Impact of probiotics, prebiotics and synbiotics on lipid metabolism in humans

Public health strategies for reducing the risk of coronary heart disease have focused on lowering plasma lipids, particularly cholesterol levels, with recent studies also highlighting triacylglycerol (TAG) as an important modifiable risk factor. One approach is to supplement the diet with probiotics, prebiotics or synbiotics. Probiotics are live microorganisms which when administered in adequate amounts confer a health benefit on the host. Putative health benefits include improved resistance to gastrointestinal infections, reduction in lipid levels and stimulation of the immune system. Prebiotics are selectively fermented dietary components that are aimed at improving host health through selective fermentation by the gut microbiota, such as bifidobacteria and lactobacilli. Animal studies have shown prebiotics to markedly reduce circulating TAG and to a lesser extent cholesterol concentrations, with favourable but inconsistent findings with respect to changes in lipid levels in human studies. Here we provide an overview of the effects, and possible mechanisms, of probiotics, prebiotics and synbiotics (combination of a probiotic and prebiotic) on circulating lipeamia in humans.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

Effect of polymorphisms in the PPARGC1A gene on body fat in Asian Indians

OBJECTIVE: To evaluate whether polymorphisms in the peroxisome proliferator-activated receptor-gamma coactivator-1 alpha (PPARGC1A) gene were related to body fat in Asian Indians. METHODS: Three polymorphisms of PPARGC1A gene, the Thr394Thr, Gly482Ser and +A2962G, were genotyped on 82 type 2 diabetic and 82 normal glucose tolerant (NGT) subjects randomly chosen from the Chennai Urban Rural Epidemiology Study using PCR-RFLP, and the nature of the variants were confirmed using direct sequencing. Linkage disequilibrium (LD) was estimated from the estimates of haplotypic frequencies using an expectation-maximization algorithm. Visceral, subcutaneous and total abdominal fat were measured using computed tomography, whereas dual X-ray absorptiometry was used to measure central abdominal and total body fat. RESULTS: None of the three polymorphisms studied were in LD. The genotype (0.59 vs 0.32, P=0.001) and allele (0.30 vs 0.17, P=0.007) frequencies of Thr394Thr polymorphism were significantly higher in type 2 diabetic subjects compared to those in NGT subjects. The odds ratio for diabetes (adjusted for age, sex and body mass index) for the susceptible genotype, XA (GA+AA) of Thr394Thr polymorphism, was 2.53 (95% confidence intervals: 1.30-5.04, P=0.009). Visceral and subcutaneous fat were significantly higher in NGT subjects with XA genotype of the Thr394Thr polymorphism compared to those with GG genotype (visceral fat: XA 148.2+/-46.9 vs GG 106.5+/-51.9 cm(2), P=0.001; subcutaneous fat: XA 271.8+/-167.1 vs GG 181.5+/-78.5 cm(2), P=0.001). Abdominal (XA 4521.9+/-1749.6 vs GG 3445.2+/-1443.4 g, P=0.004), central abdominal (XA 1689.0+/-524.0 vs GG 1228.5+/-438.7 g, P<0.0001) and non-abdominal fat (XA 18763.8+/-8789.4 vs GG 13160.4+/-4255.3 g, P<0.0001) were also significantly higher in the NGT subjects with XA genotype compared to those with GG genotype. The Gly482Ser and +A2962G polymorphisms were not associated with any of the body fat measures. CONCLUSION: Among Asian Indians, the Thr394Thr (G --> A) polymorphism is associated with increased total, visceral and subcutaneous body fat.

