Pharmacogenetics of oral antidiabetes drugs: evidence for diverse signals at the IRS1 locus

Interactions between diabetic and hypertensive drugs: a pharmacogenetics approach

Diabetes is known to increase susceptibility to hypertension due to increase in inflammation, oxidative stress, and endothelial dysfunction, leading to vascular stiffness. The polytherapy might lead to several drug-drug interactions (DDIs), which cause certain life-threatening complications such as diabetic nephropathy and hypoglycaemia. So, in this review we focused on drug-drug interactions and impact of genetic factors on drug responses for better disease management. Drug-drug interactions (DDIs) may act either synergistically or antagonistically. For instance, a combination of metformin with angiotensin II receptor antagonist or angiotensin-converting enzyme inhibitors (ACEIs) synergistically improves glucose absorption, whereas the same hypertensive drug combination with sulphonylurea might cause severe hypoglycaemia sometimes. Thiazolidinediones (TDZs) can cause fluid retention and heart failure when taken alone, but a combination of angiotensin II receptor antagonist with TZDs prevents these side effects. Interindividual genetic variation affects the DDI response. We found two prominent genes, GLUT4 and PPAR-γ, which are common targets for most of the drug. So, all of these findings established a connection between drug-drug interaction and genetics, which might be used for effective disease management.

Insulin receptor substrate-1 gene polymorphism and lipid panel data in type 2 diabetic patients with comorbid obesity and/or essential hypertension

Objective. The hallmarks of type 2 diabetes mellitus (T2DM) are insulin resistance (IR) and insulin receptor substrate (IRS) proteins essential for the insulin signaling. IRS-1 gene has not only been shown to be associated with T2DM, but also has indicated that it may significantly correlate with diabetic complications, such as coronary heart disease and obesity. The aim of this study was to evaluate changes of the lipid panel data in T2DM patients with comorbid obesity and/or essential hypertension in connection with the IRS-1 (rs2943640) polymorphism. Methods. The study involved 33 T2DM patients and 10 healthy individuals. The IRS-1 (rs2943640) polymorphism was genotyped using a TaqMan real-time polymerase chain reaction method. Blood serum lipid panel data were determined with commercially available kits using a Cobas 6000 analyzer. Results. Analysis of the serum lipid panel data depending on the presence of the C/A alleles of IRS-1 (rs2943640) polymorphism in T2DM patients, regardless of the presence/absence of comorbidities, showed significantly lower level of high-density lipoprotein cholesterol (HDL-C) and significantly higher level of non-HDL-C in the carriers of C allele vs. carriers of A allele. In T2DM patients with comorbid obesity and essential hypertension, proatherogenic lipid changes were found in both C and A alleles carriers. Analysis of the effect of IRS-1 (rs2943640) genotypes on serum lipid panel data in T2DM patients, regardless of the presence/absence of comorbidities, showed that the CC genotype carriers had more pronounced pro-atherogenic changes vs. carriers of СА and АА genotypes. In the comorbid course of T2DM (both in combination with obesity and obesity and essential hypertension), pro-atherogenic changes were found in the carriers of the CA genotype of IRS-1 (rs2943640) polymorphism. Conclusions. The presence of the C allele of IRS-1 (rs2943640) polymorphism in both homo-zygous and heterozygous states indicates increased risk of pro-atherogenic changes in T2DM patients with comorbid obesity and/or essential hypertension.

Insulin Receptor Substrate 1 Gly972Arg (rs1801278) Polymorphism Is Associated with Obesity and Insulin Resistance in Kashmiri Women with Polycystic Ovary Syndrome

Background: Polycystic ovary syndrome (PCOS) is commonly associated with metabolic abnormalities such as hyperinsulinemia, insulin resistance and obesity. The genetic variants of genes regulating insulin action, expression and regulation are suggested as possible factors involved in development and severity of clinical manifestations in PCOS. Aim: We investigated whether IRS-1Gly972Arg (rs1801278) polymorphism is associated with increased risk of PCOS in Kashmiri women. The correlation of various clinical, metabolic and hormonal markers with rs1801278 single nucleotide polymorphism was analyzed. The genotypic−phenotypic association of clinical manifestations of PCOS with the tested genetic variant was also assessed. Results: There were no significant differences in allele frequency (OR = 0.87, CI = 0.59−1.29, χ2 = 0.456, p = 0.499) or genotypic distribution (χ2 = 3.73, p = 0.15) between PCOS women and controls. No significant association was also found in the dominant (OR = 1.63, χ2 = 0.377, p = 0.53), recessive (OR = 0.79, χ2 = 1.01, p = 0.31) or heterozygote vs. homozygote (OR = 1.34, χ2 = 1.53, p = 0.22) genotype model analysis. The genotype−phenotype correlation analysis showed that the Arg allele was significantly associated with increased central adiposity markers hip circumference (p = 0.012), and body adiposity index BAI (p = 0.002) in the recessive model in PCOS women. The two-hour glucose (p = 0.04) and insulin resistance marker HOMA (p = 0.44) were significantly higher in Arg allele carriers. The androgen excess markers dehydroepiandrosterone sulfate DHEAS (p = 0.02), Ferriman−Gallwey score (p = 0.012), prevalence of acne, alopecia and hirsutism (all p < 0.01) were significantly elevated in the wild-type GG genotype. Conclusions:IRS-1Gly972Arg genetic variant does not increase the risk of PCOS in Kashmiri women. However, this polymorphism is associated with clinical manifestations of insulin resistance, obesity and hyperandrogenism, suggesting its possible role in variable phenotypic manifestations of PCOS.

