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Genes 2018, 9(11), 525; https://doi.org/10.3390/genes9110525

Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression

1
Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, 6211ER Maastricht, The Netherlands
2
Department of Epidemiology, CARIM School for Cardiovascular Diseases, Maastricht University, 6211ER Maastricht, The Netherlands
3
Department of Toxicogenomics, GROW School of Oncology and Developmental Biology, Maastricht University, 6211ER Maastricht, The Netherlands
4
Department of Human Biology, NUTRIM Research School, Maastricht University, 6211ER Maastricht, The Netherlands
5
Department of Bioinformatics—BiGCaT, NUTRIM Research School, Maastricht University, 6211ER Maastricht, The Netherlands
*
Authors to whom correspondence should be addressed.
Received: 28 September 2018 / Revised: 22 October 2018 / Accepted: 22 October 2018 / Published: 29 October 2018
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Abstract

Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. The adipose tissue is the primary tissue affected in diet-induced weight loss, yet the underlying molecular mechanisms and changes are not completely deciphered. In this study, we present a network biology analysis workflow which enables the profiling of the cellular processes affected by weight loss in the subcutaneous adipose tissue. Time series gene expression data from a dietary intervention dataset with two diets was analysed. Differentially expressed genes were used to generate co-expression networks using a method that capitalises on the repeat measurements in the data and finds correlations between gene expression changes over time. Using the network analysis tool Cytoscape, an overlap network of conserved components in the co-expression networks was constructed, clustered on topology to find densely correlated genes, and analysed using Gene Ontology enrichment analysis. We found five clusters involved in key metabolic processes, but also adipose tissue development and tissue remodelling processes were enriched. In conclusion, we present a flexible network biology workflow for finding important processes and relevant genes associated with weight loss, using a time series co-expression network approach that is robust towards the high inter-individual variation in humans. View Full-Text
Keywords: obesity; diet; adipose tissue; correlation networks; transcriptomics; differential expression; cellular processes; cytoscape; network biology; network visualisation obesity; diet; adipose tissue; correlation networks; transcriptomics; differential expression; cellular processes; cytoscape; network biology; network visualisation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Tareen, S.H.K.; Adriaens, M.E.; Arts, I.C.W.; de Kok, T.M.; Vink, R.G.; Roumans, N.J.T.; van Baak, M.A.; Mariman, E.C.M.; Evelo, C.T.; Kutmon, M. Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression. Genes 2018, 9, 525.

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