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

Effect of Metformin on Plasma Exposure of Rifampicin, Isoniazid, and Pyrazinamide in Patients on Treatment for Pulmonary Tuberculosis

BACKGROUND

To evaluate the effect of metformin on the plasma levels of rifampicin, isoniazid, and pyrazinamide in patients with drug-sensitive pulmonary tuberculosis being treated with first-line antituberculosis treatment (ATT) and to assess the influence of gene polymorphisms on the metabolic pathway of metformin and plasma levels of antitubercular drugs.

METHODS

Nondiabetic adults aged 18-60 years with pulmonary tuberculosis were randomized to either the standard ATT (ATT group) or ATT plus metformin (METRIF group) groups in a phase IIB clinical trial. An intensive pharmacokinetic study with blood collection at 0 hour (predosing), followed by 1, 2, 4, 6, 8, and 12 hours after dosing was conducted during the first month of treatment in a subset of 60 study participants after a minimum of 14 doses. Plasma concentrations of rifampicin, isoniazid, pyrazinamide, and metformin were measured by high-performance liquid chromatography using validated methods, and pharmacokinetic parameters and OCT1 and MATE1 gene polymorphisms were compared between the groups.

RESULTS

Significant increases in the clearance of rifampicin, isoniazid, and pyrazinamide were observed in patients in the METRIF group (n = 29) compared with those in the ATT group (n = 31). The AA genotypes of the single-nucleotide polymorphism of rs2289669 ( MATE1 ) in the METRIF group showed a significantly decreased area under the concentration-time curve to the last observation point and increased clearance of rifampicin.

CONCLUSIONS

Metformin altered rifampicin and isoniazid plasma concentrations in patients receiving antituberculosis treatment for pulmonary tuberculosis with little effect on sputum conversion at the end of treatment. Studies with larger sample sizes are needed to understand host drug-drug interactions.

Understanding the action mechanisms of metformin in the gastrointestinal tract

Metformin is the initial medication recommended for the treatment of type 2 diabetes mellitus (T2DM). In addition to diabetes treatment, the function of metformin also can be anti-aging, antiviral, and anti-inflammatory. Nevertheless, further exploration is required to fully understand its mode of operation. Historically, the liver has been acknowledged as the main location where metformin reduces glucose levels, however, there is increasing evidence suggesting that the gastrointestinal tract also plays a significant role in its action. In the gastrointestinal tract, metformin effects glucose uptake and absorption, increases glucagon-like peptide-1 (GLP-1) secretion, alters the composition and structure of the gut microbiota, and modulates the immune response. However, the side effects of it cannot be ignored such as gastrointestinal distress in patients. This review outlines the impact of metformin on the digestive system and explores potential explanations for variations in metformin effectiveness and adverse effects like gastrointestinal discomfort.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

INTRODUCTION

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.

RESEARCH DESIGN AND METHODS

We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.

RESULTS

Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).

CONCLUSIONS

Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.

Influence of Solute Carrier Family 22 Member 1 (SLC22A1) Gene Polymorphism on Metformin Pharmacokinetics and HbA1c Levels: A Systematic Review

BACKGROUND

Solute Carrier Family 22 Member 1 (SLC22A1, also known as OCT1) protein has a vital role in the metabolism of metformin, a first-line anti-diabetes medication. Genetic poly-morphism in SLC22A1 influences individual response to metformin.

OBJECTIVE

This review aims to compile the current knowledge about the effects of SLC22A1 genetic polymorphism on metformin pharmacokinetics and HbA1c levels.

METHODS

We followed the PRISMA 2020 standards to conduct a systematic review. We searched the publications for all appropriate evidence on the effects of SLC22A1 genetic polymorphism on metformin pharmacokinetics and HbA1c from January 2002 to December 2022.

RESULTS

Initial database searches identified 7,171 relevant studies. We reviewed 155 titles and abstracts after deleting duplicates. After applying inclusion and exclusion criteria, 23 studies remained.

CONCLUSION

Three studies found that rs12208357, rs34059508, and G465R had a considerable impact (p < 0.05) on metformin pharmacokinetics, resulting in increased metformin plasma (Cmax), a higher active amount of drug in the blood (AUC), and lower volume of distribution (Vd) (p<0.05). SLC22A1 polymorphisms with effects on HbA1c include rs628031 (four of seven studies), rs622342 (four of six studies), rs594709 (one study), rs2297374, and rs1867351 (one of two studies), rs34130495 (one study), and rs11212617 (one study) (p < 0.05).

