Retinol-Binding Protein-4-A Predictor of Insulin Resistance and the Severity of Coronary Artery Disease in Type 2 Diabetes Patients with Coronary Artery Disease

Diagnostic value of retinol-binding protein 4 in diabetic nephropathy: a systematic review and meta-analysis

Objective

Diabetic nephropathy (DN) is a major microvascular complication of diabetes and the leading cause of end-stage renal disease. Early detection and prevention of DN are important. Retinol-binding protein 4 (RBP4) has been considered as a single diagnostic marker for the detection of renal impairment. However, the results have been inconsistent. The present meta-analysis aimed to determine the diagnostic potential of RBP4 in patients in type 2 diabetes mellitus (T2DM) with DN.

Methods

We searched PubMed, Web of Science, Embase, Wanfang and CNKI databases from inception until January 2024. The meta-analysis was performed by Stata version 15.0, and sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) were pooled. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was utilized to assess the quality of each included study. In addition, heterogeneity and publication bias were evaluated.

Results

Twenty-nine studies were included in the meta-analysis. The pooled sensitivity and specificity were 0.76 [95% confidence interval (CI), 0.71-0.80] and 0.81 (95% CI, 0.76-0.85), respectively. The results showed a pooled PLR of 4.06 (95% CI, 3.16-5.21), NLR of 0.29 (95% CI, 0.24-0.36) and DOR of 13.76 (95% CI, 9.29-20.37). The area under the summarized receiver operating characteristic curve was given a value of 0.85 (95% CI, 0.82-0.88). No obvious publication bias existed in the Deeks' funnel plot asymmetry test.

Conclusion

Our findings suggest that RBP4 has a promising diagnostic value with good sensitivity and specificity for patients with T2DM with DN.

Translational Aspects of Cardiovascular Biology: From Bench to Bedside

Cardiovascular disease is the leading cause of death worldwide, and the search for novel mechanisms and therapeutics is desperately needed [...].

Impaired Organokine Regulation in Non-Diabetic Obese Subjects: Halfway to the Cardiometabolic Danger Zone

Altered organokine expression contributes to increased cardiometabolic risk in obesity. Our aim was to evaluate the associations of serum afamin with glucose homeostasis, atherogenic dyslipidemia, and other adipokines in severe obesity to clarify the early metabolic alterations. 106 non-diabetic obese (NDO) subjects and 62 obese patients with type 2 diabetes matched for age, gender, and body mass index (BMI) were enrolled in this study. We compared their data with 49 healthy, lean controls. Serum afamin and retinol-binding protein 4 (RBP4), as well as plasma plasminogen activator inhibitor-1 (PAI-1), were measured with ELISA, and lipoprotein subfractions were analyzed using Lipoprint gel electrophoresis. Afamin and PAI-1 found to be significantly higher in the NDO and T2M group (p < 0.001 and p < 0.001, respectively) than in the controls. In contrast, RBP4 was unexpectedly lower in the NDO and T2DM group compared to controls (p < 0.001). Afamin showed negative correlations with mean LDL size and RBP4, but positive correlations with anthropometric, glucose/lipid parameters, and PAI-1 in both the overall patients and the in NDO + T2DM groups. BMI, glucose, intermediate HDL, and small HDL were predictors of afamin. Afamin may serve as a biomarker for the severity of cardiometabolic disturbances in obesity. The complexity of organokine patterns in NDO subjects draws attention to the diverse spectrum of obesity-related comorbidities.

Epicardial Adipose Tissue and Diabetic Cardiomyopathy

Diabetes is a long-term chronic disease, and cardiovascular disease is the leading cause of death. Diabetic cardiomyopathy (DCM), one of the cardiovascular complications of diabetes, has many uncertain factors. Epicardial fat, as the heart fat bank, functions as fatty tissue and is the heart's endocrine organ. The existence of diabetes affects the distribution of heart fat and promotes the secretion of adipokine. In different pathological conditions, it can promote the secretion of pro-inflammatory adipokine, reactive oxygen species, oxidative stress, and even autophagy, thus affecting cardiac function. In this paper, we will elaborate on the mechanism of epicardial fat in the pathogenesis of diabetic cardiomyopathy.

