A pathophysiological approach to metabolic syndrome using factor analysis in an adult Romanian population

The aim of the study was to examine the role of insulin resistance in etiopathogenesis of metabolic syndrome in an adult Romanian population using exploratory factor analysis. We analyzed 228 non-diabetic subjects randomized in respect to the age and sex distribution of the general population. For each patient, age, sex, body mass index (BMI), systolic and diastolic blood pressure (SBP, DBP), HDL-cholesterol (HDL), plasma triglycerides (TG), fasting plasma glucose (FPG) and fasting insulin were obtained. Factor analysis was performed using principal component analysis, with Varimax rotation of the major determinants of metabolic syndrome. Mean age was 48.9 +/- 12.7 years; 107 (46.9%) were men and 121 (53.1%) women. We found three major factors, which are correlated with metabolic syndrome and may explain its variance. Factor 1 comprises SBP and DBP in men and SBP, DBP and BMI in women. Factor 2 comprises BMI, HDL, TG and FPG in men and BMI, TG and FPG in women. Factor 3 comprises fasting insulin in men and fasting insulin, TG and HDL in women. The finding of more than one factor suggests that insulin resistance is not the only pathophysiological mechanism involved. These factors appear to work independently of each other in men, but they intersect in women, suggesting that the pathophysiology of metabolic syndrome may be different in women compared with men.     

Leptin and metabolic syndrome in obese and non-obese children.

Metabolic syndrome is characterized by a clustering of metabolic abnormalities: insulin resistance - hyperinsulinemia, dyslipidemia (high triglycerides and low HDL - cholesterol serum concentrations), impaired glucose tolerance and/or type 2 diabetes, and hypertension. The aim of this study was to analyse the role of different variables of metabolic syndrome, including leptin, in 74 non-obese children and 68 children with non-syndromal obesity. As metabolic syndrome variables, we have included body mass index, waist circumference, trunk-to-total skinfolds (%), systolic blood pressure, diastolic blood pressure, glucose, uric acid, fasting insulin, triglycerides and high-density lipoprotein-cholesterol (HDL-C). Factor analysis showed 4 factors in each group. In non-obese children, waist circumference, BMI, fasting insulin, triglycerides, trunk-to-total skinfolds (%), leptin and uric acid loaded positively on factor 1, and HDL-C loaded negatively on this factor; systolic and diastolic blood pressure had high positive loadings in factor 2; HDL-C and leptin showed positive loadings and triglycerides and uric acid, negative loadings in factor 3; and, finally, glucose and insulin showed positive loadings in factor 4. These four factors explained 72.16 % of the total variance in the non-obese group. In obese children, BMI, waist circumference, leptin, diastolic blood pressure and systolic blood pressure loaded positively on factor 1; diastolic blood pressure, trunk-to-total skinfolds (%), uric acid and systolic blood pressure showed high positive loadings in factor 2; fasting insulin, glucose and triglycerides showed positive loadings in factor 3; and, finally, triglycerides showed positive loadings and HDL-C negative loadings in factor 4. These four factors explained 74.18 % of the total variance in the obese group. Our results point to a different homeostatic control of metabolic syndrome characteristics in obese and non-obese children. Leptin seems to play a key underlying role in metabolic syndrome, especially in the obese group.     

Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits

We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h(2)) and heritability explained by the common SNPs (h(g)(2)) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insulin (INS), fasting trigylcerides (TG), and fasting high-density lipoprotein (HDL). We found the percentage of h(2) accounted for by common SNPs to be 58% of h(2) for height, 41% for BMI, 46% for WHR, 30% for GLU, 39% for INS, 34% for TG, 25% for HDL, and 80% for SBP. We confirmed prior reports for height and BMI using the ARIC population and independently in the Framingham Heart Study (FHS) population. We demonstrated that the multivariate model supported large genetic correlations between BMI and WHR and between TG and HDL. We also showed that the genetic correlations between the MetS traits are directly proportional to the phenotypic correlations.     

