Human organic cation transporter (OCT1 and OCT2) gene polymorphisms and therapeutic effects of metformin

Mechanisms of Sorafenib Resistance in HCC Culture Relate to the Impaired Membrane Expression of Organic Cation Transporter 1 (OCT1)

Introduction

Sorafenib, an FDA-approved drug for advanced hepatocellular carcinoma (HCC) treatment, encounters resistance in many patients. Deciphering the mechanisms underlying sorafenib resistance is crucial for devising alternative strategies to overcome it.

Aim

This study aimed to investigate sorafenib resistance mechanisms using a diverse panel of HCC cell lines.

Methods

HCC cell lines were subjected to continuous sorafenib treatment, and stable cell lines (Huh 7.5 and Huh 7PX) exhibiting sustained growth in its presence were isolated. The investigation of drug resistance mechanisms involved a comparative analysis of drug-targeted signal transduction pathways (EGFR/RAF/MEK/ERK/Cyclin D), sorafenib uptake, and membrane expression of the drug uptake transporter.

Results

HCC cell lines (Huh 7.5 and Huh 7PX) with a higher IC50 (10μM) displayed a more frequent development of sorafenib resistance compared to those with a lower IC50 (2-4.8μM), indicating a potential impact of IC50 variation on initial treatment response. Our findings reveal that activated overexpression of Raf1 kinases and impaired sorafenib uptake, mediated by reduced membrane expression of organic cation transporter-1 (OCT1), contribute to sorafenib resistance in HCC cultures. Stable expression of the drug transporter OCT1 through cDNA transfection or adenoviral delivery of OCT1 mRNA increased sorafenib uptake and successfully overcame sorafenib resistance. Additionally, consistent with sorafenib resistance in HCC cultures, cirrhotic liver-associated human HCC tumors often exhibited impaired membrane expression of OCT1 and OCT3.

Conclusion

Intrinsic differences among HCC cell clones, affecting sorafenib sensitivity at the expression level of Raf kinases, drug uptake, and OCT1 transporters, were identified. This study underscores the potential of HCC tumor targeted OCT1 expression to enhance sorafenib treatment response.

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism

INTRODUCTION

Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects.

OBJECTIVES

To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations.

METHODS

A dual extraction method involving 80% methanol followed by MTBE (methyl tert-butyl ether) extraction enables the analysis of free fatty acids, polar metabolites, and lipids. Extracts from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days were analyzed using HILIC chromatography coupled to Q Exactive Plus mass spectrometer or reversed-phase liquid chromatography coupled to MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility.

RESULTS

Lipidomics analysis of 6 mouse tissues and plasma allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that (1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; (2) the impact on lysophosphatidylcholine (lysoPC) and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations; (3) increase of intestinal tricarboxylic acid (TCA) cycle intermediates after metformin treatment.

CONCLUSION

The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

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).

Association of SLC22A1, SLC47A1, and KCNJ11 polymorphisms with efficacy and safety of metformin and sulfonylurea combination therapy in Egyptian patients with type 2 diabetes

Background and purpose

Multidrug and toxin extrusion transporter 1 (MATE1), encoded by the SLC47A1 gene and single nucleotide polymorphisms of organic cation transport 1, may impact metformin's responsiveness and side effects. Inward-rectifier potassium channel 6.2 (Kir 6.2) subunits encoded by KCNJ11 may affect the response to sulfonylurea. This study aimed to evaluate the association between SLC22A1 rs72552763 and rs628031, SLC47A1 rs2289669 and KCNJ11 rs5219 genetic variations with sulfonylurea and metformin combination therapy efficacy and safety in Egyptian type 2 diabetes mellitus patients.

Experimental approach

This study was conducted on 100 cases taking at least one year of sulfonylurea and metformin combination therapy. Patients were genotyped via the polymerase chain reaction-restriction fragment length polymorphism technique. Then, according to their glycated hemoglobin level, cases were subdivided into non-responders or responders. Depending on metformin-induced gastrointestinal tract side effects incidence, patients are classified as tolerant or intolerant.

Findings/Results

KCNJ11 rs5219 heterozygous and homozygous mutant genotypes, SLC47A1 rs2289669 heterozygous and homozygous mutant genotypes (AA and AG), and mutant alleles of both polymorphisms were significantly related with increased response to combined therapy. Individuals with the SLC22A1 (rs72552763) GAT/del genotype and the SLC22A1 (rs628031) AG and AA genotypes were at a higher risk for metformin-induced gastrointestinal tract adverse effects.

Conclusion and implications

The results implied a role for SLC47A1 rs2289669 and KCNJ11 rs5219 in the responsiveness to combined therapy. SLC22A1 (rs628031) and (rs72552763) polymorphisms may be associated with increased metformin adverse effects in type 2 diabetes mellitus patients.

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.

Pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) in newly diagnosed Indian type 2 diabetes patients undergoing metformin monotherapy

OBJECTIVES

Type 2 diabetes (T2D) imposes an enormous burden all over the world in both developed and developing countries. Inter-individual differences are attributed to polymorphisms in candidate genes resulting in altered absorption, transportation, distribution, and metabolism of oral antidiabetic drugs (OADs). Hence, the present study was undertaken to evaluate the pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) on metformin monotherapy in newly diagnosed untreated T2D patients.

METHODS

Newly diagnosed T2D patients ( n  = 500) were enrolled according to inclusion/exclusion criteria. Initially, enrolled subjects were prescribed metformin monotherapy and followed up for at least 12 weeks. Response to metformin was evaluated in 478 patients who revisited for follow-up by measuring HbA1c.

RESULT

Out of 478 patients, 373 were responders to metformin monotherapy while 105 were non-responders. The pharmacogenetic impact was evaluated by genotype, haplotype, and pharmacogenetic analyses. 'GG' genotype and 'G' allele of SLC22A1 rs628031 G/A were observed in 48.8% and 67.7% of Met responders, respectively, while 20.9% and 49.1 % were in non-responders. Therefore, there was a 2.18-fold increase in the success rate of Met therapeutics.

CONCLUSION

Individuals carrying the 'GG' genotype or 'G' allele for SLC22A1 gene variant rs628031 G/A are better responders for Metformin monotherapy.

