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

A role for ataxia telangiectasia mutated in insulin-independent stimulation of glucose transport

Literature reports suggest that ataxia telangiectasia mutated (ATM) can activate the AMP-activated protein kinase (AMPK), a protein that can stimulate glucose transport in skeletal muscle. We hypothesized that 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR), an AMPK activator, would increase glucose transport in mouse extensor digitorum longus (EDL) muscles in an ATM-dependent manner. AICAR-stimulated glucose transport was prevented by the ATM inhibitor KU-55933 despite normal stimulation of AMPK phosphorylation. Consistent with this, AICAR caused AMPK phosphorylation but not an increase of glucose transport in ATM-deficient (ATM-/-) muscles. S231 of TBC1D1 matches the sequence motif of ATM substrates, and phosphorylation of this site is known to inhibit TBC1D1 and lead to increased glucose transport. Accordingly, we assessed TBC1D1 phosphorylation and found that AICAR-stimulated phosphorylation of TBC1D1 at S231 did not occur in ATM-/- muscles. However, activation of ATM without activation of AMPK was insufficient to increase TBC1D1 phosphorylation. The data suggest that ATM plays a role in AICAR-stimulated glucose transport downstream of AMPK.

Single nucleotide polymorphisms in the intergenic region between metformin transporter OCT2 and OCT3 coding genes are associated with short-term response to metformin monotherapy in type 2 diabetes mellitus patients

OBJECTIVES

High variability in clinical response to metformin is often observed in type 2 diabetes (T2D) patients, and it highlights the need for identification of genetic components affecting the efficiency of metformin therapy. Aim of this observational study is to evaluate the role of tagSNPs (tagging single nucleotide polymorphisms) from genomic regions coding for six metformin transporter genes with respect to the short-term efficiency.

DESIGN

102 tagSNPs in 6 genes coding for metformin transporters were genotyped in the group of 102 T2D patients treated with metformin for 3 months.

METHODS

Most significant hits were analyzed in the group of 131 T2D patients from Slovakia. Pharmacokinetic study in 25 healthy nondiabetic volunteers was conducted to investigate the effects of identified polymorphisms.

RESULTS

In the discovery group of 102 patients, minor alleles of rs3119309, rs7757336 and rs2481030 were significantly nominally associated with metformin inefficiency (P = 1.9 × 10^-6 to 8.1 × 10^-6). Effects of rs2481030 and rs7757336 did not replicate in the group of 131 T2DM patients from Slovakia alone, whereas rs7757336 was significantly associated with a reduced metformin response in combined group. In pharmacokinetic study, group of individuals harboring risk alleles of rs7757336 and rs2481030 displayed significantly reduced AUC_∞ of metformin in plasma.

CONCLUSIONS

For the first time, we have identified an association between the lack of metformin response and SNPs rs3119309 and rs7757336 located in the 5' flanking region of the genes coding for Organic cation transporter 2 and rs2481030 located in the 5' flanking region of Organic cation transporter 3 that was supported by the results of a pharmacokinetic study on 25 healthy volunteers.

Genomic Characterization of Metformin Hepatic Response

Metformin is used as a first-line therapy for type 2 diabetes (T2D) and prescribed for numerous other diseases. However, its mechanism of action in the liver has yet to be characterized in a systematic manner. To comprehensively identify genes and regulatory elements associated with metformin treatment, we carried out RNA-seq and ChIP-seq (H3K27ac, H3K27me3) on primary human hepatocytes from the same donor treated with vehicle control, metformin or metformin and compound C, an AMP-activated protein kinase (AMPK) inhibitor (allowing to identify AMPK-independent pathways). We identified thousands of metformin responsive AMPK-dependent and AMPK-independent differentially expressed genes and regulatory elements. We functionally validated several elements for metformin-induced promoter and enhancer activity. These include an enhancer in an ataxia telangiectasia mutated (ATM) intron that has SNPs in linkage disequilibrium with a metformin treatment response GWAS lead SNP (rs11212617) that showed increased enhancer activity for the associated haplotype. Expression quantitative trait locus (eQTL) liver analysis and CRISPR activation suggest that this enhancer could be regulating ATM, which has a known role in AMPK activation, and potentially also EXPH5 and DDX10, its neighboring genes. Using ChIP-seq and siRNA knockdown, we further show that activating transcription factor 3 (ATF3), our top metformin upregulated AMPK-dependent gene, could have an important role in gluconeogenesis repression. Our findings provide a genome-wide representation of metformin hepatic response, highlight important sequences that could be associated with interindividual variability in glycemic response to metformin and identify novel T2D treatment candidates.

Metformin is among the most widely prescribed drugs. It is used as a first line therapy for type 2 diabetes (T2D), and for additional diseases including cancer. The variability in response to metformin is substantial and can be caused by genetic factors. However, the molecular mechanisms of metformin action are not fully known. Here, we used various genomic assays to analyze human liver cells treated with or without metformin and identified in a genome-wide manner thousands of differentially expressed genes and gene regulatory elements affected by metformin. Follow up functional assays identified several novel genes and regulatory elements to be associated with metformin response. These include ATF3, a gene that showed gluconeogenesis repression upon metformin response and a potential regulatory element of the ATM gene that is associated with metformin treatment differences through genome-wide association studies. Combined, this work identifies several novel genes and gene regulatory elements that can be activated due to metformin treatment and thus provides candidate sequences in the human genome where nucleotide variation can lead to differences in metformin response. It also enables the identification and prioritization of novel candidates for T2D treatment.