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

Identification of Novel Intronic SNPs in Transporter Genes Associated with Metformin Side Effects

Metformin is a widely used and effective medication in type 2 diabetes (T2DM) as well as in polycystic ovary syndrome (PCOS). Single nucleotide polymorphisms (SNPs) contribute to the occurrence of metformin side effects. The aim of the present study was to identify intronic genetic variants modifying the occurrence of metformin side effects and to replicate them in individuals with T2DM and in women with PCOS. We performed Next Generation Sequencing (Illumina Next Seq) of 115 SNPs in a discovery cohort of 120 metformin users and conducted a systematic literature review. Selected SNPs were analysed in two independent cohorts of individuals with either T2DM or PCOS, using 5'-3'exonucleaseassay. A total of 14 SNPs in the organic cation transporters (OCTs) showed associations with side effects in an unadjusted binary logistic regression model, with eight SNPs remaining significantly associated after appropriate adjustment in the discovery cohort. Five SNPs were confirmed in a combined analysis of both replication cohorts but showed different association patterns in subgroup analyses. In an unweighted polygenic risk score (PRS), the risk for metformin side effects increased with the number of risk alleles. Intronic SNPs in the OCT cluster contribute to the development of metformin side effects in individuals with T2DM and in women with PCOS and are therefore of interest for personalized therapy options.

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.

Association of SLC22A1, SLC22A2, SLC47A1, and SLC47A2 Polymorphisms with Metformin Efficacy in Type 2 Diabetic Patients

Response to metformin, first-line therapy for type 2 diabetes mellitus (T2DM), exists interindividual variation. Considering that transporters belonging to the solute carrier (SLC) superfamily are determinants of metformin pharmacokinetics, we evaluated the effects of promoter variants in organic cation transporter 1 (OCT1) (SLC22A1 rs628031), OCT2 (SLC22A2 rs316019), multidrug and toxin extrusion protein 1 (MATE1) (SLC47A1 rs2289669), and MATE2 (SLC47A2 rs12943590) on the variation in metformin response. The glucose-lowering effects and improvement of insulin resistance of metformin were assessed in newly diagnosed, treatment-naive type 2 diabetic patients of Han nationality in Chaoshan China (n = 93) receiving metformin. Fasting plasma glucose (FPG), fasting insulin (FINS), glycated hemoglobin A1 (HbA1_C), homeostasis model assessment-insulin sensitivity (HOMA-IS), and homeostasis model assessment-insulin resistance (HOMA-IR) were the main metformin efficacy measurements. There were significant correlations between both SLC47A1 rs2289669 and SLC47A2 rs12943590 and the efficacy of metformin in individuals with T2DM. In normal weight T2DM patients, significant associations between the AA and GG genotypes of the rs2289669 variant of SLC47A1 and a greater reduction in FINS and HOMA-IR were detected. A significant correlation was observed between the AG genotype of the rs12943590 polymorphism of SLC47A2 and a greater reduction in HOMA-IR. Gene-environment interaction analysis showed that in the FINS interaction model, the second-order of dose30_g-SLC47A2 rs12943590 was statistically significant. The variants of SLC47A1 rs2289669 and SLC47A2 rs12943590 could be predictors of insulin resistance in type 2 diabetic patients treated with metformin. The second-order interaction of dose30_g-SLC47A2 rs12943590 may have a significant effect on FINS in patients with T2DM on metformin treatment. These findings suggest that promoter variants of SLC47A1 and SLC47A2 are important determinants of metformin transport and response in type 2 diabetes mellitus.

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.

Pharmacogenetics of Metformin Transporters Suggests No Association with Therapeutic Inefficacy among Diabetes Type 2 Mexican Patients

