A Data Integration Multi-Omics Approach to Study Calorie Restriction-Induced Changes in Insulin Sensitivity
Authors
Dao Maria Carlota, Sokolovska Nataliya, Brazeilles Rémi, Affeldt Séverine, Pelloux Véronique, Prifti Edi, Chilloux Julien, Verger Eric O., Kayser Brandon D., Aron-Wisnewsky Judith, Ichou Farid, Pujos-Guillot Estelle, Hoyles Lesley, Juste Catherine, Doré Joël, Dumas Marc-Emmanuel, Rizkalla Salwa W., Holmes Bridget A., Zucker Jean-Daniel, Clément Karine, The MICRO-Obes Consortium
Abstract
In order to examine the mechanisms responsible for the improvement of insulin sensitivity induced by calorie restriction and the interactions between physiological and lifestyle factors, Dao et al. examined the integration of big data from multiple omic techniques and lifestyle factors. They were able to create biological networks that highlighted links between specific subcutaneous adipose tissue genes and microbial species with changes in insulin sensitivity, and identified potential biomarkers that can be used in future studies to predict and improve individual response to weight loss interventions.
This article is relevant since, using similar systems biology approaches, interactions of multiple physiological factors can be examined to identify biomarkers of interest to evaluate the functional effect available to the food industry.