Heterogeneity in familial clustering of metabolic syndrome components in the multiethnic GENNID study.

OBJECTIVE: Metabolic syndrome (MetS) is defined by clustering of cardiometabolic components, which may be present in different combinations. The authors evaluated clustering in individuals and extended families within and across ancestry groups. METHODS: The prevalence of different combinations of MetS components (high fasting glucose, low high-density lipoprotein cholesterol, high triglycerides, high blood pressure, and abdominal obesity) was estimated in 1651 individuals (340 families) self-reporting as European American (EA), Hispanic/Mexican American (MA), African American (AA), and Japanese American (JA). Odds ratios were estimated using logistic regression with generalized estimating equations comparing individual MetS components, number, and combinations of components for each ancestry group versus EA. RESULTS: Clustering of all five components (Combination #16) was more prevalent in EA (29.9%) and MA (25.2%) individuals than in AA (18.7%) and JA (15.5%) individuals. Compared with EA individuals, AA individuals were 64% and 66% less likely to have high triglycerides and low high-density lipoprotein cholesterol, whereas JA individuals were 85% and 56% less likely to have abdominal obesity and high blood pressure, respectively. Compared with EA individuals, the odds of having two, four, or five components were at least 77% lower in JA individuals, whereas the odds of having three, four, or five components were at least 3.79 times greater in MA individuals. CONCLUSIONS: Understanding heterogeneity in MetS clustering may identify factors important in reducing health disparities.

Assessment of the FAM174A 11G allele as a risk allele for equine metabolic syndrome.

An 11G nucleotide repeat in the 3' UTR of FAM174A was recently postulated as a risk allele with a dominant mode of inheritance for equine metabolic syndrome (EMS) and laminitis status in Arabian horses. The objective of this project was to evaluate this hypothesis in a large and diverse across-breed population. A total of 301 ponies, 292 Morgans, 64 Arabians, 49 Tennessee Walking Horses and 59 Quarter Horses were genotyped for six observed G repeat alleles in the FAM174A 3' UTR. Phenotype data included laminitis status, baseline insulin, glucose, non-esterified fatty acids, triglycerides, adiponectin, leptin, ACTH, insulin and glucose post oral sugar test, and two proxies for insulin resistance. The 11G allele frequencies were 18.8, 6.9, 1.8, 0.2 and 0.0% in the Arabians, Tennessee Walkers, ponies, Morgans and Quarter Horses respectively. Association analyses between FAM174A genotype and EMS phenotypes, and between allele count and EMS phenotypes, identified no statistically significant associations. When a dominant effect for the 11G allele was evaluated, a statistically significant association with adiponectin levels was identified in the ponies, and pairwise comparisons revealed that the estimated marginal means were higher in ponies with the 11G allele vs. alternative alleles (i.e. the allele had a protective effect). In conclusion, our data do not support the FAM174A 11G allele as a risk allele for EMS in our studied breeds.

Prevalence of and Factors Associated with Metabolic Syndrome in Afro-Descendant Communities in a Situation of Vulnerability in Northern Brazil: A Cross-Sectional Study.

Background: Quilombos are Brazilian communities developed by survivor groups following fight against slavery. They are found in the whole of the Brazilian territory, far from urban centers, living in vulnerable and poor socioeconomic situations and continuously suffering from influence of occidentalization. Based on the hypothesis that the way Quilombolas live may be associated with metabolic syndrome (MS), the objective of this study was to estimate the prevalence of MS and to analyze the associated factors in adult residents of Quilombola communities in the northern region of Brazil. Methods: A cross-sectional study was conducted according to the guidelines of the STROBE Statement in five communities of Tocantins. Results: The study investigated 193 individuals who lived for at least 1 year in the communities. The prevalence of MS in this population was 32.12%. There was a higher prevalence of MS or metabolic disorders in women, as well as metabolic profiles related to low high-density lipoprotein and obesity among participants with MS. Conclusion: The prevalence of MS is higher compared with other Quilombola and African communities, indicating an opportunity to improve or develop new programs to reduce MS and metabolic disorders, by making changes in some habits, such as physical activities, because there were differences in metabolic disorders related to the presence of MS.

