Biomarkers Of MetS Research Articles

Intermittent energy restriction vs. continuous energy restriction on cardiometabolic risk factors in patients with metabolic syndrome: a meta-analysis and systematic review.

This is a systematic review and meta-analysis to compare the efficacy of intermittent energy restriction (IER) vs. continuous energy restriction (CER) on weight loss, body composition, blood pressure, and other cardiometabolic risk factors in patients with metabolic syndrome (MetS) risk factors. We searched and screened PubMed, Embase, Cochrane Library, and Web of Science from inception to May 8, 2022 for randomized controlled trials. Two review authors independently selected studies, extracted data, assessed quality and risk of bias and cross-checked extracts to resolve discrepancies when required. We expressed effect size as mean difference (MD) and 95% confidence interval (CI). The major outcome was the improvement of MetS risk factors, including changes in waist circumference (WC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), blood pressure (BP), and fasting plasma glucose (FPG) levels. The secondary outcomes were body weight (BW), body mass index (BMI), body fat (BF), fat free mass (FFM), hip circumference (HC), fasting insulin (FINs), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-c). The meta-analysis included 16 articles (20 trials) with a total of 1,511 participants. All studies had a low risk of bias for random sequence generation. The IER and CER intervention equally improved MetS risk factors WC (MD = -0.47, 95% CI [-1.19, 0.25]), TG (MD = -0.02 mmol/L, 95% CI [-0.11, 0.07]), FPG (MD = -0.02 mmol/L, 95% CI [-0.10, 0.05]) and BP (systolic blood pressure: MD = 0.93 mmHg, 95% CI [-2.74, 4.61]; diastolic blood pressure: MD =1.15 mmHg, 95% CI [-0.24, 2.55]), but HDL-c (MD = 0.03 mmol/L, 95% CI [0.01, 0.05]) was significant improved in IER when compared with CER. For second outcomes, BW (MD = -0.8 kg, 95% CI [-1.26, -0.33]), BF (MD = -0.75 kg, 95% CI [-1.73, -0.13]) and FFM (MD = -0.49 kg, 95% CI [-0.92, -0.05]) were also significant improved in IER, and not for other outcomes. Both IER and CER could improve MetS biomarkers, but IER was more effective than CER in the improvement of HDL-c only. For secondary outcomes, IER was also more effective for BW, BF and FFM, but there were no differences in effects for other outcomes.

Biomarkers of Osteoarthritis—A Narrative Review on Causal Links with Metabolic Syndrome

Development of OA (OA) is multifactorial and is strongly associated with risk factors such as aging, trauma, metabolic disorders, and obesity. Metabolic Syndrome (MetS)-associated OA, collectively coined MetS-OA, is an increasingly recognized entity in which metabolic disorders and low-grade inflammation play a key mechanistic role in the disruption of joint homeostasis and cartilage degradation. Although there have been enormous efforts to discover biomarkers of MetS and OA, studies investigating a pathophysiological link between MetS and OA are relatively limited, and no serum blood marker has proved diagnostic so far. OA biomarkers that are necessary to discriminate and diagnose early disease remain to be elicited, explained in part by limited prospective studies, and therefore limited tools available to utilize in any prognostic capacity. Biomarker validation projects have been established by the Biomarker Consortium to determine biochemical markers demonstrating predictive validity for knee OA. Given that the metabolic constituents of MetS are treatable to varying extents, it stands to reason that treating these, and monitoring such treatment, may help to mitigate deleterious links with OA development. This narrative review will describe the current state of biomarker identification and utility in OA associated with MetS. We discuss the pathophysiological mechanisms of disease according to constituent pathologies of MetS and how identification of biomarkers may guide future investigation of novel targets.