The cell-autonomous mechanisms underlying the activity of metformin as an anticancer drug

The biguanide drug metformin profoundly affects cell metabolism, causing an impairment of the cell energy balance and triggering a plethora of pleiotropic effects that vary depending on the cellular or environmental context. Interestingly, a decade ago, it was observed that metformin-treated diabetic patients have a significantly lower cancer risk. Although a variety of in vivo and in vitro observations emphasising the role of metformin as anticancer drug have been reported, the underlying mechanisms are still poorly understood. Here, we discuss our current understanding of the molecular mechanisms that are perturbed by metformin treatment and that might be relevant to understand its antitumour activities. We focus on the cell-autonomous mechanisms modulating growth and death of cancer cells.

The role of the p53 tumor suppressor in metabolism and diabetes

In the context of tumor suppression, p53 is an undisputedly critical protein. Functioning primarily as a transcription factor, p53 helps fend off the initiation and progression of tumors by inducing cell cycle arrest, senescence or programmed cell death (apoptosis) in cells at the earliest stages of precancerous development. Compelling evidence, however, suggests that p53 is involved in other aspects of human physiology, including metabolism. Indeed, recent studies suggest that p53 plays a significant role in the development of metabolic diseases, including diabetes, and further that p53's role in metabolism may also be consequential to tumor suppression. Here, we present a review of the literature on the role of p53 in metabolism, diabetes, pancreatic function, glucose homeostasis and insulin resistance. Additionally, we discuss the emerging role of genetic variation in the p53 pathway (single-nucleotide polymorphisms) on the impact of p53 in metabolic disease and diabetes. A better understanding of the relationship between p53, metabolism and diabetes may one day better inform the existing and prospective therapeutic strategies to combat this rapidly growing epidemic.

The Application of Genomics in Diabetes: Barriers to Discovery and Implementation

The emerging availability of genomic and electronic health data in large populations is a powerful tool for research that has drawn interest in bringing precision medicine to diabetes. In this article, we discuss the potential application of genomics to the prediction, prevention, and treatment of diabetes, and we use examples from other areas of medicine to illustrate some of the challenges involved in conducting genomics research in human populations and implementing findings in practice. At this time, a major barrier to the application of genomics in diabetes care is the lack of actionable genomic findings. Whether genomic information should be used in clinical practice requires a framework for evaluating the validity and clinical utility of this approach, an improved integration of genomic data into electronic health records, and the clinical decision support and educational resources for clinicians to use these data. Efforts to identify optimal approaches in all of these domains are in progress and may help to bring diabetes into the era of genomic medicine.

A Longitudinal HbA1c Model Elucidates Genes Linked to Disease Progression on Metformin

One-third of type-2 diabetic patients respond poorly to metformin. Despite extensive research, the impact of genetic and nongenetic factors on long-term outcome is unknown. In this study we combine nonlinear mixed effect modeling with computational genetic methodologies to identify predictors of long-term response. In all, 1,056 patients contributed their genetic, demographic, and long-term HbA1c data. The top nine variants (of 12,000 variants in 267 candidate genes) accounted for approximately one-third of the variability in the disease progression parameter. Average serum creatinine level, age, and weight were determinants of symptomatic response; however, explaining negligible variability. Two single nucleotide polymorphisms (SNPs) in CSMD1 gene (rs2617102, rs2954625) and one SNP in a pharmacologically relevant SLC22A2 gene (rs316009) influenced disease progression, with minor alleles leading to less and more favorable outcomes, respectively. Overall, our study highlights the influence of genetic factors on long-term HbA1c response and provides a computational model, which when validated, may be used to individualize treatment.

A Genome-Wide Association Study Provides New Evidence That CACNA1C Gene is Associated With Diabetic Cataract

Purpose

Diabetic cataract is one of the major eye complications of diabetes. It was reported that cataract occurs two to five times more frequently in patients with diabetes compared with those with no diabetes. The purpose of this study was to identify genetic contributors of diabetic cataract based on a genome-wide association approach using a well-defined Scottish diabetic cohort.

Methods

We adapted linked e-health records to define diabetic cataract. A diabetic cataract case in this study was defined as a type 2 diabetic patient who has ever been recorded in the linked e-health records to have cataracts in both eyes or who had previous cataract extraction surgeries in at least one eye. A control in this study was defined as a type 2 diabetic individual who has never been diagnosed as cataract in the linked e-health records and had no history of cataract surgeries. A standard genome-wide association approach was applied.

Results

Overall, we have 2341 diabetic cataract cases and 2878 controls in the genetics of diabetes audit and research in Tayside Scotland (GoDARTS) dataset. We found that the P value of rs2283290 in the CACNA1C gene was 8.81 × 10⁻¹⁰, which has reached genome-wide significance. We also identified that the blood calcium level was statistically different between diabetic cataract cases and controls.

Conclusions

We identified supporting evidence that CACNA1C gene is associated with diabetic cataract. The role of calcium in the cataractogenesis needs to be reevaluated in future studies.

Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin

Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome-wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (P = 6.6 × 10(-14)) greater metformin-induced reduction in hemoglobin A1c (HbA1c) in 10,577 participants of European ancestry. rs8192675 was the top cis expression quantitative trait locus (cis-eQTL) for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. Among obese individuals, C-allele homozygotes at rs8192675 had a 0.33% (3.6 mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes. This was about half the effect seen with the addition of a DPP-4 inhibitor, and equated to a dose difference of 550 mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

Challenges of implementing personalized (precision) medicine: a focus on diabetes

The concept of personalized (precision) medicine (PM) emphasizes the scientific and technological innovations that enable the physician to tailor disease prediction, diagnosis and treatment to the individual patient, based on a personalized data-driven approach. The major challenge for the medical systems is to translate the molecular and genomic advances into clinical available means. Patients and healthcare providers, the pharmaceutical and diagnostic industries manifest a growing interest in PM. Multiple stakeholders need adaptation and re-engineering for successful clinical implementation of PM. Drawing primarily from the field of ‘diabetes’, this article will summarize the main challenges to implementation of PM into current medical practice and some of the approaches currently being implemented to overcome these challenges.