Assessment of the FTO gene polymorphisms in male patients with metabolic syndrome.

BACKGROUND: Accumulating evidence indicates the potential involvement of the FTO gene polymorphisms in the etiology of metabolic syndrome (MetS) and related disorders. OBJECTIVES: In this study, we aimed to investigate whether the FTO gene polymorphisms are associated with the risk of MetS and its simple components in a homogeneous sample of males. MATERIAL AND METHODS: Anthropometric and biochemical parameters were assessed in 192 males. A total of 100 males met the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria for a diagnosis of MetS. The following FTO gene polymorphisms were genotyped: rs1421085, rs17817449, rs1558902, and rs9939609. RESULTS: There were significant differences between participants with distinct rs9939609 genotypes with respect to waist-to-hip ratio (WHR) and the levels of total cholesterol. Individuals with the rs1421085 CC genotype had significantly higher levels of triglycerides compared to those with other corresponding genotypes. Participants with the rs1558902 AA genotype had significantly higher body mass index (BMI), WHR, as well as the levels of total cholesterol and triglycerides. There were no significant differences in genotype distribution allelic frequencies of all tested polymorphisms between individuals with MetS and control subjects. CONCLUSIONS: Our results indicate that the genetic variation in the FTO gene might be related to single metabolic disturbances. However, the FTO gene polymorphisms are not associated with the risk of MetS.

Serum Metabolomics of Activity Energy Expenditure and its Relation to Metabolic Syndrome and Obesity.

Modifiable lifestyle factors, including exercise and activity energy expenditure (AEE), may attenuate the unfavorable health effects of obesity, such as risk factors of metabolic syndrome (MetS). However, the underlying mechanisms are not clear. In this study we sought to investigate whether the metabolite profiles of MetS and adiposity assessed by body mass index (BMI) and central obesity are inversely correlated with AEE and physical activity. We studied 35 men and 47 women, aged 30-60 years, using doubly labeled water to derive AEE and the Sedentary Time and Activity Reporting Questionnaire (STAR-Q) to determine the time spent in moderate and vigorous physical activity. Proton nuclear magnetic resonance spectroscopy was used for serum metabolomics analysis. Serine and glycine were found in lower concentrations in participants with more MetS risk factors and greater adiposity. However, serine and glycine concentrations were higher with increasing activity measures. Metabolic pathway analysis and recent literature suggests that the lower serine and glycine concentrations in the overweight/obese state could be a consequence of serine entering de novo sphingolipid synthesis. Taken together, higher levels of AEE and physical activity may play a crucial part in improving metabolic health in men and women with and without MetS risk factors.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd.

Single nucleotide polymorphisms in CIDEC gene are associated with metabolic syndrome components risks and antihypertensive drug efficacy.

The association of single nucleotide polymorphisms rs1053239 and rs2479 of cell death-inducing DFFA-like effector c with the risk of metabolic syndrome and its components, and with the efficacy and cost-effectiveness of antihypertensive drugs was investigated. Totally 1064 subjects with metabolic syndrome and 1099 controls of Chinese Han nationality were recruited. Clinical assessment was conducted with medication records collected at baseline and during 5-year follow-up. Carriers of rs2479 A allele were at higher risk to develop elevated fasting glucose than non-carriers (P = 0.004). A allele at rs2479 were associated with a 5-year aggravation of blood triglyceride (P < 0.001) and diastolic blood pressure (P = 0.003), and C allele at rs1053239 with the exacerbation of systolic (P < 0.001) and diastolic blood pressure (P = 0.001). Moreover, efficacy and cost-effectiveness of angiotensin II-targeted drugs were higher in subjects with rs2479 A allele or rs1053239 C allele. These findings suggest that carriers of rs2479 A allele are predisposed to the development of increased fasting glucose, and the progressive elevation of blood triglyceride. Individuals with A allele at rs2479 or C allele at rs1053239 are more susceptible to a rapid progression of blood pressure, and benefit more from angiotensin II-targeted therapy.

