Search

The prevalence of stroke is expected to increase partly because of prolonged life expectancy in the general population. The objective of this study was to investigate trends in the prevalence of patients hospitalized with ischemic stroke (IS) in Sweden from 1995-2010.The Swedish inpatient and cause-specific death registries were used to estimate the absolute numbers and prevalence of patients who were hospitalized with and survived an IS from 1995-2010.The overall number of IS increased from 129,418 in 1995 to 148,778 in 2010. In 1995, the prevalence of IS was 189 patients per 10,000 population. An increase in overall prevalence was observed until 2000, and then it remained stable, followed by a decline with an annual percentage change of (APC) -0.8% (95% CI -1.0 to 0.6) and with a final prevalence of 199 patients per 10,000 population in 2010. The prevalence of IS in people aged

In Sweden, previous favourable trends in blood cholesterol levels have recently levelled off or even increased in some age groups since 2003, potentially reflecting changing fashions and attitudes towards dietary saturated fatty acids (SFA). We aimed to examine the potential effect of different SFA intake on future coronary heart disease (CHD) mortality in 2025.We compared the effect on future CHD mortality of two different scenarios for fat intake a) daily SFA intake decreasing to 10 energy percent (E%), and b) daily SFA intake rising to 20 E%. We assumed that there would be moderate improvements in smoking (5%), salt intake (1g/day) and physical inactivity (5% decrease) to continue recent, positive trends.In the baseline scenario which assumed that recent mortality declines continue, approximately 5,975 CHD deaths might occur in year 2025. Anticipated improvements in smoking, dietary salt intake and physical activity, would result in some 380 (-6.4%) fewer deaths (235 in men and 145 in women). In combination with a mean SFA daily intake of 10 E%, a total of 810 (-14%) fewer deaths would occur in 2025 (535 in men and 275 in women). If the overall consumption of SFA rose to 20 E%, the expected mortality decline would be wiped out and approximately 20 (0.3%) additional deaths might occur.CHD mortality may increase as a result of unfavourable trends in diets rich in saturated fats resulting in increases in blood cholesterol levels. These could cancel out the favourable trends in salt intake, smoking and physical activity.

In metabolic diseases such as Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, the systemic regulation of postprandial metabolite concentrations is disturbed. To understand this dysregulation, a quantitative and temporal understanding of systemic postprandial metabolite handling is needed. Of particular interest is the intertwined regulation of glucose and non-esterified fatty acids (NEFA), due to the association between disturbed NEFA metabolism and insulin resistance. However, postprandial glucose metabolism is characterized by a dynamic interplay of simultaneously responding regulatory mechanisms, which have proven difficult to measure directly. Therefore, we propose a mathematical modelling approach to untangle the systemic interplay between glucose and NEFA in the postprandial period. The developed model integrates data of both the perturbation of glucose metabolism by NEFA as measured under clamp conditions, and postprandial time-series of glucose, insulin, and NEFA. The model can describe independent data not used for fitting, and perturbations of NEFA metabolism result in an increased insulin, but not glucose, response, demonstrating that glucose homeostasis is maintained. Finally, the model is used to show that NEFA may mediate up to 30-45% of the postprandial increase in insulin-dependent glucose uptake at two hours after a glucose meal. In conclusion, the presented model can quantify the systemic interactions of glucose and NEFA in the postprandial state, and may therefore provide a new method to evaluate the disturbance of this interplay in metabolic disease.

The first objective was to investigate if intracellular and extracellular levels of reactive oxygen species (ROS) within the mouse aorta increase before or after diet-induced lesion formation. The second objective was to investigate if intracellular and extracellular ROS correlates to cell composition in atherosclerotic lesions. The third objective was to investigate if intracellular and extracellular ROS levels within established atherosclerotic lesions can be reduced by lipid lowering by diet or atorvastatin.To address our objectives, we established a new imaging technique to visualize and quantify intracellular and extracellular ROS levels within intact mouse aortas ex vivo. Using this technique, we found that intracellular, but not extracellular, ROS levels increased prior to lesion formation in mouse aortas. Both intracellular and extracellular ROS levels were increased in advanced lesions. Intracellular ROS correlated with lesion content of macrophages. Extracellular ROS correlated with lesion content of smooth muscle cells. The high levels of ROS in advanced lesions were reduced by 5 days high dose atorvastatin treatment but not by lipid lowering by diet. Atorvastatin treatment did not affect lesion inflammation (aortic arch mRNA levels of CXCL 1, ICAM-1, MCP-1, TNF-α, VCAM, IL-6, and IL-1β) or cellular composition (smooth muscle cell, macrophage, and T-cell content).Aortic levels of intracellular ROS increase prior to lesion formation and may be important in initiation of atherosclerosis. Our results suggest that within lesions, macrophages produce mainly intracellular ROS whereas smooth muscle cells produce extracellular ROS. Short term atorvastatin treatment, but not lipid lowering by diet, decreases ROS levels within established advanced lesions; this may help explain the lesion stabilizing and anti-inflammatory effects of long term statin treatment.

