Pharmacogenetic studies update in type 2 diabetes mellitus

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

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

Genetic risk scores: are they important for diabetes management? results from multiple cross-sectional studies

BACKGROUND

Several genetic risk scores (GRS) for type 2 diabetes (T2DM) have been published, but not replicated. We aimed to 1) replicate previous findings on the association between GRS on prevalence of T2DM and 2) assess the association between GRS and T2DM management in a sample of community-dwelling people from Switzerland.

METHODS

Four waves from a prospective study conducted in Lausanne. Seven GRS related to T2DM were selected, and compared between participants with and without T2DM, and between controlled and uncontrolled participants treated for T2DM.

RESULTS

Data from 5426, 4017, 2873 and 2170 participants from the baseline, first, second and third follow-ups, respectively, was used. In all study periods, participants with T2DM scored higher than participants without T2DM in six out of seven GRS. Data from 367, 437, 285 and 207 participants with T2DM was used. In all study periods, approximately half of participants treated for T2DM did not achieve adequate fasting blood glucose or HbA1c levels, and no difference between controlled and uncontrolled participants was found for all seven GRS. Power analyses showed that most GRS needed a sample size above 1000 to consider the difference between controlled and uncontrolled participants as statistically significant at p = 0.05.

CONCLUSION

In this study, we confirmed the association between most published GRS and diabetes. Conversely, no consistent association between GRS and diabetes control was found. Use of GRS to manage patients with T2DM in clinical practice is not justified.

Profiling of patients with type 2 diabetes based on medication adherence data

Introduction

Type 2 diabetes mellitus (T2DM) is a complex, chronic disease affecting multiple organs with varying symptoms and comorbidities. Profiling patients helps identify those with unfavorable disease progression, allowing for tailored therapy and addressing special needs. This study aims to uncover different T2DM profiles based on medication intake records and laboratory measurements, with a focus on how individuals with diabetes move through disease phases.

Methods

We use medical records from databases of the last 20 years from the Department of Endocrinology and Diabetology of the University Medical Center in Maribor. Using the standard ATC medication classification system, we created a patient-specific drug profile, created using advanced natural language processing methods combined with data mining and hierarchical clustering.

Results

Our results show a well-structured profile distribution characterizing different age groups of individuals with diabetes. Interestingly, only two main profiles characterize the early 40-50 age group, and the same is true for the last 80+ age group. One of these profiles includes individuals with diabetes with very low use of various medications, while the other profile includes individuals with diabetes with much higher use. The number in both groups is reciprocal. Conversely, the middle-aged groups are characterized by several distinct profiles with a wide range of medications that are associated with the distinct concomitant complications of T2DM. It is intuitive that the number of profiles increases in the later age groups, but it is not obvious why it is reduced later in the 80+ age group. In this context, further studies are needed to evaluate the contributions of a range of factors, such as drug development, drug adoption, and the impact of mortality associated with all T2DM-related diseases, which characterize these middle-aged groups, particularly those aged 55-75.

Conclusion

Our approach aligns with existing studies and can be widely implemented without complex or expensive analyses. Treatment and drug use data are readily available in healthcare facilities worldwide, allowing for profiling insights into individuals with diabetes. Integrating data from other departments, such as cardiology and renal disease, may provide a more sophisticated understanding of T2DM patient profiles.

Effects of silibinin on apoptosis and insulin secretion in rat RINm5F pancreatic β-cells

We investigated whether silibinin, a flavonoid, might be useful for treating diabetes mellitus by treating five groups of rat RINm5F β-insulinemia cells as follows: control streptozotocin (STZ) group administered citrate buffer and dimethyl sulfoxide; STZ group administered 20 mM STZ; silibinin group administered 50 µM silibinin; pre-silibinin group administered 50 µM silibinin 5 h before administering 20 mM STZ; simultaneous group administered 50 µM silibinin at the same time as 20 mM STZ. For all groups, MTT assay and flow cytometry were used to evaluate cell viability and necrosis, respectively. Glucose-stimulated insulin secretion (GSIS) and insulin cell content were determined using enzyme-linked immunosorbent assay. Also, expression of genes, pancreatic and duodenal homeobox 1 (pdx1), neuronal differentiation 1 (neurod1), v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog A (mafa), glucose transporter 2 (glut2)) was determined using the real-time polymerase chain reaction. We found that silibinin improved the viability of RINm5F cells and increased GSIS and cellular insulin under glucotoxic conditions. Silibinin increased the expression of neurod1, mafa and glut2, but reduced pdx1 expression. Our findings suggest that silibinin might increase glucose sensitivity and insulin synthesis under glucotoxic conditions, which could be useful for diabetes 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.