Identification of Transporter Polymorphisms Influencing Metformin Pharmacokinetics in Healthy Volunteers

For patients with type 2 diabetes, metformin is the most often recommended drug. However, there are substantial individual differences in the pharmacological response to metformin. To investigate the effect of transporter polymorphisms on metformin pharmacokinetics in an environment free of confounding variables, we conducted our study on healthy participants. This is the first investigation to consider demographic characteristics alongside all transporters involved in metformin distribution. Pharmacokinetic parameters of metformin were found to be affected by age, sex, ethnicity, and several polymorphisms. Age and SLC22A4 and SLC47A2 polymorphisms affected the area under the concentration-time curve (AUC). However, after adjusting for dose-to-weight ratio (dW), sex, age, and ethnicity, along with SLC22A3 and SLC22A4, influenced AUC. The maximum concentration was affected by age and SLC22A1, but after adjusting for dW, it was affected by sex, age, ethnicity, ABCG2, and SLC22A4. The time to reach the maximum concentration was influenced by sex, like half-life, which was also affected by SLC22A3. The volume of distribution and clearance was affected by sex, age, ethnicity and SLC22A3. Alternatively, the pharmacokinetics of metformin was unaffected by polymorphisms in ABCB1, SLC2A2, SLC22A2, or SLC47A1. Therefore, our study demonstrates that a multifactorial approach to all patient characteristics is necessary for better individualization.

Data-dependent and -independent acquisition lipidomics analysis reveals the tissue-dependent effect of metformin on lipid metabolism

Introduction

Despite the well-recognized health benefits, the mechanisms and site of action of metformin remains elusive. Metformin-induced global lipidomic changes in plasma of animal models and human subjects have been reported. However, there is a lack of systemic evaluation of metformin-induced lipidomic changes in different tissues. Metformin uptake requires active transporters such as organic cation transporters (OCTs), and hence, it is anticipated that metformin actions are tissue-dependent. In this study, we aim to characterize metformin effects in non-diabetic male mice with a special focus on lipidomics analysis. The findings from this study will help us to better understand the cell-autonomous (direct actions in target cells) or non-cell-autonomous (indirect actions in target cells) mechanisms of metformin and provide insights into the development of more potent yet safe drugs targeting a particular organ instead of systemic metabolism for metabolic regulations without major side effects.

Objectives

To characterize metformin-induced lipidomic alterations in different tissues of non-diabetic male mice and further identify lipids affected by metformin through cell-autonomous or systemic mechanisms based on the correlation between lipid alterations in tissues and the corresponding in-tissue metformin concentrations.

Methods

Lipids were extracted from tissues and plasma of male mice treated with or without metformin in drinking water for 12 days and analyzed using MS/MS scan workflow (hybrid mode) on LC-Orbitrap Exploris 480 mass spectrometer using biologically relevant lipids-containing inclusion list for data-independent acquisition (DIA), named as BRI-DIA workflow followed by data-dependent acquisition (DDA), to maximum the coverage of lipids and minimize the negative effect of stochasticity of precursor selection on experimental consistency and reproducibility.

Results

Lipidomics analysis of 6 mouse tissues and plasma using MS/MS combining BRI-DIA and DDA allowed a systemic evaluation of lipidomic changes induced by metformin in different tissues. We observed that 1) the degrees of lipidomic changes induced by metformin treatment overly correlated with tissue concentrations of metformin; 2) the impact on lysophosphorylcholine and cardiolipins was positively correlated with tissue concentrations of metformin, while neutral lipids such as triglycerides did not correlate with the corresponding tissue metformin concentrations.

Conclusion

The data collected in this study from non-diabetic mice with 12-day metformin treatment suggest that the overall metabolic effect of metformin is positively correlated with tissue concentrations and the effect on individual lipid subclass is via both cell-autonomous mechanisms (cardiolipins and lysoPC) and non-cell-autonomous mechanisms (triglycerides).

Implications of genetic variations, differential gene expression, and allele-specific expression on metformin response in drug-naïve type 2 diabetes

PURPOSE

Metformin is widely used to treat type 2 diabetes mellitus (T2DM) individuals. Clinically, inter-individual variability of metformin response is of significant concern and is under interrogation. In this study, a targeted exome and whole transcriptome analysis were performed to identify predictive biomarkers of metformin response in drug-naïve T2DM individuals.

METHODS

The study followed a prospective study design. Drug-naïve T2DM individuals (n = 192) and controls (n = 223) were enrolled. T2DM individuals were administered with metformin monotherapy and defined as responders and non-responders based on their glycated haemoglobin change over three months. 146 T2DM individuals were used for the final analysis and remaining samples were lost during the follow-up. Target exome sequencing and RNA-seq was performed to analyze genetic and transcriptome profile. The selected SNPs were validated by genotyping and allele specific gene expression using the TaqMan assay. The gene prioritization, enrichment analysis, drug-gene interactions, disease-gene association, and correlation analysis were performed using various tools and databases.

RESULTS

rs1050152 and rs272893 in SLC22A4 were associated with improved response to metformin. The copy number loss was observed in PPARGC1A in the non-responders. The expression analysis highlighted potential differentially expressed targets for predicting metformin response (n = 35) and T2DM (n = 14). The expression of GDF15, TWISTNB, and RPL36A genes showed a maximum correlation with the change in HbA1c levels. The disease-gene association analysis highlighted MAGI2 rs113805659 to be linked with T2DM.

CONCLUSION

The results provide evidence for the genetic variations, perturbed transcriptome, allele-specific gene expression, and pathways associated with metformin drug response in T2DM.

Circulating selenoprotein P levels predict glucose-lowering and insulinotropic effects of metformin, but not alogliptin: A post-hoc analysis

AIMS/INTRODUCTION

Selenoprotein P (SeP; encoded by SEPP1 in humans) is a hepatokine that causes impaired insulin secretion and insulin resistance. Metformin downregulates SELENOP promoter activity through an adenosine monophosphate-activated kinase-forkhead box protein O3a pathway in hepatocytes. This study aimed to test our hypothesis that circulating SeP levels are associated with the glucose-lowering effect of metformin in humans.

MATERIALS AND METHODS

A total of 84 participants with poorly controlled type 2 diabetes were randomly assigned to receive metformin (1,000 mg, twice daily) or a dipeptidyl peptidase-4 inhibitor, alogliptin (25 mg, once daily) for 12 weeks. We tested metformin and alogliptin on SeP levels and factors associated therewith as a post-hoc analysis.

