The presence of two reduced function variants in CYP2C9 influences the acute response to glipizide

Encyclopaedic Review of Glipizide Pre-clinical and Clinical Status

Glipizide is an oral glucose-lowering medication that is beneficial for the treatment of type 2 diabetes. This study compiles exhaustively all accessible information on glipizide, from preclinical to clinical studies. Glipizide may be used in concert with TRAIL to treat cancer cells; in vitro studies have shown that it suppresses angiogenesis and vasculogenesis while shielding cells from glycation-induced damage. Anticonvulsant effects and modifications in the pharmacokinetics of other medications, such as Divalproex Sodium, were seen in glipizide in vivo experiments. Propranolol amplifies glipizide's hypoglycemic effect briefly in normal animals but consistently enhances it in diabetic ones. In the treatment of cancer and neurodegenerative poly(Q) illnesses, glipizide has demonstrated to offer potential therapeutic advantages. It is ineffective in preventing DENA-induced liver cancer and may cause DNA damage over time. The way glipizide interacts with genetic variants may increase the risk of hypoglycemia. Combining Syzygium cumini and ARBE to glipizide may enhance glycemic and lipid control in type 2 diabetes. Individuals with coronary artery disease who take glipizide or glyburide have an increased risk of death. The risk of muscular responses and acute pancreatitis is minimal when glipizide and dulaglutide are combined. In conclusion, glipizide has shown promising therapeutic efficacy across a variety of disorders.

Pharmacogenetic Variation in Neanderthals and Denisovans and Implications for Human Health and Response to Medications

Modern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes-genes responsible for the processing of exogenous substances such as food, pollutants, and medications-as these can relate to changing environmental effects, and beneficial variants may have been retained as modern humans encountered new environments. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remain understudied. Here, we explore 11 key cytochrome P450 genes (CYP450) involved in 75% of all drug metabolizing reactions in three Neanderthal and one Denisovan individuals and examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these 11 CYP450 genes in archaic individuals and find important predicted phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaic CYP450 genes, which may result in altered metabolism in living people carrying these variants. We also identified several variants in the archaic CYP450 genes that are novel and unique to archaic humans as well as one gene, CYP2B6, that shows evidence for a gene duplication found only in Neanderthals and modern Africans. Finally, we highlight CYP2A6, CYP2C9, and CYP2J2, genes which show evidence for archaic introgression into modern humans and posit evolutionary hypotheses that explain their allele frequencies in modern populations.

Association of CYP2C9*2 Allele with Sulphonylurea-Induced Hypoglycaemia in Type 2 Diabetes Mellitus Patients: A Pharmacogenetic Study in Pakistani Pashtun Population

Polymorphism in cytochrome P450 (CYP) 2C9 enzyme is known to cause significant inter-individual differences in drug response and occurrence of adverse drug reactions. Different alleles of the CYP2C9 gene have been identified, but the notable alleles responsible for reduced enzyme activity are CYP2C9*2 and CYP2C9*3. No pharmacogenetic data are available on CYP2C9*2 and CYP2C9*3 alleles in the Pakistani population. In Pakistan, pharmacogenetics, which examines the relationship between genetic factors and drug response, are in the early stages of development. We, for the first time, investigated the association between the CYP2C9 variant alleles CYP2C9*2 and CYP2C9*3 and the incidence of hypoglycaemia in patients with Type 2 diabetes mellitus (T2DM) receiving sulphonylurea medications. A total of n = 400 individuals of Pashtun ethnicity were recruited from 10 different districts of Khyber Pakhtunkhwa, Pakistan to participate in the study. The study participants were divided into two distinct groups: the case group (n = 200) and the control group (n = 200). The case group consisted of individuals with T2DM who were receiving sulphonylurea medications and experienced hypoglycaemia with it, whereas the control group included individuals with T2DM who were receiving sulphonylurea medication but did not experience sulphonylurea-induced hypoglycaemia (SIH). Blood samples were obtained from study participants following informed consent. DNA was isolated from whole blood samples using a Wiz-Prep DNA extraction kit. Following DNA isolation, CYP2C9 alleles were genotyped using MassARRAY sequencing platform at the Centre of Genomics at the Rehman Medical Institute (RMI). The frequency of CYP2C9*2 (low-activity allele) was more frequent in the diabetic patients with SIH compared to the control group (17.5% vs. 6.0%, p = 0.021). The frequency of its corresponding genotype CYP2C9*1/*2 was higher in cases compared to the control group (10% vs. 6% with p = 0.036); the same was true for genotype CYP2C9*2/*2 (7% vs. 3.5% with p = 0.028). Logistic regression analysis evidenced potential association of CYP2C9*2 allele and its genotypes with SIH. When adjusted for confounding factors such as age, weight, sex, mean daily dose of sulphonylurea, and triglyceride level, the association between the CYP2C9*2 allele and hypoglycaemia remained consistent. Confounding factors played no role in SIH (insignificant p-value) because both groups (cases and controls) were closely matched in term of age, weight, sex, mean daily dose of sulphonylurea, and triglyceride levels. Our study suggests that genetic information about a patient's CYP2C9 gene/enzyme can potentially assist physicians in prescribing the most suitable and safest drug, based on their genetic make-up.

