Metabolic syndrome as a risk factor for diabetes.
ABSTRACT The metabolic syndrome was initially described as an insulin-resistance syndrome characterized by the clustering of metabolic traits such as high triglycerides, low high-density lipoprotein cholesterol, high blood pressure, abdominal obesity and different degrees of impaired glucose regulation. Although different definitions have been developed by various consensus groups, epidemiological studies demonstrate that they all associate the metabolic syndrome with a similar cardiometabolic risk, which is high for diabetes (ranging between three- and 20-fold), depending on the number of components and the inclusion of impaired fasting glucose, impaired glucose tolerance or both. The latter appear to indicate the failure of the beta cell to produce enough insulin to compensate for the increased demand due to insulin resistance. There is a hyperbolic relationship between insulin production and insulin sensitivity, which can be calculated by the disposition index. When this is altered there is a higher risk of developing Type 2 diabetes. There have been no clinical trials in subjects selected by the diagnosis of metabolic syndrome, but structured lifestyle changes have been tested in people with impaired fasting glucose/impaired glucose tolerance and have been able to reduce incident Type 2 diabetes by almost 50%, as long as a weight loss of at least 5% is achieved. Oral antidiabetic and anti-obesity drugs have also been successful to a lesser degree. Some fibrates have reduced or delayed incident diabetes. Extended-release niacin has a neutral effect and statins are controversial. ACE inhibitors and ARBs are the antihypertensive agents least associated with incident diabetes.
SourceAvailable from: PubMed Central[Show abstract] [Hide abstract]
ABSTRACT: We sought develop and characterize a diet-induced model of metabolic syndrome and its related diseases. The experimental animals (Spague-Dawley rats) were randomly divided into two groups, and each group was fed a different feed for 48 weeks as follows: 1) standard control diet (SC), and 2) a high sucrose and high fat diet (HSHF). The blood, small intestine, liver, pancreas, and adipose tissues were sampled for analysis and characterization. Typical metabolic syndrome (MS), non-alcoholic fatty liver disease (NAFLD), and type II diabetes (T2DM) were common in the HSHF group after a 48 week feeding period. The rats fed HSHF exhibited signs of obesity, dyslipidemia, hyperglycaemia, glucose intolerance, and insulin resistance (IR). At the same time, these animals had significantly increased levels of circulating LPS, TNFα, and IL-6 and increased ALP in their intestinal tissue homogenates. These animals also showed a significant reduction in the expression of occluding protein. The HSHF rats showed fatty degeneration, inflammation, fibrosis, cirrhosis, and lipid accumulation when their liver pathologies were examined. The HSHF rats also displayed increased islet diameters from 12 to 24 weeks, while reduced islet diameters occurred from 36 to 48 weeks with inflammatory cell infiltration and islet fat deposition. The morphometry of adipocytes in HSHF rats showed hypertrophy and inflammatory cell infiltration. HSHF CD68 analysis showed macrophage infiltration and significant increases in fat and pancreas size. HSHF Tunel analysis showed significant increases in liver and pancreas cell apoptosis. This work demonstrated the following: 1) a characteristic rat model of metabolic syndrome (MS) can be induced by a high sucrose and high fat diet, 2) this model can be used to research metabolic syndrome and its related diseases, such as NAFLD and T2DM, and 3) intestinal endotoxemia (IETM) may play an important role in the pathogenesis of MS and related diseases, such as NAFLD and T2DM.PLoS ONE 12/2014; 9(12):e115148. DOI:10.1371/journal.pone.0115148 · 3.53 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: The study objective was to evaluate independent and interactive associations of dietary fiber intake and high urinary enterolignans with cardiometabolic risk factors. The analysis included 2260 adults (≥20 y of age) from the 2003-2010 NHANES. Logistic regression models were used to evaluate obesity and clinically defined obesity and cardiometabolic risk factors in relation to dietary fiber intake and urinary enterolignan concentrations. Three sets of models were created: 1) independent associations, 2) mutually adjusted associations, and 3) interactions. Models were adjusted for age, gender, race/ethnicity, education, smoking status, and energy intake. High concentrations were considered to be above the 90th percentile of urinary enterolignan concentrations. Increasing dietary fiber intake was associated with high blood pressure (P = 0.02) and low serum HDL cholesterol (P-trend = 0.03). High urinary enterodiol concentration was not associated with obesity or cardiometabolic risk factors. High urinary enterolactone concentration was inversely associated with obesity (OR: 0.44; 95% CI: 0.29, 0.66), abdominal obesity (OR: 0.58; 95% CI: 0.39, 0.87), high serum C-reactive protein (CRP; OR: 0.52; 95% CI: 0.37, 0.74), high serum triglycerides (OR: 0.39; 95% CI: 0.23, 0.61), low serum HDL cholesterol (OR: 0.37; 95% CI: 0.23, 0.61), and metabolic syndrome (OR: 0.47; 95% CI: 0.30, 0.74). In mutually adjusted models, enterolactone associations observed in independent models remained similar, but associations for dietary fiber intake were attenuated, with the exception of blood pressure. In interaction models, there were 2 significant interactions: between high urinary enterodiol concentration and dietary fiber intake for high serum CRP (P = 0.04) and high plasma glucose (P = 0.04). Overall, being in the highest 10% of urinary enterolactone concentration was associated with cardiometabolic risk factors, independent of dietary fiber intake and enterodiol concentration. Future studies are warranted to evaluate physiologic actions of enterolactone or aspects of the gut microbial profile responsible for lignan metabolism to enterolactone.Journal of Nutrition 06/2014; 144(9). DOI:10.3945/jn.114.190512 · 4.23 Impact Factor