RESULTS

Both metformin and aloglipitin did not change the SeP levels. Although metformin significantly increased the insulin secretory index secretory units of islets in transplantation only in participants with higher baseline SeP (>3.87), both agents similarly reduced fasting plasma glucose and glycated hemoglobin. SeP levels at baseline were correlated negatively with changes in SeP (r = -0.484, P = 0.004) and fasting plasma glucose (r = -0.433, P = 0.011), and positively with changes in C-peptide immunoreactivity (r = 0.420, P = 0.017) and secretory units of islets in transplantation (r = 0.388, P = 0.028) in the metformin, but not alogliptin, group.

CONCLUSIONS

Higher baseline levels of SeP significantly predicted metformin-mediated, but not alogliptin-mediated, glucose-lowering and insulinotropic effects. Serum SeP levels might be a novel biomarker for predicting the outcomes of metformin therapy, which might be helpful in tailoring diabetes medication.

Association between Germline Single-Nucleotide Variants in ADME Genes and Major Molecular Response to Imatinib in Chronic Myeloid Leukemia Patients

Imatinib is the most common first-line tyrosine kinase inhibitor (TKI) used to treat chronic-phase chronic myeloid leukemia (CP-CML). However, only a proportion of patients achieve major molecular response (MMR), so there is a need to find biological factors that aid the selection of the optimal therapeutic strategy (imatinib vs. more potent second-generation TKIs). The aim of this retrospective study was to understand the contribution of germline single-nucleotide variants (gSNVs) in the achievement of MMR with imatinib. In particular, a discovery cohort including 45 CP-CML patients was analyzed through the DMET array, which interrogates 1936 variants in 231 genes related to the absorption, distribution, metabolism and excretion (ADME) process. Variants statistically significant in the discovery cohort were then tested in an extended and independent cohort of 137 CP-CML patients. Finally, a total of 7 gSNVs (ABCG1-rs492338, ABCB11-rs496550, ABCB11-rs497692, CYP2D6-rs1135840, CYP11B1-rs7003319, MAT1A-rs4934027 and SLC22A1-rs628031) and one haplotype in the ABCB11 gene were significantly associated with the achievement of MMR with first-line imatinibtreatment. In conclusion, we identified a genetic signature of response to imatinib in CP-CML patients that could be useful in selecting those patients that may benefit from starting imatinib as first-line therapy, therefore avoiding the toxicity related to second-generation TKIs.

Obligatory Role of AMPK Activation and Antioxidant Defense Pathway in the Regulatory Effects of Metformin on Cellular Protection and Prevention of Lens Opacity

Increasing levels of oxidative-stress due to deterioration of the Nrf2 (NFE2-related factor)/ARE (antioxidant response element) pathway is found to be a primary cause of aging pathobiology. Metformin having anti-aging effects can delay/halt aging-related diseases. Herein, using lens epithelial cell lines (LECs) of human (h) or mouse (m) and aging h/m primary LECs along with lenses as model systems, we demonstrated that Metformin could correct deteriorated Bmal1/Nrf2/ARE pathway by reviving AMPK-activation, and transcriptional activities of Bmal1/Nrf2, resulting in increased antioxidants enzymatic activity and expression of Phase II enzymes. This ensued reactive oxygen species (ROS) mitigation with cytoprotection and prevention of lens opacity in response to aging/oxidative stress. It was intriguing to observe that Metformin internalized lens/LECs and upregulated OCTs (Organic Cation Transporters). Mechanistically, we found that Metformin evoked AMPK activation-dependent increase of Bmal1, Nrf2, and antioxidants transcription by promoting direct E-Box and ARE binding of Bmal1 and Nrf2 to the promoters. Loss-of-function and disruption of E-Box/ARE identified that Metformin acted by increasing Bmal1/Nrf2-mediated antioxidant expression. Data showed that AMPK-activation was a requisite for Bmal1/Nrf2-antioxidants-mediated defense, as pharmacologically inactivating AMPK impeded the Metformin's effect. Collectively, the results for the first-time shed light on the hitherto incompletely uncovered crosstalk between the AMPK and Bmal1/Nrf2/antioxidants mediated by Metformin for blunting oxidative/aging-linked pathobiology.

Effects of single-nucleotide polymorphism on the pharmacokinetics and pharmacodynamics of metformin

INTRODUCTION

Metformin has been recognized as the first-choice drug for type 2 diabetes mellitus (T2DM). The potency of metformin in the treatment of type 2 diabetes has always been in the spotlight and shown significant individual differences. Based on previous studies, the efficacy of metformin is related to the single-nucleotide polymorphisms of transporter genes carried by patients, amongst which a variety of gene polymorphisms of transporter and target protein genes affect the effectiveness and adverse repercussion of metformin.

AREAS COVERED

Here, we reviewed the current knowledge about gene polymorphisms impacting metformin efficacy based on transporter and drug target proteins.

EXPERT OPINION

The reason for the difference in clinical drug potency of metformin can be attributed to the gene polymorphism of drug transporters and drug target proteins in the human body. Substantial evidence shows that genetic polymorphisms in transporters such as organic cation transporter 1 (OCT1) and organic cation transporter 2 (OCT2) affect the glucose-lowering effectiveness of metformin. However, optimization of individualized dosing regimens of metformin is necessary to clarify the role of several polymorphisms.

Variants of SLC2A10 may be Linked to Poor Response to Metformin

Purpose

A study among Filipinos revealed that only 15% of patients with diabetes achieved glycemic control, and poor response to metformin could be one of the possible reasons. Recent studies demonstrate how genetic variations influence response to metformin. Hence, the present study aimed to determine genetic variants associated with poor response to metformin.

Methods

Using a candidate variant approach, 195 adult Filipino participants with newly diagnosed type 2 diabetes mellitus (T2DM) were enrolled in a case-control study. Genomic DNA from blood samples were collected. Allelic and genotypic associations of variants with poor response to metformin were determined using exact statistical methods.

Results

Several polymorphisms were nominally associated with poor response to metformin (P_uncorr < 0.05). The most notable is the association of multiple variants in the SLC2A10 gene—rs2425911, rs3092412, and rs2425904—with common additive genetic mode of inheritance. Other variants that have possible associations with poor drug response include rs340874 (PROX-AS1), rs815815 (CALM2), rs1333049 (CDKN2B-AS1), rs2010963 (VEGFA), rs1535435 and rs9494266 (AHI1), rs11128347 (PDZRN3), rs1805081 (NPC1), and rs13266634 (SLC30A8).

Conclusion

In Filipinos, a trend for the association for several variants was noted, with further observation that several mechanisms may be involved. The results may serve as pilot data for further validation of candidate variants for T2DM pharmacotherapy.

