IntroductionThis study aims to establish the Knowledge, Attitudes and Practices (KAP) of the general population (people with and without diabetes) towards diabetes. The study will examine (a) recognition and understanding of causes, prevention and treatment strategies of diabetes; (b) identify the knowledge gaps and behavioural patterns that may hamper diabetes prevention and control; (c) stigma towards and stigma perceived by people with diabetes and (d) awareness of anti-diabetes campaigns.Methods and analysisThe study is a nationwide, cross-sectional study of Singapore’s general population aged 18 years and above (n=3000), comprising Chinese, Malay, Indian and other ethnic groups, who can understand English, Chinese, Malay or Tamil language. The sample was derived using a disproportionate stratified sampling using age and ethnicity. The proportion of respondents in each ethnic group (Chinese, Malay and Indian) was set to approximately 30%, while the proportion of respondents in each age group was set around 20% in order to ensure a sufficient sample size. The respondents will be administered questionnaires on diabetes KAP, stigma towards diabetes, lifestyle, diet and awareness of local anti-diabetes campaigns. The analysis will include descriptive statistics and multiple logistic and linear regression analyses to determine the socio-demographic correlates of correct recognition of diabetes, help-seeking preferences, as well as overall knowledge and attitudes among those with and without diabetes. We will consider a p value ≤0.05 as significant.Ethics and disseminationThis study protocol has been reviewed by the Institutional Research Review Committee and the National Healthcare Group Domain Specific Review Board (NHG DSRB Ref 2018/00430). The results of the study will be shared with policymakers and other stakeholders. There will be a local mass media briefing to disseminate the findings online, in print and on television and radio. The results will be published in peer-reviewed journals and presented in scientific meetings.

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Aims: Osteoprotegerin (OPG) is a glycoprotein from tumour necrosis factor receptor superfamily, responsible for osteoclastogenesis inhibition and associated with arterial calcification and stiffness. We describe the association between metabolic syndrome (MS) and OPG in type 2 diabetes mellitus patients. Methodology: We consecutively enrolled 1220 patients from our institution's Diabetes Centre from August 2011. Anthropometric data such as fasting blood/urine were obtained, and OPG was measured by enzyme-linked immunosorbent assay (ELISA). Results: Mean (standard deviation (SD)) of age and diabetes duration was 57.4 (10.9) years and 11.2 (8.9) years, respectively. Prevalence of MS was 64.3% (95% confidence interval ( Conclusion:Higher OPG levels were associated with risk of MS and microvascular complications. Studies are needed to test whether OPG could be a useful biomarker identifying patients at risk of vascular complications and whether further exploration of this pathway may lead novel therapeutic options.

Low-density lipoprotein cholesterol (LDL-C) is a major risk factor for atherosclerotic disease. Despite its limitations, Friedewald-calculated LDL-C (F-LDL-C) remains widely used for LDL-C determination. In this observational study of 1999 adults with type 2 diabetes mellitus (T2DM), we compare the accuracy of F-LDL-C to directly measured LDL-C (M-LDL-C) and derived and validated a new [SMART2D (Singapore Study of MAcro-angiopathy and Micro-Vascular Reactivity in Type 2 Diabetes)] formula to estimate LDL-C. From 1000 randomly selected patients, M-LDL-C was compared to F-LDL-C. Using multiple linear regression to identify independent predictors for M-LDL-C, the SMART2D equation was derived and subsequently validated in the next 981 patients. F-LDL-C was 0.367 (0.216) mmol/L lower than M-LDL-C. This difference was −0.009 (0.189) for SMART2D-LDL-C. Using F-LDL-C, 27% with M-LDL-C ≥2.6 mmol/L were classified as LDL-C <2.6 mmol/L, reduced to 2.1% when using SMART2D-LDL-C. With F-LDL-C, misclassification was greater when triglycerides were ≥2.2 mmol/L, especially for the lower LDL-C cut-offs (1.8 and 2.6 mmol/L), and this was markedly improved with SMART2D-LDL-C. In conclusion, in T2DM, F-LDL-C underestimates M-LDL-C, with misclassifications that may potentially have an impact on therapeutic decisions in T2DM. The SMART2D equation improves accuracy of estimate, reducing misclassifications. Trials will be needed to ascertain the clinical significance of these findings.

Type 2 Diabetes occurs as a result of defects in insulin secretion and its function. Although mechanisms of disease are not fully elucidated, it is recognized that a progressive decline in insulin secretory capacity is responsible for its occurrence and natural course. Metabolic syndrome, known to be a precursor of Type 2 diabetes, is characterized by a constellation of vascular risk factors, with obesity playing a central role. Obesity contributes to impaired insulin function and abnormal glucose metabolism. MicroRNAs (miRNA) are highly conserved, small, RNA molecules encoded in the genomes of plants and animals and they regulate the expression of many other genes either by RNA interference (RNAi) or RNA activation (RNAa). miRNAs have been found to regulate multiple genes and seem to be crucial factors in many cellular pathways, including development, cell differentiation, proliferation and apoptosis. Pancreatic islet cell specific miRNAs which regulate insulin secretion, and adipocyte specific miRNAs which regulate adipocyte differentiation, are examples of miRNAs that are predicted to have crucial roles in governing glucose homeostasis. Further understanding of the roles of miRNAs in glucose metabolism may unravel better understanding of pancreatic cell biology and diabetes pathophysiology, allowing for newer therapeutic targets and strategies. In this review, we will be discussing about the role/function of miRNAs in insulin secretion and regulation, lipid metabolism and conditions like hypertension and cardiovascular diseases and the potential use of miRNA in therapy.