Genome-wide association analysis identifies ancestry-specific genetic variation associated with acute response to metformin and glipizide in SUGAR-MGH

AIMS/HYPOTHESIS

Characterisation of genetic variation that influences the response to glucose-lowering medications is instrumental to precision medicine for treatment of type 2 diabetes. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH) examined the acute response to metformin and glipizide in order to identify new pharmacogenetic associations for the response to common glucose-lowering medications in individuals at risk of type 2 diabetes.

METHODS

One thousand participants at risk for type 2 diabetes from diverse ancestries underwent sequential glipizide and metformin challenges. A genome-wide association study was performed using the Illumina Multi-Ethnic Genotyping Array. Imputation was performed with the TOPMed reference panel. Multiple linear regression using an additive model tested for association between genetic variants and primary endpoints of drug response. In a more focused analysis, we evaluated the influence of 804 unique type 2 diabetes- and glycaemic trait-associated variants on SUGAR-MGH outcomes and performed colocalisation analyses to identify shared genetic signals.

RESULTS

Five genome-wide significant variants were associated with metformin or glipizide response. The strongest association was between an African ancestry-specific variant (minor allele frequency [MAFAfr]=0.0283) at rs149403252 and lower fasting glucose at Visit 2 following metformin (p=1.9×10-9); carriers were found to have a 0.94 mmol/l larger decrease in fasting glucose. rs111770298, another African ancestry-specific variant (MAFAfr=0.0536), was associated with a reduced response to metformin (p=2.4×10-8), where carriers had a 0.29 mmol/l increase in fasting glucose compared with non-carriers, who experienced a 0.15 mmol/l decrease. This finding was validated in the Diabetes Prevention Program, where rs111770298 was associated with a worse glycaemic response to metformin: heterozygous carriers had an increase in HbA1c of 0.08% and non-carriers had an HbA1c increase of 0.01% after 1 year of treatment (p=3.3×10-3). We also identified associations between type 2 diabetes-associated variants and glycaemic response, including the type 2 diabetes-protective C allele of rs703972 near ZMIZ1 and increased levels of active glucagon-like peptide 1 (GLP-1) (p=1.6×10-5), supporting the role of alterations in incretin levels in type 2 diabetes pathophysiology.

CONCLUSIONS/INTERPRETATION

We present a well-phenotyped, densely genotyped, multi-ancestry resource to study gene-drug interactions, uncover novel variation associated with response to common glucose-lowering medications and provide insight into mechanisms of action of type 2 diabetes-related variation.

DATA AVAILABILITY

The complete summary statistics from this study are available at the Common Metabolic Diseases Knowledge Portal ( https://hugeamp.org ) and the GWAS Catalog ( www.ebi.ac.uk/gwas/ , accession IDs: GCST90269867 to GCST90269899).