The determination of the effect(s) of solute carrier family 22-member 2 (SLC22A2) haplotype variants on drug binding via molecular dynamic simulation systems

Single nucleotide polymorphisms detected in the solute carrier member family-22 has been shown to result in a variable response in the treatment of type 2 diabetes mellitus with Metformin. This study predicted a three-dimensional protein structure for the SLC22A2 protein sequence using AlphaFold 2 and modelled five haplotypes within SLC22A2 protein structure observed in the Xhosa population of South Africa. The protein models were used to determine the effect(s) of haplotype variations on the transport function of Metformin and 10 other drugs by the SLC22A2 protein. Molecular dynamic simulation studies, molecular docking and interaction analysis of the five SLC22A2 haplotypes were performed in complex with the ligand 5RE in a POPC lipid bilayer to understand the mechanism of drug binding. Weakest binding free energy was found between 5RE and haplotype 1. Molecular docking studies indicated the top binding ligands as well as Metformin to bind inside the transport channel in all haplotypes increasing the probability of Metformin inhibition during co-administration of drugs. Metformin showed reduced binding affinity and number of interactions compared to the top four binding molecules. Molecular dynamic simulation analysis indicated that haplotypes 1, 3 and 4 were less stable than 2 and 5. The findings suggest haplotypes 4 and 5 having stronger preference for large inhibitor molecule binding in the active site and this could result in haplotypes 4 and 5 demonstrating reduced Metformin clearance via the SLC22A2 transporter during co-administration of drugs. The current study is the first to investigate the potential effect(s) of haplotype variation on the protein structure of SLC22A2 to assess its ability to transport Metformin in an indigenous South African population.

Aronia melanocarpa Anthocyanin Extracts Improve Hepatic Structure and Function in High-Fat Diet-/Streptozotocin-Induced T2DM Mice

Anthocyanins can prevent and ameliorate type 2 diabetes mellitus (T2DM), but its mechanism of action has not been fully established. IKK/NF-κB and JAK/Stat pathways have multiple effects, triggering T2DM. Liver abnormalities in individuals with T2DM are detrimental to glycemic control. We determined whether anthocyanins could improve the liver of individuals with T2DM using IKK/NF-κB and JAK/Stat. We established a T2DM mouse model using a high-fat diet and streptozotocin and then performed Aronia melanocarpa anthocyanin extracts' (AMAEs') administration for 5 weeks. AMAEs improved blood glucose and hyperinsulinemia of T2DM mice. In the liver of AMAE-administered T2DM mice, ROS, IKKβ/NF-κB p65, and JAK2/Stat3/5B signalings were down-regulated, thereby reducing the suppressor of cytokine signaling 3 (SOCS3), iNOS, and inflammatory mediators. AMAE-improved hyperinsulinemia also down-regulated SOCS3 by decreasing p-Stat5B in hepatocytes. AMAEs enhanced glucose uptake and conversion and decreased hepatocyte enlargement and inflammatory cells in the liver of T2DM mice. These indicated that AMAEs could alleviate oxidative stress, insulin resistance, inflammation, and tissue damage in the liver of T2DM mice through inhibiting NF-κB p65 and Stat3/5B.

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.

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.

