Desynchronosis markers in risk assessment of metabolic syndrome development

2019 ◽  
Vol 1 (4) ◽  
pp. 21-26 ◽  
Author(s):  
O. V. Bobko ◽  
O. V. Tikhomirova ◽  
N. N. Zybina ◽  
O. A. Klitsenko

The objective of the study is to show significance of desynchronosis laboratory markers in risk assessment of metabolic syndrome (MS) development. Materials and Methods. There were examined 98 men, aged 43-88, diagnosed with dyscirculatory encephalopathy showing one and more risk factors for development of cardiovascular diseases. They were divided into 2 groups according to the international guidelines of 2009: with MS (n = 61) and without MS (n = 37). Parameters of fats, glucose metabolism, inflammatory mediators, fat tissue metabolism markers, melatonin metabolite excretion (6-sulfatoxymelatonin) were defined in blood serum and urine. Results. The article presents data on changes in leptin, adiponectin, PAI-1, testosterone production and 6-sulfatoxymela-tonin excretion in patients with MS. There are calculated threshold values of these markers definitely increasing MS risk and logistic regression equation which allows assessing MS risk for an individual patient. Conclusion. Detected disorders of melatonin synthesis diurnal dynamics in patients with MS and interconnection between melatonin production and adiponectin, leptin, PAI-1, testosterone synthesis allow considering these parameters as desynchronosis markers significant for MS development.

2019 ◽  
Author(s):  
Iwona Zieleń-Zynek ◽  
Joanna Kowalska ◽  
Nowak Justyna ◽  
Barbara Zubelewicz-Szkodzińska

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Salasyuk ◽  
S Nedogoda ◽  
I Barykina ◽  
V Lutova ◽  
E Popova

Abstract Background Metabolic syndrome (MetS) and abdominal obesity are one of the most common CVD risk factors among young and mature patients. However, the currently used CVD risk assessment scales may underestimate the CV risk in people with obesity and MS. Early vascular aging rather than chronological aging can conceptually offer better risk prediction. MetS, as accumulation of classical risk factors, leads to acceleration of early vascular aging. Since an important feature of MetS is its reversibility, an adequate risk assessment and early start of therapy is important in relation to the possibilities of preventing related complications. Purpose To derive a new score for calculation vascular age and predicting EVA in patients with MetS. Methods Prospective open cohort study using routinely collected data from general practice. The derivation cohort consisted of 1000 patients, aged 35–80 years with MetS (IDF,2005 criteria). The validation cohort consisted of 484 patients with MetS and carotid-femoral pulse wave velocity (cfPWV) values exceeding expected for average age values by 2 or more SD (EVA syndrome). Results In univariate analysis, EVA was significantly correlated with the presence of type 2 diabetes and clinical markers of insulin resistance (IR), body mass index (BMI), metabolic syndrome severity score (MetS z-score), uric acid (UA) level, hsCRP, HOMA-IR, total cholesterol (TC), triglycerides (TG), heart rate (HR), central aortic blood pressure (CBP), diastolic blood pressure (DBP). Multiple logistic regression shown, that presence of type 2 diabetes and IR were associated with greater risk of EVA; the odds ratios were 2.75 (95% CI: 2.34, 3.35) and 1.57 (95% CI: 1.16, 2.00), respectively. In addition, the risk of having EVA increased by 76% with an increase in HOMA-IR by 1 unit, by 17% with an increase in hsCRP by 1 mg/l, by 4% with an increase in DBP by 1 mm Hg, and by 1% with each 1 μmol / L increase in the level of UA. The area under the curve for predicting EVA in patients with MetS was 0,949 (95% CI 0,936 to 0,963), 0,630 (95% CI 0,589 to 0,671), 0,697 (95% CI 0,659 to 0,736) and 0,686 (95% CI 0,647 to 0,726), for vascular age, calculated from cfPWV, SCORE scale, QRISK-3 scale and Framingham scale, respectively. Diabetes mellitus and clinical markers of IR (yes/no), HOMA-IR and UA level were used to develop a new VAmets score for EVA prediction providing a total accuracy of 0.830 (95% CI 0,799 to 0,860). Conclusion cfPWV at present the most widely studied index of arterial stiffness, fulfills most of the stringent criteria for a clinically useful biomarker of EVA in patients with MetS. Although, parallel efforts for effective integration simple clinical score into clinical practice have been offered. Our score (VAmets) may accurately identify patients with MetS and EVA on the basis of widely available clinical variables and classic cardiovascular risk factors can prioritize using of vascular age in routine care. ROC-curves for predicting EVA in MetS Funding Acknowledgement Type of funding source: None