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.

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

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

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.

Personalized approach for type 2 diabetes pharmacotherapy: where are we and where do we need to be?

INTRODUCTION

Cluster analysis has identified distinct groups of type 2 diabetes (T2D) subjects with distinct metabolic characteristics. Thus, personalizing pharmacologic therapy to individual phenotypic and pathophysiologic characteristics has potential to improve metabolic control and reduce risk of microvascular and macrovascular complications.

AREAS COVERED

The authors review the classification of T2D, genetic markers, pathophysiology and natural history of T2D, the ABCDE approach to therapy, the ADA/EASD stepwise approach to therapy, available antidiabetic agents, and provide a more rational therapeutic approach based upon pathophysiology and cardiovascular and renal outcome trials.

EXPERT OPINION

Although insulin resistance is the earliest detectable abnormality, overt T2D does not occur in the absence of progressive beta cell failure. Because of the complex etiology of T2D (Ominous Octet), initiation of therapy with combined agents that (i) target both insulin resistance and beta cell dysfunction and (ii) prevent macrovascular, as well as microvascular, complications will be required. The ratio of C-peptide at 120 minutes (OGTT) to baseline C-peptide predicts with high sensitivity who will respond to metformin, the response to glucose-lowering agents and provides a useful tool to guide optimal glucose lowering therapy.

The L125F MATE1 variant enriched in populations of Amerindian origin is associated with increased plasma levels of metformin and lactate

Genetic factors that affect variability in metformin response have been poorly studied in the Latin American population, despite its being the initial drug therapy for type 2 diabetes, one of the most prevalent diseases in that region. Metformin pharmacokinetics is carried out by members of the membrane transporters superfamily (SLCs), being the multidrug and toxin extrusion protein 1 (MATE1), one of the most studied. Some genetic variants in MATE1 have been associated with reduced in vitro metformin transport. They include rs77474263 p.[L125F], a variant present at a frequency of 13.8% in Latin Americans, but rare worldwide (less than 1%). Using exome sequence data and TaqMan genotyping, we revealed that the Mexican population has the highest frequency of this variant: 16% in Mestizos and 27% in Amerindians, suggesting a possible Amerindian origin. To elucidate the metformin pharmacogenetics, a children cohort was genotyped, allowing us to describe, for the first time, a MATE1 rs77474263 TT homozygous individual. An additive effect of the L125F variant was observed on blood metformin accumulation, revealing the highest metformin and lactate serum levels in the TT homozygote, and intermediate metformin values in the heterozygotes. Moreover, a molecular dynamics analysis suggested that the genetic variant effect on metformin efflux could be due to a decreased protein permeability. We conclude that pharmacogenetics could be useful in enhancing metformin pharmacovigilance in populations having a high frequency of the risk genotype, especially considering that these populations also have a higher susceptibility to the diseases for which metformin is the first-choice drug.

Effects of a Common Eight Base Pairs Duplication at the Exon 7-Intron 7 Junction on Splicing, Expression, and Function of OCT1

Organic cation transporter 1 (OCT1, SLC22A1) is localized in the sinusoidal membrane of human hepatocytes and mediates hepatic uptake of weakly basic or cationic drugs and endogenous compounds. Common amino acid substitutions in OCT1 were associated with altered pharmacokinetics and efficacy of drugs like sumatriptan and fenoterol. Recently, the common splice variant rs35854239 has also been suggested to affect OCT1 function. rs35854239 represents an 8 bp duplication of the donor splice site at the exon 7-intron 7 junction. Here we quantified the extent to which this duplication affects OCT1 splicing and, as a consequence, the expression and the function of OCT1. We used pyrosequencing and deep RNA-sequencing to quantify the effect of rs35854239 on splicing after minigene expression of this variant in HepG2 and Huh7 cells and directly in human liver samples. Further, we analyzed the effects of rs35854239 on OCT1 mRNA expression in total, localization and activity of the resulting OCT1 protein, and on the pharmacokinetics of sumatriptan and fenoterol. The 8 bp duplication caused alternative splicing in 38% (deep RNA-sequencing) to 52% (pyrosequencing) of the minigene transcripts when analyzed in HepG2 and Huh7 cells. The alternatively spliced transcript encodes for a truncated protein that after transient transfection in HEK293 cells was not localized in the plasma membrane and was not able to transport the OCT1 model substrate ASP⁺. In human liver, however, the alternatively spliced OCT1 transcript was detectable only at very low levels (0.3% in heterozygous and 0.6% in homozygous carriers of the 8 bp duplication, deep RNA-sequencing). The 8 bp duplication was associated with a significant reduction of OCT1 expression in the human liver, but explained only 9% of the general variability in OCT1 expression and was not associated with significant changes in the pharmacokinetics of sumatriptan and fenoterol. Therefore, the rs35854239 variant only partially changes splicing, causing moderate changes in OCT1 expression and may be of only limited therapeutic relevance.

Organic Cation Transporter 1 an Intestinal Uptake Transporter: Fact or Fiction?

Intestinal transporter proteins are known to affect the pharmacokinetics and in turn the efficacy and safety of many orally administered drugs in a clinically relevant manner. This knowledge is especially well-established for intestinal ATP-binding cassette transporters such as P-gp and BCRP. In contrast to this, information about intestinal uptake carriers is much more limited although many hydrophilic or ionic drugs are not expected to undergo passive diffusion but probably require specific uptake transporters. A transporter which is controversially discussed with respect to its expression, localization and function in the human intestine is the organic cation transporter 1 (OCT1). This review article provides an up-to-date summary on the available data from expression analysis as well as functional studies in vitro, animal findings and clinical observations. The current evidence suggests that OCT1 is expressed in the human intestine in small amounts (on gene and protein levels), while its cellular localization in the apical or basolateral membrane of the enterocytes remains to be finally defined, but functional data point to a secretory function of the transporter at the basolateral membrane. Thus, OCT1 should not be considered as a classical uptake transporter in the intestine but rather as an intestinal elimination pathway for cationic compounds from the systemic circulation.