Circulating Nitric Oxide and Metabolic Syndrome in Arab Children and Adolescents: A Case–Control Study

Metabolic syndrome (MetS) represents a cluster of known cardiometabolic risk factors, which elevates the risk of type 2 diabetes mellitus (T2DM), atherosclerotic cardiovascular disease (CVD) and chronic kidney disease (CKD) in adults and, only recently, even in children and adolescents. Circulating nitric oxide (NOx) has been observed to influence MetS risk factors in adults, but this has been scarcely investigated in children. The aim of the present study was to determine whether circulating NOx levels correlate with known components of MetS in Arab children and adolescents. Anthropometrics, serum NOx, lipid profile and fasting glucose levels were measured in 740 Saudi Arabs aged 10-17 years (68.8% girls). The presence of MetS was screened using the criteria of de Ferranti et al. Results: Overall, serum NOx levels were significantly higher in MetS participants compared to non-MetS (25.7 µmol/L (10.1-46.7) versus 11.9 µmol/L (5.5-22.9), p < 0.001) even after adjustments for age, BMI and sex. With the exception of elevated blood pressure, higher circulating NOx significantly increased the odds for MetS and its components. Lastly, receiver operating characteristics (ROC) showed that NOx, as a diagnostic marker for MetS, had good sensitivity and was higher in boys than girls (all MetS participants: area under the curve (AUC) = 0.68, p < 0.001), (girls with MetS: AUC = 0.62, p = 0.002), (boys with MetS: AUC = 0.83, p < 0.001)). MetS and most of its components were significantly associated with circulating NOx levels in Arab adolescents and may be a promising diagnostic biomarker for MetS.

Machine learning of plasma metabolome identifies biomarker panels for metabolic syndrome: findings from the China Suboptimal Health Cohort

BackgroundMetabolic syndrome (MetS) has been proposed as a clinically identifiable high-risk state for the prediction and prevention of cardiovascular diseases and type 2 diabetes mellitus. As a promising “omics” technology, metabolomics provides an innovative strategy to gain a deeper understanding of the pathophysiology of MetS. The study aimed to systematically investigate the metabolic alterations in MetS and identify biomarker panels for the identification of MetS using machine learning methods.MethodsNuclear magnetic resonance-based untargeted metabolomics analysis was performed on 1011 plasma samples (205 MetS patients and 806 healthy controls). Univariate and multivariate analyses were applied to identify metabolic biomarkers for MetS. Metabolic pathway enrichment analysis was performed to reveal the disturbed metabolic pathways related to MetS. Four machine learning algorithms, including support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), and logistic regression were used to build diagnostic models for MetS.ResultsThirteen significantly differential metabolites were identified and pathway enrichment revealed that arginine, proline, and glutathione metabolism are disturbed metabolic pathways related to MetS. The protein-metabolite-disease interaction network identified 38 proteins and 23 diseases are associated with 10 MetS-related metabolites. The areas under the receiver operating characteristic curve of the SVM, RF, KNN, and logistic regression models based on metabolic biomarkers were 0.887, 0.993, 0.914, and 0.755, respectively.ConclusionsThe plasma metabolome provides a promising resource of biomarkers for the predictive diagnosis and targeted prevention of MetS. Alterations in amino acid metabolism play significant roles in the pathophysiology of MetS. The biomarker panels and metabolic pathways could be used as preventive targets in dealing with cardiometabolic diseases related to MetS.

Levels of Acylcarnitines and Branched-Chain Amino Acids in Antipsychotic-Treated Patients with Paranoid Schizophrenia with Metabolic Syndrome.

Several studies have shown that patients with schizophrenia are at high risk for metabolic syndrome (MetS) and bioenergetic dysfunction. Because acylcarnitines are involved in bioenergetic pathways and reflect the functioning of mitochondria, we hypothesized that these compounds are biomarkers of MetS in schizophrenia. The aim of this work was to quantify acylcarnitines and branched-chain amino acids in patients with schizophrenia comorbid with MetS. The study included 112 patients with paranoid schizophrenia treated with antipsychotics. Among them, 39 subjects met criteria of MetS. Concentrations of 30 acylcarnitines and three amino acids in dry serum spots were measured by liquid chromatography coupled with tandem mass spectrometry. MetS patients were found to have higher levels of valeryl carnitine (C5), leucine/isoleucine, and alanine as compared with patients without MetS, indicating possible participation of these compounds in the pathogenesis of metabolic disorders in schizophrenia. In patients with paranoid schizophrenia with or without MetS, lower levels of carnitines C10, C10:1, C12, and C18 were recorded as compared with the healthy individuals (n = 70), implying deterioration of energy metabolism. We believe that this finding can be explained by effects of antipsychotic medication on an enzyme called carnitine-palmitoyl transferase I.

