52) was found to be higher than the homozygotes. There was no significant difference in the frequency distribution in the diabetic population, which implies that this variant does not have any causative role in the disease etiology. The frequency distributions were found to be significantly different from the distributions in other ethnic populations such as Caucasians, Chinese, Japanese and Africans. But there was no significant difference when compared with the Gujarati Indians of Houston.

CONCLUSION

The frequency distribution of this novel variant in South Indian population forms a framework for further gene disease association studies to establish the association of this variant with metformin response. Our study could not find any association of this variant with respect to the disease etiology.

Downregulation of the acetyl-CoA metabolic network in adipose tissue of obese diabetic individuals and recovery after weight loss

AIMS/HYPOTHESIS

Not all obese individuals develop type 2 diabetes. Why some obese individuals retain normal glucose tolerance (NGT) is not well understood. We hypothesise that the biochemical mechanisms that underlie the function of adipose tissue can help explain the difference between obese individuals with NGT and those with type 2 diabetes.

METHODS

RNA sequencing was used to analyse the transcriptome of samples extracted from visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) of obese women with NGT or type 2 diabetes who were undergoing bariatric surgery. The gene expression data was analysed by bioinformatic visualisation and statistical analyses techniques.

RESULTS

A network-based approach to distinguish obese individuals with NGT from obese individuals with type 2 diabetes identified acetyl-CoA metabolic network downregulation as an important feature in the pathophysiology of type 2 diabetes in obese individuals. In general, genes within two reaction steps of acetyl-CoA were found to be downregulated in the VAT and SAT of individuals with type 2 diabetes. Upon weight loss and amelioration of metabolic abnormalities three months following bariatric surgery, the expression level of these genes recovered to levels seen in individuals with NGT. We report four novel genes associated with type 2 diabetes and recovery upon weight loss: ACAT1 (encoding acetyl-CoA acetyltransferase 1), ACACA (encoding acetyl-CoA carboxylase α), ALDH6A1 (encoding aldehyde dehydrogenase 6 family, member A1) and MTHFD1 (encoding methylenetetrahydrofolate dehydrogenase).

CONCLUSIONS/INTERPRETATION

Downregulation of the acetyl-CoA network in VAT and SAT is an important feature in the pathophysiology of type 2 diabetes in obese individuals. ACAT1, ACACA, ALDH6A1 and MTHFD1 represent novel biomarkers in adipose tissue associated with type 2 diabetes in obese individuals.

A pharmacogenetic association between a variation in calpain 10 (CAPN10) gene and the response to metformin treatment in patients with type 2 diabetes

PURPOSE

The aim of the present study was to investigate possible associations of the single-nucleotide variants in six genes encoding the key molecules mediating the metformin pharmacodynamic effect with the response to treatment with metformin in patients with type 2 diabetes.

METHODS

One hundred forty-eight drug-naïve patients with type 2 diabetes were included in the study. PRKAA1 rs249429, STK11 rs741765, PCK1 rs4810083, PPARGC1A rs10213440, HNF1A rs11086926, and CAPN10 rs3792269 variants were genotyped. The outcomes of the study were treatment success defined by achieving HbA1c <7 % and absolute reduction in HbAlc after 6-month metformin therapy. The relationships between genotypes and outcomes were evaluated in multivariate logistic and linear models. The level of statistical significance after Bonferroni correction was predefined as p<0.0083.

RESULTS

The minor G-allele of CAPN10 rs3792269 A>G polymorphism was significantly associated with less treatment success with an odds ratio of 0.27 (95 % CI 0.12-0.62, p=0.002) per variant allele. When the reduction in HbA1c was analyzed as a quantitative trait, G-allele was nominally associated with a smaller reduction in HbA1c (per allele β=-0.26, 95 % CI -0.50 to -0.02, p=0.032). The reduction in HbA1c in minor allele carriers (24 % of study population) was smaller by 0.3 % in comparison with the major allele homozygotes.

CONCLUSIONS

The present study provides the first observation of an association between a variant in CAPN10 gene and the response to metformin therapy in patients with type 2 diabetes. This observation needs to be replicated in further studies in different populations.