The Current and Potential Therapeutic Use of Metformin-The Good Old Drug

Metformin, one of the oldest oral antidiabetic agents and still recommended by almost all current guidelines as the first-line treatment for type 2 diabetes mellitus (T2DM), has become the medication with steadily increasing potential therapeutic indications. A broad spectrum of experimental and clinical studies showed that metformin has a pleiotropic activity and favorable effect in different pathological conditions, including prediabetes, type 1 diabetes mellitus (T1DM) and gestational diabetes mellitus (GDM). Moreover, there are numerous studies, meta-analyses and population studies indicating that metformin is safe and well tolerated and may be associated with cardioprotective and nephroprotective effect. Recently, it has also been reported in some studies, but not all, that metformin, besides improvement of glucose homeostasis, may possibly reduce the risk of cancer development, inhibit the incidence of neurodegenerative disease and prolong the lifespan. This paper presents some arguments supporting the initiation of metformin in patients with newly diagnosed T2DM, especially those without cardiovascular risk factors or without established cardiovascular disease or advanced kidney insufficiency at the time of new guidelines favoring new drugs with pleotropic effects complimentary to glucose control. Moreover, it focuses on the potential beneficial effects of metformin in patients with T2DM and coexisting chronic diseases.

Metformin and Chemoprevention: Potential for Heart-Healthy Targeting of Biologically Aggressive Breast Cancer

Currently, tamoxifen is the only drug approved for reduction of breast cancer risk in premenopausal women. The significant cardiovascular side effects of tamoxifen, coupled with lack of a survival benefit, potential for genotoxicity, and failure to provide a significant risk-reduction for estrogen receptor-negative breast cancer, all contribute to the low acceptance of tamoxifen chemoprevention in premenopausal women at high-risk for breast cancer. While other prevention options exist for postmenopausal women, there is a search for well-tolerated prevention agents that can simultaneously reduce risk of breast cancers, cardiovascular disease, and type-2 diabetes. Metformin is a well-tolerated oral biguanide hypoglycemic agent that is prescribed worldwide to over 120 million individuals with type-2 diabetes. Metformin is inexpensive, safe during pregnancy, and the combination of metformin, healthy lifestyle, and exercise has been shown to be effective in preventing diabetes. There is a growing awareness that prevention drugs and interventions should make the “whole woman healthy.” To this end, current efforts have focused on finding low toxicity alternatives, particularly repurposed drugs for chemoprevention of breast cancer, including metformin. Metformin's mechanisms of actions are complex but clearly involve secondary lowering of circulating insulin. Signaling pathways activated by insulin also drive biologically aggressive breast cancer and predict poor survival in women with breast cancer. The mechanistic rationale for metformin chemoprevention is well-supported by the scientific literature. Metformin is cheap, safe during pregnancy, and has the potential to provide heart-healthy breast cancer prevention. On-going primary and secondary prevention trials will provide evidence whether metformin is effective in preventing breast cancer.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

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

Epigenetic markers associated with metformin response and intolerance in drug-naïve patients with type 2 diabetes

Metformin is the first-line pharmacotherapy for managing type 2 diabetes (T2D). However, many patients with T2D do not respond to or tolerate metformin well. Currently, there are no phenotypes that successfully predict glycemic response to, or tolerance of, metformin. We explored whether blood-based epigenetic markers could discriminate metformin response and tolerance by analyzing genome-wide DNA methylation in drug-naïve patients with T2D at the time of their diagnosis. DNA methylation of 11 and 4 sites differed between glycemic responders/nonresponders and metformin-tolerant/intolerant patients, respectively, in discovery and replication cohorts. Greater methylation at these sites associated with a higher risk of not responding to or not tolerating metformin with odds ratios between 1.43 and 3.09 per 1-SD methylation increase. Methylation risk scores (MRSs) of the 11 identified sites differed between glycemic responders and nonresponders with areas under the curve (AUCs) of 0.80 to 0.98. MRSs of the 4 sites associated with future metformin intolerance generated AUCs of 0.85 to 0.93. Some of these blood-based methylation markers mirrored the epigenetic pattern in adipose tissue, a key tissue in diabetes pathogenesis, and genes to which these markers were annotated to had biological functions in hepatocytes that altered metformin-related phenotypes. Overall, we could discriminate between glycemic responders/nonresponders and participants tolerant/intolerant to metformin at diagnosis by measuring blood-based epigenetic markers in drug-naïve patients with T2D. This epigenetics-based tool may be further developed to help patients with T2D receive optimal therapy.

How Dysregulated Ion Channels and Transporters Take a Hand in Esophageal, Liver, and Colorectal Cancer

Over the last two decades, the understanding of how dysregulated ion channels and transporters are involved in carcinogenesis and tumor growth and progression, including invasiveness and metastasis, has been increasing exponentially. The present review specifies virtually all ion channels and transporters whose faulty expression or regulation contributes to esophageal, hepatocellular, and colorectal cancer. The variety reaches from Ca²⁺, K⁺, Na⁺, and Cl^- channels over divalent metal transporters, Na⁺ or Cl^- coupled Ca²⁺, HCO₃^- and H⁺ exchangers to monocarboxylate carriers and organic anion and cation transporters. In several cases, the underlying mechanisms by which these ion channels/transporters are interwoven with malignancies have been fully or at least partially unveiled. Ca²⁺, Akt/NF-κB, and Ca²⁺- or pH-dependent Wnt/β-catenin signaling emerge as cross points through which ion channels/transporters interfere with gene expression, modulate cell proliferation, trigger epithelial-to-mesenchymal transition, and promote cell motility and metastasis. Also miRs, lncRNAs, and DNA methylation represent potential links between the misexpression of genes encoding for ion channels/transporters, their malfunctioning, and cancer. The knowledge of all these molecular interactions has provided the basis for therapeutic strategies and approaches, some of which will be broached in this review.

Whole-blood transcriptome profiling reveals signatures of metformin and its therapeutic response

Metformin, a biguanide agent, is the first-line treatment for type 2 diabetes mellitus due to its glucose-lowering effect. Despite its wide application in the treatment of multiple health conditions, the glycemic response to metformin is highly variable, emphasizing the need for reliable biomarkers. We chose the RNA-Seq-based comparative transcriptomics approach to evaluate the systemic effect of metformin and highlight potential predictive biomarkers of metformin response in drug-naïve volunteers with type 2 diabetes in vivo. The longitudinal blood-derived transcriptome analysis revealed metformin-induced differential expression of novel and previously described genes involved in cholesterol homeostasis (SLC46A1 and LRP1), cancer development (CYP1B1, STAB1, CCR2, TMEM176B), and immune responses (CD14, CD163) after administration of metformin for three months. We demonstrate for the first time a transcriptome-based molecular discrimination between metformin responders (delta HbA1c ≥ 1% or 12.6 mmol/mol) and non-responders (delta HbA1c < 1% or 12.6 mmol/mol), that is determined by expression levels of 56 genes, explaining 13.9% of the variance in the therapeutic efficacy of the drug. Moreover, we found a significant upregulation of IRS2 gene (log₂FC 0.89) in responders compared to non-responders before the use of metformin. Finally, we provide evidence for the mitochondrial respiratory complex I as one of the factors related to the high variability of the therapeutic response to metformin in patients with type 2 diabetes mellitus.