Visceral and central abdominal fat and anthropometry in relation to diabetes in Asian Indians

OBJECTIVE: The objective of the study was to examine body fat distribution using computed tomography (CT), dual-energy X-ray absorptiometry (DEXA), and anthropometry in relation to type 2 diabetes in urban Asian Indians. RESEARCH DESIGN AND METHODS: This is a case-control study of 82 type 2 diabetic and 82 age- and sex-matched nondiabetic subjects from the Chennai Urban Rural Epidemiology Study, an ongoing epidemiological study in southern India. Visceral, subcutaneous, and total abdominal fat were measured using CT, while DEXA was used to measure central abdominal and total body fat. Anthropometric measures included BMI, waist circumference, sagittal abdominal diameter (SAD), and waist-to-hip ratio. RESULTS: Visceral and central abdominal fat showed a strong correlation with each other (P <0.0001), and kappa analysis revealed a fairly good agreement between tertiles of visceral and central abdominal fat (kappa=0.44, P <0.0001). Diabetic subjects had significantly higher visceral (P=0.005) and central abdominal (P=0.011) fat compared with nondiabetic subjects. Waist circumference and SAD showed a strong correlation with visceral (P <0.01) and central abdominal (P <0.0001) fat in both diabetic and nondiabetic subjects. Logistic regression analysis revealed visceral (odds ratio [OR] 1.011, P=0.004) and central abdominal (OR 1.001, P=0.013) fat to be associated with diabetes, even after adjusting for age and sex. CONCLUSIONS: Visceral and central abdominal fat showed a strong association with type 2 diabetes. Both measures correlated well with each other and with waist circumference and SAD in diabetic and nondiabetic urban Asian Indians.

The integration of lipid-sensing and anti-inflammatory effects: how the PPARs play a role in metabolic balance

The peroxisomal proliferating-activated receptors (PPARs) are lipid-sensing transcription factors that have a role in embryonic development, but are primarily known for modulating energy metabolism, lipid storage, and transport, as well as inflammation and wound healing. Currently, there is no consensus as to the overall combined function of PPARs and why they evolved. We hypothesize that the PPARs had to evolve to integrate lipid storage and burning with the ability to reduce oxidative stress, as energy storage is essential for survival and resistance to injury/infection, but the latter increases oxidative stress and may reduce median survival (functional longevity). In a sense, PPARs may be an evolutionary solution to something we call the 'hypoxia-lipid' conundrum, where the ability to store and burn fat is essential for survival, but is a 'double-edged sword', as fats are potentially highly toxic. Ways in which PPARs may reduce oxidative stress involve modulation of mitochondrial uncoupling protein (UCP) expression (thus reducing reactive oxygen species, ROS), optimising forkhead box class O factor (FOXO) activity (by improving whole body insulin sensitivity) and suppressing NFkB (at the transcriptional level). In light of this, we therefore postulate that inflammation-induced PPAR downregulation engenders many of the signs and symptoms of the metabolic syndrome, which shares many features with the acute phase response (APR) and is the opposite of the phenotype associated with calorie restriction and high FOXO activity. In genetically susceptible individuals (displaying the naturally mildly insulin resistant 'thrifty genotype'), suboptimal PPAR activity may follow an exaggerated but natural adipose tissue-related inflammatory signal induced by excessive calories and reduced physical activity, which normally couples energy storage with the ability to mount an immune response. This is further worsened when pancreatic decompensation occurs, resulting in gluco-oxidative stress and lipotoxicity, increased inflammatory insulin resistance and oxidative stress. Reactivating PPARs may restore a metabolic balance and help to adapt the phenotype to a modern lifestyle.

Top single nucleotide polymorphisms affecting carbohydrate metabolism in Metabolic Syndrome: from the LIPGENE study

Rationale:Metabolic Syndrome (MetS) is a high prevalence condition characterized by altered energy metabolism, insulin resistance and elevated cardiovascular risk.Objectives:Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS.Methods:904 SNPs (tag SNPs and functional SNPs) were tested for influence in eight fasting and dynamic markers of carbohydrate metabolism, performing an intravenous glucose tolerance test in 450 participants of the LIPGENE study.Findings:From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (a 16 % of the pre-selected) remained significant after Bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose: rs26125 (PPARGC1B); fasting insulin: rs4759277 (LRP1); C peptide: rs4759277 (LRP1); HOMA-IR: rs4759277 (LRP1); QUICKI: rs184003 (AGER); SI: rs7301876 (ABCC9), AIRg: rs290481 (TCF7L2) and DI: rs12691 (CEBPA).Conclusions:We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among aproximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.