The role of clinical response to metformin in patients newly diagnosed with type 2 diabetes: a monotherapy study

Gut microbiome encoded purine and amino acid pathways present prospective biomarkers for predicting metformin therapy efficacy in newly diagnosed T2D patients

Metformin is widely used for treating type 2 diabetes mellitus (T2D). However, the efficacy of metformin monotherapy is highly variable within the human population. Understanding the potential indirect or synergistic effects of metformin on gut microbiota composition and encoded functions could potentially offer new insights into predicting treatment efficacy and designing more personalized treatments in the future. We combined targeted metabolomics and metagenomic profiling of gut microbiomes in newly diagnosed T2D patients before and after metformin therapy to identify potential pre-treatment biomarkers and functional signatures for metformin efficacy and induced changes in metformin therapy responders. Our sequencing data were largely corroborated by our metabolic profiling and identified that pre-treatment enrichment of gut microbial functions encoding purine degradation and glutamate biosynthesis was associated with good therapy response. Furthermore, we identified changes in glutamine-associated amino acid (arginine, ornithine, putrescine) metabolism that characterize differences in metformin efficacy before and after the therapy. Moreover, metformin Responders' microbiota displayed a shifted balance between bacterial lipidA synthesis and degradation as well as alterations in glutamate-dependent metabolism of N-acetyl-galactosamine and its derivatives (e.g. CMP-pseudaminate) which suggest potential modulation of bacterial cell walls and human gut barrier, thus mediating changes in microbiome composition. Together, our data suggest that glutamine and associated amino acid metabolism as well as purine degradation products may potentially condition metformin activity via its multiple effects on microbiome functional composition and therefore serve as important biomarkers for predicting metformin efficacy.

Association of Met420del Variant of Metformin Transporter Gene SLC22A1 with Metformin Treatment Response in Ethiopian Patients with Type 2 Diabetes

Objective

This study aimed to evaluate whether the M420del variants of SLC22A1 (rs72552763) is associated with metformin treatment response in Ethiopian patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

A prospective observational cohort study was conducted on 86 patients with T2DM who had been receiving metformin monotherapy for <1 year. Patients showing ≥0.5% reduction in HbA1c levels from baseline within 3 months and remained low for at least another 3 months were defined as responders while those patients with <0.5% reduction in HbA1c levels and/or those whom started a new class of glucose-lowering drug(s) because of unsatisfactory reduction were defined as non-responders. In addition, good glycemic control was observed when HbA1c ≤7.0%, and the above values were regarded as poor. Genotyping of rs72552763 SNP was performed using TaqMan® Drug Metabolism Enzyme Genotyping Assay and its association with metformin response and glycemic control were assessed by measuring the change in HbA1c and fasting blood glucose levels using Chi-square, logistic regression and Mann-Whitney U-test. Statistical significance was set at p <0.05.

Results

The minor allele frequency of the rs72552763 SNP of SLC22A1 was 9.3%. Metformin response was significantly higher in deletion_GAT (del_G) genotypes as compared to the wild-type GAT_GAT (G_G) genotypes. Furthermore, a significantly lower median treatment HbA1 level was found in del_G genotypes as compared to G_G genotypes. However, the association of rs72552763 with metformin response was not replicated at the allele level. In contrast, the minor del_allele was significantly associated with good glycemic control compared to the G_allele, though not replicated at del_G genotypes level.

Conclusion

This study demonstrated that metformin response was significantly higher in study participants with a heterozygous carrier of M420del variants of SLC22A1 as compared to the wild-type G_G genotypes after 3 months of treatment.

Association between organic cation transporter genetic polymorphisms and metformin response and intolerance in T2DM individuals: a systematic review and meta-analysis

Background

Variants in organic cation transporter (OCT) genes play a crucial role in metformin pharmacokinetics and are critical for diabetes treatment. However, studies investigating the effect of OCT genetic polymorphisms on metformin response have reported inconsistent results. This review and meta-analysis aimed to evaluate the associations between OCT genetic polymorphisms and metformin response and intolerance in individuals with type 2 diabetes mellitus (T2DM).