Cardiometabolic disease in South Asians: A global health concern in an expanding population.

Cardiovascular disease (CVD) is one of the main causes of mortality and morbidity worldwide. As an emerging population, South Asians (SAs) bear a disproportionately high burden of CVD relative to underlying classical risk factors, partly attributable to a greater prevalence of insulin resistance and diabetes and distinct genetic and epigenetic influences. While the phenotypic distinctions between SAs and other ethnicities in CVD risk are becoming increasingly clear, the biology of these conditions remains an area of active investigation, with emerging studies involving metabolism, genetic variation and epigenetic modifiers (e.g., extracellular RNA). In this review, we describe the current literature on prevalence, prognosis and CVD risk in SAs, and provide a landscape of translational research in this field toward ameliorating CVD risk in SAs.

Bayesian Variable Selection in Multilevel Item Response Theory Models with Application in Genomics.

The goal of this paper is to present an implementation of stochastic search variable selection (SSVS) to multilevel model from item response theory (IRT). As experimental settings get more complex and models are required to integrate multiple (and sometimes massive) sources of information, a model that can jointly summarize and select the most relevant characteristics can provide better interpretation and a deeper insight into the problem. A multilevel IRT model recently proposed in the literature for modeling multifactorial diseases is extended to perform variable selection in the presence of thousands of covariates using SSVS. We derive conditional distributions required for such a task as well as an acceptance-rejection step that allows for the SSVS in high dimensional settings using a Markov Chain Monte Carlo algorithm. We validate the variable selection procedure through simulation studies, and illustrate its application on a study with genetic markers associated with the metabolic syndrome.

Assessment of the environmental and genetic factors influencing prevalence of metabolic syndrome in Saudi Arabia.

 Metabolic syndrome (MS) is a combination of factors that increases the risk of cardiovascular atherosclerotic diseases including diabetes, obesity, dyslipidemia, and high blood pressure. Cardiovascular diseases are one of the leading causes of death in the adult Saudi population where the increase in cardiovascular-related mortality is augmented by the rise in the prevalence of MS. Metabolic syndrome is a multi-factorial disorder influenced by interactions between genetic and environmental components. This review aims to provide a comprehensive assessment of studied environmental and genetic factors explaining the prevalence of MS in the Kingdom of Saudi Arabia. Additionally, this review aims to illustrate factors related to the population genetics of Saudi Arabia, which might explain a proportion of the prevalence of MS.

Using item response theory to model multiple phenotypes and their joint heritability in family data.

Many important complex diseases are composed of a series of phenotypes, which makes the disease diagnosis and its genetic dissection difficult. The standard procedures to determine heritability in such complex diseases are either applied for single phenotype analyses or to compare findings across phenotypes or multidimensional reduction procedures, such as principal components analysis using all phenotypes. However each method has its own problems and the challenges are even more complex for extended family data and categorical phenotypes. In this paper, we propose a methodology to determine a scale for complex outcomes involving multiple categorical phenotypes in extended pedigrees using item response theory (IRT) models that take all categorical phenotypes into account, allowing informative comparison among individuals. An advantage of the IRT framework is that a straightforward joint heritability parameter can be estimated for categorical phenotypes. Furthermore, our methodology allows many possible extensions such as the inclusion of covariates and multiple variance components. We use Markov Chain Monte Carlo algorithm for the parameter estimation and validate our method through simulated data. As an application we consider the metabolic syndrome as the multiple phenotype disease using data from the Baependi Heart Study consisting of 1,696 individuals in 95 families. We adjust IRT models without covariates and include age and age squared as covariates. The results showed that adjusting for covariates yields a higher joint heritability (h2=0.53) than without co variates (h2=0.21) indicating that the covariates absorbed some of the error variance.