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

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

The Genetics of Diabetes: What We Can Learn from Drosophila

Diabetes mellitus is a heterogeneous disease characterized by hyperglycemia due to impaired insulin secretion and/or action. All diabetes types have a strong genetic component. The most frequent forms, type 1 diabetes (T1D), type 2 diabetes (T2D) and gestational diabetes mellitus (GDM), are multifactorial syndromes associated with several genes’ effects together with environmental factors. Conversely, rare forms, neonatal diabetes mellitus (NDM) and maturity onset diabetes of the young (MODY), are caused by mutations in single genes. Large scale genome screenings led to the identification of hundreds of putative causative genes for multigenic diabetes, but all the loci identified so far explain only a small proportion of heritability. Nevertheless, several recent studies allowed not only the identification of some genes as causative, but also as putative targets of new drugs. Although monogenic forms of diabetes are the most suited to perform a precision approach and allow an accurate diagnosis, at least 80% of all monogenic cases remain still undiagnosed. The knowledge acquired so far addresses the future work towards a study more focused on the identification of diabetes causal variants; this aim will be reached only by combining expertise from different areas. In this perspective, model organism research is crucial. This review traces an overview of the genetics of diabetes and mainly focuses on Drosophila as a model system, describing how flies can contribute to diabetes knowledge advancement.

Genetic Association of Solute Carrier Transporter Gene Variants with Metformin Response

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by elevated blood glucose levels and is influenced by both genetic and environmental factors. It is treated with various classes of oral antidiabetic drugs, however, response to treatment is highly variable with patients failing to achieve adequate glycemic control. Treatment response variability has been associated with single nucleotide polymorphisms (SNPs) which influence the pharma-cokinetics and pharmacodynamics of drug(s). The aim of this study was to evaluate the genetic association of 17 SNPs and the response to metformin therapy in patients diagnosed with diabetes from the indigenous Nguni population of South Africa. One hundred and forty indigenous African patients diagnosed with T2DM were recruited and genotyped using the MassARRAY® system. Therapeutic response of patients was ascertained by a change in Hb A^1c. Two SNPs (rs1801282 and rs6265) were monomorphic. All other variants were within the Hardy-Weinberg equilibrium (HWE). The T allele of the SLC variant rs316009 [odds ratio (OR) = 0.25, 95% confidence interval (95% CI) = 0.01-0.09, p value = 0.044] and the CT genotype of the PCK1 variant rs4810083 (OR = 2.80, 95% CI = 1.01-7.79, p value = 0.049) were associated with an improved response to treatment after adjustment. No association was observed with post Bonferroni correction. Moreover, this study provides important additional data regarding possible associations between genetic variants and metformin therapy outcomes. In addition, this is one of the first studies providing genetic data from the understudied indigenous sub-Saharan African populations.

Therapeutic Dilemma in personalized medicine

The practice of medicine depends over a long time on identifying therapies that target an entire population. The increase in scientific knowledge over the years has led to the gradual change towards individualization and personalization of drug therapy. The hope of this change is to achieve a better clinical response to given medications and reduction of their adverse effects. Tailoring of medicine on the road of personalized medicine considers molecular and genetic mapping of the individual. However, many factors still impede the smooth application of personalized medicine and represent challenges or limitations in its achievement. In this article, we put some clinical examples that show dilemmas in the application of personalized medicine such as opioids in pain control, fluoropyrimidines in malignancy, clopidogrel as antiplatelet therapy and oral hypoglycemic drugs in Type2 diabetes in adults. Shaping the future of medicine through the application of personalized medicine for a particular patient needs to put into consideration many factors such as patient's genetic makeup and life style, pathology of the disease and dynamic changes in its course as well as interactions between administered drugs and their effects on metabolizing enzymes. We hope in the coming years, the personalized medicine will foster changes in health care system in the way not only to treat patients but also to prevent diseases.

Heparin impairs skeletal muscle glucose uptake by inhibiting insulin binding to insulin receptor

Aim

Heparin, a widely used antithrombotic drug has many other anticoagulant-independent physiological functions. Here, we elucidate a novel role of heparin in glucose homeostasis, suggesting an approach for developing heparin-targeted therapies for diabetes.

Methods

For serum heparin levels and correlation analysis, 122 volunteer's plasma, DIO (4 weeks HFD) and db/db mice serums were collected and used for spectrophotometric determination. OGTT, ITT, 2-NBDG uptake and muscle GLUT4 immunofluorescence were detected in chronic intraperitoneal injection of heparin or heparinase (16 days) and muscle-specific loss-of-function mice. In 293T cells, the binding of insulin to its receptor was detected by fluorescence resonance energy transfer (FRET), Myc-GLUT4-mCherry plasmid was used in GLUT4 translocation. In vitro, C2C12 cells as mouse myoblast cells were further verified the effects of heparin on glucose homeostasis through 2-NBDG uptake, Western blot and co-immunoprecipitation.

