The pharmacogenetics of metformin

Tailoring Type II Diabetes Treatment: Investigating the Effect of 5-HTT Polymorphisms on HbA1c Levels after Metformin Initiation

Aims

To investigate the effect of serotonin transporter (5-HTT) polymorphisms on change in HbA1c levels six months after metformin initiation in type 2 diabetes patients.

Materials and Methods

Participants of PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALidation of biomarkers) within the GIANTT (Groningen Initiative to ANalyse Type 2 Diabetes Treatment) cohort who initiated metformin were genotyped for combined 5-HTTLPR/rs25531 (L∗L∗, L∗S∗, and S∗S∗) and 5-HTT VNTR (STin 2.12, 12/-, and 10/-) polymorphisms, respectively. Multiple linear regression was applied to determine the change in HbA1c level from baseline date to six months across 5-HTTLPR/VNTR genotype groups, adjusted for baseline HbA1c, age, gender, triglyceride level, low-density lipoprotein level, and serum creatinine.

Results

157 participants were included, of which 56.2% were male. The average age was 59.3 ± 9.23 years, and the mean baseline HbA1c was 7.49% ± 1.21%. 5-HTTLPR was characterized in 46 patients as L∗L∗, 70 patients as L∗S∗, and 41 patients as S∗S∗ genotypes. No significant association was found between 5-HTTLPR and 5-HTT VNTR genotypes and change in HbA1c after adjustments.

Conclusions

5-HTT polymorphisms did not affect HbA1c levels six months after the start of metformin. Further long-term studies in large samples would be relevant to determine which polymorphisms can explain the variation in response to metformin treatment.

Frailty in end-stage liver disease: Understanding pathophysiology, tools for assessment, and strategies for management

Frailty and sarcopenia are frequently observed in patients with end-stage liver disease. Frailty is a complex condition that arises from deteriorations across various physiological systems, including the musculoskeletal, cardiovascular, and immune systems, resulting in a reduced ability of the body to withstand stressors. This condition is associated with declined resilience and increased vulnerability to negative outcomes, including disability, hospitalization, and mortality. In cirrhotic patients, frailty is influenced by multiple factors, such as hyperammonemia, hormonal imbalance, malnutrition, ascites, hepatic encephalopathy, and alcohol intake. Assessing frailty is crucial in predicting morbidity and mortality in cirrhotic patients. It can aid in making critical decisions regarding patients' eligibility for critical care and transplantation. This, in turn, can guide the development of an individualized treatment plan for each patient with cirrhosis, with a focus on prioritizing exercise, proper nutrition, and appropriate treatment of hepatic complications as the primary lines of treatment. In this review, we aim to explore the topic of frailty in liver diseases, with a particular emphasis on pathophysiology, clinical assessment, and discuss strategies for preventing frailty through effective treatment of hepatic complications. Furthermore, we explore novel assessment and management strategies that have emerged in recent years, including the use of wearable technology and telemedicine.

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.

Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study

Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.

Improving the effectiveness of anti-aging modalities by using the constrained disorder principle-based management algorithms

Aging is a complex biological process with multifactorial nature underlined by genetic, environmental, and social factors. In the present paper, we review several mechanisms of aging and the pre-clinically and clinically studied anti-aging therapies. Variability characterizes biological processes from the genome to cellular organelles, biochemical processes, and whole organs' function. Aging is associated with alterations in the degrees of variability and complexity of systems. The constrained disorder principle defines living organisms based on their inherent disorder within arbitrary boundaries and defines aging as having a lower variability or moving outside the boundaries of variability. We focus on associations between variability and hallmarks of aging and discuss the roles of disorder and variability of systems in the pathogenesis of aging. The paper presents the concept of implementing the constrained disease principle-based second-generation artificial intelligence systems for improving anti-aging modalities. The platform uses constrained noise to enhance systems' efficiency and slow the aging process. Described is the potential use of second-generation artificial intelligence systems in patients with chronic disease and its implications for the aged population.

Evaluating the efficacy and mechanism of metformin targets on reducing Alzheimer's disease risk in the general population: a Mendelian randomisation study

AIMS/HYPOTHESIS

Metformin use has been associated with reduced incidence of dementia in diabetic individuals in observational studies. However, the causality between the two in the general population is unclear. This study uses Mendelian randomisation (MR) to investigate the causal effect of metformin targets on Alzheimer's disease and potential causal mechanisms in the brain linking the two.

METHODS

Genetic proxies for the effects of metformin drug targets were identified as variants in the gene for the corresponding target that associated with HbA1c level (N=344,182) and expression level of the corresponding gene (N≤31,684). The cognitive outcomes were derived from genome-wide association studies comprising 527,138 middle-aged Europeans, including 71,880 with Alzheimer's disease or Alzheimer's disease-by-proxy. MR estimates representing lifelong metformin use on Alzheimer's disease and cognitive function in the general population were generated. Effect of expression level of 22 metformin-related genes in brain cortex (N=6601 donors) on Alzheimer's disease was further estimated.

RESULTS

Genetically proxied metformin use, equivalent to a 6.75 mmol/mol (1.09%) reduction on HbA1c, was associated with 4% lower odds of Alzheimer's disease (OR 0.96 [95% CI 0.95, 0.98], p=1.06×10-4) in non-diabetic individuals. One metformin target, mitochondrial complex 1 (MCI), showed a robust effect on Alzheimer's disease (OR 0.88, p=4.73×10-4) that was independent of AMP-activated protein kinase. MR of expression in brain cortex tissue showed that decreased MCI-related gene (NDUFA2) expression was associated with lower Alzheimer's disease risk (OR 0.95, p=4.64×10-4) and favourable cognitive function.

CONCLUSIONS/INTERPRETATION

Metformin use may cause reduced Alzheimer's disease risk in the general population. Mitochondrial function and the NDUFA2 gene are plausible mechanisms of action in dementia protection.

Literature review of the clinical characteristics of metformin-induced hepatotoxicity

Background: Knowledge of metformin-induced hepatotoxicity is based on case reports. The aim of this study was to investigate the clinical features of metformin-induced hepatotoxicity. Methods: We collected relevant literature on metformin-induced hepatotoxicity published from January 1994 to February 2022 by searching Chinese and English databases. Results: Thirty patients (19 males and 11 females) from 29 articles were included, with a median age of 61 years (range 29-83). The median time to onset of liver injury was 4 weeks (range 0.3-648) after metformin administration. Clinical symptoms occurred in 28 patients, including gastrointestinal reactions (56.7%), jaundice (50.0%), fatigue (36.7%), anorexia (23.3%), pruritus (13.3%), dark urine (13.3%), and clay-colored stools (10.0%). Serum alanine transaminase, aspartate transaminase, γ-glutamyl transferase, total bilirubin and alkaline phosphatase were elevated to varying degrees. Liver imaging in 26 patients showed hepatic steatosis (6 cases, 23.1%) and gallbladder wall thickening (11.5%). Liver biopsies from 13 patients showed portal phlebitis (61.5%), cholestatic hepatitis (38.5%), and parenchymal inflammation (38.5%). After metformin discontinuation, liver function returned to normal levels at a median of 6 weeks (range 2-16). Conclusions: Metformin-induced hepatotoxicity is a rare adverse reaction. Physicians and patients should be alert to metformin-induced hepatotoxicity.