Obesity, clinical, and genetic predictors for glycemic progression in Chinese patients with type 2 diabetes: A cohort study using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank

BACKGROUND

Type 2 diabetes (T2D) is a progressive disease whereby there is often deterioration in glucose control despite escalation in treatment. There is significant heterogeneity to this progression of glycemia after onset of diabetes, yet the factors that influence glycemic progression are not well understood. Given the tremendous burden of diabetes in the Chinese population, and limited knowledge on factors that influence glycemia, we aim to identify the clinical and genetic predictors for glycemic progression in Chinese patients with T2D.

METHODS AND FINDINGS

In 1995-2007, 7,091 insulin-naïve Chinese patients (mean age 56.8 ± 13.3 [SD] years; mean age of T2D onset 51.1 ± 12.7 years; 47% men; 28.4% current or ex-smokers; median duration of diabetes 4 [IQR: 1-9] years; mean HbA1c 7.4% ± 1.7%; mean body mass index [BMI] 25.3 ± 4.0 kg/m2) were followed prospectively in the Hong Kong Diabetes Register. We examined associations of BMI and other clinical and genetic factors with glycemic progression defined as requirement of continuous insulin treatment, or 2 consecutive HbA1c ≥8.5% while on ≥2 oral glucose-lowering drugs (OGLDs), with validation in another multicenter cohort of Hong Kong Diabetes Biobank. During a median follow-up period of 8.8 (IQR: 4.8-13.3) years, incidence of glycemic progression was 48.0 (95% confidence interval [CI] 46.3-49.8) per 1,000 person-years with 2,519 patients started on insulin. Among the latter, 33.2% had a lag period of 1.3 years before insulin was initiated. Risk of progression was associated with extremes of BMI and high HbA1c. On multivariate Cox analysis, early age at diagnosis, microvascular complications, high triglyceride levels, and tobacco use were additional independent predictors for glycemic progression. A polygenic risk score (PRS) including 123 known risk variants for T2D also predicted rapid progression to insulin therapy (hazard ratio [HR]: 1.07 [95% CI 1.03-1.12] per SD; P = 0.001), with validation in the replication cohort (HR: 1.24 [95% CI 1.06-1.46] per SD; P = 0.008). A PRS using 63 BMI-related variants predicted BMI (beta [SE] = 0.312 [0.057] per SD; P = 5.84 × 10-8) but not glycemic progression (HR: 1.01 [95% CI 0.96-1.05] per SD; P = 0.747). Limitations of this study include potential misdiagnosis of T2D and lack of detailed data of drug use during follow-up in the replication cohort.

CONCLUSIONS

Our results show that approximately 5% of patients with T2D failed OGLDs annually in this clinic-based cohort. The independent associations of modifiable and genetic risk factors allow more precise identification of high-risk patients for early intensive control of multiple risk factors to prevent glycemic progression.

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.

Intronic Variants in OCT1 are Associated with All-Cause and Cardiovascular Mortality in Metformin Users with Type 2 Diabetes

PURPOSE

Organic cation transporters (Octs) use cations like endogenous compounds, toxins, and drugs, such as metformin, as substrates. Therefore, these proteins determine the pharmacokinetics and -dynamics of metformin and thus its efficacy. Of note, metformin is today the most commonly used pharmaceutical in the treatment of type 2 diabetes (T2DM) with nevertheless a great variability in clinical response, which attributes to genetic variances. The aim of this study was to determine the influence of intronic OCT1 SNPs on prevalence of all-cause and cardiovascular death.

PATIENTS AND METHODS

Genotypes of 27 intronic SNPs in OCT1 were investigated in the LURIC study, a prospective cohort of 3316 participants scheduled for coronary angiography. We investigated whether these variants were associated with all-cause and cardiovascular death in 73 individuals with T2DM under metformin therapy, in individuals without diabetes, individuals with T2DM and individuals with T2DM without metformin therapy.

RESULTS

In a multivariate Cox regression analysis adjusted for classical cardiovascular risk factors, 4 intronic OCT1 SNPs were significantly associated with all-cause and cardiovascular mortality in individuals with T2DM on metformin therapy.

CONCLUSION

According to their OCT1 genotype, some individuals with T2DM on metformin therapy might be prone to an increased risk of cardiovascular death.

The Brain Exposure Efficiency (BEE) Score

The blood-brain barrier (BBB), composed of microvascular tight junctions and glial cell sheathing, selectively controls drug permeation into the central nervous system (CNS) by either passive diffusion or active transport. Computational techniques capable of predicting molecular brain penetration are important to neurological drug design. A novel prediction algorithm, termed the Brain Exposure Efficiency Score (BEE), is presented. BEE addresses the need to incorporate the role of trans-BBB influx and efflux active transporters by considering key brain penetrance parameters, namely, steady state unbound brain to plasma ratio of drug (K_p,uu) and dose normalized unbound concentration of drug in brain (C_u,b). BEE was devised using quantitative structure-activity relationships (QSARs) and molecular modeling studies on known transporter proteins and their ligands. The developed algorithms are provided as a user-friendly open source calculator to assist in optimizing a brain penetrance strategy during the early phases of small molecule molecular therapeutic design.

Transcriptomic analysis of human primary breast cancer identifies fatty acid oxidation as a target for metformin

BACKGROUND

Epidemiological studies suggest that metformin may reduce the incidence of cancer in patients with diabetes and multiple late phase clinical trials assessing the potential of repurposing this drug are underway. Transcriptomic profiling of tumour samples is an excellent tool to understand drug bioactivity, identify candidate biomarkers and assess for mechanisms of resistance to therapy.

METHODS

Thirty-six patients with untreated primary breast cancer were recruited to a window study and transcriptomic profiling of tumour samples carried out before and after metformin treatment.

RESULTS

Multiple genes that regulate fatty acid oxidation were upregulated at the transcriptomic level and there was a differential change in expression between two previously identified cohorts of patients with distinct metabolic responses. Increase in expression of a mitochondrial fatty oxidation gene composite signature correlated with change in a proliferation gene signature. In vitro assays showed that, in contrast to previous studies in models of normal cells, metformin reduces fatty acid oxidation with a subsequent accumulation of intracellular triglyceride, independent of AMPK activation.

