Data on the association of CYP2C9 genetic polymorphisms with sulfonylurea ( SU )‐induced hypoglycaemia ( SH ) are inconsistent. Recent studies showed that variants in the P450 oxidoreductase ( POR ) gene could affect CYP2C9 activity. In this study, we explored the effects of POR*28 and combined CYP2C9*2 and CYP2C9*3 genotypes on SH and the efficacy of SU treatment in type 2 diabetes. A total of 1770 patients were included in the analysis of SU efficacy, assessed as the combined outcome of the HbA1c reduction and the prescribed SU daily dose. Sixty‐nine patients with severe SH were compared with 311 control patients. The number of CYP2C9 deficient alleles was associated with nearly three‐fold higher odds of hypoglycaemia ( OR , 2.81; 95% CI , 1.30‐6.09; P = .009) and better response to SU treatment (β, −0.218; SE , 0.074; P = .003) only in patients carrying the POR*1/*1 genotype. Our results indicate that interaction between CYP2C9 and POR genes may be an important determinant of efficacy and severe adverse effects of SU treatment.

Type 2 diabetes (T2D) has a continuously rising prevalence worldwide. Pharmacogenetics has been recognized as a promising concept for pharmacological treatment of T2D, as antidiabetic drugs are not equally effective and safe for all patients, and the costs of diabetes treatment are increasing. The latest published guidelines on T2D treatment firmly endorse the use of newer antidiabetic drugs, sodium-glucose cotransporter-2 inhibitors (SGLT2i), dipeptidyl peptidase-4 inhibitors (DPP-IVi), and glucagon-like peptide-1 receptor agonists (GLP-1RA), considering their satisfactory pharmacological effect and good safety profile. Furthermore, SGLT2i and GLP-1RA show protective effects in patients with established atherosclerotic cardiovascular disease and chronic kidney disease. However, there has been growing evidence that the effectiveness and safety of these drug classes could depend on genetic variability. Here, we summarized the results of the published studies on the pharmacogenetic biomarkers for the three drug classes. A number of genetic variations have been investigated so far. The explored candidate genes mostly encode drug targets, drug-metabolizing enzymes, and genes linked to T2D risk. Although many of the results are promising, it is still necessary to obtain more information from larger controlled studies to confirm their clinical significance. This approach may lead towards more personalized treatment for patients with T2D.

The response to metformin, the most commonly used drug for the treatment of type 2 diabetes (T2D), is highly variable. The common variant rs7903146 C>T within the transcription factor 7-like 2 gene (TCF7L2) is the strongest genetic risk factor associated with T2D to date. In this study, we explored the effects of the TCF7L2 rs7903146 genotype on metformin response in T2D. The study included 86 newly diagnosed patients with T2D, incident users of metformin. Levels of fasting glucose, insulin, HbA1c, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, and anthropometric parameters were measured prior to metformin therapy, and 6 and 12 months after the treatment. Genotyping of the TCF7L2 rs7903146 was performed by the Sequenom MassARRAY® iPLEX® platform. At baseline, the diabetes risk allele (T) showed an association with lower triglyceride levels (p = 0.037). After 12 months of metformin treatment, the T allele was associated with 25.9% lower fasting insulin levels (95% CI 10.9–38.3%, p = 0.002) and 29.1% lower HOMA-IR index (95% CI 10.1–44.1%, p = 0.005), after adjustment for baseline values. Moreover, the T allele was associated with 6.7% lower fasting glucose levels (95% CI 1.1–12.0%, p = 0.021), adjusted for baseline glucose and baseline HOMA-%B levels, after 6 months of metformin treatment. This effect was more pronounced in the TT carriers who had 16.8% lower fasting glucose levels (95% CI 7.0–25.6%, p = 0.002) compared to the patients with CC genotype. Our results suggest that the TCF7L2 rs7903146 variant affects markers of insulin resistance and glycemic response to metformin in newly diagnosed patients with T2D within the first year of metformin treatment.

The antidiabetic drug gliclazide is partly metabolized by CYP2C19, the main enzyme involved in omeprazole metabolism. The aim of the study was to explore the interaction between omeprazole and gliclazide in relation to CYP2C19 phenotype using physiologically based pharmacokinetic (PBPK) modeling approach. Developed PBPK models were verified using in vivo pharmacokinetic profiles obtained from a clinical trial on omeprazole-gliclazide interaction in healthy volunteers, CYP2C19 normal/rapid/ultrarapid metabolizers (NM/RM/UM). In addition, the association of omeprazole cotreatment with gliclazide-induced hypoglycemia was explored in 267 patients with type 2 diabetes (T2D) from the GoDARTS cohort, Scotland. The PBPK simulations predicted 1.4–1.6-fold higher gliclazide area under the curve (AUC) after 5-day treatment with 20 mg omeprazole in all CYP2C19 phenotype groups except in poor metabolizers. The predicted gliclazide AUC increased 2.1 and 2.5-fold in intermediate metabolizers, and 2.6- and 3.8-fold in NM/RM/UM group, after simulated 20-day dosing with 40 mg omeprazole once and twice daily, respectively. The predicted results were corroborated by findings in patients with T2D which demonstrated 3.3-fold higher odds of severe gliclazide-induced hypoglycemia in NM/RM/UM patients concomitantly treated with omeprazole. Our results indicate that omeprazole may increase exposure to gliclazide and thus increase the risk of gliclazide-associated hypoglycemia in the majority of patients.