Method

A systematic search was conducted on PubMed, EMBASE, CNKI, WANFANG DATA, and VIP database for identifying potential studies up to 10 November 2022. The Q-Genie tool was used to evaluate the quality of included studies. Pooled odds ratios (OR) or standardized mean differences (SMD) and 95% confidence intervals (95% CI) were calculated to determine the associations between OCT genetic polymorphisms and metformin response and intolerance that were reflected by glycemic response indexes, such as glycated hemoglobin level (HbA1c%) or change in glycated hemoglobin level (ΔHbA1c%), fasting plasma level (FPG) or change in fasting plasma glucose level (ΔFPG), the effectiveness rate of metformin treatment, and the rate of metformin intolerance. A qualitative review was performed for the variants identified just in one study and those that could not undergo pooling analysis.

Results

A total of 30 related eligible studies about OCT genes (SLC22A1, SLC22A2, and SLC22A3) and metformin pharmacogenetics were identified, and 14, 3, and 6 single nucleotide polymorphisms (SNPs) in SLC22A1, SLC22A2, and SLC22A3, respectively, were investigated. Meta-analysis showed that the SLC22A1 rs622342 polymorphism was associated with a reduction in HbA1c level (AA vs. AC: SMD [95% CI] = -0.45 [-0.73--0.18]; p = 0.001). The GG genotype of the SLC22A1 rs628031 polymorphism was associated with a reduction in FPG level (GG vs. AA: SMD [95 %CI] = -0.60 [-1.04-0.16], p = 0.007; GG vs. AG: -0.45 [-0.67-0.20], p < 0.001). No statistical association was found between the remaining variants and metformin response and intolerance.

Conclusion

SLC22A1 rs622342 and rs628031 polymorphisms were potentially associated with glycemic response to metformin. This evidence may provide novel insight into gene-oriented personalized medicine for diabetes.

Sauver JL, Shah P, Vella A, Ryu E, Liu H, Marshall GD, Cerhan JR, Singh D, Summers RL. Predictors of Metformin Failure: Repurposing Electronic Health Record Data to Identify High-Risk Patients

CONTEXT

Metformin is the first-line drug for treating diabetes but has a high failure rate.

OBJECTIVE

To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure.

METHODS

A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure.

RESULTS

In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001).

CONCLUSION

Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.

The influence of metformin transporter gene SLC22A1 and SLC47A1 variants on steady-state pharmacokinetics and glycemic response

Interindividual variation is important in the response to metformin as the first-line therapy for type-2 diabetes mellitus (T2DM). Considering that OCT1 and MATE1 transporters determine the metformin pharmacokinetics, this study aimed to investigate the influence of SLC22A1 and SLC47A1 variants on the steady-state pharmacokinetics of metformin and the glycemic response. This research used the prospective-cohort study design for 81 patients with T2DM who received 500 mg metformin twice a day from six primary healthcare centers. SLC22A1 rs628031 A>G (Met408Val) and Met420del genetic variants in OCT1 as well as SLC47A1 rs2289669 G>A genetic variant in MATE1 were examined through the PCR-RFLP method. The bioanalysis of plasma metformin was performed in the validated reversed-phase HPLC-UV detector. The metformin steady-state concentration was measured for the trough concentration (Cssmin) and peak concentration (Cssmax). The pharmacodynamic parameters of metformin use were the fasting blood glucose (FBG) and glycated albumin (GA). Only SLC22A1 Met420del alongside estimated-glomerular filtration rate (eGFR) affected both Cssmax and Cssmin with an extremely weak correlation. Meanwhile, SLC47A1 rs2289669 and FBG were correlated. This study also found that there was no correlation between the three SNPs studied and GA, so only eGFR and Cssmax influenced GA. The average Cssmax in patients with the G allele of SLC22A1 Met408Val, reaching 1.35-fold higher than those with the A allele, requires further studies with regard to metformin safe dose in order to avoid exceeding the recommended therapeutic range.

Role of human organic cation transporter-1 (OCT-1/SLC22A1) in modulating the response to metformin in patients with type 2 diabetes

BACKGROUND

Organic cation transporter 1 primarily governs the action of metformin in the liver. There are considerable inter-individual variations in metformin response. In light of this, it is crucial to obtain a greater understanding of the influence of OCT1 expression or polymorphism in the context of variable responses elicited by metformin treatment.

