Common familial influences on clustering of metabolic syndrome traits with central obesity and insulin resistance: the Kiel obesity prevention study

Mechanisms and risk factors of metabolic syndrome in children and adolescents

Metabolic syndrome (MetS) is a complex disorder characterized by abdominal obesity, elevated blood pressure, hyperlipidemia, and elevated fasting blood glucose levels. The diagnostic criteria for MetS in adults are well-established, but there is currently no consensus on the definition in children and adolescents. The etiology of MetS is believed to involve a complex interplay between genetic predisposition and environmental factors. While genetic predisposition explains only a small part of MetS pathogenesis, modifiable environmental risk factors play a significant role. Factors such as maternal weight during pregnancy, children's lifestyle, sedentariness, high-fat diet, fructose and branched-chain amino acid consumption, vitamin D deficiency, and sleep disturbances contribute to the development of MetS. Early identification and treatment of MetS in children and adolescents is crucial to prevent the development of chronic diseases later in life. In this review we discuss the latest research on factors contributing to the pathogenesis of MetS in children, focusing on non-modifiable and modifiable risk factors, including genetics, dysbiosis and chronic low-grade inflammation.

Multi-tissue transcriptome-wide association study reveals susceptibility genes and drug targets for insulin resistance-relevant phenotypes

AIM

Genome-wide association studies (GWAS) have identified multiple susceptibility loci associated with insulin resistance (IR)-relevant phenotypes. However, the genes responsible for these associations remain largely unknown. We aim to identify susceptibility genes for IR-relevant phenotypes via a transcriptome-wide association study.

MATERIALS AND METHODS

We conducted a large-scale multi-tissue transcriptome-wide association study for IR (Insulin Sensitivity Index, homeostasis model assessment-IR, fasting insulin) and lipid-relevant traits (high-density lipoprotein cholesterol, triglycerides, low-density lipoprotein cholesterol and total cholesterol) using the largest GWAS summary statistics and precomputed gene expression weights of 49 human tissues. Conditional and joint analyses were implemented to identify significantly independent genes. Furthermore, we estimated the causal effects of independent genes by Mendelian randomization causal inference analysis.

RESULTS

We identified 1190 susceptibility genes causally associated with IR-relevant phenotypes, including 58 genes that were not implicated in the original GWAS. Among them, 11 genes were further supported in differential expression analyses or a gene knockout mice database, such as KRIT1 showed both significantly differential expression and IR-related phenotypic effects in knockout mice. Meanwhile, seven proteins encoded by susceptibility genes were targeted by clinically approved drugs, and three of these genes (H6PD, CACNB2 and DRD2) have been served as drug targets for IR-related diseases/traits. Moreover, drug repurposing analysis identified four compounds with profiles opposing the expression of genes associated with IR risk.

CONCLUSIONS

Our study provided new insights into IR aetiology and avenues for therapeutic development.

Resting Energy Expenditure in the Critically Ill and Healthy Elderly-A Retrospective Matched Cohort Study

The use of indirect calorimetry to measure resting energy expenditure (mREE) is widely recommended as opposed to calculating REE (cREE) by predictive equations (PE). The aim of this study was to compare mREE with cREE in critically ill, mechanically ventilated patients aged ≥ 75 years and a healthy control group matched by age, gender and body mass index. The primary outcome was the PE accuracy rate of mREE/cREE, derived using Bland Altman plots. Secondary analyses included linear regression analyses for determinants of intraindividual mREE/cREE differences in the critically ill and interindividual mREE differences in the matched healthy cohort. In this retrospective study, 90 critically ill patients (median age 80 years) and 58 matched healthy persons were included. Median mREE was significantly higher in the critically ill (1457 kcal/d) versus the healthy cohort (1351 kcal/d), with low PE accuracy rates (21% to 49%). Independent predictors of mREE/cREE differences in the critically ill were body temperature, heart rate, FiO₂, hematocrit, serum sodium and urea. Body temperature, respiratory rate, and FiO₂ were independent predictors of interindividual mREE differences (critically ill versus healthy control). In conclusion, the commonly used PE in the elderly critically ill are inaccurate. Respiratory, metabolic and energy homeostasis variables may explain intraindividual mREE/cREE as well as interindividual mREE differences.

Association of CDH13 Gene Polymorphism and Metabolic Syndrome in Gambian Population

Background:

Polymorphism in CDH13 gene, which encodes for the adiponectin receptor, T-cadherin, is a genetic risk factor associated with metabolic syndrome. CDH13 rs3865188, which is found in the promoter region of the CDH13 gene, has been found to be associated with metabolic syndrome and its traits in Asian and European Caucasian populations. However, to the best of our knowledge, it was yet to be assessed in a Black African population.

Objective:

The aim of this study was to investigate the association of CHD13 rs3865188 and metabolic syndrome in a Gambian population.

Methods:

It was a genetic association study in a cross-sectional design in 136 Gambian participants. CDH13 rs3865188 was genotyped using PCR master mix and sequencing. Blood sugar, triglyceride and high-density lipoprotein levels were determined by standard clinical laboratory methods.

Results:

CDH13 rs3865188 was found to be significantly associated metabolic syndrome (p=0.034). Genotype AT appeared to be risk factor for metabolic syndrome (OR=2.41, 95% CI, 1.20–4.84, p=0.014). We found genotypes CC and CA in CHD13 rs3865188 for the first time.

Conclusion:

Our study demonstrated significant association between CDH13 rs385618 and metabolic syndrome in a Gambian population (Black African population for the first time). Individuals with genotype AT are at higher risk of developing metabolic syndrome.

Molecular biochemical aspects of salt (sodium chloride) in inflammation and immune response with reference to hypertension and type 2 diabetes mellitus

Obesity, insulin resistance, type 2 diabetes mellitus (T2DM) and hypertension (HTN) are common that are associated with low-grade systemic inflammation. Diet, genetic factors, inflammation, and immunocytes and their cytokines play a role in their pathobiology. But the exact role of sodium, potassium, magnesium and other minerals, trace elements and vitamins in the pathogenesis of HTN and T2DM is not known. Recent studies showed that sodium and potassium can modulate oxidative stress, inflammation, alter the autonomic nervous system and induce dysfunction of the innate and adaptive immune responses in addition to their action on renin-angiotensin-aldosterone system. These actions of sodium, potassium and magnesium and other minerals, trace elements and vitamins are likely to be secondary to their action on pro-inflammatory cytokines IL-6, TNF-α and IL-17 and metabolism of essential fatty acids that may account for their involvement in the pathobiology of insulin resistance, T2DM, HTN and autoimmune diseases.

Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients: A 15-year prospective cohort study

BACKGROUND

Type 2 diabetes mellitus (T2DM) has high morbidity and mortality worldwide, therefore there is of paramount importance to identify the risk factors in the populations at risk early in the course of illness. A strong correlation between severity of metabolic syndrome (MetS) and HbA1c, fasting insulin and insulin resistance has been reported. Accordingly, the MetS severity score (or MestS Z-score) can potentially be used to predict the risk of T2DM progression over time.

AIM

To evaluate the association the of MestS Z-score in first degree relatives (FDRs) of T2DM with the risk of prediabetes and type 2 diabetes in future.

METHODS

A prospective open cohort study was conducted between 2003-2018. At baseline, the sample comprised of 1766 FDRs of patients with T2DM who had a normal glucose tolerance test. Relative risk (RR) and 95% confidence interval were calculated based on logistic regression. The receiver-operator characteristic analysis and area under the curve based on MetS Z-score were used to evaluate the risk of prediabetes and diabetes among the FDR population.