Ataxia-telangiectasia: future prospects

Ataxia-telangiectasia (A-T) is an autosomal recessive multi-system disorder caused by mutation in the ataxia-telangiectasia mutated gene (ATM). ATM is a large serine/threonine protein kinase, a member of the phosphoinositide 3-kinase-related protein kinase (PIKK) family whose best-studied function is as master controller of signal transduction for the DNA damage response (DDR) in the event of double strand breaks (DSBs). The DDR rapidly recognizes DNA lesions and initiates the appropriate cellular programs to maintain genome integrity. This includes the coordination of cell-cycle checkpoints, transcription, translation, DNA repair, metabolism, and cell fate decisions, such as apoptosis or senescence. DSBs can be generated by exposure to ionizing radiation (IR) or various chemical compounds, such as topoisomerase inhibitors, or can be part of programmed generation and repair of DSBs via cellular enzymes needed for the generation of the antibody repertoire as well as the maturation of germ cells. AT patients have immunodeficiency, and are sterile with gonadal dysgenesis as a result of defect in meiotic recombination. In the cells of nervous system ATM has additional role in vesicle dynamics as well as in the maintenance of the epigenetic code of histone modifications. Moderate levels of ATM are associated with prolonged lifespan through resistance to oxidative stress. ATM inhibitors are being viewed as potential radiosensitizers as part of cancer radiotherapy. Though there is no cure for the disease at present, glucocorticoids have been shown to induce alternate splicing site in the gene for ATM partly restoring its activity, but their most effective timing in the disease natural history is not yet known. Gene therapy is promising but large size of the gene makes it technically difficult to be delivered across the blood-brain barrier at present. As of now, apart from glucocorticoids, use of histone deacetylase inhibitors/EZH2 to minimize effect of the absence of ATM, looks more promising.

Genetic variants in transcription factors are associated with the pharmacokinetics and pharmacodynamics of metformin

One-third of type 2 diabetes patients do not respond to metformin. Genetic variants in metformin transporters have been extensively studied as a likely contributor to this high failure rate. Here, we investigate, for the first time, the effect of genetic variants in transcription factors on metformin pharmacokinetics (PK) and response. Overall, 546 patients and healthy volunteers contributed their genome-wide, pharmacokinetic (235 subjects), and HbA1c data (440 patients) for this analysis. Five variants in specificity protein 1 (SP1), a transcription factor that modulates the expression of metformin transporters, were associated with changes in treatment HbA1c (P < 0.01) and metformin secretory clearance (P < 0.05). Population pharmacokinetic modeling further confirmed a 24% reduction in apparent clearance in homozygous carriers of one such variant, rs784888. Genetic variants in other transcription factors, peroxisome proliferator-activated receptor-α and hepatocyte nuclear factor 4-α, were significantly associated with HbA1c change only. Overall, our study highlights the importance of genetic variants in transcription factors as modulators of metformin PK and response.

Can genetics improve precision of therapy in diabetes?

Diabetes mellitus is a lifelong, incapacitating disease affecting multiple organs. Presently, type 2 diabetes (T2D) can neither be prevented nor cured and the disease is associated with devastating chronic complications. These complications impose an immense burden on the quality of life of patients and account for about 12% of direct health care costs in Europe. Genetic analysis will increase our understanding of this heterogeneous disease and may help offer more personalized treatment.

Personalized medicine in Type 2 Diabetes

Type 2 diabetes (T2D) is a global public health concern, its prevalence in Asia, especially Taiwan, rising every year. The risk of developing T2D and diabetes complications is not only controlled by environmental but also by genetic factors. Genetic association studies have shown polymorphisms at specific loci may help identify individuals at greatest risk and response to oral antidiabetic drugs. This review probes effect of genetic profiling on T2D and its complications, using our study population as examples. Also, pharmacogenetics and pharmacogenomics of oral anitdiabetic drug will be explored.

