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

Genetic and Phenotypic Factors Affecting Glycemic Response to Metformin Therapy in Patients with Type 2 Diabetes Mellitus

Metformin is an oral hypoglycemic agent widely used in clinical practice for treatment of patients with type 2 diabetes mellitus (T2DM). The wide interindividual variability of response to metformin therapy was shown, and recently the impact of several genetic variants was reported. To assess the independent and combined effect of the genetic polymorphism on glycemic response to metformin, we performed an association analysis of the variants in ATM, SLC22A1, SLC47A1, and SLC2A2 genes with metformin response in 299 patients with T2DM. Likewise, the distribution of allele and genotype frequencies of the studied gene variants was analyzed in an extended group of patients with T2DM (n = 464) and a population group (n = 129). According to our results, one variant, rs12208357 in the SLC22A1 gene, had a significant impact on response to metformin in T2DM patients. Carriers of TT genotype and T allele had a lower response to metformin compared to carriers of CC/CT genotypes and C allele (p-value = 0.0246, p-value = 0.0059, respectively). To identify the parameters that had the greatest importance for the prediction of the therapy response to metformin, we next built a set of machine learning models, based on the various combinations of genetic and phenotypic characteristics. The model based on a set of four parameters, including gender, rs12208357 genotype, familial T2DM background, and waist–hip ratio (WHR) showed the highest prediction accuracy for the response to metformin therapy in patients with T2DM (AUC = 0.62 in cross-validation). Further pharmacogenetic studies may aid in the discovery of the fundamental mechanisms of type 2 diabetes, the identification of new drug targets, and finally, it could advance the development of personalized treatment.

Clinical perspectives and concerns of metformin as an anti-aging drug

As percentages of elderly people rise in many societies, age-related diseases have become more prevalent than ever. Research interests have been shifting to delaying age-related diseases by delaying or reversing aging itself. We use metformin as an entry point to talk about the important molecular and genetic longevity-regulating mechanisms that have been extensively studied with it. Then we review a number of observational studies, animal studies, and clinical trials to reflect the clinical potentials of the mechanisms in lifespan extension, cardiovascular diseases, tumors, and neurodegeneration. Finally, we highlight remaining concerns that are related to metformin and future anti-aging research.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

SLC22A1 rs622342 Polymorphism Predicts Insulin Resistance Improvement in Patients with Type 2 Diabetes Mellitus Treated with Metformin: A Cross-Sectional Study

BACKGROUND

Metformin is the most widely used oral antidiabetic agent and can reduce insulin resistance (IR) effectively. Organic cation transporter 1 (encoded by SLC22A1) is responsible for the transport of metformin, and ataxia-telangiectasia-mutated (ATM) is a gene relating to the DNA repair and cell cycle control. The aim of this study was to evaluate if the genetic variants in SLC22A1 rs622342 and ATM rs11212617 could be effective predictors of islet function improvement in patients with type 2 diabetes mellitus (T2DM) on metformin treatment.

METHODS

This cross-sectional study included 111 patients with T2DM treated with metformin. Genotyping was performed by the dideoxy chain-termination method. The homeostatic indexes of IR (HOMA-IR) and beta-cell function (HOMA-BCF) were determined according to the homeostasis model assessment.

RESULTS

Fasting plasma glucose (FPG) levels, HbA_1c levels, and HOMA-IR were significantly higher in patients with the rs622342 AA genotype than in those with C allele (P < 0.05). However, these significant differences were not observed between rs11212617 genotype groups. Further data analysis revealed that the association between the rs622342 polymorphism and HOMA-IR was gender related, and so was rs11212617 polymorphism and HOMA-BCF. HOMA-IR was significantly higher in males with rs622342 AA genotype than in those with C allele (P=0.021), and HOMA-BCF value was significantly higher in females carrying rs11212617 CC genotype than in those with A allele (P=0.038). The common logarithm (Lg10) of HOMA-BCF was positively correlated with the reciprocal of HbA_1c (r = 0.629, P < 0.001) and negatively associated with Lg10 FPG (r = -0.708, P < 0.001).