The relationship of body fat to metabolic disease: Influence of sex and ethnicity

Clinical investigations designed to determine risk profiles for the development of cardiovascular disease (CVD) and type 2 diabetes mellitus (DM) are usually performed in homogenous populations and often focus on body mass index (BMI), waist circumference (WC), and fasting triglyceride (TG) levels. However, there are major ethnic differences in the relationship of these risk factors to outcomes. For example, the BMI risk threshold may be higher in blacks than in whites and higher in women than in men. Furthermore, a WC that predicts an obese BMI in white women only predicts a BMI in the overweight category in black women. In addition, overweight black men have a greater risk of developing type 2 DM than do overweight black women. Although TG levels are excellent predictors of insulin resistance in whites, they are not effective markers of insulin resistance in blacks. Among the criteria sets currently available to predict the development of CVD and type 2 DM, the most well known is the metabolic syndrome. The metabolic syndrome has 5 criteria: central obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) levels, fasting hyperglycemia, and hypertension. To make the diagnosis of the metabolic syndrome, 3 of the 5 factors must be present. For central obesity and low HDL, the metabolic syndrome guidelines are sex specific. Diagnostic guidelines should also take ethnic differences into account, particularly in the diagnosis of central obesity and hypertriglyceridemia.     

Body adiposity index and other indexes of body composition in the SAPHIR study: Association with cardiovascular risk factors

Objective:

The accuracy of anthropometric surrogate markers such as the body adiposity index (BAI) and other common indexes like the body mass index (BMI), waist‐to‐hip ratio (WHR) and waist‐to‐height ratio (WHtR) to predict metabolic sequelae is essential for its use in clinical practice.

Design and Methods:

Thus, we evaluated the strength of BAI and other indexes to relate with anthropometric parameters, adipocytokines, blood lipids, parameters of glucose‐homeostasis and blood pressure in 1,770 patients from the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk (SAPHIR) study in a crosssectional design. Measurements were BAI, BMI, WHR, WHtR, abdominal subcutaneous and visceral adipose tissue (aSAT and VAT), total body adipose tissue mass, body weight, waist‐ and hip circumference (WC and HC), leptin, adiponectin, high‐density lipoprotein‐cholesterol (HDL‐C), low‐density lipoprotein‐cholesterol (LDL‐C), triglycerides (TG), fasting plasma glucose, fasting plasma insulin, the homeostasis model assessment of insulin resistance (HOMAIR), systolic and diastolic blood pressure.

Results and Conclusions:

BAI was significantly associated with leptin and HC. We conclude that BAI was the best calculator for leptin. BAI was inferior to BMI to predict anthropometric parameters other than HC, adiponectin, blood lipids, parameters of glucose homeostasis, and blood pressure in this cross‐sectional study.     

Castelli risk indexes 1 and 2 are higher in major depression but other characteristics of the metabolic syndrome are not specific to mood disorders

Aims

This study examined whether Castelli risk indexes 1 (total/high-density lipoprotein (HDL) cholesterol) and 2 (low density lipoprotein (LDL)/HDL cholesterol) and other shared metabolic disorders might underpin the pathophysiology of the metabolic syndrome, major depression or bipolar disorder.

Main methods

This cross-sectional study examined 92 major depressed, 49 bipolar depressed and 201 normal controls in whom the Castelli risk indexes 1 and 2 and key characteristics of the metabolic syndrome, i.e. waist/hip circumference, body mass index (BMI), systolic/diastolic blood pressure, total cholesterol, low-density lipoprotein (LDL) and HDL cholesterol, triglycerides, insulin, glucose, hemoglobin A1c (HbA1c) and homocysteine were assessed.

Key findings

Castelli risk indexes 1 and 2 were significantly higher in major depressed patients than in bipolar disorder patients and controls. There were no significant differences in waist or hip circumference, total and LDL cholesterol, triglycerides, plasma glucose, insulin, homocysteine and HbA1c between depression and bipolar patients and controls. Bipolar patients had a significantly higher BMI than major depressed patients and normal controls.

Significance

Major depression is accompanied by increased Castelli risk indexes 1 and 2, which may be risk factors for cardiovascular disease. Other key characteristics of the metabolic syndrome, either metabolic biomarkers or central obesity, are not necessarily specific to major depression or bipolar disorder.     