Mathematical models may help the analysis of biological systems by providing estimates of otherwise un-measurable quantities such as concentrations and fluxes. The variability in such systems makes it difficult to translate individual characteristics to group behavior. Mixed effects models offer a tool to simultaneously assess individual and population behavior from experimental data. Lipoproteins and plasma lipids are key mediators for cardiovascular disease in metabolic disorders such as diabetes mellitus type 2. By the use of mathematical models and tracer experiments fluxes and production rates of lipoproteins may be estimated.We developed a mixed effects model to study lipoprotein kinetics in a data set of 15 healthy individuals and 15 patients with type 2 diabetes. We compare the traditional and the mixed effects approach in terms of group estimates at various sample and data set sizes.We conclude that the mixed effects approach provided better estimates using the full data set as well as with both sparse and truncated data sets. Sample size estimates showed that to compare lipoprotein secretion the mixed effects approach needed almost half the sample size as the traditional method.

Dietary medium chain fatty acids (MCFA) and linoleic acid follow different metabolic routes, and linoleic acid activates PPAR receptors. Both these mechanisms may modify lipoprotein and fatty acid metabolism after dietary intervention. Our objective was to investigate how dietary MCFA and linoleic acid supplementation and body fat distribution affect the fasting lipoprotein subclass profile, lipoprotein kinetics, and postprandial fatty acid kinetics. In a randomized double blind cross-over trial, 12 male subjects (age 51±7 years; BMI 28.5±0.8 kg/m2), were divided into 2 groups according to waist-hip ratio. They were supplemented with 60 grams/day MCFA (mainly C8:0, C10:0) or linoleic acid for three weeks, with a wash-out period of six weeks in between. Lipoprotein subclasses were measured using HPLC. Lipoprotein and fatty acid metabolism were studied using a combination of several stable isotope tracers. Lipoprotein and tracer data were analyzed using computational modeling. Lipoprotein subclass concentrations in the VLDL and LDL range were significantly higher after MCFA than after linoleic acid intervention. In addition, LDL subclass concentrations were higher in lower body obese individuals. Differences in VLDL metabolism were found to occur in lipoprotein lipolysis and uptake, not production; MCFAs were elongated intensively, in contrast to linoleic acid. Dietary MCFA supplementation led to a less favorable lipoprotein profile than linoleic acid supplementation. These differences were not due to elevated VLDL production, but rather to lower lipolysis and uptake rates.

ContextNonfasting (postprandial) triglyceride concentrations have emerged as a clinically significant cardiovascular disease risk factor that results from accumulation of remnant triglyceride-rich lipoproteins (TRLs) in the circulation. The remnant TRLs are cleared from the circulation by hepatic uptake, but the specific mechanisms involved are unclear. The syndecan-1 heparan sulfate proteoglycan (HSPG) pathway is important for the hepatic clearance of remnant TRLs in mice, but its relevance in humans is unclear.ObjectiveWe sought to determine whether polymorphisms of the genes responsible for HSPG assembly and disassembly contribute to atherogenic dyslipoproteinemias in humans.Patients and designWe performed an oral fat load in 68 healthy subjects. Lipoproteins (chylomicrons and very low density lipoproteins 1 and 2) were isolated from blood, and the area under curve and incremental area under curve for postprandial variables were calculated. Single nucleotide polymorphisms in genes encoding syndecan-1 and enzymes involved in the synthesis or degradation of HSPG were genotyped in the study subjects.ResultsOur results indicate that the genetic variation rs2281279 in SULF2 associates with postprandial clearance of remnant TRLs and triglyceride levels in healthy subjects. Furthermore, the SNP rs2281279 in SULF2 associates with hepatic SULF2 mRNA levels.ConclusionsIn humans, mild but clinically relevant postprandial hyperlipidemia due to reduced hepatic clearance of remnant TRLs may result from genetic polymorphisms that affect hepatic HSPG.

Obesity is highly associated with elevated serum triglycerides, hepatic steatosis and type 2 diabetes (T2D). The I148M (rs738409) genetic variant of patatin-like phospholipase domain-containing 3 gene (PNPLA3) is known to modulate hepatic triglyceride accumulation, leading to steatosis. No association between PNPLA3 I148M genotype and T2D in Europeans has been reported. Aim of this study is to examine the relationship between PNPLA3 I148M genotypes and serum triglycerides, insulin resistance and T2D susceptibility by testing a gene-environment interaction model with severe obesity.PNPLA3 I148M was genotyped in a large obese cohort, the SOS study (n = 3,473) and in the Go-DARTS (n = 15,448), a T2D case-control study. Metabolic parameters were examined across the PNPLA3 I148M genotypes in participants of the SOS study at baseline and at 2- and 10-year follow up after bariatric surgery or conventional therapy. The associations with metabolic parameters were validated in the Go-DARTS study. Serum triglycerides were found to be lower in the PNPLA3 148M carriers from the SOS study at baseline and from the Go-DARTS T2D cohort. An increased risk for T2D conferred by the 148M allele was found in the SOS study (O.R. 1.09, 95% C.I. 1.01-1.39, P = 0.040) and in severely obese individuals in the Go-DARTS study (O.R. 1.37, 95% C.I. 1.13-1.66, P = 0.001). The 148M allele was no longer associated with insulin resistance or T2D after bariatric surgery in the SOS study and no association with the 148M allele was observed in the less obese (BMI

The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.