Mexico has been under official epidemiological alert due to diabetes since 2016. This study presents new information on the frequency and variants of metformin transporters OCT1, OCT2, OCT3, ABCB1, and CYP2C9 variants as well. It also reports the association with HbA1c control on 103 DMT2 patients. They were genotyped through real-time PCR (TaqMan assays) and grouped according to treatment: metformin and metformin + glibenclamide. Metformin plasmatic levels were determined through mass spectrometry. The analysis of HbA1c showed statistical significance across genotypes in polymorphisms rs72552763 (p = 0.022), rs622342 (p = 0.009), rs1128503 (p = 0.021), and rs2032582 (p = 0.009) within the monotherapy group. Bivariate analysis found no association between any polymorphism and HbA1c control. Two logistic regression models accounted for two diplotypes in OCT1 and ABCB1, including statistically significant covariates. The first model yielded significance in age (p = 0.026), treatment period [p = 0.001], BMI ≥ 25 kg/m2 (p = 0.043), and combined therapy (p < 0.001). There was no association with GAT/GAT of rs72552763 or A/A rs622342 in OCT1. The second model yielded significance in age (p = 0.017), treatment period (p = 0.001), BMI ≥ 25 kg/m2 (p = 0.042), and combined therapy (p < 0.001), finding no association with C/C of rs1128503 or G/G of rs2032582 in ABCB1. Our multinomial logistic regression results may benefit future predictive analyses in diabetic populations.

Association of SLC22A1 rs622342 and ATM rs11212617 polymorphisms with metformin efficacy in patients with type 2 diabetes

Metformin is the first-choice oral anti-hyperglycemic drug for type 2 diabetes mellitus (T2DM) patients. There are controversies about the association of SLC22A1 rs622342, which was not reported in the Chinese population, and ataxia-telangiectasia mutated (ATM) rs11212617 polymorphisms with metformin efficacy in T2DM. Our study was to investigate the effects of the two single nucleotide polymorphisms on the efficacy of metformin in T2DM of Han nationality in Chaoshan China. After enrollment, 82 newly diagnosed T2DM patients went on 2-month metformin monotherapy. According to BMI before treatment, the patients were divided into a normal weight group (≥18.5 and <25 kg/m2) and an overweight group (BMI ≥ 25 and <30 kg/m2). T-test, Pearson χ2 test, and regression analysis, which adjusted for age, BMI, sex, the dose of metformin, education, tea drink, smoking, and sweet, were used to evaluate the effects of rs622342 and rs11212617 on several variables, such as fasting plasma glucose (FPG). Compared with the AA or CC genotype, patients with AC genotype of rs622342 achieved greater reduction in Δ60FPG and Δ(60-30)FPG (P = 0.00820, 0.00089, respectively). For 11212617, the reduction in Δ30FPG and Δ60FPG was significantly different among patients with the AC genotype (P = 0.00026, 0.00820, respectively). Our results indicated that common variants of SLC22A1 rs622342 and ATM rs11212617 were associated with the efficacy of metformin in T2DM of Han nationality in Chaoshan China.

Determinants in Tailoring Antidiabetic Therapies: A Personalized Approach

Diabetes has become a pandemic as the number of diabetic people continues to rise globally. Being a heterogeneous disease, it has different manifestations and associated complications in different individuals like diabetic nephropathy, neuropathy, retinopathy, and others. With the advent of science and technology, this era desperately requires increasing the pace of embracing precision medicine and tailoring of drug treatment based on the genetic composition of individuals. It has been previously established that response to antidiabetic drugs, like biguanides, sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide 1 (GLP-1) agonists, and others, depending on variations in their transporter genes, metabolizing genes, genes involved in their action, etc. Responsiveness of these drugs also relies on epigenetic factors, including histone modifications, miRNAs, and DNA methylation, as well as environmental factors and the lifestyle of an individual. For precision medicine to make its way into clinical procedures and come into execution, all these factors must be reckoned with. This review provides an insight into several factors oscillating around the idea of precision medicine in type-2 diabetes mellitus.

Genetic variants in SLC22A1 are related to serum lipid levels in Mexican women

Dyslipidemia is the main risk factor for coronary artery disease and is characterized by alterations in concentrations of lipids, including low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triacylglycerols. The participation of several genes in the development of dyslipidemia has been evidenced. Genetic variants in SLC22A1 have been associated with elevated cholesterol and LDL-c levels. The aim of this study was to evaluate the association between single-nucleotide polymorphisms (SNPs) in the SLC22A1 gene with atherogenic risk lipid levels in Mexican women. Anthropometric and biochemical measurements were performed, and four SNPs in SLC22A1 were genotyped by real-time polymerase chain reaction. The Hardy-Weinberg equilibrium was verified, and haplotype frequencies were calculated. We found significant differences between the allele frequencies of the SNPs analyzed with those reported in Mexico and in the world, which could be due to differences in the historical admixture of the women studied. Generalized linear models were evaluated to determine the association between genotypes and haplotypes with lipids levels. We identified a significant increase in total cholesterol and LDL-c levels in women who were carriers of the GA and AG genotypes of the polymorphisms rs628031 and rs594709, respectively, significant effect that is also shown in a dominant inheritance model. Interestingly, we identified an important relationship of the AGC-GAT haplotype with the elevation in LDL-c levels and AGA-GAT haplotype with the elevation in HDL-c levels. On the other hand, we found a strong linkage disequilibrium between the polymorphisms studied. Our results show that variants in the SLC22A1 gene influence serum levels of atherogenic risk lipids, suggesting that these variants probably affect the function of organic cation transporter-1 and therefore, on the regulation of lipid metabolism.