RESULTS

Baseline MetS Z-scores were associated with the its latest values (P < 0.0001). Compared with individuals who were T2DM free at the end of follow up, those who developed T2DM had higher MetS Z-score at baseline (P < 0.001). In multivariable logistic regression analyses for every unit elevation in MetS Z-score at the baseline, the RR for developing future T2DM and prediabetes was (RR = 1.94, RR = 3.84), (RR = 1.5, RR = 2.17) in total population and female group, respectively (P < 0.05). The associations remained significant after adjusting the potential confounding variables. A cut off value of 0.97 and 0.94 was defined in the receiver-operator characteristic curve based on the MetS Z-score for differentiating female patients with diabetes and prediabetes from the normal population, respectively.

CONCLUSION

The MetS Z-score was associated with an increased risk of future T2DM. Appropriate interventions at earlier stages for preventing and attenuating MetS effects may be considered as an effective strategy for FDR as at-risk population.

Beyond the CNS: The many peripheral roles of APOE

Apolipoprotein E (APOE) is a multifunctional protein synthesized and secreted by multiple mammalian tissues. Although hepatocytes contribute about 75% of the peripheral pool, APOE can also be expressed in adipose tissue, the kidney, and the adrenal glands, among other tissues. High levels of APOE production also occur in the brain, where it is primarily synthesized by glia, and peripheral and brain APOE pools are thought to be distinct. In humans, APOE is polymorphic, with three major alleles (ε2, ε3, and ε4). These allelic forms dramatically alter APOE structure and function. Historically, the vast majority of research on APOE has centered on the important role it plays in modulating risk for cardiovascular disease and Alzheimer's disease. However, the established effects of this pleiotropic protein extend well beyond these two critical health challenges, with demonstrated roles across a wide spectrum of biological conditions, including adipose tissue function and obesity, metabolic syndrome and diabetes, fertility and longevity, and immune function. While the spectrum of biological systems in which APOE plays a role seems implausibly wide at first glance, there are some potential unifying mechanisms that could tie these seemingly disparate disorders together. In the current review, we aim to concisely summarize a wide breadth of APOE-associated pathologies and to analyze the influence of APOE in the development of several distinct disorders in order to provide insight into potential shared mechanisms implied in these various pathophysiological processes.

Association of Serum Renalase Levels and Renalase rs10887800 Polymorphism with Unstable Angina Pectoris Patients Having Metabolic Syndrome

PURPOSE

An increased risk of cardiovascular mortality and morbidity has been linked with metabolic syndrome (MetS), described as the secondary risk reduction target. These patients are predisposed to high complication levels such as unstable angina-pectoris (USAP) by MetS. As with the role of renalase in the regulation of blood pressure (BP), the study was carried out to determine the levels of renalase circulation in patients with USAP and MetS (USAP+MetS), as well as the association of renalase gene (RNLS) rs10887800 polymorphism and USAP and MetS susceptibility.

PATIENTS AND METHODS

A total of 134 patients with USAP+MetS and 134 control subjects were recruited in this case-control study.

RESULTS

Renalase was found to have a significantly higher level in USAP+MetS patients (23.28 ± 4.09 µg/dL) than in healthy ones (20.81 ± 2.73 µg/dL) (P < 0.001). Also, it was shown that renalase sensitivity and specificity values for the early diagnosis of USAP and MetS seemed to be 53.7% and 76.9, respectively. Moreover, the value for renalase area under curve (AUC) was 0.654 (95% CI: 0.58-0.72). The frequency of rs10887800 AG and GG genotypes of RNLS gene was significantly higher in USAP+MetS patients than in control subjects, suggesting that this genotype might be a risk factor against USAP+MetS (OR = 2.114 [95% CI 1.113-4.016]; P = 0.022) and (OR = 2.057 [95% CI 1.011-4.186]; P = 0.047), respectively.

CONCLUSION

The present results showed that renalase serum levels increased in USAP and MetS patients. Moreover, the RNLS rs10887800 was reported to be associated with a higher risk of USAP+MetS.

Development of a Genetic Score to Predict an Increase in HDL Cholesterol Concentration After a Dietary Intervention in Adults with Metabolic Syndrome

BACKGROUND

Dietary intervention (DI) is a primary strategy to attenuate some of the metabolic abnormalities associated with metabolic syndrome (MetS), including low HDL cholesterol. There is no biomarker that can identify individuals who respond to DI by increasing HDL cholesterol.

OBJECTIVE

The aim of this study was to assess the predictive power of a genetic predisposition score (GPS) in Mexican adults with MetS to identify HDL cholesterol responders to DI.

METHODS

This study followed a prospective cohort design. Sixty-seven Mexican adults aged 20-60 y (21% men) with BMI ≥25 and ≤39.9 kg/m², who had at least 3 of 5 positive criteria for MetS, were included. Participants consumed a low saturated fat diet for 2.5 mo (<7% energy as saturated fat, <200 mg of cholesterol/d) and reduced their usual diet by ∼440 kcal/d, a reduction in total energy intake of about 25%. Anthropometry and serum biochemical markers, including HDL cholesterol, were measured before and after DI. A multilocus GPS was constructed using previously reported genetic variants associated with response to diet in subjects with MetS. GPS values, designed to predict the response of HDL cholesterol to the DI, were computed for each individual as the sum of the number of effect alleles across 14 SNPs.

RESULTS

Individuals were dichotomized as high and low GPS according to median GPS (-2.12) and we observed a difference in HDL cholesterol changes on DI of +3 mg/dL (6.3%) in subjects with low GPS, whereas those with high GPS had HDL cholesterol decreases of -3 mg/dL (-7.9%) (P = 0.04).

CONCLUSIONS

Individuals with low GPS showed greater increases in their HDL cholesterol than those with high GPS. Therefore, the GPS can be useful for predicting the HDL cholesterol response to diet.

Estimation of metabolic syndrome heritability in three large populations including full pedigree and genomic information

Metabolic syndrome is a complex human disorder characterized by a cluster of conditions (increased blood pressure, hyperglycemia, excessive body fat around the waist, and abnormal cholesterol or triglyceride levels). Any of these conditions increases the risk of serious disorders such as diabetes or cardiovascular disease. Currently, the degree of genetic regulation of this syndrome is under debate and partially unknown. The principal aim of this study was to estimate the genetic component and the common environmental effects in different populations using full pedigree and genomic information. We used three large populations (Gubbio, ARIC, and Ogliastra cohorts) to estimate the heritability of metabolic syndrome. Due to both pedigree and genotyped data, different approaches were applied to summarize relatedness conditions. Linear mixed models (LLM) using average information restricted maximum likelihood (AIREML) algorithm were applied to partition the variances and estimate heritability (h²) and common sib-household effect (c²). Globally, results obtained from pedigree information showed a significant heritability (h²: 0.286 and 0.271 in Gubbio and Ogliastra, respectively), whereas a lower, but still significant heritability was found using SNPs data ([Formula: see text]: 0.167 and 0.254 in ARIC and Ogliastra). The remaining heritability between h² and [Formula: see text] ranged between 0.031 and 0.237. Finally, the common environmental c² in Gubbio and Ogliastra were also significant accounting for about 11% of the phenotypic variance. Availability of different kinds of populations and data helped us to better understand what happened when heritability of metabolic syndrome is estimated and account for different possible confounding. Furthermore, the opportunity of comparing different results provided more precise and less biased estimation of heritability.

Which predictors differentiate between obese children and adolescents with cardiometabolic complications and those with metabolically healthy obesity?

BACKGROUND/AIMS

Childhood obesity and associated metabolic comorbidities is a major global health concern. Metabolically healthy obesity (MHO) may represent a subgroup of individuals in which excessive body fat accumulation does not lead to adverse metabolic effects. We aimed to determine the prevalence of MHO among obese Israeli children and adolescents and to find predictors for metabolically unhealthy obesity (MUO).

