Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality worldwide. Defects in trophoblast invasion, differentiation of extravillous trophoblasts and spiral artery remodeling are key factors in PE development. Currently there are no predictive biomarkers clinically available for PE. Recent technological advancements empowered transcriptome exploration and led to the discovery of numerous non-coding RNA species of which microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most investigated. They are implicated in the regulation of numerous cellular functions, and as such are being extensively explored as potential biomarkers for various diseases. Altered expression of numerous lncRNAs and miRNAs in placenta has been related to pathophysiological processes that occur in preeclampsia. In the following text we offer summary of the latest knowledge of the molecular mechanism by which lnRNAs and miRNAs (focusing on the chromosome 19 miRNA cluster (C19MC)) contribute to pathophysiology of PE development and their potential utility as biomarkers of PE, with special focus on sample selection and techniques for the quantification of lncRNAs and miRNAs in maternal circulation.

Background: Visceral adiposity index (VAI) and Lipid accumulation product (LAP) are novel visceral adiposity indexes, proposed for the evaluation of cardiometabolic risk in adult population. Considering contradictory results obtained from many studies so far, we aimed to examine the potential benefit of applicability of VAI and LAP, over simple anthropometric indices and traditional lipid parameters in individuals with type 2 diabetes mellitus (DM2).Methods: A total of 180 DM2 (of them 50% females) and 119 controls who volunteered to participate in this cross‐sectional study were enrolled. Anthropometric and biochemical parameters, as well as blood pressure were obtained. VAI and LAP were calculated.Results: Multivariate logistic regression analysis showed that high‐density lipoprotein cholesterol (HDL‐c), (P<.001), waist circumference (WC), (P=.027), age (P=.001), hypolipemic therapy (P=.024), and LAP (P=.005) were independent predictors of DM2 in adjusted models.In Receiver Operating Characteristic curve analysis, used to discriminate subjects with DM2 from those who did not have it, good accuracy of the applied procedures was only achieved with models which were consisted of parameters used in VAI (Body mass index, WC, HDL‐c, triglycerides) and LAP (WC, triglycerides) indexes equations, respectively [Area under the curve (AUC)=0.819 and AUC=0.800, respectively], but not with VAI (AUC=0.781) and LAP (AUC=0.784) indexes themselves.Conclusion: Visceral adiposity index and Lipid accumulation product may not be better than parameters that enter its equation in type 2 diabetes prediction.

Background: Association between endocan and nontraditional anthropometric indices, as distinct cardiovascular disease risk factors, has not been examined in previous studies. Endocan is a novel inflammation biomarker with its higher levels involved in cardiometabolic diseases development. Taking into consideration that obesity is an independent risk factor for many cardiometabolic diseases, we aimed to explore the relationship between endocan levels and novel anthropometric indices i.e., body adiposity index (BAI), cardiometabolic index (CMI), a body shape index, body roundness index, conicity index, lipid accumulation product index and visceral adiposity index and traditional ones i.e., waist circumference, hip circumference, body mass index, waist-to-height ratio and waist-to-hip ratio in adult population. Methods: A total of 177 participants were included. Anthropometric indices and biochemical parametres were measured. Results: Univariate regression analysis demonstrated positive correlations of endocan and almost all anthropometric data. To explore independent associations of endocan and anthropometric parameters, the Model which fulfilled criteria for ordinal regression testing was created. Adjusted odds for BAI given in the Model (OR=1.120, 95% CI 1.036-1.212, P=0.004), demonstrated that a rise in BAI by 1 unit increased the probability of higher endocan concentration by 12%. As well, a rise in CMI for 1 unit, increased the probability for higher endocan levels for 2.6 times (OR=2.599, 95% CI 1.006-6.712, P=0.049). A total of 20.1% of variation in endocan levels could be explained by this Model. Conclusions: Non-traditional obesity indices, BAI and CMI independently correlated with higher serum endocan levels in adult population.