A missense variant in GLP1R gene is associated with the glycaemic response to treatment with gliptins

Gliptins act by increasing endogenous incretin levels. Glucagon-like peptide-1 receptor (GLP1R) and glucose-dependent insulinotropic peptide receptor (GIPR) are their indirect drug targets. Variants of GLP1R and GIPR have previously been associated with the incretin effect. The aim of the present pilot study was to examine associations of the GLP1R and GIPR gene variants with the glycaemic response to gliptins. A total of 140 consecutive patients with type 2 diabetes were followed-up 6 months after initiation of gliptin treatment. GLP1R rs6923761 (Gly168Ser) and GIPR rs10423928 genotyping was performed using real-time PCR, with subsequent high-resolution melting analysis. The main study outcome was reduction in glycated haemoglobin (HbA1c) after treatment. GLP1R Gly168Ser variant was significantly associated with reduction in HbA1c in an additive model (β = -0.33, p = 0.011). The mean reduction in HbA1c in Ser/Ser homozygotes was significantly lower compared with Gly-allele carriers [0.12 ± 0.23% vs. 0.80 ± 0.09% (1.3 ± 2.5 mmol/mol vs. 8.7 ± 1.0 mmol/mol); p = 0.008]. In conclusion, GLP1R missense variant was associated with a reduced response to gliptin treatment. The genotype-related effect size of ∼0.7% (8 mmol/mol) is equal to an average effect of gliptin treatment and makes this variant a candidate for use in precision medicine.

Effects of SLC22A1 Polymorphisms on Metformin-Induced Reductions in Adiposity and Metformin Pharmacokinetics in Obese Children With Insulin Resistance

Steady-state population pharmacokinetics of a noncommercial immediate-release metformin (hydrochloride) drug product were characterized in 28 severely obese children with insulin resistance. The concentration-time profiles with double peaks were well described by a 1-compartment model with 2 absorption sites. Mean population apparent clearance (CL/F) was 68.1 L/h, and mean apparent volume of distribution (V/F) was 28.8 L. Body weight was a covariate of CL/F and V/F. Estimated glomerular filtration rate was a significant covariate of CL/F (P < .001). SLC22A1 genotype did not significantly affect metformin pharmacokinetics. The response to 6 months of metformin treatment (HbA_1c , homeostasis model assessment for insulin resistance, fasting insulin, and glucose changes) did not differ between SLC22A1 wild-type subjects and carriers of presumably low-activity SLC22A1 alleles. However, SLC22A1 variant carriers had smaller reductions in percentage of total trunk fat after metformin therapy, although the percentage reduction in trunk fat was small. The median % change in trunk fat was -2.20% (-9.00% to 0.900%) and -1.20% (-2.40% to 7.30%) for the SLC22A1 wild-type subjects and variant carriers, respectively. Future study is needed to evaluate the effects of SLC22A1 polymorphisms on metformin-mediated weight reduction in obese children.

Type 2 diabetes: genetic data sharing to advance complex disease research

As with other complex diseases, unbiased association studies followed by physiological and experimental characterization have for years formed a paradigm for identifying genes or processes of relevance to type 2 diabetes mellitus (T2D). Recent large-scale common and rare variant genome-wide association studies (GWAS) suggest that substantially larger association studies are needed to identify most T2D loci in the population. To hasten clinical translation of genetic discoveries, new paradigms are also required to aid specialized investigation of nascent hypotheses. We argue for an integrated T2D knowledgebase, designed for a worldwide community to access aggregated large-scale genetic data sets, as one paradigm to catalyse convergence of these efforts.

The impact of personalized medicine of Type 2 diabetes mellitus in the global health context

Advances in the fields of genomic sciences have given rise to personalized medicine. This new paradigm draws upon a patient's genetic and metabolic makeup in order to tailor diagnostics and treatment. Personalized medicine holds remarkable promises to improve prevention and management of chronic diseases of global relevance, such as Type 2 diabetes mellitus (T2DM). This review article aims at summarizing the evidence from genome-based sciences on T2DM risk and management in different populations and in the Global Health context. Opinions from leading experts in the field were also included. Based on these findings, strengths and weaknesses of personalized approach to T2DM in a global context are delineated. Implications for future research and implementation on that subject are discussed.

Leveraging Genetics to Advance Type 2 Diabetes Prevention

In this Perspective, Jose Florez discusses how information from genetics and genomics may be able to contribute to prevention of type 2 diabetes and predicting individual responses to behavioral and other interventions.

Precision medicine: The future in diabetes care?

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

Endocrine abnormalities in ataxia telangiectasia: findings from a national cohort

BACKGROUND

Ataxia telangiectasia (AT) is a genetic multisystem disorder, presenting with progressive ataxia, immune deficiency, and propensity toward malignancy. Endocrine abnormalities (growth retardation, reproductive dysfunction, and diabetes) have been described, however detailed information regarding this aspect is lacking. We aimed to characterize endocrine anomalies and growth patterns in a large cohort of AT patients.

METHODS

Retrospective study comprising all 52 patients (aged 2-26.2 y) followed at a national AT Clinic. Anthropometric and laboratory measurements were extracted from the charts.

RESULTS

Median height-SDS was already subnormal during infancy, remaining negative throughout follow up to adulthood. Height-SDS was more impaired than weight-SDS up to age 4 y, thereafter weight-SDS steadily decreased, resulting in progressively lower BMI-SDS. IGF-I-SDS was low (-1.53 ± 1.54), but did not correlate with height-SDS. Gonadal failure was present in all 13 females older than 10 y but only in one male. Two patients had diabetes and 10 had dyslipidemia. Vitamin D deficiency was observed in 52.2% of the evaluated patients.

CONCLUSION

Our results suggest a primary growth abnormality in AT, rather than secondary to nutritional impairment or disease severity. Sex hormone replacement should be considered for female patients. Vitamin D levels should be followed and supplementation given if needed.