CONCLUSIONS

The variant of rs622342 could be a predictor of insulin sensitivity in patients with T2DM treated with metformin. The association between the rs622342 polymorphism and HOMA-IR and the association between the rs11212617 polymorphism and HOMA-BCF were both gender related.

SLC22A1 And ATM Genes Polymorphisms Are Associated With The Risk Of Type 2 Diabetes Mellitus In Western Saudi Arabia: A Case-Control Study

Introduction

Type 2 diabetes mellitus (T2DM) is a major global health problem that is progressively affected by genetic and environmental factors. The aim of this study is to determine the influence of solute carrier family 22 member 1 (SLC22A1) rs628031 and rs461473, and ataxia telangiectasia mutated (ATM) rs11212617 polymorphisms on the risk of T2DM in Saudi Arabia by considering many parameters associated with glycemic control of T2DM, such as body mass index (BMI), fasting blood glucose, glycated hemoglobin (HbA1c), and triglyceride.

Methods

In a case-control study, genomic DNA from controls and diabetic groups was isolated and genotyped for each single-nucleotide polymorphism.

Results

There were significant correlations between T2DM and both BMI and HbA1c. Significant associations between G/G and A/G genotypes of rs628031 and rs461473 variants of SLC22A1 and high levels of HbA1c were detected. Therefore, G was predicted to be the risk allele among the assessed SLC22A1 variants. A significant correlation was observed between A/A and A/C genotypes of the rs11212617 polymorphism of ATM and elevated HbA1c. Relative risk calculation confirmed A to be the risk allele in the T2DM population.

Conclusion

Our study showed the risk of the assessed SLC22A1 and ATM variants on glycemic control parameters in diabetic patients.

Tacrolimus troughs and genetic determinants of metabolism in kidney transplant recipients: A comparison of four ancestry groups

Tacrolimus trough and dose requirements vary dramatically between individuals of European and African American ancestry. These differences are less well described in other populations. We conducted an observational, prospective, multicenter study from which 2595 kidney transplant recipients of European, African, Native American, and Asian ancestry were studied for tacrolimus trough, doses, and genetic determinants of metabolism. We studied the well-known variants and conducted a CYP3A4/5 gene-wide analysis to identify new variants. Daily doses, and dose-normalized troughs were significantly different between the four groups (P < .001). CYP3A5*3 (rs776746) was associated with higher dose-normalized tacrolimus troughs in all groups but occurred at different allele frequencies and had differing effect sizes. The CYP3A5*6 (rs10264272) and *7 (rs413003343) variants were only present in African Americans. CYP3A4*22 (rs35599367) was not found in any of the Asian ancestry samples. We identified seven suggestive variants in the CYP3A4/5 genes associated with dose-normalized troughs in Native Americans (P = 1.1 × 10^-5 -8.8 × 10^-6 ) and one suggestive variant in Asian Americans (P = 5.6 × 10^-6 ). Tacrolimus daily doses and dose-normalized troughs vary significantly among different ancestry groups. We identified potential new variants important in Asians and Native Americans. Studies with larger populations should be conducted to assess the importance of the identified suggestive variants.

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

Pharmacogenetics of Metformin for Medication-Induced Weight Gain in Autism Spectrum Disorder

Objectives: We recently found that metformin attenuated weight gain due to mixed dopamine and serotonin receptor antagonists, commonly termed atypical antipsychotics, in children and adolescents with autism spectrum disorder (ASD). Previous studies have found that genetic variation predicts response to metformin in diabetes. In this study, we aimed to assess whether response to metformin for weight gain in this population is associated with variants in five genes previously implicated in metformin response in diabetes. Methods: Youth with ASD who experienced significant weight gain while taking mixed receptor antagonist medications were randomly assigned to metformin or placebo for 16 weeks, followed by open-label metformin treatment for 16 weeks. In the 53 participants with available DNA samples, we used a linear, mixed model analysis to assess response in the first 16 weeks of metformin treatment, whether in the randomized or open-label period, based upon genotypes at polymorphisms in five genes previously associated with metformin response in diabetes: ATM, SLC2A2, MATE1, MATE2, and OCT1. Results: In the primary analysis, both ATM and OCT1 showed significant effects of genotype on change in body mass index z-scores, the primary outcome measure, during the first 16 weeks of treatment with metformin. No other polymorphism showed a significant difference. Conclusion: As has been shown for metformin treatment in diabetes, genetic variation may predict response to metformin for weight gain in youth with ASD treated with mixed receptor antagonists. Further work is needed to replicate these findings and evaluate whether they can be used prospectively to improve outcomes.