Analysis of Obesity and Hyperinsulinemia in the Development of Metabolic Syndrome: San Antonio Heart Study

Objective: To use standardized cut‐offs of body mass index (BMI), waist circumference, waist‐to‐hip ratio, and fasting insulin levels to predict the development of metabolic disorders and metabolic syndrome. Research Methods and Procedures: We performed an 8‐year follow‐up study of 628 non‐Hispanic whites and 1340 Mexican Americans, ages 25 to 64 years, from the second cohort of the San Antonio Heart Study. We defined metabolic disorders as dyslipidemia (triglycerides ≥2.26 mM or high‐density lipoprotein <0.91 mM in men and <1.17 mM in women), hypertension (blood pressure ≥140/≥90 mm Hg, or receiving antihypertensive medications), and type 2 diabetes (fasting glucose ≥7.0 mM, 2‐hour test glucose ≥11.1 mM, or receiving anti‐diabetic medications). People with at least two metabolic disorders were defined as having metabolic syndrome. Results: High waist‐to‐hip ratio and fasting insulin levels were significant predictors of developing metabolic syndrome. High anthropometric indices remained significant predictors of metabolic syndrome after adjusting for fasting insulin. Waist circumference, BMI, and insulin had similar areas under the receiver operating characteristic curves (0.74 to 0.76). Further multivariate analyses combining these indices showed minimal increase in prediction. Of subjects who had a combination of high BMI (≥30 kg/m²) and high waist circumference (above “Action Level 2”), 32% developed metabolic syndrome, compared with 10% of subjects with both low BMI and low waist circumference. Discussion: These findings support the National Institutes of Health recommendations for reducing the risk of metabolic syndrome. Adjustment for baseline fasting insulin levels had only a small effect on the ability of anthropometric indices to predict the metabolic syndrome.     

Comparison of the Relative Contributions of Intra‐Abdominal and Liver Fat to Components of the Metabolic Syndrome

Abdominally obese individuals with the metabolic syndrome often have excess fat deposition both intra‐abdominally (IA) and in the liver, but the relative contribution of these two deposits to variation in components of the metabolic syndrome remains unclear. We determined the mutually independent quantitative contributions of IA and liver fat to components of the syndrome, fasting serum (fS) insulin, and liver enzymes and measures of hepatic insulin sensitivity in 356 subjects (mean age 42 years, mean BMI 29.7 kg/m²) in whom liver fat and abdominal fat volumes were measured. IA and liver fat contents were correlated (r = 0.65, P < 0.0001). In multivariate linear regression analyses including either liver or IA fat, liver fat or IA fat explained variation in fS‐triglyceride (TG) and high‐density lipoprotein (HDL) cholesterol, plasma glucose, insulin and liver enzyme concentrations, and hepatic insulin sensitivity independent of age, gender, subcutaneous (SC) fat, and/or lean body mass (LBM). Including both liver and IA fat, liver and IA fat both explained variation in TG, HDL cholesterol, insulin and hepatic insulin sensitivity independent of each other and of age, gender, SC fat, and LBM. Liver fat independently predicted glucose and liver enzymes. SC fat and age explained variation in blood pressure. In conclusion, both IA and liver fat independently of each other explain variation in serum TG, HDL cholesterol, insulin concentrations and hepatic insulin sensitivity, thus supporting that both fat depots are important predictors of these components of the metabolic syndrome.     

Post-streptococcal antibodies are associated with metabolic syndrome in a population-based cohort

Background

Streptococcal infections are known to trigger autoimmune disorders, affecting millions worldwide. Recently, we found an association between post-streptococcal autoantibodies against Protein Disulphide Isomerase (PDI), an enzyme involved in insulin degradation and insulin resistance. This led us to evaluate associations between post-streptococcal antibodies and metabolic syndrome, as defined by the updated National Cholesterol Education Program definition, 2005.