Personalized medicine in diabetes: the role of 'omics' and biomarkers

Personalized medicine, otherwise called stratified or precision medicine, aims to better target intervention to the individual to maximize benefit and minimize harm. This review discusses how diabetes aetiology, pathophysiology and patient genotype influence response to or side effects of the commonly used diabetes treatments. C-peptide is a useful biomarker that is underused to guide treatment choice, severe insulin deficiency predicts non-response to glucagon-like peptide-1 receptor agonists, and thiazolidinediones are more effective in insulin-resistant patients. The field of pharmacogenetics is now yielding clinically important results, with three examples outlined: sulphonylurea sensitivity in patients with HNF1A maturity-onset diabetes of the young; sulphonylurea sensitivity in patients with Type 2 diabetes with reduced function alleles at CYP2C9, resulting in reduced metabolism of sulphonylureas; and severe metformin intolerance associated with reduced function organic cation transporter 1 (OCT1) variants, exacerbated by drugs that also inhibit OCT1. Genome-wide approaches and the potential of other 'omics', including metagenomics and metabolomics, are then outlined, highlighting the complex interacting networks that we need to understand before we can truly personalize diabetes treatments.

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

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

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

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

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

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

The genetics of drug efficacy: opportunities and challenges

Lack of sufficient efficacy is the most common cause of attrition in late-phase drug development. It has long been envisioned that genetics could drive stratified drug development by identifying those patient subgroups that are most likely to respond. However, this vision has not been realized as only a small proportion of drugs have been found to have germline genetic predictors of efficacy with clinically meaningful effects, and so far all but one were found after drug approval. With the exception of oncology, systematic application of efficacy pharmacogenetics has not been integrated into drug discovery and development across the industry. Here, we argue for routine, early and cumulative screening for genetic predictors of efficacy, as an integrated component of clinical trial analysis. Such a strategy would identify clinically relevant predictors that may exist at the earliest possible opportunity, allow these predictors to be integrated into subsequent clinical development and provide mechanistic insights into drug disposition and patient-specific factors that influence response, therefore paving the way towards more personalized medicine.

Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State

Metformin is the most frequently prescribed drug for type 2 diabetes. In addition to its hypoglycemic effects, metformin also lowers cancer incidence. This anti-cancer activity is incompletely understood. Here, we profiled the metformin-dependent changes in the proteome and phosphoproteome of breast cancer cells using high-resolution mass spectrometry. In total, we quantified changes of 7,875 proteins and 15,813 phosphosites after metformin changes. To interpret these datasets, we developed a generally applicable strategy that overlays metformin-dependent changes in the proteome and phosphoproteome onto a literature-derived network. This approach suggested that metformin treatment makes cancer cells more sensitive to apoptotic stimuli and less sensitive to pro-growth stimuli. These hypotheses were tested in vivo; as a proof-of-principle, we demonstrated that metformin inhibits the p70S6K-rpS6 axis in a PP2A-phosphatase dependent manner. In conclusion, analysis of deep proteomics reveals both detailed and global mechanisms that contribute to the anti-cancer activity of metformin.

ATM kinase: Much more than a DNA damage responsive protein

ATM, mutation of which causes Ataxia telangiectasia, has emerged as a cardinal multifunctional protein kinase during past two decades as evidenced by various studies from around the globe. Further to its well established and predominant role in DNA damage response, ATM has also been understood to help in maintaining overall functional integrity of cells; since its mutation, inactivation or deficiency results in a variety of pathological manifestations besides DNA damage. These include oxidative stress, metabolic syndrome, mitochondrial dysfunction as well as neurodegeneration. Recently, high throughput screening using proteomics, metabolomics and transcriptomic studies revealed several proteins which might be acting as substrates of ATM. Studies that can help in identifying effective regulatory controls within the ATM-mediated pathways/mechanisms can help in developing better therapeutics. In fact, more in-depth understanding of ATM-dependent cellular signals could also help in the treatment of variety of other disease conditions since these pathways seem to control many critical cellular functions. In this review, we have attempted to put together a detailed yet lucid picture of the present-day understanding of ATM's role in various pathophysiological conditions involving DNA damage and beyond.

Recessive mutations in the cancer gene Ataxia Telangiectasia Mutated (ATM), at a locus previously associated with metformin response, cause dysglycaemia and insulin resistance

AIM

To investigate glucose and insulin metabolism in participants with ataxia telangiectasia in the absence of a diagnosis of diabetes.

METHODS

A standard oral glucose tolerance test was performed in participants with ataxia telangiectasia (n = 10) and in a control cohort (n = 10). Serial glucose and insulin measurements were taken to permit cohort comparisons of glucose-insulin homeostasis and indices of insulin secretion and sensitivity.

RESULTS

During the oral glucose tolerance test, the 2-h glucose (6.75 vs 4.93 mmol/l; P = 0.029), insulin concentrations (285.6 vs 148.5 pmol/l; P = 0.043), incremental area under the curve for glucose (314 vs 161 mmol/l/min; P = 0.036) and incremental area under the curve for insulin (37,720 vs 18,080 pmol/l/min; P = 0.03) were higher in participants with ataxia telangiectasia than in the controls. There were no significant differences between groups in fasting glucose, insulin concentrations or insulinogenic index measurement (0.94 vs 0.95; P = 0.95). The Matsuda index, reflecting whole-body insulin sensitivity, was lower in participants with ataxia telangiectasia (5.96 vs 11.03; P = 0.019) than in control subjects.

CONCLUSIONS

Mutations in Ataxia Telangiectasia Mutated (ATM) that cause ataxia telangiectasia are associated with elevated glycaemia and low insulin sensitivity in participants without diabetes. This indicates a role of ATM in glucose and insulin metabolic pathways.