Precision Medicine in Diabetes

Tailoring treatment or management to groups of individuals based on specific clinical, molecular, and genomic features is the concept of precision medicine. Diabetes is highly heterogenous with respect to clinical manifestations, disease progression, development of complications, and drug response. The current practice for drug treatment is largely based on evidence from clinical trials that report average effects. However, around half of patients with type 2 diabetes do not achieve glycaemic targets despite having a high level of adherence and there are substantial differences in the incidence of adverse outcomes. Therefore, there is a need to identify predictive markers that can inform differential drug responses at the point of prescribing. Recent advances in molecular genetics and increased availability of real-world and randomised trial data have started to increase our understanding of disease heterogeneity and its impact on potential treatments for specific groups. Leveraging information from simple clinical features (age, sex, BMI, ethnicity, and co-prescribed medications) and genomic markers has a potential to identify sub-groups who are likely to benefit from a given drug with minimal adverse effects. In this chapter, we will discuss the state of current evidence in the discovery of clinical and genetic markers that have the potential to optimise drug treatment in type 2 diabetes.

On the Verge of Precision Medicine in Diabetes

The epidemic of type 2 diabetes (T2D) is a significant global public health challenge and a major cause of morbidity and mortality. Despite the recent proliferation of pharmacological agents for the treatment of T2D, current therapies simply treat the symptom, i.e. hyperglycemia, and do not directly address the underlying disease process or modify the disease course. This article summarizes how genomic discovery has contributed to unraveling the heterogeneity in T2D, reviews relevant discoveries in the pharmacogenetics of five commonly prescribed glucose-lowering agents, presents evidence supporting how pharmacogenetics can be leveraged to advance precision medicine, and calls attention to important research gaps to its implementation to guide treatment choices.

Effects of CYP2C9*3 and *13 alleles on the pharmacokinetics and pharmacodynamics of glipizide in healthy Korean subjects

Glipizide is a second-generation sulfonylurea antidiabetic drug. It is principally metabolized to inactive metabolites by genetically polymorphic CYP2C9 enzyme. In this study, we investigated the effects of CYP2C9*3 and *13 variant alleles on the pharmacokinetics and pharmacodynamics of glipizide. Twenty-four healthy Korean volunteers (11 subjects with CYP2C9*1/*1, 8 subjects with CYP2C9*1/*3, and 5 subjects with CYP2C9*1/*13) were recruited for this study. They were administered a single oral dose of glipizide 5 mg. The plasma concentration of glipizide was quantified for pharmacokinetic analysis and plasma glucose and insulin concentrations were measured as pharmacodynamic parameters. The results represented that CYP2C9*3 and *13 alleles significantly affected the pharmacokinetics of glipizide. In subjects with CYP2C9*1/*3 and CYP2C9*1/*13 genotypes, the mean AUC_0-∞ were increased by 44.8% and 58.2%, respectively (both P < 0.001), compared to those of subjects with CYP2C9*1/*1 genotype, while effects of glipizide on plasma glucose and insulin levels were not significantly different between CYP2C9 genotype groups. In conclusion, individuals carrying the defective CYP2C9*3 and CYP2C9*13 alleles have markedly elevated plasma concentrations of glipizide compared with CYP2C9*1/*1 wild-type.

A pharmacogenetic pilot study of CYP2C9 common genetic variant and sulfonylureas therapeutic response in type 2 diabetes mellitus patients

Background

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that is associated with elevated blood glucose levels. Sulfonylureas (SFUs) are the most widely used among the oral antidiabetic drugs that are highly metabolized by cytochrome P450 family 2 subfamily C member 9 (CYP2C9). The CYP2C9 has been shown to be associated with a better glycemic response to SFUs and a lower treatment failure rate. The aim of the present study was to assess the influence of the CYP2C9 rs1067910 gene variant on the SFUs response in a group of Iranian patients for the first time.

Methods

Blood samples were taken from 30 patients with T2DM under sulfonylurea treatment. DNA extraction was performed using Salting out method, and then genotyping was performed by polymerase chain reaction (PCR) followed by Sanger sequencing.