METHODS

In a retrospective study, demographic, anthropometric, lifestyle, and cardiometabolic data were retrieved from medical records of patients with a body mass index (BMI) >95th percentile aged 6 to 17.6 years, attending a tertiary pediatric obesity clinic between 2008 and 2015, with at least 1 year of follow-up. Participants were dichotomized as either MHO or MUO based on cardiometabolic risk factor clustering (blood pressure, serum lipids, and glucose). Multivariable logistic regression was used to determine predictors of MUO.

RESULTS

Of the 230 children (median age 9.9 years) fulfilling study criteria, 48 (20.9%) were classified as MHO. Occurrence of MUO was associated with male gender, Arabic ethnicity, higher BMI-SD score, higher tri-ponderal mass index (TMI), and higher insulin resistance (IR) (presence of acanthosis nigricans and a higher level of homeostasis model assessment-IR [HOMA-IR]). Male gender (odds ratio [OR] 2.27, P = .033), presence of acanthosis nigricans at baseline (OR 2.35, P = .035), and a greater increase in BMI-SDS during follow-up (OR 2.82, P = .05) were the best predictors of MUO.

CONCLUSIONS

The MHO phenotype was present in only 20.9% of obese Israeli children. MUO was significantly associated with male gender, with presence of acanthosis nigricans, and with a greater increase in BMI-SDS during follow-up.

Normalizing resting energy expenditure across the life course in humans: challenges and hopes

Whole-body daily energy expenditure is primarily due to resting energy expenditure (REE). Since there is a high inter-individual variance in REE, a quantitative and predictive framework is needed to normalize the data. Complementing the assessment of REE with data normalization makes individuals of different sizes, age, and sex comparable. REE is closely correlated with body mass suggesting its near constancy for a given mass and, thus, a linearity of this association. Since body mass and its metabolic active components are the major determinants of REE, they have been implemented into allometric modeling to normalize REE for quantitative differences in body weight and/or body composition. Up to now, various size and allometric scale laws are used to adjust REE for body mass. In addition, the impact of the anatomical and physical properties of individual body components on REE has been quantified in large populations and for different age groups. More than 80% of the inter-individual variance in REE is explained by FFM and its composition. There is evidence that the impact of individual organs on REE varies between age groups with a higher contribution of brain and visceral organs in children/adolescents compared with adults where skeletal muscle mass contribution is greater than in children/adolescents. However, explaining REE variations by FFM and its composition has its own limitations (inter-correlations of organs/tissues). In future, this could be overcome by re-describing the organ-to-organ variation using principal components analysis and then using the scores on the components as predictors in a multiple regression analysis.

Different metabolic responses induced by long-term interdisciplinary therapy in obese adolescents related to ACE I/D polymorphism

Introduction:

The main purpose of the present study was to investigate whether I/D polymorphism of the ACE gene might affect metabolic changes related to the metabolic syndrome through a long-term interdisciplinary therapy in obese adolescents.

Methods:

In total, 125 obese adolescents who entered the interdisciplinary obesity programme were assigned to the following two subgroups: metabolic syndrome or non-metabolic syndrome. They were evaluated at baseline and after 1 year. Genomic DNA was extracted from circulating leukocytes.

Results:

Subjects with the II genotype in the non-metabolic syndrome group were only to increase their fat-free mass after therapy. Regarding lipid profile, subjects with ID and DD genotypes from both groups reduced their low-density lipoprotein cholesterol levels significantly. The metabolic parameters from the ID and DD genotypes of the non-metabolic syndrome group showed a significantly improved insulin response.

Conclusion:

In the present study, we showed that the ACE polymorphism was able to influence the fat-free mass in the I-carry allele in the non-metabolic syndrome group positively. In addition, the I-carry allele was able to improve the insulin resistance of the metabolic syndrome group significantly. These results suggest that the ACE I/D genotypes can influence, in different ways, the specific parameters of metabolism among obese adolescents submitted for long-term interdisciplinary therapy.

Shared Genetic Control of Brain Activity During Sleep and Insulin Secretion: A Laboratory-Based Family Study

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate.

Heritability of the Severity of the Metabolic Syndrome in Whites and Blacks in 3 Large Cohorts

BACKGROUND

Although dichotomous criteria for the metabolic syndrome (MetS) appear heritable, it is not known whether MetS severity as assessed by a continuous MetS score is heritable and whether this varies by race.

METHODS AND RESULTS

We used SOLAR (Sequential Oligogenic Linkage Analysis Routines) to evaluate heritability of Adult Treatment Panel-III MetS and a sex- and race-specific MetS severity Z score among 3 large familial cohorts: the JHS (Jackson Heart Study, 1404 black participants), TOPS (Take Off Pounds Sensibly, 1947 white participants), and PLRS (Princeton Lipid Research Study, 229 black and 527 white participants). Heritability estimates were larger for Adult Treatment Panel-III MetS among black compared with white cohort members (JHS 0.48; 95% confidence interval [CI], 0.28-0.68 and PLRS blacks 0.93 [95% CI, 0.73-1.13] versus TOPS 0.21 [95% CI, -0.18 to 0.60] and PLRS whites 0.27 [95% CI, -0.04 to 0.58]). The difference by race narrowed when assessing heritability of the MetS severity score (JHS 0.52 [95% CI, 0.38, 0.66] and PLRS blacks 0.64 [95% CI, 0.13-1.15] versus TOPS 0.23 [95% CI, 0.15-0.31] and PLRS whites 0.60 [95% CI, 0.33-0.87]). There was a high degree of genetic and phenotypic correlation between MetS severity and the individual components of MetS among all groups, although the genetic correlations failed to reach statistical significance among PLRS blacks. Meta-analyses revealed a combined heritability estimate for Adult Treatment Panel-III MetS of 0.24 (95% CI, 0.11-0.36) and for the MetS severity score of 0.50 (95% CI, -0.05 to 0.99).

CONCLUSIONS

MetS severity seems highly heritable among whites and blacks. This continuous MetS severity Z score may provide a more useful means of characterizing phenotypic MetS in genetic studies by minimizing racial differences.

From the past to future: from energy expenditure to energy intake to energy expenditure

Although most recent research on energy balance focusses on energy intake (EI) there is still need to think about both sides of the energy balance. Current research on energy expenditure (EE) relates to metabolic adaptation to negative energy balance, mitochondrial metabolism associated with aging, obesity and type 2 diabetes mellitus, the role of EE in hunger and appetite control, non-shivering thermogenesis and brown adipose tissue activity, cellular bioenergetics as a target of obesity treatment and the evolutionary and ecological determinants of EE in humans and other primates. As far as regulation of energy balance is concerned there is recent evidence that EE rather than body weight is under tight control. Biologically, EE is maintained within a narrow physiological range. An EE-set point has been proposed as the width between the upper and lower boundaries of the individual EE range. Regulation of EE may fail in very obese patients with an EI above their upper boundary and after drastic weight loss when patients may go far below their lower EE boundary and thus are loosing control. In population studies, fat-free mass (FFM) and its composition (that is, the proportion of high to low metabolic rate organs) are major determinants of EE. It is tempting to speculate that tight biologic control of EE is related to brain energy need, which is preserved at the cost of peripheral metabolism. There is a moderate heritability of EE, which is independent of the heritability of FFM. In future, metabolic phenotyping should focus on the EE-FFM relationship rather than on EE-values alone.