Metformin pharmacogenomics: current status and future directions

The incidence of type 2 diabetes (T2D) and its costs to the health care system continue to rise. Despite the availability of at least 10 drug classes for the treatment of T2D, metformin remains the most widely used first-line pharmacotherapy for its treatment; however, marked interindividual variability in response and few clinical or biomarker predictors of response reduce its optimal use. As clinical care moves toward precision medicine, a variety of broad discovery-based "omics" approaches will be required. Technical innovation, decreasing sequencing cost, and routine sample storage and processing has made pharmacogenomics the most widely applied discovery-based approach to date. This opens up the opportunity to understand the genetics underlying the interindividual variation in metformin responses in order for clinicians to prescribe specific treatments to given individuals for better efficacy and safety: metformin for those predicted to respond and alternative therapies for those predicted to be nonresponders or who are at increased risk for adverse side effects. Furthermore, understanding of the genetic determinants of metformin response may lead to the identification of novel targets and development of more effective agents for diabetes treatment. The goals of this workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases were to review the state of research on metformin pharmacogenomics, discuss the scientific and clinical hurdles to furthering our knowledge of the variability in patient responses to metformin, and consider how to effectively use this increased understanding to improve patient outcomes.

ATM signalling and cancer

ATM, the protein kinase mutated in the rare human disease ataxia telangiectasia (A-T), has been the focus of intense scrutiny over the past two decades. Initially this was because of the unusual radiosensitive phenotype of cells from A-T patients, and latterly because investigating ATM signalling has yielded valuable insights into the DNA damage response, redox signalling and cancer. With the recent explosion in genomic data, ATM alterations have been revealed both in the germline as a predisposing factor for cancer and as somatic changes in tumours themselves. Here we review these findings, as well as advances in the understanding of ATM signalling mechanisms in cancer and ATM inhibition as a strategy for cancer treatment.

The role of genetic factors and kidney and liver function in glycemic control in type 2 diabetes patients on long-term metformin and sulphonylurea cotreatment

This study investigated the influence of genetic polymorphisms of metformin transporters on long-term glycemic control and lipid status in type 2 diabetes patients in the everyday clinical setting. In total 135 patients treated with combination of metformin and sulphonylurea for at least 6 months were genotyped for SLC22A1 rs628031 and SLC47A1 rs2289669 polymorphisms. Relatively good blood glucose control with median HbA1c 6.9 (6.4–7.6) % was achieved on prescribed metformin dosage of 2550 (2000–2550) mg per day. Only 28 (20.7%) patients experienced mild hypoglycemia events, while no severe hypoglycemia events were observed. Most patients had normal or mildly impaired renal function. Parameters indicating renal function were not correlated with fasting glucose, HbA1c, or lipid parameters. Rs628031 and rs2289669 had minor allele frequencies of 0.385 and 0.355, respectively, and were not associated with HbA1c levels. Rs628031 was marginally associated with risk for hypoglycemia events (P = 0.046; OR = 0.51; 95% CI 0.26–0.99), while significant correlation was observed between rs2289669 and total cholesterol levels (P = 0.018). In conclusion, in patients on long-term metformin and sulphonylurea combination treatment, metformin transporters polymorphisms do not play a major role in glycemic control; however, they may influence lipid status.

Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis

BACKGROUND

Metformin is a first-line oral agent used in the treatment of type 2 diabetes, but glycaemic response to this drug is highly variable. Understanding the genetic contribution to metformin response might increase the possibility of personalising metformin treatment. We aimed to establish the heritability of glycaemic response to metformin using the genome-wide complex trait analysis (GCTA) method.

METHODS

In this GCTA study, we obtained data about HbA1c concentrations before and during metformin treatment from patients in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study, which includes a cohort of patients with type 2 diabetes and is linked to comprehensive clinical databases and genome-wide association study data. We applied the GCTA method to estimate heritability for four definitions of glycaemic response to metformin: absolute reduction in HbA1c; proportional reduction in HbA1c; adjusted reduction in HbA1c; and whether or not the target on-treatment HbA1c of less than 7% (53 mmol/mol) was achieved, with adjustment for baseline HbA1c and known clinical covariates. Chromosome-wise heritability estimation was used to obtain further information about the genetic architecture.

FINDINGS

5386 individuals were included in the final dataset, of whom 2085 had enough clinical data to define glycaemic response to metformin. The heritability of glycaemic response to metformin varied by response phenotype, with a heritability of 34% (95% CI 1-68; p=0·022) for the absolute reduction in HbA1c, adjusted for pretreatment HbA1c. Chromosome-wise heritability estimates suggest that the genetic contribution is probably from individual variants scattered across the genome, which each have a small to moderate effect, rather than from a few loci that each have a large effect.