Metformin transporter pharmacogenomics: insights into drug disposition-where are we now?

INTRODUCTION

Metformin is recommended as first-line treatment for type 2 diabetes (T2D) by all major diabetes guidelines. With appropriate usage it is safe and effective overall, but its efficacy and tolerability show considerable variation between individuals. It is a substrate for several drug transporters and polymorphisms in these transporter genes have shown effects on metformin pharmacokinetics and pharmacodynamics. Areas covered: This article provides a review of the current status of the influence of transporter pharmacogenomics on metformin efficacy and tolerability. The transporter variants identified to have an important influence on the absorption, distribution, and elimination of metformin, particularly those in organic cation transporter 1 (OCT1, gene SLC22A1), are reviewed. Expert opinion: Candidate gene studies have shown that genetic variations in SLC22A1 and other drug transporters influence the pharmacokinetics, glycemic responses, and gastrointestinal intolerance to metformin, although results are somewhat discordant. Conversely, genome-wide association studies of metformin response have identified signals in the pharmacodynamic pathways rather than the transporters involved in metformin disposition. Currently, pharmacogenomic testing to predict metformin response and tolerability may not have a clinical role, but with additional data from larger studies and availability of safe and effective alternative antidiabetic agents, this is likely to change.

A gene variant near ATM affects the response to metformin and metformin plasma levels: a post hoc analysis of an RCT

AIM

To determine the influence of polymorphisms on the effects of metformin on HbA1c, daily dose of insulin and metformin plasma concentration. Methods: In a post hoc analysis of a 4.3 year placebo-controlled randomized trial with 390 patients with Type 2 diabetes already on insulin, we analyzed the influence of polymorphisms in genes coding for ATM and the transporters OCT1 and MATE1. Outcome measures were a combined HbA1c + daily dose of insulin Z score and metformin plasma concentrations.

RESULTS

rs11212617 (ATM) was associated with an improved Z score and a lower metformin plasma concentration. In addition, the major allele of rs2289669 (MATE1) was also associated with an improved Z score.

CONCLUSION

The ATM SNP rs11212617 significantly affected the effect of metformin and metformin plasma concentration. Further research is needed to determine the clinical importance of these findings, in particular the effects on metformin plasma concentration.

Pharmacogenetics of Antidiabetic Drugs

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

Metformin Facilitates Amyloid-β Generation by β- and γ-Secretases via Autophagy Activation

The evidence of strong pathological associations between type 2 diabetes and Alzheimer's disease (AD) has increased in recent years. Contrary to suggestions that anti-diabetes drugs may have potential for treating AD, we demonstrate here that the insulin sensitizing anti-diabetes drug metformin (Glucophage®) increased the generation of amyloid-β (Aβ), one of the major pathological hallmarks of AD, by promoting β- and γ-secretase-mediated cleavage of amyloid-β protein precursor (AβPP) in SH-SY5Y cells. In addition, we show that metformin caused autophagosome accumulation in Tg6799 AD model mice. Extremely high γ-secretase activity was also detected in autophagic vacuoles, apparently a novel site of Aβ peptide generation. Together, these data suggest that metformin-induced accumulation of autophagosomes resulted in increased γ-secretase activity and Aβ generation. Additional experiments indicated that metformin increased phosphorylation of AMP-activated protein kinase, which activates autophagy by suppressing mammalian target of rapamycin (mTOR). The suppression of mTOR then induces the abnormal accumulation of autophagosomes. We conclude that metformin, an anti-diabetes drug, may exacerbate AD pathogenesis by promoting amyloidogenic AβPP processing in autophagosomes.

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.

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. 

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.