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.

Single Nucleotide Polymorphisms Associated with Metformin and Sulphonylureas' Glycaemic Response among South African Adults with Type 2 Diabetes Mellitus

Aims: To examine the association of polymorphisms belonging to SLC22A1, SP1, PRPF31, NBEA, SCNN1B, CPA6 and CAPN10 genes with glycaemic response to metformin and sulphonylureas (SU) combination therapy among South African adults with diabetes mellitus type 2 (T2DM). Methods: A total of 128 individuals of Swati (n = 22) and Zulu (n = 106) origin attending chronic care for T2DM were recruited. Nine SNPs previously associated with metformin and SUs were selected and genotyped using MassArray. Uncontrolled T2DM was defined as HbA1c > 7%. The association between genotypes, alleles and glycaemic response to treatment was determined using multivariate logistic regression model analysis. Results: About 85.93% (n = 110) of the study participants were female and 77.34% (n = 99) had uncontrolled T2DM (HbA1c > 7%). In the multivariate (adjusted) logistic regression model analysis, the CC genotype of rs2162145 (CPA6), GG and GA genotypes of rs889299 (SCNN1B) were significantly associated with uncontrolled T2DM. On the other hand, the C allele of rs254271 (PRPF31) and the GA genotype of rs3792269 (CAPN10) were associated with controlled T2DM. A significant interaction between rs2162145 and rs889299 in response to metformin and SU combination therapy was observed. Conclusions: In this study, we reported the association of rs2162145 (CC) and rs889299 (GG and GA) with uncontrolled T2DM. We also reported the association of rs254271 (C) and rs3792269 (GA) with controlled T2DM in response to metformin and SU combination therapy. Furthermore, an interaction between rs2162145 and rs889299 was established, where the genotype combination GA (rs889299) and TT (rs2162145) was associated with uncontrolled T2DM.

Pharmacogenomic Studies of Current Antidiabetic Agents and Potential New Drug Targets for Precision Medicine of Diabetes

Diabetes is a major threat to people's health and has become a burden worldwide. Current drugs for diabetes have limitations, such as different drug responses among individuals, failure to achieve glycemic control, and adverse effects. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Currently pharmacogenomics has provided potential for individualized drug therapy based on genetic and genomic information of patients, and has made precision medicine possible. Responses and adverse effects to antidiabetic drugs are significantly associated with gene polymorphisms in patients. Many new targets for diabetes also have been discovered and developed, and even entered clinical trial phases. This review summarizes pharmacogenomic evidence of some current antidiabetic agents applied in clinical settings, and highlights potential drugs with new targets for diabetes, which represent a more effective treatment in the future.

Pharmacogenetic Aspects of Type 2 Diabetes Treatment

In this article, we analyze the role of different variants of the KCNJ11, TCF7L2, SLC22A1, SLC22A3, CYP2C9, CYP2C8, PPARγ genes polymorphisms in efficacy of diabetes mellitus pharmacotherapy. T allele of the KCNJ11 rs2285676 gene polymorphism and G allele of KCNJ11 rs5218 gene polymorphism are associated with the response to IDPP-4 therapy; the presence of KCNJ11 gene rs5210 polymorphism A allele is a predictor of poor response. The effect of rs7903146 polymorphism of TCF7L2 gene was evaluated on the response to treatment of patients taking linagliptin. Linagliptin significantly reduced HbA1c levels for all three rs7903146 genotypes (CC: –0.82 %; CT: –0.77 %; TT: –0.57 %). A significantly smaller effect of therapy was observed with the genotype with ТТ. The rs622342 polymorphism of SLC22A1 gene was studied in effectiveness of metformin. The researches demonstrated that carriers of variant AA had an average decrease of HbA1c of 0.53 %, heterozygous – decrease of 0.32 %, and carriers of a minor variant of SS had an increase of 0.2 % in the level of HbA1c. A significant effect of CYP2C9 polymorphisms on the pharmacokinetic parameters of PSM was noted. When studying the kinetics of glibenclamide, it was found that carriage of the allele *2 significantly reduces glibenclamide metabolism: homozygous carriers had clearance 90 % lower than homozygous carriers of the wild variant. The studies confirmed the association of the allelic variants of Thr394Thr and Gly482Ser of PPARγ gene with higher efficacy of the rosiglitazone. The data obtained from the analysis of the association of the Pro12Ala polymorphism of PPARγ gene and the response to therapy is contradictory. Thus the personalized approach, based on the knowledge of polymorphism options, will allow choosing the most effective drug with transparent kinetics for each individual patient.

Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients

Objectives Type 2 Diabetes mellitus is a progressive metabolic disease characterized by relative insulin insufficiency and insulin resistance resulting in hyperglycemia. Despite the widespread use of metformin, there is considerable variation in treatment response; with approximately one-third of patients failing to achieve adequate glycemic control. Studies have reported the involvement of single nucleotide polymorphisms and their interactions in genetic pathways i.e., pharmacodynamics and pharmacokinetics. This study aims to investigate the association between 19 pharmacogenetics biomarkers and response to metformin treatment. Methods MassARRAY panels were designed and optimized by Inqaba Biotechnical Industries, to genotype 19 biomarkers for 140 type 2 diabetic outpatients. Results The CT genotype of the rs12752688 polymorphism was significantly associated with increased response to metformin therapy after correction (OR=0.33, 95% CI [0.16-0.68], p-value=0.006). An association was also found between the GA genotype of SLC47A2 rs12943590 and a decreased response to metformin therapy after correction (OR=2.29, 95% CI [1.01-5.21], p-value=0.01). Conclusions This is the first study investigating the association between genetic variants and responsiveness to medication for diabetic patients from the indigenous Nguni population in South Africa. It is suggested that rs12752688 and rs12943590 be included in pharmacogenomics profiling systems to individualize metformin therapy for diabetic patients from African populations.

Evaluation of the suitability of 19 pharmacogenomics biomarkers for individualized metformin therapy for type 2 diabetes patients

Objectives Type 2 Diabetes mellitus is a progressive metabolic disease characterized by relative insulin insufficiency and insulin resistance resulting in hyperglycemia. Despite the widespread use of metformin, there is considerable variation in treatment response; with approximately one-third of patients failing to achieve adequate glycemic control. Studies have reported the involvement of single nucleotide polymorphisms and their interactions in genetic pathways i.e., pharmacodynamics and pharmacokinetics. This study aims to investigate the association between 19 pharmacogenetics biomarkers and response to metformin treatment. Methods MassARRAY panels were designed and optimized by Inqaba Biotechnical Industries, to genotype 19 biomarkers for 140 type 2 diabetic outpatients. Results The CT genotype of the rs12752688 polymorphism was significantly associated with increased response to metformin therapy after correction (OR=0.33, 95% CI [0.16-0.68], p-value=0.006). An association was also found between the GA genotype of SLC47A2 rs12943590 and a decreased response to metformin therapy after correction (OR=2.29, 95% CI [1.01-5.21], p-value=0.01). Conclusions This is the first study investigating the association between genetic variants and responsiveness to medication for diabetic patients from the indigenous Nguni population in South Africa. It is suggested that rs12752688 and rs12943590 be included in pharmacogenomics profiling systems to individualize metformin therapy for diabetic patients from African populations.

rs622342 in SLC22A1, CYP2C9*2 and CYP2C9*3 and Glycemic Response in Individuals with Type 2 Diabetes Mellitus Receiving Metformin/Sulfonylurea Combination Therapy: 6-Month Follow-Up Study