Results

There was no significant difference in the fasting blood sugar (FBS) between T2DM patients with different genotypes before and after the treatment with SFUs (P = 0.073 and P = 0.893, respectively). Although HbA1c was significantly different among AA, CA and CC carriers before (P = 0.001) and after (P = 0.018) treatment, no significant change was observed after treatment in all three groups.

Conclusions

In the present study based on only 30 samples in pilot survey, it is shown that the therapeutic response to SFUs was not related to rs1057910 CYP2C9 variant.

Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

OBJECTIVE

Sulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.

RESEARCH DESIGN AND METHODS

As an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.

RESULTS

After establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.

CONCLUSIONS

We have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

A Polygenic Score for Type 2 Diabetes Risk Is Associated With Both the Acute and Sustained Response to Sulfonylureas

There is a limited understanding of how genetic loci associated with glycemic traits and type 2 diabetes (T2D) influence the response to antidiabetic medications. Polygenic scores provide increasing power to detect patterns of disease predisposition that might benefit from a targeted pharmacologic intervention. In the Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH), we constructed weighted polygenic scores using known genome-wide significant associations for T2D, fasting glucose, and fasting insulin, comprising 65, 43, and 13 single nucleotide polymorphisms, respectively. Multiple linear regression tested for associations between scores and glycemic traits as well as pharmacodynamic end points, adjusting for age, sex, race, and BMI. A higher T2D score was nominally associated with a shorter time to insulin peak, greater glucose area over the curve, shorter time to glucose trough, and steeper slope to glucose trough after glipizide. In replication, a higher T2D score was associated with a greater 1-year hemoglobin A1c reduction to sulfonylureas in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study (P = 0.02). Our findings suggest that individuals with a higher genetic burden for T2D experience a greater acute and sustained response to sulfonylureas.

[The pharmacogenetics of hypoglycemia and the glycemic variability at the patients ith type 2 diabetes mellitus]

AIM

To investigate the link between the hypoglycemia (registrated accurately by the professional Continuous Glucose Monitoring CGM; severe hypoglycemia at home) and the hetero-/homozygote carriage of single nucleotide polymorphisms (SNP) of cytochrome systems geneCYP2C9(rs1799853CYP2C9*2 иrs1057910CYP2C9*3) at the patients with Type 2 Diabetes Mellitus (T2DM) used sulphonylurea (SU).

MATERIALS AND METHODS

In Study Case-Control 120 T2DM-SU-patients genotyped by SNPs of geneCYP2C9(using PCR-RT) had been done the professional CGM (System iPro2, Medtronic) recorded Time in Range of Hypoglycemia (TIR-HYPO), level of Minimal CGM-hypoglycemia (MinGl) and standard CGM-parameters of Glycemic Variability. Severe hypoglycemia at home was recorded from visit to visit. The odds ratio (OR) of metabolic disturbances had been assessed for carriage SNPs in comparison with wide alleles.

RESULTS

The Study established that carriage of SNPsrs1799853andrs1057910geneCYP2C9at T2DM-SU-patients associated with rising of Glycemic Variability and frequency of CGM-hypoglycemia (MinGl decreasing, increasing of TIR-HYPO and number of Glycemia Excursion 4 mmol/L/h), as well as increasing severe hypoglycemia at home (p0.05). Thus, OR at the carriage ofrs1799853andrs1057910respectively equaled: for CGM-hypoglycemia 7.78 (3.0220.01) and 5.80 (0.23145.87); number of Glycemia Excursion 4 mmol/L/h 5.76 (2.2914.43) and 4.44 (1.4313.76); MinGl3.9 mmol/L 4.39 (1.7910.75) and 6.26 (1.8421.30); CV40% (vs30%) 3.63 (1.0412.62) and 15.22 (0.59393.94);p0.05.

CONCLUSION

At the real clinical practice the assessment of carriage of SNPs of geneCYP2C9before inclusion of SU to glucose-lowering scheme of T2DM-therapy it necessary to carry out for the detecting patients with a higher risk of hypoglycemia and rising of Glycemic Variability.

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

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