RESULTS

We observed that the variable response to metformin in the responders and non-responders is independent of isoform variation and mRNA expression of OCT-1. We also observed an insignificant difference in the serum metformin levels of the patient groups. Further, molecular docking provided us with an insight into the hotspot regions of OCT-1 for metformin binding. Genotyping of these regions revealed SNPs 156T>C and 1222A>G in both the groups, while as 181C>T and 1201G>A were found only in non-responders. The 181T>C and 1222A>G changes were further found to alter OCT-1 structure in silico and affect metformin transport in vitro which was illustrated by their effect on the activation of AMPK, the marker for metformin activity.

CONCLUSION

Taken together, our results corroborate the role of OCT-1 in the transport of metformin and also point at OCT1 genetic variations possibly affecting the transport of metformin into the cells and hence its subsequent action in responders and non-responders.

Multi-omics profiling: the way towards precision medicine in metabolic diseases

Metabolic diseases including type 2 diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and metabolic syndrome (MetS) are alarming health burdens around the world, while therapies for these diseases are far from satisfying as their etiologies are not completely clear yet. T2DM, NAFLD, and MetS are all complex and multifactorial metabolic disorders based on the interactions between genetics and environment. Omics studies such as genetics, transcriptomics, epigenetics, proteomics, and metabolomics are all promising approaches in accurately characterizing these diseases. And the most effective treatments for individuals can be achieved via omics pathways, which is the theme of precision medicine. In this review, we summarized the multi-omics studies of T2DM, NAFLD, and MetS in recent years, provided a theoretical basis for their pathogenesis and the effective prevention and treatment, and highlighted the biomarkers and future strategies for precision medicine.

Diffusion Mechanism Modeling of Metformin in Human Organic Cationic Amino Acid Transporter one and Functional Impact of S189L, R206C, and G401S Mutation

Metformin used as a first-line drug to treat Type 2 Diabetes Mellitus is transported via organic cation channels to soft tissues. Mutations in the SLC22A1 gene, such as Gly401Ser, Ser189Leu, and Arg206Cys, may affect the drug’s therapeutic effect on these patients. This study aims at proposing a potential structural model for drug interactions with the hOCT1 transporter, as well as the impact of these mutations at both topological and electronic structure levels on the channel’s surface, from a chemical point of view with, in addition to exploring the frequency distribution. To chemically understand metformin diffusion, we used an open model from the protein model database, with ID PM0080367, viewed through UCSF Chimera. The effect of the mutations was assessed using computational hybrid Quantum Mechanics/Molecular Mechanics, based on the Austin Model 1 semi-empirical method using Spartan 18’ software. The results demonstrate coupling energy for metformin with amino acids F, W, H and Y, because of the interaction between the metformin dication and the electron cloud of π orbitals. The mutations analyzed showed changes in the chemical polarity and topology of the structure. The proposed diffusion model is a possible approach to the interaction mechanism between metformin and its transporter, as well as the impacts of variants, suggesting structural changes in the action of the drug. Metformin efficacy considerably varies from one patient to another; this may be largely attributed to the presence of mutations on the SLC22A1 gene. This study aims at proposing a potential structural model for metformin-hOCT1 (SLC22A1) transporter interaction, as well as the identification of the effect of mutations G401S (rs34130495), S189L (rs34104736), and R206C (616C > T) of the SLC22A1 gene at the topological and electronic structure levels on the channel surfaces, from a chemical viewpoint. Our results demonstrated that the coupling energies for metformin with aromatic amino acids F, W, H and Y, because of the interaction between the metformin dication and the electron cloud of π orbitals. Changes in the chemical environment’s polarity and the structure’s topology were reported in the mutations assessed. The diffusion model proposed is a potential approach for the mechanism of interaction of metformin with its transporter and the effects of variants on the efficacy of the drug in the treatment of type 2 diabetes. The assessment of the frequency of these mutations in a sample of Colombian type 2 diabetes patients suggests that different SLC22A1 gene variants might be involved in reduced OCT1 activity in the Colombian population since none of these mutations were detected.

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.

Allele Frequency of SLC22A1 Met420del Metformin Main Transporter Encoding Gene among Javanese-Indonesian Population

BACKGROUND

Genetic variation in the genes that encode metformin transporters has been proven to cause pharmacokinetic variability and various glycemic response to metformin. Organic Cation Transporter (OCT) 1 protein encoded by the SLC22A1 gene is primarily responsible for the process of metformin influx to the hepatocytes as the target of antihyperglycemic action as well as metformin elimination through the renal. This study aimed to determine the allele frequency distribution of the SLC22A1 Met420del gene in OCT1 among the Javanese population, the largest ethnic group in Indonesia with T2DM.

