8 resultados para metabolic syndrome

em Université de Lausanne, Switzerland


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OBJECTIVE: Both subclinical hypothyroidism and the metabolic syndrome have been associated with increased risk of coronary heart disease events. It is unknown whether the prevalence and incidence of metabolic syndrome is higher as TSH levels increase, or in individuals with subclinical hypothyroidism. We sought to determine the association between thyroid function and the prevalence and incidence of the metabolic syndrome in a cohort of older adults. DESIGN: Data were analysed from the Health, Ageing and Body Composition Study, a prospective cohort of 3075 community-dwelling US adults. PARTICIPANTS: Two thousand one hundred and nineteen participants with measured TSH and data on metabolic syndrome components were included in the analysis. MEASUREMENTS: TSH was measured by immunoassay. Metabolic syndrome was defined per revised ATP III criteria. RESULTS: At baseline, 684 participants met criteria for metabolic syndrome. At 6-year follow-up, incident metabolic syndrome developed in 239 individuals. In fully adjusted models, each unit increase in TSH was associated with a 3% increase in the odds of prevalent metabolic syndrome (OR, 1.03; 95% CI, 1.01-1.06; P = 0.02), and the association was stronger for TSH within the normal range (OR, 1.16; 95% CI, 1.03-1.30; P = 0.02). Subclinical hypothyroidism with a TSH > 10 mIU/l was significantly associated with increased odds of prevalent metabolic syndrome (OR, 2.3; 95% CI, 1.0-5.0; P = 0.04); the odds of incident MetS was similar (OR 2.2), but the confidence interval was wide (0.6-7.5). CONCLUSIONS: Higher TSH levels and subclinical hypothyroidism with a TSH > 10 mIU/l are associated with increased odds of prevalent but not incident metabolic syndrome.

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AIMS: To investigate the relationship of alcohol consumption with the metabolic syndrome and diabetes in a population-based study with high mean alcohol consumption. Few data exist on these conditions in high-risk drinkers. METHODS: In 6172 adults aged 35-75 years, alcohol consumption was categorized as 0, 1-6, 7-13, 14-20, 21-27, 28-34 and ≥ 35 drinks/week or as non-drinkers (0), low-risk (1-13), medium-to-high-risk (14-34) and very-high-risk (≥ 35) drinkers. Alcohol consumption was objectively confirmed by biochemical tests. In multivariate analysis, we assessed the relationship of alcohol consumption with adjusted prevalence of the metabolic syndrome, diabetes and insulin resistance, determined with the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Seventy-three per cent of participants consumed alcohol, 16% were medium-to-high-risk drinkers and 2% very-high-risk drinkers. In multivariate analysis, the prevalence of the metabolic syndrome, diabetes and mean HOMA-IR decreased with low-risk drinking and increased with high-risk drinking. Adjusted prevalence of the metabolic syndrome was 24% in non-drinkers, 19% in low-risk (P<0.001 vs. non-drinkers), 20% in medium-to-high-risk and 29% in very-high-risk drinkers (P=0.005 vs. low-risk). Adjusted prevalence of diabetes was 6.0% in non-drinkers, 3.6% in low-risk (P<0.001 vs. non-drinkers), 3.8% in medium-to-high-risk and 6.7% in very-high-risk drinkers (P=0.046 vs. low-risk). Adjusted HOMA-IR was 2.47 in non-drinkers, 2.14 in low-risk (P<0.001 vs. non-drinkers), 2.27 in medium-to-high-risk and 2.53 in very-high-risk drinkers (P=0.04 vs. low-risk). These relationships did not differ according to beverage types. CONCLUSIONS: Alcohol has a U-shaped relationship with the metabolic syndrome, diabetes and HOMA-IR, without differences between beverage types.

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The prevalence of type 2 diabetes mellitus and of the metabolic syndrome is rising worldwide and reaching epidemic proportions. These pathologies are associated with significant morbidity and mortality, in particular with an excess of cardiovascular deaths. Type 2 diabetes mellitus and the cluster of pathologies including insulin resistance, central obesity, high blood pressure, and hypertriglyceridemia that constitute the metabolic syndrome are associated with low levels of HDL cholesterol and the presence of dysfunctional HDLs. We here review the epidemiological evidence and the potential underlying mechanisms of this association. We first discuss the well-established association of type 2 diabetes mellitus and insulin resistance with alterations of lipid metabolism and how these alterations may lead to low levels of HDL cholesterol and the occurrence of dysfunctional HDLs. We then present and discuss the evidence showing that HDL modulates insulin sensitivity, insulin-independent glucose uptake, insulin secretion, and beta cell survival. A dysfunction in these actions could play a direct role in the pathogenesis of type 2 diabetes mellitus.

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Synthetic chemicals currently used in a variety of industrial and agricultural applications are leading to widespread contamination of the environment. Even though the intended uses of pesticides, plasticizers, antimicrobials, and flame retardants are beneficial, effects on human health are a global concern. These so-called endocrine-disrupting chemicals (EDCs) can disrupt hormonal balance and result in developmental and reproductive abnormalities. New in vitro, in vivo, and epidemiological studies link human EDC exposure with obesity, metabolic syndrome, and type 2 diabetes. Here we review the main chemical compounds that may contribute to metabolic disruption. We then present their demonstrated or suggested mechanisms of action with respect to nuclear receptor signaling. Finally, we discuss the difficulties of fairly assessing the risks linked to EDC exposure, including developmental exposure, problems of high- and low-dose exposure, and the complexity of current chemical environments.