Serum Pigment Epithelium-Derived Factor Levels are Associated with Estradiol and Decrease After Adjusting for Alanine Aminotransferase in Chinese Women Based on Multiple Linear Regression Analysis.

PurposeTo assess changes in pigment epithelium-derived factor (PEDF) levels in patients with metabolic syndrome (MetS) and to investigate sexual dimorphism in serum PEDF levels and their relationships with estradiol.MethodsA total of 318 individuals (145 men, 173 women) who underwent health examinations in our department were selected. Serum PEDF, estradiol and other metabolic parameters were determined. Homeostasis model assessment of insulin resistance (HOMA- IR) and homeostasis model assessment of β-cell function (HOMA-β) were calculated to evaluate insulin resistance and β-cell function, respectively. Multiple linear regression analysis was used to analyse the factors influencing serum PEDF.ResultsSerum PEDF levels were significantly higher in subjects with MetS in both men and women (12.09±2.75 vs 8.97±3.19 μg/mL in men and 11.31±2.79 vs 8.40±2.32 μg/mL in women, MetS vs non-MetS, P<0.001). Correlation analysis showed that serum PEDF levels were significantly correlated with body mass index (BMI), waist circumference, waist-to-hip ratio, diastolic blood pressure (DBP), fasting and 2-h postprandial glucose, fasting and 2-h postprandial insulin, HOMA-β, HOMA-IR, hemoglobin A1c (HbA1c), alanine aminotransferase (ALT), aspartate aminotransferase (AST), uric acid (UA), triacylglycerol (TG) and high-density lipoprotein cholesterol (HDL-C). Elevated ALT, HOMA-IR and TG were significant predictors of increased PEDF concentrations. In women, estradiol was inversely correlated with PEDF levels (r=−0.25, P=0.011), and the association was no longer significant after adjustment for ALT.ConclusionPEDF could be used as a biomarker of MetS in both men and women. This study reported for the first time that circulating PEDF displays sexual dimorphism, which could be related to estrogen. The association between estrogen and circulating PEDF levels was attenuated after adjusting for ALT.

GPHB5 Is a Biomarker in Women With Metabolic Syndrome: Results From Cross-Sectional and Intervention Studies.

BackgroundAnimal studies have found that GPHB5 has a similar effect on system metabolism as TSH. However, the relationship between GPHB5 and metabolic diseases remains unknown. This study investigates the relationship between GPHB5 and MetS in young women.MethodsBioinformatics analysis was undertaken to explore the relationship between GPHB5 and metabolic-related genes and signaling pathways. EHC and OGTT were performed on all individuals. Lipid-infusion, physical activity, and cold-exposure tests were performed on healthy individuals. Serum GPHB5 concentrations were measured by an ELISA kit.ResultsPPI network showed that 11 genes interacted with GPHB5, in which POMC and KISS1R were involved in glucose and lipid metabolism. GO analysis showed 56 pathways for BP and 16 pathways for MF, in which OPRM1 and MCR families were related to energy metabolism. KEGG analysis found that GPHB5 is associated with lipolysis and neuroactive ligand-receptor interaction pathways. The levels of circulating GPHB5 were significantly increased, while serum adiponectin levels were lower in MetS women compared with healthy women. Obese/overweight individuals had lower adiponectin levels and higher GPHB5 levels. Circulating GPHB5 levels were positively correlated with BMI, WHR, blood pressure, FBG, 2 h-BG, HbA1c, FIns, 2h-Ins, LDL-C, FFA, HOMA-IR, and AUCg, etc. but negatively correlated with HDL-C, adiponectin, and M-values. Serum GPHB5 levels did not change significantly during the OGTT, EHC, and lipid infusion. Physical activity and cold-exposure tests did not lead to changes in GPHB5 levels. GLP-1RA treatment resulted in a significant decrease in serum GPHB5 levels.ConclusionsGPHB5 may be a biomarker for MetS.