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.

Metformin: When Should We Fear Lactic Acidosis?

Metformin, a molecule belonging to the biguanide family, represents one of the most commonly prescribed medications for the treatment of diabetes mellitus in the world. Over the sixty years during which it has been used, many benefits have been described, which are not limited to the treatment of diabetes mellitus. However, since metformin is similar to other members of the same drug family, there is still much concern regarding the risk of lactic acidosis. This article aims to highlight the correlation between the use of metformin and the onset of renal damage or lactic acidosis. Metformin-associated lactic acidosis exists; however, it is rare. The appropriate use of the drug, under safe conditions, induces benefits without risks.

The influence of SLC22A3 rs543159 and rs1317652 genetic variants on metformin therapeutic efficacy in newly diagnosed patients with type 2 diabetes mellitus: 25 weeks follow-up study

BACKGROUND AND AIMS

Among anti-diabetic medications, metformin has been proven to be the preferred initial pharmacologic agent for type 2 diabetes mellitus (T2DM) treatment. Despite its safety and efficacy, the response to metformin varies between individuals. Genetic variations, especially within genes involved in pharmacokinetics and pharmacodynamics of metformin (e.g SLC22A3), have been suggested to be responsible for the observed inter-individual differences. By considering the undeniable role of organic cation transporter 3 in hepatic uptake of metformin, this study was aimed to investigate the association of rs543159 and rs1317652 variants in SLC22A3 gene with response to metformin monotherapy in newly diagnosed patients with T2DM.

METHODS

The study included 200 T2DM patients who received metformin monotherapy for 25 weeks. The patients were classified into 2 groups according to their HbA1c values: the responders (reduction in HbA1c levels by at least 1% after 25 weeks treatment with metformin) and non-responders (less than 1% reduction in HbA1c levels after 25 weeks treatment with metformin). We used tetra ARMS-PCR method to determine genotypes of the target variants.

RESULTS

For the rs543159, CA and AA genotypes were more frequent in responders as compared to non-responders (OR = 2.48; 95% CI = 1.28-4.78, P-value = 0.0057) under the dominant model. In case of rs1317652 CC and CT genotypes were more frequent in metformin responders as compared to non-responder group (OR = 2.49; 95% CI = 1.32-4.70, P-value = 0.0043) under the dominant model. Parameters such as fasting blood sugar (FBS), HbA1c, and total cholesterol (TC) levels were significantly lower in the responder group after 25 weeks of metformin monotherapy. Moreover, according to the result of multiple linear regression rs543159 and base line HbA1c values are significantly associated with response to metformin monotherapy.

CONCLUSION

Our results suggested that rs543159 and rs1317652 in SLC22A3 gene might be associated with variability in response to metformin therapy in T2DM patients.

Considerations Regarding Public Use of Longevity Interventions

Public attention and interest for longevity interventions are growing. These can include dietary interventions such as intermittent fasting, physical interventions such as various exercise regimens, or through supplementation of nutraceuticals or administration of pharmaceutics. However, it is unlikely that most interventions identified in model organisms will translate to humans, or that every intervention will benefit each person equally. In the worst case, even detrimental health effects may occur. Therefore, identifying longevity interventions using human data and tracking the aging process in people is of paramount importance as we look towards longevity interventions for the public. In this work, we illustrate how to identify candidate longevity interventions using population data in humans, an approach we have recently employed. We consider metformin as a case-study for potential confounders that influence effectiveness of a longevity intervention, such as lifestyle, sex, genetics, age of administration and the microbiome. Indeed, metformin, like most other longevity interventions, may end up only benefitting a subgroup of individuals. Fortunately, technologies have emerged for tracking the rate of ‘biological’ aging in individuals, which greatly aids in assessing effectiveness. Recently, we have demonstrated that even wearable devices, accessible to everyone, can be used for this purpose. We therefore propose how to use such approaches to test interventions in the general population. In summary, we advocate that 1) not all interventions will be beneficial for each individual and therefore 2) it is imperative that individuals track their own aging rates to assess healthy aging interventions.

Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome

Metabolic syndrome (MetS) is a highly heritable disease and a major public health burden worldwide. MetS diagnosis criteria are met by the simultaneous presence of any three of the following: high triglycerides, low HDL/high LDL cholesterol, insulin resistance, hypertension, and central obesity. These diseases act synergistically in people suffering from MetS and dramatically increase risk of morbidity and mortality due to stroke and cardiovascular disease, as well as certain cancers. Each of these component features is itself a complex disease, as is MetS. As a genetically complex disease, genetic risk factors for MetS are numerous, but not very powerful individually, often requiring specific environmental stressors for the disease to manifest. When taken together, all sequence variants that contribute to MetS disease risk explain only a fraction of the heritable variance, suggesting additional, novel loci have yet to be discovered. In this article, we will give a brief overview on the genetic concepts needed to interpret genome-wide association studies (GWAS) and quantitative trait locus (QTL) data, summarize the state of the field of MetS physiological genomics, and to introduce tools and resources that can be used by the physiologist to integrate genomics into their own research on MetS and any of its component features. There is a wealth of phenotypic and molecular data in animal models and humans that can be leveraged as outlined in this article. Integrating these multi-omic QTL data for complex diseases such as MetS provides a means to unravel the pathways and mechanisms leading to complex disease and promise for novel treatments. © 2022 American Physiological Society. Compr Physiol 12:1-40, 2022.

Impaired metabolic effects of metformin in men with early-onset androgenic alopecia

Background

Early-onset androgenic alopecia is considered the phenotypic equivalent of polycystic ovary syndrome in men. The purpose of the current study was to investigate whether the presence of early-onset male-pattern baldness modulates metabolic effects of metformin.

Methods

This prospective case–control study included 2 groups of men at high risk for type 2 diabetes: 72 individuals with androgenic alopecia (group A) and 75 subjects with normal hair growth (group B). Both groups were matched for age, blood pressure, body mass index, insulin sensitivity and plasma lipids. Glycated hemoglobin, glucose, plasma lipids, indices of insulin sensitivity/resistance, sex hormones, high-sensitivity C-reactive protein (hsCRP) and 25-hydroxyvitamin D were determined before and after metformin treatment (1.7 g daily).

Results

Twelve-month metformin treatment reduced fat content, waist circumference, glycated hemoglobin, glucose and triglycerides, as well as improved insulin sensitivity. Although observed in both study populations, these effects were more pronounced in group B. Moreover, metformin decreased hsCRP and bioavailable testosterone levels in group B, as well as reduced 25-hydroxyvitamin D concentration in group A. Treatment-induced changes in glucose homeostasis markers correlated with the impact of metformin on hsCRP and 25-hydroxyvitamin D levels.

Conclusions

Metabolic effects of metformin in males are attenuated if they have coexisting early-onset androgenic alopecia. This finding may be partially explained by differences in severity of low-grade systemic inflammation and vitamin D status. The obtained results, requiring confirmation in large prospective studies, suggest that men with early-onset male-pattern baldness benefit to a lesser degree from metformin treatment than other men at high risk for type 2 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43440-021-00347-8.