CONCLUSIONS

We propose that metformin at clinical doses targets fatty acid oxidation in cancer cells with implications for patient selection and drug combinations.

CLINICAL TRIAL REGISTRATION

NCT01266486.

Metformin does not compromise energy status in human skeletal muscle at rest or during acute exercise: A randomised, crossover trial

5´AMP-activated protein kinase (AMPK) is a mediator of a healthy metabolic phenotype in skeletal muscle. Metformin may exacerbate the energy disturbances observed during exercise leading to enhanced AMPK activation, and these disturbances may provoke early muscular fatigue. We studied acute (1 day) and short-term (4 days) effects of metformin treatment on AMPK and its downstream signaling network, in healthy human skeletal muscle and adipose tissue at rest and during exercise, by applying a randomized blinded crossover study design in 10 lean men. Muscle and fat biopsies were obtained before and after the treatment period at rest and after a single bout of exercise. Metformin treat ment elicited peak plasma and muscle metformin concentrations of 31 μM and 11 μM, respectively. Neither of the treatments affected AMPK activity in skeletal muscle and adipose at rest or during exercise. In contrast, whole-body stress during exercise was elevated as indicated by increased plasma lactate and adrenaline concentrations as well as increased heart rate and rate of perceived exertion. Also whole-body insulin sensitivity was enhanced by 4 days metformin treatment, that is reduced fasting plasma insulin and HOMA-IR. In conclusion, acute and short-term metformin treatment does not affect energy homeostasis and AMPK activation at rest or during exercise in skeletal muscle and adipose tissue of healthy subjects. However, metformin treatment is accompanied by slightly enhanced perceived exertion and whole-body stress which may provoke a lesser desire for physical activity in the metformin-treated patients.

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.

Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin’s action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.

Role of OCT1 in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers causing death worldwide. It is difficult to detect at an early stage and most patients with advanced HCC rarely achieve satisfying therapeutic results. Accordingly, researchers have been trying to find new biomarkers for diagnosis and new methods of treatment. OCT1, a member of solute carrier super family, is highly expressed in normal liver tissues, and predominantly transports endogenous and exogenous substances, such as metabolites, drugs and toxins to hepatocytes. Studies have demonstrated that the expression of OCT1 is related to the progression and survival of HCC patients. Furthermore, sorafenib, which is regarded as the only effective molecular targeting drug for advanced HCC, is affected by OCT1 variants. In the current review, we summarized the reports about OCT1 and HCC in order to present a comprehensive overview of the relationship between OCT1 and HCC.

Effects of Comedication and Genetic Factors on the Population Pharmacokinetics of Lamotrigine: A Prospective Analysis in Chinese Patients With Epilepsy

Lamotrigine (LTG) is a second-generation anti-epileptic drug widely used for focal and generalized seizures in adults and children, and as a first-line medication in pregnant women and women of childbearing age. However, LTG pharmacokinetics shows high inter-individual variability, thus potentially leading to therapeutic failure or side effects in patients. This prospective study aimed to establish a population pharmacokinetics model for LTG in Chinese patients with epilepsy and to investigate the effects of genetic variants in uridine diphosphate glucuronosyltransferase (UGT) 1A4, UGT2B7, MDR1, ABCG2, ABCC2, and SLC22A1, as well as non-genetic factors, on LTG pharmacokinetics. The study population consisted of 89 patients with epilepsy, with 419 concentrations of LTG. A nonlinear mixed effects model was implemented in NONMEM software. A one-compartment model with first-order input and first-order elimination was found to adequately characterize LTG concentration. The population estimates of the apparent volume of distribution (V/F) and apparent clearance (CL/F) were 12.7 L and 1.12 L/h, respectively. The use of valproic acid decreased CL/F by 38.5%, whereas the co-administration of rifampicin caused an increase in CL/F of 64.7%. The CL/F decreased by 52.5% in SLC22A1-1222AA carriers. Patients with the ABCG2-34AA genotype had a 42.0% decrease in V/F, whereas patients with the MDR1-2677TT and C3435TT genotypes had a 136% increase in V/F. No obvious genetic effect of UGT enzymes was found relative to the concentrations of LTG in Chinese patients. Recommended dose regimens for patients with different gene polymorphisms and comedications were estimated on the basis of Monte Carlo simulations and the established model. These findings should be valuable for developing individualized dosage regimens in adult and adolescent Chinese patients 13–65 years of age.

Efficacious dose of metformin for breast cancer therapy is determined by cation transporter expression in tumours

BACKGROUND AND PURPOSE

It has been extensively reported that the leading anti-diabetic drug, metformin, exerts significant anticancer effects. This hydrophilic, cationic drug requires cation transporters for cellular entry where it activates its intracellular target, the AMPK signalling pathway. However, clinical results on metformin therapy (used at antidiabetic doses) for breast cancer are ambiguous. It is likely that the antidiabetic dose is inadequate in patients that have breast tumours with low cation transporter expression, resulting in non-responsiveness to the drug. We postulate that cation transporter expression and metformin dose are key determinants in its antitumour efficacy in breast cancer.

EXPERIMENTAL APPROACH

Antitumour efficacy of metformin was compared between low cation transporter-expressing MCF-7 breast tumours and MCF-7 tumours overexpressing organic cation transporter 3 (OCT3-MCF7). A dose-response relationship of metformin in combination with standard-of-care paclitaxel (for oestrogen receptor-positive MCF-7 breast tumours) or carboplatin (for triple-negative MDA-MB-468 breast tumours) was investigated in xenograft mice.

KEY RESULTS

Metformin had greater efficacy against tumours with higher cation transporter expression, as observed in OCT3-MCF7 versus MCF-7 tumours and MDA-MB-468 versus MCF-7 tumours. In MCF-7 tumours, a threefold higher metformin dose was required to achieve intratumoural exposure that was comparable to exposure in MDA-MB-468 tumours and enhance antitumour efficacy of standard-of-care in MCF-7 tumours versus MDA-MB-468 tumours. Antitumour efficacy correlated with intratumoural AMPK activation and metformin concentration.

CONCLUSIONS AND IMPLICATIONS

An efficacious metformin dose for breast cancer varies among tumour subtypes based on cation transporter expression, which provides a useful guide for dose selection.

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.