METHODS

The research involved 100 adult patients from 9 healthcare facilities in Yogyakarta Province. The PCR-RFLP method was employed as a genotype analysis to detect polymorphism using 5'-AGGTTCACGGACTCTGTGCT-3' forward primer and 5'-AAGCTGGAGTGTGCGATCT-3' reverse primer.

RESULTS

No AA variant (wild type) type was found in the SLC22A1 Met420del gene, and only 4% of the subjects had Aa heterozygote type. The allele frequencies of A and a were 2.0% and 98.0% in all subjects, respectively.

CONCLUSION

The allele frequencies in the Javanese-Indonesian population were almost the same as those in the studies involving Japanese, Chinese-Han, and Asian-American populations. This study recommends further research on the correlation between the influence of methionine deletion at codon 420 on the variability of pharmacokinetic profiles and the glycemic response to metformin as well as the incidence of gastrointestinal intolerance due to metformin administration.

Precision Diabetes Is Slowly Becoming a Reality

The concept of precision medicine is becoming increasingly popular. The use of big data, genomics and other "omics" like metabolomics, proteomics and transcriptomics could make the dream of personalised medicine become a reality in the near future. As far as polygenic forms of diabetes like type 2 and type 1 diabetes are concerned, interesting leads are emerging, but precision diabetes is still in its infancy. However, with regard to monogenic forms of diabetes like maturity-onset diabetes of the young and neonatal diabetes mellitus, rapid strides have been made and precision diabetes has already become part of the clinical tools used at advanced diabetes centres. In patients with some monogenic form of diabetes, if the appropriate gene defects are identified, insulin injections can be stopped and be replaced by oral sulphonylurea drugs. In the coming years, rapid advances can be expected in the field of precision diabetes, thereby making the control of diabetes more effective and hopefully leading to prevention of its complications and improvement of the quality of life of people afflicted with diabetes.

Genetic polymorphisms of organic cation transporter 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes: A systematic review

BACKGROUND

Metformin is one of the most commonly used drugs for the treatment of type 2 diabetes mellitus (T2DM). Despite its widespread use, there are considerable interindividual variations in metformin response, with about 35% of patients failing to achieve initial glycemic control. These variabilities that reflect phenotypic differences in drug disposition and action may indeed be due to polymorphisms in genes that regulate pharmacokinetics and pharmacodynamics of metformin. Moreover, interethnic differences in drug responses in some cases correspond to substantial differences in the frequencies of the associated pharmacogenomics risk allele.

AIM

This study aims to highlight and summarize the overall effects of organic cation transporter 1(OCT1) polymorphisms on therapeutic responses to metformin and to evaluate the potential role of such polymorphisms in interethnic differences in metformin therapy.

METHODS

We conducted a systematic review according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. We searched for PubMed/MEDLINE, Embase, and CINAHL, relevant studies reporting the effects of OCT1 polymorphisms on metformin therapy in T2DM individuals. Data were extracted on study design, population characteristics, relevant polymorphisms, measure of genetic association, and outcomes. The presence of gastrointestinal side effects, glycated hemoglobin A1 (HbA1c) levels, fasting plasma glucose (FPG), and postprandial plasma glucose (PPG) concentrations after treatment with metformin were chosen as measures of the metformin responses. This systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO).

RESULTS

According to the data extracted, a total of 34 OCT1 polymorphisms were identified in 10 ethnic groups. Significant differences in the frequencies of common alleles were observed among these groups. Met408Val (rs628031) variant was the most extensively explored with metformin responses. Although some genotypes and alleles have been associated with deleterious effects on metformin response, others indeed, exhibited positive effects.

CONCLUSION

Genetic effects of OCT1 polymorphisms on metformin responses were population specific. Further investigations in other populations are required to set ethnicity-specific reference for metformin responses and to obtain a solid basis to design personalized therapeutic approaches for T2DM treatment.