Integrated or Independent Actions of Metformin in Target Tissues Underlying Its Current Use and New Possible Applications in the Endocrine and Metabolic Disorder Area

Metformin is considered the first-choice drug for type 2 diabetes treatment. Actually, pleiotropic effects of metformin have been recognized, and there is evidence that this drug may have a favorable impact on health beyond its glucose-lowering activity. In summary, despite its long history, metformin is still an attractive research opportunity in the field of endocrine and metabolic diseases, age-related diseases, and cancer. To this end, its mode of action in distinct cell types is still in dispute. The aim of this work was to review the current knowledge and recent findings on the molecular mechanisms underlying the pharmacological effects of metformin in the field of metabolic and endocrine pathologies, including some endocrine tumors. Metformin is believed to act through multiple pathways that can be interconnected or work independently. Moreover, metformin effects on target tissues may be either direct or indirect, which means secondary to the actions on other tissues and consequent alterations at systemic level. Finally, as to the direct actions of metformin at cellular level, the intracellular milieu cooperates to cause differential responses to the drug between distinct cell types, despite the primary molecular targets may be the same within cells. Cellular bioenergetics can be regarded as the primary target of metformin action. Metformin can perturb the cytosolic and mitochondrial NAD/NADH ratio and the ATP/AMP ratio within cells, thus affecting enzymatic activities and metabolic and signaling pathways which depend on redox- and energy balance. In this context, the possible link between pyruvate metabolism and metformin actions is extensively discussed.

Estimating heritability of glycaemic response to metformin using nationwide electronic health records and population-sized pedigree

Background

Variability of response to medication is a well-known phenomenon, determined by both environmental and genetic factors. Understanding the heritable component of the response to medication is of great interest but challenging due to several reasons, including small study cohorts and computational limitations.

Methods

Here, we study the heritability of variation in the glycaemic response to metformin, first-line therapeutic agent for type 2 diabetes (T2D), by leveraging 18 years of electronic health records (EHR) data from Israel’s largest healthcare service provider, consisting of over five million patients of diverse ethnicities and socio-economic background. Our cohort consists of 80,788 T2D patients treated with metformin, with an accumulated number of 1,611,591 HbA1C measurements and 4,581,097 metformin prescriptions. We estimate the explained variance of glycated hemoglobin (HbA1c%) reduction due to inheritance by constructing a six-generation population-size pedigree from national registries and linking it to medical health records.

Results

Using Linear Mixed Model-based framework, a common-practice method for heritability estimation, we calculate a heritability measure of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${h}^{2}=12.6 \%$$\end{document}h2=12.6% (95% CI, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$6.1 \%\! -\!19.1 \%$$\end{document}6.1%−19.1%) for absolute reduction of HbA1c% after metformin treatment in the entire cohort, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${h}^{2}=21.0 \%$$\end{document}h2=21.0% (95% CI, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7.8 \%\! -\!34.4 \%$$\end{document}7.8%−34.4%) for males and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${h}^{2}=22.9 \%$$\end{document}h2=22.9% (95% CI, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10.0 \%\! -\!35.7 \%$$\end{document}10.0%−35.7%) in females. Results remain unchanged after adjusting for pre-treatment HbA1c%, and in proportional reduction of HbA1c%.

Conclusions

To the best of our knowledge, our work is the first to estimate heritability of drug response using solely EHR data combining a pedigree-based kinship matrix. We demonstrate that while response to metformin treatment has a heritable component, most of the variation is likely due to other factors, further motivating non-genetic analyses aimed at unraveling metformin’s action mechanism.

Individuals in a population might respond differently to the same medication and this phenomenon is commonly attributed to either genes or the environment. Here, we studied the familial aspects of the response to metformin, a medication used in the treatment of type 2 diabetes. We combined information from 18 years of medical records identifying newly treated patients with type 2 diabetes with information about how the trait was inherited within their families. We calculated a metric that tells us how well differences in people’s genes account for differences in their traits, and demonstrate that although the difference in response to metformin is in part explained by the genes people with type 2 diabetes inherit, most of it is not explained by genes. This finding contributes to a better understanding of differences in metformin response and might help inform treatment in future.

Kalka and Gavrieli et al. assessed the heritability of variation in the glycaemic response to metformin by leveraging electronic health records data gathered from a large cohort of patients with diabetes and combining it with pedigree information. The authors show that although the variability in this response has a heritable component, most of it is likely non-genetic.

Association between Three Variants in the PRKAA2 gene, rs2796498, rs9803799, and rs2746342, with 10-year ASCVD Risk on Newly Diagnosed T2DM in Yogyakarta, Indonesia

BACKGROUND: AMPK has pivotal roles in glucose and lipid metabolism, including  AMPKa2, which PRKAA2 encodes. Metformin as an anti-hyperglycemia agent acts through AMPK. Poor glycemia control among patients with type 2 diabetes mellitus (T2DM) could increase atherosclerosis cardiovascular disease (ASCVD) risk. Therefore, PRKAA2 genetic variation might contribute to 10-year ASCVD risk in patients with newly diagnosed T2DM receiving monotherapy metformin. AIM: The study aimed to detect an association between PRKAA2 genetic variation with 10 year-ASCVD risk among newly diagnosed T2DM patients prescribed monotherapy metformin. METHODS: This present study was a case-control study involving 107 participants. Analysis of PRKAA2 genetic variation was performed using the TaqMan assay. RESULTS: A total of 91 participants who fulfilled our criteria enrolled in this study. Most of the participants were female, with mean age 54.40±7.75 years old, mean HbA1c level of 8.35±1.31%, and the lipid profile indicated normal conditions. There was a significant difference in age (p<0.01), HbA1c level (p=0.04), sex (p<0.01), and smoking status (p<0.01) between low-risk and high-risk groups. The GT genotype of rs9803799 had 187.86 times higher possibility for high-risk of 10-year ASCVD risk than TT genotype (OR=187.86, 95%CI:2.98–11863.51). The dominant model of rs9803799 showed that GT+GG had 94.33 times higher possibility for high-risk of 10-year ASCVD risk than TT genotype (OR=94.33; 95%CI:2.32–3841.21). Other results showed that G allele of rs980377 had 20.48 times higher possibility for high-risk of 10-year ASCVD risk than T allele (OR = 20.48; 95%CI:1.48–283.30). These associations were found after multivariate analysis. CONCLUSION: Our findings indicated that rs9803799 as one of PRKAA2 genetic variations might impact the 10-year ASCVD risk among newly diagnosed T2DM patients receiving monotherapy metformin. After considering non-genetic factors, patient assessment should include potential genetic factors in cases with hyperglycemia involving treatment affecting glucose and lipid metabolism such as monotherapy metformin.   Keywords: PRKAA2, genetic variation, atherosclerosis cardiovascular disease, type 2 diabetes mellitus, metformin, Indonesia

Oral and intravenous pharmacokinetics of metformin with and without oral codeine intake in healthy subjects: A cross-over study