Pharmacogenetics: Implications for Modern Type 2 Diabetes Therapy

Many clinical treatment studies have reported remarkable interindividual variability in the response to pharmaceutical drugs, and uncovered the existence of inadequate treatment response, non-response, and even adverse drug reactions. Pharmacogenetics addresses the impact of genetic variants on treatment outcome including side-effects. In recent years, it has also entered the field of clinical diabetes research. In modern type 2 diabetes therapy, metformin is established as first-line drug. The latest pharmaceutical developments, including incretin mimetics, dipeptidyl peptidase 4 inhibitors (gliptins), and sodium/glucose cotransporter 2 inhibitors (gliflozins), are currently experiencing a marked increase in clinical use, while the prescriptions of α-glucosidase inhibitors, sulfonylureas, meglitinides (glinides), and thiazolidinediones (glitazones) are declining, predominantly because of reported side-effects. This review summarizes the current knowledge about gene-drug interactions observed in therapy studies with the above drugs. We report drug interactions with candidate genes involved in the pharmacokinetics (e.g., drug transporters) and pharmacodynamics (drug targets and downstream signaling steps) of the drugs, with known type 2 diabetes risk genes and previously unknown genes derived from hypothesis-free approaches such as genome-wide association studies. Moreover, some new and promising candidate genes for future pharmacogenetic assessment are highlighted. Finally, we critically appraise the current state of type 2 diabetes pharmacogenetics in the light of its impact on therapeutic decisions, and we refer to major problems, and make suggestions for future efforts in this field to help improve the clinical relevance of the results, and to establish genetically determined treatment failure.

Progression to treatment failure among Chinese patients with type 2 diabetes initiated on metformin versus sulphonylurea monotherapy--The Hong Kong Diabetes Registry

AIMS

To assess the development of treatment failure in Chinese patients with type 2 diabetes mellitus (T2DM) initiated on metformin or sulphonylurea (SU) monotherapy, with consideration of various potential sources of biases.

METHODS

A 1:1-matched new metformin and SU user cohort on immortal time and mean propensity score after multiple imputation was selected from a cohort of 5889 Chinese patients with T2DM. Treatment failure was defined as progression to (i) combination oral anti-hyperglycemia drug therapy, (ii) insulin use, or (iii) a treatment haemoglobin A1c (HbA1c) >7.5% (58 mmol/mol). Stratified Cox regression analysis on the matched pairs was employed to examine the associations between initial monotherapy and onset of treatment failure.

RESULTS

Of 554 new metformin and 840 new SU users, 380 were matched. During a median follow-up duration of 3 years, 173 (45.6%) metformin users and 220 (57.9%) SU users experienced treatment failure (annual failure rates of 15% and 19%, respectively). The median time from monotherapy starting to treatment failure was 3.0 [inter-quartile range (IQR): 1.8-5.4] years for metformin users, versus 1.8 (IQR: 0.9-4.1) years for SU users (p<0.001). Stratified Cox regression analysis showed significantly lower risk of treatment failure for metformin users (HR [95% CI], 0.62[0.47-0.81]; p<0.001). Consistent results were found in analyses based on traditional adjustment schemes with or without imputation.

CONCLUSIONS

By systematically incorporating new-user design, multiple imputation and matching methods, we found that Chinese patients with T2DM initiated on metformin monotherapy were associated with a significant delay in the onset of treatment failure compared to SU monotherapy.

Phenotypic and genetic characteristics of patients with type 2 diabetes with different responses to metformin therapy in Novosibirsk region

Aim: The purpose of this study was to examine the phenotypic and genetic characteristics of patients with type 2 diabetes mellitus (T2DM) with different responses to treatment with metformin (MF) in the Novosibirsk region. Materials and methods: We examined 460 patients with T2DM in the Novosibirsk region. Patients were divided into groups according to their HbA1c level: patients who achieved the target HbA1c level during MF therapy (n = 209) and those who did not reach the target HbA1c level (n=251). Genotyping of ATM (rs11212617) was performed using polymerase chain reaction by TaqMan. Results: Patients who achieved the target HbA1c level during MF treatment (good response) were older (61. 1±9. 1 years vs. 57. 4±8. 4 years, p=0. 001), had later onset of diabetes (54. 6 ± 10. 1 years vs. 49. 2±8. 5 years, p = 0. 0001) and shorter duration of diabetes (6. 5±5. 9 years vs. 8. 2±6. 1 years, p=0. 03) compared with those who did not achieve the target HbA1c level. There was no statistically significant association between ATM rs11212617 and achieving the target HbA1c level among all patients [odds ratio (OR)=0. 94, 95% confidence interval = (0. 73–1. 23), p=0. 67] or those with MF monotherapy [OR=0. 90, (0. 65–1. 25), p=0. 54] or combination therapy [OR=1. 02, (0. 72–1. 43), p=0. 92]. There was an effect of age on response to MF therapy in all three groups (all patients: p=0. 001, MF monotherapy group: p=0. 04, combination therapy group: p=0. 0009). In the MF monotherapy group, low dose MF was associated with a good response (p=0. 03), and in the combination therapy group, males were more likely to have a good response (p=0. 003). Patients with genotype C/C or A/C for ATM (rs11212617) compared with those with genotype A/A were more likely to have high levels of triglycerides [2. 33 (1. 52–4. 2) mmol/l, 2. 09 (1. 35–3. 0) mmol/l and 1. 99 (1. 49–3. 21) mmol/l, respectively, p=0. 001], coronary heart disease (CHD) (13. 4%, 13. 4% and 9. 6%, respectively, p=0. 009) and myocardial infarction (7. 8%, 3. 2% and 4. 0%, respectively, p=0. 001). Conclusion: Patients with T2DM who had a good response to MF therapy were older, more likely to be male and had a later onset of T2DM. Genotype C/C for ATM rs11212617 was associated with high triglycerides, CHD and myocardial infarction. ATM rs11212617 was not associated with response to MF therapy in the Novosibirsk region. 