2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Jin-Shuen Chen ◽  
Chung-Ze Wu ◽  
Nain-Feng Chu ◽  
Li-Chien Chang ◽  
Dee Pei ◽  
...  

We investigated the role of urokinase plasminogen activator (uPA) and its soluble receptors (suPAR) and plasminogen activator inhibitor-1 (PAI-1) in metabolic syndrome (MetS) components, insulin secretion, and resistance in schoolchildren. We enrolled 387 children, aged 10.3 ± 1.5 years, in Taipei. Anthropometry, fibrinolytic proteins, MetS components, insulin secretion, and resistance were measured. Subjects were divided into normal, overweight, and obese groups. Finally, the relationship between fibrinolytic proteins and metabolic syndrome in boys and girls was analyzed. In boys, PAI-1 was positively associated with body mass index (BMI) percentile, hypertriglyceride, insulin secretion, and resistance. In girls, PAI-1 was positively associated with obesity, hypertriglyceridemia, and insulin secretion. In girls, uPA was positively associated with insulin secretion. suPAR was positively associated with high-sensitivity C-reactive protein in both boys and girls, and with BMI percentile and body fat in girls. The obese boys had higher suPAR and PAI-1 levels than the normal group. The obese girls had higher uPA, suPAR, and PAI-1 than the normal group. Boys and girls with MetS had higher PAI-1. Fibrinolytic proteins, especially PAI-1, are associated with MetS components and insulin secretion in children. Fibrinolytic proteins changes were more likely to occur in girls than in boys.


Molecules ◽  
2022 ◽  
Vol 27 (2) ◽  
pp. 334
Author(s):  
Ji-Eun Kim ◽  
Jin-Sun Kim ◽  
Min-Jee Jo ◽  
Eunjung Cho ◽  
Shin-Young Ahn ◽  
...  

Metabolic syndrome is a cluster of metabolic indicators that increase the risk of diabetes and cardiovascular diseases. Visceral obesity and factors derived from altered adipose tissue, adipokines, play critical roles in the development of metabolic syndrome. Although the adipokines leptin and adiponectin improve insulin sensitivity, others contribute to the development of glucose intolerance, including visfatin, fetuin-A, resistin, and plasminogen activator inhibitor-1 (PAI-1). Leptin and adiponectin increase fatty acid oxidation, prevent foam cell formation, and improve lipid metabolism, while visfatin, fetuin-A, PAI-1, and resistin have pro-atherogenic properties. In this review, we briefly summarize the role of various adipokines in the development of metabolic syndrome, focusing on glucose homeostasis and lipid metabolism.


2021 ◽  
Vol 9 ◽  
Author(s):  
Qiao-Ying Xie ◽  
Ming-Wei Wang ◽  
Zu-Ying Hu ◽  
Cheng-Jian Cao ◽  
Cong Wang ◽  
...  