Methods and Findings

Metabolic data (HDL, triglycerides, fasting glucose, blood pressure, waist circumference, BMI, smoking), post-streptococcal antibodies (anti-Streptolysin O (ASO) and anti-PDI), and C-reactive protein (CRP, as a general inflammatory marker), were assessed in 1156 participants of the Wisconsin Sleep Cohort Study. Anti-PDI antibodies were found in 308 participants (26.6%), ASO≥100 in 258 (22.3%), and 482 (41.7%) met diagnostic criteria for metabolic syndrome. Anti-PDI antibodies but not ASO were significantly associated with metabolic syndrome [n = 1156, OR 1.463 (95% CI 1.114, 1.920), p = 0.0062; adjusted for age, gender, education, smoking]. Importantly, the anti-PDI - metabolic syndrome association remained significant after adjusting for CRP and fasting insulin.

Conclusions

Post-streptococcal anti-PDI antibodies are associated with metabolic syndrome regardless of fasting insulin and CRP levels. Whereas these data are in line with a growing body of evidence linking infections, immunity and metabolism, additional studies are necessary to establish the post-streptococcal – metabolic syndrome association.     

Association Of Peripheral 5-Hydroxyindole-3-Acetic Acid,A Serotonin Derivative,with Metabolic Syndrome and Low-Grade Inflammation

Objective: The constellation of metabolic abnormalities seen in metabolic syndrome (MetS) has been linked to atherosclerosis and adverse cardiovascular outcomes due to heightened inflammation. Accumulating evidence suggests that peripheral 5-hydroxyindole-3-acetic acid (5-HIAA), the derivative end-product of serotonin (5-HT), might be involved in the pathogenesis of obesity, and abnormal lipid and glucose metabolism. We examined the association between serum 5-HIAA concentrations and MetS and also highly sensitive C-reactive protein (hsCRP).Methods: We assessed 180 healthy adults (110 males and 70 females) in a cross-sectional setting. Anthropometric indices and blood pressure were measured, as were laboratory parameters including fasting 5-HIAA concentrations. The associations between 5-HIAA and individual components of MetS, as well as MetS as a single entity, were investigated with bivariate correlation and logistic regression analyses.Results: Eighty-nine individuals (49.4%) were diagnosed with MetS. Significant correlations were found between 5-HIAA concentrations and age (r = 0.184), waist circumference (r = 0.415), high-density lipoprotein (HDL) cholesterol (r = -0.148), systolic blood pressure (r = 0.374), diastolic blood pressure (r = 0.355), homeostasis model assessment of insulin resistance (r = 0.201), and hsCRP (r = 0.453) were found (P<.05 in all tests). In logistic regression, 5-HIAA was significantly associated with 4 MetS components including central obesity, raised triglycerides, raised blood pressure, and raised fasting plasma glucose (FPG) (P<.05). Moreover, 5-HIAA was a predictor of MetS as a single entity, and the relationship persisted after adjusting for hsCRP (odds ratio [OR] = 4.41, 95% confidence interval [CI]: 2.58-7.67, P<.001).Conclusion: Elevated concentrations of 5-HIAA are seen in individuals with MetS. Increased 5-HIAA is also associated with hsCRP, a marker of chronic lowgrade inflammation underlying MetS.Abbreviations: BMI = body mass index CI = confidence interval FI = fasting insulin FPG = fasting plasma glucose HbA1c = glycated hemoglobin HDL = high-density lipoprotein 5-HIAA = 5-hydroxyindole-3-acetic acid 5-HT = 5-hydroxytryptamine HOMA-IR = homeostatic model assessment of insulin resistance hsCRP = highly sensitive C-reactive protein LDL = low-density lipoprotein MetS = metabolic syndrome OR = odds ratio     

Lipocalin-2: development, analytical characterization, and clinical testing of a new ELISA.