The aim of the study was to investigate if there is a clinically relevant drug interaction between metformin and codeine. Volunteers were randomized to receive on four separate occasions: (A) orally administered metformin (1 g), (B) intravenously administered metformin (0.5 g), (C) five doses of tablet codeine 25 mg; the last dose was administered together with oral metformin (1 g), and (D) five doses of tablet codeine 25 mg; the last dose was administered together with metformin (0.5 g) intravenously. Blood samples were drawn for 24 h after administration of metformin, and for 6 h after administration of codeine and analyzed using liquid chromatography and tandem mass spectrometry. Healthy volunteers genotyped as CYP2D6 normal metabolizers (*1/*1) without known reduced function variants in the OCT1 gene (rs12208357, rs34130495, rs34059508, and rs72552763) were invited. The median absorption fraction of metformin was 0.31 and was not influenced by codeine intake. The median time to maximum concentration (Tmax) after oral intake of metformin was 2 h without, and 3 h with codeine (p = 0.06). The geometric mean ratios of the areas under the plasma concentration time‐curve (AUCs) for morphine and its metabolites M3G and M6G for oral intake of metformin‐to‐no metformin were 1.21, 1.31, and 1.27, respectively, and for i.v. metformin‐to‐no metformin 1.28, 1.34, and 1.30, respectively. Concomitant oral and i.v. metformin increased the plasma levels of morphine, M3G and M6G. These small pharmacokinetic changes may well contribute to an increased risk of early discontinuation of metformin. Hence, a clinically relevant drug‐drug interaction between metformin and codeine seems plausible.

Biodegradable copper-metformin nanoscale coordination polymers for enhanced chemo/chemodynamic synergistic therapy by reducing oxygen consumption to promote H2O2 accumulation

Chemo/chemodynamic synergistic therapy is a promising strategy to improve the antitumor effect. However, hypoxia and a limited amount of hydrogen peroxide (H2O2) in the tumor microenvironment (TME) severely restrict the therapeutic efficacy of this combined treatment. Herein, we report biodegradable doxorubicin (Dox)-loaded copper-metformin (Met) nanoscale coordination polymers (Dox@Cu-Met NPs), which exert a chemo/chemodynamic synergistic therapeutic effect by reducing oxygen (O2) consumption to promote H2O2 accumulation in the tumor. Inside tumor cells, Met can inhibit the consumption of O2 to relieve tumor hypoxia by suppressing mitochondrial respiration. The alleviated-tumor hypoxia can not only elevate H2O2 content via the Dox-activated cascade reaction of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOXs) and superoxide dismutase (SOD), but also improve the efficacy of Dox. More importantly, the depletion of glutathione (GSH) accompanies the whole treatment process, which can realize the conversion of Cu2+ to Cu+ and boost reactive oxygen species (ROS) accumulation to improve chemodynamic therapy (CDT) efficacy. Meanwhile, Met is expected to cut off the energy supply by inhibiting respiration, leading to starvation therapy. In vivo investigations demonstrate that tumor growth is significantly inhibited through the enhanced chemo/chemodynamic synergistic treatment. This work provides a new paradigm for cancer therapy using an economical and straightforward method to construct a synergistic nanomedicine platform.

Exercise-Pharmacology Interactions: Metformin, Statins, and Healthspan

There is an increased focus on treatments to extend the healthspan. There is solid evidence that exercise extends the healthspan, but other treatments, such as metformin and statins, are also gaining traction. If metformin and statins will be used to prolong healthspan, we must understand their effects in those free of disease and in combination with exercise.

Rationale for the use of metformin and exercise to counteract statin-associated side effects

INTRODUCTION

Statins are the most widely prescribed drugs for lowering low-density lipoprotein cholesterol (LDL-C) and reducing cardiovascular morbidity and mortality. They are usually well-tolerated, but have two main safety concerns: statin-associated muscle symptoms (SAMS) and new-onset type 2 diabetes (NOD).

METHODS

A PubMed search was carried out using the following key words were used: statins, statin-associated muscle symptoms, statin myalgia, statin-associated diabetes, metformin and statins, exercise and statins.

RESULTS

Mitochondrial damage and muscle atrophy are likely the central mechanisms producing SAMS, whereas decreased glucose transport, fatty acid oxidation and insulin secretion are likely involved in the development of NOD. Metformin and exercise training share many pathways that could potentially contrast SAMS and NOD. Clinical evidence also supports the combination of statins with metformin and exercise.

CONCLUSION

This combination appears attractive both from a clinical and an economical viewpoint, since all three therapies are highly cost-effective and their combination could result in diabetes and cardiovascular disease prevention.

Challenges Involved in Incorporating Personalised Treatment Plan as Routine Care of Patients with Diabetes

Diabetes is a heterogenous disorder, and patients with this disorder vary considerably in their clinical presentation, response to therapy and risk of complications. Expanding knowledge about the pathophysiology of various forms of diabetes has raised the possibility that diagnostic and therapeutic modalities can be tailored to the individual patient in a personalized manner. The recent publication of a Consensus Statement on precision diabetes care underlines the major strides made in this field in the recent past. However, while personalized diabetes care has the potential to significantly improve outcomes in patients with diabetes in a safe and cost-effective manner, its wider application presents several challenges, especially in resource-strained settings. These challenges pertain equally to precision diagnostics, precision therapeutics and precision monitoring. This article discusses some of the important challenges that care providers are likely to face in applying the personalized approach in caring for their patients with diabetes, in the context of diagnosis and management of type 1 diabetes, type 2 diabetes and monogenic forms of diabetes. Suggestions are also presented for overcoming some of these challenges.

Anti-Aging Effect of Metformin: A Molecular and Therapeutical Perspective

Aging is a time-dependent inevitable process, in which cellular homeostasis is affected, which has an impact on tissue function. This represents a risk factor for the development of numerous non-transmissible diseases. In consequence, the scientific community continues to search for therapeutic measures capable of improving quality of life and delaying cellular aging. At the center of this research is metformin, a widely used drug in Type 2 Diabetes Mellitus treatment that has a reduced adverse effects profile. Furthermore, there is evidence that this drug has beneficial health effects that go beyond its anti-hyperglycemic properties. Among these effects, its geronto-protection capability stands out. There is growing evidence that points out to an increased life expectancy as well as the quality of life in model organisms treated with metformin. Therefore, there is an abundance of research centered on elucidating the mechanism through which metformin has its anti-aging effects. Among these, the AMPK, mTORC1, SIRT1, FOXO, NF.kB, and DICER1 pathways can be mentioned. Furthermore, studies have highlighted the possibility of a role for the gut microbiome in these processes. The next step is the design of clinical essays that have as a goal evaluating the efficacy and safety of metformin as an anti-aging drug in humans to create a paradigm in the medical horizon. The question being if metformin is, in fact, the new antiaging therapy in humans?

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

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

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.

Metformin chlorination byproducts in drinking water exhibit marked toxicities of a potential health concern

Metformin (MET), a worldwide used drug for type 2 diabetes, has been found with the largest amount by weight among all drugs in aquatic environment, including the drinking water systems where this emerging micropollutant is inevitably transformed during chlorination process. Whether MET chlorination byproducts Y (C₄H₆ClN₅) and C (C₄H₆ClN₃) exist in drinking water remains unknown. Although MET has health-promoting properties, whether or how its chlorination byproducts affect health is still uncharacterized. Here we reveal that MET and byproduct C are present in worldwide drinking water with the highest doses detected for MET and C as 1203.5 ng/L and 9.7 ng/L respectively. Under simulated chlorination conditions, we also demonstrate that both byproducts can be increasingly produced with increment of MET concentration, suggesting a hidden threat on the safety and sustainability of global water supply. Through systematic evaluations, we demonstrate that MET chlorination byproducts Y and C exhibit toxicities instead of genotoxicity to live worms and human HepG2 cells at millimolar doses. Moreover, both byproducts are harmful to mice and particularly Y at 250 ng/L destroys the mouse small intestine integrity. Unprecedentedly, we unveil boiling and activated carbon adsorption as effective alternative solutions that may be in urgent demand globally for removing these byproducts from drinking water.