INTERPRETATION

Glycaemic response to metformin is heritable, thus glycaemic response to metformin is, in part, intrinsic to individual biological variation. Further genetic analysis might enable us to make better predictions for stratified medicine and to unravel new mechanisms of metformin action.

FUNDING

Wellcome Trust.

Serine 249 phosphorylation by ATM protein kinase regulates hepatocyte nuclear factor-1α transactivation

Hepatocyte nuclear factor-1 alpha (HNF1α) exerts important effects on gene expression in multiple tissues. Several studies have directly or indirectly supported the role of phosphorylation processes in the activity of HNF1α. However, the molecular mechanism of this phosphorylation remains largely unknown. Using microcapillary liquid chromatography MS/MS and biochemical assays, we identified a novel phosphorylation site in HNF1α at Ser249. We also found that the ATM protein kinase phosphorylated HNF1α at Ser249 in vitro in an ATM-dependent manner and that ATM inhibitor KU55933 treatment inhibited phosphorylation of HNF1α at Ser249 in vivo. Coimmunoprecipitation assays confirmed the association between HNF1α and ATM. Moreover, ATM enhanced HNF1α transcriptional activity in a dose-dependent manner, whereas the ATM kinase-inactive mutant did not. The use of KU55933 confirmed our observation. Compared with wild-type HNF1α, a mutation in Ser249 resulted in a pronounced decrease in HNF1α transactivation, whereas no dominant-negative effect was observed. The HNF1αSer249 mutant also exhibited normal nuclear localization but decreased DNA-binding activity. Accordingly, the functional studies of HNF1αSer249 mutant revealed a defect in glucose metabolism. Our results suggested that ATM regulates the activity of HNF1α by phosphorylation of serine 249, particularly in glucose metabolism, which provides valuable insights into the undiscovered mechanisms of ATM in the regulation of glucose homeostasis.

Genetics of type 2 diabetes: insights into the pathogenesis and its clinical application

With rapidly increasing prevalence, diabetes has become one of the major causes of mortality worldwide. According to the latest studies, genetic information makes substantial contributions towards the prediction of diabetes risk and individualized antidiabetic treatment. To date, approximately 70 susceptibility genes have been identified as being associated with type 2 diabetes (T2D) at a genome-wide significant level (P < 5 × 10⁻⁸). However, all the genetic loci identified so far account for only about 10% of the overall heritability of T2D. In addition, how these novel susceptibility loci correlate with the pathophysiology of the disease remains largely unknown. This review covers the major genetic studies on the risk of T2D based on ethnicity and briefly discusses the potential mechanisms and clinical utility of the genetic information underlying T2D.

RD Lawrence lecture 2013. Stratified approaches to the management of diabetes

A stratified approach to medicine aims to identify subgroups of patients who should be managed differently from others. Diabetes is a condition that offers considerable potential for stratification, in areas of drug response, complication risk and rate of progression amongst others. Approaches to stratification can be simple, using clinical phenotyping, or more complex involving genomic and other '-omic' technologies. In this review, I will highlight the utility of measuring endogenous insulin production to aid in diagnosis and appropriate treatment; outline key advances in monogenic diabetes where determining genetic aetiology can result in dramatic changes in treatment, and describe the developments in the field of pharmacogenetics in Type 2 diabetes.

Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression

To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

Metformin and other antidiabetic agents in renal failure patients

This review mainly focuses on metformin, and considers oral antidiabetic therapy in kidney transplant patients and the potential benefits and risks of antidiabetic agents other than metformin in patients with chronic kidney disease (CKD). In view of the debate concerning lactic acidosis associated with metformin, this review tries to solve a paradox: metformin should be prescribed more widely because of its beneficial effects, but also less widely because of the increasing prevalence of contraindications to metformin, such as reduced renal function. Lactic acidosis appears either as part of a number of clinical syndromes (i.e., unrelated to metformin), induced by metformin (involving an analysis of the drug's pharmacokinetics and mechanisms of action), or associated with metformin (a more complex situation, as lactic acidosis in a metformin-treated patient is not necessarily accompanied by metformin accumulation, nor does metformin accumulation necessarily lead to lactic acidosis). A critical analysis of guidelines and literature data on metformin therapy in patients with CKD is presented. Following the present focus on metformin, new paradoxical issues can be drawn up, in particular: (i) metformin is rarely the sole cause of lactic acidosis; (ii) lactic acidosis in patients receiving metformin therapy is erroneously still considered a single medical entity, as several different scenarios can be defined, with contrasting prognoses. The prognosis for severe lactic acidosis seems even better in metformin-treated patients than in non-metformin users.

