Comparative Effectiveness of Oral Hypoglycemic Agents for Glycemic Control and Glycemic Variability in Patients with Type 2 Diabetes Mellitus: Using Flash Glucose Monitoring.

AIM: The study aimed to compare the effectiveness of oral hypoglycemic agents (OHAs) as monotherapy, dual and quadruple therapy for glycemic control (GC) and glycemic variability (GV) in patients with type 2 diabetes (T2DM) using flash glucose monitoring system (FGM). BACKGROUND: Diabetes management largely relies on HbA1c monitoring. Glycemic variability has been an evolving glycemic target for preventing complications related to type 2 diabetes mellitus. OBJECTIVE: The purpose of the study was to compare glycemic control measures and glycemic variability measures among study groups and to study the relationships between GC and GV indices. METHODS: Retrospectively, FGM data were collected from 50 T2DM patients. The patients were classified based on prescribed number of OHAs as monotherapy [group 1: Dipeptidyl peptidase- 4 (DPP-4) inhibitors (n=10), group 2: Sodium-glucose co-transporter-2 (SGLT2) inhibitors (n=10), group 3: Sulphonylureas (n=10), group 4: Dual therapy (n=10), and group 5: Quadruple therapy (n=10)]. Measures of GC and GV were evaluated. RESULTS: Significant differences between study groups were observed in GC and GV measurements. The SGLT2 inhibitors monotherapy group demonstrated optimal GC [eA1c (%): 6.5 ± 2.2; MBG: 140.80 ± 63.94; TIR: 60.60 ± 19.96] and GV (SD: 42.38 ± 34.57; CV: 27.85 ± 6.68; MAGE: 96.76 ± 52.47; MODD: 33.96 ± 22.91) in comparison to other study groups. On using Pearson correlation analysis, mean blood glucose (MBG) and mean amplitude of glycemic excursion (MAGE) showed moderate correlation (r = 0.742)(r2 = 0.551), depicting distinct glucose variabilities at the same mean blood glucose levels. CONCLUSION: The monotherapy group of SGLT2 inhibitors demonstrated glucose-lowering effects with reduced glycemic variability. Hence, optimum glycemic control is associated with decreased glycemic variability.

Biomarkers for Antiplatelet Therapies in Acute Ischemic Stroke: A Clinical Review.

Stroke is one of the world's leading causes of disability and death. Antiplatelet agents are administered to acute ischemic stroke patients as secondary prevention. Clopidogrel involves biotransformation by cytochrome P450 (CYP) enzymes into an active metabolite, and single nucleotide polymorphisms (SNPs) can influence the efficacy of this biotransformation. Despite the therapeutic advantages of aspirin, there is significant inter-individual heterogeneity in response to this antiplatelet drug. In this clinical review, the recent advances in the biomarkers of antiplatelet agents in acute ischemic stroke are discussed. The studies reviewed herein highlight the clinical relevance of antiplatelet resistance, pharmacotherapy of antiplatelet agents predicting drug response, strategies for identifying aspirin resistance, pharmacogenetic variants of antiplatelet agents, miRNAs, and extracellular vesicles (EVs) as biomarkers toward the personalized approach in the management of acute ischemic stroke. The precise pathways contributing to antiplatelet resistance are not very well known but are presumably multi-factorial. It is essential to understand the clinical relevance of clopidogrel and aspirin-related single nucleotide polymorphism (SNPs) as potential predictive and prognostic biomarkers. Prasugrel is a next-generation antiplatelet agent that prevents ADP-platelet activation by binding irreversibly to P2Y12 receptor. There are sporadic reports of prasugrel resistance and polymorphisms in the Platelet endothelial aggregation receptor-1 (PEAR1) that may contribute to a change in the pharmacodynamics response. Ticagrelor, a direct-acting P2Y12-receptor antagonist, is easily absorbed and partly metabolized to major AR-C124910XX metabolite (ARC). Ticagrelor's primary active metabolite, ARC124910XX (ARC), is formed via the most abundant hepatic cytochrome P450 (CYP) enzyme, CYP3A4, and CYP3A5. The integration of specific biomarkers, genotype as well as phenotype-related data in antiplatelet therapy stratification in patients with acute ischemic stroke will be of great clinical significance and could be used as a guiding tool for more effective, personalized therapy.

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.