Overview of Nutraceuticals and Cardiometabolic Diseases following Socio-Economic Analysis

The importance of functional food and nutraceutical products to deal with cardiometabolic diseases (CMDs) and metabolic syndrome (MetS) has gained attention in the past few years. The aim of this narrative review is to highlight the potential and effectiveness of nutraceutical in the improvement of CMDs and MetS biomarkers, alongside their burden of disease and economic health expenditure. A science database search was conducted between May and June 2021. A total of 35 studies were included in this paper. We included male and female subjects, children, and adults, in good health or with cardiovascular or metabolic disease. CMDs and MetS have gradually become worldwide health problems, becoming two of the major causes of morbidity and mortality in western countries. The results indicate a positive link between daily consumption of nutraceutical products and an improvement in cardiometabolic and anthropometric biomarkers. In this paper we included a wide range of nutraceutical products. Most of them showed promising data, indicating that nutraceuticals could provide a new therapeutic treatment to reduce prevalence and pharmaceutical expenditures attributed to CMDs and MetS. Unfortunately, there is a huge vacuum of data on nutraceutical usage, savings, and burden reduction. Therefore, further clinical and pharmaco-economic research in the field is highly required.

Associations of zinc-\u03b1-2-glycoprotein with metabolic syndrome and its components among adult Arabs

Epidemiological studies suggest that the Zinc-α-2-glycoprotein (ZAG) plays significant physiological roles. In this study we investigate whether ZAG could be considered as a clinical biomarker in the diagnosis and prognosis of metabolic syndrome (MetS) in Saudi population. As such insights urgently required for management of MetS. Thus, we have determined serum levels of ZAG in patients with MetS and normal individuals. We have also assessed the correlation between ZAG and different components of MetS. In this case–control study, clinical information of 200 Saudi male and female subjects (age range 30–65) with MetS (n = 100) and healthy controls (n = 100) were extracted from the database of the Chair of Biomarkers of Chronic Disease (CBCD) in King Saud University (KSU), Riyadh, Saudi Arabia. MetS was screened according to NCEP ATP III criteria (National Cholesterol Education Program Adult Treatment Panel III). Fasting glucose and lipid profile levels were measured using Konelab. Serum TNF-α, IL- 6, CRP and ZAG levels were measured using commercially available assays. There was an age-dependent significant increase in ZAG level among MetS subjects than controls (43.8 ± 19.5 vs 48.1 ± 14.8; P = 0.04). A significant inverse correlation between ZAG and serum HDL-cholesterol (r = − 0.20, P < 0.05) was observed. Whereas, triglycerides (r = 0.25, P < 0.01), waist circumference (WHR) (r = 0.17, P < 0.05) and CRP (r = 0.24, P < 0.01) were all significantly and positively associated with ZAG. Circulating ZAG is associated with MetS in an age-dependent manner. Serum ZAG is a potential biomarker for MetS.

Pathogenesis and Biomarkers of Metabolic Syndrome

Metabolic syndrome (MetS) is a pathologic multifaceted condition characterized by elevated triacylglycerides, decreased high density lipoproteins, insulin resistance, increased blood pressure and fasting glucose. Together these abnormalities increase a risk of cardiovascular diseases and type 2 diabetes mellitus. Overnutrition and sedentary lifestyle followed by overweight and obesity are the main contributing factors to MetS development. The pathogenesis of MetS is very complex and not fully elucidated. The studies support the concept of oxidant/antioxidant imbalance and low-grade inflammation playing main roles in its manifestations. Diagnosis with MetS and the development of MetS complications can be detected and monitored via specific serum biomarkers. In this paper, we describe classical metabolic, hormonal and pro-/anti-inflammatory markers which are the most frequently used for MetS diagnostic and research. They include serum lipid profile (triacylglycerides, total cholesterol, low and high density lipoproteins), blood pressure, fasting glucose and HOMA-IR index, levels of anti-inflammatory adiponectin, pro-inflammatory C-reactive protein and cytokines (TNF-α, IL-1β, IL-6, etc.). We also analyze advantages of additional criteria such as levels of oxidative damages, appetite hormones (leptin, ghrelin), apolipoproteins and oxylipins, the composition of gut microbiota and levels of microbiome-derived metabolites, the ratios between different parameters as helpful biomarkers of MetS and concomitant cardiovascular diseases.