Background and Objective: Since the treatment outcome with oral anti-diabetics differs between individuals, the objective of this study is to evaluate the significance of rs622342 in SLC22A1, CYP2C9*2 (rs1799853) and CYP2C9*3 (rs1057910) with regard to the efficacy of metformin/sulfonylurea combination therapy in individuals with type 2 diabetes mellitus (T2DM). Methods: Eighty-eight Lebanese individuals with T2DM received metformin/sulfonylurea combination therapy over 3 and 6 months. The clinical and biochemical characteristics were collected. Genotyping of rs622342 in SLC22A1, CYP2C9*2 and CYP2C9*3 was performed using hybridization probes on real-time polymerase chain reaction (PCR) instrument. Statistical analysis was performed using SPSS 22.0. Results: The levels of fasting blood sugar (FBS) and glycated hemoglobin (HbA1c) showed a statistically significant reduction over 3 and 6 months of follow-up (p < 0.001). An interaction between rs622342 in SLC22A1, CYP2C9*2 and CYP2C9*3 (p = 0.035) was found associated with reduced levels of HbA1c levels after 3 and 6 months. A significant difference between the means of HbA1c was observed among the different groups after 3 and 6 months (p = 0.004 and p < 0.001, respectively). The most beneficial group was; AA and AC, *1*3, whereas the individuals that benefited the least were CC, *1*3 at 3 and 6 months. In contrast to HbA1c, no interaction was found between the three polymorphisms to affect FBS (p = 0.581). Conclusion: The combination of metformin/sulfonylurea therapy led to the maximum glycemic control in individuals with T2DM carrying AA or AC genotypes in SLC22A1 and *1*3 in CYP2C9.

The human organic cation transporter OCT1 and its role as a target for drug responses

The human organic cation uptake transporter OCT1, encoded by the SLC22A1 gene, is highly expressed in the liver and reported to possess a broad substrate specificity. OCT1 operates by facilitated diffusion and allows the entry of nutrients into cells. Recent findings revealed that OCT1 can mediate the uptake of drugs for treating various diseases such as cancers. The levels of OCT1 expression correlate with the responses towards many drugs and functionally defective OCT1 lead to drug resistance. It has been recently proposed that OCT1 should be amongst the crucial drug targets used for pharmacogenomic analyses. Several single nucleotide polymorphisms exist and are distributed across the entire OCT1 gene. While there are differences in the OCT1 gene polymorphisms between populations, there are at least five variants that warrant consideration in any genetic screen. To date, and despite two decades of research into OCT1 functional role, it still remains uncertain what are the define substrates for this uptake transporter, although studies from mice revealed that one of the substrates is vitamin B1. It is also unclear how OCT1 recognizes a broad array of ligands and whether this involves specific modifications and interactions with other proteins. In this review, we highlight the current findings related to OCT1 with the aim of propelling further studies on this key uptake transporter.

Lack of effect of the SLC47A1 and SLC47A2 gene polymorphisms on the glycemic response to metformin in type 2 diabetes mellitus patients

Background This work aimed to evaluate the influence of single nucleotide polymorphisms (SNPs) in the SLC47A1 (922-158G>A; rs2289669) and SLC47A2 (-130G>A; rs12943590) genes on the relative change in HbA1c in type 2 diabetes mellitus (T2DM) patients of South India who are taking metformin as monotherapy. It also aims to study the effects of these SNPs on the dose requirement of metformin for glycemic control and the adverse effects of metformin. Methods Diabetes patients on metformin monotherapy were recruited based on the eligibility criteria (n=105). DNA was extracted and genotyping was performed with a real-time PCR system using TaqMan® SNP genotyping assay method. The HbA1c levels were measured using Bio-Rad D-10™ Hemoglobin Analyzer. Results After adjusting for multiple comparisons (Bonferroni correction) the difference found in the glycemic response between the "GG" genotype and "AG/AA" genotype groups of the SLC47A2 gene was not significant (p=0.027; which was greater than the critical value of 0.025). Patients with "GG" genotype showed a 5.5% decrease in HbA1c from baseline compared to those with the "AG/AA" genotype (0.1% increase). The SNP in the SLC47A1 gene also did not influence the glycemic response to metformin (p=0.079). The median dose requirements based on the genotypes of the rs12943590 variant (p=0.357) or rs2289669 variant (p=0.580) were not significantly different. Similarly, there was no significant difference in the occurrence of adverse effects across the genotypes in both the SLC47A1 (p=0.615) and SLC47A2 (p=0.309) genes. Conclusions The clinical response to metformin was not associated with the SNPs in the SLC47A1 and SLC47A2 genes coding for the multidrug and toxin extrusion protein (MATE) transporters. Furthermore, the studied SNPs had no influence on the dose requirement or adverse effects of metformin.

The influence of SLC22A1 rs622342 and ABCC8 rs757110 genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian patients with type 2 diabetes

Background: The incidence of Type 2 Diabetes Mellitus (T2DM) in Egypt is considered one of the highest in the world. Metformin and Sulfonylureas are usually prescribed together due to their efficacy and their relatively low cost. Organic cation transport 1, encoded by SLC22A1 gene, is the main transporter of metformin into hepatocytes, which is considered metformin site of action. Sulfonylureas enhance insulin release from pancreatic B-cells through binding to sulfonylurea receptor 1, encoded by ABCC8 gene. Single nucleotide polymorphisms in the SLC22A1 and ABCC8 genes might affect the response of each drug.