Novel susceptibility loci identified in a genome-wide association study of type 2 diabetes complications in population of Latvia

BACKGROUND

Type 2 diabetes complications cause a serious emotional and economical burden to patients and healthcare systems globally. Management of both acute and chronic complications of diabetes, which dramatically impair the quality of patients' life, is still an unsolved issue in diabetes care, suggesting a need for early identification of individuals with high risk for developing diabetes complications.

METHODS

We performed a genome-wide association study in 601 type 2 diabetes patients after stratifying them according to the presence or absence of four types of diabetes complications: diabetic neuropathy, diabetic nephropathy, macrovascular complications, and ophthalmic complications.

RESULTS

The analysis revealed ten novel associations showing genome-wide significance, including rs1132787 (GYPA, OR = 2.71; 95% CI = 2.02-3.64) and diabetic neuropathy, rs2477088 (PDE4DIP, OR = 2.50; 95% CI = 1.87-3.34), rs4852954 (NAT8, OR = 2.27; 95% CI = 2.71-3.01), rs6032 (F5, OR = 2.12; 95% CI = 1.63-2.77), rs6935464 (RPS6KA2, OR = 2.25; 95% CI = 6.69-3.01) and macrovascular complications, rs3095447 (CCDC146, OR = 2.18; 95% CI = 1.66-2.87) and ophthalmic complications. By applying the targeted approach of previously reported susceptibility loci we managed to replicate three associations: MAPK14 (rs3761980, rs80028505) and diabetic neuropathy, APOL1 (rs136161) and diabetic nephropathy.

CONCLUSIONS

Together these results provide further evidence for the implication of genetic factors in the development of type 2 diabetes complications and highlight several potential key loci, able to modify the risk of developing these conditions. Moreover, the candidate variant approach proves a strong and consistent effect for multiple variants across different populations.

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.

Estimation of Mortality Risk in Type 2 Diabetic Patients (ENFORCE): An Inexpensive and Parsimonious Prediction Model

CONTEXT

We previously developed and validated an inexpensive and parsimonious prediction model of 2-year all-cause mortality in real-life patients with type 2 diabetes.

OBJECTIVE

This model, now named ENFORCE (EstimatioN oF mORtality risk in type 2 diabetiC patiEnts), was investigated in terms of (i) prediction performance at 6 years, a more clinically useful time-horizon; (ii) further validation in an independent sample; and (iii) performance comparison in a real-life vs a clinical trial setting.

DESIGN

Observational prospective randomized clinical trial.

SETTING

White patients with type 2 diabetes.

PATIENTS

Gargano Mortality Study (GMS; n = 1019), Foggia Mortality Study (FMS; n = 1045), and Pisa Mortality Study (PMS; n = 972) as real-life samples and the standard glycemic arm of the ACCORD (Action to Control Cardiovascular Risk in Diabetes) clinical trial (n = 3150).

MAIN OUTCOME MEASURE

The endpoint was all-cause mortality. Prediction accuracy and calibration were estimated to assess the model's performances.

RESULTS

ENFORCE yielded 6-year mortality C-statistics of 0.79, 0.78, and 0.75 in GMS, FMS, and PMS, respectively (P heterogeneity = 0.71). Pooling the three cohorts showed a 6-year mortality C-statistic of 0.80. In the ACCORD trial, ENFORCE achieved a C-statistic of 0.68, a value significantly lower than that obtained in the pooled real-life samples (P < 0.0001). This difference resembles that observed with other models comparing real-life vs clinical trial settings, thus suggesting it is a true, replicable phenomenon.

CONCLUSIONS

The time horizon of ENFORCE has been extended to 6 years and validated in three independent samples. ENFORCE is a free and user-friendly risk calculator of all-cause mortality in white patients with type 2 diabetes from a real-life setting.

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.