Prevalence of plasma small dense LDL is increased in obesity in a Thai population

Background Plasma low density lipoprotein (LDL) particles vary in size, density, electrical charge and chemical composition. An increased presence of small dense LDL (sdLDL), along with raised triglyceride concentrations and decreased high density lipoprotein (HDL) cholesterol concentrations is commonly known as the atherogenic triad and has been observed in some cases of obesity, principally in Europe and America. This study examines the prevalence of sdLDL in the plasma of an obese (BMI ≥ 25 kg/m2) Thai population. Methods Plasma from fasted obese (n = 48) and non-obese (n = 16) Thai participants was subjected to density gradient ultracentrifugation in iodixanol to separate lipoproteins. Gradients were unloaded top-to-bottom into 20 fractions which were assayed for cholesterol, triglyceride, apo B and apo A-1 to identify lipoprotein types and subtypes. Results LDL cholesterol was subfractionated into LDL I + II (fractions 3–6, ρ = 1.021-1.033 g/ml) which was considered to represent large buoyant LDL (lbLDL), LDL III (fractions 7–9, ρ = 1.036-1.039 g/ml) which was considered to represent sdLDL, and, LDL IV (fractions 10–12, ρ = 1.044-1.051 g/ml) which was considered to represent very sdLDL. Concentrations of LDL III and IV were increased by 15-20% in obese participants whilst that of LDL I + II was concomitantly decreased by 10%. This was accompanied by a 50% increase in plasma triglyceride concentrations and 15% decrease in HDL cholesterol concentrations. Only 3/16 (19%) non-obese participants had a pattern B LDL cholesterol profile (peak density of >1.033 g/ml), whilst 28/48 (58%) obese participants were pattern B. When expressed as a fraction of the LDL concentration, total sdLDL (i.e. LDL III + IV) showed highly significant correlations to plasma triglyceride concentrations and the triglyceride/HDL cholesterol ratio. Conclusions The prevalence of sdLDL is increased in obesity in a Thai population such that they demonstrate a similar atherogenic triad to that previously observed in European and American populations

Association between Cigarette Smoking and Metabolic Syndrome in Thais

Purpose: To investigate the relationship between metabolic syndrome as defined by using the modified NCEP/ATP III criteria [modified the National Cholesterol Education Program (NCEP)/Adult Treatment Panel III (ATP III) criteria] and cigarette smoking in Thai subjects. Methods: This study was carried out among 254 smokers and 144 nonsmokers from suburban and urban residential areas in Bangkok, Thailand. All anthropometric variables, blood pressures, resting heart rate and biochemical parameters in each subject were measured. Results: The anthropometric variables, biochemical parameters, blood pressures and resting heart rate were not significantly different between smokers and nonsmokers, except for white blood cell count (WBC). Cigarette smoking was associated with increased risk for metabolic syndrome (OR =1.97; 95% CI=1.11-3.42) and the percentages of metabolic syndrome in smoker and nonsmoker Thais were 22.8% and 13.2%, respectively. Moreover, the number of cigarette smoking per day showed significant association with metabolic syndrome (p=0.047). Logistic regression analysis revealed that cigarette pack-years, resting heart rate, body mass index (BMI) and total cholesterol were significantly increased risk factors for metabolic syndrome. Conclusion: The current findings suggest that cigarette smoking is associated with the increased risk of metabolic syndrome by using the modified NCEP/ATP III criteria in Thais.Keywords: Smoker; Cigarette pack-years; Modified NCEP/ATP III criteria; Biochemical parameters; Anthropometric variables

MetaPath: identifying differentially abundant metabolic pathways in metagenomic datasets

Enabled by rapid advances in sequencing technology, metagenomic studies aim to characterize entire communities of microbes bypassing the need for culturing individual bacterial members. One major goal of metagenomic studies is to identify specific functional adaptations of microbial communities to their habitats. The functional profile and the abundances for a sample can be estimated by mapping metagenomic sequences to the global metabolic network consisting of thousands of molecular reactions. Here we describe a powerful analytical method (MetaPath) that can identify differentially abundant pathways in metagenomic datasets, relying on a combination of metagenomic sequence data and prior metabolic pathway knowledge. First, we introduce a scoring function for an arbitrary subnetwork and find the max-weight subnetwork in the global network by a greedy search algorithm. Then we compute two p values (p abund and p struct ) using nonparametric approaches to answer two different statistical questions: (1) is this subnetwork differentically abundant? (2) What is the probability of finding such good subnetworks by chance given the data and network structure? Finally, significant metabolic subnetworks are discovered based on these two p values. In order to validate our methods, we have designed a simulated metabolic pathways dataset and show that MetaPath outperforms other commonly used approaches. We also demonstrate the power of our methods in analyzing two publicly available metagenomic datasets, and show that the subnetworks identified by MetaPath provide valuable insights into the biological activities of the microbiome. We have introduced a statistical method for finding significant metabolic subnetworks from metagenomic datasets. Compared with previous methods, results from MetaPath are more robust against noise in the data, and have significantly higher sensitivity and specificity (when tested on simulated datasets). When applied to two publicly available metagenomic datasets, the output of MetaPath is consistent with previous observations and also provides several new insights into the metabolic activity of the gut microbiome. The software is freely available at http://metapath.cbcb.umd.edu .https://doi.org/10.1186/1753-6561-5-S2-S

New Insights into Blastocystis spp.: A Potential Link with Irritable Bowel Syndrome

International audienceBlastocystis spp. belong to the phylum Stramenopila, a complex and heterogeneous evolutionary assemblage of heterotrophic and photosynthetic protozoa [1]. Interestingly, this is the only stramenopile living in the lower digestive tract of humans, and it also lives in other mammals, birds, reptiles, amphibians, and insects [1]. Even though isolates were reported to be morphologically indistinguishable, an extensive genetic variation among isolates from both humans and animals has been observed. Thirteen subtypes (ST1-ST13), with the first nine being found in humans, have been identified based on genes coding for the small-subunit ribosomal RNA [2]. Preferential repartition of STs exists among animals that appear to constitute the main reservoir for environmental dissemination and human contamination

Metabolomic profiling in liver of adiponectin knockout mice uncovers lysophospholipid metabolism as an important target of adiponectin action

Adiponectin mediates antidiabetic effects via increasing hepatic insulin sensitivity and direct metabolic effects. In this study we conducted a comprehensive and unbiased metabolomic profiling of liver tissue from adiponectin knockout (AdKO) mice, with and without adiponectin supplementation, fed high fat diet (HFD) to derive insight into the mechanisms and consequences of insulin resistance. Hepatic lipid accumulation and insulin resistance induced by HFD were reduced by adiponectin. HFD significantly altered levels of 147 metabolites and bioinformatic analysis indicated that one of the most striking changes was the profile of increased lysophospholipids. These changes were largely corrected by adiponectin, at least in part via direct regulation of phospholipase A2 (PLA2) as palmitate-induced PLA2 activation was attenuated by adiponectin in primary hepatocytes. Notable decreases in several glycerolipids after HFD were reversed by adiponectin which also corrected elevations in several diacyglycerol and ceramide species. Our data also indicate that stimulation of ω-oxidation of fatty acids by HFD is enhanced by adiponectin. In conclusion, this metabolomic profiling approach in AdKO mice identified important targets of adiponectin action, including PLA2 to regulate lysophospholipid metabolism and ω-oxidation of fatty acids