Results

Serum concentrations of heparin are positively associated with blood glucose levels in humans and are significantly increased in diet-induced and db/db obesity mouse models. Consistently, a chronic intraperitoneal injection of heparin results in hyperglycaemia, glucose intolerance and insulin resistance. These effects are independent of heparin's anticoagulant function and associated with decreases in glucose uptake and translocation of glucose transporter type 4 (GLUT4) in skeletal muscle. By using a muscle-specific loss-of-function mouse model, we further demonstrated that muscle GLUT4 is required for the detrimental effects of heparin on glucose homeostasis.

Conclusions

Heparin reduced insulin binding to its receptor by interacting with insulin and inhibited insulin-mediated activation of the PI3K/Akt signalling pathway in skeletal muscle, which leads to impaired glucose uptake and hyperglycaemia.

Role of Wnt signaling pathways in type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) has become a major global public health issue in the twenty-first century and its incidence has increased each year. Wnt signaling pathways are a set of multi-downstream signaling pathways activated by the binding of Wnt ligands to membrane protein receptors. Wnt signaling pathways regulate protein expression and play important roles in protecting the body's normal physiological metabolism. This review describes Wnt signaling pathways, and then aims to reveal how Wnt signaling pathways participate in the occurrence and development of T2DM. We found that Wnt/c-Jun N-terminal kinase signaling was closely associated with insulin resistance, inflammatory response, and pancreatic β-cell and endothelial dysfunction. β-catenin/transcription factor 7-like 2 (TCF7L2)-mediated and calcineurin/nuclear factor of activated T cells-mediated target genes were involved in insulin synthesis and secretion, insulin degradation, pancreatic β-cell growth and regeneration, and functional application of pancreatic β-cells. In addition, polymorphisms in the TCF7L2 gene could increase risk of T2DM according to previous and the most current results, and the T allele of its variants was a more adverse factor for abnormal pancreatic β-cell function and impaired glucose tolerance in patients with T2DM. These findings indicate a strong correlation between Wnt signaling pathways and T2DM, particularly in terms of pancreatic islet dysfunction and insulin resistance, and new therapeutic targets for T2DM may be identified.

Antidiabetic Properties of Curcumin: Insights on New Mechanisms

Plant extracts have been used to treat a wide range of human diseases. Curcumin, a bioactive polyphenol derived from Curcuma longa L., exhibits therapeutic effects against diabetes while only negligible adverse effects have been observed. Antioxidant and anti-inflammatory properties of curcumin are the main and well-recognized pharmacological effects that might explain its antidiabetic effects. Additionally, curcumin may regulate novel signaling molecules and enzymes involved in the pathophysiology of diabetes, including glucagon-like peptide-1, dipeptidyl peptidase-4, glucose transporters, alpha-glycosidase, alpha-amylase, and peroxisome proliferator-activated receptor gamma (PPARγ). Recent findings from in vitro and in vivo studies on novel signaling pathways involved in the potential beneficial effects of curcumin for the treatment of diabetes are discussed in this review.

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.

Pharmacogenetic Aspects of Type 2 Diabetes Treatment

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

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

Role of Genetic Variations in the Hepatic Handling of Drugs

The liver plays a pivotal role in drug handling due to its contribution to the processes of detoxification (phases 0 to 3). In addition, the liver is also an essential organ for the mechanism of action of many families of drugs, such as cholesterol-lowering, antidiabetic, antiviral, anticoagulant, and anticancer agents. Accordingly, the presence of genetic variants affecting a high number of genes expressed in hepatocytes has a critical clinical impact. The present review is not an exhaustive list but a general overview of the most relevant variants of genes involved in detoxification phases. The available information highlights the importance of defining the genomic profile responsible for the hepatic handling of drugs in many ways, such as (i) impaired uptake, (ii) enhanced export, (iii) altered metabolism due to decreased activation of prodrugs or enhanced inactivation of active compounds, and (iv) altered molecular targets located in the liver due to genetic changes or activation/downregulation of alternative/compensatory pathways. In conclusion, the advance in this field of modern pharmacology, which allows one to predict the outcome of the treatments and to develop more effective and selective agents able to overcome the lack of effect associated with the existence of some genetic variants, is required to step forward toward a more personalized medicine.

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.

