Introduction: Diabetes is often accompanied by undiagnosed dyslipidemia. The aim of the study is to investigate the clinical relevance of lipid profiles and lipid ratios as predictive biochemical models for glycemic control in patients with type 2 diabetes mellitus (T2DM). Methods: This is a retrospective study recruiting 140 patients with T2DM during a one-year period, 2018–2019, at the Diabetic Center Sanglah General Hospital and Internal Medicine Polyclinic Puri Raharja General Hospital. Demographic characteristics, glycosylated hemoglobin (HBA1c) , and lipid profile were recorded and analyzed using SPSS version 25.0 for Windows. The sample is then classified into good (HBA1c≤7) and poor (HBA1c>7) glycemic control. Risk analysis model, receiver operator characteristics (ROC) analysis, and correlation test were used to evaluate the association of HBA1c level with lipid profile and lipid ratio parameters. Result: Lipid profile findings such as total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) , triglycerides (TG), and lipid ratio parameter (LDL-C to high-density lipoprotein cholesterol (HDL-C) ratio) were higher in patients in the poor glycemic control group ( p <0.05) and HDL-C was significantly lower in patients with poor glycemic control ( p =0.001). There is a significant positive correlation between LDL, total cholesterol, LDL-C, TG, and TC to HDL-C ratio, triglycerides, and TC/HDL-C ratio with HBA1c level. Meanwhile, a negative correlation was observed on HDL-C with the HBA1c level. Only TC/HDL-C ratio and LDL-C/HDL-C ratio parameters may be used as predictive models (AUC>0.7), with cutoff point, sensitivity, and specificity of 4.68 (77%; 52%) and 3.06 (98%; 56%) respectively. A risk analysis model shows that the LDL-C/HDL-C ratio parameter is the most influential risk factor in the occurrence of poor glycemic control (adjusted OR =38.76; 95% CI: 27.32–56.64; p <0.001). Conclusion: Lipid profiles (LDL-C) and lipid ratios (LDL-C/HDL-C and TC/HDL-C ratio) show potential markers that can be used in predicting glycemic control in patients with T2DM.

Type 2 diabetes mellitus (T2DM) is still a global health problem. Current T2DM treatments are limited to curing the symptoms and have not been able to restore insulin sensitivity in insulin-sensitive tissues that have become resistant. In the past decade, some studies have shown the significant role of a chaperone family, heat shock protein 70 (HSP70), in insulin resistance pathogenesis that leads to T2DM. HSP70 is a cytoprotective molecular chaperone that functions in protein folding and degradation. In general, studies have shown that decreased concentration of HSP70 is able to induce inflammation process through JNK activation, inhibit fatty acid oxidation by mitochondria through mitophagy decrease and mitochondrial biogenesis, as well as activate SREBP-1c, one of the lipogenic gene transcription factors in ER stress. The overall molecular pathways are potentially leading to insulin resistance and T2DM. Increased expression of HSP70 in brain tissues is able to improve insulin sensitivity and glycemic control specifically. HSP70 modulation-targeting strategies (including long-term physical exercise, hot tub therapy (HTT), and administration of alfalfa-derived HSP70 (aHSP70)) in subjects with insulin resistance are proven to have therapeutic and preventive potency that are promising in T2DM management.

No abstract

BACKGROUND: Single-nucleotide polymorphism in the stromal cell-derived factor-1 (SDF-1)/CXCL12 gene had been associated with an increased risk of coronary artery disease (CAD). However, several published studies have shown inconsistent results. AIM: A meta-analysis was assessed to evaluate the association between SDF-1 3’A-gene polymorphism and CAD in the literature. METHODS: A systematic review was conducted in accordance with PRISMA guidelines and adhering to the Cochrane Handbook for Systematic Reviews. The literature search strategy was carried out on April 3, 2019, from PubMed, EBSCO, Google Scholar, and DOAJ during 2013–2018 period using various keywords related to SDF-1, CXCL12, polymorphism, and CAD. Original data from the group, case-control study, English full-text, and DNA polymorphism assessment using polymerase chain reaction were enrolled. Gene polymorphism in A-base nucleotide among patients with CAD and healthy subjects were evaluated. All data were analyzed using Review Manager 5.3 (Cochrane, Denmark) for meta-analysis. RESULTS: Five eligible studies extracted for data analysis (2013–2018) based on the assessment of 2-independent reviewers. Several studies have been excluded due to irrelevant criteria evaluated. A significant result was found between SDF-1 3’A gene polymorphism with the increased risk of CAD in the overall effect evaluation using a fixed-effects model (odds ratio [OR]: 2.02; 95% confidence interval 1.54-2.65; I2: 34%; p<0.001) on the forest plot. CONCLUSION: Our meta-analysis suggests that gene polymorphism in A-base nucleotide of SDF-1/CXCL-12 was associated with the susceptibility of CAD. However, a bigger-scale and well-design of case-control study should be conducted to clarify these conclusions.