Diabetes in China: Epidemiology and Genetic Risk Factors and Their Clinical Utility in Personalized Medication

The incidence of type 2 diabetes (T2D) has rapidly increased over recent decades, and T2D has become a leading public health challenge in China. Compared with European descents, Chinese patients with T2D are diagnosed at a relatively young age and low BMI. A better understanding of the factors contributing to the diabetes epidemic is crucial for determining future prevention and intervention programs. In addition to environmental factors, genetic factors contribute substantially to the development of T2D. To date, more than 100 susceptibility loci for T2D have been identified. Individually, most T2D genetic variants have a small effect size (10-20% increased risk for T2D per risk allele); however, a genetic risk score that combines multiple T2D loci could be used to predict the risk of T2D and to identify individuals who are at a high risk. Furthermore, individualized antidiabetes treatment should be a top priority to prevent complications and mortality. In this article, we review the epidemiological trends and recent progress in the understanding of T2D genetic etiology and further discuss personalized medicine involved in the treatment of T2D.

Polymorphic Variants rs3088442 and rs2292334 in the Organic Cation Transporter 3 (OCT3) Gene and Susceptibility Against Type 2 Diabetes: Role of their Interaction

AIMS

In this study, we investigated whether two common variants (rs3088442G>A and rs2292334G>A) in the organic cation transporter 3 (OCT3) gene, a high-capacity transporter widely expressed in various tissues, affect susceptibility to type 2 diabetes (T2D) in patients newly diagnosed with T2D.

METHODS

We performed a study with 150 newly diagnosed patients with T2D and 152 controls. The genetic analyses were performed using the restricted fragment length polymorphism (RFLP) after PCR amplification.

RESULTS

For the rs3088442G>A variant, A allele carriers had a significantly lower odds ratio (OR) vs. GG homozygotes in the BMI <30 kg/m² group (OR = 0.23, p <0.001) compared with the BMI ≥30 kg/m² group (OR = 0.67, p = 0.34). When ORs were adjusted for BMI, age, sex, and blood pressure, our findings showed that the overexpression of the A allele of the rs3088442G>A variant was associated with a decreased risk of T2D (OR = 0.016, p <0.001). A Bayesian logistic model revealed that the interaction of two variants studied were significantly associated with a decreased risk of T2D (OR = 0.61, p = 0.03).

CONCLUSIONS

The present study has identified the protective effect of the variant rs3088442G>A in the 3'-untranslated region of the OCT3 gene in susceptibility to T2D, and that the protective role is maintained in the presence of risky alleles of the variant rs2292334G>A. The association of the A allele of rs3088442G>A with T2D become weaker in obese people than that of non-obese. If confirmed in other populations, the rs3088442G>A variant as a genetic marker may potentially assist in the identification of individuals at an increased risk of T2D.

Association between the synonymous variant organic cation transporter 3 (OCT3)-1233G>A and the glycemic response following metformin therapy in patients with type 2 diabetes

OBJECTIVES

Organic cation transporter 3 (OCT3) as a high-capacity transporter contribute to the metabolism of metformin. The present study was conducted to determine the genotype frequencies of the variant OCT3-1233G>A (rs2292334) in patients with newly diagnosed type 2 diabetes (T2D) and its relationship with response to metformin.

MATERIALS AND METHODS

This study included 150 patients with T2D who were classified into two groups following three months of metformin therapy: responders (by more than 1% reduction in HbA1c from baseline) and nonresponders (less than 1% reduction in HbA1c from baseline). PCR-based restriction fragment length polymorphism (RFLP) served to genotype OCT3-564G>A variant.

RESULTS

The parameters such as HbA1c (P<0.001) and BMI (P<0.001) in both patients with GA + AA genotype and GG genotype decreased significantly following 3 months of metformin therapy compared with baseline. The mean reduction in HbA1c levels following 3 months was higher in patients with the A allele (0.77% reduction from baseline) than in those with the homozygous G allele (0.54% reduction from baseline). Also, in GA + AA genotypes compared with GG genotypes, the mean reduction in HbA1c values from baseline was 0.34% for responders and 0.14% for non-responders.

CONCLUSION

Considering the roles of genetic variations in the function of metformin transporters, the effect of variations such as 1233G>A in the OCT3, which is a high-capacity transporter widely expressed in various tissues cannot be ignored. Comparing the allele frequencies of OCT3-1233G>A variant in our study and different ethnic populations confirm that the variant is a highly polymorphic variant.