Clinical utility of metabolic syndrome severity scores: considerations for practitioners

The metabolic syndrome (MetS) is marked by abnormalities in central obesity, high blood pressure, high triglycerides, low high-density lipoprotein-cholesterol, and high fasting glucose and appears to be produced by underlying processes of inflammation, oxidative stress, and adipocyte dysfunction. MetS has traditionally been classified based on dichotomous criteria that deny that MetS-related risk likely exists as a spectrum. Continuous MetS scores provide a way to track MetS-related risk over time. We generated MetS severity scores that are sex- and race/ethnicity-specific, acknowledging that the way MetS is manifested may be different by sex and racial/ethnic subgroup. These scores are correlated with long-term risk for type 2 diabetes mellitus and cardiovascular disease. Clinical use of scores like these provide a potential opportunity to identify patients at highest risk, motivate patients toward lifestyle change, and follow treatment progress over time.

Apolipoprotein E4 association with metabolic syndrome depends on body fatness

BACKGROUND AND AIMS

The human Apolipoprotein E (APOE) gene is polymorphic. The APOE*4 allele is a risk factor for cardiovascular disease and could contribute to the development of the metabolic syndrome (MetS) as it may affect all MetS components. We hypothesize that the common APOE4 polymorphism differentially regulates MetS risk and that this association might be modulated by body fatness.

METHODS & RESULTS

We used body mass index (BMI) as surrogate of fatness and cross-sectionally studied the prevalence of MetS in 4408 middle-aged men of the Aragon Workers Health Study (AWHS). Our analysis revealed i) a gene dose-dependent association between APOE*4 allele and increased risk for MetS, ii) this association primarily derived from the overweight subjects. For these individuals, the MetS risk was higher in APOE*4 carriers than in non-carriers (Odds Ratio = 1.31; 95% CI, 1.03-1.67). Additionally, we examined 3908 healthy young individuals from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort, followed-up for 25 years. Compared with APOE*4 non-carriers, APOE*4 presence significantly increased the risk of developing MetS (Hazard Ratio, 1.12; 95% CI, 1.00-1.26). Again, an interplay between APOE*4 and the longitudinal development of fatness towards the onset of MetS occurred throughout the study. For individuals with BMI gain below the median, the cumulative onset rate of MetS was significantly higher in APOE*4 carriers than in the non-carriers (HR, 1.29; 95% CI, 1.07-1.55).

CONCLUSIONS

Carrying APOE*4 alleles increases MetS in a dose-dependent manner, characterizing individual's APOE genotype might help identify at-risk subjects for preventive intervention.

Prevalence, associated factors and heritabilities of metabolic syndrome and its individual components in African Americans: the Jackson Heart Study

OBJECTIVE

Both environmental and genetic factors play important roles in the development of metabolic syndrome (MetS). Studies about its associated factors and genetic contribution in African Americans (AA) are sparse. Our aim was to report the prevalence, associated factors and heritability estimates of MetS and its components in AA men and women.

PARTICIPANTS AND SETTING

Data of this cross-sectional study come from a large community-based Jackson Heart Study (JHS). We analysed a total of 5227 participants, of whom 1636 from 281 families were part of a family study subset of JHS.

METHODS

Participants were classified as having MetS according to the Adult Treatment Panel III criteria. Multiple logistic regression analysis was performed to isolate independently associated factors of MetS (n=5227). Heritability was estimated from the family study subset using variance component methods (n=1636).

RESULTS

About 27% of men and 40% of women had MetS. For men, associated factors with having MetS were older age, lower physical activity, higher body mass index, and higher homocysteine and adiponectin levels (p<0.05 for all). For women, in addition to all these, lower education, current smoking and higher stress were also significant (p<0.05 for all). After adjusting for covariates, the heritability of MetS was 32% (p<0.001). Heritability ranged from 14 to 45% among its individual components. Relatively higher heritability was estimated for waist circumference (45%), high density lipoprotein-cholesterol (43%) and triglycerides (42%). Heritability of systolic blood pressure (BP), diastolic BP and fasting blood glucose was 16%, 15% and 14%, respectively.

CONCLUSIONS

Stress and low education were associated with having MetS in AA women, but not in men. Higher heritability estimates for lipids and waist circumference support the hypothesis of lipid metabolism playing a central role in the development of MetS and encourage additional efforts to identify the underlying susceptibility genes for this syndrome in AA.

Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene

Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 "A" allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.

Genetic association study with metabolic syndrome and metabolic-related traits in a cross-sectional sample and a 10-year longitudinal sample of chinese elderly population

Background

The metabolic syndrome (MetS) has been known as partly heritable, while the number of genetic studies on MetS and metabolic-related traits among Chinese elderly was limited.

Methods

A cross-sectional analysis was performed among 2 014 aged participants from September 2009 to June 2010 in Beijing, China. An additional longitudinal study was carried out among the same study population from 2001 to 2010. Biochemical profile and anthropometric parameters of all the participants were measured. The associations of 23 SNPs located within 17 candidate genes (MTHFR, PPARγ, LPL, INSIG, TCF7L2, FTO, KCNJ11, JAZF1, CDKN2A/B, ADIPOQ, WFS1, CDKAL1, IGF2BP2, KCNQ1, MTNR1B, IRS1, ACE) with overweight and obesity, diabetes, metabolic phenotypes, and MetS were examined in both studies.

Results

In this Chinese elderly population, prevalence of overweight, central obesity, diabetes, dyslipidemia, hypertension, and MetS were 48.3%, 71.0%, 32.4%, 75.7%, 68.3% and 54.5%, respectively. In the cross-sectional analyses, no SNP was found to be associated with MetS. Genotype TT of SNP rs4402960 within the gene IGF2BP2 was associated with overweight (odds ratio (OR)  = 0.479, 95% confidence interval (CI): 0.316-0.724, p = 0.001) and genotype CA of SNP rs1801131 within the gene MTHFR was associated with hypertension (OR = 1.560, 95% CI: 1.194–2.240, p = 0.001). However, these associations were not observed in the longitudinal analyses.

Conclusions

The associations of SNP rs4402960 with overweight as well as the association of SNP rs1801131 with hypertension were found to be statistically significant. No SNP was identified to be associated with MetS in our study with statistical significance.

Genetic variants of apolipoprotein A5 T-1131C and apolipoprotein E common polymorphisms and their relationship to features of metabolic syndrome in adult dyslipidemic patients

OBJECTIVES

The aim was to evaluate the relationships of the T-1131C (rs662799) polymorphism variants of apolipoprotein A5 (Apo A5) gene and variants of apolipoprotein E (Apo E) gene common polymorphism (rs429358, rs7412) to signs of metabolic syndrome (MetS).

DESIGN AND METHODS

We examined 590 asymptomatic dyslipidemic patients divided into MetS+ (n=146) and MetS- (n=444) groups according to criteria of NCEP ATPIII Panel. We evaluated genotype frequencies and differences in MetS features between individual groups. Logistic regression analysis was used for the evaluation of Apo A5/Apo E variants as possible risk factors for MetS.

RESULTS

We found no statistical differences between genotype and allele frequencies for both Apo A5 and Apo E polymorphisms between MetS+ and MetS- groups. In all subjects and MetS- group, we confirmed well-known association of the -1131C Apo A5 minor allele with elevated triglycerides (TG, p<0.001). The Apo E gene E2 and E4 variants were associated with higher levels of TG (p<0.01) in comparison to E33 common variant. However, no statistical differences were observed in MetS+ subjects, regardless of significantly higher TG levels in this group. Apo A5/Apo E variant analysis in all dyslipidemic patients revealed significant increase of TG levels in all subgroups in comparison to common -1131T/E3 variant carriers, the most in -1131C/E4 variant subgroup. Logistic regression analysis models showed no association of Apo A5, Apo E and all Apo A5/Apo E variants with metabolic syndrome, even after adjustment for age and sex.