Lipocalin-2 (also known as neutrophil gelatinase-associated lipocalin [NGAL]) has been described as a promising marker of metabolic syndrome associated with inflammation. The aim of our work was to develop an assay for the determination of lipocalin-2 in human serum and to investigate its levels in healthy volunteers and donors suffering from metabolic syndrome. We also conducted a pilot study on individuals with metabolic syndrome and on healthy probands and measured lipocalin-2 in these individuals. We developed and evaluated the sandwich ELISA method for the quantitative determination of human lipocalin-2 in serum samples. We measured blood pressure, waist circumference, serum cholesterol, triglycerides, HDL cholesterol, LDL cholesterol, insulin, glucose, creatinine, hs-CRP, and adiponectin and calculated the BMI and Quicki insulin sensitivity index. In the study on 153 healthy volunteers, we showed that sex and age are not determinative for lipocalin-2 serum values. Furthermore, we tested 45 individuals with metabolic syndrome; values of lipocalin-2 did not differ (78.8 vs. 80.0 microg/l, p =0.56) from the data of healthy individuals from the first study. Neither group differed with regard to sex or age. Lipocalin-2 correlated with alanine aminotransferase (ALT) (r=-0.3, p<0.01) aspartate aminotransferase (AST) (r=-0.3, p<0.01), cholesterol (r=-0.21, p=0.047), creatinine (r=0.19, p=0.05), and high-sensitivity C-reactive protein (hs-CRP) (r=0.22, p=0.036). No significant correlation was found between serum lipocalin-2 and BMI, waist circumference, blood pressure, triglycerides, HDL, Quicki, or the number of metabolic syndrome components. When study patients with metabolic syndrome were further stratified according to the number of components of metabolic syndrome, serum concentrations of lipocalin-2 did not differ. The results presented demonstrate the analytical competence of the lipocalin-2 assay. However, we assumed that lipocalin-2 is not a routinely usable marker of metabolic syndrome or obesity. The association between serum lipocalin-2 and obesity or metabolic syndrome was not validated in our study.     

绝经后女性高尿酸血症患者性激素结合球蛋白与血尿酸的相关研究

目的：研究绝经后女性高尿酸血症患者血浆中性激素结合球蛋白（sexhormonebindingglobulin,SHBG）水平与血尿酸水平的相关性。方法：选取绝经后女性404例,其中高尿酸血症组204例,正常对照组200例,测量所有研究对象体重、身高、腰围、臀围、收缩压（SBP）、舒张压（DBP）,并计算体重指数（BMI）和腰臀比（WHR）,检测血尿酸（UA）、空腹血糖（FBG）、总胆固醇（TG）、甘油三酯（TC）低密度脂蛋白（LDL）、高密度脂蛋白（HDL）、雌激素（E2）、雄激素（T）、空腹胰岛素（INS）及SHBG,并计算胰岛素抵抗指数（Homa-IR）。结果：与绝经后女性尿酸正常者相比,高尿酸血症的患者UA,WHR,TC,FBG,INS,Homa-IR明显升高（P〈0．01）,DBP,WAIST和LDL升高（P〈0．05）,SHBG水平明显下降（P〈0．01）;SHBG与INs、uA、TG呈显著负相关（P〈0．05）,SHBG与E2呈显著正相关P〈0．01）。结论：绝经后女性中高尿酸血症患者的低血浆SHBG水平与高血尿酸水平显著相关,血浆SHBG水平下降与胰岛素抵抗可能高度相关,低sHBG可能作为绝经后女性患高尿酸血症的高危因素。     

Differences in the Triglyceride to HDL-Cholesterol Ratio between Palestinian and Israeli Adults

Aims

To evaluate differences in the triglyceride to HDL-cholesterol ratio (TG/HDL), thought to be a proxy measure of insulin resistance, between Palestinian and Israeli adults in view of the greater incidence of coronary heart disease and high prevalence of diabetes in Palestinian Arabs.

Research Methods

A population-based observational prevalence study of cardiovascular and diabetes risk factors in Jerusalem. Participants (968 Palestinians, 707 Israelis, sampled at ages 25-74 years) underwent fasting and 2h post-75g oral challenge plasma glucose determinations. Metabolic risk was assessed using the surrogate index TG/HDL. Sex-specific comparisons were stratified by categories of body mass index and sex-specific waist circumference quartiles, adjusted by regression for age, glucose tolerance status and use of statins.