Impact of ATM and SLC22A1 Polymorphisms on Therapeutic Response to Metformin in Iranian Diabetic Patients

Metabolic syndrome and its pathological sequel, type 2 diabetes are considered as important global health problems. Metformin is the most common drug prescribed for patients with this disorder. Consequently, understanding the genetic pathways involved in pharmacokinetics and pharmacodynamics of this drug can have a considerable effect on the personalized treatment of type 2 diabetes. In this study, we evaluated the association between rs11212617 polymorphism of ATM gene and rs628031 of SLC22A1 gene with response to treatment in newly diagnosed type 2 diabetes patients. We genotyped rs11212617 and rs628031 polymorphism by PCR based restriction fragment length polymorphism (RFLP) and assessed the role of this polymorphisms on response to treatment in 140 patients who have been recently diagnosed with type 2 diabetes and were under monotherapy with metformin for 6 months. Response to metformin was defined by HbA1c and fasting blood sugar (FBS) values. Based on such evaluations, patients were divided into two groups: responders (n= 63) and non-responders (n= 77). No significant association was found between these polymorphisms and response to treatment (OR= 0.86, [95% CI 0.52-1.41], P= 0.32) for rs11212617 and (OR= 0.45, [95% CI 0.64-1.76], P= 0.45) for rs 628031. The reported gene variants in ATM and SLC22A1 are not significantly associated with metformin treatment response in type 2 diabetic patients in an Iranian population.

A genome-wide association study suggests an association of Chr8p21.3 (GFRA2) with diabetic neuropathic pain

Background

Neuropathic pain, caused by a lesion or a disease affecting the somatosensory system, is one of the most common complications in diabetic patients. The purpose of this study is to identify genetic factors contributing to this type of pain in a general diabetic population.

Method

We accessed the Genetics of Diabetes Audit and Research Tayside (GoDARTS) datasets that contain prescription information and monofilament test results for 9439 diabetic patients, among which 6927 diabetic individuals were genotyped by Affymetrix SNP6.0 or Illumina OmniExpress chips. Cases of neuropathic pain were defined as diabetic patients with a prescription history of at least one of five drugs specifically indicated for the treatment of neuropathic pain and in whom monofilament test result was positive for sensory neuropathy in at least one foot. Controls were individuals who did not have a record of receiving any opioid analgesics. Imputation of non‐genotyped SNPs was performed by IMPUTE2, with reference files from 1000 Genomes Phase I datasets.

Results

After data cleaning and relevant exclusions, imputed genotypes of 572 diabetic neuropathic pain cases and 2491 diabetic controls were used in the Fisher's exact test. We identified a cluster in the Chr8p21.3, next to GFRA2 with a lowest p‐value of 1.77 × 10⁻⁷ at rs17428041. The narrow‐sense heritability of this phenotype was 11.00%.

Conclusion

This genome‐wide association study on diabetic neuropathic pain suggests new evidence for the involvement of variants near GFRA2 with the disorder, which needs to be verified in an independent cohort and at the molecular level.

A twin study of the trough plasma steady-state concentration of metformin

OBJECTIVE

The aim of this study was to determine the intrapair similarity in trough steady-state plasma concentrations of metformin in monozygotic and dizygotic twin pairs.

METHODS

We included 16 twin pairs (eight monozygotic and eight dizygotic twin pairs) for this study after contacting 524 twin pairs. They were dosed with metformin to steady state (1 g twice daily) for 6 days and on day 7, the trough concentration of metformin was determined 12 h after the last dose.

RESULTS

There was no strong intrapair similarity in trough steady-state plasma concentrations of metformin in either dizygotic or monozygotic twin pairs.

CONCLUSION

The trough steady-state plasma concentration of metformin does not appear to be tightly genetically regulated. The interpretation of this finding is limited by the small sample size.

Regulation of the p53 response and its relationship to cancer

p53 has been studied intensively as a major tumour suppressor that detects oncogenic events in cancer cells and eliminates them through senescence (a permanent non-proliferative state) or apoptosis. Consistent with this role, p53 activity is compromised in a high proportion of all cancer types, either through mutation of the TP53 gene (encoding p53) or changes in the status of p53 modulators. p53 has additional roles, which may overlap with its tumour-suppressive capacity, in processes including the DNA damage response, metabolism, aging, stem cell differentiation and fertility. Moreover, many mutant p53 proteins, termed 'gain-of-function' (GOF), acquire new activities that help drive cancer aggression. p53 is regulated mainly through protein turnover and operates within a negative-feedback loop with its transcriptional target, MDM2 (murine double minute 2), an E3 ubiquitin ligase which mediates the ubiquitylation and proteasomal degradation of p53. Induction of p53 is achieved largely through uncoupling the p53-MDM2 interaction, leading to elevated p53 levels. Various stress stimuli acting on p53 (such as hyperproliferation and DNA damage) use different, but overlapping, mechanisms to achieve this. Additionally, p53 activity is regulated through critical context-specific or fine-tuning events, mediated primarily through post-translational mechanisms, particularly multi-site phosphorylation and acetylation. In the present review, I broadly examine these events, highlighting their regulatory contributions, their ability to integrate signals from cellular events towards providing most appropriate response to stress conditions and their importance for tumour suppression. These are fascinating aspects of molecular oncology that hold the key to understanding the molecular pathology of cancer and the routes by which it may be tackled therapeutically.

Involvement of metformin and AMPK in the radioresponse and prognosis of luminal versus basal-like breast cancer treated with radiotherapy

Metformin is under evaluation as a potential anticancer agent. Expression of total and phospho(Thr172)-adenosine monophosphate-activated kinase-α (AMPKα and pAMPKα(Thr172) respectively), a main metformin target, was examined in radiotherapy treated breast cancers and metformin's ability to modulate Trx system expression and breast cancer radiosensitivity evaluated in vitro.