New markers in metabolic syndrome.

Metabolic syndrome (MetS) is increasing globally and is clinically significant due to its association with cardiovascular disease, type 2 diabetes and cancer. Although the pathogenesis of MetS has not been clearly elucidated, insulin resistance and chronic low-grade inflammation derived from central obesity are the most widely accepted as underlying pathophysiology. Accordingly, insulin resistance indices, adipokines and various inflammatory markers have been suggested as reliable biomarkers for MetS. Others, such as uric acid, alkaline phosphatase, γ-glutamyl transferase, are also known to positively correlate with MetS and could be diagnostically useful. In this review, we provide a comprehensive overview of MetS biomarkers and the development of a systematic approach to laboratory analysis.

The Association between Circadian Clock Gene Polymorphisms and Metabolic Syndrome: A Systematic Review and Meta-Analysis.

Simple SummaryMetabolic syndrome is a cluster of cardio-metabolic risk factors and comorbidities, including central obesity, hypertension, hyperglycemia, and dyslipidemia. In addition, different studies have shown that the disturbances in circadian rhythm are connected with components of metabolic syndrome. Circadian rhythm is the central regulator of every aspect of human health and metabolism, and metabolic homeostasis is essential in regulating energy metabolism, especially in adipose tissue. Therefore, we aimed to evaluate the association of genetic variations of circadian rhythm genes with metabolic syndrome and its components by a systematic review and meta-analysis. Our findings suggest that some variants of the circadian rhythm gene might be genetic biomarkers applied to predict metabolic syndrome susceptibility.Metabolic syndrome (MetS) is a combination of cardiovascular risk factors associated with type 2 diabetes, obesity, and cardiovascular diseases. The circadian clock gene polymorphisms are very likely to participate in metabolic syndrome genesis and development. However, research findings of the association between circadian rhythm gene polymorphisms and MetS and its comorbidities are not consistent. In this study, a review of the association of circadian clock gene polymorphisms with overall MetS risk was performed. In addition, a meta-analysis was performed to clarify the association between circadian clock gene polymorphisms and MetS susceptibility based on available data. The PubMed and Scopus databases were searched for studies reporting the association between circadian rhythm gene polymorphisms (ARNTL, BMAL1, CLOCK, CRY, PER, NPAS2, REV-ERBα, REV-ERBβ, and RORα) and MetS, and its comorbidities diabetes, obesity, and hypertension. Thirteen independent studies were analyzed with 17,381 subjects in total. The results revealed that the BMAL1 rs7950226 polymorphism was associated with an increased risk of MetS in the overall population. In contrast, the CLOCK rs1801260 and rs6850524 polymorphisms were not associated with MetS. This study suggests that some circadian rhythm gene polymorphisms might be associated with MetS in different populations and potentially used as predictive biomarkers for MetS.

Neonatal Birthweight, Infant Feeding, and Childhood Metabolic Markers.