Metformin--mode of action and clinical implications for diabetes and cancer

Metformin has been the mainstay of therapy for diabetes mellitus for many years; however, the mechanistic aspects of metformin action remained ill-defined. Recent advances revealed that this drug, in addition to its glucose-lowering action, might be promising for specifically targeting metabolic differences between normal and abnormal metabolic signalling. The knowledge gained from dissecting the principal mechanisms by which metformin works can help us to develop novel treatments. The centre of metformin's mechanism of action is the alteration of the energy metabolism of the cell. Metformin exerts its prevailing, glucose-lowering effect by inhibiting hepatic gluconeogenesis and opposing the action of glucagon. The inhibition of mitochondrial complex I results in defective cAMP and protein kinase A signalling in response to glucagon. Stimulation of 5'-AMP-activated protein kinase, although dispensable for the glucose-lowering effect of metformin, confers insulin sensitivity, mainly by modulating lipid metabolism. Metformin might influence tumourigenesis, both indirectly, through the systemic reduction of insulin levels, and directly, via the induction of energetic stress; however, these effects require further investigation. Here, we discuss the updated understanding of the antigluconeogenic action of metformin in the liver and the implications of the discoveries of metformin targets for the treatment of diabetes mellitus and cancer.

Metformin resistance alleles in polycystic ovary syndrome: pattern and association with glucose metabolism

Insulin-sensitizer treatment with metformin is common in polycystic ovary syndrome (PCOS). OCT alleles were investigated in PCOS patients to identify genetic ‘bad responders’ and ‘nonresponders’ to metformin including their possible effects on glucose metabolism without treatment. We genotyped eight SNPs in OCT1, OCT2 and ATM genes in 676 women with PCOS and 90 control women, we also measured oral glucose tolerance tests prior to treatment. Nonfunctional alleles were present in 29.8% and low-functional alleles in 57.9% of our PCOS cohort. OCT variants were significantly associated with elevated baseline and glucose-induced C-peptide levels in PCOS. Metformin bad responders or nonresponders based on OCT genotypes might be relevant in clinical practice – their modulation of metformin pharmacokinetics and pharmacodynamics and metformin-independent glucose effects remain to be elucidated.

Original submitted 7 June 2013; Revision submitted 28 October 2013

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.

Introduction to personalized medicine in diabetes mellitus

The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for "average" patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic ("omics") and other new technologies to explore pathophysiology and to characterize more precisely an individual's risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in "omic" information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.

Association between a gene variant near ataxia telangiectasia mutated and coronary artery disease in men

OBJECTIVE

Type 2 diabetes is accompanied by increased mortality from coronary artery disease (CAD), but the mechanisms linking these conditions remain elusive. Hence, treatment of hyperglycaemia alone is not sufficient to avoid CAD in diabetes. Alternative views suggest that metabolic and vascular diseases share unifying cellular defects that could serve as targets for novel therapeutic strategies. Recently, a variant [single-nucleotide polymorphism (SNP); rs11212617] near the gene for ataxia telangiectasia mutated (ATM) has been associated with glycaemic response to metformin.

MATERIALS AND METHODS

We determined rs11212617 in 240 male patients who underwent elective coronary angiography.

RESULTS

While the variant was not associated with glucose concentrations, the A allele was significantly associated with the presence of CAD (chi-square, p = 0.003), as well as with logarithmically transformed quantitative CAD indices [severe score (SS): 0.5 (0.4-0.6) vs 0.3 (0.2-0.5); extent score (ES): 2.63 (2.4-2.9) vs 1.94 (1.4-2.4), both p < 0.05, respectively]. Multivariate analysis revealed an independent association between the A allele with ES (β = 0.17, p < 0.01).