Genotype by energy expenditure interaction with metabolic syndrome traits: the Portuguese healthy family study.

Moderate-to-high levels of physical activity are established as preventive factors in metabolic syndrome development. However, there is variability in the phenotypic expression of metabolic syndrome under distinct physical activity conditions. In the present study we applied a Genotype X Environment interaction method to examine the presence of GxEE interaction in the phenotypic expression of metabolic syndrome. A total of 958 subjects, from 294 families of The Portuguese Healthy Family study, were included in the analysis. Total daily energy expenditure was assessed using a 3 day physical activity diary. Six metabolic syndrome related traits, including waist circumference, systolic blood pressure, glucose, HDL cholesterol, total cholesterol and triglycerides, were measured and adjusted for age and sex. GxEE examination was performed on SOLAR 4.3.1. All metabolic syndrome indicators were significantly heritable. The GxEE interaction model fitted the data better than the polygenic model (p<0.001) for waist circumference, systolic blood pressure, glucose, total cholesterol and triglycerides. For waist circumference, glucose, total cholesterol and triglycerides, the significant GxEE interaction was due to rejection of the variance homogeneity hypothesis. For waist circumference and glucose, GxEE was also significant by the rejection of the genetic correlation hypothesis. The results showed that metabolic syndrome traits expression is significantly influenced by the interaction established between total daily energy expenditure and genotypes. Physical activity may be considered an environmental variable that promotes metabolic differences between individuals that are distinctively active.

Racial and ethnic differences in physiology and clinical symptoms of polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders and affects approximately 5 to 10% of women of reproductive age. There exists substantial variation of physical stigmata and clinical symptoms among women, but PCOS has been known to be associated with irregular periods, infertility, increased pregnancy complications, as well as nonreproductive health problems arising from its association with the metabolic syndrome. Over the years, there have been various consensus statements regarding the diagnostic criteria, but the varying pronouncements suggest that the underlying cause is still not well understood and may be multifaceted. Importantly, the interaction of genetic predisposition and local environment is possibly responsible for the heterogeneity of phenotypes seen; it has been demonstrated that there is substantial ethnic and racial variation in the clinical presentations among PCOS patients and related individuals may vary in appearance based on nutritional and other aspects of locale. The differences in phenotype and clinical symptoms of PCOS related to the clinical, hormonal, and metabolic characteristics among various ethnic backgrounds, including Hispanics, African Americans, Asians, and Indians, need to be considered when assessing and treating these individuals. Future research must address the importance of interactions between genotype and the environment.

[Diabetes mellitus and metabolic syndrome in Siberia and in the Far East].

In Siberia and in the Far East region overall incidence of diabetes mellitus is somewhat lower than in the European part of the country, though these indices reduplicate on average in 10-15 years. The prevalence of both diabetes (both types) and metabolic syndrome among indigenous mongoloid population is lower than among Caucasian.

Genetic and functional assessment of the role of the rs13431652-A and rs573225-A alleles in the G6PC2 promoter that are strongly associated with elevated fasting glucose levels.