AMPKα and pAMPKα(Thr172) expression was assessed using a discovery (n=166) and validation cohort (n=609). Metformin's role in regulating radioresponse, and Trx family expression, was examined via clonogenic assays and Western blots. Intracellular reactive oxygen species (ROS) levels, cell cycle progression and apoptosis were assessed by flow cytometry.

High AMPKα expression associated with improved local recurrence-free (P=0.019), relapse-free (P=0.016) and breast cancer-specific survival (P=0.000065) and was, from multivariate analysis, an independent prognostic factor from the discovery cohort. From the validation cases AMPKα expression associated with relapse-free and breast cancer-specific survival in luminal breast cancers. Metformin substantially increased radiosensitivity, intracellular ROS levels and reduced Trx expression, in luminal breast cancer cells, but had little effect on basal phenotype cells.

In conclusion, high AMPKα expression associates with improved prognosis, especially in luminal breast cancer. Metformin preferentially radiosensitises luminal breast cancer cells, potentially due to alterations to intracellular ROS levels via modulation of Trx family protein expression.

(Ir)relevance of Metformin Treatment in Patients with Metastatic Pancreatic Cancer: An Open-Label, Randomized Phase II Trial

PURPOSE

We aimed to assess the safety and efficacy of metformin for treating patients with metastatic pancreatic cancer and to identify endocrine and metabolic phenotypic features or tumor molecular markers associated with sensitivity to metformin antineoplastic action.

EXPERIMENTAL DESIGN

We designed an open-label, randomized, phase II trial to assess the efficacy of adding metformin to a standard systemic therapy with cisplatin, epirubicin, capecitabine, and gemcitabine (PEXG) in patients with metastatic pancreatic cancer. Patients ages 18 years or older with metastatic pancreatic cancer were randomly assigned (1:1) to receive PEXG every 4 weeks in combination or not with 2 g oral metformin daily. The primary endpoint was 6-months progression-free survival (PFS-6) in the intention-to-treat population.

RESULTS

Between August 2010 and January 2014, we randomly assigned 60 patients to receive PEXG with (n = 31) or without metformin (n = 29). At the preplanned interim analysis, the study was ended for futility. PFS-6 was 52% [95% confidence interval (CI), 33-69] in the control group and 42% (95% CI, 24-59) in the metformin group (P = 0.61). Furthermore, there was no difference in disease-free survival and overall survival between groups. Despite endocrine metabolic modifications induced by metformin, there was no correlation with the outcome. Single-nucleotide polymorphism rs11212617 predicted glycemic response, but not tumor response to metformin. Gene expression on tumor tissue did not predict tumor response to metformin.

CONCLUSIONS

Addition of metformin at the dose commonly used in diabetes did not improve outcome in patients with metastatic pancreatic cancer treated with standard systemic therapy. See related commentary by Yang and Rustgi, p. 1031.

Inhibition of tumor energy pathways for targeted esophagus cancer therapy

Interest in targeting cancer metabolism has been renewed in recent years with the discovery that many cancer related pathways have a profound effect on metabolism and that many tumors become dependent on specific metabolic processes. Accelerated glucose uptake during anaerobic glycolysis and loss of regulation between glycolytic metabolism and respiration, are the major metabolic changes found in malignant cells. The non-metabolizable glucose analog, 2-deoxy-D-glucose inhibits glucose synthesis and adenosine triphosphate production. The adenosine monophosphate-activated protein kinase (AMPK) is a key sensor of cellular energy and AMPK is a potential target for cancer prevention and/or treatment. Metformin is an activator of AMPK which inhibits protein synthesis and gluconeogenesis during cellular stress. This article reviews the status of clinical and laboratory researches exploring targeted therapies via metabolic pathways for treatment of esophageal cancer.

IL-1B rs1143623 and EEF1A1P11-RPL7P9 rs10783050 polymorphisms affect the glucose-lowing efficacy of metformin in Chinese overweight or obese Type 2 diabetes mellitus patients

Aim: To investigate the potential genetic effect on metformin efficacy in overweight or obese Chinese Type 2 diabetes mellitus (T2DM) patients. Patients & methods: 768 SNPs in or close to 207 genes were genotyped in 84 patients treated with metformin + glibenclamide/Xiaoke Pill. Significant SNPs were then verified in 107 recent-onset overweight or obese T2DM patients treated with metformin alone. Genotyping was done by Illumina GoldenGate Assay. Results: In the discovery stage, 22 SNPs were nominally significant. IL1B rs1143623 (p = 0.011) and EEF1A1P11-RPL7P9 rs10783050 (p = 0.021) were still significantly associated with the relative change of HbA1c in the replication stage. Conclusion: IL1B rs1143623 and EEF1A1P11-RPL7P9 rs10783050 polymorphisms may contribute to metformin's glucose-lowing efficacy in overweight or obese Chinese T2DM patients.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND)

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10^-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10^-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Type 2 diabetes is the most common cause of severe kidney disease worldwide and diabetic kidney disease (DKD) associates with premature death. Individuals of non-European ancestry have the highest burden of type 2 DKD; hence understanding the causes of DKD remains critical to reducing health disparities. Family studies demonstrate that genes regulate the onset and progression of DKD; however, identifying these genes has proven to be challenging. The Family Investigation of Diabetes and Nephropathy consortium (FIND) recruited a large multi-ethnic collection of individuals with type 2 diabetes with and without kidney disease in order to detect genes associated with DKD. FIND discovered and replicated a DKD-associated genetic locus on human chromosome 6q25.2 (rs955333) between the SCAF8 and CNKSR genes. Findings were supported by significantly different expression of genes in this region from kidney tissue of subjects with, versus without DKD. The present findings identify a novel kidney disease susceptibility locus in individuals with type 2 diabetes which is consistent across subjects of differing ancestries. In addition, FIND results provide a rich catalogue of genetic variation in DKD patients for future research on the genetic architecture regulating this common and devastating disease.