Antenatal and early neonatal nutritional environment may influence later metabolic health. Infants of mothers with gestational diabetes mellitus (GDM) have higher risk for childhood obesity and metabolic syndrome (MetS). Leptin and adiponectin are known biomarkers for MetS and may guide interventions to reduce later obesity. We sought to examine the relationship between birthweight, early infancy feeding practices, and biomarkers for MetS in offspring of women with mild GDM. Secondary analysis of a prospective observational follow-up study on the offspring of women who participated in a multicenter randomized treatment trial on mild GDM. Children were evaluated by research coordinators and biospecimens collected at the age of 5 to 10. Plasma concentrations of leptin and adiponectin were compared between large for gestational age (LGA) and average birthweight (AGA) infants, and according to whether solid foods were introduced early (<6 months of age) or at the recommended age (≥6 months of age). Multivariable analysis adjusted for fetal sex, race/ethnicity, and maternal body mass index. Leptin and adiponectin were measured in 336 plasma samples. In bivariate analysis, compared with AGA children, LGA children had lower leptin (5.0 ng/mL [3.6-6.0] vs. 5.8 ng/mL [4.5 = 6.6], p = 0.01) and similar adiponectin (6.3 µg/mL [5.1-7.9] vs. 6.4 µg/mL [5.3-8.6], p = 0.49) concentrations. Maternal/child characteristics were similar between the early/delayed solid feeding groups. Leptin and adiponectin concentrations were similar in the early fed and delayed feeding groups (5.8 ng/mL [4.6-6.7] vs. 5.6 ng/mL [4.2-6.6], p = 0.50 and 6.4 µg/mL [5.4-8.1] vs. 6.4 µg/mL [5.1-8.8], p = 0.85, respectively). After controlling for covariates, children who were LGA and AGA at birth had similar leptin concentrations. Birthweight and early infancy feeding practice are not associated with alterations in leptin and adiponectin in children of women with mild GDM. · Adipocytokines are markers of metabolic status.. · Children of women with mild GDM may be at risk for MetS.. · Biomarkers similar in LGA and AGA groups.. · Biomarkers similar in early and delayed solid-fed groups.. · Nonhuman milk does not modify effect of feeding practice..

Association of dyslipidemia, diabetes and metabolic syndrome with serum ferritin levels: a middle eastern population-based cross-sectional study

Elevated serum ferritin (SFer) levels are implicated in many energy metabolism abnormalities. The association between SFer levels and metabolic disorders has not been studied in Middle Eastern populations. We aimed at exploring the association between SFer levels and serum lipids, diabetes determinants, and metabolic syndrome in a sample of Qatari adults. This study used biochemical parameters obtained from 1928 participants from the Qatar Biobank cohort. We utilized adjusted multivariable logistic regression analysis to estimate the odds ratios (ORs) for dyslipidemia, type 2 diabetes, the homeostasis model assessment of insulin resistance (HOMA-IR), and metabolic syndrome (MetS) according to sex-specific SFer quartiles (Q1 to Q4). Results revealed that the ORs for dyslipidemia increased progressively and significantly across the SFer quartiles, up to two folds in Q4 for women (OR 2.47 (1.68–3.62)) and men (OR 2.24 (1.41–3.55)) versus Q1 (OR:1). Exclusively in women, the ORs for IR (HOMA-IR > 3.58) increased significantly in Q4 (OR 1.79 (1.19–2.70)) versus OR 1 in Q1 as did the ORs for diabetes (OR: 2.03 (1.15–3.57) in Q4 versus OR 1 in Q1). We observed the same result when we pooled the participants with prediabetes and diabetes in one group. The OR for MetS also increased significantly across the Sfer Quartiles from OR: 1 in Q1 to 1.92 (1.06–3.02) in Q4 for women and to 2.07 (1.08–3.98) in Q4 in men. Our results suggest the elevated Sfer levels as a potential risk biomarker for dyslipidemia and MetS in adult Qatari men and women, and diabetes and IR in women only.

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants.

BackgroundMetabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.MethodsPotential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.FindingsNine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.InterpretationWe identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.FundingThis work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

Status of Adiponectin and hs-C-reactive Protein in Metabolic Syndrome in a Tertiary Care Teaching Hospital

Background: The metabolic syndrome (MetS), a cluster of abdominal obesity, dyslipidemia, hypertension and hyperglycemia, is a common basis for atherosclerotic vascular diseases in industrial countries exposed to overnutrition. Adiponectin is an adipose-derived plasma protein with anti-atherogenic and insulin-sensitizing activities. Materials and Methods: There were 46 subjects with MetS and 46 control groups. Mean serum level of adiponectin and high sensitive C-reactive protein (CRP) were lower and higher in subjects with MetS than control groups, respectively. Results: The serum adiponectin in the cases 2.43 ± 0.83 μg/ml was lower compared to the controls 7.54 ± 0.94 μg/ml (P value was 0.001), the difference was statistically significant. The serum hs-CRP in the cases 3.8 ± 1.26 μg/ml was lower compared to the controls 1.4 ± 0.74 μg/ml (P value was 0.001), the difference was statistically significant. Conclusion: The high hs-CRP and low adiponectin have a positive and negative relationship with certain MetS components. High sensitive C-reactive protein (hs-CRP) was found to have a stronger link to the MetS than adiponectin. It appears that high-sensitivity CRP (hs-CRP) may be a substantial risk factor for MetS. In contrast to prior findings, this study suggests that hs-CRP is more relevant than adiponectin as a diagnostic biomarker for MetS. These variations could be related to changes in lifestyle and food habits among Sambalpur residents with MetS.