STK11 rs2075604 Polymorphism Is Associated with Metformin Efficacy in Chinese Type 2 Diabetes Mellitus

Metformin is a classical oral antidiabetic drug, often recommended to be the first-choice treatment of type 2 diabetes mellitus (T2DM). Based on the previous research on STK11 and diabetes, we aimed to investigate the distributive characteristic of STK11 rs2075604 polymorphism and the potential influence of STK11 rs2075604 polymorphism on metformin efficacy among Chinese T2DM patients. There was no significant difference between T2DM patients (G = 64.8%, T = 35.2%) and healthy subjects (G = 62.7%, T = 37.2%) in STK11 rs2075604 genotype and allele frequencies. After 12 weeks of treatment, 62 patients were defined as the responders and 32 patients as nonresponders according to the decrease of HbA1c level. And the GT + TT genotype in STK11 rs2075604 can decrease HbA1c level more significantly than the GG genotype. Furthermore, the allele frequency of T in the STK11 rs2075604 was higher in the responders than the nonresponders (43.55% versus 26.56%). The T allele in the STK11 rs2075604 had a 2.133 times great chance of responding to metformin treatment. In conclusion, this study suggested that the STK11 rs2075604 genetic polymorphism was significantly associated with metformin efficacy in Chinese T2DM patients and the carriers of the T allele may gain a better therapeutic metformin efficacy compared with the G allele. This trial is registered with clinical study registration number NCT03155087.

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.

Allele frequency and genotype distribution of a common variant in the 3´-untranslated region of the SLC22A3 gene in patients with type 2 diabetes: Association with response to metformin

Background:

Organic cation transporter 3 (OCT3) is an excellent transporter for metformin, which is used as first-line therapy for type 2 diabetes (T2D). OCT3 genetic variants may influence the clinical response to metformin. This study aimed to determine the genotype and allele frequency of OCT3-564G>A (rs3088442) variant and its role in the glycemic response to metformin in patients with newly diagnosed T2D.

Materials and Methods:

Based on the response to metformin, 150 patients were classified into two groups: Sixty-nine responders (decrease in glycated hemoglobin [HbA1c] values by more than 1% from the baseline) and 81 nonresponders (decrease in HbA1c values <1% from the baseline). HbA1c levels were determined by chromatography. The variant OCT3-564G>A was genotyped using polymerase chain reaction - based restriction fragment length polymorphism.

Results:

The genotypes frequencies were 51.3% GG, 36% AG, and 12.7% AA. Allele frequency of major allele (G) and minor allele (A) in OCT3-564G>A variant was found to be 0.69 and 0.31, respectively. Fasting glucose, HbA1c, body mass index, and lipid profile in both GG genotypes and GA + AA group decreased significantly after 3 months of metformin therapy compared with baseline (P < 0.05). In both responders and nonresponders, HbA1c and fasting glucose levels were lower in patients with the GA + AA genotype than in those with the GG genotype; however, the differences were not statistically significant (P > 0.05).

Conclusion:

The A allele frequency (which may be a protective allele against coronary heart disease) in the Iranian diabetic patients was lower than Iranian, Caucasian and Japanese healthy populations. Metformin is useful in improving the lipid profile, in addition to its impacts in glycemic control, and these effects are regardless of OCT3-564G>A variant.

The Role of Metformin Response in Lipid Metabolism in Patients with Recent-Onset Type 2 Diabetes: HbA1c Level as a Criterion for Designating Patients as Responders or Nonresponders to Metformin

Background

In this study, we investigated whether response to metformin, the most frequently drug for diabetes treatment, influences the therapeutic effects of antilipidemic medication in newly diagnosed patients with type 2 diabetes mellitus (T2DM).

Methods

A total of 150 patients with T2DM were classified into two groups following 3 months of metformin therapy (1000 mg twice daily): responders (patients showing ≥1% reduction in HbA1c from baseline) and nonresponders (patients showing <1% reduction in HbA1c from baseline). The patients received atorvastatin 20 mg, gemfibrozil 300 mg, or atorvastatin 20 mg and gemfibrozil 300 mg daily.