Where Does Metformin Stand in Modern Day Management of Type 2 Diabetes?

Metformin is the most commonly used glucose-lowering therapy (GLT) worldwide and remains the first-line therapy for newly diagnosed individuals with type 2 diabetes (T2D) in management algorithms and guidelines after the UK Prospective Diabetes Study (UKPDS) showed cardiovascular mortality benefits in the overweight population using metformin. However, the improved Major Adverse Cardiovascular Events (MACE) realised in some of the recent large cardiovascular outcomes trials (CVOTs) using sodium-glucose co-transporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) have challenged metformin's position as a first-line agent in the management of T2D. Many experts now advocate revising the existing treatment algorithms to target atherosclerotic cardiovascular disease (ASCVD) and improving glycaemic control as a secondary aim. In this review article, we will revisit the major cardiovascular outcome data for metformin and include a critique of the UKPDS data. We then review additional factors that might be pertinent to metformin's status as a first-line agent and finally answer key questions when considering metformin's role in the modern-day management of T2D.

Using a limited sampling strategy to investigate the interindividual pharmacokinetic variability in metformin: A large prospective trial

AIMS

Recently a limited sampling strategy (LSS) for determination of metformin' pharmacokinetics was developed. The LSS utilizes the plasma concentration of metformin 3 and 10 hours after oral intake of a single dose to estimate the area under the concentration-time curve up to 24 hours (AUC_0-24h ). The main purpose of this study was to support the feasibility of this strategy in a large prospective trial.

METHODS

Volunteers orally ingested two 500-mg tablets of metformin hydrochloride. A blood sample was drawn three and ten hours after the ingestion. Urine was collected for 0-10 and 10-24 hours and urine volumes recorded. The AUC_0-24h was calculated using the equation AUC_0-24h = 4.779 * C₃ + 13.174 * C₁₀ . Additionally, all participants were genotyped for the single-nucleotide polymorphism A270S in OCT2, g.-66 T > C in MATE1, R61C, G465R, G401S and the deletion M420del in OCT1.

RESULTS

In total, 212 healthy volunteers participated. The median (25th - 75th interquartile range) AUC_{0 - 24h} , CL_renal , C₃ and C₁₀ , were 10 600 (8470-12 500) ng* hr* mL^-1 , 29 (24-34) L* hour^-1 , 1460 (1180-1770) and 260 (200-330) ng* mL^-1 , respectively, which is in agreement with our previous results. GFR_i was correlated with metformin AUC and CL_renal (P < .001). As expected, we found a great pharmacokinetic interindividual variability among the volunteers and no effect of the OCT1 genotype on the AUC_{0 - 24h} . We were unable to reproduce our previous finding of a gene-gene interaction (OCT2 and MATE1) effect on CL_renal in this cohort.

CONCLUSION

This study further supports the use of the 2-point LSS algorithm in large pharmacokinetic trials.

Rapid, Cost-Effective Peptide/Nucleic Acid-Based Platform for Therapeutic Antibody Monitoring in Clinical Samples

We demonstrate here a homogeneous assay, named NanoHybrid, for monoclonal antibody quantification directly in serum samples in a single-step format. NanoHybrid is composed of both synthetic peptide nucleic acids (PNAs) and nucleic acid strands conjugated to recognition elements and optical labels and is designed to allow fast fluorescence quantification of a therapeutic antibody. More specifically, we have characterized our analytical assay for the detection of trastuzumab (Herceptin), a monoclonal antibody (mAb) drug used for breast cancer treatment and for tumors overexpressing the HER2/neu protein. We show here that NanoHybrid is capable of performing fast drug quantification directly in blood serum. The results obtained with a pool of samples from breast cancer patients under trastuzumab treatment are compared with CE-IVD ELISA (enzyme-linked immunosorbent assay) showing a good agreement (Cohen's K = 0.729). Due to the modular nature of the NanoHybrid platform, this technology can be programmed to potentially detect and quantify any antibody for which a high-affinity recognition element has been characterized. We envision the application of NanoHybrid in a point-of-care (POC) drug monitoring system based on disposable kits for therapeutic drug management.

Rationale and design of a randomised controlled trial testing the effect of personalised diet in individuals with pre-diabetes or type 2 diabetes mellitus treated with metformin

INTRODUCTION

Metformin and diets aimed at promoting healthy body weight are the first line in treating type 2 diabetes mellitus (T2DM). Clinical practice, backed by clinical trials, suggests that many individuals do not reach glycaemic targets using this approach alone. The primary aim of the Personalised Medicine in Pre-diabetes-Towards Preventing Diabetes in Individuals at Risk (PREDICT) Study is to test the efficacy of personalised diet as adjuvant to metformin in improving glycaemic control in individuals with dysglycaemia.

METHODS AND ANALYSIS

PREDICT is a two-arm, parallel group, single-masked randomised controlled trial in adults with pre-diabetes or early-stage T2DM (with glycated haemoglobin (HbA1c) up to 8.0% (64 mmol/mol)), not treated with glucose-lowering medication. PREDICT is conducted at the Clinical Research Facility at the Garvan Institute of Medical Research (Sydney). Enrolment of participants commenced in December 2018 and expected to complete in December 2021. Participants are commenced on metformin (Extended Release, titrated to a target dose of 1500 mg/day) and randomised with equal allocation to either (1) the Personalised Nutrition Project algorithm-based diet or (2) low-fat high-dietary fibre diet, designed to provide caloric restriction (75%) in individuals with body mass index >25 kg/m². Treatment duration is 6 months and participants visit the Clinical Research Facility five times over approximately 7 months. The primary outcome measure is HbA1c. The secondary outcomes are (1) time of interstitial glucose <7.8 mmol/L and (2) glycaemic variability (continuous glucose monitoring), (3) body weight, (4) fat mass and (5) abdominal visceral fat volume (dual-energy X-ray absorptiometry), serum (6) low-density lipoprotein cholesterol (7) high-density lipoprotein cholesterol and (8) triglycerides concentrations, (9) blood pressure, and (10) liver fat (Fibroscan).

ETHICS AND DISSEMINATION

The study has been approved by the St Vincent's Hospital Human Research Ethics Committee (File 17/080, Sydney, Australia) and the Weizmann Institutional Review Board (File 528-3, Rehovot, Israel). The findings will be published in peer-reviewed open access medical journals.

TRIAL REGISTRATION NUMBER

NCT03558867; Pre-results.

Metformin improves blood glucose by increasing incretins independent of changes in gluconeogenesis in youth with type 2 diabetes

AIMS/HYPOTHESIS

Metformin is the only approved oral agent for youth with type 2 diabetes but its mechanism of action remains controversial. Recent data in adults suggest a primary role for the enteroinsular pathway, but there are no data in youth, in whom metformin efficacy is only ~50%. Our objectives were to compare incretin concentrations and rates of glucose production and gluconeogenesis in youth with type 2 diabetes before and after short-term metformin therapy compared with peers with normal glucose tolerance (NGT).