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Chronic disorders, such as obesity, diabetes, inflammation, non-alcoholic fatty liver disease and atherosclerosis, are related to alterations in lipid and glucose metabolism, in which peroxisome proliferator-activated receptors (PPAR)α, PPARβ/δ and PPARγ are involved. These receptors form a subgroup of ligand-activated transcription factors that belong to the nuclear hormone receptor family. This review discusses a selection of novel PPAR functions identified during the last few years. The PPARs regulate processes that are essential for the maintenance of pregnancy and embryonic development. Newly found hepatic functions of PPARα are the mediation of female-specific gene repression and the protection of the liver from oestrogen induced toxicity. PPARα also controls lipid catabolism and is the target of hypolipidaemic drugs, whereas PPARγ controls adipocyte differentiation and regulates lipid storage; it is the target for the insulin sensitising thiazolidinediones used to treat type 2 diabetes. Activation of PPARβ/δ increases lipid catabolism in skeletal muscle, the heart and adipose tissue. In addition, PPARβ/δ ligands prevent weight gain and suppress macrophage derived inflammation. In fact, therapeutic benefits of PPAR ligands have been confirmed in inflammatory and autoimmune diseases, such as encephalomyelitis and inflammatory bowel disease. Furthermore, PPARs promote skin wound repair. PPARα favours skin healing during the inflammatory phase that follows injury, whilst PPARβ/δ enhances keratinocyte survival and migration. Due to their collective functions in skin, PPARs represent a major research target for our understanding of many skin diseases. Taken altogether, these functions suggest that PPARs serve as physiological sensors in different stress situations and remain valuable targets for innovative therapies.

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Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10(-7)). These two SNPs were in high linkage disequilibrium (r(2) = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 x 10(-5)) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.

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To estimate the prevalence of metabolically healthy obesity (MHO) according to different definitions. Population-based sample of 2803 women and 2557 men participated in the study. Metabolic abnormalities were defined using six sets of criteria, which included different combinations of the following: waist; blood pressure; total, high-density lipoprotein or low-density lipoprotein-cholesterol; triglycerides; fasting glucose; homeostasis model assessment; high-sensitivity C-reactive protein; personal history of cardiovascular, respiratory or metabolic diseases. For each set, prevalence of MHO was assessed for body mass index (BMI); waist or percent body fat. Among obese (BMI 30 kg/m(2)) participants, prevalence of MHO ranged between 3.3 and 32.1% in men and between 11.4 and 43.3% in women according to the criteria used. Using abdominal obesity, prevalence of MHO ranged between 5.7 and 36.7% (men) and 12.2 and 57.5% (women). Using percent body fat led to a prevalence of MHO ranging between 6.4 and 43.1% (men) and 12.0 and 55.5% (women). MHO participants had a lower odd of presenting a family history of type 2 diabetes. After multivariate adjustment, the odds of presenting with MHO decreased with increasing age, whereas no relationship was found with gender, alcohol consumption or tobacco smoking using most sets of criteria. Physical activity was positively related, whereas increased waist was negatively related with BMI-defined MHO. MHO prevalence varies considerably according to the criteria used, underscoring the need for a standard definition of this metabolic entity. Physical activity increases the likelihood of presenting with MHO, and MHO is associated with a lower prevalence of family history of type 2 diabetes.

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BACKGROUND: Earlobe crease (ELC) has been associated with cardiovascular diseases (CVD) or risk factors (CVRF) and could be a marker predisposing to CVD. However, most studies studied only a small number of CVRF and no complete assessment of the associations between ELC and CVRF has been performed in a single study. METHODS: Population-based study (n = 4635, 46.7 % men) conducted between 2009 and 2012 in Lausanne, Switzerland. RESULTS: Eight hundred six participants (17.4 %) had an ELC. Presence of ELC was associated with male gender and older age. After adjusting for age and gender (and medication whenever necessary), presence of ELC was significantly (p < 0.05) associated with higher levels of body mass index (BMI) [adjusted mean ± standard error: 27.0 ± 0.2 vs. 26.02 ± 0.07 kg/m(2)], triglycerides [1.40 ± 0.03 vs. 1.36 ± 0.01 mmol/L] and insulin [8.8 ± 0.2 vs. 8.3 ± 0.1 μIU/mL]; lower levels of HDL cholesterol [1.61 ± 0.02 vs. 1.64 ± 0.01 mmol/L]; higher frequency of abdominal obesity [odds ratio and (95 % confidence interval) 1.20 (1.02; 1.42)]; hypertension [1.41 (1.18; 1.67)]; diabetes [1.43 (1.15; 1.79)]; high HOMA-IR [1.19 (1.00; 1.42)]; metabolic syndrome [1.28 (1.08; 1.51)] and history of CVD [1.55 (1.21; 1.98)]. No associations were found between ELC and estimated cardiovascular risk, inflammatory or liver markers. After further adjustment on BMI, only the associations between ELC and hypertension [1.30 (1.08; 1.56)] and history of CVD [1.47 (1.14; 1.89)] remained significant. For history of CVD, further adjustment on diabetes, hypertension, total cholesterol and smoking led to similar results [1.36 (1.05; 1.77)]. CONCLUSION: In this community-based sample ELC was significantly and independently associated with hypertension and history of CVD.