A Genome-wide Association Study Provides Evidence of Sex-specific Involvement of Chr1p35.1 (ZSCAN20-TLR12P) and Chr8p23.1 (HMGB1P46) With Diabetic Neuropathic Pain

Neuropathic pain is defined as pain arising as a direct consequence of a lesion or a disease affecting the somatosensory system and it affects around 1 in 4 diabetic patients in the UK. The purpose of this genome-wide association study (GWAS) was to identify genetic contributors to this disorder. Cases of neuropathic pain were defined as diabetic patients with a multiple prescription history of at least one of five drugs specifically indicated for the treatment of neuropathic pain. Controls were diabetic individuals who were not prescribed any of these drugs, nor amitriptyline, carbamazepine, or nortriptyline. Overall, 961 diabetic neuropathic pain cases and 3260 diabetic controls in the Genetics of Diabetes Audit and Research Tayside (GoDARTS) cohort were identified. We found a cluster in the Chr1p35.1 (ZSCAN20-TLR12P) with a lowest P value of 2.74 × 10(- 7) at rs71647933 in females and a cluster in the Chr8p23.1, next to HMGB1P46 with a lowest P value of 8.02 × 10(- 7) at rs6986153 in males. Sex-specific narrow sense heritability was higher in males (30.0%) than in females (14.7%). This GWAS on diabetic neuropathic pain provides evidence for the sex-specific involvement of Chr1p35.1 (ZSCAN20-TLR12P) and Chr8p23.1 (HMGB1P46) with the disorder, indicating the need for further research.

Preserved DNA Damage Checkpoint Pathway Protects against Complications in Long-Standing Type 1 Diabetes

The mechanisms underlying the development of complications in type 1 diabetes (T1D) are poorly understood. Disease modeling of induced pluripotent stem cells (iPSCs) from patients with longstanding T1D (disease duration ≥ 50 years) with severe (Medalist +C) or absent to mild complications (Medalist -C) revealed impaired growth, reprogramming, and differentiation in Medalist +C. Genomics and proteomics analyses suggested differential regulation of DNA damage checkpoint proteins favoring protection from cellular apoptosis in Medalist -C. In silico analyses showed altered expression patterns of DNA damage checkpoint factors among the Medalist groups to be targets of miR200, whose expression was significantly elevated in Medalist +C serum. Notably, neurons differentiated from Medalist +C iPSCs exhibited enhanced susceptibility to genotoxic stress that worsened upon miR200 overexpression. Furthermore, knockdown of miR200 in Medalist +C fibroblasts and iPSCs rescued checkpoint protein expression and reduced DNA damage. We propose miR200-regulated DNA damage checkpoint pathway as a potential therapeutic target for treating complications of diabetes.

Genetic variants of OCT1 influence glycemic response to metformin in Han Chinese patients with type-2 diabetes mellitus in Shanghai

AIMS/HYPOTHESIS

Genetic variation in OCT1 can influence the glycemic response to metformin. We evaluated the effects of the OCT1 single-nucleotide polymorphisms (SNPs), rs1867351, rs4709400, rs628031, and rs2297374, on metformin efficacy in type-2 diabetes mellitus (DM) patients.

METHODS

We performed a single-center prospective analysis of the distributions of these SNPs in a cohort of Han Chinese subjects in Shanghai, China (HCS), and evaluated the effects of each SNP on glycemic control in HCS DM patients following 3 months of incident metformin treatment.

RESULTS

The allele frequencies of rs4709400 and rs628031 in our HCS control group differed from those previously reported for Han Chinese subjects in Beijing (HCB), as well as those previously reported for Caucasians and Africans, whereas the allele frequencies of rs1867351 and rs2297374 were more similar to those in HCB subjects. The DM patients with the rs1867351 T/T or rs4709400 G/G genotype exhibited greater reductions in postprandial plasma glucose (PPG), compared to those with different genotypes of these SNPs. The DM patients with the rs2297374 C/T, rs4709400 G/G, or rs628031 G/G genotype exhibited greater reductions in fasting plasma glucose (FPG), and those with the rs1867351 T/T, rs628031 A/A, or rs2297374 C/T genotype exhibited greater reductions in HbA1c , compared to those with different genotypes of these SNPs. Conclusions /interpretation: The rs1867351, rs4709400, rs628031, and rs2297374 SNPs of OCT1 have selective effects on FPG, PPG, and HbA1c in HCS DM patients in response to metformin treatment. Future studies of these SNPs in larger samples of HCS DM patients are warranted.

Genetics of drug response in type 2 diabetes

The introduction of several new drug groups into the treatment of type 2 diabetes in the past few decades leads to an increased requirement for an individualized treatment approach. A personalized treatment is important from the point of view of both efficacy and safety. Recent guidelines are based mainly on entirely phenotypic characteristics such as diabetes duration, presence of macrovascular complications, or risk of hypoglycemia with the use of individual drugs. So far, genetic knowledge is used to guide treatment in the monogenic forms of diabetes. With the accumulating pharmacogenetic evidence in type 2 diabetes, there are reasonable expectations that genetics might help in the adjustment of drug doses to reduce severe side effects, as well as to make better therapeutic choices among the drugs available for the treatment of diabetes.

Genetics of Type 2 Diabetes and Clinical Utility

A large proportion of heritability of type 2 diabetes (T2D) has been attributed to inherent genetics. Recent genetic studies, especially genome-wide association studies (GWAS), have identified a multitude of variants associated with T2D. It is thus reasonable to question if these findings may be utilized in a clinical setting. Here we briefly review the identification of risk loci for T2D and discuss recent efforts and propose future work to utilize these loci in clinical setting-for the identification of individuals who are at particularly high risks of developing T2D and for the stratification of specific health-care approaches for those who would benefit most from such interventions.

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

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