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

Abstract

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.

Fig. 1

Visualization of the white adipose tissue health reference network. Nodes are colored by clustering based on network topology. Clusters are annotated with biological function based on GO overrepresentation analysis (“Methods”). Node size is scaled according to degree (number of interactions)

Fig. 2

The network signature for process Adipose expandability. Nodes are colored according to the sign of the average fold-change across different studies (blue negative and red positive). Nodes with a green border are seed nodes (i.e., significant aggregated p-value and consistent fold-change across studies), and other nodes are neighbors of these seed nodes and included in the network to add biological context. Solid edges indicate knowledge-based molecular interactions; dotted lines indicate interactions based on correlations in the reference datasets

Fig. 3

Overlay of intervention study (GEO Accession GSE57659) on the network signatures for specific processes related to white adipose tissue health. The heatmap shows the matching scores for each signature and intervention combination, where red indicates a positive score (positive “healthy” effect) and blue indicates a negative score (negative “disease” effect). Matching scores for the Oxidative capacity signature could not be calculated for any of the interventions due to lack of sufficient measurements of the markers in this signature