METHODS

This is a case-control observational study in youth with type 2 diabetes who were not on metformin (n = 18) compared with youth with NGT (n = 10) who were evaluated with a 2 day protocol. A 75 g OGTT was administered to measure intact glucagon-like 1 peptide (iGLP-1), gastric inhibitory polypeptide (GIP) and peptide YY (PYY). Insulinogenic index (IGI) and whole-body insulin sensitivity were calculated using glucose and insulin levels from the OGTT. Basal rates of gluconeogenesis (²H₂O), glucose production ([6,6-²H₂]glucose) and whole-body lipolysis ([²H₅]glycerol) were measured after an overnight fast on study day 2. Youth with type 2 diabetes (n = 9) were subsequently evaluated with an identical 2 day protocol after 3 months on the metformin study.

RESULTS

Compared with individuals with NGT, those with type 2 diabetes had higher fasting (7.8 ± 2.5 vs 5.1 ± 0.3 mmol/l, mean ± SD p = 0.002) and 2 h glucose concentrations (13.8 ± 4.5 vs 5.9 ± 0.9 mmol/l, p = 0.001), higher rates of absolute gluconeogenesis (10.0 ± 1.7 vs 7.2 ± 1.1 μmol [kg fat-free mass (FFM)]^-1 min^-1, p < 0.001) and whole-body lipolysis (5.2 ± 0.9 vs 4.0 ± 1.4 μmol kg_FFM^-1 min^-1, p < 0.01), but lower fasting iGLP-1 concentrations (0.5 ± 0.5 vs 1.3 ± 0.7 pmol/l, p < 0.01). Metformin decreased 2 h glucose (pre metformin 11.4 ± 2.8 vs post metformin 9.9 ± 1.9 mmol/l, p = 0.04) and was associated with ~20-50% increase in IGI (median [25th-75th percentile] pre 1.39 [0.89-1.47] vs post 1.43 [0.88-2.70], p = 0.04), fasting iGLP-1 (pre 0.3 ± 0.2 vs post 1.0 ± 0.7 pmol/l, p = 0.02), 2 h iGLP (pre 0.4 ± 0.2 vs post 1.2 ± 0.9 pmol/l, p = 0.06), fasting PYY (pre 6.3 ± 2.2 vs post 10.5 ± 4.3 pmol/l, p < 0.01) and 2 h PYY (pre 6.6 ± 2.9 vs post 9.0 ± 4.0 pmol/l, p < 0.01). There was no change in BMI, insulin sensitivity or GIP concentrations pre vs post metformin. There were no differences pre vs post metformin in rates of glucose production (15.0 ± 3.9 vs 14.9 ± 2.2 μmol kg_FFM^-1 min^-1, p = 0.84), absolute gluconeogenesis (9.9 ± 1.8 vs 9.7 ± 1.7 μmol kg_FFM^-1 min^-1, p = 0.76) or whole-body lipolysis (5.0 ± 0.7 vs 5.3 ± 1.3 μmol kg_FFM^-1 min^-1, p = 0.20). Post metformin iGLP-1 and PYY concentrations in youth with type 2 diabetes were comparable to levels in youth with NGT.

CONCLUSIONS/INTERPRETATION

Overall, the improved postprandial blood glucose levels and increase in incretins observed in the absence of changes in insulin sensitivity and gluconeogenesis, support an enteroinsular mechanistic pathway in youth with type 2 diabetes treated with short-term metformin.

Atypical Diabetes Presentations in Sub-Saharan Africa Classification Puzzle and Possible Role of Precision Medicine

Precision in the diagnosis and classification of diabetes mellitus, a complex heterogeneous disease is increasingly required to achieve treatment goals and prevent complications. Several reviews over decades have not completely solved the diabetes classification puzzle. African clinicians are sometimes confronted with the difficulty of classifying a newly diagnosed diabetes patient presenting atypically. These unusual presentations fall into those with diagnosis of either clinical type 1 or 2 diabetes but having some diagnostic and/or therapeutic features at variance with what are seen in the Western nations, those with tropical diabetes and those known as ketosis-prone type 2 diabetes (KPD). Reports from many African countries indicate that patients do not fit the classic pattern seen in the Western nations. In recent times, there has been groundswell of pressures and proposed models to evolve a more accurate classification of diabetes and the recent 2019 WHO diabetes classification seems to have acknowledged and accommodated these concerns. Perhaps advances in genomic knowledge could help with precision in diabetes classification, especially in Africa. This review seeks to highlight the challenges often encountered with classifying diabetes patients in Africa, and proffer suggestions on the way forward including possible benefit from advances in molecular genomics.

The impact of adjunctive metformin to progesterone for the treatment of non-atypical endometrial hyperplasia in a randomized fashion, a placebo-controlled, double blind clinical trial

OBJECTIVE

Endometrial hyperplasia (EH) is a premalignant neoplasm. Most recently, metformin has been suggested as an adjuvant medication for treating of EH with better outcome. Recent evidence has suggested that metformin has anticancer activity by inhibiting cell proliferation and tumor growth. The aim of this study was to evaluate the effect of metformin plus megestrol acetate versus megestrol acetate alone on patient with EH without atypia.

STUDY DESIGN

This double blind placebo-controlled clinical trial was conducted among 60 women with EH without atypia. Participants were allocated to two equal groups. Treatment group (M + M) received 40 mg megestrol acetate for 14 days of one month and 1000 mg metformin daily for three months. In placebo group (M + P) each patient received the same dose of megestrol acetate plus two tablets of placebo. Endometrial biopsy was performed in all patients three weeks after the last day of medication RESULTS: Data were evaluated based on 29 and 27 women in the M + M group and M + P group, respectively. After 3 months of therapy 27 (93.1 %) women in M + M group had not EH and responded to treatment, which was statistically higher than the rate of response (19 women, 70.4 %) in M + P group.

CONCLUSIONS

This study showed that megestrol plus metformin was significantly better than megestrol alone for the treatment of endometrial hyperplasia without atypia.

Noncoding SNPs associated with increased GDF15 levels located in a metformin-activated enhancer region upstream of GDF15

Aim: GDF15 levels are a biomarker for metformin use. We performed the functional annotation of noncoding genome-wide association study (GWAS) SNPs for GDF15 levels and the Genotype-Tissue Expression (GTEx)-expression quantitative trait loci (eQTLs) for GDF15 expression within metformin-activated enhancers around GDF15. Materials & methods: These enhancers were identified using chromatin immunoprecipitation followed by sequencing data for active (H3K27ac) and silenced (H3K27me3) histone marks on human hepatocytes treated with metformin, Encyclopedia of DNA Elements data and cis-regulatory elements assignment tools. Results: The GWAS lead SNP rs888663, the SNP rs62122429 associated with GDF15 levels in the Outcome Reduction with Initial Glargine Intervention trial, and the GTEx-expression quantitative trait locus rs4808791 for GDF15 expression in whole blood are located in a metformin-activated enhancer upstream of GDF15 and tightly linked in Europeans and East Asians. Conclusion: Noncoding variation within a metformin-activated enhancer may increase GDF15 expression and help to predict GDF15 levels.