CONCLUSION

Our data suggest that ATM-dependent signalling might play a role in the development of atherosclerotic vascular disease, but larger studies are necessary to substantiate such a hypothesis.

Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach

Using a nontargeted metabolomics approach of 447 fasting plasma metabolites, we searched for novel molecular markers that arise before and after hyperglycemia in a large population-based cohort of 2,204 females (115 type 2 diabetic [T2D] case subjects, 192 individuals with impaired fasting glucose [IFG], and 1,897 control subjects) from TwinsUK. Forty-two metabolites from three major fuel sources (carbohydrates, lipids, and proteins) were found to significantly correlate with T2D after adjusting for multiple testing; of these, 22 were previously reported as associated with T2D or insulin resistance. Fourteen metabolites were found to be associated with IFG. Among the metabolites identified, the branched-chain keto-acid metabolite 3-methyl-2-oxovalerate was the strongest predictive biomarker for IFG after glucose (odds ratio [OR] 1.65 [95% CI 1.39-1.95], P = 8.46 × 10(-9)) and was moderately heritable (h(2) = 0.20). The association was replicated in an independent population (n = 720, OR 1.68 [ 1.34-2.11], P = 6.52 × 10(-6)) and validated in 189 twins with urine metabolomics taken at the same time as plasma (OR 1.87 [1.27-2.75], P = 1 × 10(-3)). Results confirm an important role for catabolism of branched-chain amino acids in T2D and IFG. In conclusion, this T2D-IFG biomarker study has surveyed the broadest panel of nontargeted metabolites to date, revealing both novel and known associated metabolites and providing potential novel targets for clinical prediction and a deeper understanding of causal mechanisms.

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.

Genetic epidemiology of type 2 diabetes and cardiovascular diseases in Africa

The burdens of type 2 diabetes (T2D) and cardiovascular diseases (CVD) are increasing in Africa. T2D and CVD are the result of the complex interaction between inherited characteristics, lifestyle, and environmental factors. The epidemic of obesity is largely behind the exploding global incidence of T2D. However, not all obese individuals develop diabetes and positive family history is a powerful risk factor for diabetes and CVD. Recent implementations of high throughput genotyping and sequencing approaches have advanced our understanding of the genetic basis of diabetes and CVD by identifying several genomic loci that were not previously linked to the pathobiology of these diseases. However, African populations have not been adequately represented in these global genomic efforts. Here, we summarize the state of knowledge of the genetic epidemiology of T2D and CVD in Africa and highlight new genomic initiatives that promise to inform disease etiology, public health and clinical medicine in Africa.

Genetic polymorphisms potentially associated with response to metformin in postmenopausal diabetics suffering and not suffering with cancer

Metformin is a well-known antidiabetic medication, which, besides diabetes, may be involved into modulation of other age-related pathologies, including cancer. The study concerns 12 gene polymorphisms divided into 2 groups consisting of 6 genes each. The first group was composed from so-called "standard" (S) polymorphisms, for which the connection with metabolic response to metformin is already established. The second group included polymorphisms of genes encoding proteins possibly connected with diabetes mellitus type 2 (DM2), impaired glucose tolerance or cancer and entitled here as "associated" (A). A total of 156 postmenopausal women (average age 60.7 ± 0.7) were included, 37 of them healthy, 64 with type DM2 and concurrent treatment-naïve cancer (mostly breast, endometrial or colorectal cancer), 32 with DM2 without cancer, and 23 with treatment-naïve cancer and normal glucose tolerance. The leading metformin response S-marker in combined group of DM2 patients was the CC variant of OCT1-R61C polymorphism of organic cation transporter protein 1 gene. In cancer patients without DM2, this position belonged to AC and AA genotypes of OCT1_rs622342 polymorphism. Among the A-polymorphisms, GA variant of sex hormone-binding globulin gene SHBG_D356N was less frequently observed in DM2 patients with or without cancer. Besides, in diabetics, the same polymorphic variant of SHBG as well as GC genotype of oxidized lipoprotein receptor OLR1_G501C and GG genotype of locus rs11065987 near BRAP gene were carried rather often in combination with "metformin-positive" variant of OCT1_R61C. In addition, carriers of OCT1_R61C and OCT1_rs622342 polymorphisms with potentially positive reaction to metformin had higher insulin resistance score (HOMA-IR) values. Received data lead to the conclusion that postmenopausal diabetics, both with and without cancer, differ in genetic stigmata of potential response to metformin less than they differ from cancer patients without DM2. As genetic polymorphisms associated with metabolic and anticancer metformin (and, possibly, phenformin) effects may be different, this subject requires further investigation.