The Search for Associations of Serum Proteins with the Presence of Unstable Atherosclerotic Plaque in Coronary Atherosclerosis

To study the associations of blood proteins with the presence of unstable atherosclerotic plaques in the arteries of patients with coronary atherosclerosis using quantitative proteomics. The studies involved two groups of men with coronary atherosclerosis (group 1 (St) had only stable atherosclerotic plaques; group 2 (Ns) had only unstable atherosclerotic plaques, according to histological analysis of tissue samples); the average age of patients was 57.95 ± 7.22. Protein concentrations in serum samples were determined using the PeptiQuant Plus Proteomics Kit. The identification of protein fractions was carried out by monitoring multiple reactions on a Q-TRAP 6500 mass spectrometer combined with a liquid chromatograph. Mass spectrometric identification revealed in serum samples from patients with unstable atherosclerotic plaques a reduced concentration of proteins in the blood: α-1-acid glycoprotein, α-1-antichymotrypsin, α-1-antitrypsin, ceruloplasmin, hemopexin, haptoglobin, apolipoprotein B-100, apolipoprotein L1, afamin and complement component (C3, C7, C9). Moreover, at the same time a high concentration complements factor H and attractin. The differences were considered significant at p < 0.05. It was found that the instability of atherosclerotic plaques is associated with the concentration of proteins: afamin, attractin, components of the complement system, hemopexin and haptoglobin. The data of our study showed the association of some blood proteins with the instability of atherosclerotic plaques in coronary atherosclerosis. Their potential role in the development of this disease and the possibility of using the studied proteins as biomarkers requires further research.

Pharmacokinetic-Pharmacometabolomic Approach in Early-Phase Clinical Trials: A Way Forward for Targeted Therapy in Type 2 Diabetes

Pharmacometabolomics in early phase clinical trials demonstrate the metabolic profiles of a subject responding to a drug treatment in a controlled environment, whereas pharmacokinetics measure the drug plasma concentration in human circulation. Application of the personalized peak plasma concentration from pharmacokinetics in pharmacometabolomic studies provides insights into drugs’ pharmacological effects through dysregulation of metabolic pathways or pharmacodynamic biomarkers. This proof-of-concept study integrates personalized pharmacokinetic and pharmacometabolomic approaches to determine the predictive pharmacodynamic response of human metabolic pathways for type 2 diabetes. In this study, we use metformin as a model drug. Metformin is a first-line glucose-lowering agent; however, the variation of metabolites that potentially affect the efficacy and safety profile remains inconclusive. Seventeen healthy subjects were given a single dose of 1000 mg of metformin under fasting conditions. Fifteen sampling time-points were collected and analyzed using the validated bioanalytical LCMS method for metformin quantification in plasma. The individualized peak-concentration plasma samples determined from the pharmacokinetic parameters calculated using Matlab Simbiology were further analyzed with pre-dose plasma samples using an untargeted metabolomic approach. Pharmacometabolomic data processing and statistical analysis were performed using MetaboAnalyst with a functional meta-analysis peaks-to-pathway approach to identify dysregulated human metabolic pathways. The validated metformin calibration ranged from 80.4 to 2010 ng/mL for accuracy, precision, stability and others. The median and IQR for Cmax was 1248 (849–1391) ng/mL; AUC_0-infinity was 9510 (7314–10,411) ng·h/mL, and Tmax was 2.5 (2.5–3.0) h. The individualized Cmax pharmacokinetics guided the untargeted pharmacometabolomics of metformin, suggesting a series of provisional predictive human metabolic pathways, which include arginine and proline metabolism, branched-chain amino acid (BCAA) metabolism, glutathione metabolism and others that are associated with metformin’s pharmacological effects of increasing insulin sensitivity and lipid metabolism. Integration of pharmacokinetic and pharmacometabolomic approaches in early-phase clinical trials may pave a pathway for developing targeted therapy. This could further reduce variability in a controlled trial environment and aid in identifying surrogates for drug response pathways, increasing the prediction of responders for dose selection in phase II clinical trials.