Correlates of zinc finger BED domain-containing protein 3 and ghrelin in metabolic syndrome patients with and without prediabetes

Abstract

Abstract Background Ghrelin and zinc finger BED domain-containing protein 3 (ZBED3) are distinctively cross linked with prediabetes (preDM) and metabolic syndrome (MetS). Materials and methods In a cross-sectional design with 29 normoglycemic MetS and 30 newly diagnosed drug naïve preDM/MetS patients vs. 29 lean and normoglycemic controls; ghrelin and ZBED3 were evaluated using colorimetric enzymatic assays. Results While ZBED3 mean circulating levels (ng/mL) in both MetS groups (normoglycemic and preDM) invariably lacked discrepancy vs. controls; Appreciably ghrelin levels (ng/mL) in preDM/MetS (but not normoglycemic MetS) participants were markedly higher vs. controls. Except for fasting plasma glucose (FPG) and glycosylated-hemoglobin (HbA1C); no further intergroup discrepancy could be identified between the MetS arms. Remarkably adiposity indices (body mass index (BMI), body adiposity index (BAI), and lipid accumulation product (LAP), but not conicity index (CI) or visceral adiposity index (VAI)); atherogenicity index of plasma (but not non-high-density lipoprotein-cholesterol (non-HDL-C/HDL-C) ratio, or total cholesterol (TC)/HDL-C ratio) or any of hematological indices (red cell distribution width (RDW-CV%), monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR) and platelet (PLT) to lymphocyte ratio (PLR)) were substantially higher in both MetS (non- and preDM) groups vs. those of controls. Exceptionally low-density lipoprotein -cholesterol (LDL-C)/HDL-C ratio, and waist circumference (WC)/hip circumference (HC) ratio were much more pronounced in MetS-preDM vs. normoglycemic MetS recruits. In the MetS pool (both normoglycemic and preDM, n = 58), neither biomarker could relate to each other, or any of clinical parameters, adiposity or atherogenecity indices. Exceptionally ghrelin correlated significantly and inversely with age. ZBED3 correlated significantly and directly with RDW-CV% in the same pool of MetS recruits (n = 59). Conclusions Both biomarkers can not be ruled out as putative predictive/surrogate prognostic tools for metabolic anomalies prevention and pharmacotherapy.