Results

Prevalence of overweight and obesity was substantially larger in Palestinians (p = 0.005). Prevalence of diabetes was 2.4 and 4 fold higher among Palestinian men and women, respectively (p<0.001). Adjusted TG/HDL was higher in Palestinians than Israelis across BMI and waist circumference categories (p<0.001 for both). Higher TG/HDL in Palestinians persisted in analyses restricted to participants with normal glucose tolerance and off statins. Notably, higher TG/HDL among Palestinians prevailed at a young age (25-44 years) and in normal weight individuals of both sexes.

Conclusions

Palestinians have a higher TG/HDL ratio than Israelis. Notably, this is evident also in young, healthy and normal weight participants. These findings indicate the need to study the determinants of this biomarker and other measures of insulin resistance in urban Arab populations and to focus research attention on earlier ages: childhood and prenatal stages of development.     

Frequency of non-alcoholic fatty liver disease in overweight/obese children and adults: Clinical,sonographic picture and biochemical assessment

Non-alcoholic fatty liver disease (NAFLD) is a condition defined by significant lipid accumulation (5–10%) in hepatic tissue in the absence of significant chronic alcohol consumption. We aim to detect frequency of fatty liver among overweight/obese adults and children and associated clinical; anthropological measures; biochemical; genetic and imaging studies. Eighty three consecutive adults and 72 children included in the study. All patients underwent clinical measurements of height, body weight, body mass index (BMI), waist and hip circumference. Biochemical investigations were done to all subjects including liver function tests; lipid profile; fasting blood glucose; insulin resistance (IR); high sensitivity C reactive protein (hs-CRP); adiponectin and genotyping of adiponectin genes. Abdominal ultrasonography was done to search for fatty liver; to measure subcutaneous fat thickness (SFT) and visceral fat thickness (VFT). Fatty liver was detected in 47 (65.3%) children and in 52 (62.7%) adults. Correlation analysis in both groups revealed that enlarged liver was highly positively correlated to age; BMI, systolic blood pressure (SBP), diastolic blood pressure (DBP); waist circumference; hip circumference, subcutaneous fat thickness (SFT) and Visceral fat thickness (VFT), alanine aminotransferase (ALT), aspartate aminotransferase/alanine aminotransferase (AST/ALT). In addition in adults to fasting blood glucose, cholesterol, triglycerides (TG), low density lipoprotein (LDL), IR and hs-CRP. Homozygous T adiponectin genotype at position +276 was significantly increased among children with enlarged liver size and hs-CRP. NAFLD affects a substantial portion of adults and children; it is associated with the metabolic syndrome.     

Different anthropometric adiposity measures and their association with cardiovascular disease risk factors: a meta-analysis

Objectives

To investigate which anthropometric adiposity measure has the strongest association with cardiovascular disease (CVD) risk factors in Caucasian men and women without a history of CVD.

Design

Systematic review and meta-analysis.

Methods

We searched databases for studies reporting correlations between anthropometric adiposity measures and CVD risk factors in Caucasian subjects without a history of CVD. Body mass index (BMI), waist circumference, waist-to-hip ratio, waist-to-height ratio and body fat percentage were considered the anthropometric adiposity measures. Primary CVD risk factors were: systolic blood pressure, diastolic blood pressure, high density lipoprotein (HDL) cholesterol, triglycerides and fasting glucose. Two independent reviewers performed abstract, full text and data selection.

Results

Twenty articles were included describing 21,618 males and 24,139 females. Waist circumference had the strongest correlation with all CVD risk factors for both men and women, except for HDL and LDL in men. When comparing BMI with waist circumference, the latter showed significantly better correlations to CVD risk factors, except for diastolic blood pressure in women and HDL and total cholesterol in men.

Conclusions

We recommend the use of waist circumference in clinical and research studies above other anthropometric adiposity measures, especially compared with BMI, when evaluating CVD risk factors.     