CONCLUSION

Our study refined the role of Apo A5 and Apo E genetic variants in the group of adult dyslipidemic patients. We demonstrate that except of TG, Apo A5 T-1131C (rs662799) and Apo E (rs429358, rs7412) polymorphisms have no remarkable effect on MetS characteristics.

Genetic variation at the CYP2C19 gene associated with metabolic syndrome susceptibility in a South Portuguese population: results from the pilot study of the European Health Examination Survey in Portugal

BACKGROUND

Metabolic syndrome (MetS) is a cluster of conditions that occur together, increasing the risk of heart disease, stroke and diabetes. Since pathways implicated in different diseases reveal surprising insights into shared genetic bases underlying apparently unrelated traits, we hypothesize that there are common genetic components involved in the clustering of MetS traits. With the aim of identifying these common genetic components, we have performed a genetic association study by integrating MetS traits in a continuous MetS score.

METHODS

A cross-sectional study developed in the context of the Portuguese Component of the European Health Examination Survey (EHES) was used. Data was collected through a detailed questionnaire and physical examination. Blood samples were collected and biochemical analyses were performed. Waist circumference, blood pressure, glucose, triglycerides and high density lipoprotein cholesterol (HDL) levels were used to compute a continuous MetS score, obtained by Principal Component Analysis. A total of 37 single nucleotide polymorphisms (SNPs) were genotyped and individually tested for association with the score, adjusting for confounding variables.

RESULTS

A total of 206 individuals were studied. Calculated MetS score increased progressively with increasing number of risk factors (P < 0.001). We found a significant association between CYP2C19 rs4244285 and the MetS score not detected using the MetS dichotomic approach. Individuals with the A allelic variant seem to be protected against MetS, displaying a lower MetS score (Mean difference: 0.847; 95%CI: 0.163-1.531; P = 0.015), after adjustment for age, gender, smoking status, excessive alcohol consumption and physical inactivity. An additive genetic effect of GABRA2 rs279871, NPY rs16147 and TPMT rs1142345 in the MetS score variation was also found.

CONCLUSIONS

This is the first report of a genetic association study using a continuous MetS score. The significant association found between the CYP2C19 polymorphism and the MetS score but not with the individual associated traits, emphasizes the importance of lipid metabolism in a MetS common etiological pathway and consequently on the clustering of different cardiovascular risk factors. Despite the sample size limitation of our study, this strategy can be useful to find genetic factors involved in the etiology of other disorders that are defined in a dichotomized way.

Association of genetic variants in the adiponectin gene with metabolic syndrome: a case-control study and a systematic meta-analysis in the Chinese population

Background

The prevalence of metabolic syndrome has been rising worldwide, including in China, but knowledge on specific genetic determinants of metabolic syndrome is very limited. A number of studies have reported that polymorphisms in the ADIPOQ gene are associated with metabolic syndrome in Chinese Han populations. However, data is still conflicting. The objective of this study was to examine the associations of the adiponectin genetic variants with metabolic syndrome by a case-control study and meta-analyses in Chinese.

Methods

We first investigated the association of ADIPOQ rs2241766 (+45T>G in exon 2), rs266729 (−11377C>G in promoter) and rs1501299 (+276G>T in intron 2) polymorphisms with metabolic syndrome in a Hubei Han Chinese population with 322 metabolic syndrome patients and 161 normal controls recruited from the Yichang, Hubei. Then we comprehensively reviewed the association between ADIPOQ rs2241766/rs266729/rs1501299 and metabolic syndrome in the Chinese populations via a meta-analysis. The strength of association was assessed by odds ratios (ORs) with 95% confidence intervals (CI).

Results

The G allele frequency of rs2241766 in metabolic syndrome patients was significantly higher than those of controls group (29.8% vs 23.3%, OR = 1.40, P = 0.033). The logistic regression analysis adjusted by gender and age showed a nominally significant association for rs2241766 GG+GT genotype (P = 0.065, OR = 1.55) and rs1501299 GG genotype in recessive model (OR = 1.54, P = 0.066). However, no association was observed for rs266729 in our sample. We identified thirteen studies for rs2241766 (2,684 metabolic syndrome patients and 2,864 controls), three studies for rs266729, and eleven studies for rs1501299 (2,889 metabolic syndrome patients and 3,304 controls) in Chinese. Meta-analysis indicated significant associations for the rs2241766 G allele (OR = 1.14, 95%CI = 1.05–1.24, P = 0.003), rs266729 GG+GT genotypes (OR = 0.80, 95%CI = 0.68–0.92, P = 0.003) and rs1501299 GG+TG genotypes (OR = 1.42, 95%CI 1.16–1.75, P = 0.001).

Conclusions

Our results demonstrated ADIPOQ as a pleiotropic locus for metabolic syndrome and its components in the Han Chinese population.

Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study

BACKGROUND

Mechanisms involved in metabolic syndrome (MetS) development include insulin resistance, weight regulation, inflammation and lipid metabolism. Aim of this study is to investigate the association of single nucleotide polymorphisms (SNPs) involved in these mechanisms with MetS.

METHODS

In a random sample of the EPIC-NL study (n = 1886), 38 SNPs associated with waist circumference, insulin resistance, triglycerides, HDL cholesterol and inflammation in genome wide association studies (GWAS) were selected from the 50K IBC array and one additional SNP was measured with KASPar chemistry. The five groups of SNPs, each belonging to one of the metabolic endpoints mentioned above, were associated with MetS and MetS-score using Goeman's global test. For groups of SNPs significantly associated with the presence of MetS or MetS-score, further analyses were conducted.

RESULTS

The group of waist circumference SNPs was associated with waist circumference (P=0.03) and presence of MetS (P=0.03). Furthermore, the group of SNPs related to insulin resistance was associated with MetS score (P<0.01), HDL cholesterol (P<0.01), triglycerides (P<0.01) and HbA1C (P=0.04). Subsequent analyses showed that MC4R rs17782312, involved in weight regulation, and IRS1 rs2943634, related to insulin resistance were associated with MetS (OR 1.16, 95%CI 1.02-1.32 and OR 0.88, 95% CI 0.79; 0.97, respectively). The groups of inflammation and lipid SNPs were neither associated with presence of MetS nor with MetS score.

CONCLUSIONS

In this study we found support for the hypothesis that weight regulation and insulin metabolism are involved in MetS development.MC4R rs17782312 and IRS1 rs2943634 may explain part of the genetic variation in MetS.

Fasting and oral glucose-stimulated levels of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) are highly familial traits

AIMS/HYPOTHESIS

Heritability estimates have shown a varying degree of genetic contribution to traits related to type 2 diabetes. Therefore, the objective of this study was to investigate the familiality of fasting and stimulated measures of plasma glucose, serum insulin, serum C-peptide, plasma glucose-dependent insulinotropic polypeptide (GIP) and plasma glucagon-like peptide-1 (GLP-1) among non-diabetic relatives of Danish type 2 diabetic patients.

METHODS

Sixty-one families comprising 193 non-diabetic offspring, 29 non-diabetic spouses, 72 non-diabetic relatives (parent, sibling, etc.) and two non-related relatives underwent a 4 h 75 g OGTT with measurements of plasma glucose, serum insulin, serum C-peptide, plasma GIP and plasma GLP-1 levels at 18 time points. Insulin secretion rates (ISR) and beta cell responses to glucose, GIP and GLP-1 were calculated. Familiality was estimated based on OGTT-derived measures.