Precision medicine in diabetes prevention, classification and management

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

Mast cells participate in chronic low-grade inflammation within adipose tissue

Obesity is reckoned as one of the civilization diseases, posing a considerable global health issue. Evidence points towards a contribution of multitude immune cell populations in obesity pathomechanism and the development of chronic low-grade inflammation in the expanded adipose tissue. Notably, adipose tissue is a reservoir of mast cells which number in individuals with obesity particularly increased. Some of them tend to degranulation what generate secretion of strong pro-inflammatory and regulatory mediators, as well as cytokines/chemokines. Several lines of evidence suggest that mast cells are strictly associated with pro-inflammatory status in adipose tissue by their indirect impact on immune cell attraction and activation. Furthermore, mast cells affect adipose tissue remodelling and fibrosis by adipocyte differentiation, fibroblast proliferation and enhancing extracellular matrix proteins expression. This review will summarize current knowledge on mast cell features and their role in the development of chronic low-grade inflammation within adipose tissue.

Role of the PKCβII/JNK signaling pathway in acute glucose fluctuation-induced apoptosis of rat vascular endothelial cells

AIMS

The purpose of this study was to investigate the mechanism of vascular endothelial cell apoptosis induced by acute blood glucose fluctuation.

METHODS

Thirty rats were assigned to three groups: normal saline (SAL group), constant high glucose (CHG group) and acute blood glucose fluctuation (AFG) group. Other forty rats were assigned to SAL group, AFG group, LY group (PKCβ inhibitor LY333531 was injected intragastrically to the rats who were under acute blood glucose fluctuation) and SP group (JNK inhibitor SP600125 was injected intraperitoneally to the rats who were under acute blood glucose fluctuation). Oxidative stress and inflammatory cytokines were detected. TUNEL was performed to detect apoptosis. Pro-caspase-3, caspase-3 p17, JNK, PKC-βII and insulin signaling-related protein expression were tested by Western blotting.

RESULTS

After administration of LY333531, AFG-induced membrane translocation of PKCβII protein was inhibited, but SP600125 failed to affect AFG-induced PKCβII membrane translocation. After administration of LY333531, the AFG-induced increase in JNK activity was significantly compromised. LY333531 inhibited AFG-induced oxidative stress. However, SP600125 only slightly inhibited AFG-induced oxidative stress reaction (P > 0.05). Both LY333531 and SP600125 can reverse AFG-induced endothelial cell apoptosis increase, inflammatory cytokines levels rise and insulin signaling impairment.

CONCLUSIONS

It is necessary to actively control blood glucose and avoid significant glucose fluctuation. PKCβII/JNK may serve as a target, and inhibitors of PKCβII/JNK may be used to help prevent cardiovascular diseases in patients with poor glucose control or significant glucose fluctuation.

Identification of genetic variants in pharmacogenetic genes associated with type 2 diabetes in a Mexican-Mestizo population

Type 2 diabetes mellitus (T2DM) is one of the most prevalent chronic pathologies in the world. In developing countries, such as Mexico, its prevalence represents an important public health and research issue. Determining factors triggering T2DM are environmental and genetic. While diet, exercise and proper weight control are the first measures recommended to improve the quality of life and life expectancy of patients, pharmacological treatment is usually the next step. Within every population there are variations in interindividual drug response, which may be due to genetic background. Some of the most frequent first line T2DM treatments in developing countries are sulfonylureas (SU), whose targets are ATP-sensitive potassium channels (K_ATP). Single nucleotide polymorphisms (SNPs) of the K_ATP coding genes, potassium voltage-gated channel subfamily J member 11 (KCNJ11) and ATP binding cassette subfamily C member 8 (ABCC8) have been associated with SU response variability. To date, there is little information regarding the mechanism by which these SNPs work within Mexican populations. The present study describes the distribution of three SNPs [KCNJ11 rs5219 (E23K), ABCC8 rs757110 (S1369A) and rs1799854 (-3C/T)] among Mestizo Mexican (MM) T2DM patients, and compares it with published data on various healthy subjects and T2DM populations. Through this comparison, no difference in the KCNJ11 rs5219 and ABCC8 rs757110 allelic and genotypic frequencies in MM were observed compared with the majority of the reported populations of healthy and diabetic individuals among other ethnic groups; except for African and Colombian individuals. By contrast, ABCC8 rs1799854 genomic and allelic frequencies among MM were observed to be significantly different from those reported by the 1000 Genomes Project, and from diabetic patients within other populations reported in the literature, such as the European, Asian and Latin-American individuals [T=0.704, G=0.296; CC=0.506, CT=0.397, TT=0.097; 95% confidence interval (CI); P≤0.05]; except for South Asian and Iberian populations, which may reflect the admixture origins of the present Mexican population. This genetic similarity has not been observed in the other Latin-American groups. To the best of our knowledge, this is the first study of ABCC8 rs757110 and rs1799854 SNP frequencies in any Mexican population and, specifically with diabetic Mexicans. Knowledge of the genetic structure of different populations is key to understanding the interindividual responses to drugs, such as SU and whether genotypic differences affect clinical outcome.