Association of Serum Irisin with Metabolic Syndrome in Obese Chinese Adults

Irisin, a recently identified novel myokine, drives brown-fat-like conversion of white adipose tissues and has been proposed to mediate beneficial effects of exercise on metabolism. Circulating irisin was significantly reduced in type 2 diabetes patients; however, no evidence is available about its association with metabolic syndrome (MetS) and effects of adiposity and muscle mass on circulating irisin have been controversial. Cross-sectional data on socio-demographic, lifestyle, clinical characteristics and serum irisin were collected for 1,115 community-living Chinese adults with central obesity. Associations of serum irisin with MetS (central obesity plus any two of the following four factors (raised blood pressure (BP), raised fasting plasma glucose (FPG), raised triglyceride (TG), and reduced HDL cholesterol) and each component of MetS were analyzed using multivariable logistic regression. Among the 1,115 obese Chinese adults with a mean age of 53.2(±7.2) years, serum irisin levels (log-transformed) were significantly reduced in subjects with MetS and raised FPG than their control groups (p = 0.034 and 0.041, respectively). After adjustment for potential confounders, serum irisin was significantly associated with reduced risks of MetS and raised FPG, with odds ratios (ORs) (95% CI) per standard deviation of log-transformed irisin of 0.796 (0.505–0.959, p = 0.027) and 0.873 (0.764–0.998, p = 0.046), respectively. Associations of irisin with raised BP, raised TG and reduced HDL were not statistically significant ((ORs) (95% CI): 0.733(0.454–1.182, p = 0.202), 0.954(0.838–1.086, p = 0.478) and 1.130(0.980–1.302, p = 0.092), respectively). Stepwise multivariable linear regression analysis showed that fasting insulin, HbA1c and albumin/globulin ratio were negatively associated with serum irisin level with statistical significance (all p-values <0.05) and waist circumference was negatively associated with serum risin with marginally statistical significance (p = 0.055). These results imply that irisin may play an important role in insulin resistance and MetS and should be confirmed in future prospective studies.     

Elevated Chemerin Levels in Pakistani Men: An Interrelation with Metabolic Syndrome Phenotypes

Chemerin is a novel protein linked to adipocyte differentiation and the development of metabolic imbalances. We sought to examine the relationship of chemerin with metabolic syndrome disturbances including body fat percentage, serum lipid, glucose, insulin levels and body fat percentage in lean and obese volunteers. A cross-sectional study of 90 randomly selected healthy males from Pakistan were divided into three groups as per Body Mass Index (BMI) criteria for South Asian Population. Anthropometric measurements were taken for BMI, waist circumference, hip circumference and body fat percentage, while serum analyses were performed for fasting blood glucose, fasting insulin, fasting lipid profile and serum chemerin. Associations between serum chemerin levels and body fat and other metabolic syndrome parameters were performed using ANOVA and multiple regression analyses. Data was presented as Mean±SD. In all statistical analyses p-values <0.05 were considered significant. Circulating chemerin levels were significantly higher in obese subjects with BMI greater than 25 kg/m² compared with those with a BMI below 25 kg/m² (P = 0.001). Serum chemerin levels were found to be independently and significantly associated with serum levels of cholesterol (P = 0.0160; r = 0.255), fasting glucose (P = 0.002; r = 0.323), HOMA-IR (P = 0.004; r = 0.300) and hip circumference (P = 0.021; r = 0.246). This demonstrates that chemerin levels are associated with obesity and dyslipidemia and may play a role in the development of insulin resistance. This data suggests that chemerin may serve as an independent marker in diagnosing these conditions even before they become clinically symptomatic.     

Cortisol,obesity, and the metabolic syndrome: A cross‐sectional study of obese subjects and review of the literature

Objective:

Circulating cortisol and psychosocial stress may contribute to the pathogenesis of obesity and metabolic syndrome (MS). To evaluate these relationships, a cross‐sectional study of 369 overweight and obese subjects and 60 healthy volunteers was performed and reviewed the previous literature.

Design and Methods:

Overweight and obese subjects had at least two other features of Cushing's syndrome. They underwent measurements representing cortisol dynamics (24 h urine cortisol excretion (UFC), bedtime salivary cortisol, 1 mg dexamethasone suppression test) and metabolic parameters (BMI, blood pressure (BP); fasting serum triglycerides, HDL, insulin, and glucose). Subjects also completed the Perceived Stress Scale (PSS). UFC, salivary cortisol, and weight from 60 healthy volunteers were analyzed.

