The clinical response to sulphonylurea, an oral antidiabetic agent often used in combination with metformin to control blood glucose in type 2 diabetes (T2DM) patients, has been widely associated with a number of gene polymorphisms, particularly those involved in insulin release. We have reviewed the genetic markers of CYP2C9, ABCC8, KCNJ11, TCF7L2 (transcription factor 7-like 2), IRS-1 (insulin receptor substrate-1), CDKAL1, CDKN2A/2B, KCNQ1 and NOS1AP (nitric oxide synthase 1 adaptor protein) genes that predict treatment outcomes of sulphonylurea therapy. A convincing pattern for poor sulphonylurea response was observed in Caucasian T2DM patients with rs7903146 and rs1801278 polymorphisms of the TCF7L2 and IRS-1 genes, respectively. However, limitations in evaluating the available studies including dissimilarities in study design, definitions of clinical end points, sample sizes and types and doses of sulphonylureas used as well as ethnic variability make the clinical applications challenging. Future studies need to address these limitations to develop personalized sulphonylurea medicine for T2DM management.

Aims: To compare the cardiovascular, renal and safety outcomes of second-line glucose-lowering agents used in the management of people with type 2 diabetes.Methods: MEDLINE, EMBASE and CENTRAL were searched from inception to 13 July 2021 for randomised controlled trials comparing second-line glucose lowering therapies with placebo, standard care or one another. Primary outcomes included cardiovascular and renal outcomes. Secondary outcomes were non-cardiovascular adverse events. Risk ratios (RRs) and corresponding confidence intervals (CI) or credible intervals (CrI) were reported within pairwise and network meta-analysis. The quality of evidence was evaluated using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) criteria. Number needed to treat (NNT) and number needed (NNH) to harm were calculated at 5 years using incidence rates and RRs. PROSPERO (CRD42020168322). Results:We included 38 trials from seven classes of glucose-lowering therapies. Both sodium-glucose co-transporter-2 inhibitors (SGLT2i) and glucagon-like peptide 1 receptor agonists (GLP1RA) showed moderate to high certainty in reducing risk of 3-point major adverse cardiovascular events, 3P-MACE

Background Diabetes is one of the leading cause of chronic kidney disease (CKD) and end stage renal disease. This study aims to develop and validate different risk predictive models for incident CKD and CKD progression in people with type 2 diabetes (T2D). Methods We reviewed a cohort of people with T2D seeking care from two tertiary hospitals in the metropolitan cities of the state of Selangor and Negeri Sembilan from January 2012 to May 2021. To identify the three-year predictor of developing CKD (primary outcome) and CKD progression (secondary outcome), the dataset was randomly split into a training and test set. A Cox proportional hazards (CoxPH) model was developed to identify for predictors of developing CKD. The resultant CoxPH model was compared with other machine learning models on their performance using C-statistic. Results The cohorts included 1 992 participants, of which 295 had developed CKD and 442 reported worsening of kidney function. Equation for the three-year risk of developing CKD included gender, haemoglobin A1c, triglyceride and serum creatinine levels, estimated glomerular filtration rate, history of cardiovascular disease and diabetes duration. For risk of CKD progression, the model included systolic blood pressure, retinopathy and proteinuria. The CoxPH model was better at prediction compared to other machine learning models examined for incident CKD (C-statistic: training 0.826; test 0.874) and CKD progression (C-statistic: training 0.611; test 0.655). Risk calculator can be found at https://rs59.shinyapps.io/071221/. Conclusions The Cox regression model was the best performing modelto predict people with T2D who will develop a 3-year risk of incident CKD and CKD progression in a Malaysian cohort.

Background: Due to several limitations in the study designs of sulfonylurea pharmacogenomics studies, we investigated the clinical and genetic predictors of secondary sulfonylurea failure in Type 2 diabetes patients. Materials & methods: Patients receiving the maximum sulfonylurea and metformin doses for >1 year were enrolled. Secondary sulfonylurea failure was defined as HbA1c >7.0% (>53 mmol/mol) after a 12-month follow-up. Results: By multivariate analysis, increased insulin resistance (HOMA2-IR), baseline HbA1c >7.0%, residing in eastern Peninsular Malaysia, and the CC genotype of rs757110 ABCC8 gene polymorphism were independent predictors of secondary sulfonylurea failure (p < 0.05) while sulfonylurea-induced hypoglycemia was protective against such failure (p < 0.05). Conclusion: Sulfonylurea does not benefit patients with an increased risk of secondary sulfonylurea failure.

Aim: This study investigated the incidence of sulfonylurea-induced hypoglycemia and its predictors in Type 2 diabetes (T2D) patients. Patients & methods: In this prospective, observational study, T2D patients on maximal sulfonylurea-metformin therapy >1 year were enrolled. Hypoglycemia was defined as having symptoms or a blood glucose level <3.9 mmol/l. Results: Of the 401 patients, 120 (29.9%) developed sulfonylurea-induced hypoglycemia during the 12-month follow-up. The ABCC8 rs757110, KCNJ11 rs5219, CDKAL1 rs7756992 and KCNQ1 rs2237892 gene polymorphisms were not associated with sulfonylurea-induced hypoglycemia (p > 0.05). Prior history of hypoglycemia admission (odds ratio = 16.44; 95% CI: 1.74–154.33, p = 0.014) independently predicted its risk. Conclusion: Sulfonylurea-treated T2D patients who experienced severe hypoglycemia are at increased risk of future hypoglycemia episodes.