Highly bioavailable micellar curcuminoids accumulate in blood, are safe and do not reduce blood lipids and inflammation markers in moderately hyperlipidemic individuals.

SCOPE: Curcuminoids are poorly bioavailable, but potentially lipid- and inflammation-lowering phytochemicals. We hypothesized that curcuminoids, when administered as a micellar formulation with hundredfold enhanced bioavailability, decrease blood lipids and inflammation in subjects with moderately elevated cholesterol and C-reactive protein concentrations. METHODS AND RESULTS: We carried out a randomized, double-blind, crossover study (4-wk washout phase) with 42 subjects consuming 294 mg curcuminoids per day (as micelles) or placebo for 6 wk. At the beginning, after 3 wk and at the end (6 wk) of each intervention, we collected fasting blood samples to determine curcuminoids, blood lipids, and markers of inflammation, glucose and iron homeostasis, and liver toxicity. Daily ingestion of 98 mg micellar curcuminoids with each principal meal for as little as 3 wk resulted in fasting curcuminoid plasma concentrations of 49 nmol/L. Neither blood lipids, nor markers of inflammation, glucose and iron homeostasis, or liver enzymes differed between curcuminoid and placebo interventions. CONCLUSION: Consumption of 98 mg of highly bioavailable curcuminoids with each principal meal sufficed to achieve curcuminoid accumulation in the blood, was safe, and did not alter blood lipids, inflammation, glucose, or iron homeostasis in healthy subjects with slightly elevated blood cholesterol and C-reactive protein.

White adipose tissue reference network: a knowledge resource for exploring health-relevant relations.

Optimal health is maintained by interaction of multiple intrinsic and environmental factors at different levels of complexity-from molecular, to physiological, to social. Understanding and quantification of these interactions will aid design of successful health interventions. We introduce the reference network concept as a platform for multi-level exploration of biological relations relevant for metabolic health, by integration and mining of biological interactions derived from public resources and context-specific experimental data. A White Adipose Tissue Health Reference Network (WATRefNet) was constructed as a resource for discovery and prioritization of mechanism-based biomarkers for white adipose tissue (WAT) health status and the effect of food and drug compounds on WAT health status. The WATRefNet (6,797 nodes and 32,171 edges) is based on (1) experimental data obtained from 10 studies addressing different adiposity states, (2) seven public knowledge bases of molecular interactions, (3) expert's definitions of five physiologically relevant processes key to WAT health, namely WAT expandability, Oxidative capacity, Metabolic state, Oxidative stress and Tissue inflammation, and (4) a collection of relevant biomarkers of these processes identified by BIOCLAIMS ( http://bioclaims.uib.es ). The WATRefNet comprehends multiple layers of biological complexity as it contains various types of nodes and edges that represent different biological levels and interactions. We have validated the reference network by showing overrepresentation with anti-obesity drug targets, pathology-associated genes and differentially expressed genes from an external disease model dataset. The resulting network has been used to extract subnetworks specific to the above-mentioned expert-defined physiological processes. Each of these process-specific signatures represents a mechanistically supported composite biomarker for assessing and quantifying the effect of interventions on a physiological aspect that determines WAT health status. Following this principle, five anti-diabetic drug interventions and one diet intervention were scored for the match of their expression signature to the five biomarker signatures derived from the WATRefNet. This confirmed previous observations of successful intervention by dietary lifestyle and revealed WAT-specific effects of drug interventions. The WATRefNet represents a sustainable knowledge resource for extraction of relevant relationships such as mechanisms of action, nutrient intervention targets and biomarkers and for assessment of health effects for support of health claims made on food products.