Results:

No subject had Cushing's syndrome. UFC and dexamethasone responses were not associated with BMI or weight. However, salivary cortisol showed a trend to increase as BMI increased (P < 0.0001), and correlated with waist circumference (WC) in men (r_s = 0.28, P = 0.02) and systolic BP in women (r_s = 0.24, P = 0.0008). Post‐dexamethasone cortisol levels were weak to moderately correlated with fasting insulin (r_s = ?0.31, P = 0.01) and HOMA‐IR (r_s = ?0.31, P = 0.01) in men and systolic (r_s = 0.18, P = 0.02) and diastolic BP (r_s = 0.20, P = 0.009) in women. PSS results were higher in obese subjects than controls, but were not associated with cortisol or metabolic parameters. As expected, WC correlated with fasting insulin, HOMA‐IR, and systolic BP (adjusted for BMI and gender; P < 0.01). Literature showed inconsistent relationships between cortisol and metabolic parameters.

Conclusion:

Taken together, these data do not support a strong relationship between systemic cortisol or stress and obesity or MS.

     

Multivariate linkage scan for metabolic syndrome traits in families with type 2 diabetes

The purpose of this study was to evaluate evidence for linkage to interrelated quantitative features of the metabolic syndrome (MetS). Data on eight quantitative MetS traits (body weight, waist circumference, systolic and diastolic blood pressure, high‐density lipoprotein (HDL) cholesterol, triglycerides (TGs), and fasting glucose and insulin measurements) and a 10 cM genome scan were available for 78 white families (n = 532 subjects). These data were used to conduct multipoint, multivariate linkage analyses, including tests for coincident linkage and complete pleiotropy. The strongest evidence for linkage from the bivariate analyses was observed on chromosome 1 (1p22.2) (HDL‐TG; univariate lod score equivalent (lod_eq = 3.99)) with stronger results from the trivariate analysis at the same location (HDL‐TG‐Insulin; lod_eq = 4.32). Seven additional susceptibility regions (lod_eq scores >1.9) were observed (1p36, 1q23, 2q21.2, 8q23.3, 14q23.2, 14q32.11, and 20p11.21). The results from this study indicate that several correlated traits of the MetS are influenced by the same gene(s) that account for some of the clustering of the MetS features.     

Carotid artery intima-media thickness is associated with insulin-mediated glucose disposal in nondiabetic normotensive offspring of type 2 diabetic patients

The aim of this study was to investigate whether insulin resistance is independently associated with early manifestations of atherosclerosis. To this end, 176 normotensive offspring of type 2 diabetic patients were subjected to euglycemic hyperinsulinemic clamp to assess insulin sensitivity. Early atherosclerosis was studied by ultrasonography of the common carotid artery. Of the total 176 subjects, 145 were glucose tolerant, 18 had impaired fasting glucose, and 13 had impaired glucose tolerance. Univariate correlations showed that age, body mass index, waist, blood pressure, 2-h postchallenge glucose, fasting insulin, triglycerides, interleukin-6, fibrinogen, and white blood cell count were significantly correlated with carotid intima-media thickness (IMT), whereas HDL cholesterol and glucose disposal showed a negative correlation. A stepwise multivariate regression analysis including sex, age, waist circumference, smoking status, systolic blood pressure, diastolic blood pressure, triglyceride, HDL cholesterol, 2-h postchallenge glucose, plasma IL-6, fibrinogen, white blood cell count, insulin-stimulated glucose disposal, and fasting insulin showed that the four variables that remained significantly associated with carotid IMT were waist circumference, insulin-stimulated glucose disposal, white blood cell count, and diastolic blood pressure, accounting for 33.7% of its variation. These findings support the concept that insulin sensitivity, rather than plasma insulin levels, is associated with early atherosclerosis in nondiabetic normotensive offspring of type 2 diabetic patients.