RESULTS

A high level of familiality was observed during the OGTT for plasma levels of GIP and GLP-1, with peak familiality values of 74 ± 16% and 65 ± 15%, respectively (h (2) ± SE). Familiality values were lower for plasma glucose, serum insulin and serum C-peptide during the OGTT (range 8-48%, 14-44% and 15-61%, respectively). ISR presented the highest familiality value at fasting reaching 59 ± 16%. Beta cell responsiveness to glucose, GLP-1 and GIP also revealed a strong genetic influence, with peak familiality estimates of 62 ± 13%, 76 ± 15% and 70 ± 14%, respectively.

CONCLUSIONS/INTERPRETATION

Our results suggest that circulating levels of GIP and GLP-1 as well as beta cell response to these incretins are highly familial compared with more commonly investigated measures of glucose homeostasis such as fasting and stimulated plasma glucose, serum insulin and serum C-peptide.

Related factors of insulin resistance in Korean children: adiposity and maternal insulin resistance

Increased adiposity and unhealthy lifestyle augment the risk for type 2 diabetes in children with familial predisposition. Insulin resistance (IR) is an excellent clinical marker for identifying children at high risk for type 2 diabetes. This study was conducted to investigate parental, physiological, behavioral and socio-economic factors related to IR in Korean children. This study is a cross-sectional study using data from 111 children aged 7 years and their parents. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using fasting glucose and insulin level as a marker of IR. All children’s adiposity indices (r = 0.309–0.318, all P-value = 0.001) and maternal levels of fasting insulin (r = 0.285, P-value = 0.003) and HOMA-IR (r = 0.290, P-value = 0.002) were positively correlated with children’s HOMA-IR level. There was no statistical difference of children’s HOMA-IR level according to children’s lifestyle habits and socioeconomic status of families. An increase of 1 percentage point in body fat was related to 2.7% increase in children’s HOMA-IR (P-value < 0.001) and an increase of 1% of maternal level of HOMA-IR was related to 0.2% increase in children’s HOMA-IR (P-value = 0.002). This study shows that children’s adiposity and maternal IR are positively associated with children’s IR.

Shared genetic variance between the features of the metabolic syndrome: heritability studies

Heritability estimates of MetS range from approximately 10%-30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation in common, by reviewing the literature regarding genetic correlation coefficients. Identification of features, that have much genetic variation in common, may eventually facilitate the search for pleitropic genetic variants that may explain the clustering of MetS features. A PubMed search with the search terms "(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)" was performed. Studies published before 7th July 2011, which presented genetic correlation coefficients between the different MetS features and genetic correlation coefficients of MetS and its features with adipose tissue-, pro-inflammatory and pro-thrombotic biomarkers were included. Nine twin and 19 family studies were included in the review. Genetic correlations varied, but were strongest between waist circumference and HOMA-IR (r(2): 0.36 to 0.79, median: 0.50), HDL cholesterol and triglycerides (r(2): -0.05 to -0.59, median -0.45), adiponectin and MetS (r(2): -0.32 to -0.43; median -0.38), adiponectin and insulin (r(2): -0.10 to -0.60; median -0.30) and between adiponectin and HDL-cholesterol (r(2): -0.22 to -0.51, median -0.29). In conclusion, heritability studies suggest that genetic pleiotropy exist especially between certain MetS features, as well as between MetS and adiponectin. Further research on actual genetic variants responsible for the genetic pleiotropy of these combinations will provide more insight into the etiology of MetS.

Genetic variants and the metabolic syndrome: a systematic review

Several candidate gene studies on the metabolic syndrome (MetS) have been conducted. However, for most single nucleotide polymorphisms (SNPs) no systematic review on their association with MetS exists. A systematic electronic literature search was conducted until the 2nd of June 2010, using HuGE Navigator. English language articles were selected. Only genes of which at least one SNP-MetS association was studied in an accumulative total population ≥ 4000 subjects were included. Meta-analyses were conducted on SNPs with three or more studies available in a generally healthy population. In total 88 studies on 25 genes were reviewed. Additionally, for nine SNPs in seven genes (GNB3, PPARG, TCF7L2, APOA5, APOC3, APOE, CETP) a meta-analysis was conducted. The minor allele of rs9939609 (FTO), rs7903146 (TCF7L2), C56G (APOA5), T1131C (APOA5), C482T (APOC3), C455T (APOC3) and 174G>C (IL6) were more prevalent in subjects with MetS, whereas the minor allele of Taq-1B (CETP) was less prevalent in subjects with the MetS. After having systematically reviewed the most studied SNP-MetS associations, we found evidence for an association with the MetS for eight SNPs, mostly located in genes involved in lipid metabolism.

A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.

The metabolic syndrome represents a clustering of metabolic phenotypes (e.g. elevated blood pressure, cholesterol levels, and plasma glucose, as well as abdominal obesity) and is associated with an increased risk of atherosclerosis and type 2 diabetes. Although multiple genes influencing the specific metabolic syndrome components have been reported, few studies have evaluated the genetic underpinnings of the syndrome as a whole. Here, we describe an approach to evaluate multiple clustered traits, which allows us to test whether common genetic variants influence the co-occurrence of one or more metabolic phenotypes. By examining approximately 20,000 European American and 6,200 African American participants from five studies, we show that three regions on chromosomes 12, 19, and 20 are associated with multiple metabolic phenotypes. These genetic variants are highly intriguing candidates that may increase our understanding of the biologic basis of the clustering of metabolic phenotypes and help identify targets for early intervention.

Genetic variants in lipid metabolism are independently associated with multiple features of the metabolic syndrome

Background

Our objective was to find single nucleotide polymorphisms (SNPs), within transcriptional pathways of glucose and lipid metabolism, which are related to multiple features of the metabolic syndrome (MetS).

Methods

373 SNPs were measured in 3575 subjects of the Doetinchem cohort. Prevalence of MetS features, i.e. hyperglycemia, abdominal obesity, decreased HDL-cholesterol levels and hypertension, were measured twice in 6 years. Associations between the SNPs and the individual MetS features were analyzed by log-linear models. For SNPs related to multiple MetS features (P < 0.01), we investigated whether these associations were independent of each other.

Results

Two SNPs, CETP Ile405Val and APOE Cys112Arg, were associated with both the prevalence of low HDL-cholesterol level (Ile405Val P = < .0001; Cys112Arg P = 0.001) and with the prevalence of abdominal obesity (Ile405Val P = 0.007; Cys112Arg P = 0.007). For both SNPs, the association with HDL-cholesterol was partly independent of the association with abdominal obesity and vice versa.

Conclusion

Two SNPs, mainly known for their role in lipid metabolism, were associated with two MetS features i.e., low HDL-cholesterol concentration, as well as, independent of this association, abdominal obesity. These SNPs may help to explain why low HDL-cholesterol levels and abdominal obesity frequently co-occur.

Genetic studies of common types of obesity: a critique of the current use of phenotypes

Recent research into the genetic basis of obesity has focused upon the study of candidate genes, both functional and positional, of genes underlying weight-related Mendelian disorders and of susceptibility loci identified in genome-wide association studies. Three large genome-wide association studies on obesity, together involving more than 150,000 individuals, were published in Nature Genetics last year. The results suggested the involvement of a large number of genetic variants in disease susceptibility. Most genetic effects upon body weight are likely to become obscured by the use of inappropriate phenotypes. In particular, clinical categories such as the body mass index and Metabolic Syndrome do not provide sufficient etiological information for them to be used sensibly in genetic studies on obesity or obesity-related disease. Alleviation of this situation will not come from new genomic research tools, sophisticated statistical algorithms or ever larger sample sizes. Instead, the above notions argue in favour of so-called 'deep phenotyping'.