OBJECTIVE: Genome-wide association studies have identified a single nucleotide polymorphism (SNP), rs560887, located in a G6PC2 intron that is highly correlated with variations in fasting plasma glucose (FPG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit. This study examines the contribution of two G6PC2 promoter SNPs, rs13431652 and rs573225, to the association signal. RESEARCH DESIGN AND METHODS: We genotyped 9,532 normal FPG participants (FPG <6.1 mmol/l) for three G6PC2 SNPs, rs13431652 (distal promoter), rs573225 (proximal promoter), rs560887 (3rd intron). We used regression analyses adjusted for age, sex, and BMI to assess the association with FPG and haplotype analyses to assess comparative SNP contributions. Fusion gene and gel retardation analyses characterized the effect of rs13431652 and rs573225 on G6PC2 promoter activity and transcription factor binding. RESULTS: Genetic analyses provide evidence for a strong contribution of the promoter SNPs to FPG variability at the G6PC2 locus (rs13431652: ß = 0.075, P = 3.6 × 10(-35); rs573225 ß = 0.073 P = 3.6 × 10(-34)), in addition to rs560887 (ß = 0.071, P = 1.2 × 10(-31)). The rs13431652-A and rs573225-A alleles promote increased NF-Y and Foxa2 binding, respectively. The rs13431652-A allele is associated with increased FPG and elevated promoter activity, consistent with the function of G6PC2 in pancreatic islets. In contrast, the rs573225-A allele is associated with elevated FPG but reduced promoter activity. CONCLUSIONS: Genetic and in situ functional data support a potential role for rs13431652, but not rs573225, as a causative SNP linking G6PC2 to variations in FPG, though a causative role for rs573225 in vivo cannot be ruled out.

Bayesian methods for instrumental variable analysis with genetic instruments ('Mendelian randomization'): example with urate transporter SLC2A9 as an instrumental variable for effect of urate levels on metabolic syndrome.

The 'Mendelian randomization' approach uses genotype as an instrumental variable to distinguish between causal and non-causal explanations of biomarker-disease associations. Classical methods for instrumental variable analysis are limited to linear or probit models without latent variables or missing data, rely on asymptotic approximations that are not valid for weak instruments and focus on estimation rather than hypothesis testing. We describe a Bayesian approach that overcomes these limitations, using the JAGS program to compute the log-likelihood ratio (lod score) between causal and non-causal explanations of a biomarker-disease association. To demonstrate the approach, we examined the relationship of plasma urate levels to metabolic syndrome in the ORCADES study of a Scottish population isolate, using genotype at six single-nucleotide polymorphisms in the urate transporter gene SLC2A9 as an instrumental variable. In models that allow for intra-individual variability in urate levels, the lod score favouring a non-causal over a causal explanation was 2.34. In models that do not allow for intra-individual variability, the weight of evidence against a causal explanation was weaker (lod score 1.38). We demonstrate the ability to test one of the key assumptions of instrumental variable analysis--that the effects of the instrument on outcome are mediated only through the intermediate variable--by constructing a test for residual effects of genotype on outcome, similar to the tests of 'overidentifying restrictions' developed for classical instrumental variable analysis. The Bayesian approach described here is flexible enough to deal with any instrumental variable problem, and does not rely on asymptotic approximations that may not be valid for weak instruments. The approach can easily be extended to combine information from different study designs. Statistical power calculations show that instrumental variable analysis with genetic instruments will typically require combining information from moderately large cohort and cross-sectional studies of biomarkers with information from very large genetic case-control studies.

Metabolic syndrome: aggression control mechanisms gone out of control.

An upcoming hypothesis about the evolutionary origins of metabolic syndrome is that of a 'soldier' to 'diplomat' transition in behaviour and the accompanying metabolic adaptations. Theoretical as well as empirical studies have shown that similar to the soldier and diplomat dichotomy, physically aggressive and non-aggressive strategists coexist in animal societies with negative frequency dependent selection. Although dominant individuals have a higher reproductive success obtained through means such as greater access to females, subordinate individuals have alternative means such as sneak-mating for gaining a substantial reproductive success. The alternative behavioural strategies are associated with different neurophysiologic and metabolic states. Subordinate individuals typically have low testosterone, high plasma cholesterol and glucocorticoids and elevated serotonin signalling whereas dominant ones are characterized by high testosterone, low brain serotonin and lower plasma cholesterol. Food and sex are the main natural causes of aggression. However, since aggression increases the risk of injury, aggression control is equally crucial. Therefore chronic satiety in the form of fat should induce aggression control. It is not surprising that the satiety hormone serotonin has a major role in aggression control. Further chronically elevated serotonin signalling in the hypothalamus induces peripheral insulin resistance. Meta-analysis shows that most of the anti-aggression signal molecules are pro-obesity and pro-insulin-resistance. Physical aggression is known to increase secretion of epidermal growth factor (EGF) in anticipation of injuries and EGF is important in pancreatic beta cell regeneration too. In anticipation of injuries aggression related hormones also facilitate angiogenesis and angiogenesis dysfunction is the root cause of a number of co-morbidities of insulin resistance syndrome. Reduced injury proneness typical of 'diplomat' life style would also reorient the immune system resulting into delayed wound healing on the one hand and increased systemic inflammation on the other. Diabetes is negatively associated with physically aggressive behaviour. We hypothesize that suppression of physical aggression is the major behavioural cue for the development of metabolic syndrome. Preliminary trials of behavioural intervention indicate that games and exercises involving physical aggression reduce systemic inflammation and improve glycemic control.