Aim: Metabolic syndrome (MS) screening is essential for the early detection of the occupational population. This study aimed to screen out biomarkers related to MS and establish a risk assessment and prediction model for the routine physical examination of an occupational population.Methods: The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning was used to screen biomarkers related to MS. Then, the accuracy of the logistic regression model was further verified based on the Lasso regression algorithm. The areas under the receiving operating characteristic curves were used to evaluate the selection accuracy of biomarkers in identifying MS subjects with risk. The screened biomarkers were used to establish a logistic regression model and calculate the odds ratio (OR) of the corresponding biomarkers. A nomogram risk prediction model was established based on the selected biomarkers, and the consistency index (C-index) and calibration curve were derived.Results: A total of 2,844 occupational workers were included, and 10 biomarkers related to MS were screened. The number of non-MS cases was 2,189 and that of MS was 655. The area under the curve (AUC) value for non-Lasso and Lasso logistic regression was 0.652 and 0.907, respectively. The established risk assessment model revealed that the main risk biomarkers were absolute basophil count (OR: 3.38, CI:1.05–6.85), platelet packed volume (OR: 2.63, CI:2.31–3.79), leukocyte count (OR: 2.01, CI:1.79–2.19), red blood cell count (OR: 1.99, CI:1.80–2.71), and alanine aminotransferase level (OR: 1.53, CI:1.12–1.98). Furthermore, favorable results with C-indexes (0.840) and calibration curves closer to ideal curves indicated the accurate predictive ability of this nomogram.Conclusions: The risk assessment model based on the Lasso logistic regression algorithm helped identify MS with high accuracy in physically examining an occupational population.


Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Jawed Fareed ◽  
Vinod Bansal ◽  
Debra Hoppensteadt ◽  
Daneyal Syed ◽  
Syed Ahmad

Introduction: Metabolic syndrome (MS) represents a cluster of cardiovascular risk factors which contribute to myocardial infarction and stroke in end stage renal disease (ESRD) patients. Several metabolic biomarkers have been identified and their circulating levels provide a better understanding of the pathogenesis of MS/ESRD. The purpose of this investigation is to profile biomarkers of MS in ESRD patients. Materials and Methods: Plasma samples from 87 patients with ESRD undergoing maintenance hemodialysis and 50 normals were collected prior to a routine session. These samples were profiled for metabolic biomarkers using protein chip bioarray technology. The protein chip array was comprised of several biomarkers of MS. All results were compiled in terms of group means +/- 1 SD (SEM) and statistically analyzed. Results: In comparison to the normal samples, the ESRD group showed marked increase in circulating levels of all biomarkers. TNFa (47.4 +/- 18.3 vs 4.1 +/- 1.1 ng/mL) and IL-6 (7.8 +/- 9.1 vs 0.8 +/- 0.4 ng/mL) showed the most pronounced increase. C-peptide (14.5 +/- 4.1 vs 2.8 +/- 1.6 ng/mL), leptin (29.7 +/- 29.2 vs 5.2 +/- 7.9 ng/mL), resistan (16.1 +/- 6.0 vs 2.3 +/- 0.7 ng/mL) and ferritin (274 +/- 57 vs 57 +/- 63 ng/mL) showed a 5-fold increase in the ESRD group compared to normal. PAI-1 (5.4 +/- 5.2 vs 2.9 +/- 2.5 ng/mL), IL-1a (1.3 +/- 1.7 vs 0.35 +/- 0.07 ng/mL) and insulin (32.1 +/- 17.3 vs 17.1 +/- 1.7 ng/mL) showed modest increase in the ESRD patients. The increase in all of the MS biomarkers in the ESRD patients were highly significantly elevated, p <0.05. Conclusion: The specific biochip array for MS allows the selective determination of various biomarkers associated with this syndrome in the ESRD patients and normals. Parallel increase in resistan, insulin, C-peptide, and leptin points to the derangement of glucose metabolism in these patients. Increase IL-1a, TNFa, and ferritin suggests the upregulation of an inflammatory process. PAI-1 increase suggests a fibrinolytic deficit. The parallel derangement of the inflammatory process and metabolic syndrome contributes to the cardiovascular and cerebrovascular complications in these patients.


2019 ◽  
Vol 27 ◽  
pp. 59-66 ◽  
Author(s):  
Hayriye Korkmaz ◽  
Emre Canayaz ◽  
Sibel Birtane Akar ◽  
Zehra Aysun Altikardes

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