Metformin: the updated protective property in kidney disease

Metformin is a frontline hypoglycemic agent, which is mainly prescribed to manage type 2 diabetes mellitus with obesity. Emerging evidence suggests that metformin also exerts protective effects against various kidney diseases. Some postulate that kidney disease is actually a metabolic disease, accompanied by nonresolving pathophysiologic pathways controlling oxidative stress, endoplasmic reticulum stress, inflammation, lipotoxicity, fibrosis, and senescence, as well as insufficient host defense mechanisms such as AMP-activated protein kinase (AMPK) signaling and autophagy. Metformin may interfere with these pathways by orchestrating AMPK signaling and AMPK-independent pathways to protect the kidneys from injury. Furthermore, the United States Food and Drug Administration declared metformin is safe for patients with mild or moderate kidney impairment in 2016, assuaging some conservative attitudes about metformin management in patients with renal insufficiency and broadening the scope of research on the renal protective effects of metformin. This review focuses on the molecular mechanisms by which metformin imparts renal protection and its potential in the treatment of various kidney diseases.

Genetic variants associated with glycemic response to treatment with dipeptidylpeptidase 4 inhibitors

Aim: We examined associations of eight SNPs in/near seven candidate genes with glycemic response to 6 month treatment with DPP4 inhibitors. Patients & methods: 206 patients with type 2 diabetes (116 men and 90 women) were treated with sitagliptin or vildagliptin (both 100 mg/day) in combination with metformin or metformin/sulphonylurea over 6 months, and the reduction in glycated hemoglobin (HbA1c) was measured. Results: Rs6923761 in GLP1R was significantly associated with a reduction in HbA1c (adjusted p = 0.006). Homozygotes for the minor A allele had smaller reduction in HbA1c by 0.4% (4 mmol/mol) than the G allele carriers (p = 0.016). Conclusion: The missense variant rs6923761 in the GLP1R gene was associated with a smaller glycemic response to 6 month gliptin therapy in diabetic patients of central European origin.

Dreh, a long noncoding RNA repressed by metformin, regulates glucose transport in C2C12 skeletal muscle cells

AIMS

The anti-hyperglycemic action of metformin on skeletal muscles is presently unclear. Long noncoding RNAs (lncRNAs) are implicated in multiple cellular functions. This study aims to explore the role of lncRNAs in the glucometabolic action of metformin on skeletal muscle cells.

MAIN METHODS

Metformin accumulation was assessed using [¹⁴C]-metformin. A lncRNA array was used to investigate metformin-regulated lncRNAs in C2C12 skeletal muscle cells. Knockdown studies were applied to evaluate the function of lncRNA Dreh. A colorimetric assay was used for the measurement of medium glucose concentration; glucose transport was assessed using [³H]-2-deoxyglucose; real-time PCR was used for RNA expression analysis, and western blotting was used to assess protein expression in myotubes. A Dreh overexpression plasmid was transfected into the cells.

KEY FINDINGS

Metformin accumulated in C2C12 myotubes. Metformin reduced medium glucose concentration and repressed lncRNA Dreh expression in the myotubes. Knockdown of Dreh in the myotubes resulted in reduced glucose concentration in the culture medium, increased glucose transport, and increased levels of GLUT4 protein in the plasma membrane. Overexpression of Dreh attenuated the glucose-lowering effect of metformin in myotubes.

SIGNIFICANCE

The glucoregulatory actions of metformin are mediated in part by a lncRNA, Dreh, in the skeletal muscle cells. Dreh is a novel regulator for glucose transport and could be a therapeutic target for diabetes.

Metformin as Anti-Aging Therapy: Is It for Everyone?

Metformin is the most widely prescribed oral hypoglycemic medication for type 2 diabetes worldwide. Metformin also retards aging in model organisms and reduces the incidence of aging-related diseases such as neurodegenerative disease and cancer in humans. In spite of its widespread use, the mechanisms by which metformin exerts favorable effects on aging remain largely unknown. Further, not all individuals prescribed metformin derive the same benefit and some develop side effects. Before metformin finds its way to mainstay therapy for anti-aging, a more granular understanding of the effects of the drug in humans is needed. This review provides an overview of recent findings from metformin studies in aging and longevity and discusses the use of metformin to combat aging and aging-related diseases.

Common Variants in 22 Genes Regulate Response to Metformin Intervention in Children with Obesity: A Pharmacogenetic Study of a Randomized Controlled Trial

Metformin is a first-line oral antidiabetic agent that has shown additional effects in treating obesity and metabolic syndrome. Inter-individual variability in metformin response could be partially explained by the genetic component. Here, we aimed to test whether common genetic variants can predict the response to metformin intervention in obese children. The study was a multicenter and double-blind randomized controlled trial that was stratified according to sex and pubertal status in 160 children with obesity. Children were randomly assigned to receive either metformin (1g/d) or placebo for six months after meeting the defined inclusion criteria. We conducted a post hoc genotyping study in 124 individuals (59 placebo, 65 treated) comprising finally 231 genetic variants in candidate genes. We provide evidence for 28 common variants as promising pharmacogenetics regulators of metformin response in terms of a wide range of anthropometric and biochemical outcomes, including body mass index (BMI) Z-score, and glucose, lipid, and inflammatory traits. Although no association remained statistically significant after multiple-test correction, our findings support previously reported variants in metformin transporters or targets as well as identify novel and promising loci, such as the ADYC3 and the BDNF genes, with plausible biological relation to the metformin's action mechanism. Trial Registration: Registered on the European Clinical Trials Database (EudraCT, ID: 2010-023061-21) on 14 November 2011 (URL: https://www.clinicaltrialsregister.eu/ctr-search/trial/2010-023061-21/ES).

Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future

Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.

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.

Pharmacological Autophagy Regulators as Therapeutic Agents for Inflammatory Bowel Diseases

The arsenal of effective molecules to treat patients with chronic inflammatory bowel diseases (IBDs) remains limited. These remitting-relapsing diseases have become a global health issue and new therapeutic strategies are eagerly awaited to regulate the course of these disorders. Since the association between autophagy-related gene polymorphism and an increased risk of Crohn's disease (CD) has been discovered, a new domain of investigation has emerged, focused on the intracellular degradation system, with the objective of generating new medicines that are safer and more targeted. This review summarizes the drugs administered to IBD patients and describes recently emerged therapeutic agents. We compile evidence on the contribution of autophagy to IBD pathogenesis, give an overview of pharmacological autophagy regulators in animal models of colitis, and propose novel therapeutic avenues based on autophagy components.