Association between Polymorphisms of OCT1 and Metabolic Response to Metformin in Women with Polycystic Ovary Syndrome

Insulin-sensitizer treatment with metformin is widely used in polycystic ovary syndrome (PCOS). However, the treatment effectiveness shows individual differences in PCOS patients. Organic cation transporter (OCT) 1 and 2 have been reported to mediate metformin transport in the liver and kidney, respectively. In this study, we investigated the association between the polymorphisms of OCT1 and OCT2 and the treatment effectiveness of metformin in PCOS patients. The single nucleotide polymorphisms (SNPs) of OCT1 (rs683369 and rs628031) and OCT2 (rs316019) were analyzed in 87 PCOS and 113 control women. Oral glucose tolerance tests (OGTTs), which represented metformin treatment response, were conducted at the start of treatment and after six-month treatment. The results demonstrated that the SNP frequencies of OCT1 and OCT2 were not associated with PCOS pathophysiology, and that the polymorphisms of OCT1 and OCT2 were not associated with the OGTT parameters at baseline. However, PCOS patients with the G allele of OCT1 rs683369 and/or with the A allele of OCT1 rs628031 had increased insulin sensitivity compared to those with wild-type genotype after receiving metformin treatment. Moreover, the interactions of metformin*SNP were significant in both OCT1 rs683369 (p < 0.001) and rs628031 (p = 0.001) during the treatment period. Taken together, genetic polymorphisms of OCT1 contributed to different metformin treatment responses, and further study is needed to establish personalized treatment programs using a pharmacogenomic algorithm approach in PCOS patients.

Physiologically-Based Pharmacokinetic Modeling Analysis for Quantitative Prediction of Renal Transporter-Mediated Interactions Between Metformin and Cimetidine

Metformin is an important antidiabetic drug and often used as a probe for drug–drug interactions (DDIs) mediated by renal transporters. Despite evidence supporting the inhibition of multidrug and toxin extrusion proteins as the likely DDI mechanism, the previously reported physiologically‐based pharmacokinetic (PBPK) model required the substantial lowering of the inhibition constant values of cimetidine for multidrug and toxin extrusion proteins from those obtained in vitro to capture the clinical DDI data between metformin and cimetidine.¹ We constructed new PBPK models in which the transporter‐mediated uptake of metformin is driven by a constant membrane potential. Our models successfully captured the clinical DDI data using in vitro inhibition constant values and supported the inhibition of multidrug and toxin extrusion proteins by cimetidine as the DDI mechanism upon sensitivity analysis and data fitting. Our refined PBPK models may facilitate prediction approaches for DDI involving metformin using in vitro inhibition constant values.

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.

Epigenetic events involved in organic cation transporter 1-dependent impaired response of hepatocellular carcinoma to sorafenib

BACKGROUND AND PURPOSE

The expression of the human organic cation transporter-1 (hOCT1, gene SLC22A1) is reduced in hepatocellular carcinoma (HCC). The molecular bases of this reduction and its relationship with the poor response of HCC to sorafenib were investigated.

EXPERIMENTAL APPROACH

HCC transcriptomes from 366 samples available at TCGA were analysed. Alternative splicing was determined by RT-PCR. The role of miRNAs in SLC22A1 downregulation was investigated. Expression of Oct1 was measured in rodent HCC models (spontaneously generated in Fxr^-/- mice and chemically-induced in rats). hOCT1 was overexpressed in human hepatoma cells (HuH7 and HepG2). Sorafenib and regorafenib uptake was determined by HPLC-MS/MS.

KEY RESULTS

hOCT1 overexpression enhanced sorafenib, but not regorafenib, quinine-inhibitable uptake by hepatoma cells. In rodent HCC, Oct1 was downregulated, which was accompanied by impaired sorafenib uptake. In mice with s.c.-implanted HCC, sorafenib inhibited the growth of hOCT1 overexpressing tumours. In human HCC, hOCT1 expression was inversely correlated with SLC22A1 promoter methylation, whereas demethylation with decitabine enhanced hOCT1 expression in hepatoma cells. Increased proportion of aberrant hOCT1 mRNA variants was found in HCC samples. In silico analysis identified six miRNAs as candidates to target hOCT1 mRNA. When overexpressed in HepG2 cells a significant hOCT1 mRNA decay was induced by hsa-miR-330 and hsa-miR-1468. Analysis of 39 paired tumour/adjacent samples from TCGA revealed that hsa-mir-330 was consistently upregulated in HCC.

CONCLUSION AND IMPLICATIONS

Impaired hOCT1 expression/function in HCC, in part due to epigenetic modifications, plays an important role in the poor pharmacological response of this cancer to sorafenib.

Variability in the therapeutic response of Metformin treatment in patients with type 2 diabetes mellitus

Objective

To assess the glycemic response of metformin in patients with Type-2 Diabetes Mellitus (T2DM) as well as to see its association with reductions in BMI and GIT intolerance.

Methods

This Quasi, Experimental study was conducted at Jinnah-Allama Iqbal Institute of Diabetes and Endocrinology (JAIDE) Jinnah Hospital, Lahore from 1^st March 2016 to 30^th September 2016. Newly diagnosed T2DM patients were given metformin for duration of three months and later on they were categorized into Responders and Non-Responders on the basis of HbA1c (A1C) reductions, which were estimated by Hemoglobin (A1C) analyzer (TD4611A TAIDoc Tech. Taiwan) through photometry. Similarly, baseline BMI and BMI after three months therapy with metformin was also recorded.

Results

Among total of 200 patients, 40.5% of the patients were classified as Non-Responders whereas; 59.5% of the patients as Responders. The baseline BMI (26.09 kg/m²) was also decreased significantly after metformin therapy (25.40 kg/m²). It was found that metformin reduced the A1C in all the patients. However, the glycemic control was much better in patients with higher baseline A1C (1.13% ± 0.08) as compared to lower baseline levels (0.61% ± 0.07). Regarding GIT intolerance, 140 patients lacked the symptoms, out of which 60.7% were responders and 39.3% were non-responders.

Conclusions

Metformin lead to improvement in glycemic control in 59.5% of newly diagnosed T2DM patients after taking metformin for three months but in 40.5% it did not which may be because of combined effects of various gene polymorphisms and their interaction with non-genetic factors. Metformin reduced the BMI in all the patients; however, BMI lowering activity of metformin was same regardless of its effect on HbA1C. Moreover, the signs and symptoms of GIT intolerance did not differ between the two groups.