Type 2 diabetes, cardiovascular disease, and the evolutionary paradox of the polycystic ovary syndrome: a fertility first hypothesis.

Worldwide, the high prevalence of the Polycystic Ovary Syndrome (PCOS), a heritable cause of ovarian infertility, is an evolutionary paradox, which provides insight into the susceptibility of well-fed human populations to cardiovascular disease and diabetes. We propose that PCOS, Type 2 diabetes (T2D) and the Metabolic Syndrome are modern phenotypic expressions of a metabolic genotype attuned to the dietary and energetic conditions of the Pleistocene. This metabolic "Fertility First" rather than "Thrifty" genotype persisted at high prevalence throughout the entire agrarian period-from around 12,000 years ago until 1800 AD-primarily, we contend, because it conferred a fertility advantage in an environment defined by chronic and often severe seasonal food shortage. Conversely, we argue that genetic adaptations to a high carbohydrate, low protein agrarian diet, with increased sensitivity to insulin action, were constrained because these adaptations compromised fertility by raising the lower bound of body weight and energy intake optimal for ovulation and reproduction. After 1800, the progressive attainment of dietary energy sufficiency released human populations from this constraint. This release, through the powerful mechanism of fertility selection, increased, in decades rather than centuries, the prevalence of a genotype better suited to carbohydrate metabolism. This putative mechanism for rapid and recent human evolution can explain the lower susceptibility to T2D of today's Europid populations. This hypothesis predicts that the increasing rates of diabetes and cardiovascular disease, which typically accompany economic development, will be tempered by natural, but particularly fertility, selection against the conserved ancestral genotypes that currently underpin them.

Strategies for assessment of botanical action on metabolic syndrome in the mouse and evidence for a genotype-specific effect of Russian tarragon in the regulation of insulin sensitivity.

Published reports of botanical action are often hampered by the lack of generalized systematic approaches or by the failure to explore mechanisms that could confirm and extend the reported observations. Choice of mouse or rat housing conditions (singly or group housed) and imposed stress during handling procedures are often variable and can contribute significantly to differences in baseline phenotypes measured across studies. Differences can also be observed in the role of the extract in either the treatment of the metabolic syndrome or roles in the regulation of the emergence of metabolic syndrome. The choice of diet used can also vary between the different studies, and diet-botanical interactions must be considered. This minireview highlights the strategies being pursued by the Botanical Research Center Animal Research Core to evaluate the in vivo phenotypes of several botanical extracts during long-term feeding studies. We describe a phenotyping strategy that promotes a more rigorous interpretation of botanical action and can suggest or eliminate possible mechanisms that may be involved. We discuss the importance of selecting the mouse model, as background strain can significantly alter the underlying susceptibilities to the various components of metabolic syndrome. Finally, we present data suggesting that one of the major botanical extracts being studied, an extract of Russian tarragon, may manifest a mouse strain genotype-specific insulin-sensitizing phenotype.