Metformin Pharmacogenetics: Effects of SLC22A1, SLC22A2, and SLC22A3 Polymorphisms on Glycemic Control and HbA1c Levels

Type 2 diabetes mellitus (T2DM) constitutes a major portion of Jordan’s disease burden, and incidence rates are rising at a rapid rate. Due to variability in the drug’s response between ethnic groups, it is imperative that the pharmacogenetics of metformin be investigated in the Jordanian population. The objective of this study was to investigate the relationship between twenty-one single nucleotide polymorphisms (SNPs) in the SLC22A1, SLC22A2, and SLC22A3 genes and their effects on metformin pharmacogenetics in Jordanian patients diagnosed with type 2 diabetes mellitus. Blood samples were collected from 212 Jordanian diabetics who fulfilled the inclusion criteria, which were then used in SNP genotyping and determination of HbA1c levels. The rs12194182 SNP in the SLC22A3 gene was found to have a significant association (p < 0.05) with lower mean HbA1c levels, and this association more pronounced in patients with the CC genotype (i.e., p-value was significant before correcting for multiple testing). Moreover, the multinomial logistic regression analysis showed that SNP genotypes within the SLC22A1, SLC22A2, and SLC22A3 genes, body mass index (BMI) and age of diagnosis were significantly associated with glycemic control (p < 0.05). The results of this study can be used to predict response to metformin and other classes of T2DM drugs, making treatment more individualized and resulting in better clinical outcomes.

Current Progress in Pharmacogenetics of Second-Line Antidiabetic Medications: Towards Precision Medicine for Type 2 Diabetes

Precision medicine is a scientific and medical practice for personalized therapy based on patients’ individual genetic, environmental, and lifestyle characteristics. Pharmacogenetics and pharmacogenomics are also rapidly developing and expanding as a key element of precision medicine, in which the association between individual genetic variabilities and drug disposition and therapeutic responses are investigated. Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by hyperglycemia mainly associated with insulin resistance, with the risk of clinically important cardiovascular, neurological, and renal complications. The latest consensus report from the American Diabetes Association and European Association for the Study of Diabetes (ADA-EASD) on the management of T2D recommends preferential use of glucagon-like peptide-1 (GLP-1) receptor agonists, sodium-glucose cotransporter-2 (SGLT2) inhibitors, and some dipeptidyl peptidase-4 (DPP-4) inhibitors after initial metformin monotherapy for diabetic patients with established atherosclerotic cardiovascular or chronic kidney disease, and with risk of hypoglycemia or body weight-related problems. In this review article, we summarized current progress on pharmacogenetics of newer second-line antidiabetic medications in clinical practices and discussed their therapeutic implications for precision medicine in T2D management. Several biomarkers associated with drug responses have been identified from extensive clinical pharmacogenetic studies, and functional variations in these genes have been shown to significantly affect drug-related glycemic control, adverse reactions, and risk of diabetic complications. More comprehensive pharmacogenetic research in various clinical settings will clarify the therapeutic implications of these genes, which may be useful tools for precision medicine in the treatment and prevention of T2D and its complications.

The Continuing Evolution of Precision Health in Type 2 Diabetes: Achievements and Challenges

PURPOSE OF REVIEW

The purpose of this review was to summarize recent advances in the genomics of type 2 diabetes (T2D) and to highlight current initiatives to advance precision health.

RECENT FINDINGS

Generation of multi-omic data to measure each of the "biologic layers," developments in describing genomic function and annotation in T2D relevant tissue, along with the increasing recognition that T2D is a heterogeneous disease, and large-scale collaborations have all contributed to advancing our understanding of the molecular basis of T2D. Substantial advances have been made in understanding the molecular basis of T2D pathogenesis, such that precision health diabetes is increasingly becoming a reality. For precision diabetes to become a routine in clinical and public health, additional large-scale multi-omic initiatives are needed along with better assessment of our environment to delineate an individual's diabetes subtype for improved detection and management.

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

INTRODUCTION

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

Metformin as a geroprotector: experimental and clinical evidence

Apart from being a safe, effective and globally affordable glucose-lowering agent for the treatment of diabetes, metformin has earned much credit in recent years as a potential anti-aging formula. It has been shown to significantly increase lifespan and delay the onset of age-associated decline in several experimental models. The current review summarizes advances in clinical research on the potential role of metformin in the field of geroprotection, highlighting findings from pre-clinical studies on known and putative mechanisms behind its beneficial properties. A growing body of evidence from clinical trials demonstrates that metformin can effectively reduce the risk of many age-related diseases and conditions, including cardiometabolic disorders, neurodegeneration, cancer, chronic inflammation, and frailty. Metformin also holds promise as a drug that could be repurposed for chemoprevention or adjuvant therapy for certain cancer types. Moreover, due to the ability of metformin to induce autophagy by activation of AMPK, it is regarded as a potential hormesis-inducing agent with healthspan-promoting and pro-longevity properties. Long-term intake of metformin is associated with low risk of adverse events; however, well-designed clinical trials are still warranted to enable potential use of this therapeutic agent as a geroprotector.

Genetic polymorphisms of organic cation transporters 1 (OCT1) and responses to metformin therapy in individuals with type 2 diabetes mellitus: a systematic review protocol

BACKGROUND

Metformin is one of the most commonly used drugs for type 2 diabetes mellitus (T2DM). Despite its efficacy and safety, metformin is frequently associated with highly variable glycemic responses, which is hypothesized to be the result of genetic variations in its transport by organic cation transporters (OCTs). This systematic review aims to highlight and summarize the overall effects of OCT1 polymorphisms on therapeutic responses to metformin and to evaluate their potential role in terms of interethnic differences with metformin responses.

METHODS/DESIGN

We will systematically review observational studies reporting on the genetic association between OCT1 polymorphisms and metformin responses in T2DM patients. A comprehensive search strategy formulated with the help of a librarian will be used to search MEDLINE via PubMed, Embase, and CINAHL for relevant studies published between January 1990 and July 2017. Two review authors will independently screen titles and abstracts in duplicate, extract data, and assess the risk of bias with discrepancies resolved by discussion or arbitration of a third review author. Mined data will be grouped according to OCT1 polymorphisms, and their effects on therapeutic responses to metformin will be narratively synthesized. If sufficient numbers of homogeneous studies are scored, meta-analyses will be performed to obtain pooled effect estimates. Funnel plots analysis and Egger's test will be used to assess publication bias. This study will be reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines.

DISCUSSION

This review will summarize the genetic effects of OCT1 polymorphisms associated with variabilities in glycemic responses to metformin. The findings of this study could help to develop genetic tests that could predict a person's response to metformin treatment and create personalized drugs with greater efficacy and safety.

SYSTEMATIC REVIEW REGISTRATION

Registration number: PROSPERO, CRD42017079978.

A preclinical overview of metformin for the treatment of type 2 diabetes

Type 2 diabetes (T2D) is the most common type of diabetes mellitus and is mainly characterized by insulin resistance, β-cell dysfunction, and elevated hepatic glucose output. Metformin is a first-line antihyperglycemic agent that works mainly by regulating hepatic glucose production and peripheral insulin sensitivity. Metformin has been clinically applied for more than half a century, although the underlying pharmacological mechanisms remain elusive. This current review mainly focused on the development history of metformin and related preclinical studies on structural modification, pharmacological mechanisms for treatment of T2D, toxicology, pharmacokinetics, and pharmaceutics. The pharmacological function of metformin in lowering hyperglycemia suggests that multi-targeting could be an effective strategy for the discovery of new anti-diabetic drugs. A number of discoveries have revealed the pharmacologic mechanisms of metformin; however, precise mechanisms remain unclear. Deeper investigations on the biological features of metformin are expected to provide more rational applications and indications of this evergreen anti-T2D agent, which will in turn help to better understand the complicated pathogenesis of T2D.