Aims: To investigate the influence of SLC22A1 rs622342 (A>C) and ABCC8 rs757110 (A>C) genetic variants on the efficacy of metformin and glimepiride combination therapy in Egyptian T2DM patients.

Methods: Observational cross-sectional study in which patients receiving metformin and glimepiride combination therapy for at least 6 months were included for genotyping and classified into either responders or non-responders, based on their HbA1C level.

Results: A total of 127 patients were included and genotyped. They were divided into 93 responders (HbA1C<7%) and 34 non-responders (HbA1C≥7%). Minor allele frequencies for rs622342 and rs757110 were 0.189 and 0.271, respectively. Only SLC22A1 rs622342 variant was found to be associated with the response of combination therapy, in which AA alleles carriers were 2.7-times more responsive to metformin than C allele carriers (Recessive model, odds ratio = 2.718, p = 0.025, 95% CI = 1.112–6.385).

Conclusion: Genotyping of rs622342 can be useful in predicting the response to metformin in combination therapy in Egyptian T2DM patients.

Altered Glycemic Control Associated With Polymorphisms in the SLC22A1 (OCT1) Gene in a Mexican Population With Type 2 Diabetes Mellitus Treated With Metformin: A Cohort Study

The organic cation transporters OCT1 and OCT2 and the multidrug and toxin extrusion transporter MATE1, encoded by the SLC22A1, SLC22A2, and SLC47A1 genes, respectively, are responsible for the absorption of metformin in enterocytes, hepatocytes, and kidney cells. The aim of this study was to evaluate whether genetic variations in the SLC22A1, SLC22A2, and SLC47A1 genes could be associated with an altered response to metformin in patients with type 2 diabetes mellitus. A cohort study was conducted in 308 individuals with a diagnosis of type 2 diabetes mellitus of less than 3 years and who had metformin monotherapy. Three measurements of blood glycated hemoglobin (HbA_1c ) were obtained at the beginning of the study and after 6 and 12 months. Five polymorphisms were analyzed in the SLC22A1 (rs622342, rs628031, rs594709), SLC22A2 (rs316019), and SLC47A1 (rs2289669) genes by real-time polymerase chain reaction. The results showed a significant association among genotypes CC-rs622342 (β = 1.36; P < .001), AA-rs628031 (β = 0.98; P = .032), and GG-rs594709 (β = 1.21; P = .016) in the SLC22A1 gene with an increase in HbA_1c levels during the follow-up period. Additionally, a significant association was found in the CGA and CAG haplotypes with an increase in HbA_1c levels compared to the highest-frequency haplotype (AGA). In conclusion, the genetic variation in the SLC22A1 gene was significantly related to the variation of the HbA_1c levels, an important indicator of glycemic control in diabetic patients. This information may contribute to identifying patients with an altered response to metformin before starting their therapy.

Pharmacogenetics of type 2 diabetes mellitus, the route toward tailored medicine

Type 2 diabetes mellitus (T2DM) is a chronic disease that has reached the levels of a global epidemic. In order to achieve optimal glucose control, it is often necessary to rely on combination therapy of multiple drugs or insulin because uncontrolled glucose levels result in T2DM progression and enhanced risk of complications and mortality. Several antihyperglycemic agents have been developed over time, and T2DM pharmacotherapy should be prescribed based on suitability for the individual patient's characteristics. Pharmacogenetics is the branch of genetics that investigates how our genome influences individual responses to drugs, therapeutic outcomes, and incidence of adverse effects. In this review, we evaluated the pharmacogenetic evidences currently available in the literature, and we identified the top informative genetic variants associated with response to the most common anti-diabetic drugs: metformin, DPP-4 inhibitors/GLP1R agonists, thiazolidinediones, and sulfonylureas/meglitinides. Overall, we found 40 polymorphisms for each drug class in a total of 71 loci, and we examined the possibility of encouraging genetic screening of these variants/loci in order to critically implement decision-making about the therapeutic approach through precision medicine strategies. It is possible then to anticipate that when the clinical practice will take advantage of the genetic information of the diabetic patients, this will provide a useful resource for the prevention of T2DM progression, enabling the identification of the precise drug that is most likely to be effective and safe for each patient and the reduction of the economic impact on a global scale.