The Relationship between Metabolic Syndrome and Plasma Metals Modified by EGFR and TNF-α Gene Polymorphisms

With the escalating global prevalence of metabolic syndrome (MetS), it is crucial to detect the high-risk population early and to prevent chronic diseases. Exposure to various metals has been indicated to promote MetS, but the findings were controversial, and the effect of genetic modification was not considered. Epidermal growth factor receptor (EGFR) was proposed to be involved in the pathway of metabolic disorders, and tumor necrotic factor-α (TNF-α) was regarded as an early inflammatory biomarker for MetS. This research aimed to analyze the impact of EGFR and TNF-α gene polymorphisms on the prevalence of MetS under environmental or occupational exposure to metals. We gathered data from 376 metal industrial workers and 639 non-metal workers, including physical parameters, biochemical data, and plasma concentrations of six metals. According to the genomic database of Taiwan Biobank, 23 single nucleotide polymorphisms (SNPs) on EGFR gene and 6 SNPs on TNF-α gene were incorporated in our research. We applied multivariable logistic regression to analyze the probability of MetS with various SNPs and metals. Our study revealed some susceptible and protective EGFR and TNF-α genotypes under excessive exposure to cobalt, zinc, selenium, and lead. Thus, we remind the high-risk population of taking measures to prevent MetS.

Serum adiponectin, body adiposity and metabolic parameters in obese Egyptian children with Down syndrome.

Children with Down syndrome (DS) have a higher risk for obesity. Adiponectin plays a crucial role in obesity-related cardiometabolic comorbidities. The study aimed to explore whether body adiposity indicators, the frequency of metabolic syndrome (MetS) and its components, serum adiponectin and insulin resistance indices as well as the validity of serum adiponectin as a biomarker for MetS are different in prepubertal obese-DS children compared to matched obese-controls. Cross-sectional study included 150 prepubertal children classfied into three groups; obese-DS (n=50), obese-control (n=50) and normal-weight-control (n=50). Participants were evaluated for waist-circumference (WC), body adiposity, serum triglycerides, HDL-C, adiponectin and Homeostasis-Model-Assessment of Insulin-Resistance (HOMA-IR). MetS was defined using modified Adult Treatment Panel III-criteria. Obese-DS had significantly higher WC, %body fat, total-fat mass, trunk-fat mass, trunk/appendicular-fat mass ratio, triglycerides, insulin and HOMA-IR and significantly lower HDL-C values compared to obese-control. Higher prevalence of MetS and its components were observed in obese-DS that was evident at younger age. Adiponectin was significantly lower in obese-DS compared with obese-control and in obese-DS children with MetS compared to obesecontrol with MetS. The decrease in adiponectin with increasing grades of obesity was pronounced in obese-DS. Adiponectin exhibited strong correlations with body adiposity, several MetS components and HOMA-IR in obese-DS. Adiponectin performed better as a biomarker for MetS among obese-DS (AUC=0.808) than obese-control (AUC=0.674). Prepubertal obese-DS displayed excess body adiposity with pronounced central fat distribution, atherogenic lipid profile and higher insulin resistance compared to matched obese-control. Adiponectin performed better as potential biomarker of MetS in obese-DS than obese-control.

Factor Analysis of Metabolic Syndrome and Its Relationship with the Risk of Cardiovascular Disease in Ethnic Populations in Rural Xinjiang, China.