Principal Findings

HbA1c and fasting glucose levels were significantly different between baseline and 3 months among responders receiving atorvastatin; however, these differences were not statistically significant in nonresponders. Atherogenic ratios of low-density lipoprotein cholesterol to high-density lipoprotein cholesterol (LDL-C/HDL-C; p = 0.002), total cholesterol to HDL-C (TC/HDL-C; p<0.001) and AIP (the atherogenic index of plasma; p = 0.004) decreased significantly in responders receiving atorvastatin than in nonresponders. Moreover, responders receiving atorvastatin showed a significant increase in HDL-C levels but nonresponders receiving atorvastatin did not (p = 0.007). The multivariate model identified a significant association between metformin response (as the independent variable) and TG, TC, HDL-C and LDL-C (dependent variables; Wilk's λ = 0.927, p = 0.036).

Conclusions

Metformin response affects therapeutic outcomes of atorvastatin on atherogenic lipid markers in patients newly diagnosed with T2DM. Metformin has a greater impact on BMI in responders of metformin compared to nonresponders. Adoption of better therapeutic strategies for reducing atherogenic lipid markers may be necessary for metformin nonresponders.

Drug Transporters and Na+/H+ Exchange Regulatory Factor PSD-95/Drosophila Discs Large/ZO-1 Proteins

Drug transporters govern the absorption, distribution, and elimination of pharmacologically active compounds. Members of the solute carrier and ATP binding-cassette drug transporter family mediate cellular drug uptake and efflux processes, thereby coordinating the vectorial movement of drugs across epithelial barriers. To exert their physiologic and pharmacological function in polarized epithelia, drug transporters must be targeted and stabilized to appropriate regions of the cell membrane (i.e., apical versus basolateral). Despite the critical importance of drug transporter membrane targeting, the mechanisms that underlie these processes are largely unknown. Several clinically significant drug transporters possess a recognition sequence that binds to PSD-95/Drosophila discs large/ZO-1 (PDZ) proteins. PDZ proteins, such as the Na(+)/H(+) exchanger regulatory factor (NHERF) family, act to stabilize and organize membrane targeting of multiple transmembrane proteins, including many clinically relevant drug transporters. These PDZ proteins are normally abundant at apical membranes, where they tether membrane-delimited transporters. NHERF expression is particularly high at the apical membrane in polarized tissue such as intestinal, hepatic, and renal epithelia, tissues important to drug disposition. Several recent studies have highlighted NHERF proteins as determinants of drug transporter function secondary to their role in controlling membrane abundance and localization. Mounting evidence strongly suggests that NHERF proteins may have clinically significant roles in pharmacokinetics and pharmacodynamics of several pharmacologically active compounds and may affect drug action in cancer and chronic kidney disease. For these reasons, NHERF proteins represent a novel class of post-translational mediators of drug transport and novel targets for new drug development.

The variant organic cation transporter 2 (OCT2)-T201M contribute to changes in insulin resistance in patients with type 2 diabetes treated with metformin

AIMS

Insulin resistance is characterized by impaired biological response of peripheral tissues to the metabolic effects of insulin. Organic cation transporter 2 (OCT2) is responsible for 80% metformin clearance. Limited information is available on the potential relationship between genetic variants of OCT2 and insulin resistance. In this study, we examined the role of OCT2-T201M (602 C>T) variant in insulin resistance in patients with type 2 diabetes (T2D) who were treated with metformin.

METHODS

Serum concentrations of insulin and C-peptide were assessed using ELISA. Homeostasis model assessment for insulin resistance (HOMA-IR) and HOMA for beta cell function (HOMA-BCF) were determined. PCR-based restriction fragment length polymorphism was used to genotype the OCT2-T201M variant.

RESULTS

Patients with minor alleles had higher HbA1c concentrations (p=0.019), fasting glucose levels (p=0.023), HOMA-IR (p=0.03), and HOMA-BCF (p=0.26) than patients with common alleles. Multivariate analysis identified a significant association between the variables OCT2-T201M and gender, with HOMA-IR and HOMA-BCF (Wilks' λ=0.549, F=12.71, p<0.001 for OCT2-T201M and Wilks' λ=0.369, F=26.46, p<0.001 for gender. Changes in HOMA-BCF were inversely correlated with changes in fasting glucose levels (r=-0.412, p=0.008) and HbA1c (r=-0.257, p=0.114).

CONCLUSIONS

Our findings suggest that the loss-of-function variant OCT2-T201M (rs145450955) contribute to changes in insulin resistance and beta cell activity in patients with T2D treated with metformin. Moreover, gender as an independent variable has a significant relationship with HOMA-BCF.