Prevalence of the metabolic syndrome among extremely obese adolescents in Italy and Germany

Juvenile metabolic syndrome (MetS) is a growing major medical problem in industrialised countries. We estimated its prevalence among two similar clinic-based sequentially recruited cohorts of extremely obese adolescents (age: 12-18 years) from Italy (N=665, males=271, females=394) and Germany (N=661, males=261, females=400) using the recent IDF paediatric criteria. The prevalence of the MetS was 23.3% among the Italians and 40.4% among the Germans. A multivariate logistic regression revealed an increased risk related to age (adjusted odd ratio (AOR): 2.24; 95% confidence interval (CI): 1.59-3.16; p<0.001), BMI SDS (AOR: 3.61; 95% CI: 2.33-5.60; p<0.001), male gender (AOR: 2.36; 95% CI: 1.80-3.10; p<0.001), and in German adolescents (AOR: 2.56; 95% CI: 1.98-3.31; p<0.001). Among Italian adolescents having the MetS, 83% had 3 abnormalities, 16% had 4 abnormalities while less than 1% had all the 5 abnormalities. In the German cohort, 67%, 28% and 5% of affected individuals had 3, 4 and 5 abnormalities, respectively. These results indicate that MetS is highly prevalent among extremely obese adolescents, and suggest that (besides age, obesity and gender) national sociocultural factors, as alimentary trends, could be important. Further tools should be developed to understand international epidemiological differences concerning obesity and its comorbidities in relation to lifestyles in the countries of European Union.

Evidence for three novel QTLs for adiposity on chromosome 2 with epistatic interactions: the NHLBI Family Heart Study

We sought to identify quantitative trait loci (QTLs) by genome-wide linkage analysis for BMI and waist circumference (WC) exploring various strategies to address heterogeneity including covariate adjustments and complex models based on epistatic components of variance. Because cholesterol-lowering drugs and diabetes medications may affect adiposity and risk of coronary heart disease, we excluded subjects medicated for hypercholesterolemia and hyperglycemia. The evidence of linkage increased on 2p25 (BMI: lod = 1.59 vs. 2.43, WC: lod = 1.32 vs. 2.26). Because environmental and/or genetic components could mask the effect of a specific locus, we investigated further whether a QTL could influence adiposity independently of lipid pathway and dietary habits. Strong evidence of linkage on 2p25 (BMI: lod = 4.31; WC: lod = 4.23) was found using Willet's dietary factors and lipid profile together with age and sex in adjustment. It suggests that lipid profile and dietary habits are confounding factors for detecting a 2p25 QTL for adiposity. Because evidence of linkage has been previously detected for BMI on 7q34 and 13q14 in National Heart, Lung, and Blood Institute Family Heart Study (NHLBI FHS), and for diabetes on 15q13, we investigated epistasis between chromosome 2 and these loci. Significant epistatic interactions were found between QTLs 2p25 and 7q34, 2q37 and 7q34, 2q31 and 13q14, and 2q31-q36 and 15q13. These results suggest multiple pathways and factors involving genetic and environmental effects influencing adiposity. By taking some of these known factors into account, we clarified our linkage evidence of a QTL on 2p25 influencing BMI and WC. The 2p25, 2q24-q31, and 2q36-q37 showed evidence of epistatic interaction with 7q34, 13q14, and 15q13.

'Functional' body composition: differentiating between benign and non-benign obesity

Recent body composition analyses, together with assessments of insulin resistance, aerobic fitness, and intima-media thickness of the common carotid artery, have shown that metabolically-benign obese subjects have a similar BMI, waist circumference, and subcutaneous abdominal fat compared with non-metabolically-benign obese subjects. Research has suggested that 25-30% of the obese population do not need either treatment or prevention of secondary disorders. Therefore, assessment of functional body composition should replace nutritional status-based risk assessments (such as the body mass index) in both metabolic research and clinical decision making. The concept of ‘functional’ body composition gives us a more sophisticated view on nutritional status, metabolism, endocrinology, and diseases. Knowledge of detailed body composition enables characterization of biomedical traits which will give functional evidence relating genetic variants.

Influence of a type 2 diabetes associated prostaglandin E synthase 2 polymorphism on blood prostaglandin E2 levels

In this study we tested whether the type 2 diabetes mellitus associated prostaglandin E synthase 2 arginine to histidine polymorphism at position 298 (R298H) influences prostaglandin E2 levels in humans. Fasting prostaglandin E2 was determined in the blood of subjects carrying different genotypes of the R298H polymorphism. Subjects were matched by sex, age, and body mass index. No differences in prostaglandin E2 levels were found with respect to genotypes when considering the whole group. Male homozygous histidine carriers showed elevated prostaglandin E2 levels compared to heterozygous carriers and homozygous arginine carriers (188.2+/-42.4 vs. 80.4+/-26.5pg/ml, p=0.021; and vs. 92.9+/-15.3pg/ml, p=0.11). These differences were not evident in female subjects. In contrast, 6-keto-prostaglandin F1alpha levels as independent marker of arachidonic acid metabolism showed ambiguous results. Nevertheless, preliminary evidence of the prostaglandin E synthase 2 R298H polymorphism possibly influencing prostaglandin E2 blood levels in a gender-specific manner was obtained.

The search for putative unifying genetic factors for components of the metabolic syndrome

AIMS/HYPOTHESIS

The metabolic syndrome is a cluster of factors contributing to increased risk of cardiovascular disease and type 2 diabetes but unifying mechanisms have not been identified. Our aim was to study whether common variations in 17 genes previously associated with type 2 diabetes or components of the metabolic syndrome and variants in nine genes with inconsistent association with at least two components of the metabolic syndrome would also predict future development of components of the metabolic syndrome, individually or in combination.

METHODS

Genetic variants were studied in a large prospective study of 16,143 non-diabetic individuals (mean follow-up time 23 years) from the Malmö Preventive Project. In this study, development of at least three of obesity (BMI >or= 30 kg/m(2)), dyslipidaemia (triacylglycerol >or= 1.7 mmol/l and/or lipid-lowering treatment), hypertension (blood pressure >or= 140/90 mmHg and/or antihypertensive medication) and hyperglycaemia (fasting plasma glucose >or= 5.6 mmol/l and/or known diabetes) was defined as development of the metabolic syndrome. The risk of developing at least three components of the metabolic syndrome or the individual components was calculated by logistic regression adjusted for age at baseline, follow-up time and sex.

RESULTS

Polymorphisms in TCF7L2 (rs7903146, OR 1.10, 95% CI 1.04-1.17, p = 0.00097), FTO (rs9939609, OR 1.08, 95% CI 1.02-1.14, p = 0.0065), WFS1 (rs10010131, OR 1.07, 95% CI 1.02-1.13, p = 0.0078) and IGF2BP2 (rs4402960, OR 1.07, 95% CI 1.01-1.13, p = 0.021) predicted the development of at least three components of the metabolic syndrome in both univariate and multivariate analysis; in the case of TCF7L2, WFS1 and IGF2BP this was due to their association with hyperglycaemia (p < 0.00001, p = 0.0033 and p = 0.027, respectively) and for FTO it was due to its association with obesity (p = 0.004). A polymorphism in the GCKR gene predicted dyslipidaemia (rs1260326, OR 1.15, 95% CI 1.09-1.22, p < 0.00001) but not the metabolic syndrome. None of the studied polymorphisms was associated with more than two components of the metabolic syndrome. A composite genotype score of the 17 polymorphisms associated with type 2 diabetes predicted the development of at least three components of the metabolic syndrome (OR 1.04, p < 0.00001) and the development of hyperglycaemia (OR 1.06, p < 0.00001). Carriers of >or=19 risk alleles had 51 and 72% increased risk of developing at least three components of the metabolic syndrome and hyperglycaemia, respectively, compared with carriers of <or=12 risk alleles (p < 0.00001 for both).

