No abstract

No abstract

Background and objectives Nesfatin-1 as a potent anorexigenic peptide is secreted by pancreatic β cells. Conflicting data are available about its level among diabetic patients. Our study aimed to assess nesfatin-1 levels in newly diagnosed drug-naïve diabetic and pre-diabetic patients and its association with cardio-metabolic risk and insulin resistance (IR). This case-control study included drug-naive patients with DMT2 (group 1, n = 30) and pre-diabetes (group 2, n = 30) in addition to healthy subjects (group 3, n = 28). Anthropometric and routine biochemical assessments were performed. Serum nesfatin-1and plasma insulin levels were assessed by ELISA methods. Homeostatic model for assessment of IR (HOMA-IR) was calculated. Results Serum nesfatin-1 was significantly lower in diabetic and pre-diabetic compared to healthy subjects (3.89 ± 1.1 ng/dl and 7.47 ± 1.22 ng/dl versus 15.39 ± 3.53 respectively, p < 0.001). Also diabetic patients had statistically significant lower nesfatin-1 levels than pre-diabetic patients (p < 0.001) Roc curve analysis identified cut-off values of ≤ 9 ng/dl and ≤ 5.5 ng/dl with an AUC of 0.94 and 0.97, sensitivity of 96.7 and 100%, and specificity of 93.3% and 96.7% for diagnosis of pre-diabetes and diabetes respectively. Using bivariate analysis, nesfatin-1 was negatively correlated with glycemic parameters (fasting and 2 h postprandial blood sugar, HBA1c), IR parameters (fasting insulin and HOMA-IR) and atherogenic lipid profile (triglyceride, cholesterol, and LDL-c); and positively correlated to HDL-c in both diabetic and pre-diabetic but not in healthy. Conclusion Nesfatin-1 is an excellent predictor for pre-diabetes and DMT2. It is associated with favorable glucose and lipid metabolism probably via insulin signaling pathway.

Objective Angiopoietin-like proteins (ANGPTL) 3, 4 and 8 are upcoming cardiovascular biomarkers. Experimental studies showed that thyroid hormones altered their levels. We assessed ANGPTL3, 4 and 8 as predictors of cardiovascular functions among naïve subclinical and naïve overt hypothyroidism (SCH and OH) and altered ANGPTL levels with levothyroxine replacement (LT4) and their association with improved cardiovascular risk factors and cardiovascular function. Design and methods The study was a prospective follow-up study that assessed ANGPTL3, 4 and 8 levels, vascular status (flow-mediated dilation% of brachial artery (FMD%), carotid intima-media thickness (CIMT), aortic stiffness index (ASI)), left ventricle (LV) parameters (ejection fraction (EF), myocardial performance index (MPI), and LV mass), well-known cardiovascular risk factors and homeostatic model for the assessment of insulin resistance, at two time points, that is, among naïve SCH, naïve OH, and healthy subjects groups; and at 6 months after achieving the euthyroid state with LT4 by calculating their increased or decreased delta changes (∆↑ or ∆↓) in longitudinal arm among LT4-hypothyroid groups. Results Significantly elevated levels of ANGPTL3, 4 and 8 among hypothyroid groups than the healthy subjects were reduced with LT4. Multivariate analysis revealed ANGPTLs as independent predictors of cardiovascular functions and the contributors for ANGPTL level included ANGPTL3 and 4 for impaired FMD%, and ANGPTL8 for LV mass among naïve SCH; ANGPTL3 for EF% and ANGPTL8 for CIMT in naïve OH; ∆↓ANGPTL3 for ∆↓ASI meanwhile ∆↑freeT4 for ∆↓ANGPTL3, ∆↓fasting glucose, ∆↓triglyceride, and ∆↓thyroid peroxidase antibody for ∆↓ANGPTL4 among LT4-SCH. ∆↓ANGPTL4 for ∆↓MPI and ∆↓LV mass, meanwhile ∆↓TSH and ∆↓triglyceride for ∆↓ANGPTL3, ∆↑free T3 and ∆↓HOMA-IR for ∆↓ANGPTL4, and systolic blood pressure and waist circumference for ∆↓ANGPTL8 among LT4-OH. Conclusion Elevated ANGPTL3, 4 and 8 levels are differentially independent predictors of endothelial and cardiac function and are reduced with LT4 in SCH and OH.

Background and purpose Hepcidin is the central regulatory molecule of systemic iron homeostasis. Serum ferritin, insulin resistance (IR) and metabolic syndrome (MetS), female sex hormones, and abdominal fat distribution are related to each other and all are linked to menopausal state. Our study was the first to assess the impact of these parameters on hepcidin level among premenopausal women (group I) during the early follicular phase (group I-F) and mid-luteal-phase (group I-L) of the same reproductive cycle and among postmenopausal women (group II). Serum iron parameters, estrogen, progesterone and hepcidin, and plasma insulin were assessed. Abdominal subcutaneous fat (SCF) and peritoneal visceral fat (PVF) thickness were measured by unenhanced- CT. Group I and group II were divided into MetS and non-MetS subgroups. Results The entire group II and MetS-stratified subgroups had significant higher hepcidin level than corresponding group I-F and group I-L. Group I-L had significant higher hepcidin than group I-F. Among group I-F, group I-L, and group II, MetS subgroups had higher hepcidin but not hepcidin/ ferritin ratio (H/F) than corresponding non-MetS; and hepcidin had positive correlations with ferritin, insulin, IR, and SCF. In group I-F and group II, hepcidin had positive correlations with estrogen and progesterone; hepcidin levels increase significantly and linearly with increasing number of MetS features; and cut off values of hepcidin for prediction of MetS were 5.8 ≥ and ≥ 10.3 ng/ml respectively. Main contributors to hepcidin were iron and ferritin in all groups, SCF and progesterone in group I-F, and insulin, progesterone, and MetS in group II. H/F ratio was higher in group II. Conclusion Postmenopausal state (postMS), MetS, and luteal phase are independently associated with high hepcidin level. Serum iron parameters (iron and ferritin) as main regulators of hepcidin are preserved regardless of menopausal state. Its regulation differs based on menopausal state: IR, MetS, and progesterone in postMS meanwhile abdominal SCF and progesterone in premenopausal states. Despite positive associations of estrogen and progesterone with hepcidin, they do not explain its higher level in postMS. Hepcidin levels linearly increase with number of Mets feature and it had high sensitivity for diagnosis of MetS.