Forkhead box(O) in control of reactive oxygen species and genomic stability to ensure healthy lifespan

SIGNIFICANCE

Transcription factors of the Forkhead box O class (FOXOs) are associated with lifespan and play a role in age-related diseases. FOXOs, therefore, serve as a paradigm for developing an understanding as to how age-related diseases, such as cancer and diabetes interconnect with lifespan. Understanding the regulatory inputs on FOXO may reveal how changes in these regulatory signaling pathways affect disease and lifespan.

RECENT ADVANCES

Numerous regulators of FOXO have now been described and a clear and evolutionary conserved role has emerged for phosphoinositide-3 kinase/protein kinase B (also known as c-Akt or AKT) signaling and c-jun N-terminal kinase signaling. Analysis of FOXO function in the context of these signaling pathways has shown the importance of FOXO-mediated transcriptional regulation on cell cycle progression and other cell fates, such as cell metabolism, stress resistance, and apoptosis in mediating disease and lifespan.

CRITICAL ISSUES

Persistent DNA damage is also tightly linked to disease and aging; yet, data on a possible link between DNA damage and FOXO have been limited. Here, we discuss possible connections between FOXO and the DNA damage response in the context of the broader role of connecting lifespan and disease.

FUTURE DIRECTIONS

Understanding the role of lifespan in diseases onset may provide unique and generic possibilities to intervene in disease processes to ensure a healthy lifespan.

Beyond aspirin-cancer prevention with statins, metformin and bisphosphonates

Cancer risk reduction using pharmacological means is an attractive modern preventive approach that supplements the classical behavioural prevention recommendations. Medications that are commonly used by large populations to treat a variety of common, non-cancer-related, medical situations are an attractive candidate pool. This Review discusses three pharmacological agents with the most evidence for their potential as cancer chemopreventive agents: anti-hypercholesterolaemia medications (statins), an antidiabetic agent (metformin) and antiosteoporosis drugs (bisphosphonates). Data are accumulating to support a significant negative association of certain statins with cancer occurrence or survival in several major tumour sites (mostly gastrointestinal tumours and breast cancer), with an augmented combined effect with aspirin or other non-steroidal anti-inflammatory drugs. Metformin, but not other hypoglycaemic drugs, also seems to have some antitumour growth activity, but the amount of evidence in human studies, mainly in breast cancer, is still limited. Experimental and observational data have identified bisphosphonates as a pharmacological group that could have significant impact on incidence and mortality of more than one subsite of malignancy. At the current level of evidence these potential chemopreventive drugs should be considered in high-risk situations or using the personalized approach of maximizing individual benefits and minimizing the potential for adverse effects with the aid of pharmacogenetic indicators.

The new perspectives on genetic studies of type 2 diabetes and thyroid diseases

Recently, genome-wide association studies (GWAS) have led to the discovery of hundreds of susceptibility loci that are associated with complex metabolic diseases, such as type 2 diabetes and hyperthyroidism. The majority of the susceptibility loci are common across different races or populations; while some of them show ethnicity-specific distribution. Though the abundant novel susceptibility loci identified by GWAS have provided insight into biology through the discovery of new genes or pathways that were previously not known, most of them are in introns and the associated variants cumulatively explain only a small fraction of total heritability. Here we reviewed the genetic studies on the metabolic disorders, mainly type 2 diabetes and hyperthyroidism, including candidate genes-based findings and more recently the GWAS discovery; we also included the clinical relevance of these novel loci and the gene-environmental interactions. Finally, we discussed the future direction about the genetic study on the exploring of the pathogenesis of the metabolic diseases.