CONCLUSIONS/INTERPRETATION

Polymorphisms in susceptibility genes for type 2 diabetes (TCF7L2, WFS1, IGF2BP2) and obesity (FTO) predispose to the metabolic syndrome by increasing the risk of one specific component of the metabolic syndrome. The findings argue against a unifying genetic component for the metabolic syndrome.

The metabolic syndrome

The "metabolic syndrome" (MetS) is a clustering of components that reflect overnutrition, sedentary lifestyles, and resultant excess adiposity. The MetS includes the clustering of abdominal obesity, insulin resistance, dyslipidemia, and elevated blood pressure and is associated with other comorbidities including the prothrombotic state, proinflammatory state, nonalcoholic fatty liver disease, and reproductive disorders. Because the MetS is a cluster of different conditions, and not a single disease, the development of multiple concurrent definitions has resulted. The prevalence of the MetS is increasing to epidemic proportions not only in the United States and the remainder of the urbanized world but also in developing nations. Most studies show that the MetS is associated with an approximate doubling of cardiovascular disease risk and a 5-fold increased risk for incident type 2 diabetes mellitus. Although it is unclear whether there is a unifying pathophysiological mechanism resulting in the MetS, abdominal adiposity and insulin resistance appear to be central to the MetS and its individual components. Lifestyle modification and weight loss should, therefore, be at the core of treating or preventing the MetS and its components. In addition, there is a general consensus that other cardiac risk factors should be aggressively managed in individuals with the MetS. Finally, in 2008 the MetS is an evolving concept that continues to be data driven and evidence based with revisions forthcoming.

Association of different obesity indices with blood pressure and blood lipids in children and adolescents

The aim of the present study was to compare individual associations of BMI, triceps skinfold (TSF), waist circumference (WC) and percentage fat mass (%FM) with blood pressure (BP) and blood lipids in children and adolescents. Cross-sectional data on BMI, TSF, WC, %FM as well as on BP, TAG and HDL were analysed in 4220 (BP) and 729 (lipids) 9–11-year-old children and 3174 (BP) and 536 (lipids) 13–16-year-old adolescents as part of the Kiel Obesity Prevention Study. All obesity indices were similarly associated with BP and blood lipids. In girls, WC had closer correlations to BP than BMI (systolic BP: 0·27 and 0·24 for BMI, 0·34 and 0·28 for WC in 9–11- and 13–16-year-olds). Subjects with an obesity index ≥ 90th percentile had higher prevalences of elevated BP and blood lipids than subjects with a normal index. In children with normal BMI or WC, an additionally elevated second obesity index was associated with a 2·5–7·4-fold higher prevalence of high BP when compared with children with normal indices. In adolescents, an elevated WC plus an elevated second obesity index was associated with a 2·6–8·2-fold higher prevalence of high BP when compared with adolescents with an elevated WC plus a normal second index. We conclude that (i) both BMI and WC are appropriate to estimate CVD risk, (ii) the use of a second obesity index is recommended in children with normal BMI or normal WC as well as in adolescents with elevated WC and (iii) all obesity indices seemed to be appropriate for risk assessment.

Familial influences and obesity-associated metabolic risk factors contribute to the variation in resting energy expenditure: the Kiel Obesity Prevention Study

BACKGROUND

A low metabolic rate may be inherited and predispose to obesity, whereas a higher metabolic rate in obesity may be acquired by obesity-associated cardiometabolic risk.

OBJECTIVE

We aimed to explain the interindividual variation in resting energy expenditure (REE) by assessing 1) the association between REE and body composition, thyroid hormones, and obesity-related cardiometabolic risk factors, and 2) the familial (genetic and environmental) contribution to REE.

DESIGN

REE and metabolic risk factors (ie, blood pressure and plasma insulin, glucose, and C-reactive protein concentrations) were assessed in 149 two- or three-generation families, including at least one overweight or obese member. Heritability of REE, respiratory quotient (RQ), thyroid hormones [thyrotropin (TSH), free triiodothyronine (FT3) and free thyroxine (FT4)], and body composition (fat-free mass and fat mass) were estimated by using variance components-based quantitative genetic models.

RESULTS

REE adjusted for body composition, sex, and age (REEadj) significantly correlated with systolic and diastolic blood pressure, plasma insulin and glucose concentrations, and the homeostasis model assessment (HOMA) (r = 0.14-0.31, P < 0.05). Thyroid hormones had a modest influence on REE variance only. Heritability was 0.30 +/- 0.07 for REEadj and 0.29 +/- 0.08 for REE after additional adjustment for thyroid hormones and metabolic risk. Furthermore, heritability was estimated to be 0.22 +/- 0.08 for RQ, 0.37 +/- 0.08 for TSH, 0.68 +/- 0.06 for FT4, and 0.69 +/- 0.05 for FT3 (all significantly larger than zero).

CONCLUSIONS

Obesity-related cardiometabolic risk factors contribute to interindividual variation in REE, with hypertension and insulin resistance being associated with a higher REE. REE was moderately heritable, independent of body composition, sex, age, thyroid function, and cardiometabolic risk.

Childhood obesity, hypertension, the metabolic syndrome and adult cardiovascular disease

1. The worldwide epidemic of obesity in adults has been mirrored in children in developed and developing countries. 2. Central obesity appears to be driving a cluster of abnormalities often referred to as the metabolic syndrome. 3. The definition of the metabolic syndrome in children is not suited to arbitrary cut-offs and a definition using the significant clustering of risk factors that is already evident in childhood and adolescent populations may be preferable. 4. An Australian population study showed that 25% of 8-year-olds and 29% of 14-year-olds could be described by the high risk cluster with features similar to adult metabolic syndrome. 5. The high risk cluster was significantly linked to high and low birthweight, shorter duration of breast-feeding, larger postnatal weight gains after 12 months of age and raised C-reactive protein, gamma glutamyl transferase and alanine transaminase levels. At-risk young adults have also been shown to have macroscopic atherosclerosis in post-mortem studies. 6. Identification of at-risk children has obvious benefits for the individual and as well, for prevention of a future cohort with raised cardiovascular morbidity and mortality; however, complexities and controversies exist in doing so. Familial, genetic and lifestyle risk factors aggregate and labelling children with predisease may be problematic. Committed political and societal changes are necessary to reduce childhood obesity and subsequent adult cardiovascular disease.

Heritability of cardiovascular risk factors in a Brazilian population: Baependi Heart Study

Background

The heritability of cardiovascular risk factors is expected to differ between populations because of the different distribution of environmental risk factors, as well as the genetic make-up of different human populations.

Methods

The purpose of this analysis was to evaluate genetic and environmental influences on cardiovascular risk factor traits, using a variance component approach, by estimating the heritability of these traits in a sample of 1,666 individuals in 81 families ascertained randomly from a highly admixed population of a city in a rural area in Brazil.

Results

Before adjustment for sex, age, age², and age × sex interaction, polygenic heritability of systolic (SBP) and diastolic (DBP) blood pressure were 15.0% and 16.4%, waist circumference 26.1%, triglycerides 25.7%, fasting glucose 32.8%, HDL-c 31.2%, total cholesterol 28.6%, LDL-c 26.3%, BMI 39.1%. Adjustment for covariates increased polygenic heritability estimates for all traits mainly systolic and diastolic blood pressure (25.9 and 26.2%, respectively), waist circumference (40.1%), and BMI (51.0%).

Conclusion

Heritability estimates for cardiovascular traits in the Brazilian population are high and not significantly different from other studied worldwide populations. Mapping efforts to identify genetic loci associated with variability of these traits are warranted.