BackgroundThis cohort study created a risk equation of CVD for the Uyghur and Kazakh ethnic groups with metabolic syndrome (MetS) in Xinjiang and its associated factors, evaluated the model’s feasibility, and provided theoretical support for the prevention and early diagnosis of CVD.MethodsA total of 5655 participants from Xinyuan and Jiashi counties in Xinjiang from 2010 to 2012 were selected, including 3770 and 1885 training and validation samples, respectively. A factor analysis was performed on 975 patients with MetS in the training sample, whereas potential factors related to CVD were extracted from 21 MetS biomarkers. Cox regression was used to create and verify a CVD-risk prediction model based on training samples. The receiver operating characteristic curve was drawn to evaluate the model’s prediction efficiency.ResultsThe cumulative incidence of CVD was 9.20% (training sample, 9.12%; validation sample, 9.36%). Nine potential factors were extracted from the training sample population with MetS to predict the CVD risk: lipid (hazard ratio [HR], 1.205), obesity (HR, 1.047), liver function (HR, 1.042), myocardial enzyme (HR, 1.008), protein (HR, 1.024), blood pressure (HR, 1.027), liver enzyme (HR, 1.012), renal metabolic (HR, 1.015), and blood glucose (HR, 1.010). The area under the curve of the training and validation samples was 0.841 (95% confidence interval [CI], 0.821–0.861) and 0.889 (95% CI, 0.870–0.909), respectively.ConclusionThe CVD prediction model created with nine potential factors in patients with MetS in Kazakh and Uyghur has a good predictive power.

Discrimination Associated with Metabolic Syndrome among African Americans from the Jackson Heart Study

We enthusiastically read the paper entitled “Experiences of Discrimination Are Associated with Worse Metabolic Syndrome Severity Among African Americans in the Jackson Heart Study” by Cardel et al. [1]. Despite the detected association between experiences of discrimination and metabolic syndrome (MetS) severity (using the Z-score described), some limitations in the methodology should be further discussed. First, the validity of the MetS Z-score used remains debatable. The underlying assumption in the calculation of this Z-score is based on simultaneous use of the known five biomarkers namely blood pressure, fasting blood glucose, abdominal fat/circumference, fasting blood triglycerides, and fasting blood high-density cholesterol as a cluster of circumstances that bundle together to define MetS by Adult Treatment Panel III (ATP III) criteria [2]. Even though previous research may be in support of this approach [3-6], the assumption has major limitations. Each biomarker has a defined threshold, with the value above that threshold showing a certain amount of future cardiovascular and metabolic disease risk. However, the value below that threshold has no distinct risk prediction capability. In other words, adding these biomarker scores together has more limited prediction ability because any increase risk detected by these individual biomarkers only increases the opportunity of creating a new parameter with relatively lower prediction ability. As an exemplification; in this study, there are higher baseline MetS scores among the older / aging participants, especially in 46 to 64 years group. Nevertheless this phenomenon is expected given that 1) interaction with time will enhance the correlation; and 2) the MetS older individuals criteria is determined by extreme measurements of at least three MetS biomarkers [2]. Second, although the prevalence of MetS diagnosed by ATP III is ascertained, the authors did not provide any data to compare proposed MetS Z-score with traditional ATP III dichotomous criteria to see whether the effect of discrimination on MetS is different. If there is no significantly better prediction of discrimination for MetS between the two methods, why MetS Z-score should be calculated and used? Third, the linkage between discrimination and MetS remains unclear (and underdeveloped) because 1) MetS is the risk predictor for later cardiovascular and metabolic disease instead of the health outcome caused by certain psychological factor like discrimination [2]; and 2) the process that affects MetS development is complex. Both intrapersonal determinants like awareness and interpersonal factors like social network may contribute to MetS progression. Therefore, a theoretical mechanism/model for discrimination associated with MetS is needed to unravel the interplay with personal and societal correlates that can holistically describe how MetS progresses among African Americans. Clearly, the statistical approach used to generate MetS Z-score warrants further validation. A theorized framework supporting the relationship between the MetS and its predictive ability is needed in order to explain how MetS’ consequences develop and inform future use of MetS per se or its derived Z-score for risk assessment.