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 medicine in diabetes prevention, classification and management

Diabetes has become a major burden of healthcare expenditure. Diabetes management following a uniform treatment algorithm is often associated with progressive treatment failure and development of diabetic complications. Recent advances in our understanding of the genomic architecture of diabetes and its complications have provided the framework for development of precision medicine to personalize diabetes prevention and management. In the present review, we summarized recent advances in the understanding of the genetic basis of diabetes and its complications. From a clinician's perspective, we attempted to provide a balanced perspective on the utility of genomic medicine in the field of diabetes. Using genetic information to guide management of monogenic forms of diabetes represents the best-known examples of genomic medicine for diabetes. Although major strides have been made in genetic research for diabetes, its complications and pharmacogenetics, ongoing efforts are required to translate these findings into practice by incorporating genetic information into a risk prediction model for prioritization of treatment strategies, as well as using multi-omic analyses to discover novel drug targets with companion diagnostics. Further research is also required to ensure the appropriate use of this information to empower individuals and healthcare professionals to make personalized decisions for achieving the optimal outcome.

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.

Implication of critical pharmacokinetic gene variants on therapeutic response to metformin in Type 2 diabetes

Aim: Metformin, an oral hypoglycemic drug is the first line of treatment for Type 2 diabetes individuals. We studied the effect of critical gene single nucleotide polymorphisms  on the glucose lowering effect of metformin. Method: We performed a prospective study on 221 newly diagnosed, treatment-naive Type 2 diabetes subjects. Individuals were started with metformin monotherapy and followed up for 12 weeks. Results: Our association analysis revealed that SLC22A2 rs316019 and SLC47A2 rs12943590 were significantly associated with metformin drug response across co-dominant and dominant models, respectively. SLC22A2 rs316019 GG and SLC47A2 rs12943590 GA combined genotypes showed maximum average change in HbA1c level. Conclusion: The present study proposes a role of SLC22A2 rs316019 and SLC47A2 rs12943590 in the pharmacokinetic action of metformin.

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.

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.

Pharmacogenetic studies update in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a silent progressive polygenic metabolic disorder resulting from ineffective insulin cascading in the body. World-wide, about 415 million people are suffering from T2DM with a projected rise to 642 million in 2040. T2DM is treated with several classes of oral antidiabetic drugs (OADs) viz. biguanides, sulfonylureas, thiazolidinediones, meglitinides, etc. Treatment strategies for T2DM are to minimize long-term micro and macro vascular complications by achieving an optimized glycemic control. Genetic variations in the human genome not only disclose the risk of T2DM development but also predict the personalized response to drug therapy. Inter-individual variability in response to OADs is due to polymorphisms in genes encoding drug receptors, transporters, and metabolizing enzymes for example, genetic variants in solute carrier transporters (SLC22A1, SLC22A2, SLC22A3, SLC47A1 and SLC47A2) are actively involved in glycemic/HbA1c management of metformin. In addition, CYP gene encoding Cytochrome P450 enzymes also play a crucial role with respect to metabolism of drugs. Pharmacogenetic studies provide insights on the relationship between individual genetic variants and variable therapeutic outcomes of various OADs. Clinical utility of pharmacogenetic study is to predict the therapeutic dose of various OADs on individual basis. Pharmacogenetics therefore, is a step towards personalized medicine which will greatly improve the efficacy of diabetes treatment.

Role of SLC22A1 polymorphic variants in drug disposition, therapeutic responses, and drug-drug interactions

The SCL22A1 gene encodes the broad selectivity transporter hOCT1. hOCT1 is expressed in most epithelial barriers thereby contributing to drug pharmacokinetics. It is also expressed in different drug target cells, including immune system cells and others. Thus, this membrane protein might also contribute to drug pharmacodynamics. Up to 1000 hOCT1 polymorphisms have been identified so far, although only a small fraction of those have been mechanistically studied. A paradigm in the field of drug transporter pharmacogenetics is the impact of hOCT1 gene variability on metformin clinical parameters, affecting area under the concentration-time curve, Cmax and responsiveness. However, hOCT1 also mediates the translocation of a variety of drugs used as anticancer, antiviral, anti-inflammatory, antiemetic agents as well as drugs used in the treatment of neurological diseases among. This review focuses exclusively on those drugs for which some pharmacogenetic data are available, and aims at highlighting the need for further clinical research in this area.