Targeting endothelial metaflammation to counteract diabesity cardiovascular risk: Current and perspective therapeutic options

The association of obesity and diabetes, termed "diabesity", defines a combination of primarily metabolic disorders with insulin resistance as the underlying common pathophysiology. Cardiovascular disorders associated with diabesity represent the leading cause of morbidity and mortality in the Western world. This makes diabesity, with its rising impacts on both health and economics, one of the most challenging biomedical and social threats of present century. The emerging comprehension of the genes whose alteration confers inter-individual differences on risk factors for diabetes or obesity, together with the potential role of genetically determined variants on mechanisms controlling responsiveness, effectiveness and safety of anti-diabetic therapy underlines the need of additional knowledge on molecular mechanisms involved in the pathophysiology of diabesity. Endothelial cell dysfunction, resulting from the unbalanced production of endothelial-derived vascular mediators, is known to be present at the earliest stages of insulin resistance and obesity, and may precede the clinical diagnosis of diabetes by several years. Once considered as a mere consequence of metabolic abnormalities, it is now clear that endothelial dysfunctional activity may play a pivotal role in the progression of diabesity. In the vicious circle where vascular defects and metabolic disturbances worsen and reinforce each other, a low-grade, chronic, and 'cold' inflammation (metaflammation) has been suggested to serve as the pathophysiological link that binds endothelial and metabolic dysfunctions. In this paradigm, it is important to consider how traditional antidiabetic treatments (specifically addressing metabolic dysregulation) may directly impact on inflammatory processes or cardiovascular function. Indeed, not all drugs currently available to treat diabetes possess the same anti-inflammatory potential, or target endothelial cell function equally. Perspective strategies pointing at reducing metaflammation or directly addressing endothelial dysfunction may disclose beneficial consequences on metabolic regulation. This review focuses on existing and potential new approaches ameliorating endothelial dysfunction and vascular inflammation in the context of diabesity.

Role of continuous glucose monitoring for type 2 in diabetes management and research

The advent of continuous glucose monitoring (CGM) is a significant stride forward in our ability to better understand the glycemic status of our patients. Current clinical practice employs two forms of CGM: professional (retrospective or "masked") and personal (real-time) to evaluate and/or monitor glycemic control. Most studies using professional and personal CGM have been done in those with type 1 diabetes (T1D). However, this technology is agnostic to the type of diabetes and can also be used in those with type 2 diabetes (T2D). The value of professional CGM in T2D for physicians, patients, and researchers is derived from its ability to: (1) to discover previously unknown hyper- and hypoglycemia (silent and symptomatic); (2) measure glycemic control directly rather than through the surrogate metric of hemoglobin A1C (HbA1C) permitting the observation of a wide variety of metrics that include glycemic variability, the percent of time within, below and above target glucose levels, the severity of hypo- and hyperglycemia throughout the day and night; (3) provide actionable information for healthcare providers derived by the CGM report; (4) better manage patients on hemodialysis; and (5) effectively and efficiently analyze glycemic effects of new interventions whether they be pharmaceuticals (duration of action, pharmacodynamics, safety, and efficacy), devices, or psycho-educational. Personal CGM has also been successfully used in a small number of studies as a behavior modification tool in those with T2D. This comprehensive review describes the differences between professional and personal CGM and the evidence for the use of each form of CGM in T2D. Finally, the opinions of key professional societies on the use of CGM in T2D are presented.